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                                                               7-35

-------
smoking nor total household smoking had any influence on the prevalence of wheezing. When the
authors controlled for family history of respiratory allergy, direct effects of maternal smoking on
prevalence of wheezing failed to reach statistical significance.  However, there was a strong
association between maternal smoking and wheezing among children with a positive  family history
of respiratory allergy (OR = 4.5, 95% C.I. = 1.7, 12.0), and the interaction between these terms
was highly significant in multivariable analysis, suggesting the combined importance of both
genetic factors and maternal smoking.
       Park and Kim (1986) studied  3,651 children aged 0 to 14 from a randomized, clustered
sample of households in South Korea (response rate: 89%). A questionnaire was administered to
household members about their smoking habits and respiratory symptoms.  Mothers  answered
questions about the presence of cough in the child in the 3 months prior to interview.  The authors
reported dose-response relationships  between the child's cough and number of smokers in the
family, number of smokers in the same room, number of cigarettes smoked by all family
members, and number of cigarettes smoked by parents. The relationship was present in children
of different ages (less than 5 years, 6 to 11 years, and 12 to 14 years). The authors controlled for
parental education, socioeconomic status, birth rank, parental age, birth interval, number of
family members, and number of siblings. Family members with cough or with morning phlegm
production were  significantly more likely to live  with children with cough. After correcting for
these two factors, chronic cough was 2.4 times as likely in children of families whose members
smoked  1 to 14 cigarettes  per day (95% C.I. = 1.4, 4.3) and 3.2 times as likely in children of
families whose members smoked more than 15 cigarettes per day (95% C.I. =  1.9,  5.5).  However,
effects were more noticeable and only reached statistical significance in children of families
whose adult members did not have chronic cough.
        Bisgaard  and coworkers (1987) studied 5,953 infants of a total of 8,423 eligible newborns
(71%) enrolled in a prospective study.  At the age of 1 year, the child's mother was  interviewed
 regarding episodes of wheeze during the previous year and possible risk factors for  wheezing.
 The risk of wheezing was 2.7 times as high (95% C.I. = 1.8, 4.0) in children whose mothers smoked
 three or more cigarettes per day as in children whose mothers smoked fewer  than three cigarettes
 per day. Results were independent of social status and sex of the child. The authors decided not
 to control for quarter of birth or use of day-care facilities, with the assumption that these factors
 did not modify the relationship between maternal smoking and wheezing. Also, biases could have
 been introduced by the fact that almost one-third of the original sample was not  included in the
 analysis.
        Geller-Bernstein and coworkers (1987) studied 80 children aged 6 to  24 months who had
 been seen as outpatients or inpatients in Israel for wheezing and who had a diagnosis of atopy.
                                            7-36

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The children were examined every 6 months during 4 years by a physician. At the end of
assessment, the authors classified children as having "recovered" if they had been symptom-free
for at least 1 (the last) year; otherwise they were classified as "persistent wheezers." "Persistent
wheezers" were more likely to have smoking parents than were "recovered" children (OR = 3.1,
95% C.I. = 1.1, 8.9). This result was independent of changes in IgE levels during the study period.
The authors did not control for the possible confounding effect of parental symptoms.
       Cogswell and coworkers (1987) studied 100 newborns who had at least one parent with a
history of hay fever or asthma.  Ninety-two children were still being followed at 1 year of age and
73 at the age of 5 years. Children were examined periodically and whenever they had signs of
respiratory illness. At the child's first birthday, the number of those who had developed wheezing
was equally distributed between parents who did or did not smoke. By the age of 5 years,
however, 62% of parents who smoked had children who had wheezed compared with 37% in
nonsmoking families (p < 0.05). It is unlikely that these results can be explained by the
confounding effect of parental symptoms, because all parents were allergic by definition. It is
also quite unlikely that preferential withdrawal of nonwheezing children of smoking parents could
have biased the results.
       Toyoshima and coworkers (1987) from Osaka, Japan, followed 48 of 65 wheezy infants
and children less than 3 years old for up to 4 years.  Outcome information  was obtained from
charts or by telephoning the child's mother. Among  18 children  who were still symptomatic 25 to
44 months after their first visit, 17 lived with smokers compared with 13 of 22 children who lived
with smokers and who stopped having symptoms during followup (OR = 11.8, 95% C.I. =
1.3, 105.0).  Results were independent of family history of allergy, feeding practices,  and
disturbances at birth.  Selection bias related to the number of subjects lost  for followup or with
missing information could have influenced the results of this study.
       Tsimoyianis and collaborators (1987) evaluated the effects of exposure to ETS on
respiratory symptoms in a group of 12- to 17-year-old high school athletes (N = 193).  Histories
of smoking by all household members were obtained for all subjects.  Athletes exposed to ETS at
home were more likely to report cough  than were unexposed athletes (p = 0.08). Frequency of
bronchitis, wheeze, and shortness of breath was similar in both groups. A  greater awareness of
the smoking habits of those around them by subjects with cough cannot be excluded as an
explanation of these findings, but this source of bias cannot explain the exposure-response  trends
for ETS and lung function seen in this same sample (see Section 7.8.1).
       Andrae and collaborators (1988) mailed questionnaires to the parents of 5,301 children
aged 6 months to 16 years living in the city of Norrkoping, Sweden. Data were  obtained from
4,990 children (94% response rate). Children with parents who smoked had exercise-induced
                                           7-37

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 cough more often than did children of nonsmokers (OR = 1.4, 95% C.I. = 1.1, 1.8). Exposure to
 ETS interacted with living in houses with damage by dampness; children exposed to both had
 more exercise-induced cough and allergic asthma when compared to those exposed to only one or
 neither.  Results of this cross-sectional study may have been biased by preferential reporting of
 symptoms by smoking parents, although a reliability study performed  in a random sample was
 reported to confirm 95% of the answers regarding respiratory symptomatology.  In addition, no
 effort was made to  control for active smoking in older children.
       Somerville and coworkers (1988) enrolled 88% of 8,118 eligible children aged 5 to 11 from
 England and Scotland. Data on the child's respiratory symptoms and parental smoking were
 obtained from a self-administered questionnaire completed by the child's mother.  After
 exclusions for missing data, the proportions of children available ranged from 60.9% to 63.9% of
 all subjects, depending on the variables involved.  Logistic regression analysis was used to control
 for child's age, presence of siblings, one- or two-parent families, paternal employment, social
 class, maternal smoking during pregnancy, overcrowding, maternal education, maternal age,
 triceps skinfold thickness, and birth weight. For Scottish children (who were only  19% of all
 subjects), the authors  found a significant relationship between number of cigarettes smoked at
 home and "chest ever  wheezy" (p < 0.01;  OR not reported). Among English children, there was a
 significant relationship between number of cigarettes smoked at home by mother and father
 together and prevalence of a wheezy or whistling chest most nights (adjusted OR in children
 whose parents smoked 20 cig./day = 1.6; 95% C.I. = 1.2, 2.2).  Attacks  of bronchitis and cough
 during the day or at night were also significantly correlated with number of cigarettes smoked by
 parents in the English sample; odds ratios in children of parents who smoked 20 cigarettes per day
 were  1.4 and 1.3, respectively, but no confidence intervals were reported.  The authors concluded
 that the effect of parental smoking on respiratory symptoms in this age group is small and requires
 a large number of subjects to be detected.
       Rylander and collaborators (1988) from Stockholm, Sweden, studied 67 children aged
 4 to 7 years who had been hospitalized with virologically proven  RSV  infections before age 3.
 Questionnaires  were mailed to parents regarding their smoking habits and the child's history of
 wheezing illnesses after  the initial episode. Children who had subsequent occasional wheezing
 (N » 21) were more likely to have smoking parents than those (N = 24) who had no subsequent
 respiratory symptoms  (OR = 4.3,  95% C.I. = 1.1, 16.4).  However, frequency of parental smoking
 among children who had no subsequent respiratory symptoms was not  significantly different from
that of children who had subsequent recurrent wheezing.  The inconsistency of the results in this
study may be explained  by the small number of subjects involved.
                                           7-38

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       Strachan (1988) studied 1,012 of a target sample of 1,095 schoolchildren aged 6.5 to 7.5
years in Edinburgh, Scotland. Parents answered a questionnaire on their smoking habits and on
respiratory symptoms in their children.  There was no relationship between number of smokers in
the household and prevalence of wheezing in the population.  Cough at night (> 3 nights in the'
past month) was more likely to occur in children living with one smoker (OR = 1.6; 95% C.I. =
1.1, 2.6) or two smokers (OR = 2.5; 95% C.I. = 1.5, 4.0) than in children living with nonsmokers.
Occurrence of "chesty colds" in children was also more frequent in households with one  (OR - 1.3;
95% C.I. = 0.9,  1.9) or two smokers (OR = 1.9; 95% C.I. = 1.3, 3.0).
       A subsequent report (Strachan et al., 1990) based on the same population sample studied
the relationship between salivary cotinine levels and respiratory symptomatology in a subset of
770 children (see also Strachan et al. [1989], Section 7.4.1). The authors found no relationship
between cotinine levels and wheezing or frequent night cough.  Frequency of chesty colds was
significantly correlated with quintals of salivary cotinine (p < 0.01).  The authors noted  that
objective markers of recent exposure to ETS may not adequately reflect exposure at some critical
period in the past.  They also noted that there may be  different ways of understanding the concept
of "wheezing" and proposed that this could explain the lack of association between this symptom
and both questionnaire-based and cotinine-based assessment of exposure to ETS in their sample.
       Lewis and coworkers (1989) performed a case-control study of risk factors for chronic
cough in children under 6 years in Salford, United Kingdom. They enrolled 60 children referred
to a pediatric outpatient clinic with cough lasting more than 2 months or frequent episodes of
cough without wheeze. These 60 subjects were compared with controls admitted for routine
surgical procedures. Children with chronic cough were 1.7 times (95% C.I. = 0.8, 3.5) as likely to
live with a smoker as were controls. Because of the small number of subjects and the high
prevalence of parental smoking (> 50%), the power of this study may have been too low to allow
for meaningful conclusions.
       Neuspiel and coworkers (1989) studied 9,670 of 9,953 eligible children enrolled at birth in
Great Britain.  Information on parental smoking was obtained at birth, at age 5 years, and at age
10 years. Outcome data were obtained from maternal  interviews when the children were 10 years
old. Children of smoking mothers had 11% higher risk (95% C.I. = 2%, 21%) of wheezing between
ages 1 and 10 than did children of nonsmoking mothers. An exposure-response relationship was
also present: Cumulative incidence was 5.2% in children whose mothers  were nonsmokers,  6.6% in
children whose mothers smoked 1 to 4 cigarettes per day, 7.5% in children whose mothers smoked
5 to 14 cigarettes per day, 8.1% in children whose mothers smoked 15 to 24 cigarettes per day, and
8.9% in children whose mothers smoked more than 24 cigarettes per day.  The risk also was
increased in children of mothers who did not smoke during pregnancy but were smokers
                                           7-39

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thereafter (RR = 2.2, 95% C.I. = 1.2, 3.9).  The association persisted after a logistic regression
model was used to control for the effect of child's sex, child allergy, paternal smoking, parental
allergy, crowding, bedroom dampness, feeding practices, gas cooking, and social status.  The
increase in risk was cut approximately in half but did not disappear when additional corrections
for maternal respiratory symptoms and for a measure of maternal depression were made. Results
of this study may be explained in part by preferential reporting of wheezy illnesses by smoking
mothers. However, it is unlikely that the association between maternal smoking and wheezy
illnesses found in this study can be explained exclusively by uncontrolled sources of bias; there
was a striking exposure-response effect, and the association persisted after controlling for most
known confounders and was independent of maternal smoking  during pregnancy.
       Chan and  collaborators (1989a) studied 134 children aged 7 years out of 216 eligible
infants of under 2,000 g birthweight who were admitted to the  neonatal unit of two hospitals in
London, England. Parents of these 134 children and of 123 control schoolchildren born in the
same period but with normal birthweight completed a self-administered questionnaire on
respiratory illnesses and on social and family history.  At age 7, children whose mothers smoked
were at increased risk of having frequent wheeze independent of their neonatal history (adjusted
OR « 2.7; 95% C.I. = 1.3, 5.5), although the increase only  reached statistical significance for
children of normal birthweight.  Prevalence of frequent cough  was also more likely to occur in
children of smoking mothers (OR = 2.4,  95% C.I. = 1.3, 4.6), and the association was significant
for both cases and controls studied separately.  The authors performed a logistic regression to
control for possible confounders (only the low-birthweight group was included). The relationship
between frequent wheeze and maternal smoking persisted among low-birthweight children after
controlling for family history of asthma, atopy, socioeconomic  status, and use of neonatal oxygen.
The relationship between frequent cough and maternal smoking was no longer significant among
low-birthweight infants after controlling for the same possible  confounders.  For the low-
birthweight group, the authors assessed the reliability of some of the responses to their
questionnaires; there was a high correlation (r = 0.96) between the number of hospitalizations
reported by parents and those documented in the outpatient clinic of the neonatal unit that
followed the infants.  The authors concluded that  misclassification due to parental failure to recall
previous respiratory illnesses in the low-birthweight group was unlikely.
       Krzyzanowski and collaborators (1990) studied a sample of 298 children aged 5 to 15 who
were family members of county employees enrolled in a prospective study. Parents answered a
questionnaire on their smoking habits and on respiratory symptoms in their children.  Indoor
formaldehyde concentrations in the living environment also were measured. Prevalence rates of
chronic bronchitis (as diagnosed by a physician) were significantly higher in children  exposed
                                            7-40

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both to ETS and to formaldehyde concentrations of over 60 parts per billion than in children with
one or none of these exposures. The authors also reported that similar effects were not seen in
adults.
       Dijkstra and collaborators (1990) obtained consent for participation in their study for
1,051 of a total of 1,314 (80%) eligible 6- to 12-year-old schoolchildren from a rural area in The
Netherlands. Parents completed a self-administered questionnaire on their smoking habits and on
respiratory symptoms in their children. Complete information was available for 775 children.
When compared to children of nonsmoking households, children exposed to ETS at home were
significantly more likely to have cough on most days for at least 3 months consecutively
(OR = 2.5,  95% C.I. = 1.1, 5,6), wheezy or whistling  sounds in the chest in the last year (OR = 1.9;
95% C.I. =  1.0, 3.5), and attacks of shortness of breath with wheeze in the last year (OR = 2.0; 95%
C.I. = 0.9, 4.2). Exposed children were significantly more likely to have one or more of the above
symptoms than were unexposed children (OR = 2.0; 95% C.I. = 1.2, 3.7).  Results were still
significant  after adjusting for parental respiratory symptoms and for maternal smoking during
pregnancy.  The authors also measured nitrogen dioxide in the homes of all children but found no
association of the latter with respiratory symptoms.
       Mertsola and coworkers (1991) followed prospectively for 3 months 54 patients aged 1 to 6
years from Turku, Finland, who had a history of recurrent attacks of wheezy bronchitis.  The
parents were told to record the symptoms of the child daily and were asked to bring their child to
the hospital emergency room if the child developed signs of an acute respiratory infection.
Incidence of prolonged wheezing  episodes (> 4 days) during followup was significantly more
likely in children exposed to ETS than in  unexposed children (OR = 4.8; 95% C.I. = 1.9, 12.6).
The result was independent of number of siblings, age, sex, medication, and personal history of
allergy.                                                                           ,

7.5.2. Summary and Discussion on Cough, Phlegm, and Wheezing
       Recent studies reviewed in this report that were not included either in the Surgeon
General's report (U.S. DHHS, 1986) or in the NRC report (1986) substantially confirm the
conclusions reached in those two reports.  There is sufficient evidence for the conclusion that ETS
exposure at home is causally associated with respiratory symptoms such as cough, phlegm, or
wheezing in children.
       The evidence is particularly strong for infants and preschool children; in this age range,
most studies have found a significant association between exposure to ETS (and especially to
maternal smoking) and respiratory symptoms in the children, with odds ratios generally ranging
between 1.2 and 2.4. Selection bias may have influenced the results of certain cross-sectional
                                            7-41

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studies; retrospective studies also may have been biased by preferential recall of their children's
symptoms by smoking parents.  However, the presence of a causal relationship is strongly
supported by the consistency of the results for different geographic areas (Japan, Korea, People's
Republic of China, Europe, and North America) and by the positive findings in prospective
studies that are less subject to selection and recall  biases.
       In addition, efforts have been made by all researchers to control for possible confounders
and to avoid sources of bias. It is not feasible for each study to take into account all possible
factors that may affect the relationship under study; some of these factors may even be unknown
at present. However, all reviewed studies have controlled for at least some of the best-known
confounders (family history of  respiratory illnesses, parental respiratory  symptoms, socioeconomic
status, crowding, presence of other siblings, home dampness, gas cooking, maternal level of
education, perinatal problems, low birthweight, maternal age, birth rank, and maternal stress, or
depression). Of these possible confounders, a history of respiratory symptoms in parents has been
particularly scrutinized. The NRC report (1986) noted that bias may be  introduced by parents
who have a history of respiratory illnesses for several reasons.  These parents may overstate their
children's symptoms, or their children actually may have more respiratory illnesses and symptoms.
The latter possibility could be the result of intrafamily correlation of susceptibility (referred to as
familial resemblance by Kauffmann and coworkers [1989a]).  Because smokers are  more likely to
have respiratory symptoms, one would expect that controlling for respiratory symptoms in parents
would result in a decrease in statistical significance of the relationship between ETS and
symptoms  in the child.  In fact, most recent studies that have addressed the issue report that
controlling for family history of respiratory symptoms decreases  but does not entirely explain the
increased risk of respiratory symptoms in young children exposed to ETS.  It has been stressed,
however, that the use of these statistical adjustment procedures may induce an underestimation of
the effect of passive smoking; this would indeed be the case if parents with symptoms (and thus
more likely to be smokers) were more prone to report symptoms  in their children than were
parents without symptoms.  Several studies also have found that the effect is independent of
maternal smoking during  pregnancy and cannot be attributed exclusively to intrauterine exposure
to tobacco products (although the latter may potentiate the effects of postnatal exposure to ETS).
        The evidence is significant but less compelling for a relationship between exposure to ETS
and respiratory symptoms in school-age children.  Odds ratios for this age group are usually
between 1.1 and 2.0.  Several studies have shown  that, among school-age children, there are
significant differences in susceptibility to ETS exposure between individuals. There is, in fact,
evidence showing that several factors may amplify the effects of passive smoking:  prematurity, a
family history of allergy, a personal history of respiratory illnesses in early childhood, and being
                                            7-42

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exposed to other environmental pollutants such,as formaldehyde.  In addition, long-term exposure
may have more important effects than short-term exposure. One study of 7-year-old children
(Strachan, 1988; Strachan et al., 1990) used both questionnaires regarding smoking habits in the
household and the child's saliva cotinine levels as indices of exposure to ETS. The authors found
a significant increase in the. risk of having frequent cough when the questionnaire was used to
ascertain exposure, but no association between saliva cotinine levels and frequency of cough.  As
the authors remarked, biochemical markers permit characterization of recent tobacco smoke
exposures, but they may not adequately reflect exposure at some critical period in the past.
Recent studies of intraindividual variability of cotinine levels also have suggested that it may be
misleading to assess the validity of questionnaire measures against a single determination of a
biologic marker (Coultas, 1990b; Idle, 1990). It is thus possible that associations evaluated with
salivary cotinine are likely to underestimate the true relationship between passive smoking and
respiratory morbidity (Strachan et al., 1990).
       In the case of older children who may have started experimenting with cigarettes, the
confounding effects of active smoking need to be considered.  Most researchers have been aware
of this problem and have attempted to control for it.  A great difficulty lies in misclassification of
smokers due to underreporting. Young persons may be reluctant to admit smoking cigarettes.   ,
Data are often obtained from parents, who may not be aware of the child's smoking.
       In summary, this report concludes that ETS exposure at home causes increased prevalence
of respiratory symptoms in infants and young children. There is also good  evidence indicating
that passive smoking causes respiratory symptoms in some older children, particularly in children
who have predisposing factors that make them more susceptible to the  effects of ETS.
7.6. EFFECT OF PASSIVE SMOKING ON ASTHMA
       Studies addressing the effects of passive smoking on frequency of asthma were directly
reviewed only in the Surgeon General's report (U.S. DHHS, 1986) and not explicitly in the report
on environmental tobacco smoke by the NRC (1986). The Surgeon General's report concluded
that epidemiologic studies of children had shown no consistent relationship between the report of
a doctor's diagnosis of asthma and exposure to involuntary smoking.  The report pointed out that,
although one study had shown an association between involuntary smoking and asthma
(Gortmaker et al., 1982), others had not (Schenker et al., 1983; Horwood et al.,  1985). This
variability was attributed to differing ages of the children studied, differing exposures,  or
uncontrolled bias. The report also concluded that maternal cigarette smoking may influence the
severity of asthma.  Alteration of nonspecific bronchial responsiveness was proposed as  a
mechanism for this latter effect.
                                           7-43

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7.6.1.  Recent Studies on the Effect of Passive Smoking on Asthma in Children
       Several new cross-sectional and longitudinal studies published after the U.S. Surgeon
General's report (U.S. DHHS, 1986) was released have addressed the relationship between
frequency, incidence, and severity of asthma and parental cigarette smoke (Table 7-7).  (Studies
on the relationship between ETS exposure and bronchial responsiveness were reviewed in Section
7.2.4.)
       Burchfield and coworkers (1986) studied 3,482 nonsmoking children and adolescents ages
0 to 19 years out of 4,378 eligible subjects from Tecumseh, Michigan.  Subjects or their parents
(for children aged 15 years or younger) answered questionnaires on past history of asthma and
other respiratory conditions. Information on parental smoking habits was obtained from each
parent. Prevalence rates of asthma were higher among children whose parents both had smoked
during the child's lifetime than among children whose parents had never smoked.  The effect was
stronger and only reached statistical significance for males (OR for boys = 1.7,  95% C.I. = 1.2, 2.5
in boys; OR for girls = 1.2, 95% C.I. = 0.8,  1.9).  Children with one parental smoker were not more
likely to have asthma than was the unexposed reference group. When results were stratified by
parental history of respiratory conditions, there was some reduction in the magnitude of the
parental smoking effects, but results remained significant for asthma in males.  Results were also
independent of age, parental education, family size, a diagnosis of hay fever, and a history of
other allergies. Reporting bias and diagnostic bias  may in  part explain the relationships reported
in this study; smoking parents may be more likely to report asthma in their children, and
physicians may be more prone to diagnose asthma in children of smoking parents.
       D. Evans and coworkers (1987) studied 191 out of 276 children aged 4 to 17 years from
low- income families who were  receiving health care for physician-diagnosed asthma in New
York.  Excluded children were younger and had fewer emergency room visits for asthma than
those with complete data. The authors suggested that the latter subjects had more severe asthma
than the general  community population of low-income children with asthma. Emergency room
visits and hospitalizations for asthma were assessed by reviewing hospital records.  Passive
smoking by  the child was measured by asking one parent if he or she or anyone else in the house
smoked.  Authors did not differentiate between maternal and paternal smoking; no attempt was
made to assess the degree of exposure to cigarette smoke.  Eight children who were active smokers
were excluded. There was a significant correlation between number of emergency room visits and
cigarette smoke exposure  (p = 0.008); the mean frequency (± SD) of annual emergency room visits
observed for children exposed to passive smoking was 3.1 ± 0.4, compared with 1.8 ± 0.3 for
children from nonsmoking households. Passive smoking had no effect  on either the frequency of
days with asthma symptoms or on the annual  frequency of hospitalizations. Results were
                                           7-44

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independent of ethnicity and parental employment status.  The association could have been
explained by lower compliance with prescribed treatment of their children's asthma by smoking
parents, but the authors found no significant differences in compliance (as assessed by an index of
asthma self-management activities) between smoking and nonsmoking parents. The authors
estimated that the additional cost for emergency care for asthma was $92  ± $68 per family per
year.
       O'Connor and coworkers (1987) performed bronchial challenges with subfreezing air in
292 subjects 6 to 21 years of age. They were selected from 879 eligible subjects of the same age
who were participating in a longitudinal study on respiratory illnesses in East Boston. An attempt
was made to include as many subjects as possible who reported a history of asthma or wheezing on
standardized questionnaires.  Therefore, the latter group of subjects were overrepresented among
those tested.  The change in FEV^ caused  by subfreezing air was significantly higher in asthmatic
subjects whose mothers smoked at least one cigarette per day than in those whose mothers were
nonsmokers.  This relationship was independent of age, sex, height, personal smoking, paternal
smoking, atopy, and baseline lung function.  There was no relationship between maternal smoking
and response to cold air among nonasthmatics.
       Murray and Morrison (1989) studied 415 nonsmoking children  aged 1 to 17 years
consecutively referred to an allergy clinic in Vancouver, Canada, for asthma or recurrent
wheezing of the chest.  Questionnaires were administered to the parents of all children at the time
of their first visit.  Forced expiratory flows and bronchial reactivity to histamine also were
measured.  An asthma symptom score was calculated for each subject based on the severity of
asthma and the need for medication, as reported by parents. Children  of smoking  mothers had
significantly higher indices of asthma severity (p < 0.01) and significantly lower FEVX (84.4%
predicted vs. 77.3% predicted, p < 0.01) than did children of nonsmoking mothers. They were also
significantly more responsive to histamine than were children of nonsmoking mothers (p = 0.01).
The effect was present in both genders but was stronger for boys than  for girls.  Also, the effect
was stronger for older children (12 to 17 years of age) than  for children 6 years of age or younger.
The authors also reported a positive correlation between length of exposure to ETS and asthma
symptom score. It  is unlikely that these results can be explained by parental overreporting
because the association between passive smoking and severity of symptoms paralleled that between
passive smoking and objective measurements of severity.
       In their previously reviewed report (Section 7.5.1), Krzyzanowski and coworkers (1990)
found that children exposed to ETS and to more than 60 ppb of formaldehyde had significantly
higher prevalence rates of asthma than those  exposed to only one of these contaminants or to none
(OR for the latter comparison = 9.0; 95% C.I. = 2.4, 34.0). No such association was seen among
                                           7-48
-------
adult household members. It is unlikely that this association is attributable to parental
overreporting of asthma because the authors relied on objective measurement of indoor
formaldehyde concentrations.
       Sherman and collaborators (1990) reported on the results of a longitudinal study of
determinants of asthma in a sample of 770 schoolchildren enrolled in East Boston in 1974.
Questionnaires were used to obtain data on respiratory symptoms and illnesses, cigarette smoking
history of parents and children, and  household demographics.  They were administered on entry
and for 11 consecutive years (1978-1988). Parents answered for children aged 9 or less, except for
questions on the child's smoking history. The authors identified risk factors for the onset of
asthma, the occurrence of which antedated the time of first diagnosis of asthma.  There was no
significant relationship between maternal smoking and either prevalence of asthma at the first
survey or incidence of new cases of asthma during followup (sex-adjusted RR = 1.1; 95% C.I. =
0.7, 1.7). The authors considered it unlikely that this finding could be due to exposure levels too
low to increase the risk of asthma. However, no effort was made to assess the relationship
between incidence of asthma and number of cigarettes smoked by parents. Likewise, no effort
was made to determine the possible role of factors known to modify exposure to ETS such as
parental socioeconomic level (Strachan et al., 1989).
       Weitzman and coworkers (1990) studied 4,331 children  aged 0 to 5 years who were part of
the U.S. National Health Interview Survey.  Children were categorized as having asthma if their
parents reported that asthma was current at the time of interview and had been present for more
than 3 months.  Mothers were asked about their smoking habits during and after pregnancy. Odds
of having asthma were 2.1 times as high (95% C.I. = 1.3, 3.3) among children of mothers who
smoked 10 or more cigarettes per day than among children of nonsmoking mothers. The risk of
having asthma was not significantly  increased in children of mothers who smoked fewer than 10
cigarettes per day. Use  of asthma medication was also more frequent among children of mothers
who smoked 10 or more cigarettes per day (OR = 4.1; 95% C.I. = 1.9, 8.9).  Results did not change
significantly after controlling for gender, race,  presence of both parents, family size,  and number
of rooms in the households.  No information was available on parental respiratory symptoms or
socioeconomic status.  The results of this study  could be explained partially by overreporting of
asthma  by smoking mothers.
        Oldigs and collaborators (1991) exposed 11 asthmatic children to ETS and to ambient air
for 1 hour. They found no significant difference in lung function or in bronchial responsiveness
to histamine after ETS exposure when compared with sham exposure.  The study was designed
only to  determine if acute exposures to ETS caused immediate  effects, and it did not assess the
changes induced by chronic exposure to ETS.                                      ,
                                           7-49
-------
       Martinez and coworkers (1992) studied incidence of new cases of asthma in a population
sample of 774 out of 786 eligible children aged 0 to 5 years enrolled in the Tucson study of
chronic obstructive lung disease. At the time of enrollment, the child's parents answered
standardized questionnaires about personal respiratory history and cigarette smoking habits.
Surveys were performed on-an approximately yearly basis, and parents were asked if the child had
been seen by a doctor for asthma in the previous year.  There were 89 (11.5% of the total) new
cases of asthma during followup. Children of mothers with 12 or fewer years of formal education
and who smoked 10 or more cigarettes per day were 2.5 times as likely (95% C.I. = 1.4, 4.6) to
develop asthma as were children of mothers with the same education level who did not smoke or
who smoked fewer than 10 cigarettes per day. This relationship was independent of self-reported
symptoms in parents.  Decrements in lung function paralleled the increase in asthma incidence.
No relationship was observed between maternal smoking and asthma incidence among children of
mothers with more than 12 years of formal education.
       Ehrlich et al. (1992) studied 72 children with acute asthma recruited in the emergency
room; 35 nonacute asthmatic children from an asthma clinic; and 121 control children without
asthma from the emergency room.  They assessed exposure to ETS both by questionnaire and by
measurement of urinary levels of cotinine/creatinine ratios. Smoking by maternal caregiver  was
significantly more prevalent among asthmatic children (OR = 2.0, 95% C.I. = 1.1, 3.4).  This  was
confirmed by a significant difference between groups in prevalence of cotinine to creatinine ratio
of greater or equal to 30 ng/mg (OR = 1.9; 95% C.I. = 1.0, 3.4).  There was no difference in
exposure indices between acute and nonacute asthmatics. The authors concluded that smoking by
a maternal caregiver was a significant risk factor for clinically significant asthma in children.

7.6.2. Summary and Discussion on Asthma
       There is now sufficient evidence to conclude that passive smoking is causally associated
with additional episodes and increased severity of asthma in children who already have the
disease.  Several studies have found that bronchial  responsiveness is more prevalent and more
intense among asthmatic children exposed to maternal smoke. Emergency room visits are more
frequent in children of smoking mothers, and these children also have been found to need more
medication for their asthma than do children of nonsmoking mothers (see Table 7-4).
       A simple bronchospastic effect of cigarette smoke is probably not responsible for the
increased severity of symptoms associated with passive smoking because acute exposure to ETS
has been found to have little immediate effect on lung function parameters and airway
responsiveness in asthmatic children.  Therefore, the mechanisms by which passive smoking
enhances asthma in children who already have the  disease are likely to be similar to those
                                           7-50
-------
 responsible for inducing asthma and entail chronic exposure to relatively hig;h doses of ETS (see
 discussion below). Murray and Morrison (1988) reported that ETS exposure decreased lung
 function and increased medication requirements in asthmatic children only during the cold, wet
 season and not during the dry, hot season in Vancouver, Canada. These seasonal differences may
 be at least partly explained by the finding by Chilmonczyk and collaborators; (1990) that urine
 cotinine levels of children exposed to ETS are significantly higher in winter than in summer.
 These seasonal fluctuations also suggest that the effects of passive smoking on asthma severity are
 reversible and that decreasing exposure to ETS could prevent many asthmatic attacks in affected
 children.
        New evidence available since the Surgeon General's report (U.S. DHHS, 1986) and the
 NRC report (1986) also indicates that passive smoke exposure increases the dumber of new cases
 of asthma among children who have not had previous episodes (see Table 7-7 for results and
 references). Although most studies are based on parental reports of asthma, it is highly unlikely
 that the relationship between asthma and ETS exposure is entirely attributable to reporting bias.
 In fact, concordance in the relationship between ETS exposure and both questionnaires and
 objective  parameters such as lung function or bronchial provocation tests has been reported in
 several  studies. The association is also biologically plausible; the mechanisms that are likely to be
 involved in the relationship between ETS exposure and asthma have been discussed extensively  in
 Section 7.2. The consistency of all the evidence leads to the conclusion that ETS is a risk factor
 for inducing new cases of asthma.  The evidence is suggestive of a causal association but is not
 conclusive.
        Data suggest that levels of exposure required to induce asthma in children are high; in
 fact, most recent and earlier studies that classified children as exposed to ETS if the mother
 smoked one cigarette or more usually failed to find any effect of ETS on asthma prevalence or
 incidence. Furthermore, two recent large studies found an increase in the prevalence (Weitzman
 et al., 1990) or incidence (Martinez et al., 1992)  of asthma only if the mother smoked 10 cigarettes
 or more per day.  It is also important to consider that, for any level of parental smoking, exposure
 to ETS is higher in children belonging to families of a lower socioeconomic level (Strachan et al.,
 1989) and that the relationship of maternal smoking to asthma incidence may be stronger  in such
 families (Martinez et al.,  1992). Concomitant exposure to other pollutants alsio  may enhance the
 effects of  ETS (Krzyzanowski et al., 1990).

7.7.  ETS  EXPOSURE AND SUDDEN INFANT DEATH SYNDROME
                                                                       I
       The relationship between ETS exposure and sudden infant death syndrome (SIDS) was not
addressed  in either the Surgeon General's report (U.S. DHHS, 1986) or in the NRC report (1986).
                                           7-51
-------
Because of the importance of this syndrome as a determinant of infant mortality and because of
the available evidence of an increased risk of SIDS in children of smoking mothers, the issue has
been added to this report (Table 7-8).
       SIDS is the most frequent cause of death in infants aged 1 month to 1 year.
Approximately 2 of every  1,000 live-born infants (more than 5,000 in the United States alone
each year) die suddenly and unexpectedly, usually during sleep, and without significant evidence
of fatal illness at autopsy (CDC, 1989b).  The cause or causes of these deaths are unknown. The
most widely accepted hypotheses suggest that some form of respiratory failure is involved with
most cases of SIDS.
       In 1966, Steele and Langworth (1966) first reported that maternal smoking was associated
with an increased incidence of SIDS. They studied the hospital records of 80 infants who had
died of SIDS in Ontario, Canada, during  1960-1961 and compared them with 157 controls
matched for date of birth, sex, hospital at which the child was  born, and parity of the mother.
Infants of mothers who smoked 1 to 19 cigarettes per day were twice as likely (OR = 2.1; 95%
C.I. « 1.1, 3.8) to die of SIDS as were infants of nonsmoking mothers.  The odds ratio was 3.6
(95% C.I. = 1.7, 7.9) when infants of mothers who smoked 20 or more cigarettes per day were
compared to infants of nonsmoking mothers. The authors reported that the risk of dying of SIDS
was higher in low-birthweight infants whose mothers smoked when compared with
low-birthweight infants whose mothers did  not smoke.  However, they made no effort to control
for other confounders that were related both to maternal smoking and to SIDS, such as maternal
age and socioeconomic status.  In addition, they made no reference to the relative roles of in utero
exposure to tobacco smoke products and  postnatal ETS exposure.
       Naeye and collaborators (1976) studied 59,379 infants born between 1959 and 1966 in
participating hospitals from several U.S.  cities.  After meticulous investigation of clinical and
postmortem material, they identified 125 of these infants (2.3 per 1,000 live births) as having died
of SIDS and compared  them  with 375 infants matched for place of birth, date of delivery,
gestational age, sex, race, and socioeconomic status. Infants of mothers who smoked were more
than 50% more likely (OR =  1.6; 95% C.I. = 1.0, 2.4) to die of SIDS than  were those of mothers
who denied smoking.  When  compared with the latter, infants of mothers who smoked six or more
cigarettes per day were 2.6 times more likely (95% C.I. = 1.7, 4.0) to die  of SIDS. The authors
made no attempt to distinguish between  in utero exposure to tobacco smoke products and ETS
exposure after birth.
       Bergman and Wiesner (1976) selected 100 well-defined cases of SIDS occurring in white
children in King County, Washington. These cases were matched for race, sex, and birth date
with 100 controls. Questionnaires were mailed to the mothers of cases and controls, but only 56
                                            7-52
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                                               7-54
-------
cases and 86 controls returned them.  Mothers who did not respond tended to be younger and
poorer.  A higher proportion of mothers of SIDS victims smoked cigarettes during pregnancy (61%
vs. 42%). Infants of mothers who smoked after delivery were 2.4 times as likely (95% C.I. = 1.2,
4.8) to die of SIDS as were infants of nonsmoking mothers.  The relationship between postnatal
exposure to ETS and SIDS was significantly stronger and only reached statistical significance for
mothers aged 25 years or less (OR = 4.4; 95% C.I. = 1.7, 11.2). Infants of mothers aged 25 years or
less who smoked 20 or more cigarettes per day were 7.7 times as likely to die of SIDS (95% C.I. =
1.7, 35.4) as were infants of nonsmoking mothers. Effects were independent of maternal
education.  The authors did not try to determine the independent effects of prenatal and postnatal
exposures to maternal smoking on the incidence of SIDS.                       -
       Lewak and coworkers (1979) studied all infants who died during the first year of life and
who were enrolled in a health plan in Oakland, California. Using predefined criteria, they
classified 44 infants (2.3 per 1,000 live births) as having died of SIDS and  compared them with the
rest of the population for several possible risk factors for SIDS. Mothers of  infants  who died of
SIDS were 4.4 times (95% C.I. = 2.1, 9.2) as likely to be smokers as mothers of infants who
survived. Paternal smoking had no significant influence on SIDS frequency.  The authors made no
effort to control for possible confounding factors, nor did they discriminate between the possible
roles of prenatal and postnatal exposure  to tobacco smoke products.
       Malloy and coworkers (1988) linked birth and death certificates to study possible risk
factors for neonatal and postneonatal mortality in over 305,000 singleton white live  births in
Missouri. They identified 372 infants whose deaths were attributed to SIDS (1.2 per 1,000 live
births).  Infants whose mothers smoked were 1.8 times as likely (95% C.I. = 1.4, 2.2) to die of SIDS
than were infants of nonsmoking mothers. This relationship was independent  of maternal marital
status, education level, age, parity, and child's birthweight. There were no data available  that
would have allowed one to differentiate the effects of prenatal and postnatal exposure to tobacco
smoke products.
       Hoffman and collaborators (1988) reported on the results of the National Institute of Child
Health and Human Development Cooperative Epidemiological Study of Sudden Infant Death
Syndrome risk factors.  They studied 800 SIDS cases and 1,600 control infants  collected at six
study centers across the United States. Control infants were matched for age only (N = 800) or for
age, low birthweight, and race (N = 800). SIDS cases  were 3.8 and 3.4 times as likely to have
smoking mothers as the first and second control groups mentioned earlier, respectively (p < 0.005
for both comparisons).  There were no data on prenatal and postnatal exposure to tobacco  smoke
products.
                                            7-55
-------
       Haglund and Cnattingius (1990) examined risk factors for SIDS in a prospective study
based on more than 279,000 Swedish infants who survived the first week of life. SIDS was
reported as the sole cause of death in 190 infants (0.7 per 1,000), and in most cases the diagnosis
was confirmed by the results of an autopsy.  Infants of mothers who smoked one to nine cigarettes
per day were 1.8 times as likely (95% C.I. = 1.2, 2.6) to die of SIDS as were infants of nonsmoking
mothers. Infants of mothers who were heavy smokers had an even higher risk (OR = 2.7; 95%
C.I. = 1.9, 3.9) of dying of SIDS, suggesting an exposure-response  relationship. These findings
were independent of birthweight, maternal age, social situation, parity, sex, and type of birth. No
information was available regarding smoking in the household by either mother or father after the
infant's birth.
       Mitchell  and coworkers (1991) studied SIDS cases occurring in several health districts in
New Zealand between November 1, 1987, and October 31, 1988.  After careful assessment of the
material available from necropsy, 162 infants were classified as having died of SIDS (3.6 per 1,000
live births). These cases were  matched for age with three to four times as many controls. The
researchers interviewed the parents and obtained complete information for 128 cases and 503
controls. Information on maternal smoking during pregnancy (as a yes/no variable) was obtained
from the obstetric records, whereas information on number of cigarettes smoked by the mother in
the 2 weeks preceding the interview was obtained from questionnaires. Mothers of infants who
died of SIDS were 3.3 times as likely (95% C.I. = 2.2, 5.0) to smoke during pregnancy as were
mothers of controls.  The analysis of the relationship between maternal smoking after the child's
birth and frequency of SIDS showed clear evidence of a biological gradient of risk.  Odds ratios
were as follows:  1.9 (95% C.I.  =  1.0, 3.5) for mothers who smoked 1 to 9 cigarettes per day; 2.6
(95% C.I. - 1.5, 4.7) for mothers who smoked 10 to 19 cigarettes per day; and 5.1 (95% C.I. =
2.9, 9.0) for mothers who smoked 20 or more cigarettes per day. The association between
maternal smoking and SIDS frequency was independent of antenatal care, maternal age, maternal
education, marital status, sex, neonatal problems, parity, socioeconomic status, birthweight,
gestational age, race, season of death, sleep position at death, and breastfeeding.
       In summary, there is strong evidence that infants whose mothers smoke are at increased
risk of dying suddenly and unexpectedly during the  first year of life. This relationship is
independent of all other known risk factors for SIDS, including low birthweight and low
gestational age.  The finding that there is a biological gradient of risk extending from  nonsmoking
mothers to those smoking more than 20 cigarettes per day adds to the evidence that exposure to
cigarette smoke products is involved in the sequence of events that result in SIDS.  Available
studies cannot differentiate the possible effects with respect to SIDS of exposure to tobacco smoke
products in utero from those related to passive smoking after birth. As explained earlier (Section
                                           7-56
-------
7.2.2), both human and animal studies show that maternal smoking during pregnancy may modify
and potentiate the effects of postnatal ETS exposure.  The relationship between maternal smoking
and SIDS is independent of low birth weight, which is the most important known effect of
maternal smoking during pregnancy.  In addition, the incidence of SIDS is apparently associated
with days of higher air pollution  levels (Hoppenbrouwers et al., 1981), which could indicate a
direct effect of airborne contaminants.
       In view of the fact that the cause of SIDS is still unknown, it is not possible to assess the
biological plausibility of the increased incidence of SIDS related to ETS exposure. Consequently,
at this time this report is unable to assert whether or not passive smoking is a risk factor for SIDS.

7.8.  PASSIVE SMOKING AND  LUNG FUNCTION IN CHILDREN
       The Surgeon General's report (U.S. DHHS, 1986) reviewed 18 cross-sectional and
longitudinal studies on the effects of ETS exposure on lung function in children (Table 7-9). The
report concluded that "the available data demonstrate that maternal smoking reduces lung function
in young children" (page 54). The hypothesis was proposed that passive smoking during
childhood, by affecting the maximal level of lung function attainable during early adult life, may
increase the subsequent rate of decline of lung function and, thus, increase  the risk of chronic
obstructive lung disease.
       The NRC report (1986) reached similar conclusions after reviewing  12 articles (Table 7-9).
The authors' summary asserted that "estimates of the magnitude of the effect of parental smoking
on FEVj function in children range from 0 to 0.5% decrease per year. This small effect is
unlikely by itself to be clinically  significant. However,  it may reflect pathophysiologic effects of
exposure to ETS in the lungs of the growing child and, as such, may be a factor in the
development of chronic airflow obstruction in later life" (page 215).

7.8.1.  Recent Studies on Passive Smoking and Lung Function in Children
       Studies appearing since the 1986 reports are presented in Table 7-10.
       Lung  function measurements were included in the cross-sectional study by O'Connor and
collaborators (1987) described earlier (Section 7.6.1).  When compared to 97 nonasthmatic children
of nonsmoking mothers (mean age ± SEM = 12.8 ± 0.3  years), 168 nonasthmatic children of
smoking mothers (mean age  ± SEM  = 12.9 ± 0.2 years)  had significantly lower mean percentage
of predicted FEVj (mean ±  SEM = 108.0 ± 1.4 vs.  101.4 ± 1.1, respectively, p < 0.001) and
significantly lower FEF25.75 (103.0 ± 2.3 vs. 88.2 ± 1.5, respectively, p < 0.001). These effects
were independent of personal smoking by the child.
                                           7-57
-------
Table 7-9. Studies on pulmonary function referenced in the Surgeon General's and National
Research Council's reports of 1986
  Study
 No. of
subjects
Age of subjects
Surgeon
General
NRC
  Berkey et al. (1986)           7,834
  Brunekreef et al. (1985)         173
  Burchfield et al. (1986)       3,482
  Chen and Li (1986)             571
  Comstoek et al. (1981)        1,724
  Dodge (1982)                  558
  Ekwo et al. (1983)            1,355
  Ferris et al. (1985)           10,000
  Hasselblad et al. (1981)      16,689
  Kauffmann et al. (1983)       7,818
  Kentner et al. (1984)          1,851
  Lebowitz (1984)                117
  Lebowitz and Burrows          271
  (1976)
  Schilling et al. (1977)            816
  Tager et al. (1979)              444
  Tager et al. (1983)            1,156
  Tashkin et al. (1984)          1,080
  Vedal et al. (1984)            4,000
  Ware etal. (1984)            10,106
  Weiss etal. (1980)              650
  White and Froeb (1980)       2,100
          Children (6 to 10)              X
          Adult women                  X
          Infants/children (0 to 10)        X
          Children/adol. (8 to 16)         X
          Adults                         X
          Children (8 to 10)              X
          Children (6 to 12)              X
          Children/adol. (6 to 13)
          Children (5 to 17)              X
          Adults                         X
          Adults                         X
          Families                       X
          Children/adol. (<16)            X

          Children/adol. (<18)            X
          Children (5 to 19)
          Children (5 to 9)                X
          Children (7 to 17)              X
          Children (6 to 13)              X
          Children (6 to 13)
          Children (5 to 9)                X
          Adults                         X
                                           X
                                           X
                                           X
                                           X
                                           X
                                           X
                                           X

                                           X
                                           X
                                           7-58
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-------
       Lebowitz and coworkers (1987) reported on the results of a longitudinal study of
pulmonary function development in Tucson, Arizona. The authors analyzed 1,511 observations
over an average followup period of 8.8 years in 353 subjects aged 5.5 to 25 years.  The last
available lung function value (as residuals after regressing the data with different power functions
of age and height) was used as outcome.  Residuals for vital capacity were significantly higher
among subjects aged 14 years or less at entry whose mothers smoked cigarettes (mean = +3.3 vs.
-1.4 among nonexposed subjects, p < 0.001).  Parental smoking had no direct effect on outcome
FEY], or Vmax50%, but showed significant interactions with personal smoking and parental history
of airway obstructive diseases in their effects on Vmax50%; subjects who had started smoking or
whose parents had airway obstructive diseases and were exposed to ETS had the lowest Vmax50%
residuals at the  end of followup.
       In subsequent reports, Lebowitz and Holberg (1988) and Tager and coworkers (1987)
reanalyzed two  sets of longitudinal pulmonary function data:  the one on which the preceding
study from Tucson,  Arizona, was based (Lebowitz et al.,  1987) and data for children of similar age
from East Boston, Massachusetts (Tager et al., 1983).  The objective was to determine if the
different answers with regard to the effect of  maternal smoking (significant for the Boston study;
no effect for the Tucson study) were due to the use of different statistical tools. Applying the
same multivariable analysis of covariance for both data sets, Lebowitz and Holberg (1988)
confirmed the positive effect of maternal smoking of FEF25_75% with the data from Boston (p <
0.05) and the lack of a significant effect of maternal smoking on Vmax50% with the data from
Tucson, Arizona. A first-order autoregressive model applied by Tager and collaborators (1987) to
both data sets showed effects of maternal smoking on FEVj with the Boston data but not with the
Tucson data. The authors concluded that the most likely factor responsible for the disparate
results was the exposure difference in the two populations.
       Tsimoyianis and collaborators (1987) compared the prevalence of low levels of FEF25_75%
(< 70% of predicted) in athletes exposed and unexposed to ETS (for more information on this
study see Section 7.5.1). Of 132 exposed athletes,  18 (13.6%) had low FEF25_75% compared with  2
of 61 (3.3%) unexposed athletes (OR = 4.7; 95% C.I.= 1.1, 20.8).
       Kauffmann  and collaborators (1989b) assessed familial factors related  to lung function in a
cross-sectional study of 1,160 French children. Levels of lung function (FEVj and FEF25_75%)
were significantly lower in children with mothers who smoked when compared to those whose
mothers were nonsmokers.  The authors reported a loss of 10 mL of FEVj (p < 0.05) and of 15
mL/s of FEF25_75%  (p < 0.01) for every gram of tobacco  smoked per day by the mother.  These
associations were independent of sex, town of origin, age, height, weight, and intrafamilial
aggregation of lung function. There was no effect of paternal smoking on lung function.
                                           7-61
-------
        Chan and coworkers (1989b) performed lung function tests in a cohort of 130 children of
 low birthweight (under 2,000 grams) at 7 years. These authors had previously reported on the
 respiratory outcome of these same children (see Section 7.5.1). Children of low birthweight whose
 mothers smoked had significantly lower values of percentage of predicted Vmax75% than did low-
 birth weight children whose mothers did not smoke (80.7% vs. 91.4%, p < 0.01). This association
 was independent of sex, birthweight, neonatal respiratory illness, and treatment.  As 92% and 79%
 of mothers who smoked when the child was 7 years old were smokers before and during their
 pregnancy, respectively, it was not possible to determine whether the effect of maternal smoking
 was fetal or postnatal.
       The study by Dijkstra and collaborators (1990) has been described earlier (Section 7.5.1).
 The authors studied, together with respiratory symptoms, lung function and its relationship with
 indoor exposures to ETS and nitrogen dioxide in a population of 634 Dutch children 6 to 12 years
 of age.  When compared with unexposed children, children exposed to ETS had significantly lower
 levels of FEVi (-1.8%; 95% C.I. = -0.2, -3.3), FEF25.75%  (-5.2%; 95% C.I. = -1.4, -8.8) and
 Peak Flow (-2.8%; 95% C.I. = -0.6,  -4.8). Adjustment for smoking by the mother when she was
 pregnant with the investigated child removed little of the effect of current ETS exposure on lung
 function. The authors  suggested that this indicated that the associations seen at ages 6 to 12 years
 were not just mirroring harm that was caused when the children  were exposed in utero to tobacco
 smoke components inhaled by the mother.  There was no association between exposure to NO2 and
 lung function.
       A previously mentioned study by Strachan and coworkers (1990) (Section  7.5.1) included
 lung function  measurements in 757 children.  Lung function variables were adjusted for sex,
 height, and housing characteristics. The authors found a significant negative correlation between
 salivary cotinine concentrations and levels of FEF25_75% (p < 0.05) and Vmax75% (p < 0.05). For
 these indices, the difference between adjusted mean values  for the  top and bottom quintiles of
 salivary cotinine was of the order of 7% of the mean value in the children with undetectable
 levels.
       The longitudinal study by Martinez and coworkers (1992) has been  reviewed earlier
 (Section 7.6.1). In addition to their findings on incidence of childhood asthma, these authors
 reported  that, at the end of followup, children of mothers with 12 or fewer years  of formal
education and  who smoked 10 or more cigarettes per day had 15% lower mean values for
percentage of predicted FEF25_75% than did children of mothers of  the same level of education
who were nonsmokers or smoked fewer than 10 cigarettes per day.  Maternal smoking had no
effect on percentage of predicted FEF25_7S% values in children of mothers who had at least some
education beyond high school.  Female children of smoking mothers (£: 10  cig./day) had 7%
                                          7-62
-------
higher vital capacity than did female children of mothers who were nonsmokers or light smokers
(< 10 cig./day), and this was independent of maternal education. All differences were still
significant after controlling for parental history of respiratory disease.

7.8.2. Summary and Discussion on Pulmonary Function in Children
       This report concludes that there is a causal relationship between ETS exposure and
reductions in airflow parameters of lung function (FEV15 FEF25_76%, Vmax50%, or Vmax75%) in
children.  For the population as a whole, these reductions are small relative to the intraindividual
variability of each lung function parameter; for FEF2B_76%, for example, reductions range from
3% to 7% of the levels seen in unexposed children, depending on the study analyzed.  Groups of
particularly susceptible or heavily exposed subjects have larger decrements: Exposed children of
low birthweight, for example, had 12% lower Vmax75% than did children of similar birthweight
who were not exposed to ETS (Chen, 1989).  Likewise, children of less educated mothers who
smoked 10 or more cigarettes per day were shown to have 15% lower mean FEF25_75% than
children of less educated mothers who did  not smoke or smoked fewer than 10 cigarettes per day.
This stronger effect may be explained by Strachan and coworkers' (1989) finding that children of
lower socioeconomic status have higher salivary cotinine levels, for any amount of parental
smoking, than do children of higher socioeconomic status.
       The studies reviewed suggest that a continuum of exposures to tobacco products starting in
fetal life may contribute to the decrements in lung function found in older children.  In fact,
exposure to tobacco smoke products inhaled by the mother during pregnancy may contribute
significantly to these changes, but there is strong  evidence indicating that postnatal exposure to
ETS is an important part of the causal pathway.
       New longitudinal studies have demonstrated that young adults who were exposed earlier in
life to ETS are also more susceptible to the effects of active smoking (Lebowitz et al., 1987). In
addition, Sherrill and collaborators (1990) showed, in a longitudinal study, that children who
entered a longitudinal study with lower levels of lung function still had significantly lower levels
later in  life.  The high degree of tracking shown by these spirometric parameters implies that the
decrements in lung function related  to passive smoking may persist into adulthood.  Although the
subsequent rates of decline in lung function of these subjects have yet to be studied in detail, the
findings by Sherrill and coworkers (1990) support the idea proposed by the Surgeon General's
report (U.S. DHHS, 1986) that, by the mechanisms described above, passive smoking  may increase
the risk of chronic airflow limitation.
                                           7-63
-------
7.9. PASSIVE SMOKING AND RESPIRATORY SYMPTOMS AND LUNG FUNCTION IN
     ADULTS
       Both the NRC report (1986) and the Surgeon General's report (U.S. DHHS, 1986)
extensively reviewed the evidence then available on involuntary smoking and respiratory health in
adults. The Surgeon General's report concluded that healthy adults exposed to ETS may have
small changes on pulmonary function testing but are unlikely to experience clinically significant
deficits in pulmonary function as a result of exposure  to ETS alone.  The report added that the
small magnitude of the effect implied that a previously healthy individual would not develop
chronic lung disease solely on the basis of ETS exposure in adult life. It was suggested that small
changes in lung function may be markers of an irritant response, possibly transient, to the irritants
known to be present in ETS.
       The NRC report concluded that it was difficult to document the extent to which a single
type of exposure like ETS affects lung function. The  report attributed this difficulty to the large
number of factors, including other exposures, that affect lung function over a lifetime.  The
report added that results in adults should be evaluated for possible misclassification of ex-smokers
or occasional smokers as nonsmokers, as well as possible confounding by occupational exposures to
other pollutants. The authors of the report considered it "unlikely that exposure to ETS can cause
much emphysema" (page 212), but that, "as one of many pulmonary insults, ETS may add to the
total burden of environmental factors that become sufficient to cause chronic airway or
parenchyma! disease" (page 212).

7.9.1.  Recent Studies on Passive Smoking and  Adult Respiratory Symptoms and Lung Function
       Six recent studies of respiratory symptoms and lung function in adults are presented in
Table 7-11.
       Svendsen and collaborators (1987) studied longitudinal data from 1,245 married American
men aged 35 to 57 years who reported that they had never smoked. Subjects who had smoking
wives had significantly higher mean levels of exhaled carbon monoxide (7.7 vs. 7.1  ppm,
p < 0.001) but not of serum thiocyanate.  These men also had lower levels of age- and
height-adjusted FEVi (mean difference = 99 mL; 95% C.I. = 5, 192.4 mL).  However, those with
wives who smoked 20 or more cigarettes per day had higher mean adjusted ¥EVt (3,549  mL) than
those with wives who smoked 1 to 19 cigarettes per day (3,412 mL), whereas nonexposed subjects
had mean adjusted FEVj^ of 3,592 mL.
       Kalandidi and coworkers (1987) studied 103  Greek ever-married women aged 40 to 79
who were admitted in 1982 and 1983 to a hospital in Athens with obstructive or mixed type
reduction of pulmonary function, without improvement after bronchodilatatiori.  The women
                                          7-64
-------
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denied that they had ever been smokers, and their husbands' smoking habits were compared with
those of 179 ever-married controls of the same age selected from visitors to the hospital. Patients
were 1.9 times more likely to have smoking spouses than were controls (95% C.I. = 1.0, 4.0).
However, odds ratios were higher for women whose spouses smoked 20 or fewer cigarettes per
day (2.5) than for those whose spouses smoked more than 20 cigarettes per day.  The unusually
high number of nonsmoking women hospitalized with chronic lung disease in a 2-year period
suggests that some could have severe asthma unresponsive to bronchodilators and that the results
could in part illustrate exacerbation of symptoms in asthmatic women exposed to ETS.
       Masi and coworkers (1988) mailed questionnaires to 818 subjects aged 15 to 35 who had
previously performed detailed lung function testing and carboxyhemoglobin (COHb)
measurements.  A total of 636 subjects responded to the questionnaire, and 293 denied having
smoked regularly before the date of the  lung function tests.  All but five subjects had COHb
values below 5 grams %.  Questionnaires assessed past and present ETS exposure, both at home
and at work. Indices of cumulative exposure to ETS at home and at work were calculated from
the number of reported smokers on each location, the smoking conditions reported for each area,
and the number of years of exposure. In men, there were significant inverse relationships
between cumulative exposure to ETS in the home and maximal expiratory flows at low lung
volumes. A more detailed analysis showed that in these subjects, exposure before 17 years of age
had the strongest effects on lung function, whereas exposure in the 5 years preceding the lung
function tests had no effect on lung function.  Exposure at work significantly decreased the
diffusing characteristics of  the lung in women.
       Kauffmann and collaborators (1989a) compared the results obtained from a parallel
analysis of the association of passive smoking with respiratory symptoms and lung function in
2,220 American women aged 25 to 69 years  and 3,855 French women aged 25 to 59 years.  Women
were classified according to their personal and current  spouse's smoking habits. After adjusting
for age, city of origin, educational level, and occupational exposure, ever-passive-smokers
(excluding active smokers) had significantly more wheeze than true never-smokers (i.e., never
active and  with nonsmoking spouse) in the U.S. sample (OR of approximately 1.3; C.I. cannot be
calculated). There was a positive trend  for French passive smokers to have more chronic cough
(OR = 1.4) and dyspnea (OR = 1.2), but both results could be due to  chance (95% C.I. = 0.8, 2.4
and 0.9, 1.6, respectively).  In both samples, no significant decrease of lung function was observed
for passive smokers compared with true never-smokers in the whole sample, although FEVj/FVC
values for  ever-passive-smokers tended to be intermediate between those of true never-smokers
and ex-smokers or active smokers. French women aged 40 or older who were passive smokers  had
                                           7-67
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significantly lower FVC (p < 0.01) and FEVl (p < 0.01) than did true never-smokers, but no such
effect was seen among American women of the same age.
       Hole and coworkers (1989) studied cardiorespiratory symptoms and mortality in a cohort
of 7,997 subjects aged 45 to 64 and followed for 11 years in urban west Scotland. A self-
administered questionnaire was used in  1972-76 to assess respiratory symptoms and active
smoking by each member of the household.  When compared with true never-smokers (i.e.,
persons who were not active smokers and did not live with an active smoker), passive smokers
were invariably at a higher risk of having each cardiorespiratory symptom examined (including
infected sputum, persistent sputum, and dyspnea), but all 95% confidence intervals for odds ratios
included 1.  FEV^ (adjusted for sex, age, and height) was significantly higher in true never-
smokers than in passive smokers (p < 0.01), but this effect was mainly due to the low adjusted
FEVj of passive smokers with high exposure (i.e., exposed to a cohabitee who smoked >  15
cig./day; mean = 1.83 L) when compared with those with low exposure (mean = 1.89 L) or with no
exposure (mean = 1.88 L).  This study was initiated when there was little concern for the possible
ill effects of passive smoking and is based on self-reports of active smoking by cohabitees.  It is
thus probably  not affected by classification bias due to overreporting of symptoms by smokers.
       Schwartz and Zeger (1990) studied data from a cohort of approximately 100 student nurses
in Los Angeles who kept diaries of acute respiratory symptoms (cough, phlegm, and chest
discomfort)  and for whom data on exposure to passive smoking and air pollution were available.
After controlling for personal smoking,  a smoking  roommate increased the risk of an episode of
phlegm (OR * 1.4; 95% C.I. = 1.1, 1.9) but not of cough. The authors also excluded asthmatics (on
the assumption that medication could bias the results) and found that in this case, the odds ratio of
having phlegm increased to 1.8 (95% C.I. = 1.3, 2.3).  The greater sensitivity of diaries of acute
symptoms such as those used herein, compared with the indices of period prevalence of symptoms
used in other studies, may  have increased  the power of this study.  However, overreporting by
exposed subjects is still a possible source of bias in a study that is solely based on self-report of
symptoms.

7.9.2. Summary and Discussion on Respiratory Symptoms and Lung Function  in Adults
       Recent studies have confirmed the conclusion by the Surgeon General's report
(U.S. DHHS, 1986) that adult nonsmokers exposed to ETS may have small reductions in lung
function (approximately 2.5% lower mean FEVj in the studies by Svendsen et al. [1987] and Hole
et al. [1989]). Using modern statistical tools designed for longitudinal studies, new evidence also
has emerged suggesting that exposure to ETS may increase the frequency of respiratory symptoms
                                           7-68
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in adults.  These latter effects are estimated to be 30% to 60% higher in ETS-exposed nonsmokers
compared to unexposed nonsmokers.
       Because active smoking causes significant reductions in lung function and significant
increases in prevalence of respiratory symptoms (U.S. DHHS, 1984), the reported effects of
passive smoking in adults are biologically plausible.  From a quantitative point of view, effects of
passive smoking on lung function are approximately comparable to those reported for light (< 10
cig./day), male active smokers (Camilli et al., 1987). However, because of the self-selection of
smokers and other factors, it is difficult to make direct quantitative comparisons between the
effects of active and passive smoking. The process of self-selection is likely to occur among
smokers by which more susceptible individuals never start smoking or quit smoking early in life
(the "healthy smoker" effect). Therefore, lower lifetime doses may be required to elicit effects
among nonsmokers than among smokers. The different nature of ETS and MS also has been
discussed in previous chapters and must be taken into account when comparing effects of active
and passive smoking.
       Several sources of bias and confounding factors need to be considered in studies of the
effects of single exposures in adults.  Classification bias due to underreporting of active smoking
or past smoking may significantly affect the results of these studies.  Because there is marital
aggregation of smoking (i.e., smokers tend to marry smokers, and nonsmokers are more prone to
marry nonsmokers),  this source of misclassif ication is more probable among spouses of smokers
and may introduce differential biases in some studies. The resulting small overestimation  of
effect may be nevertheless substantial for effects that are particularly subtle, such as those
described for ETS exposure  in adults. In addition, recent public concern with passive smoking
may increase the awareness of respiratory symptoms in exposed subjects, who may be thus more
prone to report symptoms than are unexposed subjects.  Studies using objective measures of lung
function obviously are not affected by the latter type of bias.
       Adults are exposed to multiple sources of potentially harmful substances during their
lifetimes, and it is not always possible to control for the effects of these substances because they
often are unknown or unmeasurable. In general, the majority of these exposures should introduce
nondifferential error to the studies, which would lead to underestimates of the true effects. For
example, a significant nondifferential error may be introduced by ETS exposure during
childhood, which is  known to cause decrements in lung function (see Section 7.7) that may be
carried into adulthood.  ETS exposure during childhood also is known to cause childhood
respiratory diseases (see Sections 7.3, 7.5, and 7.6).  Such childhood respiratory diseases, whatever
the cause, also may be reflected  in decreased respiratory health in adulthood.  These effects have
                                            7-69
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not been accounted for in the studies of ETS exposure and lung function in adults, but it is likely
that they would lead to underestimates of the ETS effects in the adult studies.
       Conversely, effects of ETS would be overestimated if a certain noxious exposure were
more likely to occur among ETS-exposed subjects. In this sense, social factors need to be
accurately controlled, because prevalence of smoking is significantly higher among less educated
than among higher educated subjects (Pierce et al., 1989).  Most reviewed studies have controlled
for indices of socioeconomic level in a satisfactory manner. Finally, lifestyles may differ between
spouses of smokers and those of nonsmokers, but it is not possible to determine a priori the effect
of this confounder on the relationship between passive smoking and respiratory health.
       The influence of these factors and sources of bias, together with the subtlety of the
effects, may explain the  inconsistent and sometimes contradictory results of the studies reviewed
in this report. In fact, such variability should be expected, particularly for studies with relatively
low power (i.e., low probability of finding a statistically significant difference when a difference
really exists).  The lack of a dose-response relationship in some studies also may be explained by
the multiplicity of uncontrolled factors that may affect lung function.
       In summary, recent evidence suggests that passive smoking has subtle but statistically
significant effects on the respiratory health  of nonsmoking adults.
                                            7-70
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         8. ASSESSMENT OF INCREASED RISK FOR RESPIRATORY ILLNESSES
               IN CHILDREN FROM ENVIRONMENTAL TOBACCO SMOKE

       In the preceding chapter, a review was presented of recently published studies regarding
the association between respiratory illnesses in children and environmental tobacco smoke (ETS)
exposure. The biological plausibility and the possible pathogenetic mechanisms involved in each
group of illnesses included in the chapter also were discussed.  The purpose of this chapter is to
consider the weight of the evidence as a whole, to analyze in detail possible sources of systematic
bias or confounding that may explain the observed associations, and to estimate the population
impact of ETS-associated respiratory illnesses.

8.1.  POSSIBLE ROLE OF CONFOUNDING
       In the review of the available evidence indicating an association (or lack thereof) between
ETS exposure and the different outcomes considered in this report, the possible role of several
confounding factors was analyzed in detail (see Chapter 7).  Such analysis will only be summarized
here.
       •    Other indoor air pollutants (wood smoke, NO2, formaldehyde, etc.) have not been
             found to explain the effects of ETS but may interact with it to increase the risk of
             both respiratory illnesses and decreased lung function in children.
       •    Many of the studies reviewed in this report and in those of the National Research
             Council (NRC,  1986) and the Surgeon General (U.S. DHHS, 1986) used either
             multivariate statSstical methods of analysis or poststratification of the sample to
             control for the possible confounding effects of socioeconomic status. Others
             controlled for this effect by study design. It can be concluded that socioeconomic
             status does not explain the reported effects of ETS on children's health, although
             children belonging to some social groups may be at an increased risk of suffering the
             effects of passive smoking (see also Section 8.3).
        •    The effect of parental symptoms on the association between ETS and child health
             also has been extensively analyzed.  It can be concluded that, although parents with
             symptoms may  be more aware of their children's symptoms than are parents without
             symptoms,  it is unlikely that this fact by itself explains the association. In fact,
             objective parameters of lung function, bronchial responsiveness, and atopy, which
             are not subject to such sources of bias, have been found to be altered in children
             exposed to ETS.
                                             8-1
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        •    The effects of passive smoking may be modified by several characteristics of the
             exposed child. Increased risk has been reported in premature infants and infants of
             low birthweight, infants who are not breast-fed, infants who are kept at home with
             smoking mothers and not sent to day-care centers, asthmatic  children, and children
             who are active smokers.
        •    Maternal smoking during pregnancy has significant effects on fetal growth and
             development and may affect lung growth as well as the immunologic system.
             However, reports of important effects of paternal smoking on the child's health and
             studies in which ETS exposure was found to have effects that were independent of
             in utero exposure indicate that maternal smoking during pregnancy does not explain
             the  relation between passive smoking and child health, but modifies the effects of
             ETS.
        In summary, there are no single or combined confounding factors that can explain the
 observed respiratory effects of passive smoking  in children.

 8.2. MISCLASSIFICATION OF EXPOSED AND UNEXPOSED SUBJECTS
        The importance of misclassification of exposed and  unexposed children has not been
 addressed and will be analyzed in detail below.
        Two possible sources of systematic bias related to subject misclassification are considered.
 The first is upward bias from the effect of active smoking in children; the  second is downward
 bias due to misreporting and background exposure.  Both have also been considered in the
 assessment of ETS and  lung cancer in adults. Adjustment for background exposure will be  similar
 to that presented  in Chapter 6, except that data for increased incidence of some ETS-associated
 respiratory diseases show some evidence of thresholds that must also be taken into account.

 8.2.1.  Effect of Active Smoking in Children
       The possibility needs to be considered that some children may be smokers themselves and
 that this may happen more often among children of smoking parents than among those of
 nonsmoking parents. This would bias the  results upwards or against the null effect. This source
 of bias is only applicable to studies of older children; regular active smoking may occur but is rare
 before early adolescence. A study of third graders in Edinburgh, Scotland, by Strachan and
 coworkers (Strachan et al., 1989, see Section 7.4.1, for example) showed that salivary cotinine
 levels compatible  with active smoking were found in 6 of 770 children ages 6-1/2 to 7-1/2 years,
suggesting only a  small  potential for bias.  Consideration should also be given to the fact that some
                                           8-2
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of the effects described m Chapter 7 (for example, the increased risks for acute respiratory
illnesses [Section 7.3] and for cough, phlegm, and wheezing [Section 7.5]) have been found to be
stronger in younger children (i.e., those less likely to be active smokers) than in older children.
This observed reduced effect with increasing age may be in part due to an age-related  increase in
misclassification of exposed subjects as "unexposed" (see below), but it is clear that these specific
effects of ETS do not increase  with age, as would be expected if active smoking biased the results
of studies of ETS effects in older children. It can thus be concluded that the association between
respiratory health in children and ETS is  not attributable to active smoking by some  children. It
has been suggested that active  and passive smoking may interact to increase the effects of either
exposure separately (Lebowitz and Holberg, 1988). This interaction is biologically plausible,
because it is likely that active smoking may be more harmful in children whose lungs have been
previously affected by ETS (see Section 7.1).

8.2.2.  Misreporting and Background Exposure
       Various investigators have measured cotinine levels in body fluids in infants  and children
and correlated the results with parental reports of ETS exposure. Coultas and coworkers (1987)
reported that  37% of children  under 5 years of age whose parents were nonsmokers had a salivary
cotinine level greater than  0, compared with 32% of children ages 6 to 12 and with 35% of
children ages  13 to 17. These  authors did not ask parents to report possible sources of ETS
exposure for their children other than their own tobacco consumption.  Strachan and coworkers'
study in 6-1/2- to 7-1/2-year-old children in Scotland (Strachan et al., 1989) showed  that 73% of
children from households with no smokers had detectable  concentrations  of cotinine in saliva,
whereas only  1 in 365 children from households with one or more smokers had no detectable
salivary cotinine.  The assay used by Strachan and coworkers was  10 times more sensitive than that
used by Coultas and coworkers, and this  may explain the larger number of subjects  with
detectable levels in the former study when compared with the latter.
        Greenberg and coworkers (1984)  studied cotinine levels in 32 infants in North  Carolina
 with reported exposure to  tobacco smoke within the previous 24 hours and in 19 unexposed
 infants. All subjects were under 10 months old. Urine samples of all exposed infants contained
 cotinine, whereas all unexposed infants except 2 (11%) had undetectable  urine cotinine or levels
 below those of exposed infants with the  lowest levels of urine cotinine.  This same group of
 researchers reported results for a larger sample (433 infants at a mean age of 18 days)  of the same
 population (Greenberg et al.,  1989). They found that,  of  157 infants who reportedly lived in
 nonsmoking households  and were also not in contact with smokers the previous week, 37 infants
                                             8-3
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 (24%) had cotinine in their urine. They concluded that these infants had contact with tobacco
 smoke during the previous week and that this contact was unknown to or was not reported by
 their mothers.
        Greenberg and coworkers (1991) followed 152 of the 433 infants originally enrolled and
 reassessed exposure to ETS (through maternal interviews) and urine cotinine levels when the child
 was 12.3 ± 0.6 months old. They found a significant increase in the prevalence of tobacco smoke
 absorption, indicated by excretion of cotinine, during the first year of life (from 53% at a mean
 age of 3 weeks to 77%).  The interviews showed that this was mainly due to an increased exposure
 to nonhousehold sources of smoke (from 14% to 36%). The proportion of infants who reportedly
 had no contact with smokers but had cotinine in their urine increased from 24% at 3 weeks to 49%
 at 1 year of age.
       These results indicate that studies relying exclusively on parental questionnaires to
 ascertain ETS exposure in children may misclassify many exposed subjects as nonexposed.
 Moreover, the degree of misclassification may increase with the child's age.
       The possible consequences of this misclassification of exposure need to be discussed in
 detail. Nondifferential misclassification (i.e., exposure classification that is incorrect in equal
 proportions of diseased and nondiseased subjects) biases the observed results toward  a conclusion
 of no effect (Rothman, 1986).  The effect of differential misclassification depends on the
 direction in which misclassification occurs. If true ETS exposure is preferentially reported by
 parents of diseased subjects (i.e., there is reporting bias), an excess of disease prevalence would be
 found among  exposed  subjects when compared with unexposed subjects that is unrelated to any
 biological effect of ETS.  The evidence available clearly indicates that this is a very unlikely
 explanation for the reported misclassification of ETS exposure in infants and children. In fact,
 reporting bias cannot explain the substantial increase in "underreporting" of exposure with age.
 The logical explanation is provided by the finding that exposure to nonhousehold smokers
 increases significantly  with age and parallels the increase in  the proportion of subjects who have
 cotinine  in their urine  (Greenberg et al., 1991). There is no  reason to believe that exposure to
 smokers  may occur preferentially among diseased children, and the contrary may be more
 reasonable; the increased awareness of the ill effects of ETS  inhalation may induce parents to limit
 contact between their diseased children and nonhousehold smokers. Thus, the net effect of
misclassification of exposure, both nondifferential and differential, should be a systematic   .
downward bias or bias  toward observing no effect.  A correction for the nondifferential
misclassification bias of background exposure is made in Section 8.3.
                                            8-4
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8.3.  ADJUSTMENT FOR BACKGROUND EXPOSURE
       An important conclusion of the previous discussion is that studies based on parental
questionnaires may underestimate the health risk from ETS in children due to underreporting of
ETS exposure. The NRC (1986) report on passive smoking adopted the use of cotinine measures
to correct for misreporting of ETS exposure for lung cancer effects, and this approach was
adapted for use in Chapter 6 of this report. It will also be employed here, with the cotinine ratios,
however, based on exposure data in children rather than in adults. The method is based on several
assumptions:  (1) cotinine concentrations in body fluids of nonsmokers are linearly related to ETS
exposure, (2) the excess risk of respiratory illness in subjects exposed to ETS is linearly related to
the dose of ETS absorbed, (3) the relationship between ambient and absorbed ETS is linear,  and
(4) one cotinine determination may adequately represent average  childhood exposure to ETS.
       As support for assumptions 1 and 2, three recent studies have used body cotinine levels as
biomarkers for ETS exposure in children.  All three have  found significant associations between
cotinine levels and respiratory effects in children. Etzel et al. (1992) found a significant
relationship between serum cotinine levels and otitis media with effusion for children who
attended a day-care facility during the first 3 years of life.  Ehrlich et al. (1992), in a study  that
used questionnaires on maternal caregiver smoking as well as urinary cotinine levels to assess ETS
exposure, found that by either measure ETS exposure was significantly associated with both acute
and nonacute asthma in children.  Furthermore, urinary cotinine  levels in asthmatic children
showed a highly significant correlation with maternal caregiver smoking status. In the third
study, Reese et al. (1992) found urinary cotinine levels significantly (p < 0.02) elevated in children
admitted to the hospital with bronchiolitis compared with a group of similarly aged children
admitted with nonrespiratory illnesses. There was also a highly significant correlation (p < 0.0005)
between urinary cotinine levels and maternal smoking  as determined by questionnaire. Thus, the
evidence suggests that questionnaire ascertainment of childhood exposure to ETS and cotinine
biomarkers in children are highly correlated with each other and  that both correlate with
childhood diseases. This information is used to develop the risk assessment models below.
       While considerable evidence exists for assumptions 1 through 3 (see also Chapter 3), there
is some evidence that assumption 4 may not be entirely warranted, at  least for older children.
Coultas and coworkers (1990b), in a small study of 9 children from 10 homes with at least 1
smoker, reported that there is considerable variability in cotinine levels in body fluids within
individuals exposed to ETS when such levels are  repeatedly measured on different days.
However, Henderson et al. (1989), doing repeated urinary cotinine measures in preschool children,
found stable levels over 4 weeks.  Thus, while the method of adjustment is based on group mean
                                            8-5
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body cotinine levels, which apparently reflect household ETS levels well, the Intraindividual
variability, at least in older children, may subject these means to some error.
       Application of the method proposed by the NRC requires some knowledge of Z, the ratio
between the operative mean dose level in the "exposed" group, dE, and the mean dose level in the
"unexposed" group, dN. RR(dE), the relative risk for the group identified as "exposed" compared
with the group identified as "unexposed," is thus given by
                                RR(dE) = (l+Z*/3dN)/(l+/?dN)
(8-1)
where ft is the amount of increase per unit dose and Z > RR(dE) > 1. (The "unexposed" group
actually contains those with background exposure plus those truly unexposed.)
       Several studies are available that could be used for the purpose of estimating Z. Jarvis and
coworkers (1985) studied 569 nonsmoking schoolchildren ages 11 to 16 in Great Britain. The
investigators reported that, when compared with salivary cotinine levels in children of
nonsmoking parents (N = 269), mean levels of salivary cotinine were 3.0 times as high in children
whose father smoked (N = 96), 4.4 times as high in children whose mother smoked, and 7.7 times
as high in children whose parents were both smokers.  Pattishall and  coworkers (1985) reported
that children from homes with smokers (N = 20) had 4.1 times as high mean levels of serum
cotinine as children from nonsmoking families. Black children in the same study, however, had
lower values of Z (2.8) than did white children. Coultas and coworkers (1987) found that, among
600 U.S. children up to age  17 years, mean salivary cotinine levels were between 1.3 and 2.6 times
as high among subjects exposed to one cigarette smoker at home as among unexposed subjects,
and between 2.9 and 3.5 times as high among subjects exposed to two or more smokers at home as
among  subjects not exposed to cigarette smokers at home. Strachan and coworkers (1989) reported
separate results for 6-1/2- to 7-1/2-year-old Scottish children belonging to families living in their
own homes and for those belonging to families living in rented homes.  In the former, geometric
mean salivary cotinine was 6 times as high among subjects exposed to one cigarette smoker at
home as among unexposed subjects and  16 to 17 times as high among subjects exposed to two or
more smokers at home as among unexposed subjects.  For children belonging to families living in
rented  homes, the same ratios  were 3 to  5.5 times and 4 to 7 times, respectively.
       While  these studies show consistent relationships between mean body cotinine levels in
children and home smoker occupancy, there is also a wide variability in the estimated Z ratios,
ranging from  1+ to 17.  These  different estimates may have very important effects on the
background exposure adjustment and, thus, on the calculation of adjusted relative risks for
                                           8-6
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different studies (see also Chapter 6). For example, for a study in which the observed relative risk
(RR) is 2.0 but for which the Z ratio is 3, equation 8-1 can be solved for 0dN, which is the
estimated increase in relative risk for the group called "unexposed" but who in fact have been
exposed to  some recent ETS.  Solving, /3dN =1. Thus, the adjusted RR for the group identified as
"unexposed" would be 2, and the adjusted RR for an "exposed" group compared with a truly
unexposed  group would be 1 + (3*1) = 4, i.e., twice the observed risk. For a similar example
(observed RR = 2) but with Z = 5, 0dN = 0.3, the RR for a group identified as "unexposed" in this
case would be 1.3, and the adjusted RR for an "exposed" to a truly unexposed group would be
2.67. Finally, if the observed RR is still 2 but Z = 17, |3dN = 0.07, RR for "unexposed" would be
1.07 and the adjusted RR for exposed children would be 2.13. These results are shown in Table
8-1.
       These calculations show that when use of parental questionnaires significantly
underestimates their children's exposures to other sources of ETS (other than via the parental ETS)
and values of Z are lower (as found in black children by Pattishall and coworkers [1985], and in
children of lower socioeconomic status by Strachan and coworkers [1989]), the "true" RR of
children exposed to ETS may be considerably underestimated. But perhaps the most important
conclusion that may be derived from the above analysis is that exposure to ETS from sources other
than smoking parents may be high enough to constitute a significant risk for their health. This
may be particularly consequential for children of lower socioeconomic levels, whose nutritional
status, crowded conditions at home, and opportunity for contact with biological agents of disease
make them a part of the population that is particularly susceptible to respiratory illnesses during
infancy and childhood.  Available data show that ETS exposure via nonhousehold members in
these children, as measured by cotinine levels in body fluids, may be as much as one-third that of
children exposed to one smoking parent (Z = 3).  In the example presented above (observed
RR = 2), the estimate of the adjusted relative risk is 4 for children of smoking  parents to the truly
unexposed children.  However, using the same assumptions, children of nonsmoking parent? who
are exposed to ETS (at background levels found in some of the studies)  would have twice as high  a
risk of developing the illness under study as children truly unexposed to ETS.
       A cautionary note about the model is appropriate. Table 8-1 shows that, for observed
RR = 2 and Z = 3, the adjusted relative risk is 4.  However, as the observed RR and Z get closer
together* the  behavior of the model becomes erratic. This is shown in Table 8-2.  In fact, the
 model (equation 8-1) becomes undefined if Z is less than or equal to the observed RR, and it
 reaches some stability only as Z becomes at least 30% to 50% greater than the RR.          ,
                                             8-7
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 Table 8-1. Adjusted relative risks for "exposed children." Adjusted or background exposure based
 on body cotinine ratios between "exposed" and "unexposed" and equation 8-1

1.0
Observed
1.50
Relative
1.75
Risks
2.00
(RR) 2.50
3.00
1.50
1
-
-
-
-
-
Z Ratio of bodv cotinine levels 7"exoo$fedV"un£xttrtsad'»S
2.00
1
3.00
7.00
-
-
-
3.00
1
2.00
2.80
4.00
10.00
-
',"'1 5,00,
1
1.71
2.15
2.67
4.00
6.00
7.00 JO.OQ , 13.00
1
1.64
2.00
2.40
3.33
4.50
1
1.59
1.91
2.25
3.00
3.86
1
1.57
1.87
2.18
2.86
3.60
17.00
1
1.55
1.84
2.13
2.76
3.43
Table 8-2. Behavior variations in adjusted relative risks from equation 8-1 when the observed
relative risks and Z ratios are close together

Z ratio

1.50
Observed
1.75
Relative
2.00
Risks
2.25
(RR)
2.50
1.50
_

-3.5
-2.0

-1.5

-1.25
1,75
4.50

-
-6.00

-3.38

-2.50
2.00
3.00

7.00
_

-9.00

-5.00
2,25
2.50

4.38
10.00

_.

-12.50
2,50 2.75 \ 3.00 10,00
2.25

3.50
6.00

13.50

-
2.10

3.06
4.67

7.88

17.50
2.00

2.80
4.00

6.00

10.00
1.59

1.91
2.25

2.62

3.00
                                            8-8
-------
       Fortunately, the estimates of Z presented above are appreciably greater than the observed
relative risk estimates seen in Chapter 7, and in the observed range of both RR and Z, the model
yields relatively stable estimates of the adjusted RR.  Furthermore, as discussed in Chapter 6, the
values of RR and Z are expected  to be correlated for each study, i.e., the greater the Z ratio between
exposed and unexposed groups in each study, the greater should be the observed RR and the less the
effect of the (equation 8-1) adjustment.
        If the above model is correct, then exposure of children to ETS other than at home (parental
smoking)  may be an important risk factor for respiratory illness in childhood. On the other hand, it
is also possible that for at least some respiratory illnesses, outside exposure to ETS has relatively little
effect, either because outside exposures in younger children tend to be less than those of older
children or because there may be a threshold of exposure below which certain respiratory effects may
not be expected to occur. For this latter case, equation 8-1 is not an appropriate model, and the
observed  relative risk would be taken to be the true risk.  Both models are addressed in the sections
that follow.

8.4.  ASSESSMENT OF RISK
        Neither the NRC report (1986) nor the Surgeon General's report (U.S. DHHS, 1986)
attempted to assess the population or public health impact of the increased risk of respiratory
disorders in children attributable to ETS exposure. In this section, estimates will be derived for the
number of ETS-attributable lower respiratory tract infections in infants and for the induction and
exacerbation of childhood asthma.  Quantifying the public health impact of other conditions, such as
reduced lung function, coughing, wheezing, and middle ear effusion, is difficult, either because of
the  lack of overt symptoms or because some necessary U.S. population health statistics are not
available. Estimates of sudden infant death syndrome (SIDS) occurrences attributable to ETS will not
 be made  but will be discussed in Section 8.4.3.
        For the following quantitative analyses, estimates will be developed  in terms of ranges. The
 ranges are derived by the use of both threshold and nonthreshold (equation  8-1) models, different
 estimates for population incidence and prevalence, and estimated values of  Z and  RR from studies
 reviewed above. Various differences in design, disease definition, and conduct among these studies
 make them less adaptable to meta-analysis techniques than were the lung cancer studies. To the
 extent that a less rigorous statistical analysis is attempted here, the ranges should reflect that
 uncertainty.
                                              8-9
-------
 8.4.1. Asthma
        From the analysis of studies regarding risk for asthma and ETS exposure, it was concluded
 that passive smoking increases both the number and severity of episodes in asthmatic children.  It was
 further concluded that ETS is a risk factor for new cases among previously asymptomatic children,
 since the evidence is suggestive, but not conclusive, of a causal association (see Section 7.6). Relative
 risks for asthma ranged from 1.0 to 2.5 in the studies analyzed, but methodologies differed
 considerably among studies,  and effects were often found only in children of mothers who smoke
 heavily. Of the four large studies, totaling more than 9,000 children (Burchfield et al., 1986;
 Sherman et al., 1990; Weitzman et al., 1990; Martinez et al., 1991b), three showed statistically
 significant risk estimates ranging from 1.7 to 2.5, with the  two largest ratios, 2.5 (Martinez et al.,
 1991b) and 2.1 (Weitzman et al., 1990), coming from comparisons using children of heavily smoking
 mothers (£: 10 cig./day) as the exposed group. The third study (Burchfield et al., 1986) had OR = 1.7
 for males with two smoking parents, but results  were not significant either for girls or for children
 with one parental smoker.  The fourth study (Sherman et al., 1990) (770 children) did not find an
 effect, but made no  effort to assess the effect of heavy smoking  by parents,  nor was there control for
 socioeconomic status.  Thus,  assigning a range of 1.75 to 2.25 for the estimated relative risk of
 developing asthma for children of mothers who smoke 10 or more cigarettes per day appears
 reasonable and is within the ranges of observed risk.
       The above results suggest two possible scenarios.  One scenario is that relatively heavy
 exposure to ETS is needed  to bring on asthma, i.e., there  is a threshold of exposure below which
 effects will  not occur. Alternatively, lesser exposures may  merely induce fewer effects,  not
 detectable statistically with these study designs.  The choice of scenario does not affect the observed
 relative risk but will affect whether or not an adjustment for background exposure (Z ratio) is
 appropriate.  Under  the first  (threshold) scenario, the estimates of RR = 1.75 to 2.25 need no
 adjustment; under the alternative (nonthreshold) scenario, equation 8-1 applies.
       Considering the nonthreshold model  first, from the  discussion in Section 8.3, it can be
 assumed that values of 3 to 10 may be a reasonable range for estimates of Z (i.e., the ratio of body
 cotinine levels in children whose mothers smoke  heavily to  those of children whose mothers do not
smoke). Lower values of Z would yield significantly larger estimates of asthma cases attributable to
ETS. Based on the above estimates for a range of Z and RR and use of the nonthreshold model, the
estimated range of adjusted relative risks for children of mothers who smoke 10 or more cigarettes
per day would be approximately 1.91 to 6.00 (see Table 8-3). Transforming relative risks to
                                            8-10
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attributable risks (Rothman, 1986), 48% to 83% of all cases of asthma among children of mothers
who smoke 10 or more cigarettes per day may be attributable to passive smoking based on
                                        100*(1 -
(8-2)
where ARE is the attributable risk (%) for the exposed population.
       Under the assumptions of the threshold model, RR - 1.75 to 2.25 for children of heavily
smoking mothers, and the ARE - 43% to 56% (see Table 8-3); for children of light-smoking
mothers, RR - 1 and the ARE = 0.
       To calculate the percentage of all cases occurring in a mixed population of exposed and
unexposed individuals that is attributable to exposure (ART), knowledge of the prevalence of
mothers smoking 10 or more cigarettes per day is needed because
                                     ART = ARE*Pi
 (8-3)
where Pr is the proportion of cases that is exposed (Rothman, 1986). It has been reported that
approximately 26% of the population of women of childbearing age smoked in the United States
in 1988 (CDC, 1991b) and in 1990 (CDC, 1992b). For the number of cigarettes smoked, Weitzman
and coworkers (1990), using the 1981 National Health Information Survey (NHIS), found that
approximately 50% of smoking mothers of children ages 0 to 5 years smoke  10 or more cigarettes
per day. The 1990 NHIS reports that 78% of smoking women ages  18 to 44 smoke at least 10
cigarettes per day (data courtesy of Dr. Gary Giovino, CDC). We have used an average of 65% to
derive the estimates in Table 8-3.  Based on these figures and the threshold model, it can thus be
estimated that approximately 7% to 9% of all cases of asthma may be attributable to exposure to
ETS from  mothers who smoke 10 or more cigarettes per day.  Estimates of the prevalence of
asthma among U.S. children less than age 18 vary from 5% to 10% (Clark and Godfrey, 1983) to
3% to 8% (R. Evans et al., 1987), depending on disease definition. This latter paper uses the data
from the 1979-1981 NHIS and derives a population asthma prevalence of 2 million to 5 million.  A
more recent  estimate  from the 1989 NHIS is 3.9 million (U.S. DHHS,  1990b). Use of these
population prevalence figures and the threshold model provides a range of 8,000 to 26,000 as the
annual number of new cases of childhood asthma attributable to mothers who smoke 10 or more
cigarettes per day. The confidence in this estimate  is medium and is dependent on the conclusion
that ETS is a risk factor for asthma induction.
       If the nonthreshold model applies, use of the same prevalence figures leads to a range of
13,000  to 60,000 new cases per year attributable to all ETS exposures  (Table 8-3).
                                          8-12
-------
       While the range of 8,000 to 60,000 is plausible, the existing data are more supportive of
the threshold model, which assumes that rather heavy exposures to ETS are required to induce
asthma in previously asymptomatic children (Section 7.6.2). Thus, the range of 8,000 to 26,000
will be adopted as the more probable range of new cases among children per year attributable to
ETS exposure.
       In view of the increased number and severity of asthmatic episodes also caused by ETS,
the public health impact of ETS on asthmatic children is considerably greater than the range of
estimates for new cases presented above. Shephard (1992), after reviewing several studies,
concludes that ETS exposure (from any source) exacerbates preexisting asthma in approximately
20% of patients. If this figure is correct, up to 1 million asthmatic children could be affected.
Also, in an earlier study, O'Connell and Logan (1974) found that parental smoking aggravated
clinical symptoms of 67% of 265 asthmatic children in the Midwest versus 16% of 137 controls
(p < 0.0001) and that  10% of 400 asthmatic patients (of both smoking and nonsmoking parents)
considered  tobacco smoke a major aggravating factor. D. Evans and coworkers (1987) found that
passive smoking by asthmatic children in New York City (via presence of smokers in  the
household) was associated with a mean annual increase of 1.34 emergency room visits per year for
asthmatic symptoms, an increase of 63% over asthmatic children from nonsmoking households.
Ehrlich et al. (1992), in a study not reviewed by Shephard (1992), found that asthmatics with
clinically significant symptoms had both higher cotinine levels than controls (p = 0.04) and an
OR = 2.0 (p = 0.03) for maternal caregivers who smoke.  Using this estimate of 2.0 with
equation 8-1 and a Z = 3 also leads to an attributable risk fraction, ART, of 20% (equation 8-3).
Multiplying this 20% by the 2 million to 5 million asthmatic children in the United States yields
estimates of 400,000 to 1,000,000 whose condition  is aggravated by exposure to ETS.  Thus,
exposure to ETS in general and especially to parental ETS adversely affects hundreds of thousands
of asthmatic children.

8.4.2.  Lower Respiratory Illness
       From the assessment of available data (see Section 7.3), it was concluded that exposure of
infants and young children to ETS causes an increased incidence  of lower respiratory illness
(LRI).  An examination of the data in the referenced studies of both Tables 7-1 and 7-2 leads to
the conclusion that the observed risk of having LRIs is approximately 1.5 to 2.0 times as high in
young children whose mothers smoke as in those whose mothers do not smoke and that the risk  is
probably higher in infants than in toddlers.
       This estimate  is also consistent with that of the NRC (1986), which estimated a relative risk
of up to 2 for infants who have one or more parents who smoke.  The more recent evidence
                                           8-13
-------
reviewed here strongly suggests that the increased risk due to ETS exposure lasts for at least the
first 18 months and decreases after that. Based on this evidence, this chapter estimates a relative
risk range of 1.5 to 2.0 for infants and children up to 18 months old who have smoking mothers.
It will assume that the increased risk is zero after 18 months.
       Based on these findings, and following equation 8-1 with a range of Z = 3 to 10 and
RR « 1.5 to 2.0, the adjusted relative risk range becomes 1.6 to 4.0, and ARE takes the range 38%
to 75%.  As in the previous section, for equation 8-3, the mixed population attributable risk ART
takes the range 10% to 20%, again based on 1988 and 1990 estimates of approximately 26% women
of childbearing age who smoked (CDC, 1991b, 1992b).  Because the estimated mean number of
cigarettes smoked by these women is approximately 17 to 20 per day (CDC 1991b, 1992b), it is
reasonable  to assume that most children of smoking mothers will be exposed.  Therefore, the
proportion  of cases exposed, Pr, is estimated to be 0.26.
       It has recently been shown that the incidence of LRIs early in life is approximately 30%
(Wright et al., 1991). When the analysis is limited to the first 18 months of life, the population at
risk is approximately 5.5 million children.  A slight modification of the same algorithms described
above yields 150,000 to 300,000 cases of LRIs annually in children under 18 months old
attributable to exposure to ETS generated mostly by smoking mothers.  For RR = 1.5 and Z = 10,
the attributable risk fraction for the exposed population, ARE, is 0.38, and the attributable risk
fraction for the total population, AR, is 0.10.  Assuming 3,7 million children less than 1 year old
and a 30% incidence of LRI, the ETS-attributable population risk is 110,000. In order to get the
incidence rate for the 1.8 million children aged 12 to 18 months, also with 30% incidence, the
110,000 must be subtracted from the 540,000 before multiplying by 0.10.  The product of 43,000
is then added to 110,000 to determine the total annual incidence of 150,000 LRIs. For RR = 2.0
and Z - 3 the total annual incidence is about 300,000.  Approximately 5% of these LRIs require
admission to a hospital (Wright et al., 1989); therefore, it is estimated that 7,500 to 15,000
hospitalizations yearly for LRIs may be attributable to ETS exposure.
       While these estimates may appear large, three factors suggest that they are on the low side.
First, although these estimates are calculated only  for children less than 18 months old, Section 7.3
presents evidence that these ETS-attributed increased risks extend at a decreasing rate up to
3 years of age.  Second, no estimates have been calculated for exposure in a smoking father-
nonsmoking mother household.  Third, these numbers do not take into  account the fact that many
infants and young children have recurrent LRIs, and therefore, more than one episode of such
illnesses may be attributable to ETS in each exposed child.
                                           8-14
-------
8.4.3.  Sudden Infant Death Syndrome
       Because this report concludes that there is an association between maternal smoking and
SIDS but is unable to determine the contribution that ETS makes to that association (see Section
7.7), no estimate of ETS-attributable SIDS deaths will be calculated. The Centers for Disease
Control (CDC, 1991a) provides an estimate of 702 SIDS deaths attributable to maternal smoking,
based on a relative risk of 1.5 for infants of actively smoking mothers.  While this report concurs
with the numbers and the methodology used to determine that estimate, it is unable to apportion
the in utero, lactation, and ETS exposure components of the risk.

8.5.  CONCLUSIONS
       This chapter has attempted to estimate the impact on the U.S. population of ETS exposure
on childhood asthma and lower respiratory tract infections in young children.  For new cases of
asthma in previously asymptomatic children under 18 years of age, we estimate that 8,000 to
26,000 is a probable range of new cases per year that are attributable to ETS exposure from
mothers who smoke at least 10 cigarettes per day. The confidence in this range is medium and is
dependent on the conclusion that ETS is a risk factor for asthma induction.
       While the data are most supportive of a situation in which heavy exposures to ETS are
required to induce new cases of asthma, two other scenarios would lead to larger estimates.  The
first is that even in the  absence of smoking mothers, a child could receive heavy ETS exposure
from other sources.  The second is that lesser ETS exposures induce fewer numbers of new cases,
and the increase is not statistically detectable.  Under this latter (nonthreshold) scenario, the range
of new cases of asthma annually attributable to ETS exposure is 13,000 to 60,000.
       This report concludes that, in addition to inducing new cases of asthma, ETS exposure
increases the number and severity of episodes among this country's 2 million to 5 million
asthmatic children.  This chapter considers exposure to parental smoking to be a major
aggravating factor to approximately 10%, or 200,000,  asthmatic children.  Estimates of the number
of asthmatics whose condition is aggravated  to some degree by ETS exposure are very approximate
but could run well over 1 million.
       This chapter also estimates that 150,000 to 300,000 cases annually of lower respiratory
tract infections in children up to 18  months old are attributable to ETS exposure, most of which
comes from smoking parents (mostly mothers).  These ETS-attributable cases are estimated to
result in 7,500 to 15,000 hospitalizations annually.  Confidence in these estimates is high based on
the conclusion of a causal association and the strong validity of parental smoking as a surrogate of
temporally relevant ETS exposure in infants and young children. Additional cases and
                                           8-15
-------
hospitalizations are expected to occur in children up to 3 years old in decreasing numbers, but this
report makes no further quantitative estimates.
       Infants' exposure to ETS may also be responsible for a portion of the more than 700 deaths
from SIDS attributable to maternal smoking by the CDC (199la), but this report is unable to
determine whether and to what extent these deaths can be attributed specifically to ETS exposure.
       The estimates of population impact presented above are given in ranges and approximate
values to reflect the uncertainty of extrapolating from individual studies to the population.  As
with the lung cancer population impact assessment (Chapter 6), these extrapolations are all based
on human studies conducted at true environmental levels. Therefore, they suffer from none of
the uncertainties associated with either animal-to-human or high-to-low exposure extrapolations.
       In addition to the estimates presented above, ETS exposure in children also leads to
reduced lung function, increased symptoms of respiratory irritation, and increased prevalence  of
middle ear effusion, but this report does not provide estimates  of the population impact of ETS
exposure for these conditions.
                                           8-16
-------
                         ADDENDUM:  PERTINENT NEW STUDIES






       Several pertinent studies on the respiratory health effects of passive smoking have




appeared since the cutoff date for inclusion in this report.  The studies are cited here for the



benefit of anyone who may wish to follow up on these topics.  The studies are briefly described



below, and the authors' conclusions are presented. We do not formally review these studies in this



report, and the citations do not represent a full literature search. These new studies are generally




consistent with this report's conclusions that environmental tobacco smoke (ETS) exposure




increases the risk of lung cancer in nonsmokers and affects the respiratory health of infants.



       Two of the new studies are case-control studies of ETS and lung cancer in U.S. female




nonsmokers (Stockwell et al.,  1992; Brownson et al., 1992).  Stockwell et al. conclude that "long-




term exposure to [ETS] increases the risk of lung cancer in  women who have never smoked."



Similarly, Brownson et al. conclude, "Ours and other recent studies suggest a small but consistent



increased risk of lung cancer from passive smoking."




       In an autopsy study of Greeks who had died of causes other than respiratory diseases,



Trichopoulos et al. (1992) found an increase in "epithelial, possibly precancerous, lesions" in the



lungs of nonsmoking women who were married to smokers.  The authors concluded that their




results "provide support to the body of evidence linking passive smoking to lung cancer.  . . ." In a




fourth study, a case-control study of ETS exposure and lung cancer in  dogs, Reif et al. (1992)



found an association between lung cancer and exposure to a smoker in  the home for breeds with



short- and medium-length noses.  These results are not statistically significant, and the authors



characterize their findings as "inconclusive."



       Finally, Schoendorf and Kiely (1992) conducted a case-control  analysis of sudden infant




death syndrome (SIDS) and maternal smoking status (i.e., maternal smoking both during and after



pregnancy [combined exposure], maternal smoking only after pregnancy [passive exposure], and



no maternal smoking).  These investigators conclude that their data "suggest that both intrauterine



and passive tobacco exposure  are associated with an increased risk of SIDS."




                                          ADD-1
-------
ADDENDUM REFERENCES

Brownson, R.C.; Alavanja, M.C.; Hock, E.T.; Loy, T.S. (1992) Passive smoking and lung cancer in
       nonsmoking women. Am. J. Public Health 82:1525-1530.

Reif, J.S.; Dunn, K.; Ogilvie, G.K.; Harris, C.K. (1992) Passive smoking and canine lung cancer
       risk. Am. J. Epidemiol. 135:234-239.

Schoendorf, K.C.; Kiely, J.L. (1992) Relationship of sudden infant death syndrome to maternal
       smoking during and after pregnancy. Pediatrics 90:905-908.

Stockwell, H.G.; Goldman, A.L.; Lyman, G.H.; Noss, C.I.; Armstrong, A.W.; Pinkham, P.A.;
       Candelora, E.G.; Brusa, M.R. (1992) Environmental tobacco smoke and lung cancer risk in
       nonsmoking women. J. Natl. Cancer Inst. 84:1417-1422.

Trichopoulos, D.; Mollo, F.; Tomatis, L.; Agapitos, E.; Delsedime, L.; Zavitsanos, X.; Kalandidi,
       A.; Katsouyanni, K.; Riboli, E.; Saracci, R. (1992) Active and passive smoking and
       pathological indicators of lung cancer risk in an autopsy study. JAMA 268:1697-1701.
                                         ADD-2
-------
                  APPENDIX A






REVIEWS AND TIER ASSIGNMENTS FOR EPIDEMIOLOGIC




        STUDIES OF ETS AND LUNG CANCER
-------
-------
                 APPENDIX A. REVIEWS AND TIER ASSIGNMENTS FOR
                 EPIDEMIOLOGIC STUDIES OF ETS AND LUNG CANCER

A.l. INTRODUCTION
       This appendix contains material that is used in Section 5.5, entitled Analysis by Tier and
Country. As described in that section, each study is individually reviewed and assigned to one of
four tiers based on its assessed utility for the objective of evaluating the evidence of an
association between environmental tobacco smoke (ETS) exposure and incidence of lung cancer.
The means of constructing study reviews is described in the next section, followed by a
description of the scheme for scoring studies on various items and then assigning the studies to
tiers according to the outcome.  The final section of this appendix contains the individual study
reviews and the tier numbers assigned to them.

A.2. CONSTRUCTION OF INDIVIDUAL STUDY REVIEWS
       Descriptions of the four prospective cohort studies are individualized according to the
requirements of each study.  Reviews of case-control studies follow a structured format,
consisting of three parts:  (1) the author's abstract, which summarizes the most salient features and
conclusions in the author's opinion; (2) a study description based on the contents of a completed
study form designed around principles of good epidemiologic practice and issues  specific to
environmental tobacco smoke; and (3) a section of comments related to evaluation and
interpretation of the study.  The study reviews are used to assign studies to tiers according to the
procedure described in Section A.3.
       The review form for case-control studies shown in Section A.2.1 was completed for each
case-control study in order to systematically extract information about characteristics of interest
for preparation of the reviews.  The form was an aid in treating study reviews uniformly and
noting  omissions or incomplete discussion on issues that may affect the potential for bias or
confounding.
       The study descriptions in Section A.4 were then prepared by following the outline and
information in the completed forms.  Some items included in the form pertain to  characteristics
that would apply to a case-control study on any  topic, i.e., they are "generic items" related to
principles of good epidemiologic investigation; the remaining items tend to identify areas of
potential bias specific to the topic of ETS and lung cancer.
                                           A-l
-------
A.2.1.  Review Form for Case Control Studies
PARTI. GENERAL
       Study name	
       Location	
       Time period (data collection).
       Study objective(s)	
       The source of the primary data set is the current study
                    or a parent study
              containing CS (current)	FS (former)	NS (never-smoker)
       Study uses term "nonsmoker"	or "never-smoker"	to mean
              nonsmoker	
              never-smoker
       "Exposed" to ETS means (preferably in terms of spousal smoking)
       Recall span (how far back in time ETS exposure was measured).
       ETS sources include cigarette
cigar
pipe
                             other
       Describe inclusion of nonsmoking (never-smoking) females not currently married (number
       of cases and controls, assumptions regarding exposure)
                                          A-2
-------
II. DATA COLLECTION (includes NS_
       Inclusion/exclusion criteria
              Cases	
           FS
        CS
unless noted)
              Controls (include matching variables in PART V)_
       Main source of subjects
              Hospital(s) #	
              Community
              Other__	
       Incident cases   Y	
       Control sampling
              Cumulative  	
              Unmatched   	
       Method of collection
              Face-to-face
              Telephone
              Self-admin, ques.
              Medical records
              Vital stat. records
              Other
                     Controls
 N
       Density
       Matched
Cases
Controls
       Collected data verified/corroborated with other sources  Y_
                                                Cases
       Sample size
       (prior to attrition)
              females
                                     N
                                   Controls
       Attrition
       (selection or followup)
             females
             males
                                           A-3
-------
      Source of response
            subject
            proxy
      Exposure sources  NS_
      Age
Childhood
Adulthood
  Spouse
  Parents/in-laws
  Other family/
       live-ins
Workplace
Other
NS        FS
             Distribution
                    _FS_
                    Yes
CS
                                   CS
                            Cases
                                                                   Controls
             Mean
             Standard error
             Standard deviation
             Range

PART III. CLINICAL DATA
       Primary lung cancer verified by
             Histology            	
             Cytology            	
             Radiology/clinical    	
             Death certificate     	
             Tumor registry       	
             Mortality records     	
             Other	    _
              Not verified
                                   NS
            FS
CS
       Airway proximity (no. exp cases/no, cases)
                                          NS
                   FS
                                                                         CS
-------
             Central
             Peripheral
       Tumor type (no. exp cases/no, cases)
             Squamous cell        	
             Small cell
             Adenocarcinoma
             Large cell
             Others or unspecified
PART IV. STATISTICAL ANALYSIS  (includes NS_

       Raw data (for analysis)
             females
              males
unexp

exp

unexp

exp
                                                      Table
                           NS
                                                      Table
                           FS
              Comments (include measure of exposure)    Table

       Unadjusted (crude) analysis

              Estimate      OR _	% CI (	

              Comments                               Table

              Test of       p-value   •••	
               signif.

              Test for       p-value	
               trend

              Comments                               Table

       Adjusted analysis

              Estimate      OR	% CI (
FS
CS
CS
unless noted)
                                        Controls
                                          A-5
-------
              Test of
                signif.
p-value
              Test for
                trend

              Comments •
p-value
                           Table
 PART V. DEPENDENT VARIABLES (potential confounders and effects modifiers considered)
                  In Matching
 Age
 Gender
 Race/ethnicity
 Hospital
 Residence/
  neighborhood
 Housing type
 House/room sizes
 Vital statistics
 Smoking status
 SES
 Medical health
 Menstrual/
  reproductive
 Occupation
 Outdoor air
  pollution
 Cooking habits
 Drinking
 Diet
 Education
 Family history
  of lung cancer
 Other indoor
  smoke/fumes
 Radon
 Lifestyle
 Climate/
  ventilation
           In Analysis
Otherwise
A.3. TIER CLASSIFICATION SCHEME

       The items and study scores used in the algorithm to calculate tier numbers are given in

Table A-l. The items and scoring system in that table and the algorithm for converting the scores
to a tier number are the topics of this section.

       The items displayed in the headings of Table A-l will be described after explanation of

how assignments are calculated from the numbers in that table.  Positive values in the table are
                                          A-6
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unfavorable (penalty points); a blank entry means the item was not a problem; negative values are
favorable (bonus points) and occur in a few instances where the study performed well above the
norm indicated by a blank, e.g., FONT, KOO, and HOLE(Coh) each have an entry of "-0.5" under
"Less than 90% confirmation by histology or cytology" in Category C for particularly high
attention given to confirming primary lung cancer in subjects classified as cases. Bonus scores are
always -0.5 and are assigned somewhat sparingly as they have the potential to cancel penalty
scores and thus mask a study weakness.  Parentheses around an entry indicate that the penalty
points were assigned due to  insufficient information (so there is effectively a penalty imposed if
the information needed was not included in the source). The asterisk that occurs under the item
"unsuitable indoor environment" is a marker  that automatically places the study into Tier 4 under
the assignment rule to be described next (the unsuitable environment refers to high levels of coal
smoke in all instances).
       Tier numbers for each study are calculated from the entries in  Table A-l as follows.
Totals are calculated by category and across all items, as shown in Table A-2. If the total for each
category is less than 2.5, then the  tier assignment is determined as follows:
                     Total Score
                     1.75 or less
                     2.00 - 3.75
                     4.00 - 5.75
                     6.00 or greater
Tier
  1
  2
  3
  4
The value 2.5 is designated as a cutoff point for each category.  If a study has one or more
category totals greater than or equal to 2.5, the tier classification is increased by 1 (i.e., 1 is added
to the tier number shown in the above table if any category totals are 2.5 or greater). The three
studies conducted in regions of China where indoor air is heavily polluted with smoke from
burning coal, denoted by an asterisk under item "unsuitable indoor environment," are .placed in
Tier 4 (see reviews in Section A.4 for GENG, LIU, and WUWI). The resultant assignment of
studies to tiers is shown in Table A-2.
       A scheme that attempts to assess utility and to numerically rank studies accordingly, as
done here, has a high degree of subjectivity.  Different analysts would be apt to disagree about
elements of any such approach and the appropriate weights for those elements in assigning studies
to tiers, as suggested above.  One of the difficulties is that the significance of a study "weakness"
is difficult to assess. For example, the use of proxy respondents may be a source of bias, but the
direction and magnitude of bias are unknown for any given study.  Thus, one is faced with rating
studies largely on the basis of one's ability to ascertain what study features are significant and
                                            A-7
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Table A-l.  Study scores for tier assignments
  Study
                       Category A
                                        x  Category B
Fanner,
sniokers
Included
Smoking
status
unverified
Exposure
criteria,"^
questionable
Exposure
of
unraarrieds
Exposure
status
unverified
  AKIB
  BROW
  BUFF
  CHAN
  CORR
  FONT
  GAO
  GARF
  GENG
  HUMB
  INOU
  JANE
  KABA
  KALA
  KOO
  LAMT
  LAMW
  LEE
  LIU
  PERS
  SHIM
  SOBU
  SVEN
  TRIG
  WU
  WUWI
  BUTL(Coh)
  GARF(Coh)
  HIRA(Coh)
  HOLE(Coh)
              -0.5
1
0.5
1

0.5
0.5
              -0.5
0.5
                            1
                            1.5
                            2
              1.5
              0.5
              1

              1

              1
                                                        -0.5
(0.5)

(0.5)
0.5

0.5
0.5
                                          -0.5
                                          0.5
                                                       (continued on the following page)
                                        A-8
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Table A-l. (continued)
CateaorvC Cateemrv r> 11
Secondary
lung cancers
Study possible
AKIB
BROW
BUFF
CHAN 0.75
CORR
FONT
GAO
GARF
GENG
HUMB
INOU 0.75
JANE
KABA
KALA
KOO
LAMT
LAMW
LEE 0.75
LIU 0.75
PERS
SHIM
SOBU
SVEN
TRIG
WU
WUWI
BUTL(Coh)
GARF(Coh) 0.5
HIRA(Coh) (0.5)
HOLE(Coh) (0.5)
Less than Less than
90% confirm. 90% faee-
histol./cytol. to-face
l 0.5


0.5
-0.5
0.5

0.5
(0.5)

0.5
-0.5

(0.5)
1
0.5
0.5
0.5
1
1
1
0.5
0.5
1 0.5
0.5
-0.5
UnfaJinded
interviews




(0.5)
(0.5)
(0.5)


(0.5)
0.5

(0.5)

(0.5)
0.5


(0.5)
(0.5)
0.5
0.5
0.5
0.5




                                                         (continued on the following page)
                                         A-9
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Table A-l. (continued)
                                                               Category F
                                                        >-     (Cohort Only)
                                                     Change in      ',  More than
                                                 '  " smoking ot
                                                     EfS status
Uneven proxy
response
distribution
  More than
  10% proxy
"  respondents
   BUTL(Coh)
   GARF(Coh)
   HIRA(Coh)
   HOLEfCoh
                                                         (continued on the following page)
                                          A-10
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Table A-l. (continued)
 Study
 AKIB
 BROW
 BUFF
 CHAN
 CORR
 FONT
 GAO
 GARF
 GENG
 HUMB
 INOU
 JANE
 KABA
 KALA
 KOO
 LAMT
 LAMW
 LEE
 LIU
 PERS
 SHIM
 SOBU
 SVEN
 TRIG
 WU
 WUWI
 BUTL(Coh)
 GARF(Coh)
 HIRA(Coh)
 HOLE(Coh)
                                               Category G
Unsuitable
indoor
environment
 (Case-control only)
Smoking-refated
-disease in
controls ,
                       0.75
                       0.75
                       0.75
Nonincident
cases
included
0.5
(0.5)
                         0.5


                         (0.5)


                         (0.5)
                      0.75
                      0.75
                      0.5
                        (0.5)
                                                        (continued on the following page)
                                        A-ll
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Table A-l. (continued)
                                          Category H
                                                               Prob!e»(s)
                                                               with stat methods
Uncontrolled for
other factors
Uncontrolled
for age
  AKIB
  BROW
  BUFF
  CHAN
  CORR
  FONT
  GAO
  GARF
  GENG
  HUMB
  INOU
  JANE
  KABA
  KALA
  KOO
  LAMT
  LAMW
  LEE
  LIU
  PERS
  SHIM
  SOBU
  SVEN
  TRIG
  WU
  WUWI
  BUTL(Coh)
   GARF(Coh)
   HIRA(Coh)
   HOLE(Coh)
                                        A-12
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Table A-2. Total scores and tier assignment
Cateaorv
Study A
AKIB
BROW
BUFF
CHAN
CORR
FONT -0.5
GAO
GARF
GENG 1
HUMB 0.5
INOU 1
JANE
KABA 0.5
KALA
KOO
LAMT 0.5
LAMW
LEE
LIU
PERS -0.5
SHIM
SOBU
SVEN
TRIG 1
WU
WUWI 1
BUTL(Coh)
GARF(Coh)
B CD
-0.5 1 0.5
1.5
1.5
2.5 1.25
0.5 0.5
-0.5 -0.5 0.5
1.5 0.5 0.5
1
1
0.5
1 1.25 0.5
0.5
1
0.5 0.5
-0.5

0.5
1.25 0.5
1 1.75
0.5
1
1
1.5
1 0.5
0.5 1.5
0.5 0.5
0.5
1 1.5 0.5
B F G H
1 0.5
1.75 0.5 2.0
1 1.5
0.75 0.75 1.5
0.5 0.5 1.5
0.5 0.5
1.5
1.5 1.25
* 2.5
1.75
1 1.25
0.5 1
1.5

1
1.5
2.5
0.5
* 2.5
0.5
1.25 1.5
0.75 1
0.5
1.5
1
* 1.
0.5 1
1.25
Total
2.5
5.75
4.0
6.75
3.5
0
4.0
3.75
4.5
2.75
6.0
2.0
3.0
1.0
0.5
2.0
3.0
2.25
5.25
0.5
3.75
2.75
2.0
4.0
3.0
3.0
2.0
4.25
Tier
Assign.
2
3
3
4
2
1
3
2
4
2
4
2
2
1
1
2
3
2
4
1
2
2
2
3
2
4
2
3
                                                         (continued on the following page)
                                         A-13
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Table A-2.  (continued)



Study
HIRA(Coh)
HOLE(Coh)
	 Catesorv

V S <* ., if % * !••* vf ivyy -- ^ J f f
A i C D E F ^ G H Total
0.5 1 0.5 2.0
1 1.0

ff f/f
Tier
Assign.
••••••••
2
1
*Unsuitable indoor environment

some quantitative construct reflecting an opinion of their relative importance.  Additionally, there
is the possibility of misinterpreting the source or of the omission of needed information from the
source. A further limitation is the inability to include all features of all studies that might affect
one's judgment of it.
       Reservations notwithstanding, the heterogeneity of the ETS studies in objectives and
characteristics of design, data collection, analysis, and interpretation make it worthwhile to
classify studies according to some evaluation of their utility for assessing ETS and lung cancer.
The items used for scoring studies are described in the remainder of this section. The descriptions
are written in the language of case-control studies (references to "cases," "controls," etc.).  Where
cohort studies are evaluated (end of Table A-l), the equivalent concept for cohort studies is
applied under each category heading, with exceptions as noted in the text. An "ideal" is described
for each item, to give the scores a reference point. The ideal applies to the needs of this report,
however, and not to what may have been the ideal for the individual study objectives.
        Very few of the studies were designed and executed with the sole, or even primary,
objective of this report. Consequently, high penalty  scores or an unfavorable tier assignment
indicating limited utility for our objectives should not be interpreted as low study quality relative
to the purpose for which the study was conducted. Comments included on the likely direction of
bias refer to bias of the relative risk estimate.  "Upward bias" is an expected excess in the observed
relative risk above its true (but unknown) value (which is 1.0 if the null hypothesis of no effect is
correct).  "Downward bias"  refers to bias in the opposite direction. "Bias toward the null
hypothesis" is used sometimes in the text. It refers to an influence on the observed relative risk
toward 1.0, the value of the true relative risk when the null hypothesis is correct. When the true
relative risk exceeds 1, "bias toward the null" and "downward bias" are interchangeable.  The
probable magnitude of bias is more difficult to ascertain than the likely direction of bias.  The
                                             A-14
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relative values of the penalty scores under items in Table A-l reflect our judgment on this issue.
To determine why a specific study was scored with penalty or bonus points on any particular item,
the reader needs to refer to the review of that study in Section A.4.  A description of items in
Table A-l follows.

Category A: Never-Smoker Status
       •   Inclusion of former smokers. The ideal is for all subjects to be true never-smokers.
           Inclusion of subjects who report themselves as never-smokers but who are actually
           current smokers causes an upward bias in the relative risk (see Section 5.2.2 and
           Appendix B). Inclusion of former smokers may be a source of upward bias by similar
           arguments.  Some degree of  former smoking may be inconsequential depending on
           how much was smoked and the subsequent duration of abstinence, but this
           relationship is not well understood. Penalty points of 0.5 or 1 were assigned to studies
           that allowed some prior smoking because we view it as adding some degree of
           uncertainty compared with exclusive use of never-smokers as subjects.
       •   Verification of smoking status. The ideal  is to implement all means available to verify
           the never-smoking status claimed by subjects. No  studies were penalized on this item,
           but the few studies (i.e., FONT and PERS) that conducted thorough verification were
           given a bonus of -0.5.
Category B:  ETS-Exoosure Criteria
       •   Exposure criteria questionable. The ideal is for a female to be classified as ETS
           exposed according to a measure of duration (e.g., years of spousal smoking) and a
           measure of intensity (e.g., number of cigarettes smoked per day by the spouse). Of
           course, collecting data on measures of exposure is not meaningful unless it enters into
           the analysis.  For the purpose of this report, the objective for case-control studies is to
           differentiate between subjects as sharply as possible on exposure to ETS using spousal
           smoking as an indicator. Knowledge is too limited to know how to accomplish this
           exactly, but extremes wherein the exposed group contains subjects with very little
           exposure or includes only subjects with very high exposure (while all lesser exposed
           subjects are classified as "unexposed") should bias results toward the null hypothesis.
           For cohort studies, GARF(Coh)  was penalized  because the duration of exposure to
           spousal ETS was limited.
       •   Exposure of unmarrieds. Ideally for this report, where the presence or absence of
           spousal smoking is emphasized as the main determinant of ETS exposure because of its
                                           A-15
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           high commonality among studies, subjects would be female never-smokers whose
           history of exposure to spousal smoke has been reasonably constant over an extended
           duration (independent of whether a subject may have been married more than once).
           Studies vary in the extent to which this topic is considered and how it is handled, and
           assumptions may need to be considered in view of a country's social practices. For
           example, some studies classify women as unexposed to ETS while unmarried,  which
           may be more reasonable in some cultures than others (e.g., probably more reasonable
           in Greece than in the United States).  Biases resulting from this item are most
           commonly toward the null hypothesis.                                      ,
       •   Verification of exposure status.  The ideal is to verify statements regarding present
           and past exposure to ETS from spousal smoking from other sources. Two studies,
           AKIB and FONT, were given bonus points for extended efforts in  that direction; no
           studies were penalized.

Category C: Lung Cancer Indication
       •   Secondary lung cancers possible.  The ideal is assurance that all cases are accurately
           diagnosed with primary lung cancer and that cases are not included where the lung
           cancer may be secondary to another site.  This item is closely related to the next one,
           which is concerned with the method of diagnosis/confirmation. Bias is toward the
           null hypothesis.
       •   Less than  90% confirmation by histology or cytology.  The ideal is that the original
           diagnosis of lung cancer, or a confirmation of it, is conducted by histology.  No
           penalty points are assigned, however,  if at least 90% of the cases are diagnosed or
           confirmed by histology or cytology. Three studies, FONT, KOO, and HOLE(Coh),
           were given bonus points for extended efforts in diagnostic confirmation.  The
           direction of bias is toward the null hypothesis.

Category P: Interview Type
       •   Less than 90% face-to-face interview. The ideal interviewing technique is face-to-
           face by trained interviewers. The effect on the quality of information from other
           types of data collection is unclear, but telephone interviews and mail-in questionnaires
           probably increase the rate of misclassification of subject information.  The bias is
           toward the null hypothesis if the proportion of interviews by type is the same  for cases
           and controls, and of indeterminate direction otherwise.
                                           A-16
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       •   Unblinded (case-control studies only). The ideal is for the interviewer to be unaware
           whether the subject is among the cases or controls and the subject to be unaware of
           the purpose and intended use of the information collected.  Blinding of the
           interviewer is generally not possible in a face-to-face interview.  In face-to-face and
           telephone interviews, potential bias may arise from the investigator's expectations
           regarding the relationship between ETS exposure and lung cancer incidence. The
           potential for bias is probably less with mail-in interviews.

Category E: Proxy Respondents
       •   More than 10% proxy respondents (10% of total for cohort studies and  10% of either
           total cases or total controls for case-control studies). The ideal is for data to be
           supplied by the subject because the subject generally would be expected to be the
           most reliable source. A subject may be either deceased or too ill to participate,
           however, making the use of proxy responses unavoidable if those subjects are to be
           included  in the study (some studies appeared to exclude them).  The direction and
           magnitude of bias from use of proxies is unclear, and may be inconsistent across
           studies.
       •   Uneven distribution between cancer/noncancer subjects.  Ideally, the use of proxies is
           evenly distributed between cases and controls because this might be expected to
           minimize any net bias remaining from the use of proxy responses. The use of proxies
           is often much higher for cases than for controls, as one might expect. The effect of
           proxy distribution on bias is indeterminate.

Category F: Followup (Cohort Studies Only)
       •   Changes in smoking or ETS exposure not addressed.  The ideal is for any changes in
           personal smoking status or exposure to spousal ETS to be  recorded and taken into
           account in the analysis. If a subject begins active smoking during the course of the
           study, it may  lead to upward bias (from arguments like those given for the effect of
           smokers who misreport themselves as never-smokers, as discussed in Section 5.2.2 and
           Appendix B); if the smoking status of the spouse changes, the likely bias would be
           toward the null hypothesis.
       •   More than 10% loss to followup. The ideal, of course, is zero loss to followup. The
           ideal is not achievable in practice, but it seems reasonable to expect  loss to followup
           not to exceed  10%. The bias from loss to followup is indeterminate.  Random loss may
                                           A-17
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           have less effect than if subjects who are not followed up have some significant
           characteristics in common.
Category G: Design Issues
           Unsuitable indoor environment.  The ideal indoor air environment contains no
           significant sources of pollution from nontobacco sources that likely contain one or
           more of the known or suspected carcinogens identified in tobacco smoke or would
           otherwise be expected to increase the incidence of lung cancer. The presence of high
           concentrations of indoor smoke from unvented or inadequately vented indoor
           combustion of coal for purposes of warmth or cooking is commonplace in some
           regions of China where studies were conducted. This condition is indicated in some
           studies and has been confirmed from other sources (see reviews in Section A.4 for
           GENG, LIU, and WUWI). It is expected that indoor coal smoke increases the level
           and variability of exposure to many of the same carcinogenic agents that occur in ETS,
           and therefore detection of an incremental increase in lung cancer incidence from ETS
           would be highly unlikely in such a setting.
           Smoking-related disease in controls (case-control studies only). The ideal is for
           controls to be free of any disease related to tobacco smoke. This is an issue in some
           studies where hospital controls are  used. Potential bias is toward the null hypothesis.
           Nonincident cases included (case-control studies only).  The ideal is for all cases to be
           incident (i.e., new cases  that develop during an interval of time). A few studies began
           with prevalent cases and then proceeded with incident cases.  The use of prevalent
           cases may introduce some bias of unknown direction because prevalence is affected by
           survival rate and lung cancer patients generally do not survive for an extended period.
           All studies scored on this item were given one-half point,  which is in parentheses in
           most instances, indicating that information in the source is incomplete.  Interview
           information must be obtained from surviving kin or other proxy subjects as well, but
           that issue is treated separately in  a  following item. Potential bias is of uncertain
           direction.
Category H: Analysis Issues
           Uncontrolled for age. The ideal is to control for age by matching on age in the design
           and then adjusting for age in the analysis of data.  There is no clear formula for
           deciding which variables should be included in a matched analysis, and/or addressed
           in the analysis of the data collected. Age, however, is likely correlated with total
                                           A-18
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           exposure for those classified as exposed to ETS and is suspected of playing a role in
           cancer etiology.  The potential bias from age might be significant, but its likely
           direction and magnitude depend in an unknown way on the disparity of age
           distributions between cases and controls.
       •   Uncontrolled for other factors of importance.  This item applies to studies that report
           an increased association of lung cancer with factors other than ETS exposure but do
           not consider further whether these factors may be confounders that should be
           controlled for in the analysis for ETS.  For a variable to be a confounder of ETS,
           exposure to  the variable and to ETS must be correlated (which determines the degree
           of confounding), and the association of the factor with lung cancer must be causal.
           The correlation should be readily calculable from the study data. Conclusions about
           causation may not  be warranted, but one could still make the necessary calculations
           under the assumptions  that they are causative and then report what implications
           causation (if correct) would have for the assessment of ETS.  The expected effect from
           controlling for confounders is  to move the estimated relative risk closer to the true
           value.
       •   Problem(s) with statistical methods. The ideal is that conclusions are drawn from the
           application of statistical methods that are appropriate to the problem and accurately
           interpreted.  One penalty point was assigned studies where we  took issue with the
           statistical methodology or results. The direction of bias is indeterminate, in general, as
           the situations differ between studies.

A.4. INDIVIDUAL STUDY REVIEWS
       This section of Appendix A contains a review  of each epidemiologic study based on the
primary references listed in Table  5-1. Descriptions of the four prospective cohort studies are
individualized according to the requirements of each study—for example,  HIRA(Coh) has a long
history of controversy in the literature, so the main arguments are chronicled and discussed as part
of the review.  As noted previously, reviews of case-control studies follow a structured format,
consisting of three parts: (1) the author's abstract, which summarizes the most salient features and
conclusions in the author's opinion; (2) a study description based on the contents of a completed
study format designed around  principles of good epidemiologic practice and features specific to
ETS; and (3) a section of comments related to evaluation and interpretation of  the study.  The
author's abstract is, of course,  entirely the author's own words; the study description is intended to
portray accurately the reference article vis-a-vis items in the study format, so  the author's words
                                            A-19
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are used when possible; the comments section is entirely our own assessment of characteristics
relevant to study interpretation and utility in this report.
       An abstract only is available for the case-control study by Stockwell et al., (1991), referred
to as STOC, which has not appeared in print yet. There is insufficient information on the study to
include it in the main body of this report.  Similarly, an abstract only is available for the second
study of Kabat and Wynder (Kabat, 1990), which is included in an addendum following the
review of their first study, KABA. The data for many of the studies reviewed have been
extracted from a larger, more comprehensive study that includes active smokers.  The subjects and
their data used for investigation of an association between ETS exposure and lung cancer
incidence are referred to as "ETS subjects" and "ETS data," respectively.

A.4.1. AKIB(Tier2)
A.4.1.1.  Author's Abstract
       "A case-control study conducted in Hiroshima and Nagasaki, Japan, revealed a 50%
increased risk of lung cancer among nonsmoking women whose husbands smoked. The risks
tended to increase with amount smoked by the husband, being highest among women who worked
outside the home and whose husbands were heavy smokers, and to decrease with cessation of
exposure. The findings provide incentive for further evaluation of the relationship between
passive smoking and cancer among nonsmokers."

A.4.1.2.  Study Description
       This community-based case-control study was conducted in Hiroshima and Nagasaki,
Japan, in 1982. The data collected on passive smoking are part of a larger investigation of lung
cancer among atomic bomb survivors, the principal objective of which is to evaluate the
interactive roles of cigarette smoking and ionizing radiation. This article reports on married
female never-smokers, an unmatched subset of the data from the whole study.
       The whole study includes a total of 525 primary lung cancer cases diagnosed between 1971
and 1980. Cases were identified from the Hiroshima and Nagasaki Tumor and Tissue Registries
and other records.  Controls were selected from among the cohort members without lung cancer,
two per case in Hiroshima and three per case in Nagasaki.  The controls were individually
matched  to the cases with respect to year of birth (±2 years), city of residence (Hiroshima or
Nagasaki), sex,  biennial medical examinations, and vital status. The majority of cases were
deceased; those cases were matched to decedent controls by year of death (±3 years), in addition
to the other criteria. Controls were selected from causes of death other than cancer and chronic
                                           A-20
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respiratory disease.  Face-to-face interviews were conducted for 81% (82%) of the eligible cases
(controls), but 80% to 85% of the interviews for both cases and controls were actually conducted
with the subject's next of kin.  The mean age of cases at diagnosis is 72.1 years (range 36-94) for
males and 70.2 (range 35-95) for females, which is high for lung cancer in Japan.  Fifty-seven
percent of the cases were pathologically confirmed; the remaining 43% were diagnosed by
radiological or clinical findings.
       ETS exposure in adulthood was assessed by spousal smoking status, including the average
number of cigarettes smoked per day, age the spouse started smoking, and, for those who stopped
smoking, the  age at cessation. For childhood exposure, a single question was asked regarding
whether the subject's mother or father or both smoked when the subject was living at home as a
child; responses were obtained for only two-thirds of the subjects. No specific information on
exposure to smoking by other household members' smoking or to smoking in the workplace was
obtained.  ETS exposure data were checked by comparing smoking status with records from
RERF surveys in  1964-68 (self-reported by subjects when they were alive).  Cases and controls
who had never married were excluded.  Of the female cases exposed to spousal smoking, 16% had
squamous or small cell carcinoma, whereas no unexposed cases had those cell types. No
information was provided on location of the carcinomas.
       The number of  female cases exposed to ETS is 73 out of 94 (number exposed/total)
compared with 188 out of 270 female controls (crude odds ratio [OR] is 1.52 [95% confidence
interval [C.I.] = 0.88, 2.63], by our calculations). Application of logistic regression to the whole
study that includes active smokers, gives an adjusted odds ratio of 1.5 (90% C.I. = 1.0, 2.5), similar
to the crude analysis. It is not stated explicitly that matching variables were included in the
logistic regression model. Four additional analyses were conducted on the ETS data alone (i.e.,
without active smokers). The authors stratified exposure by number of cigarettes smoked per day
by husband (0, 1-19, 20-29, 30+) and obtained a marginally significant trend (p = 0.06).  No dose-
response gradient was found in the association between the number of years the husband smoked
cigarettes and the risk of lung cancer in female never-smokers; the odds ratio decreases from
lowest to highest exposure level (2.1, 1.5, and 1.3). Stratified analysis according to recency of
exposure to husband's smoking (unexposed, exposed but not within the past 10 years, and exposed
within the past 10 years) shows a significant upward trend (p = 0.05). Further stratification of
exposed subjects by occupation found that lung cancer risk tends to increase across occupational
categories in the following order:  housewife, white collar worker, blue collar worker. The highest
odds ratio occurred for women who had blue collar jobs and were married to men who smoked
one or more packs of cigarettes  per day, but the number involved was small. It is reported that
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additional analyses of the data indicated that factors for matching in the whole study have little
influence, but the details are omitted.
       Limited histological information is provided. Among cases exposed to spousal smoking,
16% had squamous or small cell cancer, and 84% had adenocarcinoma or large cell cancer. All of
the unexposed cases had adenocarcinoma.
       The authors conclude that there may be a moderate excess in lung cancer risk associated
with passive smoking. The odds ratio for lung cancer among nonsmoking women tends to increase
with amount smoked by their husbands, a trend seen among  housewives, as well as among women
who work outside the home. There was little association with parental smoking or from passive
smoking that had ceased more than 10 years previously.

A.4.1.3.  Comments
       The larger study from which the ETS data are taken  was primarily intended to investigate
the interaction of smoking and ionizing radiation in atomic bomb survivors of Nagasaki and
Hiroshima. The information on passive smoking has been collected posthumously in a large
percentage of the cases, requiring heavy use of proxy responses. The response rate was not high,
however, because some next of kin refused to answer questions about deceased relatives and no
attempt was made to  locate next of kin of some subjects who had died or moved away from
Hiroshima or Nagasaki.  The dependence on proxy respondents raises questions about the validity
of the exposure data for some measures, particularly in childhood, and about detailed information
such as the number of cigarettes smoked per day, duration of smoking habit, and years since
cessation of smoking.  Information on childhood exposure was  obtained for only two-thirds of the
subjects. The omission of data on subjects where the next of kin had refused response or the
subject had moved may be a source of bias. The diagnosis of lung cancer was not pathologically
confirmed in more than 40% of the cases.  Also, it is not clear that the subjects are representative
of the target population. They had been exposed to ionizing radiation to varying  degrees,
whatever implication that may have; they are among the survivors, which may suggest selective
characteristics; and their age distribution is high, ranging from about 35 to 90 years of age with an
average of 70 years or more.
       Only ever-marrieds are included in the ETS subjects, which is helpful in the analysis.
There is some ambiguity in the statistical analyses, however,  in reference to Tables 2 through 6
(the main results).  The tables contain odds ratios that are reported to be the result of logistic
regression with matching.  The details regarding matching in the analysis are not given, but it is
reported that analysis of the crude data and matched logistic  regression give similar values.
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Regarding the analyses for trend, the outcome seems to be sensitive to the measure of exposure
used.  The odds ratios are strictly increasing for stratification by number of cigarettes smoked per
day, but a different pattern emerges when ETS exposure is measured by the number of years the
husband smoked cigarettes.
       In general, the conclusions are presented more strongly than the data warrant. The
assertions are somewhat tenuous that risks tend to increase with amount smoked by the  husband,
are highest among those who work outside the home and whose husbands are heavy smokers, and
decrease with cessation of smoking.  Conversely, whereas little association between ETS exposure
in childhood and lung cancer is reported, relevant information was available for only two-thirds
of the subjects, and its accuracy is questionable because most of that information was provided by
proxies.  Overall, the observed data suggest that ETS exposure may be related to risk of lung
cancer, but there is some potential for misclassification and other sources of bias.  Thus, this study
provides  some useful information  on lung cancer risk in passive smokers, but its interpretation
needs to be conservative, taking into account the atypical characteristics of the subjects and other
concerns described above.

A.4.2. BROW (Tier 3)
A.4.2.1.  Author's Abstract
       "The relation between various risk factors and adenocarcinoma of the lung was evaluated
in a case-control study. Subjects were selected from the Colorado Central Cancer Registry from
1979-82 in the Denver metropolitan area. A total of 102 (50 males and 52 females)
adenocarcinoma case interviews and 131 (65 males and 66 females) control interviews were
completed. The control group consisted of persons  with cancers of the colon and bone marrow.
The risk estimates associated with cigarette smoking were significantly elevated among  males
(OR = 4.49) and females (OR = 3.95) and were found to increase significantly (p < 0.01) with
increasing levels of cigarette smoking for both males and females.  For adenocarcinoma in
females, the age- and smoking-adjusted odds ratios at  different levels of passive smoke exposure
followed an increasing overall trend (p = 0.05). After additional adjustment for potential
confounders, prior cigarette use remained the most  significant predictor of risk of
adenocarcinoma among males and females. Analysis restricted to nonsmoking females revealed a
risk of adenocarcinoma of 1.68 (95% C.I. = 0.39, 2.97)  for passive smoke exposure of 4 or more
hours per day.  Neither sex showed significantly elevated risk for occupational exposures,
although males bordered on significance (OR = 2.23, 95% C.I. = 0.97, 5.12). The results suggest
the need  to develop cell type-specific etiologic hypotheses."
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A.4.2.2.  Study Description
       This study was conducted in Denver, Colorado, to evaluate the role of smoking, passive
smoking, occupation, community air pollution, and socioeconomic status in the etiology of
adenocarcinoma of the lung. Because subjects include active smokers, the data on ETS subjects
are part of a larger data set.
       Cases and controls were drawn from the Colorado Central Cancer Registry. All subjects
were diagnosed with lung adenocarcinoma between 1979 and 1982. Cases are white female
Denver residents of at least 6 months' duration. Controls are of similar description to the cases,
except that they were diagnosed with colon cancer or bone marrow cancer. Controls were
matched on  a group basis to produce the same age and gender composition.  It is not clear if
incident cases were  used and whether control sampling was cumulative or density.
       The  subjects are not matched on smoking  status, so the data on ETS subjects alone are
unmatched for all variables considered in the larger study.  Face-to-face interviews were
conducted, blindly,  on a total of 149 cases and 169 controls, after attrition in selection and follow-
up of 47 cases and 38 controls. The subject was interviewed in 31% of the cases and 61% of the
controls; the remaining interviews were conducted with a friend  or relative.  The mean age of the
female cases (controls) was 64.9 (68.2) years; no further details are provided. Clinical verification
of lung cancer diagnosis was conducted microscopically.
       "Exposed" to ETS is used in two ways, depending on context:  (1) the husband smoked
(presumably "ever-smoked" is intended, rather than "currently  smokes," but that is not explicit);
(2) the subject was in the presence of tobacco smoke, from any source, 4 or more hours per day on
average. Although there are two operational definitions of exposure, neither includes duration of
ETS exposure.  Questions were apparently asked regarding exposure in both childhood and
adulthood, the latter including sources in the home and in the workplace. No indication was
found that the data  collected from subjects were checked for internal consistency or against other
sources. No mention was found regarding the number of unmarried women in the study or what
assumptions may have been made regarding their exposure to ETS when spousal smoking is the
source considered (the first of the definitions given above).
       The  ETS subjects consist of 4 out of 19 (exposed/total) female cases and 7 out of 47
controls, when ETS exposure means the spouse smoked (Definition 1). For exposure from all
sources (Definition 2), the corresponding numbers for cases and controls are 4 out of 19 and 6 out
of 47, respectively.  The crude odds ratio is 1.52 (95% C.I. = 0.39, 5.96) for Definition 1 of ETS
exposure and 1.82 (95% C.I. = 0.45, 7.36) for Definition 2 (data communicated  from first author,
Brownson).  A test for trend using hours per day  as the exposure measure is conducted on the
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whole data set for females including smokers (33 of 52 cases are smokers and 19 of 66 controls are
smokers; the two exposure categories, 4 to 7 and 8 or more hours per day of exposure to passive
smoke, contain a total of only 4 cases  and 6 controls who are nonsmokers, but 19 cases and 7
controls who are smokers). The method of Miettenen is applied with stratification on age and
smoker status (p = 0.05  for trend). The data for never-smokers alone were used in a multiple
logistic regression to compare subjects exposed 0 to 3 hours per day with those exposed from all
sources 4 or more hours per day (Definition 2 of ETS exposure).  Adjustments were made for age,
income, and occupation. The reported odds ratio is 1.68 (95% C.I. = 0.39, 2.97).  (Note:  It appears
that the upper confidence value may be in error. In view of the outcome for the crude odds ratio,
a value about twice what is shown might be anticipated.)
       To summarize the statistical tests and authors' conclusions, no significant risk estimates
were shown when smoking by the spouse was considered as a dichotomous variable.  When the
data for both active smokers and  passive smokers were stratified according to level of passive
smoke exposure, a statistically significant trend in the risk estimates was shown for females
(p = 0.05) after adjustment for age and cigarette smoking.  However, after adjustment by logistic
regression for age, income, occupation, and cigarette smoking, with the two exposure categories
for ETS combined (> 3  and 4+ hours per day), no significant risk was detected.

A.4.2.3.  Comments
       The study is very small when  reduced to the never-smokers alone.  The measure of ETS
exposure used (hours/day from all sources) is not very specific to differentiate exposed from
unexposed persons, particularly exposure 20 to 30 years ago, which may be more relevant than
current exposure. Only 15% of the controls have a husband who smoked; only 13% of ETS
subjects are exposed from any source 4 or more  hours per day.  Thus, the cut-point selected by
the researchers  for general ETS exposure (4+ hours/day) may be too high, resulting in a
substantial amount of exposure in the "unexposed"  group.  For either definition of ETS exposure,
however, the percentage exposed is extremely low.  Details are lacking also in other areas that may
have a bearing (e.g., the treatment of unmarried subjects—whether they were present and, if so,
the assumption made regarding ETS exposure).
       We experienced some difficulty with the statistical analyses.  One of the adjusted
procedures is the trend test.  Perhaps  because the number of ETS subjects is so small, smokers
were included in the analysis and then a method was used to attempt to adjust the effects of their
presence on the outcome. It would be preferable, in our view, to omit the smokers from the
analysis entirely. There are so few ETS subjects in the exposure categories (see above) that it
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 seems highly unlikely that a test for trend would be significant if based on the ETS subjects alone
 (we did not have the number of ETS subjects by exposure group, however, so we were unable to
 conduct the trend test to check the outcome).
        When the two exposure categories were combined and only the ETS subjects used, the
 results were not close to statistically significant (OR is 1.68; 95% C.I. = 0.39, 2.97). We also view
 that result with caution because using the same data for analysis  that were used to determine
 which variables to adjust for may distort the statistical interpretation. There also may be a
 typographical error in the upper confidence limit because the value shown is only about half the
 corresponding  value for the crude odds ratio.
        The remaining analyses are from the crude odds ratio, 1.52 (95% C.I. = 0.39, 5.99) and 1.82
 (95% C.I. = 0.45, 7.36),  which suggests a possible association between ETS exposure and lung
 cancer, although it could easily be ascribed to chance  in view of  the wide confidence intervals.
 The study has a very strict requirement for classification as exposed to ETS (4+ hours per day
 from any source of ETS), which is reflected in only 15% of the controls being designated as
 exposed (40-60% is more typical). This percentage is  only slightly higher than the  12% figure
 based on simply being married to a smoker.  The control subjects thus appear unrepresentative of
 exposure to the target population, or else the classification of subjects exposed is too rigid.  The
 crude odds ratio may be the preferred statistical measure to represent the outcome of the data, but
 care should be  exercised in using the results from this study in conjunction with those of other
 studies.

 A.4.3. BUFF (Tier 3)
 A.4.3.1. Author's Abstract
       "A population-based case-comparison interview study of  lung cancer was conducted from
 1979 to 1982 in six Texas coastal counties—Orange, Jefferson, Chambers, Harris, Galveston, and
 Brazoria—to  evaluate the association of lung cancer with occupational and other environmental
 exposures. Lung cancer mortality rates in these counties consistently have exceeded lung cancer
 mortality rates  observed for Texas and the United States from 1950-69 to 1970-75 for both sexes
 and races (white and nonwhites).
       Histologically and cytologically confirmed incident cases diagnosed during the interval
July 1976 to June 1980 among white male and female residents ages 30 to 79 years were
ascertained from participating hospitals in the six-county area. Both population-based and
decedent comparisons were selected and matched on age, race, sex, region of residence, and  vital
status at time of ascertainment. The exposures of primary interest in the study of lung cancer are
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those associated with occupation (employment in specific industries and occupations) in
conjunction with tobacco, alcohol, diet, and residential exposures."

A.4.3.2.  Study Description
       This population-based case-control study was conducted in six coastal counties of eastern
Texas to evaluate the association of lung cancer with occupational and other environmental
exposures.  Those of primary interest are associated with occupation in conjunction with tobacco,
alcohol, diet, and residential exposures.  The ETS subjects are part of this larger study that
includes active smokers.
       Cases include males and females ascertained from hospital and State records during
1976-80, except for Harris County, which includes only females from 1977-80.  All subjects are
white (including Hispanic) county residents of at least 6 months.  Cases are incident, without
restriction to cell type, and histologically diagnosed to eliminate secondary lung cancers (there is
some inconsistency in the article on whether all diagnoses were by histology or whether some  were
by cytology). Controls were selected from State and Federal records,  group matched on age, sex,
race or ethnicity, county of residence, and vital status. The candidate sample size is estimated in
the report at approximately 1,650, including both sexes, of which just over 700 were lost to
attrition in selection or followup for various reasons.  Face-to-face  interviews were conducted,  a
large number of which were with  next of kin as necessitated by inclusion of decedent cases and
controls.  For example, for females, the number of subject interviews is only 18% for cases
(81/460)  and 24% (116/366) for controls. The  distribution of ages is similar for cases and
controls, based on  groupings of 10-year  intervals.
       "ETS exposed" means having ever lived with a household member who smoked regularly.
Exposure sources include the home environment during childhood and adulthood but exclude the
workplace.  There is no mention of whether data on ETS exposure were cross-checked with other
interview questions or other sources. No indication was found regarding unmarried females in the
sample and how marital status may affect level of exposure to ETS. Some summary information is
provided on the distribution of tumors by cell  type, but totals include smokers, so they are not
reproduced here. The ETS data for females consist of 33 out of 41  (exposed/total) cases and  164
out of 196 controls; for males, the respective figures are 5 out of 11 and 56 out of 90.  For the
exposure definition given above,  the crude  odds ratio reported is 0.78 (95% C.I.  = 0.34, 1.81) for
females (direct calculation from the data yields a value of 0.81; Buffler apparently added 0.5 to all
cells to compensate for inclusion of no subjects in some cells).  Little  difference was found when
female smokers  were categorized  by number of years lived with a household member who smoked.
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 No adjusted statistical analysis is provided to account for variables used in matching for the study
 as a whole, nor is there a test for trend. The authors conclude that no effect of passive smoking is
 indicated for lung cancer.  No attempt is made to evaluate whether exposure to ETS in childhood
 or adulthood is a factor.

 A.4.3.3.  Comments
        The potential relationship between ETS exposure and lung cancer risk was not a principal
 issue in the design of this study.  As described in the abstract,  and more fully in the study
 description above, other potential etiologic factors were of more central concern. There are
 several limitations regarding the study's contribution to the epidemiologic evidence on ETS
 exposure and lung cancer risk.  For example, the interview question on exposure to ETS is not
 very specific. "Having lived with a household member who smoked regularly" does not distinguish
 between exposure in childhood and in adulthood, between substantial and only light exposure, or
 between short-term and long-term exposure. One might expect a high percentage of  persons to
 qualify as "exposed" under such a broad definition, and that is  what the study demonstrates:  84%
 of the controls are classified as exposed.  With such a high percentage, both cases and controls may
 include a number of subjects who have experienced very light  exposure to ETS. Another concern
 in this study is the use of decedent subjects. The majority of both male (86%) and female (82%)
 cases in the study (including smokers) were deceased.  Consequently, a very high percentage of
 interviews was by proxy (82% of cases and 76% of controls).
        This study was conducted in a region with a significantly higher age-adjusted mortality
 rate for lung cancer than for the United States in general.  For all ages combined, the  overall
 excess lung cancer mortality in the Texas study area is approximately 30% to 40% and is
 considerably higher for some age groups, according to the article.  This was the apparent
 motivation for the study, with emphasis on important occupational and industrial exposures for
 residents of the Texas coastal area, including those associated with shipbuilding and repair,
 chemical and petrochemical manufacturing,  petroleum refining, construction, and metal
 industries. If these nonsmoking factors affect the incidence of lung  cancer, then they may be
 confounding the attempt to detect an effect from passive smoking.  Appropriate statistical
 methods need to be applied to adjust the effect of each risk factor for the others.
       Other factors may affect  the ETS analysis also.  Harris County, which is frequently
addressed in the article as distinct from the other five counties, was apparently added  to the study
later (case ascertainment began 1 year later there  and included only females; 10 of the 11 hospitals
that did not participate are in Harris County). Consequently, there are some regional differences
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in the study as well as ethnic and racial differences (white and Hispanic).  Although the authors
took care to match controls on these and other factors, the matching only applies to the whole
study (91% and 97% of male and female cases, respectively, are classified as having smoked
regularly), not to the ETS subject group specifically, and there is no adjustment for these factors
in the analysis.  The unadjusted analysis, the insensitive indicator of ETS exposure, and the large
use of decedent cases and proxy  responses limit the value of this study for assessing any health
effects associated with passive smoking.

A.4.4. BUTL(Coh) (Tier 2)
       This study was undertaken to explore the role of active and passive smoking in Seventh-
Day Adventists in California.  Subjects were participants in a larger prospective cohort study of
factors affecting health in Adventists.
       In 1974, the Adventist Health Study was initiated with the purpose of investigating the
associations  of a number of lifestyle and nutritional factors with morbidity and mortality in
California Seventh-Day Adventists. Registered Adventist households were identified by
contacting the clerks of all 437 California Adventist churches. A basic demographic questionnaire
sent to all households received a  response rate of 58%. In 1976, all subjects aged 25 or older in
1974 were asked to  complete a lifestyle questionnaire that included many demographic, medical,
psychological, and dietary variables.  More than two-thirds of the targeted subjects responded.
From the non-Hispanic whites among these respondents, Butler and his colleagues drew two
cohorts. One consisted of 22,120 spouses married and living together at the time of completion of
the lifestyle questionnaire in 1976 ("spouse-pairs" cohort) and the other of 6,467 individuals
participating in an Adventist Health Smog Study of air pollution and pulmonary disease (the
"ASHMOG" cohort); about two-thirds of the ASHMOG cohort also was included in the spouse-
pairs cohort.
       Subjects received annual  forms for self-reporting of hospitalizations in the past year.
Medical records relating to reported hospitalizations were then reviewed.  Mortality was traced in
four ways:  linkage  with California Death Certificate and National Death  Index Systems, church
clerk notification of deaths entered in church records, and followup of hospitalization history
form responses (or nonresponses).  Underlying and contributing causes of death were obtained
from death certificates.  Death certificates were obtained for all reported  fatalities.
       For the spouse-pairs cohort, subjects were considered  unexposed to ETS if their spouses
were either never-smokers or ex-smokers baptized into the Adventist church—which proscribes
tobacco usage—before marriage.  Those whose spouses were ex-smokers with less than  5 years of
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total smoking also were considered unexposed. All other subjects with ex- and current smoker
spouses were classified as exposed.
       Incidence rates were calculated using person-years. In the spouse-pairs cohort,
age-adjusted lung cancer mortality rates for females married to past or current smokers were
higher than those for female spouses of never-smokers, yielding relative risks of 1.94 and 2.47 for
past and current smokers, respectively. Comparison of wives with ever- versus never-smoking
husbands yielded a relative risk of 2.0. The same age-adjusted relative risk resulted when
analyses  were restricted to the 9,207 never-smoking females included in the spouse pairs.
Virtually identical risk estimates resulted from both Mantel-Haenszel and maximum likelihood
analyses. None of the relative risks was statistically significant at the 5% level.
       In the ASHMOG cohort, the relative risk of lung cancer adjusted for age and past smoking
status among females was 1.16 for women who had lived with a smoker for at least 11 years
compared with women who had not lived with a smoker; no difference was observed for women
who had lived for less than 11 years with a smoker, although this group was only one-tenth as
large as  the others.  A similar pattern  was seen among males  who had lived for at least 11 years
with a smoker, with an adjusted relative risk of 1.17.
       In the spouse-pairs cohort, age-adjusted rates of smoking-related cancers (excluding lung
cancer) were only slightly higher among nonsmoking females married to smokers than among
nonsmokers (relative risk [RR] = 1.06); the relative risk rose  to 1.22 when lung cancers were
included.
        In the ASHMOG cohort, age-adjusted rates using conditional maximum likelihood  analysis
for all smoking-related cancers were higher among males who lived with a smoker (RR = 1.45 for
 1-10 years; 1.74 for 11+ years) or worked with a smoker (RR = 2.62 for 1-10 years; 1.47 for 11+
 years).  Among females, in contrast, only one (at RR = 1.03) of the four exposed categories had a
 higher rate than the nonexposed groups.
        All lifestyle questionnaires were administered anonymously, thus reducing the potential
 for inaccurate responses caused by fear of discovery;  respondents to the special supplemental
 ASHMOG  questionnaire were assured of confidentiality but not anonymity.
         Although causes of death were obtained from death certificates, review of medical records
 revealed histological confirmation in  99% of the primary malignancies reported among the spouse-
 pairs cohort.  Thus, substantial misclassification of lung cancer deaths  is unlikely. Subsequent
 study of patients discharged from 1 of the 11 participating Adventist medical centers over a 6- .
 month period  indicated that under 2% of study participants  failed to report their hospitalizations;
 serious  underascertainment of cases thus also seems unlikely. Losses to followup by study's end
 totaled  only 1.2% of the original study cohort—a very low rate.
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       Comparing the results of the 1976 questionnaire with those of a supplemental
questionnaire given to ASHMOG subjects in 1987, 4.7% of male smokers now reported themselves
as "never-smokers" and 1.4% of never-smokers now reported themselves as nonsmokers.
Concordance of female responses was even higher. This concordance of responses does not
necessarily imply the degree of accuracy of responses, only their reliability.
       Comparison of responses to the 1987 questionnaire by females revealed that about 6% of
those previously classified as not having a smoking spouse now reported having had one; the
converse was also true for 6% of the women.  These data indicate a mild nondifferential
misclassification of exposure, which would push results toward the null.
       Information is available on a large number of variables of possible interest as potential
confounders or risk mediators.  Unfortunately, the modest number of total lung cancer deaths
among females in the spouse-pairs cohort (8) or among both sexes in the ASHMOG cohort (13)
discourages attempts to control for other potential confounders in addition to age in the analyses.
Separate consideration of the association between variables other than passive smoking and age-
adjusted lung cancer mortality among women indicated a high relative risk (RR > 4) for spousal
blue collar occupation.  No other variables produced nearly as strong or consistent an association;
in fact, the only other consistent association was a relative risk of 1.3 to 1.6 for nonrural status.
Unfortunately, no breakdown of blue collar spousal status by exposure groups was presented.
        By virtue of its basic design, the inherent minimization of sources of confounding
provided by its study population and the level of information available regarding potential
confounders, and other sources of bias, the Butler study has many of the key ingredients to
produce convincing results. Unfortunately, this potential goes largely unrealized because of the
low number of outcome events occurring during the followup period, which for the most part
renders stratification or  control for multiple factors simultaneously impractical; even stratification
by several age or exposure levels produces  unstable results.
        Nevertheless, the findings of this study are quite consistent with the hypothesis that ETS
exposure of nonsmokers is associated with  mildly elevated lung cancer, (active) smoking-related
cancer, and ischemic heart disease mortality. Insofar as the study data allow for consideration of
potential misclassification and  confounding effects, neither misclassification nor confounding can
account for the observed association. Because of the limited number of outcome events, several
 possible confounding factors could not be definitively or adequately addressed in the  analyses, and
 the observed associations were not statistically significant; therefore, the study's findings must be
 viewed as suggestive but not of themselves convincing.
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 A.4.S. CHAN (Tier 4)
 A.4.5.1.  Author's Abstract
 (Note:  This study is described in two sources, both of which were used for the description below.
 Chan et al. [1979] is the more complete description, but it contains considerable attention to active
 smoking as a cause of lung cancer.  Chan and Fung [1982] is a condensed version that specifically
 addresses nonsmokers. The abstract given here is for the 1979 article.  No abstract is provided in
 the 1982 source.)
        "Bronchial cancer is a disease of high and increasing annual incidence in Hong Kong,
 especially in women, whose age-specific death rates from this cause are among the highest in  the
 world.  A case-control study of the relationship of bronchial cancer with smoking was carried out
 during 1976-77, taking particular note of the histological type of the tumor. Two hundred and
 eight male and 189 female patients were interviewed, covering about one-half the total number of
 cases of bronchial cancer registered as dead from the disease in Hong Kong during the period of
 the survey. The association with smoking was more evident in males than in females, and in
 squamous and small cell types, as a group, than in adenocarcinoma. Forty-four percent of the
 women with  bronchial cancer were nonsmokers, their predominant tumor being adenocarcinoma,
 and in them no association could be detected with place of residence or occupation.  There was no
 strong evidence of an association with the use of kerosene or gas for cooking; 23 did not use
 kerosene. The cause of the cancer in these nonsmoking women remains unknown."

 A.4.5.2. Study Description
 (Note:  This description is primarily based on Chan et al. [1979]. Chan and Fung [1982] are cited
 when used as a reference.)
        This study is the earliest of four from Hong Kong that consider ETS exposure as a
 potential etiologic factor for lung cancer incidence in nonsmoking women. Here, however, that
 objective is secondary to  evaluation of the relationship of bronchial cancer with active smoking.
        In the whole study, target cases are the lung cancer patients, male and female, in five
 hospitals in Hong Kong during 1976-77 who were willing and able to be interviewed, Controls
 are patients of the same general age groups from the orthopedic wards of the same hospitals as the
 cases. No specific diseases are excluded. Cases are incident and control sampling is density. The
 candidate sample size  is 208 (189) male (female) cases and 204 (189) male (female) controls.
 Attrition from selection of followup is not reported but appears to be high. Subjects were
personally interviewed, when possible. About half of the estimated  number of lung cancer cases
diagnosed in Hong Kong during the study period were  actually interviewed.  Some patients were
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too ill to answer questions, and more than expected were treated elsewhere than in the hospitals
covered. No interviews with next of kin were obtained for the cases interviewed.
       The ETS subjects (never-smokers) alone include 84 (2) female (male) cases and 139 (30)
female (male) controls  The age distribution of the female cases (controls) is, by percentage, as
follows: age less than 40, 7 (5%); ages 40 to 49,  15 (15%); ages 50 to 59, 23 (30%); ages 60 to 69,
23 (22%); and age 70 or more, 32 (28%). Cases with a histological diagnosis were reviewed and
verified by reexamination of the pathological specimens.  In the absence of a histological
specimen, cytological diagnosis was accepted.  In some cases, on histological grounds, secondary
adenocarcinoma was suspected, and a few cases were rejected after detailed examination of the
clinical records. Of the cases, 46 (55%) were diagnosed by histology, 23 (27%) by cytology, and 15
(18%) by radiology and clinical means. Diagnoses by cell type were as follows:  squamous or small
cell, 19 (22%); adenocarcinoma or large cell, 40 (48%); others and unspecified, 25 (30%). Of the
unspecified, 15 had no histological or cytological verification.
        ETS subjects are never-smokers. Classification of a subject as exposed or unexposed to
ETS is based on the response to these questions: (1) If you do not smoke, have you been exposed
to cigarette  smoke from other people at home or at work? (2) Does your husband/wife smoke? (If
"yes," how many cigarettes per day?)  (The first question is included in Chan et al. [1979].  The
second one is from a personal communication of Linda C. Koo.)  No information is reported on
the distribution of tumors by central and peripheral location.
        The ETS data on females based on question 1, above, consists of 50 out of 84
(unexposed/total)  cases and 73 out of 139 controls. The authors state that "this is a rather
subjective approach to the problem."  No statistical estimates are  provided; our calculation of the
crude odds  ratio is 0.75 (95% C.I. = 0.43, 1.30). No clear conclusion is drawn regarding  the
potential relationship between ETS exposure and lung cancer occurrence, but the authors imply
that no connection was found (which the odds ratio and confidence  interval amply support).  The
authors found no particular occupation as being dangerous.  Their findings also do not support air
pollution as a factor, and they provide no strong evidence that cooking with various types of fuel
 is relevant.

 A.4.5.3.  Comments
        Although data on spousal smoking were collected along with an indication of the number
 of cigarettes smoked per day, they are referred to only in the 1982 article," where the  authors note
 without further elaboration that more nonsmoking cases have nonsmoking spouses.  It is reported
 that answers to the question, "Are you exposed to the tobacco smoke of others at home or at
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 work?" gave no indication that other people's smoking was a risk factor for lung cancer in
 nonsmokers, with 40.5% of cases and 47.5% of controls answering yes to this question.  Why the
 data for spousal smoking are not given and analyzed is unknown. The question about general ETS
 exposure combines sources in the household and workplace and refers only to current exposure
 without a measure of duration, which would likely affect any risk associated with passive
 smoking.
        Although it is reported that cases and controls are similar in age, occupation, and other
 characteristics, comparability is questionable. The article cites a criticism of the whole study
 (including smokers) for use of orthopedic patients as controls, on the basis that some patients may
 be hospitalized with smoking-related diseases (e.g., osteoporosis). It was found that the controls
 smoke more than a group representative of the population of Hong Kong.  This would create a
 bias toward negative association. Although these comments refer to smoking habits, they suggest
 the potential for selection bias of controls that may extend to nonsmoking  controls as well.
        It is noted, also, that there are  more cases from Hong Kong Island  than would be expected
 from the population distribution of Hong Kong as a whole, possibly due to more success
 contacting cases in Hong Kong Island than in Kowloon.  The authors caution about reaching any
 conclusion about the distribution of cases within Hong Kong as a whole. The failure to follow up
 on patients who were eventually treated at other hospitals or were too ill to be interviewed is
 itself, of course, a potential source of bias.
        Other differences are apparent between cases and controls. Among nonsmokers, a higher
 percentage of cases than controls (1) are Cantonese (81  vs. 70) or (2) have ever cooked with
 kerosene (73 vs. 60). It is speculated that the Cantonese diet, high in nitrite or nitrate content,
 may be a factor in lung cancer incidence (Chan and Fung, 1982).  More broadly, these
 comparisons between cases and controls indicate differences in ethnic composition, lifestyle, and
 socioeconomic status that are difficult  to assess.
       In summary, ETS subjects are not matched in the design, and an adjusted statistical
 analysis is not conducted. Consequently, potential sources of bias are not controlled. There is
 substantial basis to question the comparability of cases and controls, as described above. Data
 quality is suspect because confirmation of primary lung cancer was limited and cases were missed
 because patients were too ill to be interviewed personally or were eventually treated at another
 hospital.  Also,  the question posed to subjects for classification as exposed  or unexposed to ETS is
 sufficiently general to invite a subjective response. Overall, methodological shortcomings hamper
 the interpretation of this study's results.
       The finding that spousal smoking appears to be more frequent in controls, mentioned in
the 1982 report, is noted to be at variance with the Hirayama study,  which may have motivated
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the authors to conduct this secondary analysis of ETS exposure using their previously collected
data.  Whatever the motivation, the limitations of the original study, which was not designed to
assess passive smoking, limit this study's value for assessing ETS exposure and lung cancer.

A.4.6. CORK (Tier 2)
A.4.6.1.  Author's Abstract
       "Questions about the smoking habits of parents and spouses were asked in a case-control
study involving 1,338 lung cancer patients and 1,393 comparison subjects in Louisiana, United
States. Nonsmokers married to heavy smokers had an increased risk of lung cancer, and so did
subjects whose mothers smoked. There was no association between lung cancer risk and paternal
smoking.  The association with maternal smoking was found only in smokers and persisted after
controlling for variables indicative of active smoking. It is not clear whether the results reflect a
biological effect associated with maternal smoking or the inability to control adequately for ,
confounding factors related to active smoking. This preliminary finding deserves further
investigation."

A.4.6.2.  Study Description
       This study was conducted in Louisiana to investigate the relationship of smoking habits of
parents and spouses to lung cancer occurrence.  Results of the study were published in 1983; some
clarifying details regarding study methodology were supplied in a 1984 paper addressing only  the
effects of active smoking. The accrual period is not stated; cases are probably a mixture of
prevalence and incidence, and controls are cumulatively sampled.  ETS subjects constitute a small
portion of the whole study, which includes active smokers.
       Cases consist of patients diagnosed with primary lung cancer, exclusive of
bronchioalveolar carcinoma, from participating hospitals in several Louisiana parishes (counties),
predominantly in the  southern part of the state. A total of 302 female and 1,036  male cases and
an equal number of controls are included in the whole study. Controls were selected from other
patients, excluding those diagnosed with emphysema, chronic bronchitis or obstructive pulmonary
diseases, or certain cancers (laryngeal, esophageal, oral  cavity, and bladder).  They  were matched
to cases on hospital, age (+ 5 years), sex, and race.  Information about active and passive  smoking
was obtained by interview (presumably face-to-face and unblinded), with responses obtained
from next of kin in 24%  of cases and 11% of controls; no  information  on refusals is provided.
ETS subjects were identified by exclusion of  individuals who had ever smoked or had never been
married, which eliminated 279 female and 1,026 male cases. Removal of subjects with no spousal
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smoking data eliminated one additional female and two male cases, leaving 22 female and 8 male
cases. Similarly, a total of 1,080 men and women were excluded from controls.  No demographic
comparisons are given, either for the whole study or for the ETS subjects alone, nor is the number
of proxy responses provided for the ETS subjects.  Histological confirmation was obtained for
97% of cases in the whole study, including ever-smokers.
       "ETS exposed" is used in two ways, depending on the analysis given: (1) the spouse has
smoked at least 1 pack-year of cigarettes or (2) the spouse currently smokes.  Units of exposure
are pack-years and current consumption is in cigarettes per day for (1) and (2), respectively.  ETS
exposure in childhood means that at least one parent smoked during most of the subject's
childhood.  Types of tobacco smoking other than cigarettes (e.g., cigars and pipes) are referenced
indirectly in regard to interview questions but are not included in the data analysis.  Other sources
of exposure, either at home or in the workplace, are not considered. Never-married women are
excluded from ETS analysis, but no information is given on the number of nonsmoking widows
and divorcees and  how they were handled with regard to ETS exposure.  Adenocarcinoma
accounts for 54% of lung cancers in nonsmoking women, compared with 22% in women who
actively smoke. No further histological breakdowns are provided.
       For the main  analysis of spousal smoking, exposure constitutes 1 or more pack-years of
spousal cigarette consumption. ETS-exposed subjects include  14 (61) of 22 (133) female cases
(controls) and 2 (26) of 8 (180) male cases (controls). These data yield a crude odds ratio of 2.07
(95% C.I. = 0.81, 5.25) for females (confidence interval was calculated by reviewers). Among
females, stratification by 0, 1 to 40, and 41 or more pack-years of exposure yields odds ratios of
1.0, 1.18, and 3.52, respectively, with the highest exposure category being statistically significant
at p < 0.05. No adjusted results are presented.  It is, however,  reported that analyses based on
current daily spousal  cigarette consumption produced very similar results to the pack-year
analyses. In addition, it is reported that neither exclusion of proxy interview data nor restriction
to same-race subjects significantly  alters the results.  Analysis  of parental smoking during
childhood embraces the combined population of smokers  and nonsmokers, adjusting for smoking
status by logistic regression. Maternal smoking is associated with significantly increased estimated
risk of lung cancer (OR = 1.38, p < 0.05) but paternal smoking is not (OR = 0.83).  No association
was noted among nonsmokers alone, but the authors note that small numbers preclude adequate
analysis of this group.
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A.4.6.3.  Comments
       The study entails a major multicentric effort to assemble hospital-, age-, race-, and sex-
matched lung cancer cases and controls from Louisiana hospitals.  Its use of trained local
interviewers familiar with the region's culture increases the probability of obtaining accurate
interview data for the nearly 3,000 subjects involved.  Exclusion of active smokers to assess ETS
exposure, however, exacts a toll on the study's power and validity. Because the initial matching of
cases and controls did not include smoking status, the ETS subjects are unmatched in the analyses
of spousal and parental smoking. This potential problem is not addressed by the authors.  The
lack of any demographic information on cases and controls leaves the comparability of these
groups uncertain.
       The potential problem of misdiagnosis of primary lung cancer is minimized by the;high
rate (97%) of histological case confirmations. Eligibility criteria for controls were intended to
exclude smoking-related diseases.  Some 15% of the controls had cardiovascular disease, however,
which has been associated with both active and passive smoking.  The authors also speculate that
the inclusion of adenocarcinoma, reportedly less smoking-associated than other lung cancers,  may
have diluted the significance of their results, but they do not present analyses using their
extensive histological data to assess this question.
        Restriction  of the spousal smoking analysis to ever-married individuals eliminates
potential bias due to differences between  lifelong single and married individuals. Stratification by
gender controls for any sex-related differences.  Both race and proxy interviews were reported to
have no effect on the spousal smoking results, and the  spousal smoking association was still
observed after division of women into more than and less  than 60 years of age. A small number
of nonsmoking ever-married cases (8 males and 22 females for this study) hampers efforts to
control statistically for other factors; nonetheless, direct adjustment for age and race is needed.
        It is concluded that females married to heavy smokers have an increased risk of lung
cancer.  A significant increase  in risk for nonsmokers was found  from maternal but not from
paternal smoking in childhood. The results for childhood exposure,  however,  use statistical
methods to adjust for the presence of active smokers.  It would be preferable,  in our view, to
remove the data for active smokers prior  to analysis. The potential for bias in all of the analyses,
which could be in either direction and may or may not be of consequence, needs to be kept in
mind when using this study's results.
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 A.4.7. FONT (Tier 1)
 A.4.7.1.  Author's Abstract
        "The association between exposure to ETS and lung cancer in female lifetime never-
 smokers was evaluated using data collected during the first 3 years of an ongoing casercontrol
 study. This large, multicenter, population-based study was designed to minimize some of the
 methodological problems that have been of concern in previous studies of ETS and lung cancer.
 Both a cancer control group and a population control group were selected in order to evaluate
 recall bias. A uniform histopathologic review of diagnostic material was conducted for case
 confirmation and detailed classification. Biochemical determination of current exposure to
 tobacco and screening of multiple sources of information to determine lifetime nonuse were
 employed to minimize misclassification of smokers as nonsmokers.
        A 30% increased risk of lung cancer was associated with exposure to ETS from spouse, and
 a 50% increase was observed for adenocarcinoma of the lung.  A statistically significant positive
 trend in risk was observed as pack-years of exposure from spouse increased, reaching a relative
 risk of 1.7 for pulmonary adenocarcinoma with exposures of 80 or more pack-years.  The
 predominant cell type of the reviewed, eligible lung cancer cases was adenocarcinoma (78%).
 Results were very similar when cases were compared with each control group and when separate
 analyses were conducted for surrogate and personal respondents.  Other adult-life exposures in
 household, occupational, and social settings each were associated with a 40% to 60% increased risk
 of adenocarcinoma of the lung. No association was found between risk of any type of lung cancer
 and childhood exposures from father, mother, or other household members."

 A.4.7.2. Study Description
        This study was initiated in 1985 in five major U.S. metropolitan areas to investigate the
 association between exposure to ETS and lung cancer in female lifetime never-smokers.  The
 study was designed specifically to address this issue and includes only never-smokers.  The results
 reviewed are from an interim report, with the completed study expected to encompass an
 additional 2 years of case accrual.
       Patients were English-, Spanish-, or Chinese-speaking female residents 20 to 79 years  of
 age who have never used tobacco, have no prior history of malignancy, and have
 histopathologically confirmed primary lung cancer. The lung cancers were originally diagnosed at
 participating hospitals in Atlanta, Houston, Los Angeles, New Orleans, and the San Francisco Bay
area, between December 1, 1985, and December 31, 1988. Two control groups were assembled,
one from colon cancer patients and the  other from the general population, with the same general
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eligibility requirements as cases.  The population control group, consisting of women selected
from the general population by random digit dialing and by sampling from Health Care Financing
Administration files, was frequency-matched on age (< 50, 50-59, 60-69, 70+), with two controls
per case. The colon cancer controls were frequency-matched to cases by 10-year age groups and
by race.  The lung cancer group consists of incident cases, but there is no indication whether
density or cumulative sampling was employed for either control group.  Exposure data  were
collected in face-to-face, apparently unblinded, interviews.
       Extensive efforts were made to include only never-smokers.  For cases and colon cancer
controls, medical records were reviewed for tobacco use and physicians were contacted as
necessary.  Eligible cases not previously excluded and all population controls were contacted by
telephone to screen for prior use of tobacco (no more than 100 cigarettes smoked or use of any
tobacco in  any form  for more than 6 months).  Urinary cptinine was bioassayed to eliminate any
misreported current smokers.
       A total of 514 eligible cases were identified, of which  83 were not interviewed  for
unspecified reasons and 2 had urinary cotinine levels consistent with active smoking. Independent
histopathologic review by a pulmonary pathologist  was performed for 84% (359/429) of the lung
cancer cases, resulting in nine exclusions. Only the remaining 420 cases are included in the study.
Colon cancers were not reviewed.  Of 489 (1,105) eligible colon cancer (population) controls, 131
(311) were not interviewed and 7 (14) were excluded for high urinary cotinine.  Proxies were
interviewed for 143 (34%) of the lung cancer cases and 35 (10%) of the colon cancer controls,
whereas no proxies were used for the population controls.
       Cases and the two control groups all have similar age distributions, with the majority of
subjects between 60  and 79 (73%, 74%, and 74% of the cases,  colon, and population groups,
respectively). The proportion of whites is similar across all groups (63-69%), but the control
groups contain a somewhat higher  proportion of blacks and lower proportion of other minorities,
and a little higher percentage of high school graduates (76% and 79% vs. 68%). Cases and controls
are comparable by metropolitan size of adulthood and childhood residences and also by annual
income.
        Four sources of adult ETS  exposure are assessed: smoking by (1) spouse(s) and (2) other
household members  while living with the subject, and reported exposure to ETS in (3)
occupational and (4) social settings. Three sources of possible exposure in childhood (up to 18
years of age) are considered:  smoking by (1) father, (2) mother, or (3) other household member(s)
while living in the subject's home  for at least 6 months. Subjects are characterized as ever- versus
never-exposed with  a subanalysis by tobacco type  (cigarette, pipe, or cigar). Years of  exposure
are also tabulated. In addition, cigarettes per day for spouse and for other household sources and
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 pack-years for spouse(s) are calculated.  No checks on exposure (aside from the cotinine
 screening) are reported.
        Adenocarcinoma is the dominant type of lung cancer among study subjects, representing
 76% (311/409) of all cases included in the study (with the exception of 11 cases with "review
 pending") and also  78% (281/359) of all independently confirmed primary bronchogenic
 carcinomas among  those cases. Other cell types include 12% (48/409) large cell, 7% (27/409)
 squamous cell, 3% (14/409) small cell, and 2% (9/409) other cancers.  No data on airway proximity
 are provided.
        The final study population (for this interim report) consists of 420 lung cancer cases, 351
 colon cancer controls, and 780 population controls. Exposure to spousal smoking from all types of
 tobacco is reported for 294 cases, 231 colon cancer controls, and 492 population controls, yielding
 similar odds ratios (adjusted for age, race, area, income, and education) of 1.28 (95% C.I. = 0.93,
 1.75) and 1.29 (0.99, 1.69) using the respective control groups.  Elevated but statistically
 nonsignificant observed risks are also observed when cigarette,  cigar,  and pipe exposure are
 assessed separately, with either control group. Restriction of analyses to the 281 independently
 reviewed adenocarcinomas results in stronger associations, with adjusted odds ratios of 1.44 (95%
 C.I. = 1.01,  2.05) and 1.47 (1.08, 2.01) for all types of tobacco, and increased odds ratios for each
 type of tobacco as well.
        Odds ratios  were also calculated for ETS exposure from cigarette smoking alone, with the
 two control groups  combined (the individual results using each control group are entirely
 consistent).  For all lung cancer types combined, the adjusted odds ratios are 1.21 (0.96,  1.54) for
 spousal smoking, 1.23 (0.97, 1.56) for other household members, 1.34 (1.03, 1.73) for occupational
 environments, and 1.58 (1.22, 2.04) for social exposure, the last two of which are significant
 (p < 0.05 and 0.01, respectively).  The corresponding odds ratios for adenocarcinoma cases alone
 continue to  be uniformly higher:  1.38 (95% C.I. =  1.04, 1.82), 1.39 (1.05, 1.82), 1.44 (1.06, 1.97),
 and 1.60 (1.19, 2.14). The odds ratio tends to increase over years of exposure for all carcinomas
 combined and for adenocarcinoma alone, although not monotonically (without downturns).  The
 tests for upward trend are all significant or suggestive, with p-values ranging from < 0.001 to 0.07
 (these p-values are one-half those reported, which apply to a trend in either direction).  Finally,
 for spousal smoking measured in pack-years, the upward trend is significant for adenocarcinoma
 alone and for all lung cancers together (p < 0.005 and 0.04, respectively).
       The  authors interpret their findings as evidence of a causal relationship between  ETS
exposure in  adulthood and lung cancer in never-smoking women.  In contrast to adulthood,  ETS
exposure during childhood shows no association with lung cancer,  for  either all cell types
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combined or adenocarcinoma alone. Adjusted odds ratios for childhood exposure tend to be
slightly (but not significantly) below unity for all exposure sources.

A.4.7.3.  Comments
       This study is much larger than any other ETS case-control study.  More than 400
never-smoking female lung cancer cases were enrolled in just over 3 years, in contrast to the 25 to
75 cases typical of most studies, and two control groups were formed, totaling more than 1,200
subjects.  Additionally, the cases and controls are drawn from five widely dispersed metropolitan
centers in the United States, representing a population of approximately 18.5 million people, about
8% of the U.S. population. This characteristic increases the generalizability of the study and
diminishes the potential for bias related to locale.
       Extensive efforts were made to achieve  precision and validity, in evidence throughout the
study. Cases and controls are highly comparable. They are frequency-matched on age and, for
colon cancer controls, on race as well.  The distributions of other demographic variables—annual
income, childhood residence, and adult residence—are quite similar between cases and both
control groups. The control groups contain a little higher (lower)  proportion of blacks (Asians and
Hispanics) and a higher percentage of high school graduates. These differences, however, should
not have influenced the reported associations because all odds ratios are adjusted for race and
education.
       The use of incident cases reduces the potential for selection bias, and the implementation
of two control groups allowed for assessment of potential bias from comparison with cancer
patients or the general population alone.  The similarity of results obtained from the two control
groups suggests little bias from choice  of controls.
       The use of a multistep procedure to eliminate inclusion of former or current smokers
reduces the potential for smoker misclassification as a source of upward bias.  As a further
safeguard, urinary cotinine was bioassayed for  all consenting persons to exclude those likely to be
current smokers. This  is the only published study  we are aware of to implement this precaution.
Attention to histopathology is also very thorough.  Inclusion of only histologically diagnosed
primary carcinoma reduces the likelihood of diagnostic error, which is further reduced by the use
of independent histopathologic review of most  cases by a single pulmonary pathologist.  The
study's histopathologic findings bring out two interesting points.  First, comparison of cell type
diagnoses between hospital and independent reviewers revealed poor concordance for large (56%)
and squamous (67%) cell carcinomas, indicating that cell-type-specific analyses for these cancers
may be misleading,  particularly if all diagnoses are not made by the same pathologist. The
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histopathologic review also resulted in a net increase of adenocarcinomas from 244 to 281, 78% of
the total, a higher proportion than in most but not all other studies. The statistical results were
stronger when limited to cases of adenocarcinoma alone.
       Exposure information was obtained in the most reliable way, by face-to-face interviews
with each interviewer trained and fluent in the subject's primary language. Information for a
substantial proportion of lung cancer cases (34%) was obtained from proxy respondents, but fewer
proxies were required for colon cancer controls (10%), and none  were used for population
controls. The use of proxy respondents raises the possibility of information bias, but their
exclusion reportedly did not alter the study's findings.  The apparent lack of blinding also raises
the possibility of interviewer bias, but it is unlikely that such bias (or recall bias, for that matter)
would focus its effect on adenocarcinoma. Also, the same relationships hold whether the colon
cancer or population controls are used.
       Particular attention is paid to all sources of ETS exposure, which is more informative than
addressing only spousal smoking, with four sources in adulthood  and three in childhood evaluated
both individually and in combination. Additionally, subjects are counted as exposed to the ETS
of a spouse or other household smoker only while living with the source, giving a more accurate
account of exposure than simply determining whether a spouse or household member ever
smoked. Consequently, the measures of ETS exposure are more specific by source, and probably
more accurate, than in most studies.  This reduces bias toward unity in  the odds ratio arising from
poor distinction between exposed and unexposed subjects. Still,  further accuracy might have been
achieved by stipulating  that smoking must occur in the subject's  household or presence, but this is
a minor point.                                                                              .
       Most of the standard risk modifiers,  such as age, race, geographic area, income, and
education, are adjusted  for in all analyses and thus can be ruled out as sources of the observed
results. Although information on diet, occupational exposures, and "other exposures of interest"
were collected, these factors are not addressed in this interim report. Thorough treatment of the
possible impact of these factors presumably will be undertaken after subject accrual is finished
and published in the completed study.
       To summarize, this study was designed specifically and solely to address the topic of ETS
as a potential lung cancer risk to nonsmoking women. Several issues were given special attention,
such as the potential misclassification of smoking status, histopathologic specificity, recall bias,
and source of ETS exposure.  Histopathologic specificity has not  been convincingly demonstrated
in prior studies, and the meaning of "exposed to ETS" has differed widely between studies, even
those addressing spousal smoking only. The  remaining issues are largely related to controlling
potential sources of bias and confounding to enhance validity.  The qualitative rigor and
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completeness of detail in this study is impressive.  In addition, it is quite large, which increases
precision of estimates and power to detect an association, if it exists. Use of dietary,
occupational, and other exposure data in the analyses, along with an additional 2 years of subject
accrual, will make the completed study for which this constitutes an interim report even more
valuable.  As it stands, however, this study is already the largest and most useful case-control
study available.  Its high quality and the reasonable consistency of the evidence across sources of
ETS exposure strongly support an increase in lung cancer incidence associated with passive
smoking.                                               .

A.4.8. GAO(Tier3)
A.4.8.1. Author's Abstract
       "A case-control study involving interviews with 672 female lung cancer patients and 735
population-based controls was conducted to investigate the high rates of lung cancer, notably
adenocarcinoma, among women in Shanghai.  Cigarette smoking was a strong risk factor, but
accounted for only about one-fourth of all newly diagnosed cases of lung cancer. Most patients,
particularly with adenocarcinoma, were lifelong nonsmokers.  The risks of lung cancer were
higher among women reporting tuberculosis and other preexisting lung diseases.  Hormonal factors
were suggested by an increased risk associated with late menopause and by a gradient in the risk
of adenocarcinoma with decreasing menstrual cycle length, with a threefold excess among women
who had shorter cycles. Perhaps most intriguing were associations found  between lung cancer and
measures of exposure to cooking oil vapors.  Risks increased with the number of meals cooked by
either stir frying, deep frying, or boiling; with the frequency of smokiness during cooking; and
with the frequency of eye irritation during cooking.  Use of rapeseed oil, whose volatiles
following high-temperature cooking may be mutagenic, was also reported more often by the
cancer patients. The findings thus confirm that factors other than smoking are responsible for the
high risk of lung cancer among Chinese women and provide clues for further research,  including
the assessment of cooking practices."

A.4.8.2.  Study Description
        This study was undertaken in Shanghai, China, during  1984-86 to explore reasons for the
high rates of lung cancer among women in Shanghai.  Potential etiologic factors associated with
the high occurrence of adenocarcinoma among females in  a population where few women smoke
cigarettes is of particular interest. Several potential risk factors, in addition to exposure to ETS,
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 are investigated.  These are included in the abstract above. Smokers are included in the study as
 well as nonsmokers.
       A special reporting system for lung cancer linked with the area's medical facilities was set
 up for the study period, integrated with the Shanghai Cancer Registry. Incident cases of lung
 cancer occurring among 35- to 69-year-old female residents of urban Shanghai from February
 1984 to February 1986 were interviewed by trained study personnel. Controls were women
 selected from residents of the urban Shanghai community by stratified random sampling designed
 to mimic the age distribution of Registry-reported lung cancer cases during 1980-81. It is not
 clear whether cumulative or density sampling was employed.
       Face-to-face interviews were conducted with 672 cases and  735 controls. No cases refused
 to be interviewed, but 93 died before interview and were  therefore excluded; it is not mentioned
 whether there were any refusals among potential controls. Nonsmokers composed 436 of the cases
 and 605 of the controls. In the total subject population, distribution of age, education, and
 marital status between cases and controls is described as similar, except for a larger proportion of
 controls (32% vs. 20%) in the oldest age group (65-69 years).  The age distribution in the ETS
 population alone is not described.
       ETS exposure is based on living with a smoker.  For general  exposure in childhood or
 adulthood, exposed subjects are those who ever lived with a smoker. For spousal smoking alone,
 however, women are ETS exposed only if they lived with a smoking husband for at least 20 years.
 General ETS exposure sources include all household members but not coworkers. Verification of
 exposure data was not mentioned. Based on the reported exposure criteria, widows  and divorcees
 would have been included in the spousal smoking data set, whereas never-married women would
 have been excluded.
       For ETS subjects, 246 (375) cases (controls) from the total of 672 (735) cases (controls) are
 included in Table II of the article  that lists the number of cases and controls by number of years
 lived  with a smoking husband. Presumably, the 190 cases and 230 controls not included in the
 table are unmarried (or never-married) and do not include women married and living with a
 nonsmoker; no explanation is provided in the article.
       Among nonsmoking women included in.Table II, 189 out of 246 cases and 276 out of 375
 controls had lived with a smoking husband for at least 20 years. These subjects were divided into
exposure categories of 20 to 29, 30 to 39, and 40 or more years for comparison with the
"unexposed" (< 20 years spousal smoking) subjects. The  authors present no unadjusted analyses,
but calculations from their raw data yield an overall odds ratio of 1.2 and stratum-specific odds
ratios of 1.2,  1.3, and  1.1 for 20 to 29, 30 to 39, and 40 or more years of exposure, respectively.
Age-  and education-adjusted odds ratios increase with the number of years exposed:  1.1 (95%
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C.I. = 0.7, 1.8) for 20 to 29 years, 1.3 (0.8, 2.1) for 30 to 39 years, and 1.7 (1.0, 2.9) for 40 or more
years.  The authors report an odds ratio of 2.9 (1.0, 8.9) for squamous and oat cell cancer for 40
years of exposure or less but present no other type-specific results.
       Information on cell type is available for the 542 (81%) study cases diagnosed by histology
or cytology; the rest of the cases  were diagnosed by radiological or other means.  Diagnostic
evidence was reviewed by a team of pathologists and clinicians.  For the lung cancer cases
histologically typed, adenocarcinoma (61%)  greatly predominates, followed by squamous (22%),
small cell (6%), and other (11%) types.  No breakdowns of tumor type are provided for the ETS
group.
       The authors conclude that ETS may account for some, but probably few, of the cancers
among nonsmokers, because there was little or no association with ever having lived with a
smoker.  Among nonsmoking women married to smokers, however, there was an upward trend in
risk associated with increasing years of exposure.  This latter finding is consistent with reports in
other parts of the world. Little evidence was found to implicate the type of fuels used for
cooking in lung cancer risk; occupational factors did not appear  to be important, nor did familial
tendency to lung cancer. Our data suggest,  however,  that prior lung diseases, hormonal  factors,
and cooking practices may be involved.  Most provocative is the association with cooking oil
volatiles, and further investigations are needed to evaluate their  contribution to the high lung
cancer rates among Chinese women in various parts of the world.

A.4.8.3.  Comments
       The number of ETS subjects for analysis is relatively large. Unfortunately,  the study is
unmatched, with  no demographic breakdown of the cases and controls, either for the whole study
or for the ETS subjects alone.  Controls were selected to make their age distribution similar to that
expected for cases in the whole study, but the similarity  may not apply to ETS subjects alone.
Consequently, there is little basis for evaluating the comparability of cases and controls. Age and
education were adjusted for in the analyses, which has some compensatory value.
       The use of direct interview with all subjects without reliance on proxies to gather exposure
information should enhance the  validity of  the exposure comparisons. On the other hand,  the
possible use of unblinded interviewers could have biased results. In light of the lack of  association
noted for passive smoke exposure as a child or adult,  however, it is unlikely that such a  bias
produced the observed association between  spousal smoking and lung cancer. For evaluation of
spousal smoking, the reference group can hardly be classified as "unexposed" to spousal  smoking
because it includes women who lived with a smoking husband for  up to 20 years. The
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investigators probably selected the cutoff level of exposure for their spousal smoking reference
group to balance the numbers in each exposure category, as a practical matter. The reference
group contains an undisclosed number of women who may have been exposed to spousal smoking
for many years,  potentially creating a substantial bias toward the null hypothesis (no association
between ETS exposure and lung cancer).  Consequently, the odds ratios may be biased downwards.
The relative comparison across years of spousal smoking, however, is not affected.  An increasing
trend in the odds ratio was observed, but no statistical test for trend  is cited.  In a similar vein, it
appears that active smokers may have been included in  the data analysis of overall ETS exposure.
That factor, in combination with the use of ever- versus never-exposed classifications without
regard to degree or duration of ETS exposure in the analyses, may have reduced the likelihood of
detecting any positive association that may exist.
       The study appears to have focused on potential risk factors other than ETS.
Unfortunately, the effects of these other factors on the  ETS results were not explored, even
though many of these appeared to be stronger risk factors than passive smoking.  Some factors,
such as  age and education,  were adjusted for in all analyses.  Control for education should in turn
produce a degree of adjustment for factors related to socioeconomic  status (e.g., dwelling size and
quality of diet).
       Overall, the study presents evidence of a mild duration-dependent association between
lung cancer and  spousal smoking that skirts statistical significance. Several sources of
misclassification bias are possible, but most would tend  to bias the odds ratio downward.  The
study was not, however, specifically designed to evaluate the ETS-lung cancer hypothesis.
Information was collected and analyzed on a number of other potential risk factors, but they were
not adjusted for in the analysis.  Coupled with other limitations, this omission  reduces the weight
of the study's results with regard to ETS,  although they support an increase in lung cancer risk
with spousal smoking.

A.4.9. GARF (Case-Control) (Tier 2)
A.4.9.1. Author's Abstract
       "In a case-control study in four hospitals from 1971 to 1981,  134 cases of lung cancer and
402 cases of colon-rectum cancer (the controls) were identified in nonsmoking women. All cases
and controls were confirmed by histologic review of slides, and nonsmoking status and  exposures
were verified by interview. Odds ratios increased with  increasing number of cigarettes smoked by
the husband, particularly for cigarettes smoked at home. The odds ratio for women whose
husbands smoked 20 or more cigarettes at home was 2.11 (95% C.I. = 1.13, 3.95).  A logistic
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regression analysis showed a significant positive trend of increasing risk with increasing exposure
to the husband's smoking at home, controlled for age, hospital, socioeconomic class, and year of
diagnosis. Comparison of women classified by number of hours exposed a day to smoke in the
last five years and in the last 25 years showed no increase in risk of lung cancer."

A.4.9.2.  Study Description
       This study was undertaken in New Jersey and Ohio to investigate the  relationship of
involuntary smoking to primary lung cancer.  All data were collected specifically for this study,
and only nonsmokers were included as subjects. Cases are the lifelong nonsmoking women
histologically diagnosed with primary lung cancer during 1971-81 in four participating New
Jersey and Ohio hospitals. Controls selected from patients with colorectal cancer were matched
3 to 1 to  a case  on hospital and age (±5 years). Subjects were not restricted to incident cases, and
controls were apparently cumulatively sampled. Exposure data were obtained by blinded,
face-to-face interviews with subjects or their relatives.
       A total of 1,175 female lung cancer cases were initially identified from medical records.
Exclusion of women found to be current or former smokers or not to have histologically verified
primary lung cancer eliminated 1,041 of the identified cases, leaving 134 ETS subjects.
Interviews were conducted with patient, spouse, or child in about 75% of the subject population,
whereas the rest were conducted with another relative. The age distributions of  cases and controls
are nearly identical.
       ETS exposure includes pipe and cigar use as well as cigarette smoking. Three sources of
passive smoking are considered, which will be referred to as follows:  "exposure to husband's
smoke" means having a husband or other related cohabitant who smokes more than occasionally,
either (1) anyplace or (2) at home; "general exposure" applies to the smoke of others at home,
work, or otherwise who have smoked more than occasionally during the past (1)5 years or (2) 25
years; and "childhood exposure" refers to experiencing ETS from any source during childhood.
Husband's smoking is quantified as cigarettes  per day and years  smoked; general exposure is given
as average hours per day; and childhood exposure is treated as a dichotomous variable.  Only 57
percent of the cases were women living with a husband at the  time of diagnosis.  No checks on
exposure status are described, and no classification of subjects by marital status was implemented.
Adenocarcinoma (87) predominates among lung cancer cases, followed by large cell (21), small cell
and miscellaneous (15),  and squamous cell cancer (11); no data on airway proximity are provided.
       Ninety of 134 cases were exposed to husband's (or other  relative's) smoking at home,
compared with  245 of 402 controls, giving a crude odds ratio of 1.31 (reported 95% C.I. = 0.99,
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1.73; C.I. calculated by reviewers is 0.87, 1.98). For husband's smoking of 20 or more cigarettes
per day, the highest exposure category, the odds ratio increases to 2.11 (1.13, 3.95).  Husband's
smoking averaged 11.5 cigarettes per day for the exposed subject. For husband's smoking
anyplace, 91 of 134 cases and 254 of 402 controls  were exposed, giving a crude odds ratio of 1.23
(0.94, 1.60). At the highest exposure category, 40 or more cigarettes per day, the odds ratio is 1.99
(1.13, 3.50). Cigar and pipe smoking alone yields odds ratios of 1.17 and 1.13 for husband's
smoking at home and anyplace, respectively. There are statistically  significant trends  for both
husband's smoking at home and for smoking anyplace when measured by cigarettes per day, but
not when evaluated by number of years smoked.  The odds ratio for ETS exposure from husband's
smoke, both total and at home, is calculated by source of interview respondent for the categories
of "self," "husband," "daughter or son," and "other." It is readily apparent that the excess risk is
attributable to "daughter or son," with some contribution from "other." None of the excess risk is
attributable to "self or "husband."
       General smoke exposure also shows an association with lung cancer.  Exposure over the
past 5 and past 25 years yields odds ratios of 1.28  (0.96, 1.70) and 1.13 (0.60, 2.14), respectively.
The odds ratios do not increase with increasing level of exposure, however, and none of the
association's is statistically significant. No association was found between childhood smoke
exposure and lung cancer (OR = 0.9, 0.74-1.12).  When the odds ratio is calculated by  source of
respondent, "other" and "self account for the excess risk when smoking for 5 years is the measure;
for 25 years of smoking, "other" and "daughter or  son" account for the excess risk.
       Stratification by cell type reveals that husband's smoking is much more strongly associated
with squamous cell (OR = 5.00, both for smoking  at home and anyplace) than adenocarcinoma
(corresponding ORs = 1.33 and 1.48);  no association with other cell types was detected.
Stratification by age and socioeconomic status suggests little effect of these variables on  the
results.  The results,  however, appear to be sensitive to whether the  interview data were  obtained
from the subject or a surrogate (offspring, relative, etc.), as noted above.
       A logistic regression analysis including adjustment for age, hospital, socioeconomic status,
and year of diagnosis was  undertaken for passive smoking.  Cigarettes per  day of husband's at-
home smoking is significantly associated with lung cancer, with an estimated relative risk of 1.7 at
exposure of 20 cigarettes per day compared to none.  In contrast, husband's smoking outside the
home is not significantly associated with lung cancer, although the estimated relative risk is 1.26
for 20 cigarettes per day.  General smoke exposure is not significantly associated with lung cancer,
for either the past 5 years or 25 years of exposure. Adjustment for  type of respondent reportedly
had no significant effect on the logistic regression results.
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A.4.9.3.  Comments
       The abundance of nonsmoking cases (134) and controls (402) in this study relative to most
ETS studies gives it above-average statistical power.  Comparability of cases and controls appears
good based on their very similar age distributions, matching on hospital and age, and restriction to
nonsmokers, although the lack of further demographic comparisons means that divergence on
some other factor(s) cannot be ruled out.
       A major difficulty in this study, however, arises from the extensive use of proxy
respondents.  Only 12% (16 of 134) of the case interviews were with the patient. In the stratified
analysis,  it was found that the husband's smoking at home is positively associated with lung cancer
only when the smoking information is provided by a son or a daughter rather than by the patient
or her husband. This leads to several possibilities.  Perhaps the son or daughter claimed that the
patient's  husband smoked when he actually did not, thereby shifting cases from the nonexposed to
exposed category and increasing the odds ratio, or the patient or her husband claimed that the
husband  did not smoke when actually he did, thereby shifting cases from the exposed to
nonexposed category and depressing the odds ratio.  In general, it is thought more likely that true
smokers are misclassified as nonsmokers more often than  true nonsmokers are misclassified as
smokers (see, for example, Lee, 1986, and Machlin et al.,  1989). Also, Machlin indicates that
proxies tend to misclassify smokers no more often than smokers themselves do. Thus, it may be
that the son or daughter data are better than the self or husband data.  Alternatively, the
difference among the reporting sources may be due only to chance; the results in JANE on self or
proxy reports are quite the opposite of those in this paper, with the proxy reports (in this case
including the spouse) leading to lower odds ratios than the self-reports.
       Another possible problem with this study is the use of colon and rectal cancer cases as
controls on the theory that these diseases are not smoking related.  A recent paper, Zahm (1991),
notes that associations have been found between smoking  and these cancers. If these associations
carry over to  passive smoking, they might bias the result downward.
       In general, the detailed results from the stratified  analysis in Table 6 of the paper exhibit
considerable variation, probably caused by chance. Hence, the overall results in Table 5 of the
article, where all the cases and controls are used, may be the most reliable. They indicate an odds
ratio of 1.31 (1.24 after adjustment for smoker misclassification bias in the body of this report)
for exposure to all types of husband's smoking at home.
       The study's exposure assessment methodology is strengthened  by the attempt to maintain
blinding  by not informing interviewers of the study hypothesis or the subjects' disease status.
This is impractical in most studies, but given the use of controls who also have cancer and a high
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proportion of proxy interviews, effective blinding of interviewers and subjects may have been
largely achieved here.  Detailed data on smoke exposure at home as well as elsewhere, including
pipe and cigar smoking, were collected. Pipe and cigar smoking are often not considered in ETS
studies, thus constituting a potential source of exposure misclassification, and smoking at home
should be a more meaningful index of smoke exposure than total smoking. What the authors
termed "husband's smoking" actually includes smoking by related cohabitants as well. Presumably,
this was done both to increase subject numbers (by not excluding unmarried women) and to
enhance detection of passive smoke exposure. However, it could cause some oversight with regard
to classification of ETS exposure (e.g., a widow, living with a nonsmoking sister, whose husband
had been a heavy smoker). Less understandable is the failure to include smoking by unrelated
cohabitants and the inclusion of single women living alone.  Diagnostic misclassification  is
unlikely given the histological verification of all cases and controls.
       Both husband's at-home and total cohabitant smoking are associated with lung cancer, the
association being stronger for at-home smoking.  Both exposures show a statistically significant
general increase in association with level of smoking, with substantial associations only at high
levels. The adjusted association for at-home cohabitant  smoking is much stronger (OR = 1.7;
p = 0.03) than that for smoking outside the home (OR =  1.3; p = 0.13), a pattern consistent with
home smoke exposure rather than some other smoking-related factor as the basis of the observed
results. General ETS exposure, in contrast, was inconsistently related to lung cancer in the
unadjusted analyses, with a stronger association for  exposure within the last 5 years than within
the last 25 (possibly attributable to better recall).  No dose-response  pattern is evident, however,
and no association was found in the adjusted analyses.
       The adjusted analyses include age, hospital, socioeconomic status, and year of diagnosis in
a logistic regression model, along with the passive smoking variable. This adjustment did not
significantly reduce the association between  husband's smoking at home and lung cancer observed
before the adjustment, but it did eliminate any association with  general ETS exposure.  Thus, the
results for husband's smoking at home are probably  not biased due to influences of age,
socioeconomic status, hospital, or temporal variables.  Dietary factors, heating and cooking
practices, and family history of cancer were  not considered as modifying risk; thus, an effect by
one or more of these factors cannot be ruled out.
       The heavy reliance on proxy respondents and their uncertain impact on the analysis leaves
some uncertainty in interpretation.  On the favorable side of this issue,  the authors'  attempt to
blind subjects and interviewers to the study hypothesis lessens the likelihood of potential bias
from proxy response, and no significant effect due to respondent type was found in the adjusted
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analyses. Some of the exposure categories seem vague, but this would tend to reduce the
magnitude of the observed association rather than to give rise to one.  In summary, this study is
suggestive of a dose-dependent association between smoking in the home and lung cancer, with
reservations due to the use of proxies.

A.4.10. GARF(Coh) (Tier 3)
A.4.10.1.  Author's Abstract
       "Lung cancer mortality rates were computed for nonsmokers in the American Cancer
Society's (ACS) prospective study for three 4-year periods from 1960 to  1972 and in the Dorn
study of veterans for three 5-year periods from 1954 to 1969.  There was no  evidence of any trend
in these rates by 5-year age groups or for the total groups.  No time trend was observed in
nonsmokers for cancers of other selected sites except for a decrease in cancer of the uterus.
Compared to nonsmoking women married to nonsmoking husbands, nonsmokers married to
smoking husbands showed very little, if any, increased risk of lung cancer."

A.4.10.2.  Study Description
       This study examines the role of passive smoking in lung cancer among married women in
the United States. It uses data collected in a large prospective study initiated by Cuyler Hammond
of the ACS in 1959. The ACS's objective was to evaluate the association between potential cancer
risk factors and cancer mortality. Although data  were collected on the smoking status of women
and their spouses at the start of the study, Hammond thought the study data should not be used to
estimate lung cancer death rates in relation to amount of passive smoking by  female never-
smokers. Specifically, Hammond notes that the study was not designed for that purpose, and no
special information on the subject was obtained; information was available on the smoking habits
of the husbands of many of the married women in the study, but not on  the smoking habits of the
former husbands of women who were widowed, divorced, separated, or married for a second time.
More important is his statement that women  in America at that time were not generally barred
from public and social gatherings where men were smoking, and working husbands who smoked
generally did much if not most of their smoking away from home (Hammond and Selikoff, 1981).
Similar reservations  are expressed by Garfinkel, who also notes that 13% of the women
nonsmokers who  died of lung cancer in the ACS study reported that they were previously married
and that the classification of their exposure to their husbands' smoking may not be pertinent
(Garfinkel, 1981, p. 1,065).
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       A total of 29 ACS divisions encompassing 25 states took part in the study; participating
counties were in turn selected by division leaders based on feasibility.  Data collection was
undertaken by networks of volunteers set up within participating counties. Recruitment of
subjects and subsequent followup monitoring were undertaken by volunteers who were instructed
to enlist qualifying acquaintances.  Subjects were restricted to persons more than 30 years of age
whose household contained at least one person over 45 years of age.  Illegal immigrants and
persons who were illiterate, institutionalized, or itinerant were excluded. Detailed questionnaires
were distributed to subjects and all members of their household over 35 years of age.  These
questionnaires covered factors such as diet, alcohol consumption, and occupational exposures as
well as smoking habits, but they did not address passive smoke exposure. Volunteers who
recruited subjects were given responsibility for tracing the subject's vital statistics for the next 6
years and contacting living subjects again in 1961,  1963, and 1965 to complete a questionnaire on
changes in smoking habits. Alternate researchers were appointed as necessary to replace
volunteers who moved or quit.  Finally, death certificates  were obtained for subjects reported
deceased; where death due to cancer was indicated, verification was sought from the certifying
physician. Although followup initially ceased with 1965, in 1972 an additional followup was
initiated in 26 of the original 29 ACS divisions and terminated in September 1972.

A.4.10.3. Comments
       The passive smoking study being described was undertaken  by assembling a subcohort of
married women who reported that they had never smoked and whose husbands completed a
questionnaire including smoking habits. This subcohort totaled 176,739 women out of the 375,000
never-smoking women enlisted  by the ACS in 1959. Women Were divided into three exposure
categories based  on their husband's smoking status—nonexposed for never^-smokers, and low
(high) for current smokers of less  (more) than 20.  Wives of former  cigarette smokers and men
who smoked cigars or pipes rather than cigarettes were excluded (Garfinkel, 1984); presumably,
these had already been excluded from the reported total (176,739).  Mortality rates were computed
by 5-year age intervals for unexposed women (i.e., wives of nonsmokers), from which the
expected number of deaths for exposed women was estimated under the hypothesis that spousal
smoking does not affect lung cancer mortality.  The ratio of observed to expected deaths in  the
exposed group provides an age-standardized mortality  ratio.  This mortality ratio is 1.27 (95% C.I.
» 0.85, 1.89) for spousal smoking of under 20 cigarettes per day (low exposure) and 1.10 (0.77,
1.61) for over 20 cigarettes per day (high exposure).
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       In a separate analysis, women healthy at the start of followup were divided into groups
matched on age (5-year grouping), race, education, urban or rural residence, and occupational
exposure of husband to dust, fumes, or vapors.  Each of these matched groups was then
subdivided into zero, low, and high exposure categories. The proportion of observed deaths in
each category was multiplied by the proportion of subjects in the smallest category of the matched
group relative to that category.  This "adjusted" number of deaths was then summed across all
groups with a given exposure and compared with the corresponding value for the unexposed (zero
exposure) category to provide a mortality ratio.  In addition, we conducted a Mantel-Haenszel
analysis of mortality using data supplied by Garfinkel that yielded results similar to the author's
analyses.  Ages 35 to 39 and 70 to 79 were excluded  due to insufficient numbers. After stratifying
by age and correcting for time under study, the calculated lung cancer risk was greater in subjects
whose  husbands smoked, but the predicted risk at low exposure  was greater than at high exposure.
It is notable, however, that the lower risk at higher exposure is entirely attributable to the 50- to
59-year-old age group; otherwise, predicted mortality would be equivalent at the low and high
exposure (see Table C-1 of the report under discussion).
       The original ACS cohort study was a massive undertaking. By using it as the basis of his
cohort, Garfinkel was able to assemble a very large number (more than 170,000) of never-smoking
married women. A cohort of this magnitude attains a number of lung cancer cases ordinarily
feasible only by means of a large case-control study, while avoiding the attendant pitfalls of
potential recall and interviewer bias associated with  case-control studies. There are several
important limitations, however, that make the results of this study difficult to interpret. The ACS
study was not designed to yield a representative sample of the general population.  The sample of
women is older (all at least 35 years of age, two-thirds between  40 and 59 at start of followup),
more educated (only 5.6% were limited to a grade school education), and contains a much smaller
proportion of ethnic minorities (only 6.8% nonwhite) than the general population (Stellman and
Garfinkel, 1986).  Although not representative of the population as a whole, the relative
homogeneity of the subject population does reduce the potential for complications of
interpretation that differences in ethnic or socioeconomic factors or both may pose, and it
increases efficiency by not including subjects belonging to age groups unlikely to experience
significant mortality during followup.  Overall, the study population's unrepresentativeness
strengthens rather than undermines the study's conclusions. It would have been useful, however,
to confirm that exclusion of greatly underrepresented groups, such as nonwhites and persons with
no formal education beyond the eighth grade, had no effect on the results.
       Because the data on smoking habits were collected prospectively, no information on
exposures prior to 1959 was obtained.  Exposure history for the years before 1959 may be as
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important as for the 12 years of followup, however, if lung cancer has a long latency period, such
as 20 years or so. Inclusion of persons whose exposure status may have changed markedly by 1959
could be a biasing influence.  Neither were changes in exposure status during the followup period
considered, despite the availability of data on smoking habits in 1961, 1963, 1965, and 1972.  In
fairness to the author, keep in mind that our comments are directed at evaluation of the study for
its contribution to the issues of passive smoking and lung cancer, although the ACS study was not
designed to assess ETS exposure. The only data collected on ETS exposure are based on the
spouse's current smoking habits at initiation of the study. If the ACS study had been directed at
evaluation of health effects of ETS, these issues would likely have  been taken into consideration
to sharpen the classification of subjects with respect to ETS exposure.  Overall, the likely
consequence of these factors is to reduce the sensitivity of the study to detect an association
between lung cancer and ETS exposure, but the potential for bias in the direction of a false
positive cannot be ruled out.  For example, if wives of smokers are more likely to become active
smokers during followup than wives of nonsmokers, these changes in smoking status could bias
results toward finding a positive association with passive smoking.  (Relevant to this particular
example, the authors state that "very few" subjects reported a change in their smoking status, but
provide no further details. Also, 12 or fewer years is a short exposure to produce lung cancer. It
is thus probable that any bias introduced by active smoking would  be minor; furthermore, the fact
                                                                   i
that a stronger association was observed for low than for high levels of spousal smoking argues
against a confounder associated with spousal smoking. Nevertheless, potential sources of  bias may
be present that influence the study outcome in either direction.)
       During 1959-65, confirmation of primary lung cancer diagnosis was obtained from
physicians for 78% of all cancer cases. Among 203 cases of lung cancer in nonsmoking women
diagnosed by death certificate, confirmation attempts on an unspecified number of these  cases
found  34 misdiagnosed as primary lung cancer, whereas 10 primary lung cancers were discovered
among cancers diagnosed as nonlung on death certificates. Thus, it appears that only about 85%
of the  death certificate diagnoses of primary lung cancer were accurate, while a small percentage
of primaries were misdiagnosed as cancers of other sites. No confirmation of diagnoses was
undertaken during the period after 1965 when nearly two-thirds (119 out of 182, according to
data supplied to reviewers by Garfinkel) of the lung cancer deaths in the ETS study population
were reported.  In light of the misdiagnosis rates found for 1959-65, it is likely that a substantial
percentage of the study's reported primary lung cancers in cases actually arose in other sites,
whereas a substantial percentage of reported cancers of other sites  actually arose in the lung.  The
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resultant errors in subject classification probably bias the results toward no association (i.e., a false
negative conclusion),//a positive association actually exists.
       Loss of subjects to followup is another source of potential bias. A subsequent report on
the ACS cohort (Garfinkel, 1985) states that, whereas more than 98% of the original cohort was
successfully traced through 1965, more than 10% (3 of 29) of the original ACS divisions declined
to participate in the  1971-72 followup effort.  In the study now under review, Garfinkel reports
successful followup of 98.4% through 1965 and 92.8% through 1972, apparently not considering
subjects in the division who declined to participate in the extended followup as losses. It thus
appears that, whereas more than 98% of the original cohort was successfully followed up through
1965, less than 90% of the cohort was targeted for followup through 1972, and losses for this
targeted group approached 7%. Such losses not only reduced the number of observed deaths—
and, hence, the study's power—but introduced the possibility that differential loss to followup
could have distorted the study's results. A greater proportion of losses among exposed subjects
than among unexposed could partially mask a true positive association, whereas greater loss  among
the unexposed could potentially create a spurious association.
       Aside from the issues above, the study controls for  risk modifiers. Subjects were all of the
same gender and marital status, and age was controlled for  in all analyses. Analysis by groups
matched on race, education, residence, and occupation, along with age, produced nearly identical
results as the analyses standardized by age alone, indicating no confounding due to these and
unlikely confounding due to other socioeconomic, occupational,  or geographic factors.
       In summary, this study predicts a weak positive association between spousal smoking at
levels of 1  to 19 cigarettes per day and lung cancer, but only  slight association at higher exposure
levels; neither association is statistically significant. The lack of apparent dose-response pattern
undermines the association, but the confidence intervals of the point estimates for the high- and
low-exposure groups overlap so broadly that the existence of a dose-response relationship cannot
be ruled out entirely. Meaningful interpretation of the results for the issue of ETS exposure and
lung cancer, however,  is limited.  Because the study's objectives  were directed elsewhere, the data
collected on ETS exposure are limited to the status of spousal smoking at the start of the study.
Past history and future changes in status are not well addressed.  There is ample indication that
death certificate diagnoses are not a reliable source for the  selection and classification of subjects.
Although a second 6-year followup period was undertaken to increase the followup period to 12
years, its success was limited by incomplete participation and, perhaps, by organizational
difficulties related to long-term reliance on volunteers (who may relocate, change interests,  lose
contact with the subjects originally enlisted over an extended period, etc.).  Even if the followup
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were entirely successful, however, 12 years of followup without regard to exposure experience is
not a particularly long period to evaluate the lung cancer potential for ETS because the latency
period associated with active smoking may be on the order of 20 years. Although the ACS study
has been an important contribution to its main study objectives, the limited exposure information
and other potential sources of bias for the issue of passive smoking and lung cancer leave its
assessment in question.

A.4.11. GENG (Tier 4)
A.4.11.1. Author's Abstract
       Not included in source.

A.4.11.2. Study Description
       This study was conducted in Tianjin, where China's highest incidence of female lung
cancer occurs, to illustrate the relationship between cigarette smoking and lung cancer in females.
The study explores both active and passive smoking, so the analyses for passive smoking apply to a
subgroup of the larger subject population. The source of the study's subjects and the time over
which they accrued are not specified. Subjects resided in Tianjin for more than 10 years.  The
source of controls is not given, but they consist of females pair-matched with cases on race, age
(±2 years), marital status, and birthplace. It is unclear from the article whether cases were
incident or prevalent and how controls were obtained.  A draft summary description of this study
(Liang and Geng, undated) from Liang indicates,  however, that hospitalized cases (96) were
matched with inpatient  controls and that general population cases (61) were matched with
neighborhood controls.
       The source of the study's exposure data is  not clearly stated, but the draft from Liang
indicates that all identified cases and controls were interviewed.  No information on collection or
verification of smoking or other data is provided.  The  authors state that cases and controls do not
differ significantly in age, education, occupation, race, marital status, birthplace, or residence,
but this refers only to the total study population of 157 cases and 157 controls that includes active
smokers; the same similarity may not hold for the  54 cases and 93 controls used in the passive
smoking analysis.  Tumor types are provided for 85% of the total case population but not
specifically for the passive smoking subpopulation; adenocarcinomas (36.9%) predominate, being
about twice as common  as squamous (22.3%) or small cell (19.7%) tumors. Although nearly 85% of
the total cases were diagnosed histologically or cytologically, it does not appear that verification of
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diagnosis or primary status of tumor was undertaken by the authors, and no information on tumor
distribution is supplied.
       A nonsmoker (which usually means never-smoker) is ETS exposed if the spouse smokes.
Presumably, women  not currently married are excluded from the analysis, although they could
have been included with some assumption  made regarding their exposure status. Information on
dose and duration of exposure was collected but not used  in the passive smoking analysis, and it is
not indicated if cigar or pipe smoke was included.  ETS exposure from parents and colleagues is
reported to have been evaluated. The parental smoking referred to is apparently in adulthood, as
cohabitants in the home, but that is not made explicit. Exposure during childhood was not
specifically addressed.
       Among the ETS subjects, 34 of 54  cases and 41 of 93 controls were exposed.  This yields a
statistically significant crude odds ratio of 2.16 (95% C.I. = 1.03, 4.53) for husband's smoking.  No
analyses adjusted for age or other factors are reported. On a rather confusing note, an odds ratio
of 1.86 is cited twice later, but that value is inconsistent with the odds ratio of 2.16 from the raw
data.  Whether this is an error or the product of an unspecified adjustment by conditional logistic
regression, which the authors employ for other purposes throughout the paper, is unknown.  The
odds ratio increases with the number of cigarettes smoked per day by the husband  and with the
duration of the husband's smoking.  The odds ratios for smoking rates of 1 to 9, 10 to 19, and 20
or more cigarettes per day are 1.4, 2.0, and 2.8, respectively. For 1 to 19, 20 to 39, and 40 or
more years of exposure, the odds ratios are 1.5, 2.2, and 3.3, respectively. No tests for trend are
cited, and the relevant data are not given.  Consideration of ETS exposure from smoking  by
father, mother, or "colleagues" reportedly yielded no results that are "quite significant." No
further details are provided, and it is not clear whether these results consider past smoking status
or apply only to current status.
       The authors conclude that active and passive smoking are the most important risk factors
for female lung cancer in Tianjin.  They attribute 35% to  42% of lung cancer occurring in their
nonsmoking female population to passive smoking. Female lung cancer also is found to be
associated with other factors, such as occupational exposure, with an odds ratio of  3.1 (95%
C.I. = 1.58, 6.02); history of lung disease, with an odds ratio of 2.12 (95% C.I. = 1.23, 3.63); and
cooking with coal, where the odds ratio increases with the duration of exposure from 1.5 to 5.5
(see Table 8 of this reference).
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A.4.11.3.  Comments
       The quality of this study is difficult to assess given the dearth of details supplied by the
authors. Certainly the number of nonsmoking cases and controls included is more substantial than
in some other studies, and the reported association between passive smoking and lung cancer is
statistically significant.  Questions regarding the mechanics of data collection and analysis,
however, remain unanswered.
       Exposure and other data were obtained from hospitalized subjects at bedside and from
others in their homes. Apparently no information was obtained from proxy sources; the number
of cases (or controls) who could not be  interviewed is unspecified. No blinding was employed,
but that may not have been feasible. Despite the reported similarity of the demographic
characteristics of the total case and control populations, dissimilarity cannot be ruled out within
the subgroup used for ETS analyses. Although the whole study, including active smokers, is
matched on several variables, that matching need not apply to the  ETS subjects alone.
       Lack of validation of diagnostic and exposure information may have led  to substantial
misclassification, although the fact that 85% of the lung cancer diagnoses were obtained via
histology or cytology suggests that diagnostic misclassification would not have been extreme.
Lack of consideration of former smoking status is a potential problem.  Inclusion of former
smokers among the nonsmokers, in combination with a tendency for former smokers to marry
smokers, could produce an upward bias in the odds ratios.
       Finally, although the crude odds ratio of 2.16 for passive smoking is statistically
significant, it does not take into account even the most basic potential confounder—age.  For the
larger case-control population (including smokers), occupational exposure (OR = 3.1), history of
lung disease (OR = 2.64), and cooking with coal (OR = 1.54-5.56,  rising with cumulative
exposure) are statistically significant risk factors that the authors claim have joint effects with
smoking, yet the ETS analysis is not adjusted for these likely confounders.  The anomalous odds
ratio of 1.86 given later in the results may have been adjusted for age or other factors, but there is
no way to tell.  Also, the detection of an effect of ETS would be unexpected if the  study area
suffered from high environmental levels of carcinogenic combustion products of coal,  as seen in
LIU and WUWI.  Although the literature contains no studies of Tianjin, Beijing is nearby. Zhao
(1990) reports that mean levels of a urinary indicator of polyaromatic hydrocarbon  exposure
(1-HP) in nonsmoking housewives are  much lower in Beijing than in Shenyang, one of the WUWI
study sites, but Wang (1990) found that indoor air pollution, principally due to coal burning,
sometimes masks the effect of active cigarette smoking.
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       In summary, the study's results are consistent with the hypothesis that passive smoking
increases the risk of lung cancer, but they are not definitive. More detail regarding the mechanics
of the study is needed to assess its general validity.  If warranted, a clearer and more complete
analysis of the study's data regarding passive smoking, including consideration of the information
on dose, duration, and potential confounders already available, would then be useful. For the
current evaluation of epidemiologic evidence on ETS exposure and lung cancer, too many
questions remain about  the design and execution of the study to properly interpret the data and
assess the authors' conclusions.

A.4.12.  HIRA(Coh) (Tier 2)
(Note:  Because of the many publications relating to this study, a different format of presentation
is used.)
       This cohort study and a later case-control study based on it were undertaken to explore the
relationship of passive smoking and other factors with lung cancer in Japanese women.  Subjects
and data used in this study were,  however, drawn from a larger study that was not designed to
investigate passive smoking.
       An exploratory study of mortality determinants targeting adults at least 40 years of age
inhabiting 29 health center districts in Japan was initiated in 1965.  In autumn of 1965, more than
90% of the target population was interviewed to ascertain the status of lifestyle factors that might
affect health (e.g., cigarette smoking, alcohol consumption, and occupation).  Individuals,
including husbands and wives, were interviewed separately. Followup of the interviewees was
conducted using a combination of an annual census of residents and death certificates to monitor
mortality. Mortality, as determined by death certificate, was the outcome variable.  Hirayama
used this study population to examine the potential effect of passive smoking on lung cancer
mortality. In 1981, he reported the results derived from the first 14 years of followup (through
1979) in the British Medical Journal.
       A total of 142,857 women were interviewed in 1965, of whom 91,540 were nonsmokers
whose husbands also had been  interviewed regarding smoking status.  Using their husbands'
smoking status as a surrogate for exposure to ETS, Hirayama calculated lung cancer mortality rates
for comparison of women married to smokers with women married to nonsmokers; rates also were
calculated using various strata of spousal smoking intensity (number of cig./day), as well as age
and occupation.  A total of 346 lung cancer deaths occurred in this cohort during the first 14 years
of followup.
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       After standardization for age and occupation, it was found that women whose husbands
smoked daily had a higher annual rate of lung cancer mortality than did women whose husbands
were nonsmokers or only "occasional" smokers. The rate increased with the level of smoking (e.g.,
8.7/100,000 annually for no or occasional smoking, 14.0 for smoking 1-19 cig./day, and 18.1 for
20+ cig./day). Higher rates and a dose-response pattern were observed in women married to
smokers after stratification on either husband's age or agricultural work status. Mortality due to
two diseases associated with active smoking, emphysema and asthma, was also higher in wives of
smokers and increased with exposure.  Conversely, mortality due to two cancers not linked to
active smoking, cervical and stomach cancer, was no higher in wives of smokers. Consideration of
husbands' drinking habits had no significant impact on mortality for lung cancer or other diseases
mentioned above.
       Further study results appeared in the October 3, 1981, issue of the British Medical Journal.
Among other things, results were presented by husband's age in 10-year intervals instead of 20-
year intervals and for 10 occupational categories instead of 2.  These tabulations revealed a
statistically significant overall association between husbands' smoking and lung cancer mortality
with a dose-response pattern (1.00 RR for nonsmokers plus former smokers, 1.44 RR for medium
smokers, and 1.85 RR for heavy smokers).  Also of interest was a breakdown of lung cancer
mortality and smoking habits in  greater detail for  both husband and wife. Notably, nonsmoking
husbands with smoking wives showed a higher lung cancer mortality rate (RR  = 2.94) than did
those with nonsmoking wives. Because nonsmoking husbands with smoking wives were rather
rare, however, the numbers in this stratum were low (only seven deaths); thus, the observed
association was not statistically significant.
        In 1984, Hirayama published results of an  additional 2 years of followup of his cohort in
Preventive Medicine. The same basic associations reported after 14 years  of followup for spousal
smoking and lung cancer remained after 2 additional years of followup.   Mortality rates increased
with increasing exposure after stratification by age of  husband, occupation, geographical area, and
time period during study; a trend had been reported after stratification for age of wife at start of
study only for ages 40 to 49 and 50 to 59.  It also was reported that the elevation of lung cancer
mortality in nonsmoking women married to smokers was significantly less among women who
consumed green-yellow vegetables daily (e.g., for spousal smoking of 20+ cig./day, the RRs for
disease mortality were 1.63 and 2.38). No such pattern was observed for ischemic heart disease.
In addition, a statistically significant excess of para nasal sinus cancer in nonsmoking wives of
smokers had been observed, which showed an apparent dose-response relationship across four
smoking categories,  culminating in an RR of  3.44 for  spouses of smokers of more than 20
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 cigarettes per day.  That effect dwarfed those related to social class and dietary factors that were
 also examined.
        In 1988, Hirayama reported the results of a case-control study nested within his cohort in
 Environmental Technology Letters. To explore the relationship of women's age at marriage as well
 as husbands' smoking status with lung cancer mortality, lung cancer cases occurring among
 nonsmoking women in the cohort study were contrasted with stomach cancer cases as controls.
 Including only women under 59 years of age at the start of the cohort, the study divided husbands'
 smoking into three categories—none, 1 to 19, and 20 or more cigarettes  per day. Age at marriage
 also was trifurcated in 19 or fewer, 20 to 23, and 24 or more years.  Apparently as a result of
 exclusion of women over the age limit or because of missing data, only  115 cases and 423 controls
 were ultimately compared out of the 200 lung cancers and 854 stomach cancers among the
 nonsmoking female cohort.  Adjusting for woman's age and husband's smoking category resulted
 in odds ratios for lung cancer of 4.95, 1.76, and 1.41 for the respective age-at-marriage groups;
 the first two of these odds ratios were statistically significant.  An additional comparison found
 that among  lung cancer cases, the mean age at first marriage to a smoking husband was nearly
 8 years less  than the mean age at start of smoking for active smokers.
        A greatly expanded nested study was presented in the following  year (Hirayama, 1989).
 The study was designed to explore the potential effect  of dietary habits  on the relationship
 between lung cancer and spousal smoking.  A "baseline" sample of 2,000 nonsmoking wives, aged
 40 to 69 at the start of the cohort study, with known spousal smoking habits was randomly
 selected from the available cohort of 90,458 for comparison with the 194 lung cancer cases
 occurring in equivalent subjects within the cohort.  After determining that the age distributions of
 the case and baseline groups were very similar within smoking categories, the combined
 population was stratified on daily versus less-than-daily consumption for each of five food types
 (green-yellow vegetables, fish, meat, milk, and soybean paste soup), and wives with smoking and
 nonsmoking husbands were contrasted to assess differences in dietary habits.  After adjustment
 for wife's age and husband's occupation, only daily meat consumption was significantly more
 common among wives of smoking husbands, and this was limited to smokers of 20 or more
 cigarettes per day. Calculation of odds ratios for dietary habits resulted  in a "significant" elevation
 only in daily fish consumers (OR = 1.365, 90% C.I. = 1.05, 1.77; Table IV).  A nearly significant
 lowering of the odds ratio was found in daily meat consumers.
       Finally, odds ratios were calculated for lung cancer adjusted by wife's age, husband's
occupation,  and each of the dietary habit categories in succession. A dose-response pattern was
observed between lung cancer and husband's smoking that persisted after adjustment for any of
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the five dietary factors. Odds ratios for the five dietary habit categories ranged from 1.42 to 1.69
for former smokers and smokers of 1 to 19 cigarettes per day and from 1.66 to 1.91 for smokers of
20 or more cigarettes per day compared with nonsmoking husbands.  The observed trend was
highly statistically significant, regardless of which factor was adjusted for in the calculation.

A.4.12.1. Chronology of Controversy
       Publication of Hirayama's initial 14-year followup results in  1981 provoked a sizeable
volume of commentary in the scientific literature. Following the release of updated results in
1983-84, the study attracted little controversy until the latter part of the 1980s, when criticisms
were directed at the study by a  number of authors. This process reached its culmination in
response to the EPA's release for external review of the document Health Effects of  Passive
Smoking: Assessment of Lung  Cancer in Adults and Respiratory  Disorders in Children,  which
placed considerable emphasis on Hirayama's results. An author-by-author, letter-by-letter
consideration of the arguments  regarding Hirayama's work would be dauntingly duplicative and
tedious.  Instead, the most-discussed concerns are highlighted below, followed by an overall
assessment of the study as it stands today.
Chronology of Selected Events Relevant to the Hiravama Cohort Study
Jan. 7, 1981   Results of cohort study are published in British Medical Journal (282:183-185).
Oct. 3, 1981   Comments and letters to the editor by Kornegay  and Kastenbaum (of the U.S.
              Tobacco Institute), Mantel, Harris, and DuMouchel, and MacDonald regarding Jan.
              7 article appear in British Medical Journal, along with the author's reply.
March 3-5    Hirayama presents updated results for his study cohort incorporating an
and July      additional 2 years of followup (for a total of 16 years) to the International Lung
10-15, 1983   Cancer Update Conference in New Orleans and the 5th World Conference on
              Smoking and Health in Winnipeg, Canada.
Dec. 17, 1983 Updated results of the cohort study are published in Lancet.
 1984
 1985
 1987
Results presented in conference of July 1983, and in summary form in Lancet later
that year, are published in full in Preventive Medicine. In addition, Hirayama now
reports a statistically significant increase in brain tumors with husbands' smoking.
In a roundtable discussion published in the same journal, Lee proposes that
misclassification of active smoking status may have biased Hirayama's results.
Another publication of results for the  16-year followup appears in Tokai Journal
of Experimental Clinical Medicine.
Hirayama includes previously published  study data  in a book chapter (Aoki et al.,
1987).
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 1988
 1988
1989
1989
Uberla and Ahlborn publish an article from the Proceedings of the Indoor Ambient
Air Quality Conference in London (which is essentially the same as an earlier
presentation at the 1987 Tokyo International Conference on Indoor Air Quality)
criticizing the Hirayama study on several grounds.  Their primary assertion is that
correction for the cohort's age distribution removes the apparent effect of spousal
smoking.
Hirayama publishes the  results of nested case-control study based on cohort study
data in Environmental Toxicology Letters.  Estimated risk of lung cancer is
reported to increase with earlier age of marriage to smoker.
Layard and Viren publish a paper presented at the Conference on the Present and
Future of Indoor Air Quality in Belgium. Making their own projections  of
expected deaths and estimating losses to followup, they conclude that mortality
rates were anomalously low and followup losses unacceptably high in the Hirayama
study.
Hirayama publishes nested case-control results in Present and  Future of Indoor Air
Quality. Positive association of husband's smoking and lung cancer with  dose-
response pattern is reported after adjustment for dietary variables.
A.4.12.2. Some Major Critical Works
       A basic point raised by MacDonald (1981) and others soon after publication of Hirayama's
initial results concerned the selection of the study's sample population.  It appeared that the
29 health centers included in the study were selected on grounds of convenience rather than to
provide a randomly sampled, representative cross-section of the Japanese population. The
resultant sample might thus be unrepresentative of the Japanese population as a whole.
       Hirayama replied in 1981 that "the satisfactory representativeness [of the study population]
 . . . with regard to demographic and social indices was confirmed after the survey."  He did not,
however, provide supporting data.  MacDonald (1981) contended  that the six prefectures from
which the sample was drawn are relatively industry-heavy.  Hirayama (1983a) presented data
showing  that 40,390 of the cohort's wives were married to agricultural workers, 19,264 to industry
workers, and 31,886 to "others," indicating some overrepresentation of agricultural areas. He later
(1990b) cited quality of incidence data, geographical diversity, and coverage of communities of
both urban and rural character as well as different dominant industries as key selection criteria.
Women aged 70 or more are clearly underrepresented,  composing less than 1% of the study's 40-
and-older nonsmoking female population; this aspect of the study will be addressed later.
       The  key problem arising from an unrepresentative sample is that it may limit
generalizability of results derived from that sample to the population as a whole. In lieu of good
reasons to think that the association between exposure  and disease would be  different in the study
population and the general population, however, the possibility of an unrepresentative sample

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assumes less importance.  Further, in this case, substantial numbers from each major geographical
and occupational element of the general population were included in the sample.  And, as will be
seen in the subsequent discussion, similar patterns of association were observed in a number of
demographic subgroups.
       Misclassification may occur in any  epidemiologic study.  Most of the critical commentary
has focused on potential misclassification of exposure status.  Because the study relies on
interview data to establish smoking status,  misreporting by interviewees may affect accurate
classification of both wives and their husbands' smoking habits.  It has been argued that women
are especially likely to misrepresent their smoking habits because smoking is considered less
socially acceptable for women than for men, particularly in Asian societies. Such misclassification
would tend to reduce the degree of association between passive smoke exposure and its effect(s) if
women in the "exposed" and "unexposed" groups were equally likely to misreport their own
smoking.  One of the most prominent criticisms leveled at the Hirayama study postulates a
differential misclassification of smoking status in women.  Peter Lee (Lehnert, 1984) raised the
argument that if women married to smokers are more likely to be (or to have been) smokers than
women who are married to nonsmokers, and a given percentage of smoking women claim to be
nonsmokers,  then purportedly nonsmoking wives of spousal smokers will include a higher
proportion of active smokers than wives of spousal nonsmokers. This will cause bias in the
direction of a positive association.  Arguments over the probable size of this bias have occurred
with estimated elevations in risk ranging from a few percent to around 50%, depending on
assumptions regarding the extent of misreporting, the risk inherent in active smoking, and the
degree of marital concordance between smokers (Lehnert, 1984; Wald et al., 1986; Lee, 1987a, b).
       Uberla and Ahlborn (1987) raised a number of points regarding the Hirayama study,
including those previously mentioned.  Citing the "severe selection bias by age," the authors report
that the increase in risk with spousal smoking disappears when this bias is corrected for.  The
study population in fact contained a very small proportion of women aged 70 or older (only about
!%)---so small that the rates generated by nonsmoking married women aged 70 or older are too
unstable to provide meaningful results. But by taking the negative results observed in this tiny,
unstable stratum of the cohort and weighting them to "correct" for the underrepresentation of this
age group, the overall association is made to disappear. Such a "correction" is meaningless.  In
addition, Hirayama (1990b) has noted that the authors inappropriately adjusted to the  total female
population rather than to the population of currently married females, and he characterized the
adjustment as "neither of scientific significance nor of creative value."
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       The authors also essentially take Lee's approach to the differential misclassif ication
problem and claim that a modest differential misclassification "leads to risk ratios of around
unity."  As seen previously, this argument is plausible but purely speculative—and potential biases
toward the null are ignored in this and other "corrections." The authors conclude that "the null
hypothesis ... is consistent with the Hirayama data in the same way as is the alternative." But
unless one applies the aforesaid "corrections," the Hirayama data are, in fact,  more consistent with
the hypothesis of association than with the null hypothesis.
       Layard and Viren (1989) estimated "projected" mortality rates for a cohort with the age
and time distribution found in the Hirayama cohort by applying "standard demographic life table
procedures" to year- and age-specific life table data from United Nations and Japanese sources.
They concluded that female all-cause and lung cancer reported rates were only 76% and 85%,
respectively, of projected values. In a separate analysis, the authors also "calculated the numbers
of person-years that would have been observed in the cohort if there had been 100% followup"
from the reported numbers of deaths. The assumptions used in this calculation are unstated. The
authors  then estimated, based on the difference between their person-years for  100% followup
and the  reported person-years, and an assumption that 8 years of observation were lost on average
for each person lost to followup over the 16-year course of the study, that approximately 10% of
the cohort was lost to followup.  Dismissing  other possible causes  of their estimated mortality
deficits, Layard and Viren conclude that "it  is possible that biases exist in the data which might
invalidate an observed relationship between  exposure  to ETS and  mortality."
       Acceptance of Layard and Viren's conclusions must start with acceptance of the validity of
their assumptions and calculations, not all of which are stated explicitly.  Beyond that, their
rejection of alternative explanations for the  difference between projected and reported deaths is
not convincing. For example, random sampling variation and regional variations in death rates are
both dismissed because neither could produce an effect as large as that observed, although the
authors' figures indicate that in combination they could well account for a sizeable portion  of the
difference. Likewise, the effect of admitting only (initially) "healthy" people to  the cohort is
dismissed based on the observation of "still very substantial cohort deficits in the last years  of the
study" without specification of how substantial such deficits were and ignoring the fact that a
pattern in which all-cause mortality is most  affected and cancer mortality least, as their
calculations showed, is the expected pattern  for an effect of selection of healthy individuals.
Finally, to produce a spurious association, a  bias must operate differently on the exposed (smoking
spouse)  and unexposed (nonsmoking spouse) groups, and no evidence is provided that supports
such a pattern.  In fact, Hirayama (1990b) reported an approximately 8%  loss to followup for the
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whole cohort, which did not differ significantly by male smoking status.  Lacking a pattern of
differential loss, the most likely effect of loss to followup is a reduction in the observed
associations due to missing mortality events.  The effect of selecting an abnormally healthy cohort
would in a strict sense limit generalizability of conclusions but would not in itself produce an
exposure-effect association when none actually existed.

A.4.12.3. Critique and Assessment
       Hirayama's cohort is drawn from a study population assembled to explore the associations
between a number of potential health-influencing factors determined via interview and
subsequent mortality.  Thus, the study was not designed to investigate passive smoking and lung
cancer specifically. Most of the weaknesses attributable to Hirayama's study derive from this fact.
       The only indicator of ETS available to Hirayama was self-reported smoking status at time
of baseline interview.  Thus, misclassification of spousal smoking status is possible, and change in
status over time, modifiers of exposure to spousal  smoking, and other sources of ETS exposure
cannot be determined.
       As previously seen, an overrepresentation of current and former active .smokers claiming
to be nonsmokers among wives of tobacco smokers probably biases the association between spousal
smoking  and lung cancer in reported nonsmokers upward.  Even the leading proponent of this
argument, however, states that unless this bias is much stronger than it appears to be in U.S. and
Western populations, it could not account for the major part of the observed results (Lee, 1990).
Lack of information regarding the amount of smoking actually done in the home and in the
presence of the spouse, room size and ventilation, and other exposure-modifying factors must lead
to imprecision in the estimates of exposure via spousal smoking.  This imprecision would make an
actual ETS-lung cancer association more difficult to detect. The fact that spousal smoking
exposure, even if precisely measured, is an imperfect surrogate for total ETS exposure because
workplace and ambient environmental sources are not assessed introduces a similar effect. Both of
these problems would thus introduce a bias toward the null, suggesting that the study's results are
an underestimate of the real association.
       Mortality information was derived from death certificate linkage. It has been contended
that lung cancer is routinely overdiagnosed as a  cause of death on death certificates, thus
undermining the study's credibility. But  the resultant misclassification of cause  of death would
presumably be nondifferential,  and thus bias results toward the null. To cause overestimation of
the association, a greater proportion of women in  the spousal smoking groups than in the
nonsmoking group would have to be falsely diagnosed as having lung cancer.   Because the study
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cohort was made up of nonsmoking women, there would be little reason for such a pattern (unless,
of course, all such cases came from women who falsely reported their initial smoking status or
took up smoking in the course of the study and the misclassification/smoking habit concordance
hypothesized by Lee were actually strongly at work).
       No information is given regarding whether the same interviewers interviewed both
husbands and their wives. Thus, interviewers may not have been blind to spousal smoking
characteristics of  interviewees.  This is likely to have been of little importance, however, because
the outcome—lung cancer mortality—was measured prospectively, and thus did not occur for
some time after exposure had been assessed.  If information bias was to some  extent operant in the
interview, the most likely scenario would find women whose husbands  smoked being probed more
strongly for admission of their own smoking than were women whose husbands did not smoke.
This would tend to reduce underreporting of active smoking in the "exposed" group relative to the
"unexposed" group.  The result would be to lower the observed association between husbands'
smoking and lung cancer mortality.
       Hirayama's cohort includes only married, reportedly nonsmoking women who were at least
40 years of age and "healthy" at the start of the study. In addition, almost all of these women were
under 70 years of age, and agricultural families composed a larger part of the cohort than of the
general  population.  Thus, the cohort does not present a proportionately accurate cross-section of
the Japanese population as a whole.  Nevertheless, there is little obvious reason why a relationship
between spousal smoking and lung cancer mortality found in this cohort should be dismissed on
the grounds that it is not generalizable to the greater Japanese (or other) population.
       The  possibility that confounding by other risk factors explains an observed association
must be considered in any study. For lung cancer, of course, smoking, gender, and age are major
risk determinants. Restriction of comparison groups to same-gender nonsmokers avoids possible
effects due to gender or smoking (but see misclassification discussion regarding smoking status).
Age is only  partially restricted in the study design, so its consideration  in the  analysis is essential.
Hirayama chose to control for husband's age in analyzing the cohort study's results.  All observed
associations persisted after such adjustment.  Spousal ages should be closely correlated,  but direct
adjustment using  the subject's own age rather than the age of their spouse would clearly be
preferable.  One such analysis was supplied (Hirayama,  1983a), and in it a significant association
between spousal smoking and lung cancer mortality persisted.  Furthermore, in analyzing  the
nested case-control studies, adjustment for wife's age was used throughout, which produced
findings that confirmed the results of the cohort study.
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       The potential role of confounding by other factors in the observed results has received
considerable emphasis.  A correlation between smoking and lower socioeconomic status with
concomitant lifestyle and environmental differences could be expected. Among these differences,
particular attention has been paid to the possible effect of dietary factors  (particularly low beta-
carotene intake) and occupational exposures, both of which, some hold, should correlate with
spousal smoking and thus could bring about the observed association even if spousal smoking and
ETS exposure have no  effect.  Yet, neither stratification on daily green-yellow vegetable
consumption—the best available surrogate for  beta carotene intake in the  data—nor on
agricultural versus nonagricultural occupation  of husband eliminated the association between
spousal smoking and lung cancer mortality  in the cohort study.  Similarly, adjustment for
husband's occupation and any of five dietary habit characteristics, along with wife's age, yielded
similar results in the case-control approach. Thus, neither of the major proposed confounders
satisfactorily accounts for the observed results.
       Because the data set does not contain the necessary information to examine effects due to
differences in cooking practices  (such as stir-frying), this cannot be ruled out, although such
practices might be expected to co-vary with some of the dietary factors considered in the analyses.
Similarly, use of coal for cooking or heating cannot be directly assessed, although a degree of
covariance with dietary habits or occupation is likely.
       Husbands' drinking habits were only marginally associated with lung cancer risk; mortality
rates stratified by both drinking  and smoking would have been more useful  (and stratification by
wives' own drinking habits would have been more useful still).
       When lung cancer mortality among wives is stratified by wife's age (in 10-year
increments) and husband's smoking  category, a clear dose-response pattern is seen only in the 40
to 49 and 50 to 59 age strata, whereas a decrease in mortality with spousal smoking is seen in the
70 and older stratum. Given that the latter stratum includes less than 1% of the cohort and very
few deaths, its rates are too unstable to justify much confidence. The dose-response pattern does
become weaker with ascending age strata, however, which has led to conclusions of inconsistency
with an ETS-lung cancer connection and presence of confounding. Hirayama has proposed that
age-related increases in spousal mortality, smoking cessation, and decreased time spent in
husband's proximity during the followup period may account for the observed pattern (Hirayama,
1990a). The proximity effect seems questionable because retirement of older husbands would
eliminate time spent away from the  house at work, but the other arguments  are plausible.
Alternatively, older women recently  married to smokers may be more likely to die from
competing  causes of death that increase with age before passive-smoke cancer develops.
Remarriage, possibly to a spouse whose smoking habits differ from those of the former spouse,
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 also would increase with age and could lead to misclassification of (former) exposure with a bias
 toward the null.  (It is unfortunate that history of former spouses' smoking habits and recency of
 marriage apparently were not obtained in the baseline interview because if the information had
 been collected, the aforementioned problems could have been readily addressed.) Temporal trends
 in some risk modifiers, such as dietary factors, also could play a role.
        Confounding cannot be ruled out entirely in certain instances, but the underlying question
 that must be raised in this regard is the following:  // the spousal smoking group contains a
 disproportionate number of individuals with risk-elevating factors such as poor diet, lack of
 exercise, low socioeconomic status, and occupational hazard exposure, and these factors are
 sufficient to produce an increase in lung cancer mortality relative to the spousal nonsmoking
 group, despite an absence of any real smoking effect, why does this  multitude of risk factors result
 in elevations of established smoking-related diseases  only and no substantial elevation of risk  of
 other causes of mortality (except brain cancer, which encompasses relatively few deaths)?
        In considering the study's results in broader terms, Hirayama's findings are consistent with
 the hypothesis that exposure of nonsmoking women to passive smoke via spousal smoking
 increases risk of lung cancer. The observed association is statistically significant. In addition, the
 persistence of the association after stratification on numerous variables, the observation of a
 parallel association in nonsmoking  husbands of smoking wives, the appearance of associations with
 other smoking-related diseases, the existence of a dose-response pattern in most analyses of strata
 containing adequate numbers, and  the production of  similar conclusions by either cohort or case-
 control approaches argues against attribution of results purely to chance or confounding.
        Possible inclusion  of active, smokers among "nonsmoking" spouses of smokers through
 misclassification bias or differential change in smoking status during followup remains the study's
 greatest weakness. This problem could have been addressed by followup interviews or
 questionnaires coupled with verification of smoking status by alternative means  in a subsample of
 the cohort, and still could be. In addition, losses to followup and failure to use more sophisticated
 survival analysis techniques are weaknesses that probably reduced the study's power.
       Overall, the Hirayama study provides supportive, although not definitive, evidence that
 ETS exposure increases lung cancer risk.

 A.4.13. HOLE(Coh) (Tier 1)
       This prospective cohort  study was undertaken in the towns of Paisley and Renfrew,
Scotland.  The primary objective was to explore the relationship between passive smoking and
cardiorespiratory symptoms and mortality, including  lung cancer.  The towns were selected
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because they are situated in an area with a high incidence of lung cancer.  All persons residing in
these towns between 45 and 64 years of age, inclusive, were visited between 1972 and 1976. Each
person was asked to complete a self-administered questionnaire and to visit a cardiorespiratory
screening center where further interviews were conducted; 80% (15,399 persons) responded.
       Participating households in which at least two "apparently healthy" subjects lived were
included in the study, yielding a study population of 3,960 males and 4,037 females.  Data on
smoking habits were obtained from the questionnaire and verified by interview at the screening
visit. Mortality among subjects was traced  using the Scottish National Health Service Central
Register and General Register offices  (for death certificate linkage), as well as the national cancer
registry system. Results for followup  through  1982 were published in 1984 (Gillis et al., 1984).
The primary results reported here are  for followup through 1985, published in 1989 (Hole et al.,
1989). In addition, the results of unpublished data extending followup through December of 1988
are reported (personal communication from Hole to  A.J. Wells).
       Smoking habits were divided into three categories:  persons who have never smoked,
former smokers, and current smokers. In addition, the number of cigarettes smoked per day was
obtained for current smokers.  Both pipe and cigar smokers were excluded from the group who
had never smoked.  Never-smokers with former or current smokers as cohabitants in their
household were classified as passive smokers; otherwise never-smokers were classified as
"controls."  This classification yielded  1,538 passive smokers and 917 controls for both sexes
combined. The corresponding numbers for females  alone are  1,295 and 489.
       The number of lung cancer deaths among females occurring in the cohort during the
followup period is only six, too small  to yield much  statistical precision. The unpublished data
extending followup through 1988 includes one additional female lung cancer death that occurred
subsequent to 1985.  The crude relative risk is  2.27 (95% C.I. = 0.40, 12.7), which is in the
direction of a positive association between  ETS exposure and lung cancer. The extremely wide
confidence interval is the result of the small number of cancer deaths being compared and
indicates that the data could easily arise when  the true value of the relative risk  is much larger or
smaller than the estimated value. After adjustment  for age and social class, the relative risk is
1.99 (95% C.I. = 0.24, 16.72). Lung cancer incidence was somewhat higher than mortality (10
cases vs. 7 deaths), yielding an adjusted relative risk of 1.39 (95%  C.I. = 0.29, 6.61).  The relative
risks for adjusted mortality (5.30) and incidence (3.54) were higher in males than in females but
were based on even fewer cases (four  deaths, six incident cases).
        Although the observed association could easily occur by chance, it is a useful contribution
to the pool of evidence on lung cancer and passive smoking. Consequently, it is worth noting that
the observed associations are not likely to be attributable to other  factors, because they  persisted
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after control not only for age and gender, but for social class, diastolic blood pressure, serum
cholesterol, and body mass index. Thus, differences in lifestyle or environmental factors such as
diet, housing, and employment between passive-smoking households and nonsmoking households
is an unlikely source of the results.  Specific adjustment for potential occupational exposures or
radon were not carried out, but these variables would presumably co-vary with social class to a
great extent.
       As for other sources of bias, interviewer bias can be discounted because subjects were
"apparently healthy" at interview and supplied smoking information before cardiovascular
screening, and the investigators did not begin determining the passive smoking status of subjects
until 1983 (for the first published study on this cohort).  The extent of loss to followup is not
specified, so one cannot tell whether this was a potential source of problems.  However, linkage
was carried out through two registries for general mortality and an additional registry specifically
designed for cancers. Diagnoses of cancer mortality from death certificates were checked against
cancer registry records for verification, thus reducing potential inaccuracies attendant on use of
death certificates.
       Some data regarding misclassification were collected in an additional questionnaire
administered to a portion of the cohort at some unspecified point in the study. Among controls,
5% said that their household contained a smoker—presumably someone who had not met the
inclusion criteria (e.g., age 45 to 64) for the study.  Thus, a small portion of the control group was
actually currently exposed, which would produce a slight bias toward the null. Differential
misclassification of smokers as never-smokers resulting from concordance of smoking habits
among cohabitants cannot be assessed or ruled out, despite the authors' suggestion that persons
cohabitating with smokers may be more likely to falsely claim to be smokers themselves,
providing a bias toward the null.
       In summary, this study appears well designed and executed, but the number of  ETS-
exposed  subjects is small.  Although the study carries little statistical weight, there are no apparent
methodological problems that would limit its usefulness otherwise.

A.4.14.  HUMB(Tier2)
A.4.14.1. Author's Abstract
       "As part of a population-based case-control study of lung cancer in New Mexico,  we have
collected data on spouses' tobacco-smoking habits and on-the-job exposure to asbestos. The
present analyses include 609 cases and 781  controls with known passive and personal  smoking
status, of whom 28 were lifelong nonsmokers with lung cancer. While no effect of spouse
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cigarette smoking was found among current or former smokers, never smokers married to smokers
had about a twofold increased risk of lung cancer.  Lung cancer risk in never-smokers also
increased with duration of exposure to a smoking spouse, but not with increasing number of
cigarettes smoked per day by the spouse. Our findings are consistent with previous reports of
elevated risk for lung cancer among never-smokers living with a spouse who smokes cigarettes."

A.4.14.2.  Study Description
       This population-based case-control study was conducted through the New Mexico Tumor
Registry during 1980-84. The original purpose was to explain differing lung cancer occurrence in
Hispanic and non-Hispanic whites in  New Mexico. The study questionnaire included questions on
spousal smoking and  on indirect exposure to asbestos through a spouse's job. The current report
describes the risks associated with those exposures in smokers and nonsmokers.  The data on ETS
exposure in nonsmokers  is  extracted from the larger study containing smokers.
       For the whole study,  a total of 724 eligible primary lung cancer patients were identified,
of which 641 were interviewed (89%). About one-half (48%) of the ease interviews were
conducted with the subject.  Information on the remaining subjects was obtained from surrogates,
generally the surviving spouse or a child. Cases were collected in two series, the first consisting of
patients with cancer incident in 1980-82. That group includes all cases less than 50 years of age
and all Hispanics, but not those exclusively. The number of cases was supplemented by a second
series of patients with cancer incident to a 1-year period beginning November 1983. Most of the
controls were selected by random telephone sampling,  but some older subjects were randomly
selected from Medicare participants.  The control group was frequency-matched to the cases for
sex, ethnicity, and 10-year age category, at a ratio of approximately 1.2 controls per case.
Interviews were held for 784 of the 944 eligible controls, with 98% of the responses from subjects.
       The term "never-smoker" means not a cigarette smoker, where the latter is defined to be
someone who has smoked for at least 6 months. The smoker classification is divided further into
current smokers and ex-smokers. The current smoker status includes smokers who have  stopped
within 18 months before the  interview; the ex-smoker status applies if smoking ceased more than
18 months before the interview. Assuming that the minimum 6-month duration of smoking is
intended to apply to current and ex-smokers, never-smokers could have smoked previously for up
to 6 months.
       An  ETS-exposed subject is one ever-married to a spouse who smoked cigarettes,
regardless of the spouse's use of pipes or cigars. No information was obtained on exposure to ETS
from other sources, such as from other household smokers, in the workplace, or from parental
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smoking during childhood.  Measures of ETS exposure from spousal smoking include duration of
exposure (in years) and the average number of cigarettes smoked per day by the spouse. The ETS
subjects (never-smokers) include 20 (4) female (male) cases and 162 (130) controls (the article
reports 8 male cases, the number used in much of the analyses, but 4 of those 8 were found to be
smokers, personal communication from Humble). The age distribution for the female cases
(controls) is as follows: age less than 65, 5 (74); age 65 or more, 15 (88).
       The odds ratio for the crude data on female never-smokers is 1.8 (90% C.I. = 0.6, 5.4) for
spousal smoking of cigarettes only and 2.3 (90% C.I. = 0.9, 6.6) when spousal smoking also
includes use of pipes and cigars. Based on  mean cigarettes per day smoked by the spouse, the
odds ratio of 1.2 at more than 20 cigarettes per day is somewhat lower than the odds ratio of  1.8 at
the lower rate, fewer than 20 cigarettes per day. For duration of exposure, the odds ratio
increases from 1.6 at less than 27 years to 2.1 at 27 or more years. It is reported that adjustment
for age and ethnicity did not alter these results from the crude analysis. A trend test is included
for duration of spousal smoking, but the sample sizes are too small to be meaningful. Application
of logistic regression to adjust for variables gives values very  close to the odds ratios for the crude
analyses shown above for spousal smoking, for use of cigarettes only and also for combined use of
cigarettes, cigars, and pipes.
       The distribution of cases by cell type is given, but only with males and females combined.
The ratios of ETS-exposed cases to the total, by cell type, are as follows:  squamous cell (2/4),
small cell (1/1), adenocarcinoma (either 6/12, 7/12, or 8/12),  and others (either 3/3, 2/3, or 1/3,
depending on correct ratio for adenocarcinoma).
       The authors conclude that the results indicate increased risk from ETS exposure in never-
smokers but not in active smokers.

A.4.14.3. Comments
       This study evaluates smokers as well as nonsmokers for increased risk of lung cancer from
spousal smoking.  Not surprisingly, the number of smokers among the cases far  outweighs the
number of nonsmokers. No evidence of added risk to smokers from passive smoking is found.
Such  an evaluation, however, puts a great deal of faith in the exposure data and the  power of
statistical methods to detect what may be only a marginal increase in risk from ETS  on top of
active smoking.
       Of more central concern to this review is the assessment of lung cancer from ETS exposure
in never-smokers. The ETS  data are taken  from a larger study, so the matching no longer applies,
although the adjustment for those variables (ethnicity and age category) in the analysis is
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 worthwhile. The article suggests that the high rate of proxy response for cases in the original
 study (52%) may be due, at least in part, to inclusion of decedent cases.  That topic is not
 explicitly addressed, however, and controls were not matched to cases on vital status.
 Never-smokers apparently may have a history of smoking, provided it is of less than 6 months'
 duration. Whether any never-smokers actually have a short smoking history is not discussed, but
 the never-smoker classification is  less strict than in most studies.
        The data are evaluated in a number of different ways, consistently yielding an increased
 odds ratio.  The number of cases, however, is too small (15 exposed, 5 unexposed) for the
 observed odds ratio to achieve statistical significance. Similar values of the  odds ratios might be
 observed in a larger study, but, of course, that cannot be assumed.  The study outcome is
 consistent with an association between ETS exposure and lung cancer occurrence.

 A.4.15.  INOU(Tier4)
 A.4.IS.1. Author's Abstract
 (Note:  No abstract was provided; the following was paraphrased from author's discussion.)
        A case-control study on smoking and lung cancer in women was conducted in Kamakura
 and Miura, both in Kanagawa prefecture, Japan. The two cities are distinctly different in social
 environment; the former is a residential community and the latter is a fishing village. After
 stratification on city and age groups, the odds ratio of lung cancer in nonsmoking wives was
 shown to be 1.58 when husbands smoked fewer than 19 cigarettes a day and  3.09 when husbands
 smoked 20 or more cigarettes a day. For comparison, the odds ratio for active smoking is 5.50.
 Although the study size is quite small, it provides additional evidence favoring the passive
 smoking and lung cancer hypothesis.

 A.4.15.2. Study Description
       This study was conducted to assess the roles of active and passive  smoking in the etiology
 of lung cancer in women. It is unclear  how subjects or diagnoses were obtained, but cases are
 women who died of lung cancer in Kamakura or Miura in the time periods 1980-83 and 1973-81,
 respectively.  Controls, consisting of women who died of cerebrovascular disease during the same
 timeframes, are individually matched to cases on year of birth, year of death (±2.5 years), and
 district of residence. It is not clear whether incident cases were used.
       Face-to-face interviews were conducted by public health nurses and  midwives. ETS
subjects consist of the 28 nonsmoking cases and 62 nonsmoking controls remaining after
elimination of 9 cases and 12 controls who were smokers. Husband's smoking status was not
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available for unspecified reasons in a total of 8 cases and 20 controls, but these figures include
smokers as well as nonsmokers.  The exact number of nonsmokers for which spousal smoking
status was available is not specified but can be back-calculated from what is given (see below).
No information is given on the number of proxy respondents, the age distribution of the subjects,
or attempts to confirm diagnoses of primary lung cancer.
       The term  "nonsmoker" is not defined, so it is not clear whether it refers to persons who
never smoked or who do not smoke at present. Nonsmoking women whose husbands smoke at
least five cigarettes per day are classified as exposed to passive smoking. Considerations of
former smoking or marital status, ETS exposure at the workplace or in childhood, and duration of
exposure are not addressed.  No attempts to verify the reliability or validity of the data are
mentioned.
       The number of subjects is not delineated by case versus control and exposed versus
unexposed figures.  They can be determined from the odds ratio and confidence interval,
however, as 18  of 22 (exposed over total) cases and 30 of 47 controls.  For nonsmoking women
with smoking husbands, the crude odds ratio calculated by the reviewers is 2.55 (95% C.I. = 0.74,
8.78). (Note: OR = 2.25 is erroneously reported in the article. The OR  value of 2.55 has been
confirmed by Hirayama.)  When husbands' smoking is divided into  two strata (< 19 cig./day and
20+ cig./day), the odds ratios increase with exposure from 1.16 to 3.35, giving a statistically
significant trend  (p < 0.05).  Age-adjusted odds ratios of 1.39 and 3.16 are reported for the two
strata; adjustment for both age and district  yields corresponding odds ratios of 1.58 and 3.09.
(Note: The first OR value, 1.58, is incorrectly reported in the article as 2.58. The value  1.58 has
been confirmed by Hirayama.)  The authors conclude that, although the study size is quite small,
the results provide more evidence favoring  the hypothesis that passive smoking causes lung cancer.

A.4.15.3.  Comments
       The number of subjects remaining after active smoking and missing data exclusions is
small, guaranteeing poor power and lack of statistical significance in the absence of large odds
ratios. The details on study design are limited.  The source of cases and controls is not mentioned,
for example, and it is unclear whether incident or prevalent cases were used.
       Information regarding quality control and related concerns is equally sparse.  Interviewers
used standardized questionnaires, which would help to promote consistency, but no mention is
made of blinding them to subject background or study question, the absence of which could
introduce interviewer bias (probably in a positive direction). Because cases and controls are stated
to have died during the study period, it is probable that proxy respondents were ^required, but the
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 extent is unknown. In addition, neither duration of ETS exposure from spousal smoking nor
 exposure from other sources, such as other cohabitants, was considered. The resultant inaccuracy
 of exposure assessment probably biases the results toward the null. Lack of information on
 former smoking status or verification of diagnosis may introduce biases of indeterminate
 direction. Except insofar as the district acts as a surrogate for factors related to socioeconomic
 status, no risk modifiers other than age or district of residence were considered. The meaning of
 "nonsmoker" is not given, so treatment of smoking history is unknown, and it is unclear whether
 the accurate and meaningful segregation of never-smoking subjects needed for effective analysis
 was accomplished.
       Although a substantial odds ratio was observed for husband's smoking, these results are
 based on a small sample with too few details provided to assess adequately the study's design and
 execution and its bearing on the evidence, particularly with regard to potential sources of bias.
 The statistical uncertainty of the odds ratios given is reflected in the extremely wide confidence
 intervals shown.  The test for trend does not add any additional information. It is basically a
 restatement of the significant comparison between the heavily exposed group (husband smokes >
 20 cig./day) and the unexposed  group.  Unfortunately, the brevity of the description of this study
 in the source available severely  limits its utility.

 A.4.16. JANE (Tier 2)
 A.4.16.1.  Author's Abstract
       "The relation between passive smoking and lung cancer is of great public health
 importance.  Some previous studies have suggested that exposure to environmental tobacco smoke
 in the household can cause lung cancer, but others have found no effect. Smoking by the  spouse
 has been the most commonly used measure of this exposure.
       In order to determine whether lung cancer is associated with exposure to tobacco smoke
 within the household, we conducted a population-based case-control study of 191 patients with
histologically confirmed primary lung cancer who had never smoked  and an equal number of
persons without lung cancer who had never smoked. Lifetime residential histories including
information on exposure to environmental tobacco smoke were compiled and analyzed.  Exposure
was measured in terms of 'smoker-years,' determined by multiplying the number of years  in each
residence by the number of smokers in the household."
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A.4.16.2.  Study Description
       This study was undertaken in New York State to clarify the role of exposure to tobacco
smoke in the household as a possible cause of lung cancer among nonsmokers. Interviews were
conducted with former smokers as well as never-smokers initially (Varela, 1987), but because
matching was carried out on smoking status, only never-smoking case-control pairs were included
in the analyses for this article.  The study includes both males and females, which are combined in
all of the analyses.  There are 146 (45)  female (male) pairs.
       'Cases are never-smokers aged 20 to 80 years newly diagnosed with lung cancer at 125
referral centers in New York from July 1, 1982, to December 31, 1984. Controls are cumulatively
sampled never-smokers identified from files of the New York Department of Motor Vehicles.
Controls are individually matched to cases on age (± 5  years), gender, and residence.  In addition,
the same interview type (proxy or direct) was used for  controls as for their corresponding cases.
Exposure data were collected face-to-face via standardized questionnaire, and interviewers were
apparently uninformed of the subject's diagnosis.
        From the 439 case-control pairs interviewed, 242 pairs containing former smokers and
6 pairs with a mismatch on the source  of response were excluded. Of the remaining 191 pairs
used in the ETS study, interviews were conducted directly with the subjects in 129 pairs (68%)
and with proxies in 62 pairs (32%) (if a proxy was interviewed for a case, then a proxy was used
for the  matching control as well). No  demographic comparisons were provided for the ETS cases
and controls. For the whole study including smokers, the mean age of cases and controls is nearly
identical (67.0 and 68.1, respectively; Varela, 1987).  Histological verification of diagnosis was
obtained for all but five cases  (for whom only clinical information was available) out  of the initial
population of 439.
        Persons smoking no more than 100 cigarettes over the course of their lifetime  qualified as
never-smokers for this study.  Cigar or pipe smoking was apparently not considered.  Exposure to
ETS was deemed to occur when a smoker lived in the subject's household at any time from
infancy to adulthood. Both total household smoke exposure and spousal smoke exposure were
determined. Preadult (before  21 years of age) and adult exposure were examined separately.
Exposures were computed in units of "smoker-years," the total number of years lived with each
smoker summed over smokers. In addition, pack-years were calculated for spousal smoking.
Workplace exposure also was estimated by smoker-years, whereas exposure in social settings was
estimated subjectively on a scale from 1 to 12 for each decade of life and summed. Exposure data
were not checked, and marital status was not considered in the analyses.  No information on tumor
type or location was provided  for the  never-smoking population.
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       Preadult exposure to 24 or more smoker-years occurred in 52 (29) cases (controls), whereas
82 (94) were exposed to 1 to 24 smoker-years and 57 (68) were unexposed. Odds ratios were
calculated using matched-pairs regression analysis. Preadult passive smoking yielded increasing
odds ratio of 1.09 (95% C.I. = 0.68, 1.73) for 1 to 24 smoker-years and 2.07 (1.16, 3.68) for 25 or
more smoker-years.  The odds ratios for adult exposure are low but also increase—from 0.64
(0.34, 1.21) at 1  to 24 smoker-years to 1.11  (0.56, 2.20) at 75 or more smoker years.  The odds
ratios for lifetime exposure increase from 0.78 (0.36, 1.67) at 1 to 24 smoker-years to 1.80 (0.83,
3.90) at 25 to 99 smoker-years and then dip to 1.13 (0.56, 2.28) at 100 or more smoker-years.
Spousal smoking was not significantly associated with lung cancer.  In fact, when results were
stratified by type of interview, proxy interviews yielded strong and, in  some instances, statistically
significant negative associations for spousal smoking, with odds ratios between 0.20 and 0.68 for
ETS expressed in terms of present or absent, smoker-years, and pack-years of exposure. The
odds ratios for direct interviews, in contrast, range from 0.71 to 1.10 and are uniformly higher
than the odds ratios for corresponding proxy responses.  Workplace exposure to  150 or more
person-years yielded an odds ratio of 0.91 (0.80, 1.04), whereas a social setting exposure score of
20 led  to a statistically  significant decreased odds ratio of 0.59 (0.43, 0.81).
       The  authors conclude that they found a significant adverse effect of relatively high levels
of exposure  to ETS during early life (before age 21). For those who were exposed to 25 or more
smoker-years in their first two decades of life, the risk of lung cancer doubled.  By contrast, the
authors found no adverse effect of exposure to ETS during adulthood, including exposure to a
spouse who smoked.  This lends further support to the observation that  passive smoking may
increase the risk of subsequent lung cancer, and it suggests that it may be particularly important
to protect children and adolescents from this environmental hazard.

A.4.16.3. Comments
       The  number of never-smoking cases is relatively large, resulting in above-average
statistical power for evaluation of ETS effects.  Controls were matched  to cases on smoking status,
as well as the key demographic factors of age, gender, and neighborhood. Comparability of cases
and controls was likely good, as evidenced by the similar mean ages for the total population,
although no  other comparative information is available.  In view of the  use of population-based,
basically healthy controls, it is questionable that any attempted diagnostic blinding would be
effective. The study's  matching on smoking status with subsequent retention of matching and use
of matched-pairs analysis for ETS exposure effectively eliminates potential effects on risk
attributable  to age, gender, or residence, and it makes bias by related factors (such as
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socioeconomic status) less likely.  A rare feature is the use of matching on interview type (i.e.,
proxy or subject direct) to control for bias due to this source.  Comparison of spousal smoking
results for direct and proxy interviews, however, indicates consistently lower estimated risks from
proxies.  This suggests that use of proxy respondents did not merely lead to increased random
misclassification but might have biased the outcome toward a negative association.  The authors
posit that proxies of lung cancer patients may be more likely to underreport exposure than those
of control subjects. Curiously, however, although the authors report that odds ratios "frequently
differed according to type of interview," they do not specify how the odds ratios differed for
exposure other than spousal smoking. Also, the composition of the proxy groups—• relative
proportions of spouses, other relatives, and friends or associates—is never discussed, leaving
unexplored the possibility that misreporting by spouses of cases may lie at the heart of the
observed discrepancy.  It is also interesting that the outcome of self-responses versus proxy
responses in this study is in the opposite direction of the findings in GARF. Diagnostic
misclassification is unlikely, given the histological verification of nearly all cases.
       The restriction of subjects to persons smoking no more than 100 cigarettes in their lifetime
theoretically eliminates active smoking as a source of bias, although no verification  of smoking
status was undertaken. Consideration of potential  sources of ETS exposure is commendably
thorough, and the calculation of total years of  living with smokers, regardless of relation to the
smoker, as an index of household smoke exposure  minimizes the possibility that any source (e.g.,
roommates) is overlooked.  In contrast, the index of exposure in social settings is highly
subjective, and persons more habituated to passive smoke may report a given exposure as less
severe than persons less accustomed to smoke,  thus creating a negative bias.  The proportion of
controls classified as exposed to ETS is 80%, which is high in comparison with other studies. This
suggests that  some exposed controls may have only minor exposure to ETS, making  detection of an
association (if present) less likely. Unlike almost every other ETS study, males and  females are
combined in the analysis and only the joint results are reported.  Because there are 45 (146) pairs
of males (females), the sample sizes are sufficient to warrant reporting odds ratios separately by
sex and to test the hypothesis of no  difference due to gender.
       Lung cancer odds ratios for  adulthood, lifetime, and spousal smoking are consistently well
below  1 for low ETS exposure relative to nonexposure, as if exposure had a protective effect.
Thereafter, however,  the odds ratios associated with increasing levels of exposure are suggestive
of an upward trend in response.  Although we  would not dismiss the occurrence of this outcome as
attributable to chance alone, it is consistent with the baseline  lung cancer mortality  rate in the
control population simply being higher than that of the case population for reasons other than
exposure to spousal smoking.  A pervasive (systematic) negative bias linked with exposure could
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also produce such an effect. Both of these contingencies are necessarily speculative because there
is no evidence in the article to support either, aside from the outcome of the data analysis.
Further fueling the speculation, however, are the markedly lower odds ratios obtained from
surrogate responses, indicative of some source of bias acting unequally on proxy and nonproxy
sources. Also speculative is the idea that using predicted responses from a model that fits the data
poorly might produce such an effect, but that level of detail is beyond the scope of most published
articles, including this one. Some discussion of these issues by the authors, as well as separation of
the analyses by sex, would enhance interpretation of results and facilitate their comparison with
results of other studies on females.
       The authors' finding that exposure during childhood and adolescence appears to influence
subsequent lung cancer risk more than exposure during adulthood raises some interesting
possibilities.  More time may be spent in proximity to a household smoker (particularly the
mother), on average, in childhood than in adulthood. According to data presented by K.M.
Cummings (Roswell Park Memorial Institute, Buffalo, New York) at the Science Advisory Board
meeting on EPA's draft ETS report (U.S. EPA, 1990), on December 4-5, 1990, heavy childhood
exposure is a better surrogate for total lifetime exposure than is spousal exposure.  Also, early
exposure may appear to become a risk, either due to a long latency period for lung cancer or,
perhaps, due to increased susceptibility at an earlier age. The results suggesting an effect from
early exposure but not from spousal smoking are more nearly atypical than reinforced by other
studies, though, and the number of exposure sources considered raises the possibility that the
strength of association seen for  preadult exposure may be due to chance. However, after
elimination of 78 pairs with incomplete marriage or household exposure data, the association
persisted and was strengthened (OR = 2.59), arguing against chance as the major influence.  It is
unclear what role, if any, negative bias due to proxy respondents may have had in the nonspousal
analyses.
       In summary, the findings for preadult exposure are not readily attributable to chance or
confounding, although some role of interviewer bias or other factors such as diet cannot be ruled
out.  No association with lung cancer incidence is observed for spousal smoking. The authors
conclude, however, that, spousal smoking aside, other sources of household ETS exposure support
the conclusion that exposure to  ETS can cause cancer. That conclusion is not unequivocal in our
view.  In general, the odds ratios (aside from preadulthood exposure) tend to be low but trend
upward with exposure, exhibiting more of a patterned response than one might expect to see due
to randomness. This is puzzling because there is no apparent source of bias and the study appears
to have been conducted with considerable forethought and thoroughness. The only exception
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noted is the lack of separate analyses and comparisons of males and females.  These concerns
notwithstanding, the study is a useful addition to the literature on ETS exposure and lung cancer.

A.4.17. KABA(Tier2)
A.4.17.1.  Author's Abstract
       "Among 2,668 patients with newly diagnosed lung cancer interviewed between 1971 and
1980, 134 cases occurred in 'validated' nonsmokers. The proportion of nonsmokers among all
cases was  1.9% (37 of 1,919) for men and 13.0% (97 of 749) for women, giving a sex ratio of 1:2.6.
Kreyberg Type II (mainly adenocarcinoma) was more common among nonsmoking cases,
especially women, than among all lung cancer cases. Comparison of cases with equal numbers of
age-, sex-, race-, and hospital-matched nonsmoking controls showed no differences by religion,
proportion of foreign-born, marital status, residence (urban/rural), alcohol consumption, or
Quetelet's index.  Male cases tended to have higher proportions of professionals and to be more
educated than controls.  No differences in occupation or occupational exposure were seen in men.
Among women, cases were more likely than controls to have worked in a textile-related job (RR =
3.10, 95% C.I. = 1.11, 8.64), but significance of this finding is not clear. Preliminary data on
exposure to passive inhalation of tobacco smoke, available for a subset of cases and controls,
showed no differences except for more frequent exposure among male cases  than controls to
sidestream tobacco smoke at work.  The need for more complete information on exposure to
secondhand tobacco smoke is  discussed."

A.4.17.2. Study Description
        In 1969, the American Health Foundation began interviewing newly  diagnosed lung cancer
patients with cancer at sites potentially related to tobacco use for a case-control study (Wynder
and Stellman, 1977) that is still ongoing. The current article considers the data on lung cancer in
nonsmokers alone  collected from newly diagnosed  lung cancer patients between 1971 and 1980.
Several factors  are of interest: histology, demographic factors, residence, Quetelet's index, alcohol
consumption, previous diseases, occupation and occupational exposures, and  ETS exposure.  The
number of nonsmokers among the cases is small, so the authors consider the  results to be
preliminary.
        The study from which the data on lung cancers in nonsmokers are extracted is a very large
effort that includes tobacco-related cancers at multiple organ sites and includes smokers as well as
nonsmokers.  The  cases are from approximately 20 hospitals in 8 U.S. cities (about one-third from
New York City). With reference to the lung  cancer cases in that study, histologic type of lung
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cancer was determined from pathology reports and discharge summaries. Secondary lung cancer
cases were excluded.  Controls consist of hospital patients with diseases unrelated to tobacco use
who were pair-matched with cases on hospital, age (within 5 years), sex, race (with five
exceptions), date of interview (within 2 years), and nonsmoking status.  Cases appear to be
incident, and control sampling is density. All subjects were interviewed while they were  in the
hospital. The questionnaire for the interviews was expanded in 1976. Questions on exposure to
ETS were not included, however, until an addendum to the questionnaire in 1978, which was then
modified in 1979.
       The term "nonsmoker" applies to subjects who have smoked fewer than one cigarette, pipe,
or cigar per day for a year. The term "never-smoker" is used interchangeably. Independent of the
intended definition, however, subjects whose hospital charts indicated any record of smoking,
even in the remote past, were excluded from the nonsmoker classification.  ETS subjects include
53 (25) females (males), after combined attrition of 22 (9 without primary lung cancer and 13 with
a record of smoking). The age distribution of the female cases (controls) is as follows:  age less
than 50, 12 (15); age 50 to 59, 26 (24); age 60 to 69, 29 (34); age 70 or more, 30 (24).  Histologic
data on lung cancer type are given for female cases:  squamous cell (16), adenocarcinoma (60),
alveolar (12), large cell (4), and unspecified (5).  The authors report that exposed cases did not
differ from the unexposed cases in the distribution of histologic type.
       A person is "ETS exposed" (1) at home, if currently exposed on a regular basis to family
members who smoke, (2) at work, if currently exposed on a regular basis to tobacco smoke at
work, and (3) to spousal smoke, if the spouse smokes.  There are data on 53 cases and their
controls for exposure at home and at  work, but data on only 24 cases and 25 controls for spousal
smoking. This is because of the change in the questionnaire from 1978 to 1979 and because
spousal smoking was only applicable for women currently married. Because nonsmoking status
was a variable for matching, the 53 pairs of cases and controls for analysis of exposure at home or
at work are matched; the data for spousal smoking, however, are technically not matched. There
is no indication at all of an association between ETS exposure and lung cancer for women from
exposure at home, at work, or from spousal smoking.  For ETS exposure at home, there are 16 of
53 (exposed/total) cases and 17 of 53  controls; for exposure at work, the figures are 26 of 53 cases
and 31 of 53 controls; and  for spousal smoking, the data are 13 of 24 cases and 15 of 25 controls.
No statistical calculations are provided for females. From our calculations, the odds ratio  for
spousal smoking is 0.79 (95% C.I. = 0.25, 2.45). (Among male subjects, exposure to ETS in the
workplace was slightly significant, p = 0.05, as reported in the article.)  For other potential risk
factors for lung cancer in women other than passive smoking, it was found that cases were more
likely than controls to have worked in a textile-related job (OR = 3.1; 95% C.I. = 1.1, 8.6), but
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the significance of the finding was not clear.  It also was found that more female cases had a
history of pneumonia compared with controls, but no interpretation could be attached to the
observation.

A.4.17.3. Addendum
       Unpublished preliminary results of a study of ETS and lung cancer in never-smokers
conducted at the American Health Foundation have been reported at two meetings—The
American Public Health Association (APHA) 119th Annual Meeting, Atlanta, Georgia, November
10-14, 1991, and The Toxicology Forum,  1990 Annual Winter Meeting, Washington, D.C.,
February 19-21, 1990.  A completed report for our review was not available at the cutoff date for
inclusion in this document (personal communication with the first author, Dr. G.C. Kabat).
Enclosed below is the abstract for the APHA meeting.

            RISK FACTORS FOR LUNG CANCER IN LIFETIME NONSMOKERS
                             Geoffrey C. Kabat, Ernst L. Wynder

       Risk factors for lung cancer in lifetime nonsmokers (NS) were assessed in a hospital-based
       case-control study carried out between 1983 and 1990.  The study population consisted of
       41 male and 69 female NS cases and 117 male and 187 female NS controls matched on age,
       race, hospital, and date of interview.  Evidence of an effect of exposure to ETS was
       inconsistent.  In males, there was no difference between cases and controls in reported
       exposure to ETS (yes/no) in childhood, in nonsignificant association with exposure in
       childhood (OR = 1.6, 95% C.I.  = 0.9, 2.8), but no association with exposure in adulthood at
       home or at work. Male cases were somewhat more likely to have a smoking spouse (OR =
       1.6, 95% C.I. = 0.7, 3.9), whereas there was no difference in females. Cases and controls
       did not differ in reporting a history of previous respiratory diseases. Female cases were
       more likely to report a history  of radiation treatment (OR = 4.3, 95% C.I. = 1.5, 12.3). In
       females, but not in males, a significant inverse association was  observed between body
       mass index (based on self-reported weight 5 years prior to diagnosis) and lung cancer risk.

 A.4.17.4.  Comments
       Although the study contains more than 2,600 patients, only a small number of nonsmokers
 are available because questions about ETS exposure were not included in the interview until 1978
 and the questions were changed in 1979.  It is not known just how the questionnaire was changed,
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 although the general tenor of the article suggests care in study planning and execution. The
 design for the larger study from which the ETS data are taken is pair-matched on numerous
 factors of potential interest, including "nonsmoking status," which contributes favorably to the
 analysis of ETS data alone.  Cases with secondary tumors were excluded, histological type was
 considered, and all subjects  were personally interviewed.  It appears that only the currently
 married females were included in the question regarding exposure to spousal smoke, which
 alleviates the need to make some approximating assumptions regarding exposure of widows, single
 females, and so forth.
       Two areas that may need to be addressed in the analysis of ETS subjects have to do  with
 the definition of "ETS exposure" and "nonsmoker."  The duration of smoking was comparable  in
 cases and controls, but interview questions regarding exposure to ETS refer only to current
 exposure (this is not explicit in the article but was confirmed by the first author). Any effect
 from reliance on current exposure alone should be a bias toward the null hypothesis.  Also, a
 measure of exposure in units (e.g., number of cigarettes per day or pack-years smoked by spouse)
 would make the question less subjective and help to dichotomize on ETS exposure more sharply.
 Because lung cancer may have a latency period of 20 years or so, exposure in the past, both  in
 terms of duration and intensity, should be more meaningful than current exposure alone.  With
 regard to the definition of nonsmoker, the requirement is less rigid than is often imposed. Ever-
 smokers are included provided they did not smoke more than the equivalent of 1 cigarette per day
 for 1 year (about  18 packs).  It is difficult to know, however, what constitutes a "negligible" level
 of past smoking.  Any bias from  former smoking should inflate the relative risk, but that outcome
 appears unlikely in  this study (RR = 0.74).
       One of the factors of interest  to the investigators is occupation, so cases and controls were
 not matched on that variable. For ETS exposure, occupation could be a confounding factor.
 Among females, the controls contain a higher percentage of professional and skilled workers than
 do the cases (47 to 25) and a lower percentage of housewives (41 to 50). Some differences are also
 apparent in  religious preference between cases and controls that may bear some influence through
 lifestyle or dietary practices. Variables such as these may need to be taken into account in an
adjusted analysis when more data become available.

A.4.18. KALA(Tierl)
A.4.18.1.  Author's Abstract
       "A case-control study was undertaken in Athens to explore the role of passive smoking and
diet in lung  cancer,  by histologic type, in nonsmoking women. Among 160 women with lung
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cancer admitted to one of seven major hospitals in Greater Athens between 1987 and 1989, 154
were interviewed in person; of those interviewed, 91 were lifelong nonsmokers.  Among 160
Identified controls with fractures or other orthopedic conditions, 145 were interviewed in person;
of those interviewed 120 were lifelong nonsmokers.  Marriage of a nonsmoking woman to a
smoker was associated with a relative risk for lung cancer of 2.1 (95% C.I. = 1.1, 4.1); number of
cigarettes smoked daily by the husband and years of exposure to husband's smoking were
positively, but not significantly, related to lung cancer risk.  There was no evidence of any
association with exposure to smoking of other household members, and the association with
exposure to passive smoking at work was small and not statistically significant. Dietary data
collected through a semiquantitative food-frequency questionnaire indicated that high
consumption of fruits was inversely related to the risk of lung cancer (the relative risk between
extreme quartiles was 0.27 (95% C.I. = 0.10, 0.74). Neither vegetables nor any other food group
had an additional protective effect; furthermore, the apparent protective effect of vegetables was
not due to carotenoid vitamin A content and was only partly explained  in terms  of vitamin C.
The associations of lung cancer risk with passive smoking and reduced fruit intake were
independent.  Passive smoking was associated with an increase of the risk of all histologic types of
cancer, although the elevation was more modest for adenocarcinoma."

A.4.18.2.  Study Description
       This study was undertaken in Athens, Greece, in 1987-89. It sought to explore the role of
passive smoking and diet  in the causation of lung cancer in nonsmoking women.  All data used in
the study were collected specifically for that purpose.
       Cases are never-smoking women  hospitalized in one of seven Greater  Athens area
hospitals during an 18-month period of 1987-89 with a definite diagnosis of lung  cancer from
histologic, cytologic,  or bronchoscopic exam. Controls were selected from female never-smoking
patients in the orthopedic ward of the same seven hospitals and an orthopedic hospital.  A control
was interviewed within 1  week of a corresponding case, thus essentially density-sampled but
otherwise unmatched. Cases were not specifically restricted to incident cancers.  All subjects were
interviewed face-to-face by one of five trained interviewers; interviews apparently were
unblinded. A total of 160 lung cancer cases and an equal number of controls  were initially
identified; 6 cases and 12 controls were too ill to interview, whereas 3 controls and no cases
refused to participate.  After exclusion of smokers, 91 cases  and 120 controls  remained.  The age
distributions of the cases  and controls are very similar: for cases (controls), 16.5% (14.2%) were
less than 50 years of age,  19.8 (18.3%) were 50 to 59, 29.7 (25.8%) were 60 to  69, and 34.1 (41.7%)
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 were 70 or older.  Current residence, level of education, occupation (housewife vs. other) and
 marital status were also similarly distributed between cases and controls.  Case diagnosis was
 established by histology (48%), cytology (38%), or bronchoscopy (14%), with exclusion of cancers
 diagnosed as secondary.
        Persons reportedly smoking fewer than 100 cigarettes in their lifetime are classified as
 nonsmokers.  No mention is made of pipe or cigar smoking. Several different sources of ETS
 exposure are considered:  husbands who smoke quantified in terms of years exposed and average
 number of cigarettes smoked per day; household members other than husbands who smoke,
 quantified by the sum of years exposed to each smoker; and coworkers who smoke, measured by
 the number of smokers sharing the "same closed space" as the subject. Presumably, childhood
 exposure is included in the household exposure assessment. For spousal smoking, single women
 are considered unexposed, whereas exposure of widowed or divorced women is based on the
 period when they were married.  No attempts to verify exposure are mentioned.
        For analysis of husband's smoking based on cigarettes per day, 64 out of 90 (exposed/total)
 cases and 70 out of 116 controls gives a crude odds ratio of 1.6 for 90 cases and 116 controls; 64
 cases and 70 controls were exposed.  The authors present results stratified by four exposure
 categories, which indicate no significant association (p = 0.16).  Crude data for husband's smoking
 stratified by five levels of smoking duration (never, < 20, 20-29, 30-39, and 40+ years) yield a
 marginally significant increase in association with increasing duration (p = 0.07), with odds ratios
 of 1.0, 1.3, 1.3, 2.0, and 1.9, respectively.  No statistically significant association was noted for
 ETS exposure from other household members (p = 0.60) or for exposure at work (p = 0.13), but
 the crude odds ratios for these exposures were 1.41 and 1.39, respectively.  Stratification by level
 of intake for each of 16 food and nutrient groups yielded a significant negative (favorable)
 association with cereals (p = 0.04) and a possible association with fruits (p = 0.11).
       Multiple logistic regression was then used to adjust results for age,  education, and
 interviewer.  An adjusted  relative risk estimate of 1.92 (95% C.I. = 1.02, 3.59) was obtained for
 marriage to a smoker.  After adjustment, trends for estimated lung cancer risk showed an increase
 with duration of exposure (average 16% per 10 years) and packs per day (6% per pack), but these
 were not statistically significant.  No trend was observed for ETS in the household or workplace.
 Adjustment for other sources of air pollution had  no  effect on the analyses. Adjustment of
 dietary analyses for age, education, interviewer, and  total energy intake indicated a significant
 decrease in estimated risk between highest and lowest quartiles of consumption of fruit
(RR = 0.33; p = 0.02) and a nearly significant increase with consumption of retinol (RR =1.31;
p « 0.06), whereas beta carotene (RR = 1.01) and other dietary factors had  no significant effect.
Adding fruit consumption to the model for passive smoking increased the adjusted relative risk
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for husband's smoking slightly, from 1.92 to 2.11. Stratification by lung cancer cell type yielded
somewhat lower adjusted estimated relative risks for adenocarcinoma (2.04) than for squamous,
small, and large cell cancer combined (2.58). No adjusted results were presented for other
household or workplace exposure.
       The authors' conclusion is best reflected in their abstract (shown in full above).  Marriage
of a nonsmoking woman to a smoker was associated with a relative risk for lung cancer of 2.1.
Number of cigarettes smoked daily by the husband and years of exposure  to husband's smoking
were positively, but not significantly, related to lung cancer risk. There was no evidence of any
association with exposure to smoking of other household members, and the association with
exposure to passive smoking at work was small and not statistically significant. Dietary data
indicated that high consumption of fruits was inversely related to the risk of lung cancer. Neither
vegetables nor any other food group had an additional protective effect. The associations of lung
cancer risk with passive smoking and reduced fruit intake were independent.  Passive smoking
was associated with an increase of the risk of all  histologic types of cancer, although the elevation
was more modest for adenocarcinoma.
       It is noted that these findings are compatible with the relatively low incidence of lung
cancer in the Greek population—a population with the highest per capita  tobacco consumption in
the world, but with a very high fruit consumption as well.

A.4.18.3. Comments
       This study was generally well designed and executed.  Set up specifically to address passive
smoking and diet as etiological factors in lung cancer,  it  includes sufficient numbers of
nonsmoking women to produce substantive results. Interviews were face-to-face, and no proxies
were used, enhancing accuracy and comparability of responses, whereas the very low rate of
refusal minimizes potential bias  due to volunteer selection.  Cases and controls were  very similar
demographically, were drawn from most of the same hospitals, and were matched temporally on
time of interview, so comparability seems high.  Furthermore, the study hospitals' patient
population accounts for the majority of lung cancer and  trauma patients seen in the  Athens  area,
enhancing generalizability of results. Most lung cancers were histologically or cytologically
confirmed, reducing chances for misclassification of disease status.
        On the  debit side, the apparently unblinded interviews could have been biased (although
what can be accomplished toward that end is limited). Adjustment for interviewer in the analyses
did not affect the results, however, and it is unlikely that all interviewers would share the same
bias.  Determination of what constitutes workplace exposure is vague,  and childhood exposure is
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 not clearly differentiated from adult household exposure; these were notably the passive smoking
 categories, which showed the least association with lung cancer. ETS exposure in the workplace is
 analyzed with regard to trend (Table 2), with levels of exposure represented by "housewife" (zero
 exposure), "minimal," and "some," resulting in a p value of 0.13. Perhaps correctly, the authors
 cautiously note the evidence that ETS exposure is associated with increased risk (referring to
 Table 2 in general, not just exposure at work) but indicate that the differences are not large
 enough to be interpretable without controlling for other factors. An analysis of exposed versus
 unexposed for the workplace may have been useful, especially an adjusted analysis.  Our
 calculation of the crude odds ratio for a comparison of "minimal" and "some" exposure at work is
 1.7, which is suggestive.
       Methodological rigor and thoroughness are  particularly evident in the treatment of other
 factors that may affect risk.  Despite the demographic similarity of cases and controls, the key
 demographic variables of age and education were nevertheless controlled for in the analyses, along
 with interviewer  identity.  The potential effects of air pollution, total energy intake, and other
 dietary factors on lung cancer incidence were examined, and the impact of cancer type was
 evaluated.  An association of husband's smoking with lung cancer yielding an odds ratio of around
 2 persisted with adjustment for those factors.  The authors claim to have taken special effort to
 exclude ex-smokers from misclassification as never-smokers, taking account of this potential
 source of upward bias. No discussion was found, however, of what measures were taken to
 control misclassification of former smokers as never-smokers, beyond interviewing subjects about
 current and former smoking habits.
       In summary, this  study presents evidence of a level- and duration-dependent association
 between husband's smoking and lung cancer in a well-defined and highly comparable group of
 Greek cases and controls. Positive but  nonsignificant relationships with general home or
 workplace passive smoking were observed, and there are indications that additional analysis of
 workplace exposure may  be worthwhile. No effect of air pollution was observed.  With regard to
 dietary factors, the large  number of potential factors considered raises the issue of multiple
 comparisons. Fruit consumption may be a significant factor, but further evidence is needed to
 firmly establish this, particularly in view of the number of dietary factors explored.  Dietary
 factors, however, do not account for the results for ETS exposure in this study. The results
 regarding spousal smoking cannot be readily attributed to bias, and they provide good quantitative
data on the issue of passive smoking and lung cancer.  This well-conducted study makes a
valuable contribution to the evidence on lung  cancer and ETS exposure.
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A.4.19. KATA (No tier assignment is made on this study because the OR is undefined.)
A.4.19.1.  Author's Abstract
       "It is becoming noticeable in Japan that with increased incidence of lung cancer, there has
been an increase in pulmonary carcinoma in women.  Active smoking by women is increasing,
while concern over passive smoking has been intensifying, and the effect of passive smoking on
carcinogenesis has become a social problem.  Regarding this effect, immunological'and public
health reports have appeared in Japan, but there have been few clinical reports, and detailed
analysis of patients has been inadequate.  Lung cancer presents a variegated histological picture,
and presumably there are different carcinogenic factors for different histological types, although
there have also been few reports on this subject.  The effect of passive smoking probably varies
depending on the regional environment and custom, and these factors should also be analyzed and
included in the investigation. The present report describes our findings regarding  the effects of
smoking and familial aggregation of cancer in cases of pulmonary carcinoma in women."

A.4.19.2. Study Description
       This study was undertaken in the Nara Prefecture, Japan, to investigate the effects of
smoking and familial aggregation of cancer in cases of pulmonary carcinoma in women. Active
smokers are included in the  study, from which the nonsmokers are  drawn for analysis. Matching
is retained, however, in the  nonsmokers.
       For the whole study, subjects were drawn from a hospital (presumably the  Nara Prefecture
Medical University Hospital) during an unspecified period of time.  Cases are female patients
with histologically diagnosed lung cancer; controls are female patients  with "nonmalignant"
disease, matched 2 to 1  with cases on age plus or minus 2 years.  It  is not clear if only incident
cases were used and if controls were density sampled. Case diagnoses  were obtained from
histological  exam results, whereas control diagnoses were presumably from medical charts.  Other
information was  collected from apparently unblinded "questioning," with an unspecified degree of
reliance on proxy responses from family  members.
        A total of 25 cases and 50 controls are included in the study; no information on refusals is
provided. Exclusion of active smokers leaves only 17 cases and, with retention of 1:1 matching,
 17 controls.  Mean ages for  the total study population are 67.5 ±  8.8 years (67.6 + 8.5 years) for
cases (controls).  The age distribution of  ETS subjects is not discussed. Nonsmokers are defined
by exclusion of "active smokers," with no delineation between former and current  smokers. ETS
exposure is  defined as exposure to smoking more or less daily through living with  a smoker.
Three periods of ETS exposure are considered: current, past, and childhood, the last for those
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"exposed since early childhood." Clearly these types are not mutually exclusive, although current
sources of exposure are omitted from the "past" exposure category, even if present for a long time.
        ETS exposure is quantified as cigarettes per day smoked times number of years. No
mention is made of cigar or pipe smoking, nor of checks on exposure data. No distinction is made
regarding marital status. Tumors occurring among current passive smokers were mostly
adenocarcinomas (13/17), the remainder (4/17) being squamous or small cell cancers.  Airway
proximity was not specified.  Excluding active smokers, all 17 cases were current passive smokers,
compared with 14 out of 17 controls, for an odds ratio of 1.2, whereas past passive smoking
characterized  16 of 17 cases and 17 of 17 controls,  for an odds ratio of 0.9 (these odds ratios
reflect the substitution of 0.5 for 0 in the exposure categories in which no subjects fall).
Childhood passive smoking was reported in 13 of 15 cases and 7 of 15 controls (apparently all
those for whom information was available), for an  odds ratio of 7.4 (p < 0.1). None of the passive
smoking odds  ratios was statistically significant at the 5% level.  No definite conclusion can be
drawn from the present study, but there is a suggestion that passive smoking is  associated with
development of lung cancer in the Nara region. The effect of passive smoking  that continued to
the present time was especially marked, particularly in  squamous cell carcinoma and small cell
carcinoma.  With adenocarcinoma, an effect of passive  smoking in the past is suspected. Along
with passive smoking, the association of some intrinsic  factor (genetic tendency) to varying
degrees in the different histologic types of lung cancer in women, especially in adenocarcinoma, is
apparent.

A.4.19.3.  Comments
       The  histological diagnosis of all cases, in combination with the apparent involvement of
the researchers in the diagnoses, virtually eliminates the potential pitfall of misclassification of
lung cancer  cases.  It also allows specific breakdowns by cell type. With regard to passive
smoking, however, limitations related to exclusion  of active smokers greatly reduced the study's
potential.
       In their initial analyses, the authors investigate passive smoking without excluding or
stratifying on  active smoking and report statistically significant associations with lung cancer and
combined effects with family history of cancer. This is not a meaningful analysis, because the;
effects of active and passive smoking cannot be separated and passive smoke exposure probably
correlates  strongly with extent of active smoking.  Excluding active smokers greatly reduces the
available numbers  of matched subjects and, in combination with the very high exposure
prevalence among  qualifying controls, makes the differences  between cases and controls (highly
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unstable for all comparisons except for that of childhood exposure. Even here, with an estimated
relative risk of 7.4, the results do not reach the 5% level of statistical significance, notwithstanding
the problem of multiple comparisons.  The authors also conduct cell-type-specific analyses, but
these too fail to yield significant results.  The extraordinarily high proportion of exposed present
and past passive smoking controls is apparently a fluke, because the proportion is not as high in
the total control subject population (or childhood passive smoking controls).  Nevertheless,
exposure was very common among controls. This indicates that the exposure criteria may be too
lax or, alternatively, that the control population included a substantial proportion of persons with
smoking-related diseases (controls  being only stipulated not to have malignant disease).
       In light of the minimal utility of the study's passive smoking analyses, detailed
consideration of design strengths and weaknesses is unwarranted.  Major points not already
mentioned relate to information ascertainment and confounding. Interviews were apparently
unblinded and, especially if conducted by the authors themselves, may thus have been biased
toward uncovering exposure among cases (although the high  prevalence of exposure among
controls as well as cases argues against this).  Furthermore, the extent of proxy interviews,
potentially decreasing accuracy of exposure assessment, is  unclear.
       All subjects are female and, although results are not age adjusted, matching on age was
retained for all analyses. No other risk factors except family history of cancer were considered,
probably due to limited subject numbers, because much information on other factors was
collected. Moreover, family history was  considered only in the nonmeaningful analyses, which
did not differentiate active and passive smokers. Thus, although the problems with numbers and
exposure misclassification probably reduced the study's ability to detect whether an association
exists, information bias and confounding could have biased results either up or down.
       In summary, this study's data are consistent with an association of passive smoking,
particularly childhood exposure, with lung  cancer, but the results are too unstable and subject to
potential bias to carry much weight, and the quantitative results must be viewed with extreme
caution.

A.4.20. KOO(Tier 1)
A.4.20.1. Author's Abstract
       "Lifetime exposures to environmental tobacco smoke from the home  or workplace for 88
"never-smoked" female lung cancer patients and 137 "never-smoked" district controls were
estimated in Hong Kong to assess the  possible causal relationship of passive smoking to lung
cancer risk. When relative risks based on the husband's smoking habits, or lifetime estimates of
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total years, total hours, mean hours/day, or total cigarettes/day, or earlier age of initial exposure,
were combined with years of exposure, there were no apparent increases in relative risk.
However, when the data were segregated by histological type and location of the primary tumor, it
was seen that peripheral tumors in the middle or lower lobes (or less strongly, squamous or small
cell tumors in the middle of lower lobes) had increasing relative risks that might indicate some
association with passive smoking exposure."

A.4.20.2. Study Description
       This study, the second of four from Hong Kong, is based on a secondary data set of
reported female never-smokers.  The parent study from Which the data on ETS subjects were
drawn includes ever-smokers in a matched case-control study of 200 cases and 200 controls (Koo
et al., 1984; also see Koo et al., 1983). Its objective is to assess the role of passive smoking as a
potential etiological factor in the high incidence rate of lung cancer among Chinese females in
Hong Kong.  The current article emphasizes the quantitation of lifetime ETS exposure and the
histological profile of lung cancer in exposed never-smokers.
       In the parent study, cases are  from the wards or outpatient departments of eight hospitals
in Hong Kong during 1981-83.  Controls are healthy subjects from the community, matched on
age (within 5 years), district of residence, and type of housing (public or private). The cases are
incident, and control sampling is density. Attrition due to selection or followup totals 26 (8 too ill
to interview and 18 with secondary lung cancers), leaving 200 cases for interview. Face-to-face
interviews of 1.5 to 2 hours were conducted directly with cases and controls.  There was no
restriction of cases by cell type of lung cancer. The ETS subjects extracted from the parent study
include 88 cases and 137  controls. Of the 88 cases, 83 were confirmed by histology and 5 were
"confirmed malignant." The number  of squamous cell and small cell cases combined is 32 (23 ETS
exposed; 72%); the corresponding figure for adenocarcinoma and large cell combined  is 44 (31
ETS exposed; 70%); 12 cases are of another cell type or otherwise unspecified. For the 86 cases
with available information, tumors were centrally located in 37 (25 ETS exposed; 67%) and
peripherally in 46 (34 ETS exposed; 74%).
       The term "never-smoker" applies to persons who have smoked a total of  fewer than 20
cigarettes. Interview questions regarding exposure to ETS include cigarette and  cigar smoking in
the home during childhood, by the  spouse and other cohabitants in adulthood, and workplace
exposure. "ETS exposed" is technically used in several ways.  For the comparison of exposed with
unexposed ever-marrieds, it means the husband ever smoked in the wife's presence. For measures
of exposure in terms of duration or rate (e.g., total years, hours/day,  total hours, and  cig./day),
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there is some variation.  For example, total years of exposure is derived by adding the years
during which tobacco exposure occurred in the home or workplace. The total hours of exposure
are calculated by multiplying  the average hours per day of exposure by the years of exposure from
each household smoker, or the amount of exposure at each workplace.  The mean hours per day of
exposure are found by adding the hours per day of home and workplace exposures and dividing
this figure by the age of the subject. This figure is intended to approximate the average number
of hours of exposure per day  experienced by the subject, over her lifetime.  Cumulative exposure
is estimated by the total cigarettes smoked by family members, weighted by  years of exposure.
       When data are analyzed on the simple basis of whether a husband ever smoked in the
presence of the wife, the crude and adjusted odds ratios are 1.55 (95%  C.I. = 0.94, 3.08) and 1.64
(95% C.I. = 0.87, 3.09), respectively. The crude analysis applies to ever-marrieds only, which
excludes three subjects. An adjusted analysis uses cigarettes per day smoked by the husband as
the measure of ETS exposure. Conditional logistic regression was applied with stratification on
district of residence, and housing type (public/private); model parameters were included for age,
family history of lung cancer (yes/no),  number of live births, and  number of years since exposure
at home or in the workplace.
       The crude and adjusted methods give very similar odds ratios and confidence intervals,
but the tests for trend differ substantially. The test for trend on the crude data is based on the
Mantel-Haenszel test, using midpoints of the intervals for cigarettes per day smoked by the
husband; the significance value is p = 0.10. The p value for trend  in the adjusted analysis is 0.32.
For analysis of data by other  measures of .exposure, as described above, the estimated odds ratio
ranges between 1.0 and 4.1 across the three levels  of the various measures of ETS exposure for
both the analyses of the crude data and the adjusted analyses by conditional logistic regression,
with two exceptions from analysis of the crude data for hours per  day  of exposure.  The results
are not statistically significant in most cases, because the sample sizes at each exposure level are
small.  The dose-response patterns observed  are clearly sensitive to the measure of ETS exposure
used, with several exhibiting  an apparent peak at a low exposure level. Although the authors
acknowledge that it was troubling to find the lack of a response pattern, no further explanation is
given.
       The authors did not detect a significant trend in the crude  or adjusted odds ratio for the
four lifetime measures of passive smoking (total years, hours, mean hours/day, cig./day).
Although the odds ratio for the intermediate level exposures of hours per day and cigarettes per
day  was significant, the odds ratio at the highest levels of exposure for these two variables fell to a
nonsignificant 1.0 to 1.2. In  fact, the odds ratio for the highest exposure levels for three out of
the four measurements  were  below  all of those with lower exposures and ranged from a very weak
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1.0 to 1.4. On the other hand, most of the crude and adjusted odds ratios were greater than 1.0.
Measurements based on increasing intensity of exposure, defined as increasing years (or hours, or
cig./day) by mean hours per day of exposure, also did not indicate a dose-response relationship.
The analysis of total years of exposure with age of exposure did not suggest that earlier age of
initial exposure and increasing years of exposure led to higher odds ratios.
       It is concluded that when the lung tumors were segregated by histological type and
location, the resulting analyses showed that peripheral tumors in the middle or lower lobes, and
squamous or small cell tumors in the same lobes, exhibited better odds ratio patterns for passive
smoking in terms of consistency, strength, and dose response. The odds ratio for total years,
hours, and hours per day measurements of squamous and small cell lung tumors indicated
consistently elevated risks with increasing exposure.  This pattern was not found for any of the
adjusted odds ratios for adenocarcinoma or large cell lung cancers.
       The cases are divided into two groups histologically, those with squamous cell or small cell
tumors and those with adenocarcinoma or large cell malignancies.  Although none of the crude or
adjusted analyses are found to be significant, it is  concluded that an observed dose-response
pattern seems to be  more apparent in the squamous or small cell group.  With regard to tumor
location, some evidence suggests that peripheral tumors in the middle or lower lobes may be more
common in passive smokers.

A.4.20.3.  Comments
       As described above, the data employed in the  current study were taken from a larger
retrospective study of female lung cancer in  Hong Kong (Koo et al., 1984)  that matched 200 cases
and controls on age, district of residence, and housing type (private or public, an indication of
socioeconomic status).  Attention to detail and accuracy is evident in most aspects of the parent
study.  In particular, considerable effort was put into  attempting to ascertain a better quantitative
measure of exposure than used in preceding studies of ETS.  Records were  apparently verified to
the extent possible to cross-check the accuracy of  information collected, cancers were verified
histologically, and analyses investigated questions related to the histological types and sites of
tumors that may be  related to passive smoking.
       The never-smokers from the parent study, 88  cases and 137 controls, compose the
secondary data set on which  the current article is based.  The matching of the subjects, of course,
is no longer assured, leaving the comparability of the  two groups uncertain. In addition, 60 (27%)
of the subjects are widows, with no information provided on the distribution between cases and
controls. Because spousal smoking is typically the variable on which ETS exposure pivots, this
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may have some bearing on the response. However, an adjustment is made in some analyses for
years since exposure to cigarette smoke ceased.                                      ...,.-
       Some factors in the study itself may be contributing to the variable dose-response patterns.
First, the number of ETS subjects is fairly small. When the subjects are classified into finer
categories of exposure, the statistical variability is greatly increased (total of cases and controls is
typically below 60). Second, questionable measurements of ETS may be causing some distortion.
For instance, in the calculation of total years and total hours of ETS exposure, the years and hours
were not added for simultaneous exposure  to more than one smoker. Pipe smoking and the
cigarette consumption levels of coworkers were excluded from the weighted average of the total
cigarettes per day smoked by each household member. Thus, measurement appears to be based on
the assumption that never-smoking women were exposed to ETS evenly throughout their lives (the
authors claim that only subjects were used for which the exposure  remained relatively regular
during the lifetime, although no mention was found of cases being omitted because of failure to
satisfy this criterion).  Even if this assumption were valid, childhood and adulthood exposures are
mixed  as if the effects of exposure are interchangeable. Interestingly, differences between
exposure in childhood and adulthood is one of the questions addressed in the article.
        Although the  objective is worthy,  the attempt to quantitate exposure more precisely than
previous studies appears to obscure more than to clarify. Some assumptions are not made very
explicit, and their potential implications are not addressed well, which leaves some uneasiness
about the conclusions.  The authors have published at least three articles before this study that
have some bearing on  passive smoking and lung cancer, but their results are not discussed in the
current study, even when the data analyzed are from the same source (Koo et al., 1983, 1984,
1985).  Those articles, one of which  describes the parent study (the 1984 citation), appear to reach
somewhat different conclusions from this study regarding the predominance of histological type
associated with passive smoking. Putting the current study's conclusions within the context of
related prior work would enhance their clarity and  interpretation.
       Considering the reservations described above, the suggestion that the evidence indicates
some association of passive  smoking with the location of tumors is  an overinterpretatipn of the
data.  A weaker conclusion  is warranted, namely, that ETS exposure is associated with increased
lung cancer incidence. What may be of most value in this study is  the analysis based on the
dichotomous classification of cases and controls as exposed or unexposed based on spousal
smoking. Two concerns, however, will be  reiterated.  The ETS data are taken  from a larger study
not matched on smoking status, so they are unmatched.  The study includes 80 widows, without
mention of their distribution between  cases and controls.  In the adjusted analysis, an attempt is
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made to take into account the number of years since last exposure, which would require some
assumption regarding the change of risk relative to cessation of exposure.  Both of these concerns
are mitigated, however, by the similarity of the odds ratios and confidence intervals for the
unadjusted and adjusted analyses.  The care and thoroughness of the study in general make the
results on the odds ratio for exposure to spousal smoke a useful contribution for evaluation with
other study outcomes.

A.4.21. LAMT(Tier2)
A.4.21.1. Author's Abstract
       "In a case-control study in  Hong Kong, 445 cases of Chinese female lung cancer patients
all confirmed pathologically were compared with 445 Chinese female healthy neighborhood
controls matched for age. The predominant histological type was adenocarcinoma (47.2%). The
relative risk in ever-smokers was 3.81 (p < 0.001, 95% C.I. = 2.86, 5.08).  The RRs were
statistically significantly raised for all major cell types with significant trends between RR and
amount of tobacco smoked daily.  Among never-smoking women, RR for passive smoking due to
a smoking husband was 1.65 (p < 0.01, 95% C.I. = 1.16, 2.35),  with a significant trend between RR
and amount smoked daily by the husband.  When broken down by cell types, the numbers were
substantial only for adenocarcinoma (RR = 2.12, p < 0.01, 95% C.I.  = 1.32, 3.39) with a significant
trend between RR and amount smoked daily by the husband.  The results suggest that passive
smoking is a risk factor for lung cancer, particularly adenocarcinoma in Hong Kong Chinese
women who never smoked."

A.4.21.2. Study Description
       This hospital-based case-control study was conducted  in Hong Kong during 1983-86, to
investigate whether smoking is a major risk factor for lung cancer in Hong Kong Chinese women
and, if so, to determine the relationship between smoking and the histological types of lung
cancer. Both active and  passive smoking are of interest. The  ETS subjects constitute only a
subset of the whole study because  it includes active smokers.
       Eligible cases for the whole study are the 445 female patients with pathology-verified lung
cancer admitted  into eight large hospitals in Hong Kong during 1983-86.  Cases were interviewed
in person.  Only a few eligible patients declined or were too ill to cooperate. An equal number of
healthy neighborhood controls were identified and interviewed by density sampling.  Controls
were matched to cases on sex, age  (+5 years), and place of residence.  The cases and controls
include both never-smokers and ever-smokers, but smoking status was not used in matching.
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"Never-smoker" means a person who never smoked as much as one cigarette per day, or its
equivalent, for as long as 1 year.
       A woman is "ETS exposed" if her husband smoked for at least 1 year while they lived
together.  If the husband was an ever-smoker, information on the type of tobacco and amount
usually smoked per day by the husband and the duration of exposure was obtained.  No
information was collected  on ETS exposure from other household members' smoking or smokers at
work.  Single (never-married) women were classified as nonexposed (6.8% and 5.2% in cases and
controls, respectively). The treatment of widowed and divorced subjects is not explicitly
addressed. Age and place  of residence, as well as a series of other demographic variables, are
similar between cases and  controls.
       The distribution of lung cancer by cell type in ETS cases is as follows:  squamous cell, 12
of 27 (number exposed/total); small cell, 6 of 8; adenocarcinoma, 78 of 131; large cell, 7 of 9; and
others  or unspecified, 12 of 24. The corresponding crude odds ratios and 95% confidence
intervals are 0.85 (0.35, 2.06), 3.00 (0.53, 16.90), 2.12 (1.32, 3.39), 3.11 (0.50, 19.54), and 1.08
(0.41, 2.82), respectively.  The odds ratio for all cell types combined is 1.65 (1.16, 2.35), based on
115 of 199 (exposed/total) cases and 152 of 335 controls. The data for all cell types together, and
for adenocarcinoma alone, are both significant at p < 0.01.  No information is available on the
airway proximity of tumors.
       Trend tests were conducted for the amount smoked daily by the husband, categorized in
terms of cigarettes as "nil," 1 to  10, 11 to 20,  and  21 or more. The odds ratios in the three
exposure categories are 2.18, 1.85, and 2.07,. respectively, when all cell types are included.  For
adenocarcinoma alone, the corresponding odds ratios are slightly higher (2.46, 2.29, and 2.89,
respectively). The dose-response relationship does not appear to increase between the lowest dose
and the highest dose, but a test for trend is significant (p < 0.01 for all cell types and p < 0.001 for
adenocarcinoma alone) when the "nil" group is included.  No adjusted analyses are given.
       The authors conclude that the significant  trends observed between relative risk and
amount smoked daily by husband, for all cell types combined and for adenocarcinoma alone,
support the view that the observed association between ETS exposure and lung cancer is likely to
be causal.

A.4.21.3.  Comments
       This study is the fourth of the Hong Kong epidemiologic inquiries into tobacco smoke as a
possible etiological factor in the high rate of lung cancer, particularly adenocarcinoma, among
women. Active smoking was included as well as passive smoking because the previous studies in
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Hong Kong were inconclusive.  According to the authors, this led to the hypothesis that smoking
is not a risk factor for adenocarcinoma in Hong Kong Chinese women. Matching of controls to
cases was conducted for the whole study, including active smokers. It cannot be assumed,
however, that the never-smokers alone, who constitute 45% of the cases and 76% of the controls,
are matched.
       Overall, the study demonstrates care in planning and execution.  The sample size of ETS
subjects is moderately large, providing higher statistical power than the previous Hong Kong
studies. All cases were pathologically confirmed as primary lung cancers, essentially eliminating
the potential for error due to disease misclassification. Odds ratios were calculated by histological
type for comparison. Cases and controls were interviewed personally, apparently with no proxy
respondents and very few refusals, which reduces the potential for response bias. The exclusive
use of incident cases helps to control potential selection bias, and density sampling of controls
contributes to comparability of cases and controls.  For the whole study, including smokers,
healthy controls were matched to cases by sex, age, and neighborhood of residence. The mean and
standard deviation of ages are nearly identical in cases and controls.  According to the authors, a
comparison by other demographic variables showed that, for the whole study, cases and controls
were also comparable in place of birth, duration of stay in Hong Kong, level of education, marital
status, and husband's occupation.  Further attention to detail is evident in the clear definitions of
"never-smoker" and "ETS exposure," essential to accurate classification of subjects  for analysis and
interpretation.  Single women were treated as not exposed to husband's smoking, which  could be a
source of bias because these women may be exposed from other household members. This
possibility was considered,  however, because the article reports that similar results were obtained
when single women were excluded.
       In summary, the crude odds ratios vary between 2.1 and 3.1 for small cell carcinoma,
adenocarcinoma, and large  cell  carcinoma, with adenocarcinoma significant at p <  0.01.  The odds
ratios are consistently elevated at all three intensity levels of spousal smoking, varying between 1.8
and 2.9, with the odds ratio for adenocarcinoma alone somewhat higher than for all cell types
combined.  There is no apparent upward trend, however, from the lowest smoking intensity (1-10
cig./day) to the highest (21+ cig./day). These statistical results are ostensibly suggestive of an
association between ETS exposure and lung cancer incidence, but they are based on only crude
data with cases and controls unmatched, even on ages. Nor are statistical  methods  used  that could
adjust for matching variables, or other factors, in the data analysis (e.g., by stratification or
logistic regression). Although this study was carefully conducted in  most respects, the disregard
for potential confounding effects leaves the authors' conclusion uncertain.
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A.4.22. LAMW(Tier3)
(Note:  This study is part of the thesis of LAM Wah Kit submitted to the University of Hong
Kong for the M.D. degree in 1985, entitled A Clinical and Epidemiological Study of Carcinoma in
Hong Kong.  The description given below is from Chapter 7 of the thesis only, entitled Case-
Control Study of Passive Smoking, Kerosene Stove Usage and Home Incense Burning in Relation to
Lung Cancer in Nonsmoking Females (1981-84), which the author submitted in response to our
request. The abstract below was prepared by the  reviewers, since none was available from the
author.)

A.4.22.1.  Abstract
       The study's objective is to investigate the  hypothesis that an inhaled carcinogen may be
related to the high incidence of centrally situated adenocarcinoma of the lung observed in
nonsmoking female patients. Air pollution is probably not an important factor because it
presumably affects both men and women. Most women in Hong Kong either stay at home or join
the work force in commerce, services, or manufacturing, which are not associated with any known
risk factor for lung cancer. Three etiological activities, all predominantly in  the home, are
considered in this study: passive smoking, kerosene stove cooking, and home incense burning.  No
evidence was found to implicate exposure to kerosene stove fumes or incense burning in centrally
located adenocarcinoma. There is suggestive evidence of an association between ETS exposure
from smoking husbands and occurrence of peripheral (but not central) adenocarcinoma. Why the
location tends to be peripheral  instead of central is speculative.

A.4.22.2.  Study Description
(Note: The details of the study are not complete in the material provided.  Some useful
information, however, is available.)
       The cases are all of the  Chinese female patients admitted to the University Department of
Medicine, Queen Mary Hospital, Hong Kong, between January  1981 and April 1984 with
histologically and/or cytologically confirmed carcinoma of the lung of the four major cell types.
Care was taken  to exclude  patients with secondary carcinoma of the lung; otherwise, all patients
were included.  The controls are Chinese female patients admitted to the orthopedic wards of the
hospital in the period 1982-84, comparable to lung cancer patients in age and social class.  Patients
with pathological fractures due to  smoking-related malignancies or with peripheral  vascular
disease-related orthopedic conditions were excluded.
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       Both cases and controls were patients of the third-class general wards, mostly from the
lower income group. All subjects were interviewed in person. The questions covered dialect
group, occupation, smoking habits, passive smoking, domestic cooking with kerosene, and home
incense burning, in the form of a standardized questionnaire. For very ill patients, or for patients
who spoke a dialect other than Cantonese or Mandarin, the next of kin was interviewed, with the
patient as interpreter. The whole study, including active smokers, contains 161 cases and 185
controls, similar in age (median age is 67.5 [66] for cases [controls]), socioeconomic status (as
measured by occupation and years of schooling), and recent residence. The author considered it
unnecessary to stratify on these or any other variables.
       The ETS subjects consist of 75 (144) cases (controls), including 16(14) never-married
cases (controls). The distribution of cases by cancer cell type is as follows: squamous cell (7),
small cell (3), large cell (5), and adenocarcinoma (60).  Questions related to ETS exposure include
details on each smoker in the home (husband, others, mother, and father), amount smoked per
day, hours of ETS exposure per day, and number of years smoked.  Information about exposure in
the workplace includes size of the workplace, number of coworkers who smoke, exposure
time/day, and number of years of exposure at work.
       Only the data for adenocarcinoma, the predominant cell type observed and the
pathogenesis of interest, are analyzed. The number of cases is 37 out of 60 (exposed/total), and
the number of controls is 64 out of 144, where ETS exposure refers to spousal smoking.  The odds
ratio (calculated by the reviewers) is 2.01 (95% C.I. =  1.09, 3.72). The author divides the cases by
location according to airway proximity, with 18 of 32 (exposed/total) located centrally and 19 of
28 in peripheral regions.  The respective risk ratios are 1.61 and 2.64. Two tests were conducted
for significance, including the Bayesian  risk ratio analysis and a test of the slope for the exposure
parameter in a simple logistic regression model. The significance levels are 0.11 and 0.19,
respectively, for the central location and 0.01 and 0.02, respectively, for peripheral tumors. The
test results differ widely  for total passive smoking (home or workplace).  For the central location,
the respective significance levels are 0.09 and 0.3;  for peripheral locations, the corresponding
values are 0.03 and 0.15.  It is suggested that the different outcomes for the two tests applied to
total passive smoking may be due to a nonlinear logistic dose-response curve or to errors in
assessing the level of exposure due to incomplete information. The apparent association between
passive smoking and peripheral adenocarcinoma (and not central tumors) in the cases was
unexpected. Based on the available raw data, exposure to a smoking spouse, cohabitant, and/or
coworker is associated with an odds ratio of 2.51 (95% C.I. = 1.34, 4.67) for all cell types
combined. The author concludes that there is a suggestion of passive smoking associated with
peripheral adenocarcinoma, particularly passive smoking attributable to smoking husbands.
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Kerosene and incense burning were not found to be associated with adenocarcinoma, either
central or peripheral.

A A.22.3. Comments
       Cases and controls appear to be comparable in age, socioeconomic status, and recent
residence for the whole study (including active smokers), although the study design is not matched
on these or other variables. Some discrepancies between cases and controls are apparent, however,
such as a higher percentage of cases than controls working outside the home  (41% compared with
28%).  The figures for nonsmokers alone (i.e., the ETS subjects) are not given, so comparability is
uncertain for analysis of ETS exposure. Care has been taken to include only primary lung cancer
patients among the cases, essentially eliminating this potential source of bias. Subjects were
personally interviewed, with apparently only a small number of proxy respondents required,
although no figure is given.  The interviews apparently were not blinded, but that may not have
been feasible considering the nature of the questions asked and the use of noncancer patients as
controls. Considerable attention is given to histological type of cancer and the location in terms of
airway proximity.
       The author is particularly interested in the etiology of adenocarcinoma and focuses
discussion on the adenocarcinoma cases to the exclusion of others. Although the raw data
pertaining to other cell types are tabulated, more attention to those types in the analyses would
have been useful. The adenocarcinoma cases are categorized further by central and peripheral
location, which are analyzed separately. Again, a combined analysis  would be useful (the
reviewers calculated the crude odds ratio for the combined data,  which is given above). Although
logistic regression is employed as one of the two statistical tools for analysis, factors that may
differ between cases and controls are not included.  Potential confounding variables need to be
controlled for, by logistic regression, poststratification, or otherwise. To claim that cases and
controls are similar in  potential confounding characteristics does not  alleviate the need to adjust
for them in the analysis, particularly when the ETS data are a subset of the larger data set  to
which reference is made.  Similarly,  in testing three factors for an association with lung cancer
(passive smoking, cooking with kerosene, and burning incense), it would be  useful to conduct an
analysis  that will allow evaluation of the effect of each after adjustment for  the other two.
       The suggestive evidence that passive smoking  is more likely associated with
adenocarcinoma in peripheral rather than central locations may be logical but is weak, especially
considering the lack of analytical rigor. The proportion of ETS-exposed cases of adenocarcinoma
is  18 of 32 (56%) for central locations and 19 of 28 (68%) for peripheral locations.  This difference
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is not statistically significant (p = 0.26 by Fisher's exact test).  Consequently, the "apparent
association" between passive smoking and peripheral adenocarcinoma (and not central tumors) may
well be due to chance alone. There is suggestive evidence in the data that passive smoking may be
associated with lung cancer (OR = 2.01, p < 0.03 for a one-sided test), but that is based only on
the crude odds ratio in unmatched data and needs to be confirmed by a more thorough evaluation
of the data that takes potential confounders into account. Overall, this study provides some
suggestive evidence for an association between passive smoking and lung cancer.  Potential
confounders (including age) have not been controlled for, however, so attribution of the elevated
odds ratio to ETS exposure is uncertain.

A.4.23. LEE (Tier 2)
A.4.23.1. Author's Abstract
       "In the latter part of a large hospital case-control study of the relationship of type of
cigarette smoked to risk of various smoking-associated diseases, patients answered questions on
the smoking habits of their first spouse and on the extent of passive smoke exposure at home, at
work, during travel and during leisure. In an extension of this study an attempt was made  to
obtain smoking habit data directly from the spouses of all lifelong nonsmoking lung cancer cases
and of two lifelong nonsmoking matched controls for each case. The attempt was made regardless
of whether the patients had answered passive smoking questions in the hospital or not.
       Among lifelong nonsmokers, passive smoking was not associated with any significant
increase in risk of lung cancer, chronic bronchitis, ischemic heart disease, or stroke in any
analysis.
       Limitations of past studies on passive smoking are discussed and the need for further
research underlined. From all the available evidence, it appears that any effect of passive smoke
on risk of any of the major diseases that have been associated with active smoking is at most
small, and may not exist at all."

A.4.23.2. Study Description
       This study was undertaken in England, essentially from 1979 to 1983.  Its stated objective
is to investigate the relationship between passive smoking and risk of lung cancer in nonsmokers.
It is an outgrowth, however, of a hospital-based case-control study to assess whether the risk of
cardiorespiratory disease associated with smoking varies by type of cigarette smoked. It was
initiated in 1977 in 10  hospital regions  in England. In 1979, interviewers began gathering
information on passive smoking as  well in four of the regions.  Then in 1982, this case-control
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study of the effects of passive smoking was begun using nonsmoking cases identified by the
ongoing cardiorespiratory effects study. For the new study, spouses of cases and specially selected
controls were interviewed regarding smoking habits. Previously collected data on passive smoke
exposure obtained from patients back to 1979 were used.
        Basically, two substudies were conducted. One used the data obtained directly from
hospitalized cases and controls to address several sources of passive smoke, including spousal
(henceforward the "passive smoking" study); the second substudy used data obtained from the
spouses of cases and controls along with corresponding information from the patients themselves,
when available,  to address spousal smoke exposure only (henceforward the "spousal smoking"
study).  Cases for the passive smoking study were currently married lifelong nonsmokers
diagnosed with lung cancer (of any  cell type), chronic bronchitis, ischemic heart disease, or stroke
in one of four participating hospital regions. Controls were currently married lifelong nonsmoker
inpatients diagnosed with a condition definitely or probably not related to smoking and
individually matched on sex, age, hospital region, and, when possible, hospital ward and time of
interview.  Thus, density sampling was used when possible. For the spousal smoking study,
previously married patients were excluded; the same criteria otherwise applied, except that
controls were now matched on sex, age decade, and—as far as possible—hospital and time of
interview.
        Diagnoses were obtained from medical records. Exposure data were obtained through
apparently unblinded, presumably face-to-face interviews with inpatients and their spouses.  A
total of 3,832 married cases and controls were interviewed regarding passive smoking through
1982; it is unclear how many potential subjects refused or died before interview.  Only 56 of these
were married lung cancer cases meeting the spousal smoking study criteria. Spousal interview data
were obtained for 34 of these cases and 80 controls;  interviews were refused by the remainder.
Although matching of cases and controls was initially carried out, it was not retained in the
analysis, and no  demographic comparison of cases and controls used in the analyses is provided.
Diagnoses were apparently drawn from patients' charts; provisional diagnoses were used where no
final diagnosis was specified, no data on diagnostic technique(s) or histology was presented, and
no diagnostic verification was reported.
       The patient population consists of never-smokers, defined as lifelong nonsmokers, which
presumably excludes cigar and pipe  smokers. Exposure to ETS is approached in several ways.
The primary exposure is that of a spouse smoking manufactured cigarettes at some point over the
course of a marriage. Spousal smoking in the 12 months before interview also was assessed.  In
addition, "regular" exposure to passive smoke in various situations (i.e., at home or work, during
travel or leisure) was assessed.  The first two exposures were quantified in numbers of cigarettes
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smoked per day, the others in terms of "not at all, a little, average, or a lot." Thus, it appears that
cigar and pipe smoking may not have been included in the spousal smoking exposures.
Comparison of individual responses regarding spousal smoking status by patients and their spouses
revealed a high degree of concordance (97%) for smoking during the past 12 months and a
substantial concordance (85%) for smoking during marriage. No other checks on exposure data
were reported.
       The ETS patient data set includes 56 cases and 112 controls who met the initial study
criteria. Not all of these answered each passive exposure question, however, and not all met the
criteria for the spousal interview study.  Similarly, spouses of 34 cases and 80  controls provided
exposure information of  varying completeness.  Thus, the numbers involved in each analysis
varied considerably. For smoking during marriage, data obtained directly from spouses indicated
that for males and females  combined, 24 of 34 lung cancer cases and 51 of 80 controls were
exposed, which yields a crude odds ratio of 1.4 for spousal smoking.  With standardization for age,
an odds ratio of 1.33 (95%  C.I. = 0.50, 3.48) was reported.  Data obtained from qualifying patients,
in contrast, revealed 13 of  29 cases and 27 of 59 controls to be exposed, yielding a crude and
adjusted odds ratio of 1.00 (95% C.I. = 0.41, 2.44). Stratification by gender yielded adjusted odds
ratios from spousal interview data of 1.60 (0.44, 5.78) and 1.01 (0.23, 4.41) for females and males,
respectively, with corresponding odds ratios from patient interview data of 0.75 (0.24, 2.40) and
1.5 (0.37, 6.34).  When spouses identified as smokers  by interview with either source were
classified as exposed, an  odds  ratio of 1.00 (0.37, 2.71) was obtained for female subjects.  For the
larger inpatient passive smoking study population, age-standardized odds ratios for passive smoke
exposure at home, at work, during travel, and  during leisure revealed no consistent associations,
with as many negative as positive relationships observed after adjustment for  both age and
whether still currently married.  The same inconsistency held true for spousal smoking during the
last 12 months and during  the whole marriage.  Adjustment for working in a dusty job reportedly
did not affect the conclusion that passive smoking was not associated with risk.
       Spousal smoking  was slightly negatively associated with chronic bronchitis, ischemic heart
disease, and stroke, whereas a combined ETS exposure index was negatively associated with heart
disease but positively associated with bronchitis and  stroke.
       The author concluded  that the findings appear consistent with the general view, based on
all the available evidence,  that any effect of passive  smoking on risk of lung cancer or other
smoking-associated diseases is at most quite small, if it exists at all. The  marked increases in risk
noted in some studies are more likely to be a result of bias in the study design than of a true
effect of passive smoking.
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A.4.23.3. Comments
       The heart of this study is the spousal interview investigation of lung cancer and spousal
smoking. Only 34 case spouses and 80 control spouses, and even fewer of the corresponding cases
and controls themselves, are included, which gives the study low statistical power.  Because the
study began with hospital inpatient married lifelong nonsmokers, and matching on several key
factors was  employed, good comparability of cases and controls would seem readily achievable.
No case-control demographics are provided, however, and matching is  abandoned in the analyses.
The occurrence of interview refusals and omitted responses (themselves a potential source of
selection and information bias) may have contributed to the decision  to abandon matching, with
the aim of preventing further  substantial reduction in numbers through exclusion of unmatched
subjects.  As a result, the comparability of the cases and controls is uncertain.  At least all are
drawn from the same four hospital areas within a fairly limited timespan, which, in combination
with the other study criteria, reduces  the likelihood of serious noncomparability.
       Numerous opportunities for misclassification  of disease and exposure status are present.
Current working diagnoses are apparently drawn from patient charts  without verification, and
controls are selected from patients with diagnoses judged either probably or definitely not
associated with smoking by unspecified criteria.  This creates considerable potential for
misclassification, both through inaccuracies in diagnoses generally and through inclusion of
smoking-related diseases in the control group particularly, which would produce a downward bias
in results. Exposure misreporting and recall problems would seem least likely where spouses are
interviewed directly about exposure within the past 12 months.  Results for this situation  are not
presented, although they are reportedly similar to those for smoking during marriage.
       The  larger inpatient study elicited smoking data from patients, and only for their first
spouse for patients who had remarried; thus, exposure occurring in subsequent marriages  is not
addressed. In addition, no information on duration or level of smoking in marriage is used in any
of the spousal smoking analyses. The  most likely result of these problems is nondifferential
misclassification resulting in a bias toward the null.  For general estimated home, work, travel, or
leisure exposure  to passive smoke,  rough quantification is attempted by having patients categorize
their exposure as "not at all, a  little, average, or a lot." By necessity, this is a very subjective
evaluation, and people more acclimated to smoke and tolerant of exposure might well tend to
characterize a given amount of exposure as less severe than would a person less tolerant of smoke
who more actively avoids exposure. This tendency would produce a bias toward negative
association.
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       Standardization for age and restriction of cases and controls to currently married lifelong
nonsmokers should control the effects of age, marital status, or active smoking, although
misreporting of current or former active smoking cannot be ruled out entirely. Dusty occupation
reportedly had no effect on the larger inpatient study results. Potential effects of race,
socioeconomic status, diet, cooking habits, or any additional factors were not addressed.
       One might expect  the most accurate reporting of spousal smoke exposure when spouses, are
interviewed directly regarding their own smoking habits, and the most inadvertent
misclassification when patients are queried about the smoking status of their first marital partner
only. Analyses along these lines yielded slightly positive associations with smoking for the former
and negative with  the latter approach.  No consistent pattern of association was seen for other
sources and lung cancer, although high combined exposure scores were associated positively with
chronic bronchitis and stroke and negatively with ischemic heart disease.
       In summary, this study presents equivocal results that neither strongly confirm nor refute;
the hypothesis that passive smoking mildly increases risk of lung cancer.  The quality of the study,
however, is a limitation. The discrepant results for subject-supplied data (OR = 0.75) and spouse-
supplied data (OR = 1.60), varying degrees of completeness of information on subjects, and the
subjective nature of questions regarding ETS exposure limit confidence in the  study's data and, „
consequently, the results of its analysis of those data.

A.4.24.  LIU (Tier 4)
A.4.24.1. Author's Abstract
       "In Xuanwei County, Yunnan Province, lung cancer mortality rates are among the highest
in China in both males and females.  Previous studies have shown a strong association of lung
cancer mortality with indoor air pollution from 'smoky' coal combustion.  In the present case-
control study, 110 newly diagnosed lung cancer patients and 426 controls were matched with
respect to age, sex, occupation (all subjects were farmers), and village of residence (which
provided matching with respect to fuel use).  This design allowed assessment of known and
suspected lung cancer risk factors other than those mentioned above.  Data from males and
females  were analyzed by conditional logistic regression. In females  who do not smoke, the
presence of lung cancer was statistically significantly associated with chronic bronchitis (OR
7.37, 95% C.I. » 2.40, 22.66)  and family history of lung cancer (OR 4.18, 95% C.I. =  1.61, 10.85).
Females' results also suggested an association of lung cancer with duration of cooking food (OR
1.00, 9.18, and 14.70), but not with passive smoking (OR 0.77, 95% C.I. = 0.30, 1.96). In males,
lung cancer was significantly associated with chronic bronchitis (OR 7.32, 95% C.I. = 2.86, 20.18),
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family history of lung cancer (OR 3.78, 95% C.I. = 1.70, 8.42), and personal history of cooking
food (OR 3.36, 95% C.I. = 1.27, 8.88). In males, a dose-response relationship of lung cancer with
smoking index (years of smoking/amount of smoking) was shown by risks of 1.00, 2.61, 2.17, and
4.70."

A.4.24.2. Study Description
       This study was undertaken in Xuanwei County of China's Yunnan Province, a county
whose lung cancer mortality rates are among the country's highest and wherein burning of smoky
coal indoors in unventilated pits is a common practice. The study sought to assess "the influence
of factors other than type of fuel on the occurrence of lung cancer in Xuanwei."
       Cases of newly diagnosed lung cancer occurring among farmers at hospitals and clinics in
Xuanwei between November 1985 and December 1986 were identified as potential study subjects.
Up to five controls were identified for each case, depending on availability after matching on age
(±2 years), gender, and village of residence.  A total of 112 cases were identified, from which 2
were excluded due to unknown addresses.  Of 452 candidate controls, 26 were excluded due to
erroneous questionnaire responses.  All subjects were interviewed face-to-face by trained
personnel using a standardized questionnaire, and blinding extended to both interviewers and
interviewees.
       The final study groups  consist of 54 (56) female (male) cases and 202 (224) female (male)
controls. Mean age is 52 years for both cases and controls, who are also similar in family size,
ethnicity, birthplace, dwelling  type, and type of fuel used (smoky coal, wood). Separate
breakdowns for males and females are not provided.  Very few of the cases (19/110 = 17%) were
histologically or cytologically diagnosed, and no verification of diagnosis  or exclusion of
secondary tumors was undertaken (except to monitor mortality among some of the cases).
       Exposure to ETS was not evaluated for males. Among females, only one subject (a
control) reported ever having smoked, so the ETS population of females effectively consists of
never-smokers. Subjects were classified as exposed to ETS if their household contained at least
one smoker.  Exposure is not quantified, and it is unclear whether former or only current
exposure is intended.  No checks on exposure status or consideration of marital status are
mentioned, and no histological data are presented.
       The proportion of exposed female subjects is 45 out of 54 (176/202) for cases (controls),
yielding a crude odds ratio of 0.74.  A conditional logistic regression analysis adjusted for other
risk factors (presumably the other factors referred to are age-began-cooking and years-of-
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cooking) gives an odds ratio of 0.77 (95% C.I. = 0.30, 1.96).  No further analyses of ETS exposure
are provided.
       Four non-ETS factors are significantly associated with lung cancer among females:  family
history of lung cancer (OR = 4.18; 95% C.I. = 1.61, 10.85), personal history of bronchitis (OR =
7.37; C.I. = 2.40, 22.66), age-began-cooking (OR = 2.44-1.03, but with a reversing and
nonsignificant dose-response), and years-of-cooking (OR = 2.49-2.25, nonsignificant trend).
Among males, significant positive associations were noted for total smoking index, often-cooking-
own-food, family history of lung cancer, and history of chronic bronchitis, whereas age-began-
smoking, years of smoking, and intensity of smoking showed modest but nonsignificant
associations with  lung cancer.
       The authors conclude that "it is quite conceivable that the large amount of air pollutants
inhaled during indoor smoky coal burning in Xuanwei partly overwhelm the carcinogenic effect
of tobacco smoking" and "may also overwhelm the carcinogenic effect of passive smoking." "Our
results disclose important associations of lung cancer with factors other than fuel type and
therefore indicate that those factors must be considered in any comprehensive, quantitative risk
assessment of lung cancer in Xuanwei. Our results also confirm indirectly that smoky coal
pollution is an important determinant of lung cancer in Xuanwei."

A.4.24.3.  Comments
        This modestly sized study was not designed to test for effects  of ETS exposure.  Rather, it
is a hypothesis-generating exercise aimed at covering a broad range of possible risk factors.
Within that context, the study has considerable merit, but as an investigation of ETS it has
numerous flaws.
        Restriction to farmers minimizes concerns with occupation and overall lifestyle, and
control selection, including matching on age, gender, and village, produced demographically
comparable case and control populations for males and females combined despite the enigmatic
exclusion criterion for controls.  It is unknown, however, whether the groups remain comparable
after subdivision into males and females.
        The use of newly diagnosed cases reduces potential selection bias due to inclusion of
prevalent cases, but the heavy reliance (83%) on  clinical and radiological diagnosis and the absence
of independent confirmation or exclusion of secondary tumors introduces a strong potential for
misclassification  of disease and precludes analyses by cell type.  The observation that followup of
a number of lung cancer patients revealed that almost all died within  6 months of diagnosis does
little to confirm diagnostic validity,  contrary to the authors' interpretation.  Such presumably
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 random misclassification would make detection of an existing ETS-lung cancer association more
 difficult.
        Exposure data collection procedures, particularly the exclusive use of face-to-face
 interviews without resort to proxies and the blinding of both interviewers and subjects, are
 laudable.  For ETS, however, the exposure measure used is nonspecific and nonquantitative.
 Complications due to past exposure and differences in degree or duration could distort the
 observed disease-exposure relationship, probably biasing results toward no effect.
        Potential confounding is not adequately addressed in the statistical analysis.  The authors
 are particularly concerned with indoor smoky coal burning due to the known strong correlation
 between smoky coal use and lung cancer mortality in Xuanwei. Wishing to focus their
 investigations on factors other than smoky coal, they matched cases and controls on village,  which
 "provided  effective matching on fuel  type."  But because age and a host of other demographic
 factors, as well as smoky coal  consumption, were comparably distributed in cases and controls (see
 study description),  these factors were not considered further in  the data analysis. This is a serious
 flaw, for pair matching was not retained in the analysis; thus, none of the above factors is
 effectively controlled for. The conditional regression analyses do control for risk factors other
 than those cited above, but exclusion  of age, fuel type (e.g., smoky coal), and degree of exposure
 to fuel  fumes may produce misleading results.  •
        The presence of other significant risk factors for lung cancer makes detection of an effect
 from ETS, if present, less likely.  Masking by the presence of smoky coal and other factors in the
 study environment is probably a factor in the remarkably weak association between active
 smoking and lung cancer among study males (adjusted OR = 1.36).  If even an effect of active
 smoking remains largely obscured under study conditions, it is unlikely that an effect of ETS
 would be detected.  Supporting these concerns are other recent studies  in Xuanwei County that
 have confirmed widespread smoky coal use (e.g., 100% of households in Cheng Guan commune
 before 1958) and serious indoor air pollution with combustion byproducts, including mean indoor
 benzo[a]pyrene (BaP) levels of 9-15 ng/m3 in two communes using smoky coal during fall of 1983
 (Mumford  et al.,  1987). Prior use of smoky coal at age 12 is associated with an OR of 3.7 for lung
 cancer in pair-matched female residents (Chapman et al., 1988). He et al. (1991), who report a
 strong association between indoor BaP and lung cancer, conclude that indoor air  pollution appears
 to be the strongest risk factor for lung cancer in Xuanwei females.
       Overall, this study makes important contributions to  its principal objectives but is not
helpful  in assessing ETS and lung cancer. It is observed, for example, that persons in areas of
Xuanwei with high lung cancer rates (and high smoky coal consumption) may inhale more BaP by
spending 8  hours indoors than by smoking 20 cigarettes.  Due to  such factors, the authors  observe,
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"the effect of passive smoking on lung cancer may depend on local environmental factors and
results obtained in a given region therefore may not be applicable to other regions." Avoidance of
areas atypically rich in competing exposures and careful control of potential confounders and
interactive risk factors must be key objectives in studies of ETS and lung cancer.

A.4.2S. PERS(Tierl)
A.4.25.1. Author's Abstract
       "The relation between passive smoking and lung cancer was examined by means of a case-
control study in a cohort of 27,409 nonsmoking Swedish women identified from questionnaires
mailed in 1961 and 1963.  A total of 77 cases of primary carcinoma of the bronchus or lung were
found in a followup of the cohort through 1980.  A new questionnaire in 1984 provided
information on smoking by study subjects and their spouses  as well as on potential confounding
factors. The study revealed a relative risk of 3.3, constituting a statistically significant increase
(p < 0.05) for squamous cell and small cell carcinomas in women married to smokers and a positive
dose-response relation.  No consistent effect could be seen for other histologic types, indicating
that passive smoking is related primarily to those forms of lung cancer that show the highest
relative risks in smokers."

A.4.25.2. Study Description
       This case-control study, undertaken to explore the role of passive smoking in lung cancer,
is based on cohorts of Swedish women assembled prior to 1963.  Nonsmokers were drawn from
these cohorts  to create matched case and control groups.
       Cases are nonsmoking Swedish women included in the Swedish National Census or Twin
Registry who responded to smoking status questionnaires in 1961-63 and who subsequently
 developed primary lung or bronchial cancer by 1980. Two control groups were cumulatively
 sampled from National Census  or Twin Registry subjects who did not develop lung or bronchial
 cancer.  In group 1,  two controls were matched to each case on year of birth (± 1 year). In
 group 2, two  controls were matched to each case (2:1) on year of birth (± 1 year) and vital status
 in 1980.  Thus, there were 58 cases and 232 controls from the National Census and 34  cases and
 136 controls from the Twin Registry. A  followup questionnaire that included questions on spousal
 and parental smoking habits was distributed to each subject or the next  of kin in 1984. Out of 92
 cases of tracheal, bronchial, lung, or pleural cancer occurring by 1980, 15 cases in which a
 diagnosis of primary cancer of the lung or bronchus was not established were excluded. Exclusion
 of women indicated to be active smokers according to the 1984 questionnaire, or for whom ETS
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exposure information was not available, eliminated a further 10 cases.  Active smoking and lack of
exposure information eliminated 21 of the 368 controls initially assembled. Histological
confirmation was available for 64 of the 77 cases with primary lung or bronchial cancer; 12 cases
were cytologically confirmed, and the remaining case was verified at autopsy.
       Never-smokers are subjects who report that they have never smoked any form of tobacco.
A woman is ETS exposed if she has ever been married to a tobacco smoker; for women married
more than once, only the longest marriage is considered. Exposure to spousal smoking *is
quantified in units of cigarettes per day or packs of pipe tobacco per week; parental smoke
exposure is defined as 0, 1,2, etc. (equal to the number of parents who smoke).  No other sources
of ETS exposure are considered.  Never-smoking status was checked by comparing the responses
to the 1961-63 questionnaires with those obtained in 1984. Data on sources of ETS were not
checked. Never-married  women  were classified  as nonexposed to  spousal smoke; widows and
divorcees were classified according to the smoking status of the former husband with whom they
had lived the longest.  Of the never-smoking cases for whom passive smoking information was
available, squamous and small cell tumors constituted 20 cases, 13 of whom were exposed to
spousal smoke; of the other 47 cases, 20 were exposed to spousal smoke.
       Responses to the ETS questionnaire were available for a total of 81 never-smoking cases
and 347 never-smoking controls.  The 67 cases with primary lung or bronchial cancer constitute
the ETS study subjects. It is not clear how many of the 347 potential controls were employed in
each analysis. Presumably many (up to 4 for each excluded case from the original 81 never-
smoking cases) were not used in the matched analysis, whereas most or all were used in the
unmatched analyses described subsequently.
       A total of 33 of the 67 cases were exposed to spousal smoking.  Among the never-smoking
women, matched analyses indicate that the odds ratio for marriage to a smoker is 3.8 (95% C.I. =
1.1, 16.9) for squamous or small cell cancer compared with control group 1, 3.4 (0.8, 20.1)
compared with control group 2, and 3.3 (1.1, 11.4) compared with  both groups combined.,, .For
other cell types, corresponding odds ratios are 0.7, 0.8, and 0.8, respectively. Subsequent,analyses
abandoned matching and pooled all controls.  For squamous and small cell cancer, high exposure
to spousal smoking (15 or more cig./day or at least one pack of pipe tobacco/week for 30+ years)
is associated with an age-adjusted odds ratio of 6.4 (1.1, 34.7), whereas the lower exposure is
associated with an odds ratio of 1.8 (0.6, 5.3).  The estimated odds  ratios for other types of cancer
are also elevated for the higher exposure, but not at the lower one. Odds ratios adjusted for age
and spousal smoking when at least one parent smokes as well are above 1 (1.9; 95% C.I. = 0.5, 6.2)
for squamous and small cell types but not for other types.
                                          A-lll
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        Logistic regression analyses reportedly produced the same results as did the stratified
 analyses.  In addition, occupation, household radon, and urban or rural status had no significant
 effect.  It is notable, however, that for all cancers combined, the odds ratio for radon exposure is
 1.4 (0.4, 5.4), the odds ratio for spousal smoking is 1.2 (0.6, 2.6), and the odds ratio for radon and
 spousal smoking combined is 2.5 (0.8, 8.5). No separate analyses for squamous and small cell
 cancer are provided for radon and other potential confounders.  The authors conclude that
 exposure to ETS is related primarily to the forms of lung cancer that show the highest relative
 risks in smokers. The results are internally consistent.

 A.4.25.3.  Comments
        Although based on cohorts assembled for other purposes, this case-control study was
 specifically designed to investigate passive smoke exposure. Thus, all participants are  ETS
 subjects that are matched. Matching criteria are rather modest—birthdate (± 1 year) for control
 group 1 and birthdate and vital status for control group 2. Because the study targeted  all cases
 detected in the same cohorts from  which matching controls were randomly drawn, good
 comparability of cases and controls is likely.  No demographic comparisons of cases and controls
 for whom ETS information was available—and thus who constituted the analytical subjects—were
 provided to confirm this,  however. Data on active smoking among subjects were collected both at
 the start and after the end of mortality monitoring, providing an opportunity to verify the
 nonsmoking status over time and exclude individuals whose status had changed (apparently those
 reported in 1984 to have smoked daily for at least 2 years were so excluded). Thus, the
 probability of significant misclassification of active smoking status is low.  Data on passive
 smoking were collected only after the end of mortality monitoring and by necessity employed
 proxy respondents extensively, so some misclassification of exposure is likely. Self-administration
 of questionnaires eliminates  interviewer bias as a source of error, making misclassification less
 likely to be systematic, but preferential recall of smoke exposure by  relatives of cancer victims
 could have produced a bias.  Misclassification of disease is unlikely to have been a problem
 because most cases were histologically diagnosed and secondary  lung cancers were excluded.
       Consideration of spousal smoke exposure only in their longest marriage among  women
married more than once means that some of the unexposed group probably had substantial
exposure to spousal smoking, creating a bias toward no association. Classification of all
never-married women as unexposed despite possible smoking by cohabitants creates the same bias.
Few subjects (less than 20%) were single, but the frequency of remarriage is unknown; therefore,
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it is unclear how important this bias might have been.  Lack of consideration of workplace smoke
exposure also may have contributed a bias toward the null hypothesis of no association.
       The authors addressed a number of potential confounders and risk modifiers. Restriction
of subjects to women eliminates potential effects of gender, and age is addressed by retaining
age-matching or, alternatively, adjusting for age in all analyses. Reportedly neither occupation,
radon, nor urban residence had significant confounding effects, which makes confounding by
other factors related to socioeconomic status or lifestyle unlikely, too.  An analysis of parental
smoking controlled for spousal smoking. The authors do, however, present evidence that the odds
ratio for simultaneous exposure to radon and spousal smoke approximately equals the sum of the
separate odds ratios for radon and spousal smoke, consistent with additivity of the effects. But,
perhaps due to limited numbers, they report results only for all cancers combined rather than for
the squamous and small cell subgroup in which the only significant spousal smoking association
was observed.
       In summary, this study reports a consistent, dose-related, and (for high exposure levels)
statistically significant positive association between exposure to spousal tobacco smoke and
squamous and small cell carcinoma of the lung; a positive but nonsignificant association was  also
observed for parental smoke exposure.  No significant associations were observed for other cell
types. The observed associations apparently are not due to confounding by other major risk
factors, although dietary and smoking habits were not directly addressed.  A possible recall bias
cannot be ruled out but seems unlikely given the negative results obtained for cancers other  than
squamous and small cell.  The study provides a useful contribution to investigation of the
relationship between ETS exposure and lung cancer.

A.4.26. SHIM (Tier 2)
A.4.26.1. Author's Abstract
       "A case-control study of Japanese women in Nagoya was conducted to investigate the
significance of passive smoking and other factors in relation to the etiology of female lung cancer.
A total of 90 nonsmoking patients with primary lung cancer and their age- and hospital-matched
female controls were asked to fill in a questionnaire in the hospital.  Elevated RR of lung cancer
was observed for passive smoking from mother (RR = 4.0;  p < 0.05) and from husband's father
(RR = 3.2; p < 0.05).  No association was observed between the risk of lung cancer and smoking of
husband or passive smoke exposure at work. Occupational exposure to iron or other metals also
showed high risk (RR = 4.8; p  < 0.05).  No appreciable differences in food intakes were observed
between cases and controls."
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A.4.26.2. Study Description
       This study was undertaken in Nagoya, Japan, during 1982-85 to investigate the
significance of passive smoking and other factors such as occupational history, domestic heating
system, and dietary habits in the etiology of lung cancer in nonsmoking Japanese women.  All data
were collected specifically for this study, which was limited to never-smokers.
       All subjects were obtained from four hospitals in Nagoya.  Cases are women with primary
lung cancer (of any type) treated in these hospitals between August 1982 and July 1985 who
reported  themselves to be never-smokers and consented to interview.  Controls are women with a
diagnosis other than lung cancer from the same or adjacent wards with controls matched 2:1 with
cases on age (±1 year), hospital, and date of admission. Cases were not restricted to incident
disease, but controls were essentially density-sampled by admission date. Data collection was by
self-administered questionnaire; no attempt at blinding is described. Of 118 female lung cancer
cases treated during the study period, 4 refused to participate in the study and 24 were excluded
as current or former smokers.  Only a single matching control could be found for 17 of the cases.
No other information  on loss of potential controls is provided. There is a total of 90 (163) cases
(controls), with 52 (91) currently married to a smoker. Cases and controls share identical age
ranges (35-81 years) and have nearly identical mean ages (59 years for cases, 58 for controls). All
cases were histologically diagnosed, excluding secondary lung cancers.
       All study subjects are self-reported never-smokers. A number of individual sources of
ETS in the home are considered, including smoking by mother, father, husband, father-in-law,
mother-in-law, offspring, and siblings.  For each of these sources, smoking in the home at any
time constituted exposure.  Workplace exposure was characterized simply as presence or absence;
for other exposures, the number of cigarettes per day was obtained. In addition, data on  length of
marriage, time spent in the same room as the wife,  and total number of cigarettes smoked were
obtained  for husbands.  Exposure data were not checked, and marital status was not considered in
the design or analysis  of the study.  The predominant type of lung cancer is adenocarcinoma
(69 of  90 cases), followed by squamous (13), large cell (4), small cell (3), and adenoid cystic
carcinoma (1).  No data on airway proximity are provided.
       Logistic regression was used to estimate the relative risk  for each source of ETS exposure.
No significant association with lung cancer was noted for smoking by the husband (RR = 1.1),
father  (RR =1.1), husband's mother (RR = 0.8), offspring (RR = 0.8), or siblings (RR = 0.8);
smoking  by the subject's mother (RR = 4.0) and by the husband's father (RR = 3.2), however, are
significant (p < 0.05).  None of eight dietary factors, including green-yellow vegetable and fruit
intake, demonstrated a significant association, nor did type of cooking fuel or frequency of
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cooking oil use.  Occupational history of exposure to iron or other metals shows a moderately
strong but nonsignificant association (RR = 2.8), whereas for use of kerosene, coal, or charcoal
heating there is a mild association (RR = 1.6-1.7).
       Simultaneous stratification by father-in-law's and mother's smoking indicates that the
effects of the two exposures are not additive. Smoking by father-in-law, smoking by mother, and
occupational metal exposure were included simultaneously in a logistic regression model. After
adjusting the effect of each variable for the other two, the relative risk for maternal smoking,
father-in-law's smoking, and metal exposure are 2.1, 3.2 (p < 0.05), and 2.4, respectively. The
authors conclude that the exposure to tobacco smoke from household members (i.e., mother or
husband's father) could be associated with female lung cancer.  Because the precise situation of
passive smoking in the home or other places is still unclear, however, the authors find that further
studies are  needed to clarify the significance of passive smoking in relation to the etiology of lung
cancer in Japanese women.

A.4.26.3. Comments
       This study employs a moderate number of well-matched cases and controls. Their
comparability appears good, as supported by the identical age ranges and similar mean age and
occupational categories for the two groups. A further strength of the study is its lack of reliance
on proxy information with attendant potential for inaccurate recall. Exposure information was
obtained from self-administered questionnaires, which eliminates the possibility of interviewer
bias but  may lead to inaccuracy due to misinterpretation of questions or varying care in their
completion. Such problems with exposure information would tend to mask any actual association.
Lung cancer was histologically diagnosed in all subjects and secondary lung cancers excluded, so
diagnostic accuracy appears good for cases. Control diagnoses, however, were not validated, so
some smoking-related disorders (in addition to the heart conditions noted in 3% of controls) may
be included among the controls, a problem that once again would tend to reduce any observed
association.
       Restriction of subjects to never-smokers maximizes efficiency because effects of passive
smoking would likely be dwarfed by active smoking.  But it is unclear precisely what subjects
were asked about their smoking status.  Were any cut-points regarding past history, duration, or
intensity specified?  Thus, some misclassification of smoking status may have occurred, and if a
greater proportion of persons with smoking family members misreport themselves to be never-
smokers, this would create an upward bias.
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        The authors restrict their assessment of exposure from relatives to at-home smoking,
 which should be more meaningful than total smoking as a potential source of passive smoke
 exposure.  Furthermore, they collected data on smoking habits of all relatives, not just spouses or
 parents, thus reducing the chance of missing an exposure source. On the other hand, there is no
 consideration of total household smoking (all sources combined), cumulative exposure (except for
 husbands), or of pipe or cigar smoking; nor is  there differentiation of current and former
 exposure—all potential sources of exposure misclassification, which would tend to make an
 association more difficult to detect.
        Of the several sources of ETS exposure at home, only the relative risks for smoking by the
 mother and by the father-in-law are suggestive, and both of these are significant (p < 0.05).
 When these sources are considered simultaneously, however, and the effect of each is adjusted for
 the other, smoking by the husband's father remains significant (RR = 3.2; p < 0.05) but the effect
 of mother's smoking is diminished (RR = 2.1)  and is not statistically significant. Exposure from
 the father-in-law is, of course, in adulthood.  There is no evidence of an effect from husband's
 smoking (RR = 1.1), however, and these exposure sources were considered simultaneously so that
 the effect of one could be adjusted for the other. The large number of comparisons (e.g., eight
 groupings of passive smoke exposure, alternative spousal exposure measures, several occupational
 factors, and eight dietary factors) increases the likelihood that an observed relative risk will
 appear to be significant by chance alone (the effect of multiple comparisons).
        Another aspect of the statistical analysis worth noting is that, although cases and controls
 appear well matched on age, hospital, and hospital admission date, these factors are not included
 in an adjusted analysis of the data (aside from  the example  with three sources of exposure
 described above). Consequently, some bias due to these factors is a possibility, although the
 demographic similarities between cases and controls makes a large effect unlikely.
        In summary, this study presents some interesting results.  It finds a strong (adjusted
 RR « 3.2) and statistically significant  association between father-in-law's smoking at home and
 lung cancer and associations for maternal smoking and occupational metal exposure as well. The
 lack of association for any of the other sources of ETS examined could be due to problems with
 exposure assessment and control disease criteria.  Equally, however, given the unclear treatment of
 matching factors in the analysis and the number of variables explored, the few substantial
associations noted might be due to chance, confounding, or  both. Were potential confounders
clearly treated in their analyses,  this study would have made a stronger contribution. As it stands,
the study's data are of moderate utility, providing the number of comparisons and limitations
regarding bias are kept in mind.
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A.4.27. SOBU(Tier2)
A.4.27.1.  Author's Abstract
       "A hospital-based case-control study among nonsmoking women was conducted to clarify
risk factors in nonsmoking females in Japan.  Cases consisted of 144 nonsmoking female lung
cancer patients, and these were compared to 713 nonsmoking female controls. The odds ratios
(95% confidence interval) for use of wood or straw as cooking fuels when subjects were 30 years
old was estimated as 1.77 (1.08, 2.91).  For those whose household members, other than husbands,
had smoked, the odds ratio was estimated as 1.50 (1.01, 2.32). For those whose mothers had
smoked, the odds ratio  was estimated as 1.28  (0.71, 2.31).  Use of heating appliances did not show
an elevated risk. Some points to be noted in this study of low-risk agents for lung cancer are
discussed."

A.4.27.2.  Study Description
       This study was  conducted in Osaka, Japan, to clarify risk factors for lung cancer in
nonsmoking females in Japan. Of interest are the roles of both  active and passive smoking and
other indoor air pollutants, particularly smoke or fumes from sources of indoor cooking and
heating. This article reports only on female nonsmokers in the  study, which is not  matched on
any variables. A very similar article presenting interim results and using slightly fewer subjects
than the one described here is by Sobue and coworkers (1990).
        Cases consist of all newly admitted lung cancer patients in eight Osaka hospitals between
January 1986 and December 1988.  Controls were collected from newly admitted patients in one or
two other wards of the same hospitals during that period.  Almost 90% of the controls were
admitted as cancer patients, about half of whom were diagnosed with breast cancer. Self-
administered questionnaires designed for this study were completed by both cases and controls at
the time of hospital admission. Cases are incident, and control  sampling is density, unmatched
aside from the time of hospital admission (within 1.5 years).  The entire study, including active
smokers and males, consists of 295 (1,079) female  (male) cases and 1,073 (1,369) female (male)
controls.  Nonsmoking females compose 156 cases, of which there was missing information on 12.
The resultant number of ETS subjects is 144 (731) female nonsmoking cases (controls). The age
distribution of the cases (controls)  is as follows: 40 to 49, 20 (238); 50 to 59, 34 (229); 60 to 69, 41
(186); and 70 to 79, 34 (78).  The corresponding percentages are 14 (33), 34 (31), 28 (25), and 24
(11), which indicates that controls  tend to be younger than cases.  Also, the mean age of cases
(controls) is 60 (56).  There was no systematic review of histological diagnosis. All original
diagnoses were confirmed microscopically, however, and  all the pathologists involved in the eight
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participating hospitals were experienced specialists in lung cancer. Thus, the likelihood of
secondary lung cancers among the cases should be small.
       Several sources of ETS exposure are included, all of which occur in the home.  Exposure
in adulthood is expressed by two measures—smoking by the husband and other household
members (the last category consists chiefly of households where the husband's father and/or sons
smoke). Three sources of exposure in childhood are considered—father smokes, mother smokes,
and other household members smoke.  No information is provided on how exposure to spousal
smoking is handled for unmarried women (single, divorced, or separated). The entire complement
of cases and controls is included in the summary data for each of the five sources of exposure
given above. If only married women were included in the study, no mention of it was found.
       The histological data for ETS subjects are not classified by exposure to ETS, but the
percentage of cases by cell type are given:  squamous cell (8), small cell (5), adenocarcinoma (78),
large cell (5), and other (4).  The ETS data on spousal smoking consists of 80 of 144
(exposed/total) cases and 395 of 731 controls, for an odds ratio of 1.13 (95% C.I. = 0.78, 1.63).
(Our calculations give 1.06 [0.74, 1.52].)  The odds ratio for ETS  exposure from other household
members in adulthood is 1.57 (95% C.I. = 1.07,  2.31). (Our calculated values are 1.77 [1.21, 2.58].)
For ETS exposure in childhood by the father, mother, and by other household members, the
respective odds ratios are 0.79 (95% C.I. = 0.52, 1.21), 1.33 (95%  C.I. = 0.74, 2.37), and 1.18
(95% C.I. = 0.76, 1.84). Tests were conducted by the Mantel-Haenszel procedure, with
stratification by age and education (two levels). Analysis by logistic regression, adjusted for age
at time of hospitalization, was conducted for two of the exposure measures described above with
similar outcomes. Based on this evidence, the author concludes that for childhood exposure, a
slight increase of risk was suggested for those with smoking mothers, although statistical
significance was not observed.  For exposure in adulthood, an elevated risk was estimated for
those with smoking household members other than husbands.
       The statistical analysis includes exposure to sources other than ETS, namely, the use of
wood or straw as cooking fuel, the use of heating equipment that pollutes the room with
combustion products, and the use of charcoal foot warmers.  All  exposures considered, including
ETS, are smoke or fumes from products burned indoors. It is concluded that significantly
elevated risks were observed for subjects who had used  wood or straw as cooking fuels at 30 years
of age (OR = 1.89; 95% C.I. = 1.16, 3.06). No elevated risks were found for sources of indoor
heating  (use of kerosene, gas, coal, charcoal, and wood stoves without chimneys). Similarly, no
significance was found for the use of charcoal foot warmers, a practice that was popular until the
1960s.
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A.4.27.3.  Comments
       With 144 cases and 731 controls, the sample size is larger than many of the other
case-control studies on ETS.  Information on cases and controls was obtained by self-administered
questionnaire, which is generally considered less reliable than face-to-face interviews. The
questionnaires were presumably completed by the subjects themselves in all cases, however, which
is preferable to proxy-supplied information. The information supplied was not verified from
other sources, as noted by the authors in reference to testing for biomarkers of exposure to
tobacco smoke (they note that laboratory tests can only detect recent exposure, but they could still
be useful in eliminating current smokers who may misreport themselves as never-smokers).
Although cases and controls were newly diagnosed patients within a short time period in the eight
participating hospitals and were supplied with the same questionnaire, there are still some
questions regarding the comparability of cases and controls and their  representativeness of the
target population.
       Controls tend to be younger than cases:  While mean ages are 56 and 60, respectively, 33%
of controls, compared with 14% of cases, are below the age of 40. Controls also tend to be more
educated than cases, with 69% of controls having completed  10 or more years of education
compared to 52% of cases.  Differences in age and educational level further reflect differences in
lifestyle and socioeconomic status that may affect risk of disease. Also, the controls are
predominantly cancer patients too, almost half with breast cancer, suggesting that the controls may
be a biased sample (as  noted  by the authors).  On  the other hand, exclusion of breast cancer
controls reportedly leaves the results unchanged.  Furthermore, the statistical analysis stratifies on
age and education, so even though cases and controls were not strictly matched on these variables,
the reported results should not be due to confounding by either of these factors.
        Although some of the issues and reservations described above are methodological in nature
and apply  to the study throughout, others are specific to the ETS data alone. For example, one
might expect a question regarding the use of cooking with wood or straw at age 15 and at age 30
to be open to little subjective interpretation or error in recall, presuming that methods of cooking
persisted for several years between  changes within a household.  Although there is some suggestive
evidence of increased lung cancer from ETS exposure, the statistical  evidence may be stronger for
an association between lung cancer and use of wood or straw for cooking at age 30.  Further
support is  provided by the observation that among those who had used wood or straw for cooking
at age 30,  90% had also used those fuels at age 15, suggesting extended exposure in most cases.
The age distribution of those exposed to wood or straw cooking  is not given, but exposure at
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 30 years of age and before would allow for the long latency expected for lung cancer because 86%
 of the patients are at least 50 years of age.
       The smoke from cooking sources may obscure or distort any impact of ETS exposure
 because the two sources probably contain some of the same carcinogens. The temporal dimension
 of exposure also may be a factor because indoor smoke from cooking may be less common at
 present than 30 years ago in comparison to ETS exposure. Further statistical analysis to adjust the
 effect of ETS exposure for the presence of smoke from cooking might aid interpretation of the
 results in this study.

 A.4.28.  STOC
 A.4.28.1. Author's Abstract
 (Note: This study has not been published. Only the abstract is available, which is given below.)
       "Risk factors for lung cancer among women who  had never smoked cigarettes were
 examined in an ongoing, population-based, case-control  study conducted in Florida. One hundred
 and twenty-four primary carcinomas of the lung and 241 control women who had never smoked
 were  included.  Results suggest that childhood and adult  exposures to environmental tobacco
 smoke may increase the risk of lung  cancer among women who never smoked cigarettes. Having a
 husband who smoked cigarettes resulted in a statistically  significant increase in risk of lung cancer
 among women who had never smoked, with an odds ratio of 1.8 (95% C.I. 1.1, 2.9). A 40%
 increase in  risk was observed among  women with less than 25 years of exposure to a spouse who
 smoked,  when compared with women who reported their spouse had never smoked, with the risk
 increasing to 60% among women exposed 25 years or longer.
       When exposure to tobacco smoke in childhood was considered, the data were less
 consistent.  Having a parent who had smoked during the  respondent's childhood did not increase
 the risk of lung cancer.  However, among those respondents with high levels of exposure to
 parental smoking, an excess risk, although not statistically significant, was observed.  Never-
 smoking  women who accumulated 25 or more exposure years experience a 70% increase in risk
 (OR =* 1.7, 95% C.I. 0.8,  3.6) of lung  cancer compared with women who reported neither parent
 had smoked cigarettes."

 A.4.29. SVEN (Tier 2)
 A.4.29.1. Author's Abstract
       "In a population-based case-control study, the association between female lung cancer and
some possible etiological agents was investigated:  210 incident cases in Stockholm County,
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Sweden, and 209 age-matched population controls were interviewed about their exposure
experiences according to a structured questionnaire.  A strong association between smoking habits
and lung cancer risk was found for all histological subgroups. Relative cancer risk was found for
all histologic subgroups. Relative risk for those who had smoked daily during at least 1  year
ranged between 3.1 for adenocarcinoma to 33.7 for small cell carcinoma in a comparison with
never-smokers. All histological types showed strong dose-response relationships for average daily
cigarette consumption, duration of smoking, and cumulative smoking. There was  no consistent
effect of parental smoking on the lung cancer risk in smokers.  Only 38 cases had never been
regular smokers and the risk estimates for exposure to environmental tobacco smoke were
inconclusive. The high relative risks of small cell and squamous cell carcinoma associated with
smoking may have relative implications for risk assessments regarding passive smoking."

A.4.29.2. Study Description
       This study was undertaken in Stockholm County, Sweden, from 1983 to 1986 to investigate
the association between female lung cancer and some possible etiologic agents, particularly active
and passive smoking.  Because active smoking was an exposure of interest, cases and controls were
not matched on smoking status; thus, the ETS study population is unmatched.
       Cases are  Swedish-speaking women with primary lung cancer from three Stockholm
County hospitals  who were willing and able to be interviewed between September 1983 and
December 1985.  Cases with carcinoid tumors were excluded from the ETS analysis. Both
population and hospital-based control groups were assembled. Population controls were women
randomly selected from the county population register, matched to a case on birthdate and
interviewed between September 1983 and December 1986.  Hospital controls were subjects
originally interviewed as potential lung cancer cases but  subsequently diagnosed with
nonmalignant conditions.  Population controls were enlisted and interviewed as soon as  a case's
diagnosis was confirmed, but because this confirmation took as long as a year after the  interview,
controls were not density sampled.  Unblinded interviews were conducted face-to-face with all
cases (and hospital controls) and 58% of the total population controls; the remainder were
interviewed by telephone.
        After exclusion of 21 potential cases due to initial diagnostic uncertainty,  refusal, or illness
precluding interview, 210 confirmed cases remained. Elimination of  172 ever-smokers and four
subjects with carcinoid or not-microscopically-confirmed tumors left 34 never-smoking cases.
Similarly, 209 population and  191 hospital controls were included in the total study, but a
 combined total of only 174 were never-smokers. The  total case population averaged 62.5 years of
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 age, but no other demographic information regarding cases or controls is provided. All cases used
 in the ETS analyses were histologically or cytologically confirmed primary lung cancers.
        Daily smoking for at least 1 year is the criterion for a smoker; all other persons are
 considered never-smokers.  Pipe and cigar smoking are never specifically addressed. Exposure to
 ETS is calculated for four sources:  mother, father, home, and work.  Having a smoking mother or
 father (at any time during ages 0-9 years) constitutes exposure to that particular source, whereas
 the presence of a smoker at home and work constitutes exposure.  Adulthood and total lifetime
 exposure are considered separately for home and workplace exposure.  Exposure levels are
 arbitrarily scored 1 for nonexposure, 2 for exposure to one source, and 3 for exposure to both
 sources in  trend analyses of never-smokers, where exposures are considered in pairs (i.e., maternal
 and paternal smoking, home and workplace exposure).  No other units of ETS exposure are used.
 Adenocarcinomas constituted 22, squamous cell 5, and small cell 2 of the 34 lung cancers
 occurring among never-smokers in the ETS population; no further histologic details regarding the
 ETS study population are provided.
        To maximize available case numbers, parental smoking was first analyzed among all cases
 and community controls using stratification to adjust for active smoking (cig./day) and age.  A
 risk of 1.8  (95% C.I. = 0.5, 7.0) was estimated for maternal smoking and 0.8 (0.3, 1.4) for paternal
 smoking. A trend analysis in which maternal, paternal only, and no parental smoke exposure were
 scored as 3, 2, and 1, respectively, revealed no indication of trend  (p = 0.9).  Analyses restricted to
 never-smokers used both community and hospital-based controls combined. Among cases
 (controls), for childhood up  through 9 years of age, 3 (5) had smoking mothers, 12 (71) had
 smoking fathers (but not mothers), and 19 (98) were unexposed. This yielded an age-adjusted risk
 estimate of 3.3 for maternal  smoking (with or without paternal smoking) and 0.9 for paternal
 smoking during childhood. Adult exposure at home and at work yielded an estimated risk of 2.1,
 whereas exposure at home or work yielded a risk of 1.2.  For lifetime exposure, the estimated risks
 for exposure as both a child  and adult and as either a child or an adult were 1.9 and 1.4,
 respectively.  None  of these associations were  statistically significant, and no significant trends
 were observed. The authors  conclude that the results pertaining to ETS in the present study were
not conclusive. The small number of never-smokers among the cases could be  one important
reason.  It should be noted, however, that most of the point estimates of relative risk were greater
than unity, which agree with results from previous studies on ETS exposure and with risk
estimates concerning active smoking.
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A.4.29.3. Comments
       This study was undertaken to explore the role of active as well as passive smoking in lung
cancer.  After exclusion of active smokers, the available number of cases is too small to yield,
much statistical power.
       Cases and population-based controls were initially matched on date of birth, but this
matching was abandoned in the ETS analysis; furthermore, unmatched hospital-based controls are
combined with the population-based controls in most analyses to boost available  numbers. The
comparability of these groups is thus unclear, and the authors provide no demographic
comparisons to facilitate assessment of this potential problem. The reported similarity of results
using only population-based controls is reassuring, but no details are provided as to how similar
results actually were.
       Diagnostic misclassification of  cases is unlikely, given the histological or  cytological
confirmation of all  cases and exclusion of secondary cancers. All cases were interviewed face-to-
face, but 42% of controls were interviewed by telephone.  The accuracy of responses may thus be
lower for controls than for cases. In addition, because interviews were not conducted blindly,
inflation of estimated associations through interview bias is possible. A potential bias is also
introduced by the rather large amount  of active smoking required for classification as an ever-
smoker.  This allows considerable active smoking among persons in the never-smoker group, the
effect of which could mask an effect of passive exposure, or, if co-varying positively with passive
smoking, cause overestimation of association.
       The first set of analyses of paternal and maternal smoking includes ever-smokers while
attempting to adjust for active smoking on the basis of average daily cigarette consumption. The
adequacy of this adjustment is questionable given the large estimated risks associated with active
smoking relative to those posited for passive smoking, so the elevated estimated risks for maternal
smoking obtained in these analyses are of questionable validity.
       Restriction  of the analyses to never-smokers similarly produces an elevated odds ratio for
maternal smoking of 3.3, but the numbers involved (three cases and five controls) are so small that
this value is quite unstable. A pattern of  increasing estimated risk with increasing sources of
exposure (at home or at work) as an adult and increasing periods of exposure (in childhood or
adulthood) over the lifetime is suggestive  of an association between lung cancer  and  ETS, but
again small numbers preclude statistical significance of these results.
       Restriction  of the study population to females rules out the possibility of a gender-related
effect.  The likelihood of an ethnicity  effect is reduced by restriction to Swedish-speaking
residents of Stockholm County, and age is reportedly controlled for in all analyses.  No other
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 potential risk modifiers are addressed. For example, marital status is not considered in the
 analyses of spousal smoking, leaving open the possibility that nonsmoking-related differences
 between married and unmarried women contributed to the observed association.  The reported
 similarity of results when only population controls were used instead of hospital and population
 controls combined provides a general argument against bias due to source of controls, although no
 specifics regarding the degree of similarity were supplied.
        In summary, this study presents consistent evidence of associations between lung cancer
 and maternal, home, and workplace passive smoking exposure. Limited numbers preclude
 statistical significance, and interviewer bias or effects due to dietary or other factors cannot be
 ruled out as contributors to the observed results. Bearing these limitations in mind, the study's
 results are inconclusive but (excluding the analyses that include active smokers) do make a useful
 contribution to the pool of information available regarding ETS and lung cancer.

 A.4.30.  TRIG (Tier 3)
 A.4.30.1. Author's Abstract
       "Fifty-one women with lung cancer and 163 other hospital patients were interviewed
 regarding the smoking habits of themselves and their husbands.  Forty of the lung cancer cases
 and 149 of the other patients were nonsmokers. Among the nonsmoking  women, there was a
 statistically significant difference between the cancer cases and the other patients with respect to
 their husbands' smoking habits. Estimates of the relative risk of lung cancer associated with
 having a husband who smokes were 2.4 for a smoker of less than one pack and 3.4 for women
 whose husbands smoked more than one pack of cigarettes per day.  The limitations of the data are
 examined; it is evident that further investigation of this issue is warranted."

 A.4.30.2. Study Description
       This study was undertaken in Athens, Greece, to investigate the relationship of spousal
 smoking and  lung cancer.  All female Caucasian Athenian residents admitted to, one of three  chest
 or cancer hospitals in Athens  and assigned a final diagnosis of lung cancer other than
 adenocarcinoma and alveolar  carcinoma from September 1978 through June  1980 were
 interviewed by a physician. Controls were gathered from nonsmoking female Caucasian Athenian
 patients hospitalized during the same time period in the Athens Orthopedic Hospital. Some
prevalent cases were thus presumably included, so control sampling probably approximated a
density approach but did not strictly conform to one.
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       Diagnostic information was obtained from patients' charts. Exposure information was
obtained by face-to-face unblinded interviews conducted by the same physician for all subjects.
A total of 51 cases and 163 controls were interviewed.  Of these, 11 cases and 14 controls reported
themselves to be active smokers, leaving 40 cases and 149 controls as ETS subjects. No interview
refusals are reported.  Mean age of cases (controls) is 62.8 (62.3) years. Husband's education was
marginally higher in controls than cases, with 63% and 58% of spouses having completed primary
school, respectively. No other demographic comparisons are  reported for the ETS subjects alone.
For the sample population including smokers, factors such as age, duration of marriage,
occupation, education, and urban versus rural residence are all similar for cases and controls,
except once again educational level is slightly higher for controls.  There is no  indication that
verification of diagnosis or exclusion of secondary lung cancers was undertaken in cases. Of the
51 total cases, 14 were diagnosed histologically, 19 cytologically, and 18 by radiological or clinical
means.  No breakdown is given for the ETS subjects alone.
       The study classifies as nonsmokers both reported never-smokers and former smokers who
quit more than 20 years ago. It is not mentioned whether cigar and pipe smoking are considered
as sources of exposure. Nonsmoking women are considered exposed to ETS if they are married to
a man classified as a smoker. The  average number of cigarettes smoked per day by the husband
and the number of years of marriage are used to estimate the total number of cigarettes smoked by
the husband during marriage.  No data on childhood or nonspousal ETS exposure  were collected.
Single women are grouped with women married to a nonsmoker and are thus considered
unexposed. Widowed or divorced women were classified according to their former husband's
smoking status on the assumption that smoking stopped at death or divorce.  No checks of
exposure information are reported.
        For ETS subjects, the number of cases (controls) exposed  over the total is  29 to 40
(78/149). The crude odds ratio calculated by the reviewers is 2.4 (95% C.I. = 1.12, 5.16). The
results presented in the article are all stratified by level of husband's smoking. The odds ratios are
1.8, 2.4, and  3.4 when the husband is a former smoker, smokes 1  to 20 cigarettes per day, and
smokes 20 or more cigarettes per day, respectively.  No confidence intervals are given, but a test
for upward trend was statistically significant (p < 0.02).  When ETS exposure is estimated by total
number of cigarettes smoked during marriage, odds ratios (1.3, 2.5, and 3.0) increase with
cumulative exposure (1-99,  100-299, and 300+ thousand, respectively).  The upward trend remains
statistically significant at p < 0.02.  No analyses adjusted for age or other factors.  With regard to
age and other demographic variables, the authors conclude from the similarity of cases and
controls that it is not necessary to stratify for these variables in the analysis, particularly because
none is significantly associated with smoking in the study.
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       The authors note that this study has obvious limitations and is offered principally to
suggest that further investigation of this issue should be pressed. Most seriously, the numbers of
cases are small.  Nevertheless, the association is in the direction expected if passive smoking is
related to lung cancer, and the outcome is unlikely to be due to chance. Other limitations noted
include the high percentage (35%) of cases lacking cytology and the selection of controls from a
hospital different from those of the cases; it is argued, however, that neither of these appears to
be consequential. The observation is made that it is potentially easier to detect an effect of
passive smoking in the Greek population  than in most Western populations, because in the latter
groups, the overwhelming effects of active smoking, together with the high correlation between
smoking habits of spouses, would tend to confound and conceal the lesser effects of passive
smoking.

A.4.30.3.  Addendum
       In a letter to the editor of Lancet  in 1983, Trichopoulos et al. released a data table derived
from extension of subject collection through December 1982. This nearly doubled the sample size
used in the 1981 publication, yielding 77  nonsmoking cases (102 total)  and 225 smoking controls
(251 total).  The crude odds ratio  calculated by the reviewers is 2.08 (95% C.I. =  1.20, 3.59). The
results for the expanded study show very little change; (estimated) relative risks  when husbands
are former smokers (1-20 cig./day and >  20 cig./day) compared with nonsmokers are 1.95,  1.95,
and 2.54, respectively. The test for upward trend in the dose-response is significant (p = 0.01).
No other analyses are presented.

A.4.30.4.   Comments
       This study was conceived  and undertaken to explore the association of spousal smoking
with lung cancer and does not rely on a preexisting data set.  Thus, the investigators were in a
position to design their selection and data collection to maximize the strength of their findings.
This did not, however, prevent the appearance of some design and analytical flaws.
       Demographics of the total case and control populations are very similar.  All subjects in
the spousal smoking analysis are resident  Athenian nonsmoking women hospitalized in  the same
area of Athens; case and control groups have very similar mean ages, and their husbands are
comparable in education.  Thus, the groups probably have good demographic comparability,
although it would have been helpful if the detailed demographic comparisons were focused on the
nonsmokers alone.  Most of the controls (108 out of 163) were being treated for fractures, a
relatively minor and nonchronic illness compared with lung cancer, which may make them more
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representative of the general community than of hospitalized patients as a whole. This should
reduce the problem of inclusion of smoking-related illnesses in the control group.
       Although the researchers sought to exclude adenocarcinomas and alveolar carcinomas,
presumably considering these would be less smoking related, nearly two-thirds of the cases were
not histologically confirmed, so an indeterminate number of these cell types was probably
included.  More important, the infrequency of histologic confirmation and lack of mechanisms to
verify diagnoses or primary tumor status introduces potential for misclassification.  The likely
effect is a bias toward no association.
       The researchers  clearly devoted considerable thought to the smoking and exposure criteria,
particularly with regard to  changes in smoking and marital status over time.  Single women were,
however,  automatically  classified as unexposed. The authors contend that this is warranted by the
traditional nature of Greek society and report that analyses restricted to married women result in
similar, and still statistically significant, associations, although with somewhat lower estimated
risks. There  is a small reduction in the odds ratios after exclusion of single women, however, and
the restriction of the full analyses and results to married women may have been useful.
        Another issue related to exposure concerns inclusion of former smokers in the study,
provided  they had not smoked for at least 20 years. Active smoking 20 to 30 years before the
onset of lung cancer may be of etiological relevance, however, in view of a long latency period for
lung cancer.  Although  use of the same interviewing physician for  all subjects eliminates the
problem of interobserver variability, it leaves open the potential problem of  interviewer bias in
exposure  assessment, presumably toward a positive association, because the interviews were
apparently conducted unblinded (virtually unavoidable with regard to diagnosis, given that
controls were drawn from orthopedic trauma and rheumatology wards).
        A larger concern, however, is the potential effect of risk factors or modifiers not
addressed in the analysis. The authors contend that the similar distribution of demographic
variables  between cases and controls eliminates the need to consider these variables in the
analyses,  but adjusting  for relevant variables is recommended even in a matched study (see Section
5.4.1).  More convincing is the contention that these variables were not significantly associated
with smoking in these data, although no specifics are included.  The appearance of a statistically
significant trend for ETS exposure measured by either current spousal smoking or cumulative
cigarette  consumption during marriage lends further support to an association between spousal
smoking and increased  lung cancer incidence. Potential factors such as diet, cooking, and heating
practices, however, are not addressed.
        Overall, the issues addressed above would probably produce a conservative bias, resulting
in an underestimate of  the degree of association.  The study's basic design is sound. It provides
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statistically significant evidence of dose-response, and although the limitations described above
should be borne in mind, it provides useful data for assessment of the relationship between ETS
and lung cancer.

A.4.31. WU(Tier2)
A.4.31.1. Author's Abstract
       "A case-control study among white women in Los Angeles County was conducted to
investigate the role of smoking and other factors in the etiology of lung cancer in women. A total
of 149 patients with adenocarcinoma (ADC) and 71 patients with  squamous cell carcinoma (SCC)
of the lung and their age- and sex-matched controls were interviewed. Personal cigarette smoking
accounted for almost all of SCC and about half of ADC in this study population.  Among
nonsmokers, slightly elevated RRs for ADC were observed for passive smoke exposure from
spouse(s) (RR =*  1.2; 95% C.I. =  0.5, 3.3) and at work (RR = 1.3; 95% C.I. = 0.5, 3.3). Childhood
pneumonia (RR  = 2.7; 95% C.I.  =  1.1, 6.7) and childhood exposure to coal burning (RR = 2.3;
95% C.I. = 1.0, 5.5) were additional risk factors for ADC. For both  ADC and SCC, increased risks
were associated with decreased intake of /3-carotene foods but not for total preformed vitamin A
foods and vitamin supplements."

A.4.31.2.  Study Description
       This study was  undertaken in California during 1981 and 1982 to investigate the role of
smoking and other factors in the etiology of lung cancer in women.  These other factors included
prior lung disease, coal heating and cooking, diet, and occupation. Both active and passive
smokers are included; some of the ETS analyses retain active smokers while attempting to adjust
for smoking status.
       Cases are white female English-speaking Los Angeles County residents under 76 years of
age at time of diagnosis with primary adenocarcinoma or squamous cell cancer of the lung
between April 1, 1981, and August 31, 1982. Cases are restricted  to U.S.-, Canadian-, or
European-born individuals with no history of prior cancer other than nonmelanoma skin cancer.
Controls are density sampled, matched individually on  neighborhood and age (±5 years), and
meet all case criteria (except, of course, diagnosis of lung cancer). The L.A. County tumor
registry was used to identify incident cases for inclusion in the study, whereas controls were
recruited house to house. Interviews to obtain exposure data were conducted by telephone with
participating subjects, apparently unblinded.
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       A total of 490 eligible cases were identified; 270 were not interviewed because they were
too ill or had died (190), their physician refused permission to contact them (28), they could not
be located (8), or they refused (44).  Those not interviewed did not differ significantly from those
interviewed with regard to age or their marital, religious, or smoking status as recorded on
registry records.  Refusals eliminated 70 potential controls. The case and control populations had
nearly identical mean ages for adenocarcinoma, 59.7 versus 59.5 years, respectively, and for
squamous cell cancer, 61.4 versus 61.1 years, respectively.  No other demographics are provided.
Histologic diagnoses were obtained for all cases.
       For spousal smoking, exposure constitutes having a spouse who smoked while living with
the subject. For workplace smoke, exposure is based on the opinion of the subject. It is not clear
whether for the lung cancer analyses, parental smoking refers only to adult life (as for spousal and
workplace exposure) or to the childhood and teen years (as was stipulated for coal and preadult
lung disease exposures).  Adult life seems most probable.  Units of exposure for spousal and
parental smoking are cigarettes per day and years of exposure, apparently entered into a regression
model as a combined variable; for occupational exposure, units are in  years of exposure. Exposure
data were apparently not checked, treatment of cigar and pipe smoking is never mentioned, and
no results are reported  for household smoking aside from spouse and parents, although
information on this exposure was collected. Never-married women were excluded from the
spousal smoking analysis, but marital status was not otherwise considered in the analyses. The
only histologic or airway proximity information provided for the ETS subjects is that 29
adenocarcinomas occurred among nonsmokers, 12 of which were bronchoalveolar.
       The total study population includes 220 cases and an equal number of matched controls.
Of the cases, 149 are adenocarcinoma and  71 are squamous cell. Nonsmokers constituted 29 of the
adenocarcinoma cases and 62 of the corresponding controls, while composing 2 of the squamous
cell cases and 30 of the controls. No raw data are presented regarding passive smoking and lung
cancer. Logistic regression analysis of matched pairs was used in all calculations. Results
restricted to nonsmokers are presented only for adenocarcinoma. An estimated relative risk of 1.2
is found for spousal smoking, 1.3 for workplace exposure, and 0.6 for smoking by either parent.
None of these estimates was statistically significant.  Exposure from spouses and at work,
however, shows a dose-response trend with years of exposure, yielding estimated relative risks of
1.0,  1.2, and 2.0, for 0, 1 to 30, and 30 or more years of exposure, respectively.
        Analyses that include active smokers but attempt to adjust for them by including the
number of cigarettes smoked per day and age at start of smoking in a logistic regression model are
presented for both lung cancer types.  For adenocarcinoma, estimated relative risks for maternal,
paternal, spousal, and workplace exposure of 1.7, 1.3, 1.2, and 1.2,  respectively, were obtained.
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For squamous cell cancer, maternal, paternal, spousal, and workplace relative risks are 0.2, 0.9,
1.0, and 2.3, respectively. None of these estimates is statistically significant.
       History of lung disease at least 5 years prior to diagnosis of lung cancer reportedly had no
significant association with lung cancer.  History of lung diseases before age 16 yielded a
significant association for pneumonia (RR = 2.7 [95% C.I. = 1.1, 6.7] for adenocarcinoma and
RR « 2.9 [95% C.I. = 0.5, 17.4] for squamous cell cancer) but not for six other diseases.
       Heating or cooking with coal during the childhood and teenage years is also significantly
associated with lung cancer (RR = 2.3 [95% C.I. = 1.0, 5.5] for adenocarcinoma and RR =1.9
[95% C.I. - 0.5, 6.5]  for squamous cell). Among dietary factors, low beta carotene consumption is
significantly associated with adenocarcinoma (RR = 2.7) and mildly associated with squamous cell
(RR - 1.5). Diets low in dairy products and eggs have similar relative risk values. No significant
associations were noted for vitamin A consumption, occupation, or other health history factors not
previously considered.
       The authors conclude that the etiology of squamous cell carcinoma can be explained almost
entirely by cigarette smoking. Cigarette smoking, however, explains only about half of the
adenocarcinoma cases. On the basis of this study, childhood lung disease and exposure to coal
fires in childhood explain at least another 22% of adenocarcinoma cases.  Passive smoking and
vitamin A may be involved, but more research is needed to clarify their roles in lung cancer
etiology.

A.4.31.3.  Comments
       This study took particular care with its treatment of case and control assembly. Extensive
inclusion criteria extending to both groups, matching not only on age but neighborhood of
residence, and retention of matching through analysis all bode well for comparability of cases and
controls.  The virtually identical mean ages of cases and controls indicate the success of these
efforts. In addition, exclusive use of incident cases reduces the potential for selection  bias, and
density sampling of controls reduces potential problems with temporal variation.  The only real
fault in the treatment of cases and controls is the failure to provide any demographic comparison
other than for age, thus denying concrete confirmation of the expected high case-control
comparability.
       Case diagnoses are likely to be  accurate, because all were histologically diagnosed, making
misclassification unlikely and making cell-type-specific analyses possible.  Although no one
pathologist or team verified these determinations, the authors note that there is generally good
interobserver agreement for the cell types included in this study.  Potentially eligible cases not
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interviewed due to illness, refusal, or other reasons did not differ significantly in demographic or
smoking status from those actually interviewed, again arguing against biased selection.
       No proxy interviews were used, and all subjects were English-speakers, enhancing the
chances of obtaining accurate exposure information. On the other hand, interviews were by
telephone—possibly decreasing accuracy relative to face-to-face interviewing—and apparently
unblinded, thus introducing possible interviewer bias toward positive results.
       Collection of exposure data seems generally adequate, except that treatment of pipe and
cigar smokers is not described. This is coupled with an uncertain definition of parental smoking
and lack of treatment of household smokers other than parents or spouses in the analyses, despite
collection of data on this point. These uncertainties probably translate into nondifferential
exposure misclassification, biasing results toward the null.
       The analyses suffer from the common problem of restricted numbers of nonsmoking
cases—29 for adenocarcinoma and only 2 for squamous cell. Some factors examined are restricted
to nonsmokers alone for adenocarcinoma, but for most analyses, an adjustment for active smoking
by logistic regression modeling was  attempted. The adequacy of such adjustment may be
questionable. For adenocarcinoma,  however, the results for passive smoking were very  similar,
regardless of whether restriction or  adjustment was used. Further, a dose-response pattern was
seen for cumulative years of spousal and workplace exposure among nonsmokers. The results of
the analyses for squamous cell are too unstable to be meaningful, given the paucity of cases.
       The findings of substantial associations between lung cancer (or, at least, adenocarcinoma)
and childhood pneumonia and coal burning are of interest.  It must be borne in mind that seven
adult respiratory diseases (including pneumonia) as well as six other childhood respiratory diseases
were examined, so the possibility that the pneumonia association was an artifact of multiple
comparisons cannot be ruled out. History of hysterectomy and multiparity showed nearly    ;,.
significant associations with adenocarcinoma, but it is not clear how many other health  history
factors also were considered. Coal burning has been associated with lung cancer in several other
studies. Similarly, as in several other  studies, one found an association with low beta carotene
intake, but there was no evidence of a dose-response gradient, and no significant association was
found  for preformed  vitamin A.  The strongest association with a dietary factor was actually that
for low intake of dairy products and eggs, which showed a  consistent dose-response pattern.  The
use of a matched-pair analytical approach controls for effects of age or neighborhood, which also
reduces the likelihood of neighborhood-related factors such as socioeconomic status as major
sources of bias.  Confounding due to active smoking can be ruled out in the passive smoking
results for adenocarcinoma and is not likely  in regard  to other factors given adjustment for this
variable in all analyses. Likewise, the authors report that adjustment for childhood pneumonia,
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coal burning, and beta carotene intake did not alter their results. Strangely, however, no
adjustment for dairy product and egg intake—the dietary factor with the most convincing
association with lung cancer in their data—was carried out.
       Overall, this study's results are consistent with a mild association between spousal  and
workplace ETS exposures and lung adenocarcinoma, although they support no such association for
parental smoking.  In addition, the study raises childhood pneumonia, coal burning during early
life, low intakes of beta carotene, and low intake of dairy products and eggs as potential moderate
risk factors that should be considered by future studies.  The results for squamous cell carcinoma
are uncertain given the small number of nonsmoking cases available, and in all instances,  they lack
statistical  significance due to sample size limitations. Thus,  the study provides useful information
on the relationship of adenocarcinoma of the lung with ETS and a number of other factors;
information regarding squamous cell cancer is of less utility for the objectives of this report.

A.4.32. WUWI (Tier 4)
A.4.32.1.  Author's Abstract
       "A case-control study of lung cancer involving interviews with 965 female patients and
959 controls in Shenyang and Harbin, two industrial cities that have among the highest rates of
lung cancer in China, revealed that cigarette smoking is the  main causal factor and accounted for
about 35% of the tumors among women.  Although  the amount smoked was low (the cases
averaged eight cigarettes per day), the percentage of smokers among women over age 50 in these
cities was nearly double the national average.  Air pollution  from coal burning stoves was
implicated, as risks of lung cancer increased in proportion to years of exposure to Kang and other
heating devices indigenous to the region. In addition, the number of meals cooked by deep frying
and the frequency of smokiness during cooking were associated with risk of lung cancer.  More
cases  than controls reported workplace exposures to coal dust and to smoke from burning fuel.
Elevated risks were observed for smelter workers and decreased risks for textile workers.  Prior
chronic bronchitis/emphysema, pneumonia, and recent tuberculosis contributed significantly to
lung cancer risk, as did  a history of tuberculosis and lung cancer in family members. Higher
intake of  carotene-rich  vegetables was not protective against lung cancer in this population. The
findings were qualitatively similar across the major cell types of lung cancer, except that  the
associations with smoking and  previous lung diseases were stronger for squamous/oat cell cancers
than for adenocarcinoma of the lung."
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A.4.32.2.  Study Description
       The objective of this study was to evaluate the role of potential risk factors for lung
cancer in Harbin and Shenyang, two cities among those with the highest mortality rate for lung
cancer in China. Active smokers are included in the cases, so data on ETS subjects constitute a
subset of the whole study.
       Cases consist of female residents under age 70 newly diagnosed with primary lung cancer
in about 70 participating hospitals in Harbin and Shenyang between 1985 and 1987.  Controls are
female residents randomly selected from the general population of these cities and frequency
matched by 5-year age group to the  age distribution of female lung cancer cases reported in the
cities in 1983.  Trained interviewers collected  information on smoking habits, diet, cooking and
heating practices, and other factors from subjects in face-to-face unblinded interviews.
       A total of 1,049 qualifying cases were  found, including both ever-smokers and
never-smokers, of which 405 were diagnosed by histology, 309 by cytology, and 351 by radiology
or clinical means. (Note: These diagnostic numbers  do not total 1,049. The 351 figure may be
intended to be 251, which would give a total of 965 diagnoses, about the number of cases
interviewed.) Of these,  85 either died prior to interview, refused to participate, or could not be
located. Mean age of participating cases was 55.9 years, whereas that of the 959 controls was 55.4
years.  Nonsmokers compose 417 of  the interviewed  cases and 602 of the controls.
       A smoker is defined as a person who has smoked cigarettes for 6 months or longer, so a
nonsmoker apparently may have smoked for up  to 6 months.  Information on all types of tobacco
products smoked was collected. Sources of  ETS exposure include smoking by any household
cohabitant and smoking by individuals (spouse, mother, and father) over the course of the
subject's lifetime.  Exposure at the workplace is also addressed. ETS exposure in the home is
expressed in terms of cigarettes per day and number of years smoked; no units of measurement
are used for workplace smoking. No checks on exposure data were undertaken. Marital status of
subjects is not discussed. Of the cases with histological or cytological data, adenocarcinomas
compose 310 (41.7%), squamous cell cancers 201 (28.9%), small and oat cell cancers 117 (16.8%),
and large cell or unspecified types 66 (9.5%).  No data on airway proximity or diagnostic
breakdowns limited to nonsmokers are provided.
       Statistical analyses of potential risk factors, including ETS, largely include data on active
smokers and then adjust for the effect due to  smoking by logistic regression, along with  other
potential confounders such as age, education,  and location (Shenyang vs. Harbin). These analyses
indicate no increase in risk from household sources of ETS, with estimated  relative risks of 0.8
(household cohabitants), 0.9  (spouse), 1.0 (mother), and  1.0 (father).  The estimated risk  for
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workplace exposure is nonsignificant (RR = 1.2). Restriction of analyses to ETS subjects alone
(i.e., only the nonsmokers) produced similar results, with estimated relative risks of 0.7 for general
cohabitant, 0.7 for spouse, 0.9 for mother,  1.1 for father, and 1.1 for workplace exposure.  The
ETS exposure from spousal smoking is significantly low (i.e., associated with a decrease in lung
cancer by this analysis, as apparent from the confidence interval; RR = 0.7; 95% C.I. = 0.6, 0.9).
       The smoking-adjusted analyses indicate associations with lung cancer for several types of
heating devices, including kangs (brick beds heated by pipes from the stove or by burners directly
underneath), coal stoves, and heated brick walls or floors. The risk associated with the use of
burning kangs (those heated by stoves underneath) shows an upward trend with years of use,
becoming statistically significant at 21  or more years of use (RR = 1.5; 95% C.I. = 1.1, 2.0).
Significantly elevated risks are also associated with use of heated brick walls or floors (RR = 1.5
[1.1, 2.1] for 1-20 years of use; RR = 1.4 [1.1, 1.9] for > 20 years). Nonsignificant increases in
risk are noted for use of kangs of all types, coal  stoves, and coal burners; nonsignificant
reductions in risk are indicated for noncoal stoves and central heat. Deep-frying cooking at least
twice a month and eye irritation during cooking are both significantly associated with lung cancer,
as are regular intake of animal protein and fresh fruit.  (Note:  Multiple comparisons may be a
factor for the apparent significance of some items, as discussed further in the next section.)
       The authors find no overall association between lung cancer and ETS  exposure.  On the
other hand, coal burning, exposure to cooking oil fumes, and chronic lung disease all may be risk
factors. Consumption of beta carotene shows no evidence of a protective effect. Overall, active
smoking is the major cause of lung cancer among women in the regions sampled.

A.4.32.3.   Comments
       The sample size is impressive, with ETS exposure data available for nearly  1,000 cases
including smokers and more than 400 cases when restricted to nonsmokers, thus providing
substantial statistical power. All subjects are women recruited from two industrial cities in
northeast China, reducing potential for complications due to regional or urban-rural differences.
Nearly all of the hospitals in these cities were involved, all cases occurring in these hospitals were
targeted, and the rate of participation among eligible cases was high; thus  potential for selection
bias is minimized. The effective case recruitment in combination with the use of general
population controls maximizes generalizability of the study's results for northeast China.  It would
have been useful, however, to present the results for the two component study locations
separately. Although coordinated in planning and execution, there are two separate study
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locations, and the sources of heterogeneity between them tends to be obscured when results are
combined.
       Unfortunately, the study's results with regard to ETS are more limited than the strengths
listed above might suggest.  The inclusion of age, education, and city as control variables in all
analyses is laudable, thus eliminating the possible influence of these factors. The attempt to
control for potential sources of confounding that may be causally related to lung cancer by
statistical methods, however, is less certain.  Although some analysis was conducted with  data for
active smokers included, to the authors'  credit they also analyzed data for ETS subjects alone (i.e.,
with the data for active  smokers removed), which is the surest way to control for confounding by
active smoking.  Other potential causes of lung cancer (e.g., air pollution from coal-burning
stoves, smokiness during cooking, and deep-fat frying foods) also need to be taken into account in
an analysis of ETS.  This cannot always be accomplished effectively by statistical methods,
particularly when there  are multiple risk factors to be taken into account that are variable, poorly
measured, and possibly more potent risk factors than ETS may be.
       A case-control study is ideally designed and  executed under conditions where cases and
controls are as comparable as possible aside from the factor of interest, such as ETS exposure.
The presence of other risk factors may tend to  pollute and  obscure, much like the contamination
of a laboratory experiment.  In this same sense, the presence of indoor sources of smoke other
than ETS may contaminate an environment for measuring ETS effects because the non-ETS
smoke likely contains many of the same  carcinogens as ETS, and possibly in much larger
quantities, depending on the relative levels of exposure.  Other factors outside the home,  such as
workplace exposure to coal dust and to smoke from burning fuel that was reported more  often in
cases  than controls, contribute to the potential confounding in a similar way. Consequently, a
credible analysis of ETS requires being able to  adjust for these likely confounding factors
satisfactorily, and the ability to do that depends on precise measures of all exposures as well as the
presence of substantial numbers of subjects for various exposure combinations. That kind of
statistical analysis is not given  in the article, and it does not appear to have been possible, based
on conversations with the authors (Wu-Williams and Blot) and the text of the article: "Despite the
large  size of our study, we were unable to clarify the magnitude of risks due to passive smoking,
recognized as a cause of lung cancer around the world (U.S. DHHS, 1986). Perhaps in this study
population the effects of environmental  tobacco smoke was obscured  by the rather heavy
exposures to pollutants from coal-burning  Kang, other indoor heating sources, and high levels of
neighborhood air pollution (Xu et al., 1989)."
       The potential rate of non-ETS sources of indoor air pollution, particularly coal
combustion, appears exceptionally .strong in the study area. For example, a case-control study of
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primary lung cancer in urban Shenyang residents aged 30-69 in 1985-87 reports that the age,
education, and smoking-adjusted OR for kang use among women ranges from 1.9 to 3.4, the latter
figure being for the higher exposure level (at least 50 years of use). Fully 44% of the controls and
55% of the cases are at the highest exposure level, and only 3% of controls and less than 1% of
cases have no exposure. Benzo[a]pyrene levels in 30 homes sampled during the winter averaged
60 ng/m3, which is 60 times the U.S. recommended limit, and indoor measurements in single and
two-story homes were even higher (Xu et al., 1989).  Abstracts of two papers published in Chinese
indicate that similar conditions exist in Harbin. Sun (1992) found a smoking-adjusted OR for soft
coal use of 2.26 with a highly significant trend for duration of exposure among female residents.
Also, Wang (1989) reports ORs of 10.6 for high coal consumption and 15.2 for "indoor smog
pollution in winter" among females in Harbin. It is noted that winter levels of benzo[a]pyrene are
26.7 times higher in residents' bedrooms than outdoors, suggesting that indoor coal combustion
may even be more of a problem in Harbin than Shenyang.
       The multivariate analysis reported in the article reinforces the viewpoint that any ETS
effect may be dominated by the presence of other risk factors. In that analysis, variables were
allowed to enter a logistic regression model in the  order of their explanatory value (a stepwise
regression exercise in statistical terminology). The order of entry into the model is deep frying,
eye irritation,  pneumonia, household tuberculosis, burning kang, self-reported occupational
exposure to burning fuel, passive smoking,  and heated brick wall or floor. Passive smoking, in
this exercise, is significant (p < 0.05) but in the direction of reducing lung cancer, not
contributing to it.  The 0.05 value, however, is not fully meaningful as a significance level for
ETS, because of the stepwise procedure used (the same data used in the construction of a model is
used for testing variables in the model) and because of the likely confounding between ETS and
other variables.  Note, for example, that passive smoking entered the model ahead of heated  brick
wall or floor, which is highly significant when analyzed alone, whereas passive smoking is not.
       The evidence for association of lung cancer with burning coal and deep-frying foods is
particularly provocative, as it indicates two factors that may play a substantial role in the etiology
of lung cancer in northeast China and, hence, in other areas as well where such practices occur.
The associations noted with other factors are also of interest, but their importance is undermined
by the problem of multiple comparisons.  In the table presenting results for dietary factors, for
example, 26 risk estimates are computed, 4  of which are significant at the 5% significance level
(for a two-sided test, 2.5% level for the test of an effect), only one more significant finding than
expected due to chance alone.
       Being somewhat speculative, the use of cases age 70 and below may be a factor.  Wells
(1988) showed that about one-half of the female passive smoking deaths occur after age  70 for the
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studies included in that reference.  If ETS is a risk for lung cancer and if individual susceptibility
to lung cancer is a factor, some of the stronger risk factors such as coal burning and cooking oil
may have caused lung cancer in the more susceptible subjects before passive smoking had a
chance to exert itself.
       In summary, this large and basically well-executed study observed no significant
association between exposure to ETS from cohabitants, spouse, parents, or workplace and lung
cancer.  Lack of control for a number of other significant risk factors identified in the study
undermines these results, however.  The associations with coal burning for heat and oil frying are
particularly notable. Use of the heating devices most strongly linked with lung cancer is
presumably more common in colder northern regions, whereas stir-frying may be more
widespread in Asian communities, without regard to climate. Thus, this study was exploratory,
designed to generate hypotheses rather than to test the specific hypothesis that ETS exposure is
associated with lung cancer.  It identifies a number of potential  risk factors for consideration in
future studies.  The prevalence of these factors in the study population combined with the lack of
analysis of their association with ETS exposure, however, renders the  results for ETS inconclusive.
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             APPENDIX B






METHOD FOR CORRECTING RELATIVE RISK




    FOR SMOKER MISCLASSIFICATION
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               APPENDIX B.  METHOD FOR CORRECTING RELATIVE RISK
                           FOR SMOKER MISCLASSIFICATION

B.I. INTRODUCTION
       The purpose of this appendix is to present the details of the method used in Section 5.2.2.
to correct observed passive smoking relative risks for the systematic upward bias caused by
misclassification of some smokers as never-smokers. The method used is that proposed by A. J.
Wells and W. F. Stewart (Wells, 1990) with minor modifications, including an adjustment for
passive smoking risk to smokers. This appendix covers the following:  the principles of the
method (Section B.2); how the method differs from those previously used by the National
Research Council and P. N. Lee (Section B.3); the data used to calculate the misclassification
factors and other parameters (Section B.4); the mathematical model used to calculate the corrected
relative risks (Section B.5); and a numerical example to show how the method is applied in a
practical case (Section B.6). The results show that the bias due to smoker misclassification is
highly unlikely to be responsible for the increased risks observed in the passive smoking lung
cancer epidemiology studies. Evidence is also presented suggesting that the true downward
corrections for smoker misclassification bias may be even smaller than those developed below and
used in Section 5.2.2. While some of the rates presented below are subject to variability and
argument, attempts are made to provide reasonable  estimates and a defensible methodology.
       There is considerable literature on this topic and a history of controversy regarding the
magnitude of the bias and whether it may explain the observed increase in lung cancer mortality
due to ETS exposure. The NRC report on the health effects of passive smoking (NRC, 1986)
delves into this topic in considerable detail. It concludes that bias  is likely; further, it estimates an
adjustment for the summary relative risk from the combined results for all ETS studies. The NRC
report further concludes that smoker misclassification does not account for the observed passive
smoking risk.  On the other hand, in various publications Lee (1987b, 1988, 1990, 1991a) has
claimed that the smoker misclassification bias is large enough to explain most or all of the
observed passive smoking lung cancer risk.
       Approaches to estimation of misclassification bias have used mathematical modeling with
parameters estimated from a variety of sources that have not always been consistent.  The
procedure described below attempts to rectify some previous sources of misunderstanding on this
topic and utilizes the extensive data sources now available to improve parameter estimates and
tailor refinements to individual populations.
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B.2. PRINCIPLES OF THE WELLS-STEWART METHOD
       The Wells-Stewart method is based on the following principles, the nature and need for
which have largely become apparent from the chronological evolution and disparate approaches to
and results for this problem.
       The parameters are:
       a.  Since the passive smoking epidemiology is essentially concerned entirely with self-
           reported never-smokers, it is necessary to limit the misclassifieds to those who  said
           they never smoked, not simply to nonusers, because the latter would include a
           substantial proportion of self-reported former smokers.
       b.  Use one minus sensitivity or its close relative, false negatives (misclassified  smokers)
           divided by observed positives (self-reported smokers) as the vehicle for transferring
           misclassification  data from cotinine and discordant answer studies to the passive
           smoking studies.  Sensitivity is the term used to describe the fraction correctly
           classified as exposed, namely, true positives divided by true positives plus false
           negatives, but since we are assuming that the true positives and the observed positives
           are the same (no  misclassification of never-smokers as smokers), sensitivity in  this
           case becomes observed positives divided by observed positives  plus false negatives.
           Then one minus sensitivity becomes false negatives divided by observed positives plus
           false  negatives.  Ignoring the false negatives in the denominator introduces  negligible
           error. In any case, do not use specificity (true negatives divided by true negatives plus
           false  positives) or any parameter that uses as its denominator true  or observed
           negatives (self-reported never-smokers).  The reason is that sensitivity is  affected
           much less by smoker prevalence  than parameters based on observed negatives.
       c.  Calculate a correction for each epidemiologic study separately  using a misclassified
           smoker relative risk and a proportion of smokers among subjects and spouses that is
           characteristic of  the timeframe and locale of each study.  Use data from the study
           itself or from another study with the same target population, if possible.
       d.  Use only female  data to correct misclassification of female subjects.
       For the mathematical model, calculate the  corrected risk directly—that is, do  not first
 calculate a bias assuming no  passive risk and then divide the observed risk by that bias  to get a
 corrected risk.
       Subjects found to be misclassified as nonsmokers are categorized according to their self-
 reported smoking status—former or current.  Misclassified current smokers are further classified
 as "regular" or "occasional," according to observed cotinine levels. "Regular" means the  cotinine
 level is above 30% of the self-reported smoker mean; "occasional" applies to the range 10% to 30%.
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Cotinine levels are not informative for misclassified former smokers, who tend to be long-term
abstainers (10+ years, according to Lee [1987b] and Wald et al. [1986]). The two studies with
detailed cotinine levels on female current smokers (Lee, 1986 and Haddow et al., 1986, in Table
B-l) indicate that about 10% of the current smokers are occasionals.

B.3. DIFFERENCES FROM EARLIER WORK
       The Wells-Stewart method differs from the method used by the NRC (1986), which is also
described by Wald et al. (1986), in that the NRC method failed to separate the misclassified
smokers into regular, occasional, and ex-smokers, and failed to account for the effect of smoker
misclassification on active smoker risk. The NRC made an overall correction to the aggregated
passive relative risk using United Kingdom (U.K.) smoking prevalence and risk rather than
making the corrections study-by-study with appropriate smoking prevalences and risk for each
study's time and locale, and it mixed male data with female data in arriving at misclassification
factors.  Their calculated bias of 1.34/1.25 = 1.07, or 7%, for the combined worldwide studies is
substantially higher than the 2% overall bias that would result if the biases in Table 5-7 were
aggregated. The discrepancy is largely due to NRC's use of U.K. parameters for all of the studies
regardless of locale, plus some overestimation of the impact of misclassified occasional and ex-
smokers.
       Lee's methods have evolved over the years in three stages.  In Lee (1987b, 1988), he
improved on the NRC method in that he divided the misclassified smokers into ex-smokers and
current regular and occasional smokers, and he corrected the smoker risk for misclassification.
However, all of the five principles listed above were violated to some degree, resulting in about a
twelvefold overestimation of the bias (Wells, 1992).  The Lee (1990) paper correctly limits
misclassifieds to never-smokers, relates misclassified smokers to smokers, not to never-smokers,
and treats each study separately, but still mixes male input data with female data for use in
calculating bias for females.  Furthermore, his mathematical model  still relies on the assumption
of a passive smoking relative risk of 1.00 (no risk), an assumption that fails at passive risks above
about 1.3 and overstates those biases.  In addition, Lee (1990) has changed from separating the
misclassified smokers into three  groups in favor of the (less useful) overall category of "ever-
smokers." Most recently, Lee (1991a) presented a more complex mathematical model that includes
a term for passive risk, but the method still has the other shortcomings noted for Lee (1990).  A
comparison of the most recent Lee bias estimates with those in Table 5-7 is shown in Table B-2
for the five U.S. studies with the greatest statistical weight. When Lee's inputs are used with the
Wells-Stewart mathematical model, the calculated biases are, if anything, somewhat larger than
when using Lee's most recent model.  Therefore,  the difference between Lee's most recent
                                            B-3
-------
Table B-l. Observed ratios of occasional smokers to current smokers (based on cotinine studies)
Study
Lee (1986)
Coultas
etal. (1988)
Haddow
et al. (1986)
Feyerabend
et al. (1982)3
Jarvis (1987)
Pojer (1984)
Wald et al.
(1984)
Overall
Females , , ] '",
-^ ? ffts
Occl.2 Current Occl./current Qccl
4 72 0.056 12
59
10 64 0.156
7
12
25
13
14 136 0.103 128
Both
Current
176
278

82
90
187
131
944
sexes1
Qccl./eurrent
0.068
0.212

0.085
0.133
0.134
0.099
0.136
JThe "both sexes" data are shown to indicate that the female value of 10.3% is not unduly high.
2Occasional smokers are defined as persons who have cotinine levels in body  fluids that are
 between 10% and 30% of the mean of all self-reported current smokers.
3The Feyerabend et al. (1982) data are for nicotine.
estimates of bias and those shown in Table 5-7 are in practical terms due almost entirely to
differences in input parameters.  The input parameters we have chosen are developed in the next
section, and comparisons with the Lee parameter estimates are shown as footnotes to Table B-2.

B.4. PARAMETER ESTIMATES
       The key input in these calculations is the proportion of misclassified regular current
smokers who claim they have never smoked.  Our definition of misclassified regular current
smokers, first suggested by Lee (1987b), produces a mean cotinine level approximately equal to
that of all self-reported current smokers. Detailed data from  three large cotinine studies have
been assembled for use herein with the cooperation of their principal investigators (Coultas,
Cummings, and Pierce in Table B-3).  The data identify individual nonsmokers with cotinine
values greater than 10% of the mean for self-reported smokers, by sex and self-reported smoking
status (never or former). Data on nonusers are also available from several other studies (the lower
                                            B-4
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-------
Table B-3. Misclassification of female current smokers
Self -reported smoking status number

Study
Coultas et al. (1988)2


Cummings (1990)3


Pierce et al. (1987)4


Subtotal


Lee (1986)5


Haddowetal. (1986)5


Haddow et al. (1988)5


Riboli (1991)5'6~U.S.7


Riboli (1991)5-6--East Asia8


Riboli (1991)5'6— Greece9


Total


Proportion misclassified10

Cotinine
level1
10-30
30+
All
10-30
30+
All
10-30
30+
All
10-30
30+
All
10-30
30+
All
10-30
30+
All
10-30
30+
All
10-30
30+
All
10-30
30+
All
10-30
30+
All
10-30
30+
All
10-30%
30+

Never
7
5
387
0
2
225
9
3
232
16
10
844
3
3
333
1
0
174
15
1
1,128
1
0
224
1
1
325
0
0
96
37
15
3,124
24.2%
1.09%
Number
Former
3
8
79
1
0
143
4
3
79
8
11
301
2
2
125
1
1
58
7
1
380
0
0
81
1
0
25
0
0
5
19
15
975
12.4%
1.09%

Current


184


116


167
(67% never)
(48% never)
467


256


64


503


143


77


15


1,525


                                                          (continued on the following page)
                                          B-7
-------
Table B-3. (continued)

 JCotinine levels are in units of percentages of the mean of self-reported smokers for each study;
 30+% are defined as current regular smokers, 10-30% are occasional smokers.
 2Dr. Coultas kindly provided the individual cotinine values for females ages 18+ that were used m
 Table 3 of their paper. The totals differ slightly from the totals in the paper.
 3Dr Cummings kindly provided the cotinine levels for the six misclassified current smokers,
 three males and three females. As noted in the paper, current smokers were recruited during
 only the first half of the study. Therefore, the total equivalent current smokers were estimated
 from the current  smoker/never-smoker ratio from national statistics.
 Individual cotinine levels for the misclassifieds by gender are from a personal communication
 from Petra Macaskill, who now has the basic data for this study.
 5For Lee (1986), Haddow et al. (1986, 1988), and Riboli (1991), no breakdown was given between
 "Never" and "Former."  An estimate was made based on the subtotal distribution. The number ot
 smokers had to be estimated in some cases. The mean for self-reported smokers for Haddow et
 al. (1988) was very low, at 145 ng/mL, because the women were pregnant.
 6Personal communication—individual country data from Riboli et al. (1990).
 7New Orleans, Los Angeles, and Honolulu.
 8China (Shanghai), Hong Kong, and Japan  (Sendai).
  AtHcns
 1&The observed current smokers are assumed to be 90% regular (1,372) and 10% occasional (153)
  smokers  For regular smokers, misclassification as never-smokers is 15/1,372 = 1.09% of
  observed current regulars or 15/(1,372 + 15 + 15) =  1.07% of true current regulars.  For
  occasional smokers, misclassification is 37/153 = 24.2% of observed current occasional or
  377(153 + 37 + 19) = 17 7% of true current occasionals.  For current smokers misclassified as
  former smokers,  the factors are 15/1,372 = 1.09% for observed and 15/1,402 = 1.07% for true
  regular smokers, and 19/153 = 12.4% for observed and  19/209 = 9.1% for true occasionals.


 portion of Table B-3). The proportions of misclassified  smokers who would have said "never"

 versus "former" are estimated using the proportions observed in the first three studies. Data sets

 not differentiating outcomes by sex have not been used.  Also, the large 1987 study by Haddow

 and colleagues has not been used for this purpose on the advice of one of the authors (personal

 communication from G.J. Knight). This study of the effect of current smoking on birthweight

 relied on the cotinine data to distinguish smokers from nonsmokers. The questionnaire data were

 not collected in a  manner that could be equated to the care that would be taken in either their or

 others' passive smoking studies.
        The number of self-reported never- and former smokers with sufficiently high cotinine

 levels to be reclassified as current smokers  is shown by study in Table B-3.  As described above,

 those with cotinine levels in the 10-30% range are considered to be occasional smokers, whereas

 those above 30% are treated as regular smokers.  If it is assumed (Table B-l) that 1,372 (90%) of

 1,525 self-reported current smokers are regular smokers, leaving 153 (10%) as occasionals, then

 the percentage of current regular smokers misclassified as never-smokers totalled over all studies

 in Table B-3 is 15/1,372 or 1.09%. The percentage is almost the same if the number of true, i.e.,
                                             B-8
-------
self-reported plus misclassified current regular, smokers is used. For the occasional smokers only,
the misclassification rate is much higher, about 24% (18%) of observed (true) occasional smokers.
It is possible, however, that the subjects classified as occasional smokers based on cotinine levels
in the range 10-30% may contain some true never-smokers that are just highly exposed to passive
smoke.
       The cutoff points used, namely, 30% of the self-reported current smoker mean cotinine
level to distinguish misclassified regular smokers from occasional smokers and 10% of the self-
reported current smoker mean cotinine level to distinguish occasional smokers from current
nonsmokers, were chosen originally by Lee (1987b). They are justified as follows:  the actual
cotinine levels of the 15 misclassified current smokers in the Never column of Table B-3 whose
levels exceeded 30% of the mean cotinine level for self-reported current smokers in each study
were divided by the mean smoker cotinine level for that study. These values were then averaged
for each study, and a mean for all studies was obtained by weighting each study's mean by the
number of smokers in that study.  The overall mean cotinine level for the misclassified smokers
was 94% of the mean for all of the self-reported smokers because the misclassifieds tended to
concentrate near the bottom of the 30%+ range. A cutoff  of 35% could be justified since the
misclassifieds' mean cotinine level was 99% of the mean for the self-reported smokers, but we
chose to continue with 30% to  be conservative.
       The cutoff between the current nonsmokers and the occasional smokers must be somewhat
arbitrary because there is an overlap between heavily ETS-exposed nonsmokers and very light
current smokers.  Authors who have tried to eliminate all possible smokers from their cohorts have
used lower cutoff points. For example, Coultas et al. (1988), Cummings (1990), and Haddow et al.
(1988), who were trying to eliminate smokers, used cutoffs between 7% and 8%.  However, Pierce
et al. (1987) and Lee (1986), who, as we are, were trying to distinguish smokers from nonsmokers,
used higher cutoffs, 16% and 9%, respectively.  The mean  of the percentages (calculated as above
for the misclassified current regular smokers) that the misclassified occasional smokers' cotinine
levels bear to the mean of the self-reported current smokers is 16% for the seven studies in Table
B-3. This is lower than the midpoint of the 10-30% range, again because the individual values
concentrate at the lower end of the range. If we had used  a 5% cutoff instead  of 10%, the
misclassifieation rate for occasional smokers would have been increased from 24% to about 40%,
but the average of the percentages of current self-reported mean cotinine levels for the
misclassified occasional smokers would have dropped from 16% to 13%. This in turn would
reduce the estimated smokers' relative risk for this group,  and the overall effect on the corrected
risk of never-smokers would be negligible.
                                           B-9
-------
       The studies in Table B-4 provide data on discordant answers, i.e., reported never-smokers
who have called themselves smokers on one or more previous occasions. Based on those data, the
estimated percentage of former smokers misclassified as never-smokers is  11.7% (10.8%) of the
observed (true) number of former smokers.  As mentioned previously, evidence suggests (Wald
et al., 1986; Lee, 1987b) that most former smokers misclassified as never-smokers have been
nonsmokers for an extended period, such as  10+ years, and may have been light smokers on
average.  Accordingly,  we have used a weighted average of the data of Alderson et al. (1985),
Lubin et al. (1984), and Garfinkel and Stellman (1988) for 10+ year abstainers to estimate
misclassified former smoker relative risk, namely, an excess risk that is 9% of current self-
reported smoker excess risk.
       Some confusion and misleading conclusions on smoker misclassification have resulted from
the practice of expressing the number of smokers misclassified as never-smokers as a percentage
of the total number of (either true or observed) never-smokers, rather  than as a percentage of the
number of smokers.  That leads to a higher expected percentage of smokers misclassified as never-
smokers among cases than controls because lung cancer cases are much more likely to have been
smokers than never-smokers.  Some people (Lee,  1988) have interpreted a higher percentage of
observed never-smokers later found to be misclassified smokers among the cases as evidence that
smokers with lung cancer are more apt to claim falsely to be never-smokers than persons without
cancer.  That conclusion, however, appears to  be an artifact of treating the misclassification rate
as a percentage of the number of never-smokers rather than as a percentage of the number of
smokers. The study data summarized in Table B-5 do not support that conclusion. If anything,
they are more supportive of the conclusion that ever-smokers in lung cancer studies may be less
likely to misrepresent themselves as never-smokers than members  of the general public who are
questioned in community surveys.  The 1.0% average misclassification  rate shown in Table B-5 for
the lung cancer cases suggests that estimates such as the 5.7% from the general population studies
(Table B-5) or the equivalent of 3.9% of ever-smokers (Table B-4) that we have used may be
much too high. Further corroboration that the misclassification rates from the community studies
are too high relative to those in the epidemiologic studies is found in the recent lung cancer case-
control study by Fontham et al. (1991), which specifically included in its design a screening by
urinary cotinine levels  to eliminate current smokers from both cases and controls. After
eliminating possible smokers among the self-reported never-smokers by the usual epidemiologic
questionnaire and medical records review techniques, the investigators found by cotinine
measurements that only two probable occasional smokers and no probable regular smokers were
left among the 239 never-smoking  lung cancer cases for which cotinine measurements were made.
Using the procedures herein and assuming 43% ever-smokers among controls and an ever-smoker
                                           B-10
-------
Table B-4. Misclassification of female former smokers reported as never-smokers based on
discordant answers
Reported never-smokers
who reported earlier that
they had smoked1
Study Locate
Kabat and Wynder
(1984)2 U.S.
Controls
Cases
Machlin
et al. (1989) U.S.
Krall et al. (1989)3 Mass.
Britten (1988)4 U.K.
Lee (1987b) U.K.
Akiba et al. (1986) Japan
Overall5
Former
smokers
-------
Table B-5. Misclassification of female lung cancer cases
Source
•••••••••BHHHHMMBMHMMMI
CHAN
Chan et al. (1979)1
KABA
Kabat and Wynder (1984)2
AKIB
Akiba et al. (1986)
PERS
Pershagen et al. (1987)
HUMB
Humble et al. (1987)3
Total
General population4
''"Number of ever-sxaokers
12

652

38

179

223

1,104
1,838
Number Husclassifsecl
1

7

0

2

1

11 (1.0%)
104 (5.7%)
 !Chan sampled five Type I and II never-smokers, one of whom was said by a relative to have
 smoked a few hand-wrapped cigarettes for a year at age 71. The ratio of smoking to nonsmoking
 cases for Types I and II was 44/19, which, multiplied by 5, leads to 12 estimated ever-smokers.
 2Dr. Kabat (personal communication) advised that of 13 misclassifieds, 8 were females, 1 of whom
 used snuff.
 3Of the four misclassifieds found, Dr. Humble (personal communication) has advised that most if
 not all  were males. We have assumed one female.
 ''The general population data are taken from the four nonlung cancer cohorts in Table B-4,
 namely, Machlin et al. (1989), Krall etal. (1989), Britten (1988), and Lee (1987b).
 relative risk of 8, which translates to 10 for misclassified current regular smokers, 2.44 for
 misclassified occasional, and 1.81 for misclassified ex-smokers, there would have been 1,363
 smoker cases, consisting of 1,328 current smokers and 35 occasional smokers to go along with 420
 never-smoking cases. It is seen that a misclassification rate of 0/1,328 = 0.00% for regular
 smokers is well below the 1.09% that we have used from the surveys in Table B-3. For
 occasionals, there would be 20 cases to go along with 239 never-smoking cases, yielding a
 misclassification rate of 2/20 - 10%, which is also well below the 24.2% for occasionals that we
 have used from Table B-3.
        Another indication that the estimates based on community surveys may be too high comes
 from analysis of male data.  The observed percentage of never-smokers is typically much lower
 for males (17% to 35%) than females (41% to 86%).  To correct for smoker misclassification, we
 set up a table analogous to Table B-6 where the number of current and former smokers
                                           B-12
-------
 Table B-6. Deletions from the "never" columns in Tables B-13 and B-16 and corrected elements
Wife's smoking status
Husband's
smoking status
Table B-13
(controls)
Table B-16
(cases)

Never
Ever
Never
Ever
Former
CD
0.00679
0.01275
0.00198
0.00770
QccL
(2) *
0.00194
0.00532
0.00120
0.00365
Regular
(3)
0.00081
0.00219
0.00217
0.00604
Sum1
(4)
0.00953
0.02027
0.00534
0.01739
Observed
never
(5)
0.286
0.242
0.052
0.092
Corrected
never2
#)
0.27647
0.22173
0.04666
0.07461
 2(6) =
 misclassified as never-smokers are subtracted from the reported number of never-smokers.  When
 the misclassification rates generated from community surveys are applied to the male data* the
 outcome is not credible—the number deleted for misclassification exceeds the total number of
 reported never-smokers in 3 of the 11 examples of which we are aware and drives the corrected
 relative risk well below unity in 4 more. This outcome indicates that the misclassification rates
 derived from the community surveys are too high. It is probable that the true smoker
 misclassification bias is on the order of one-fourth to one-half of the values shown in Table 5-7.
       It has also been suggested (Lee, 1991b) that East Asian women misclassify themselves at
 much higher rates than Western women. The data from the International Agency for Research on
 Cancer (Riboli, personal communication) in Table B-3 do not support that claim, however,
 because the East Asia (Hong Kong, Japan, and China) misclassification rate for current regular
 smokers is  1/77 = 1.3%, which is not much different from the overall rate of 1.09%.
       In conclusion, it would appear that the bias introduced by misclassification of smokers as
 never-smokers is not a serious problem. It probably increases observed excess relative risks on a
 worldwide basis by about 1% and for combined U.S. studies by about 3%.

 B.S. MATHEMATICAL MODEL
       The proportion of smokers, mh0, misclassified as never-smokers is estimated separately for
 former smokers (m10), occasional smokers (m20), and regular smokers (m30).  Similarly, the
proportion of current smokers, mhl, misclassified as former smokers is estimated separately for
occasional smokers (m21) and regular smokers (m31).  These estimates are given in Tables B-3 and
B-4. It is assumed that there is no misclassification of true never-smokers as current or former
                                          B-13
-------
smokers or of true former smokers as current smokers.  Also, these misclassification factors are
used for all the studies unless otherwise noted. We suspect that misclassification rates probably
vary from study to study. That variability, however, would tend to cancel out as the individual
study results are combined.
       Let cijk designate the observed distribution of controls (i = 0) and cases (i = 1) by their
smoking status (j = 0,1,2,3) and the smoking status of their husbands (k = 0,1), as illustrated in
Table B-7. Following the notational convention that a dot in the subscript position means
summation on that subscript, then c0.. = Cj.. = 1.
       The observed c^'s are corrected for misclassification of the wife's smoking status by first
specifying a 4 x 4 matrix of distribution (Table B-8), where Phj (h,j = 0,1,2,3) is the probability
that a subject with true smoking status h will also be observed to have smoking status j. The
subscripted notation is shown in Table B-8 for easy reference.  P.. is equal to unity.
       For passive smoking, we are interested only in correcting the ci0k values that are for the
observed never-smokers. It is assumed that the Phj's are the same for cases and controls
(nondifferential misclassification). For given values of wife's subject status  (i) and husband's
smoking status (k), the correction when the wife's observed smoking status is "never" (j = 0) is:
                                                                                       (B-l)
 where C;ok is the corrected form of the element ci0k.  Then the corrected passive risk, RR(c),
 becomes:
                              RR(c) = (C,oi  x
 The values of c0jk in Table B-7 are from prevalence data in the study itself or from a related
 study, from concordance data, and from each study's data on the smoking prevalence of the
 never-smokers' husbands. If necessary, the number of former smokers can be estimated from the
 ever-smokers based on data from nine studies known to us where the percentage of both current
 smokers and former smokers  is known (see Table B-9). These data indicate a time trend in
 nontraditional societies, from 20% former smokers relative to  ever-smokers in 1960 to 45% in
 1985; we estimate an 8-year lag for the traditional societies such as Hong Kong, China, Japan, and
 Greece, based on the data in  Koo et al. (1983) and Sobue et al. (1990).
                                             B-14
-------
Table B-7.  Notation for distribution of reported female lung cancer cases and controls by
husband's smoking status
Wife's observed smoking status (j)
Wife's
subject
status (!)
Control
(i = 0)

Case
(i-D

Husband's
smoking
status (k)
Never (k = 0)
Ever (k = 1)
Total
Never (k = 0)
Ever(k= 1)
Total
Never
( j - 0}
cooo
C001
coo-
C100
C101
C10-
Ex OccL
0*1) 0*2)
C010 C020
C011 C021
C01- C02-
C110 C120
clll C121
cll- C12-
Reg.
0 * 3) Total
C030 C0-0
C03i CQ-I
C03- C0- ( = 1)
C130 cl-0
C131 cl-l
c,, .„,_(•-„
Table B-8. Notation for distribution of subjects by observed and true smoking status
'
Wife's observed
smoking status 0)

Never (j = 0)
Former ( j = 1)
Occl.(j = 2)
Reg- 0 = 3)
Total
Wife's true smoking status (h)

Never Former Occl, Reg.
(h = 0) (h=l) (h = 2) (h-3)
POO PIO P20 P30
P01 Pi! >21 P31
P02 Pl2 P22 P32
PP "D T>
A-J •* 1 1 Jr oa - Jr -ao
"J = U 
-------
Table B-9. Observed ratios of female former smokers to ever-smokers in the U.S., U.K., and
Swedish studies:  populations or controls (numbers or percentage)
Study
Hammond (1966)1
Buffler
etal. (1984)2
Wu et al. (1985)2
Lee (1987b)3
Brownson
et al. (1987)2
Britten (1988)3
Humble
et al. (1987)2
Svensson
et al. (1989)2
Garfinkel and
Stellman (1988)1
Time-
frame
1960
1978
1980
1980
1980
1982
1982
1984
1982
Never-
smokers
78.0%
41%
92
48.3%
47
767
162
120
58.9%
Current
smokers
17.6%
38%
73
33.6%
11
558
63
53
18.7%
Former
smokers
4.4%
21%
55
18.1%
8
320
48
36
22.4%
Ever-
smokers
22.0%
59.0%
128
51.7%
19
878
111
89
41.1%
Former/ever-
smokers
0.20
0.36
0.43
0.35
0.42
0.36
0.43
0.40
0.54
Assumed ratios bv vears (nontraditional societies)4

Year
Ratio
1960 1965
0.20 0.25
1970
0.30
1975 1980
0.35 0.40
1985
0.45

       age distribution of never-smoking cases.
 2Using age distribution of ever-smoking cases.                                ,
 3Smoking status of general population.
 ''Traditional societies (Japan, Greece, China, Hong Kong) are estimated to lag these ratios by
 about 8 years, based on data in Koo et al. (1983) and Sobue et al. (1990). However, because the
 bias for the traditional societies is very low, changes in values of this parameter have little effect.

       To calculate the individual elements, c0jk, of Table B-7, it is necessary to establish
 concordance factors—that is, the cross products in 2 x 2 tables of smoking status of husbands and
 wives by smoking level of the wives. Using data from Sutton (1980), Lee (1987b), Akiba et al.
 (1986), and Hirayama (1984) and the detailed data in Lee (1987b) on never-smokers, current
 smokers, and former smokers, we have calculated that an appropriate average concordance factor
 for current smoking wives and ever-smoking husbands versus never-smoking wives and never-
 smoking husbands is 3.2; for ever-smoking  wives and husbands versus never-smoking wives and
 husbands, it is 2.8, and for former smoking wives and ever-smoking husbands versus never-
                                            B-16
-------
smoking wives and husbands, it is 2.2. These concordance factors can be expected to vary from
study to study, but the effect of the variability should tend to cancel out as the studies are
                                               3        - • -         .     •      .• •  •
aggregated. The element CQQ. and a quantity s0 = JT CQJ. are obtained from smoking prevalence
                                              j=i
data in the study itself, in a related study on the same cohort, or as a last resort from national
statistics.  If national statistics are used, care must be taken to use the rates from an age
distribution that is consistent with the age distribution of the passive smoking cases. The elements
C0j. and c02. + c03. are taken from the  study or are estimated from Table B-9.  The element c02. is
estimated to be 10% of (c02. + c03.); c03. is 90%. The elements CQQQ and cmi are obtained from c00.
and the proportion  of never-smoking controls in the study who are married to either never-
smokers or ever-smokers. The elements COK) and con are obtained by solving the equations
                                                              3               3
coio + con = coi- and (cooo x con)/(cooi x coio) = 2-2-  Terms s^ = £ cojo and s01 = £ c0jl are
                                                             j=i             j=i
obtained from the equations SQQ + sol = s0 and (s01  x CQOO)/(CQQI x SQQ) = 2.8. Then c020 + c030 =
soo ~ coio anc* C02i + C03i = soi ~  con- The values of c020 and c02, are then assumed to be  10% of
C020 + coso anc* C02i + C03i> respectively, and c030 and c031  are assumed to be 90%.
       To obtain the elements for the subject cases (i =  1) in Table B-7, it is necessary first to set
up relative risks for the passively exposed (k = 1)  and not passively exposed (k = 0) wives by
observed smoking status (j = 0,1,2,3). These risks are shown in Table B-10.
       In most instances, the relative risk, RR(e), for female ever-smokers can be obtained from
the study itself or from a related paper (Table B-11). In a few instances, it is necessary to
estimate RR(e) from other "studies similar in time  and locale.  In some papers, a current smoker
risk also is given. We assume (see explanation above) that  the misclassif ied regular smoker risk,
RR(a)3, is equal to the self-reported current smoker risk.  Where only RR(e) is available, RR(a)3
can be assumed to be equal to 1.24 x  RR(e) based on the data in Table B-12.  Because occasional
smokers have mean cotinine levels that are  16% of those of regular smokers, it is assumed that
RR(a)2 - 1 = 0.16(RR(a)3 - 1), and because the former smokers  (j =  1) are  said to be, on average,
long term (Wald et al.,  1986; Lee, 1987b), we have averaged the data of Alderson et al. (1985),
Lubin  et al. (1984), and Garfinkel and Stellman (1988) for the ratio of excess risk of 10+ year
former smokers to the excess risk for  current smokers and  found it to be 9%.  Thus, RR(a), -  1 =
0.09(RR(a)3-l).
                                            B-17
-------
Table B-10. Notation for observed lung cancer relative risks for exposed-(k=l) and nonexposed
(k=0) wives by the wife's smoking status, using average never-smoking wives RR(a)0 as the
reference category
^ ,"•" ,'"•''- WifeTs smoking status
Husband's
smoking status
Never (k=0)
Ever (k=l)
Weighted avg.
active risk
Passive risk1
RR(p)j -
RRjI/RRjO
Never- s
,0 = 0)
RRoo
RR01
RR(a)0= 1.00

RR(p)o
Formet
(j-'l) x
RR10
RRn
RR(a)i

RR(p)l
v ^ fs ^
^,IT_pccL , R-eg.
"DO 1? U
K.K.2Q «-«-30
RR21 RR3i
RR(a)2 RR(a)3

RR(p)2 RR(P)3
Observed passive risk—the ratio of the exposed risk to the unexposed risk in each column.
                                           B-18
-------
Table B-ll.  Prevalences and estimates of lung cancer risk associated with active and passive
smoking
Case-
control
AKIB

BROW6



BUFF

CHAN

CORR

FONT10





GAO

GARF

GENG

HIRA16

HUMB
•
INOU

JANE

£ver-sm
-------
Table B-ll. (continued)
Case-
control
KABA22

KALA



KATA

KOO

LAMT

LAMW

LEE

LIU

PERS

SHIM

SOBU



SVEN

TRIG

WUWI

„ , Ever-smokers
Prev. Crude Prev. of
(%)r RR2 , exposed (%)3
42

17



28

32

24

22

6026

0.05

3711

2111

21



43

10

37

5.90
(4.53, 7.69)
3.32
(2.12, 5.22)


1.21
(0.50, 2.90)
2.77
(1.96, 3.90)
3.77
(2.96, 4.78)
4.12
(2.79, 6.08)
4.6126

*

4.211

2.811

2.81
(2.22, 3.57)


5.97
(4.11,8.67)
2.8 130
(1.69, 4.68)
2.24
(1.92, 2.62)
60

60



82

49

45

56

68

87

43

56

54



66

52

55

Never-smokers
Crude
RR2'4
0.79
(0.30, 2.04)
1.6223
(0.99, 2.65)
1.4123
(0.78,2.55)
*24

1.55
(0.98, 2.44)
1.65
(1.22, 2.22)
2.5125
(1.49,4.23)
1.03
(0.48, 2.20)
0.74
(0.37, 1.48)
1.28
(0.82, 1.98)
1.0828
(0.70, 1.68)
1.0623
(0.79, 1.44)
1.7723
(1.29, 2.43)
1.2629
(0.65, 2.48)
2.0830
(1.31, 3.29)
0.79
(0.64, 0.98)
Adj. ^
RR2>4>*
*

1.92
(1.02, 3.S9)7


*

1.64

*

*

0.75/1. 6027

0.77
(0.35, 1.68)
1.2
(0.7, 2.1)7
*

1.1323
(0.78, 1.63)7
1.5723
(1.07, 2.31)7
1.429

*

0.7

                                                          (continued on the following page)
                                          B-20
-------
 Table B-ll. (continued)

Case-
control
BUTL
(Coh)
GARF
(Coh)
HIRA
(Coh)
HOLE34
(Coh)
Ever-smokers
Prev; Crude
(%)* RR2
1411 4.011
2233 3.5833
16 3.2017
(1.96, 3.90)
56 4.211
-
Prev. of
exposed (%f
*
72
77
73
Never-smokers
Crude
RR2*4
2.4532
*
1.38
(1.03, 1.87)
2.27
(0.40, 12.7)

Adj. ^
RR2*4** ,
2.02
(0.48, 8.S6)7
1.1712
(0.85, 1.61)7
1.61
*
1.99
(0.24, 16.7)7
 Percentage ever-smokers in controls of whole study (or parent study).
 2Parentheses contain 90% confidence limits, unless noted otherwise. Crude ORs and their
  confidence limits were calculated by the reviewers wherever possible. Boldface type indicates
  values used for analysis in text of this report. OR for case-control studies; relative risk (RR) for
  cohort studies. The reference category for active smoking is all never-smoking; for passive
  smoking, it is unexposed never-smokers.
 3Percentage of never-smoking controls exposed to spousal smoking, unless noted otherwise.
  ORs for never-smokers applies to exposure from spousal smoking, unless indicated otherwise.
 Calculated by a statistical method that adjusts for other factors (see Table 5-5).
  Adenocarcinoma only.  Data and OR values communicated from author (Brownson).
 795% confidence interval (C.I.).
 8Exposure to regularly smoking household member. Differs slightly from published value of
  0.78, wherein 0.5 was added to all exposure cells.
 9Excludes bronchioalveolar carcinoma.  Crude OR with bronchioalveolar carcinoma included is
  reported to be 1.77, but raw data for calculation  of confidence interval are not provided.
10The first, second, and third entries are calculated for population controls, colon cancer controls,
  and both control groups combined, respectively.  For adenocarcinoma alone, the corresponding
  ORs, both crude and adjusted, are higher by 0.15 to 0.18.
HFrom other studies  similar in location and time period (see Table 5-7).
12Composite measure formed from categorical data at different exposure levels.
13For GAO, data are  given as (number of years lived with a smoker, adj. OR): (< 20, 1.0), (20-29
  1.1), (30-39,  1.3), (40+,  1.7).
14Estimate for  husband smoking 20 cigarettes per day.
15Crude OR reported in study is 3.05 (95% C.I. = 1.77, 5.30); adjusted OR is 2.6 (95% C.I. = 1.4,
 4.6).
16Case-control study nested in the cohort study of Hirayama. OR for ever-smokers is taken from
 cohort study.  This case-control study is not counted in any summary  results where HIRA(Coh)
 is included.
17Crude OR is  calculated from prospective data in Hirayama (1988).  Adjusted OR for ever-
 smokers given there is 2.67 (no confidence interval).

                                                            (continued on the following page)
                                           B-21
-------
Table B-ll.  (continued)

18OR reported in study is 2.25, in contrast to the value shown that was reconstructed from the
 confidence intervals reported in the study; no reply to inquiry addressed to author had been
 received by press time.
19For Inoue, data are given as (number of cig./day smoked by husband, adj. OR): (< 19, 1.58),
 (20+, 3.09).
20Taken from Rabat (1990) as closest in time and place.
21From subject responses/from proxy responses.
22For second  KABA study (see addendum in study description of KABA), preliminary
 unpublished data and analysis based on ETS exposure in adulthood indicate 68% of
 never-smokers are exposed and OR = 0.90 (90% C.I. = 0.51, 1.58), not dissimilar from the table
 entry shown.
^For the first value, "ETS exposed" means the spouse smokes; for the second value, "ETS
 exposed" means a member of the household other than the spouse smokes.
24Odds ratio is not defined because number of unexposed subjects is 0 for cases or controls.
'"Table entry is for exposure to smoking spouse, cohabitants, and/or coworkers; includes  lung
 cancers of all cell types. The OR for spousal smoking alone is for adenocarcinoma only:
 2.01 (90% C.I. = 1.20, 3.37).
26From Alderson et al.  (1985).
27From subject responses/from spouse responses.
28From crude data estimated to be the following: exposed cases 52, exposed controls 91,
 unexposed cases 38, unexposed controls 72.
29Exposure at home and/or at work.
30Known adenocarcinomas and alveolar carcinomas were excluded, but histological diagnosis was
 not available for many cases. Data are from  Trichopoulos et al. (1983).
31Raw data for WU is from Table  11 of the Surgeon General's report (U.S.  DHHS, 1986). Data
 apply to adenocarcinoma only.
32RR is based on person-years of exposure to spousal smoking. Prevalence in those units is 20%.
33Prevalence is calculated from figures in Hammond (1966) for the age distribution of the cases.
 RR is from U.S. Surgeon General (U.S. DHHS, 1982).
34RR values under never-smoker are for lung  cancer mortality.  For lung cancer incidence, crude
 RR is 1.51 (90% C.I. = 0.41, 5.48) and adjusted RR is 1.39 (95% C.I. = 0.29, 6.61).

 *Data not available.
                                           B-22
-------
Table B-12. Observed ratios of current smoker lung cancer risk to ever-smoker risk for females
Study
Alderson
et al. (1985)
Buffler .
et al. (1984)
Garf inkel and
Stellman
(1988)
Humble et al.
(1985)
Svensson
et al. (1989)
Wu et al.
(1985)
Overall
Exposed cases
plus controls
901
701
832
268
261
317
3,280
Lung
Current
smoker
4.5
7.9
12.7
18.0
8.46
6.5
8.05
cancer RR
Ever-
smoker
4.75
6.9
8.35
13.0
6.10
4.4
6.52
Ratio
Current smoker RR/
ever-sraolcer RR
0.95
1.15
1.52
1.38
1.39
1.48
1.241
lrThe summary ratio of 1.24 is the geometric mean of the individual ratios weighted by the
 exposed cases plus controls in that study.

       The elements RRoo and RR+ C00l)
                                                RR(p)0.
(B-3)

(B-4)
       Various assumptions regarding passive risks can be used for j = 1,2, and 3. We have
assumed, based on the data in Varela (1987), who found that 242 long-term former smokers had
essentially the same passive risk as 197 never-smokers, that the passive risk for former smokers is
the same as for never-smokers, namely, that RR(p)t = RR(p)0. Passive relative risks for female
smokers were taken from seven of the passive smoking studies (Akiba et al., 1986; Brownson et
                                           B-23
-------
al., 1987; Buffler et al., 1984; Humble et al., 1987; Koo et al., 1985; Wu et al., 1985; Hole et al.,
1989). The estimates range from 0.7 to 2.3 with no evident trend with either active smoking risk
or passive smoking risk.  The weighted log mean estimate is 1.25. Since the smokers not exposed
to passive smoke already are exposed to considerable ETS from their own smoking,  it is probable
that the additional ETS from others will have an additive effect rather than a multiplicative
effect. Therefore, we have assumed a difference of 0.25 between the active smoking risks of
passively exposed and nonexposed current smokers such that RR2i - RR2o = RR3i ~ RR30 - 0-25,
and RR2i/RR2o * RR(p)a and RR3i/RR3o = RR(P)S- The values for RR20 and RR30 are derived as
follows:
       RR20 = RR(a)2 - 0.25 c02i/c02., and RR21 = RR20 + 0.25
       RR30 » RR(a)3 - 0.25 C031/c03., and RR31 = RR30 + 0.25.
                                                                               (B-5)

                                                                               (B-6)
The relative risks for former smokers, RRjo and RRn> can t>e obtained by solving the equations
and
       RR(p)1 = RRn/RR10
RR(a)t « [(RRj0 c010)
                                   con)]/(c0,0 + con).
(B-7)

(B-8)
       Crude versions of the elements c^ (i = 1 for cases) are obtained by multiplying each
element c0jk by its respective RRj^. These are then normalized to give the case elements of Table
B-7 by
                            cijk:
                                   cdjkRRjk

                                   j=0 lc=0
                                                                                      (B-9)
       The next step is to set up Table B-8, which is the table of subjects by observed and true
smoking status. This is done by multiplying the observed misclassification rates (Pho/P.j) from
Tables B-3 and B-4 by the appropriate elements from Table B-7. For example, P10 = c0i.(P10/P.j).
An attempt was made to use the true misclassification rates from Tables B-3 and B-4 on the
theory that they would exhibit less variability in being transferred from the cotinine and
discordant answer studies to the passive smoking calculations.  However, the method is laborious
and, as is shown in the Correa example below, does not lead to increased accuracy.
                                           B-24
-------
       The next step is to develop a deletions table to implement Equation B-1 above using the
control and case smoking prevalences in Table B-7 and the distribution in Table B-8. Each
observed element, ci0k, in Table B-7 is multiplied by its appropriate observed misclassification
factor, Ph0 /P.j, where h = j, to yield a deletion element to be subtracted from the appropriate
observed wives' never-smoking-status elements:  CQQQ, CQQJ, c100, and c101, to obtain corrected
elements COOQ, COM, Cioo> an<* CIQI- Thus,
                                         3                 •     . •  -       -
= cooo ~  2J c()jo
            ^
                                                     etc-
(B-10)
Once these corrected never-smoker elements are obtained, the relative risk corrected for smoker
misclassification is obtained from Equation B-2; RR(c)0 = (Ci01 x COQQ)/(CIOQ x GO^), and the
bias becomes RR(p)0 /RR(c)0.

B.6. NUMERICAL EXAMPLE
       Using the Correa et al. (1983) study as an example, the study tells us that 52.8% of the
wives never smoked and that 45.9% of the never-smoking wives were exposed to their spouses'
smoke.  This establishes COQ. as 0.528 and CQQQ and CQQJ as 0.286 and 0.242, respectively. The
quantity s0., the proportion of ever-smokers, by difference is 0.472. From Correa's Table 2 we
find that the former smokers are 35.5% of the ever-smokers.  Thus, the former smokers, c0i.,
become 0.167, and the current smokers (c02. +  c03.) become 0.305.  The current smokers are
divided into current regular smokers at 90% (c03. = 0.275) and current occasional smokers at 10%
(c02. = 0.030). These data are shown in the bottom line of Table B-13.
       Using the concordance factor of 2.8 for ever-smokers versus never-smokers, it is possible
to show as described above that 33.2% of the females in the Correa study would be ever-smoker
wives with smoking husbands (s0i) and that 14.0% would be ever-smoker wives with never-
smoking husbands (SQQ). Similarly, using the concordance factor of 2.2 for former smoking wives
and ever-smoking husbands versus the never-smokers, the former smoking wives married to ever-
smoking husbands (con) would be 10.9% of the total and those married to the never-smoking
husbands (c0i0) would be 5.8%.  Then by difference, exposed current smoking wives (c021 + c031)
would be 22.3%, to be split into 20.1% regular smokers (c031) and 2.2% occasional smokers  (c021),
and the nonexposed current smoking wives (c020 + c030) would be 8.2%, split into 7.4% regular
smokers (c030) and 0.8% occasional smokers (c020). These data now supply all the elements needed
in Table B-13 and the control part of Table B-7.
       The estimate of relative  risk for passive smoking, RR(p)0, for females is 2.07 (Correa et
al.,  1983). The age- and sex-adjusted relative risk for current smoking from a related  paper
                                           B-25
-------
Table B-13.  Observed smoking prevalence among the controls—Correa example
Wife's smoking status
Husband's
smoking status
Never
Ever
All
Never
0.286
0.242
0.528
Former
0.058
0.109
0.167
Occasional
0.008
0.022
0.030
Regular
0.074
0.201
0.275
Alt
0.426
0.574
1.000
(Correa et al., 1984) is 12.6.  The ratio of female smoking crude risk to the average for males and
females is about 80%, indicating an age-adjusted current female risk of about 10. (Note:  This is
different from the current smoker relative risk that would be calculated from the crude ever-
smoker risk of 12.4 used in Table 5-7 [of this report] and  Table B-3. The adjusted risk is used
here simply as an example.)  With these inputs and the weights of controls in the study, the
various exposed and nonexposed relative risks are those shown in Table B-14.  The weighted
average risk for the occasional smokers is calculated as 0.16 (current regular risk — 1) + 1, which
for this example is 0.16 (10 — !) + != 2.44.  The weighted average risk for former smokers is 0.09
(current regular risk  — 1) + 1, which is 0.09 (10 — 1) + 1 = 1.81. The weighted average risks are
split between never-smoking and ever-smoking husbands by using the  passive risks, the
population weights, and Equations B-3, B-4, B-5, B-6, B-7, and B-8.  A crude case prevalence
table is then made up (Table B-15) by multiplying each c^ by its respective RRj^.  This table is
then normalized (Equation B-9) by dividing by 3.653 to yield Table B-16, which is the lower half
of Table B-7 for this example.
       The smoking  status distribution table (Table B-17) is developed, as described above, from
the misclassification factors in Tables B-3 and B-4 and the bottom line of Table B-13. For
example, to arrive at element (h = 3, j = 0), the observed P.3 of 0.275 is multiplied by an observed
misclassification factor of 0.0109 (from Table B-3) to yield 0.003.  To explore the value of using
the true misclassification factors instead of the observed ones, the true  and observed m's were
carried to five decimal places.  An approximation procedure to determine the true smoking
probabilities P0., PlM P2., and P3. was carried through four stages. The resulting total true
distribution of smoking status rounded to three decimal places was essentially identical to the
distribution shown in the bottom line of Table B-17. Similarly, any differences in the individual
elements were very small and beyond the accuracy of the  underlying data. The Correa study was
                                           B-26
-------
Table B-14* Observed relative risks—Correa example
Wife's smoking status
Husband's
smoking status
Never
Ever
Weighted average
Passive risk, RR(p),
Never
0.67
1.39
1.00
2.07
Former
1.07
2.21
1.81
2.07
Occasional
0-2)
2.26
2.51
2.44
1.11
Regular
9.82
10.07
10.00
1.025
Table B-15. Crude case table, prevalence of cases by smoking status—Correa example
Wife's smoking status
Husband's
smoking status
Never
Ever
All
Never
0.192
0.336
0.528
Former
0.062
0.240
0.302
Occasional
0.018
0.055
0.073
Regular
0.726
2.024
2.750
All
0.998
2.655
3.653
Table B-16. Normalized case table, prevalence of cases by smoking status—Correa example
Wife's smoking status
Husband's
smoking status
Never
Ever
All
Never
0.052
0.092
0.144
Former
0.017
0.066
0.083
Occasional
0.005
0.015
0.020
Regular
0.199
0.544
0.743
All
0.273
0.727
1.000
                                          B-27
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Table B-17.  Distribution of subjects by observed and true smoking status for wives in Correa
example1
- - - Wife's true ismoking status
Wife's observed
smoking status
Never (j = 0)
Ex (j - 1)
Occasional (j = 2)
Regular (j - 3)
All
Never
' (h*0)
0.499
0
0
0
0.499
Former
0.019
0.160
0
0
0.179
Occasional
0.007
0.004
0.030
0
0.041
Regular
-------
                     APPENDIX C






LUNG CANCER MORTALITY RATES ATTRIBUTABLE TO SPOUSAL




        ETS IN INDIVIDUAL EPIDEMIOLOGIC STUDIES
-------
-------
    APPENDIX C.  LUNG CANCER MORTALITY RATES ATTRIBUTABLE TO SPOUSAL
                     ETS IN INDIVIDUAL EPIDEMIOLOGIC STUDIES

       Many of the epidemiologic studies on lung cancer and environmental tobacco smoke (ETS)
were part of larger investigations that included ever-smokers and never-smokers. For those
studies, the lung cancer mortality rate (LCMR) for all causes,  appropriate to the location and time
period of the study, has been obtained from other sources. Those values and parameter estimates
from the studies are used to partition the excess LCMR from all causes (i.e., the excess after
allowance for baseline sources) into components attributable to ever-smokers (from current and
former smoking) and never-smokers (from exposure to spousal ETS) and to estimate the LCMR in
the subpopulations of interest—unexposed never-smokers (meaning not exposed to spousal
smoking), exposed never-smokers (exposed to spousal smoking), and ever-smokers ("exposed" is
not used to mean exposure to nonspousal ETS, which applies to the whole target population).  The
method is explained in Sections 6.3.1 and 6.3.2.
       Lung cancer mortality rates for the case-accrual periods of case-control studies are
displayed in Table C-l.  For the studies that collected data on both ever-smokers and never-
smokers, the parameter estimates used are shown in Table C-2. The value for the lung cancer
mortality rate is from Table C-l, and the remaining estimates  are from individual study data.  The
rate for the followup period of the study is estimated for HIRA(Coh) and GARF(Coh).  These
values  may not be very "representative" for lung cancer mortality in these two cohort studies
because they extended over several  years, and the LCMRs changed from year to year, particularly
in the United States.  This same difficulty arises in choosing a "representative" year for lung
cancer mortality in the case-control studies, although to a lesser degree. The most extreme
examples are KABA, PERS, INOU, and GARF, with case-accrual periods of 10 years or more.
       The estimates of prevalence of ever-smokers and the percentage of never-smokers exposed
to spousal smoking are the observed proportions in the control group. The extent to which the
control group is representative of the country's population differs between studies; the study
reviews in Appendix A provide more detailed information.  The restriction of cell types among
cases in some studies is another consideration. Active smoking is much more strongly associated
with occurrence of squamous and small cell carcinoma than with large cell carcinoma and
adenocarcinoma. FONT presents evidence that passive smoking is more associated with
adenocarcinoma than with other cell types.  As noted in Table  5-14, some studies excluded
candidate lung cancer cases of specific histopathological types.  This  may produce some bias and
distortion of comparison between studies.  For example, BROW includes only cases of
adenocarcinoma, which should  bias  the relative risk of ever-smokers toward unity, thus
                                          C-l
-------
Table C-l.  Female lung cancer mortality from all causes in case-control-studies1
Study
AKIB
BROW
BUFF
CHAN
CORK3
GAO4
GARF
GENG*
HIRA5
HUMB3
INOU
JANE3
KABA6
KALA6
KATA6
KOO
LAMT6
LAMW
LEE
PERS6
SHIM6
SOBU6
SVEN6
TRIG
WU
WUWI8
Location
Japan
USA
USA
HK
USA
China
USA
China
Japan
USA
Japan
USA
USA
Greece
Japan
HK
HK
HK
Eng/Wal
Sweden
Japan
Japan
Sweden
Greece
USA
China
Case
accrual
1971-80
1979-82
1976-80
1976-77
1979-82
1984-86
1971-81
1983
1965-81
1980-84
1973-83
1982-84
1961-80
1987-89
1984-87
1981-83
1983-86
1981-84
1979-82
1961-80
1982-85
1986-88
1983-85
1978-80
1981-82
1985-87
Begin
5.13
15.68
13^94
23.59
26.0
*
9.45
*
4.46
17.7
5.55
23.7
4.69
6.58
*
22.34
22.75
22.34
16.28
3.71
7.46
7.46
7.72
6.88
17.20
*
Average
6.05
17.29
15.29
23.59
26.0
18.0
13.55
27.8
5.70
17.7
6.53
23.7
13.20
6.586
7.466
22.61
23.46
22.88
17.11
5.09
7.466
7.466
7.726
6.40
18.15
11.6
End
7.08
19.09
17.20
23.59
26.0
*
17.20
*
7.08
*
7.46
*
17.20
6.58
*
22.75
23.69
23.69
17.89
7.56
7.46
7.46
7.72
5.99
19.09
*
Accrual-
lOyrs
average2
4.57
9.49
7.86
19.05
9.49
14.3s
6.87
13.83
4.01
10.55
4.93
9.06
6.61
6.75
4.66
19.82
21.33
20.09
12.60
3.956
5.65
6.36
5.78
5.75
10.14
9.22
Accrual-
20yrs
average2
2.30
4.75
4.38
*
4.75
5.13
*
*
*
5.13
2.95
5.42
4.16
5.836
2.26
*
*
*
8.1
*
4.28
4.93
3.80
5.317
4.96
*
1Rates are per 100,000 per year, standardized to the 1950 world population age distribution. Data
 are drawn from Kurihara et al. (1989), and annual rates for 2-year periods were averaged over
 the years cases were accrued for each study unless otherwise noted.  Where part (or all) of the
 accrual period fell 1 or 2 years outside the years for which rates were available, rates from the
 nearest 2-year period available were assumed to apply to the missing years. U.S. rates are for
 white females only.

                                                             (continued on the following page)
                                             C-2
-------
2The accrual-10 years average is the average for the time period of the same length as the accrual
 period but 10 years previous to it. Similarly, the accrual-20 years value is for the time period 20
 years previous to the accrual period.
3Data for accrual period from 1978-82 rates in IARC (1987b), standardized to  1950 world
 population from Kurihara et al. (1989).  For Correa, weighted average of white and black rates;
 for Humble, weighted average of Hispanic and non-Hispanic white rates.
4Accrual period data for GAO and GENG derived from IARC (1987b) by standardizing to same
 1950 world population used by Kurihara et al. (1989). GAO rates are for 1978-82; GENG, 1981-
 82. For the accrual-10 years value, GAO and GENG are 1973-75 rates standardized to the 1960
 world population from China Map Press (1979). The GAO accrual-20 years value is nonadjusted
 1961 rate from Kaplan and Tsuchitani (1978).
6The nested case-control study of Hirayama (mortality rates for this study also apply to the cohort
 study in which it is nested).
6Where rates for the period were not available in Kurihara et al. (1989), substitutions  were made as
 follows:  Kalandidi from 1984-85 rates; Rabat, 1982-83; Katada, 1982-83; Lam, T., 1984-85;
 Pershagen, 1952-53; Shimizu, 1982-83; Sobue, 1982-83; and Svensson, 1982-83.
7World-standardized rate for 1961-65 from Katsouyanni et al. (1990) (in Greek: translation
 provided by Trichopoulos).
8Accrual period value estimated by multiplying LCMR in Shanghai for period  1978-82
 (standardized to the  1950 world population) by the ratio of LCMRs in  Liaoning and Heilonjiang
 to Shanghai, for the  period 1973-75 (standardized to the 1960 world population). Data are from
 China Map Press (1979).  Value for accrual-10 years is the 1973-75 rate.

*Data not available.
                                           C-3
-------
Table C-2. Parameter values used to partition female lung cancer mortality into component
sources1
Case-control
AKIB
BROW
BUFF
CHAN
CORR
GAO
GARF(Coh)
GENG
HIRA
HIRA(Coh)
HUMB
INOU
KABA
KALA
KOO
LAMT
LAMW
LEE
SOBU
SVEN
TRIG
WU
WUWI
Lung cancer
mortality
6.05
17.29
15.29
23.59
26.00
18.00
7.002
27.80
5.70
5.702
17.70
6.53
13.20
6.58
22.61
23.46
22.88
17.11
7.46
7.72
6.40
18.15
11.60
'^'Ever-sm
Prevalence
21
29
59
26
47
18
33
41
16
16
41
16
42
17
32
24
22
60
21
43
11
58
37
DJK&IT& •*
Relative
2.38
4.30
7.06
3.48
12.40
2.54
3.58
2.77
3.20
3.20
16.30
1.66
5.90
3.32
2.77
3.77
4.12
4.61
2.81
5.97
2.ai
4.38
2.24

- ' Nevejr-Si
Percentage
exposed (%}
70
15
84
47
46
74
72
44
77
77
56
64
60
60
49
45
56
68
54
66
52
60
55
trtokers
Relative
risk
1.50
1.50
0.81
0.74
1.90
1.19
1.15
2.16
1.53
1.37
1.98
2.55
0.74
1.92
1.54
1.64
2.51
1.01
1.13
1.19
2.08
1.31
0.78
*For studies with data on both ever-smokers and never-smokers.  Table entries are
 Tables 5-8, B-ll, and C-l, which contain explanatory footnotes.
2Average of world-standardized rates for location during followup period of study
 et al. (1989).  White female rates used for GARF.
drawn from

from Kurihara
                                           C-4
-------
 attributing too little lung cancer mortality to active smoking and too much to passive smoking and
 background sources.
       Of a more positive nature, there is some advantage to using data from a single study to
 assign attributable fractions to different causes. To estimate the yearly number of lung cancers
 from each cause, the fraction is multiplied by the LCMR for the location and time of the study;
 that figure has to be obtained from sources on vital statistics. As seen in Table C-2, the mortality
 rates from lung cancer vary considerably between and within countries.  For example, the rates
 used for studies  in the United States range between 9 and 26. Applying the lung cancer rate
 suitable to each individual study should provide better estimates for comparison within  a country
 than using a single figure for the whole country for some specific year.
       Despite the reservations described, partitioning the lung cancer mortality for each study
 into components attributable to ever-smoking, spousal ETS, and baseline sources (nontobacco
 smoke and nonspousal ETS) provides a broad overview worth noting.  The calculated values are
 shown in Table C-3.  Estimates of relative risk for exposure to spousal ETS (RR2 in  notation of
 Section 6.3.2) less than 1.0 (see Table 5-9) were replaced by 1.0 to avoid a negative LCMR
 attributable to spousal ETS and the consequent inflation of the LCMR attributable to baseline
 sources and ever-smoking.  Aside from the studies for Hong Kong and China, estimates of lung
 cancer mortality due to background sources cluster  in the interval 1.5 to 5.5 (excluding BROW,
 which is strongly biased), predominantly from 3 to  5. The values for Hong Kong and China,
 however, are much higher, ranging from 7 to 14.5.  The presence of indoor sources of non-ETS
 encountered in some of the studies in China may be a factor, but there is no apparent explanation
 for the outcome  in Hong Kong. Assuming that the  background rate of lung cancer is much higher
 in Hong Kong (and possibly China) as it appears, then the question arises  as to whether  the high
 excess rate relative to  other countries may be attributable to higher exposure to ETS aside from
 spousal smoking  or whether it is more likely due to  other causes. Summary data from the
 10-country collaborative study of ETS exposure to nonsmoking women conducted by the
 International Agency for Research on Cancer (IARC) (Riboli et al., 1990) was kindly submitted to
 us for Hong Kong, Japan (Sendai), and the United States (Los Angeles, New Orleans) from  Drs.
 L.C. Koo, H. Shimizu, A. Wu-Williams, and T.H. Fontham, respectively.  The average
 cotinine/creatinine (ng/mg) levels for nonsmoking women who are not employed and not married
 to a smoker are close for Sendai, Los Angeles, and New Orleans, but they  are several times  higher
for Hong Kong.  Consequently, a high contribution  to background lung cancer mortality from
ETS aside from spousal smoking cannot be eliminated as a factor.
                                           C-3
-------
Table C-3. Female lung cancer mortality rates by attributable source1
s , ,"', „•-//! Baseline
- " sources*
Study
AKIB
BROW
BUFF
CHAN
CORR
GAO
GARF(Coh)
GENG
HIRA(Coh)
HUMS
INOU
KABA
KALA
KOO
LAMT
LAMW
LEE
SOBU
SVEN
TRIG
WU
WUWI
Location
Japan
USA
USA
HK
USA
China
USA
China
Japan
USA
Japan
USA
Greece
HK
HK
HK
Eng./Wales
Japan
Sweden
Greece
USA
China
No. ' '
3.47
8.22
3.34
14.34
2.89
12.36
3.41
10.67
3.28
1.57
2.97
4.32
3.04
11.41
10.94
7.35
5.37
5.05
2.19
3.42
5.17
7.95
% ^
57
48
22
61
11
69
49
38
58
9
45
33
46
50
47
32
31
68>
28
53
28
69
SpQusai smoking
t'//'l'i VOTln- r
" 'NO. %
0.96
0.44
0.00
0.00
0.63
1.42
0.25
3.21
0.78
0.51
2.47
0.00
1.39
2.05
2.39
4.85
0.01
0.28
0.16
1.71
0.40
0.00
16
3
0
0
2
8
4
12
14
3
38
0
21
9
10
21
0
4
2
27
2
0
Ever-smoking "
No. %
1.61
8.63
11.95
9.25
22.47
4.22
3.34
13.92
1.63
15.62
1.09
8.88
2.15
9.14
10.12
10.68
11.73
2.13
5.37
1.27
12.58
3.65
27
50
78
39
86
23
47
50
29
88
17
67
33
40
43
47
69
29
70
20
69
31
 *Rates are per 100,000 per year. Data not available for GARF, JANE, PERS, SHIM, BUTL(Coh),
 and HOLE(Coh).
 2Nonspousal ETS and non-ETS sources.
                                          C-6
-------
       The lung cancer attributable to ever-smoking, spousal smoking, and baseline sources
 depends on the population proportions for those categories as well as the relative risks.  Study
 estimates of the LCMR in each category, in units of lung cancer deaths per 100,000 at risk per
 year, are shown in Table C-4. The last two columns show the ratios of the LCMR and the excess
 LCMR for. exposed never-smokers to ever-smokers. As above, relative risk estimates of less than
 1.0 were set to  1.0 for the calculations. There is considerable variability across study estimates,
 even within the same country, as observed previously in the relative risks for spousal smoking.
       To  summarize,  for studies that included data on ever-smokers, the LCMR for all causes
 was partitioned by attributable source  (Table C-3). Although there is considerable uncertainty in
 the estimates from statistical variability and other sources, the outcomes provide some useful gross
 comparisons. For example, the lung cancer mortality rates from all causes differ markedly
 between countries and  also vary widely between studies within the United States.  The proportion:
 of lung cancers attributable to ever-smoking is very high in the United States, compared with
 some more traditional countries (e.g., Japan and Greece).
       Individual study estimates of the number of lung cancer deaths per year per 100,000 of the
 female population from exposure of never-smokers to spousal ETS are predominantly between 0
 and about 2.5. Estimates of the LCMR attributable to baseline sources (nonspousal ETS and
 nonsmoking causes) are somewhat higher, largely between 2 and 5, except in Hong Kong and
 China, where they range between 7+ and 14. (The U. S. study denoted as BROW has a high value,
 but that should  be upwardly biased because it used only cases of adenocarcinofna, which is not a
 common cell type in smokers.) For reasons discussed in Chapter 5, we would be reluctant to draw
 conclusions about China on the basis of the epidemiologic studies. The evidence from Hong
Kong, however, is very suggestive that the lung cancer rate in women due to baseline sources is
very high.  The extent to which that is attributable to nonsmoking sources of lung cancer and/or
high exposure to nonspousal ETS is not apparent.  The cotinine data for Hong Kong from the
 10-country IARC study (Riboli et al.,  1990) is consistent with excessively high ETS exposure;
therefore, nonspousal ETS may be a factor.
                                           C-7
-------
Table C-4. Lung cancer mortality rates of female ever-smokers (ES) and never-smokers (NS) by
exposure status1
Study
AKIB
BROW
BUFF
CHAN
CORR
GAO
GARF(Coh)
GENG
HIRA(Coh)
HUMB
INOU
KABA
KALA
KOO
LAMT
LAMW
LEE
SOBU
SVEN
TRIG
WU
WUWI
Location
Japan
USA
USA
HK
USA
China
USA
China
Japan
USA
Japan
USA
Greece
HK
HK
HK
Eng/Wal
Japan
Sweden
Greece
USA
China
(I)
Unexposed
3.47
8.21
3.34
14.34
2.89
12.35
3.41
10.66
3.28
1.57
2.96
4.32
3.04
11.41
10.94
7.35
5.36
5.05
2.18
3.41
5.16
7.95
~~ (2)
Exposed
NS*
5.21
12.32
3.34
14.34
5.49
14.70
3.92
23.03
4.49
3.11
7.56
3.78
5.84
17.57
17.94
18.45
5.42
5.70
2.60
7.10
6.77
7.95
ES
11.16
37.99
23.59
49.91
50.70
35.79
13.54
44.62
13.49
39.66
9.80
25.46
15.66
39.98
53.12
55.89
24.91
15.18
14.69
14.99
26.85
17.81
<2) As a
percentage
of (3)
47
32
14
29
11
41
29
52
33
8
77
17
37
44
34
33
22
38
18
47
25
45
(2) - 
-------
     APPENDIX D






STATISTICAL FORMULAE
-------
-------
a
c
b
d
                        APPENDIX D.  STATISTICAL FORMULAE

D.I. CELL FREQUENCIES
       The observed outcome of a case-control study or a cohort study may be depicted in a 2 x 2
table, where a, b, c, and d are cell frequencies.
                                                ETS Exposed
                                                 Yes    No
                              Lung Cancer   Yes
                                Present
                                            No

D.2. CASE-CONTROL STUDIES
       The true (but unknown) odds ratio is estimated by the observed odds ratio (OR),
                                       OR = ad/bc.
A confidence interval on the (true) odds ratio may be calculated from the normal approximation
to the distribution of log(OR), the natural logarithm of OR (Woolf, 1955).  The variance of
log(OR) is estimated by

                            Var(log(OR)) = I/a + 1/b + 1/c + 1/d

and the standard error by its square root,

                               SE(log(OR)) = (Var(log(OR)))*.

Approximate 90% confidence limits are given by

                               log(OR) ±  1.645 SE(log(OR)).

The value 1.645 is replaced by 1.96 for 95% confidence limits and, in general, by Za/2 for
100(1 - a)% confidence limits. The confidence bounds  obtained in this way are sometimes called
logit limits (Breslow and Day, 1980, p. 134).  Significance level (p-value) of a test for effect, i.e.,
H0: (true) odds ratio = 1 against the alternative Ha:  (true) odds ratio > 1, is the area under the
standard normal curve to the right of the value of the test statistic, given by
log(OR)/SE(log(RR)).
                                           D-l
-------
       If the (true) odds ratios are assumed to be equal in k studies, then a pooled estimate is
calculated from
                               log(OR(P))=
where the summations are on i, from 1 to k; OR(P) is the pooled estimate; log(OR)j is the
logarithm of OR from the i^ study; and w{ = (Var(log(OR)i))'1 is the weight of the i& study
(Breslow and Day, 1980).

D.3. COHORT STUDIES
       The true (but unknown) relative risk is estimated by the observed relative risk (RR),

                                    RR = (a/a+c)/(b/b+d).

A confidence interval on the (true) relative risk may be calculated from the normal approximation
to the distribution of log(RR), using the analogue of Woolf's method referred to above (Katz et
al.,  1978).  The variance of log(RR) is estimated by,

                           Var(log(RR)) = c/(a2 + ac) + d/(b2 + bd)

and the standard error by its square root,

                               SE(log(RR)) = (Var(log(RR)))i.

       The remaining calculations follow the description for case-control studies in Section D.2
with "odds ratio" and "OR" replaced by "relative risk" and "RR," respectively.  The pooled estimate
of relative risk from both case-control and cohort studies is calculated  by the same methodology
for pooling estimates from case-control studies or from cohort studies separately, i.e., the
logarithm of each individual estimate is weighted  inversely proportional to its estimated variance
(Kleinbaum et al., 1982).
                                            D-2
-------
                               SELECTED BIBLIOGRAPHY
       Note:  This section includes all references cited in the report as well as additional
references that were reviewed during the preparation of this report. This bibliography is not
intended to be a comprehensive list of all references available on the topic.

Adams, J.D.; O'Mara-Adams, K.J.; Hoffmann, D. (1987) Toxic and carcinogenic agents in
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       Carcinogenesis 8(5):729-731.                                                ,

Aguayo, S.M.; Kane, M.A.; King, T.E.; Schwarz, M.I.; Grauer L.; Miller, Y.E. (1989) Increased
       levels of bombesin-like peptides in the lower respiratory tract of asymptomatic cigarette
       smokers. J. Clin. Invest. 84:1105-1113.

Akiba, S.; Kato, H.; Blot, W.J. (1986) Passive smoking and lung cancer among Japanese women.
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Alderson, M.R.; Lee, P.N.; Wang, R. (1985) Risks of lung cancer, chronic bronchitis, ischaemic
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Alfeim, I.; Randahl, T. (1984) Contribution of wood combustion to indoor air pollution as
       measured by mutagenicity in Salmonella  and polycyclic aromatic hydrocarbon
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American Academy of Pediatrics, Committee on Environmental Hazards. (1986) Involuntary
       smoking—a hazard to children.  J. Pediatr. 77(5):755.

Ames, B.N. (1983) Dietary carcinogens  and anticarcinogens. Science 221:1256-1264.

Anderson, L.J.; Parker, R.A.; Strikas, R.A.; et al. (1988) Day-care center attendance and
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Andrae, S.; Axelson, O.; Bjorksten, B.; Fredriksson, M.; Ljellman, N-IM. (1988) Symptoms of
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Aoki, Y.; et al.  (1987) Smoking and health. Elsevier Science Publishers B.V. (Biomedical Division),
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Arundel, A.;  Sterling, T.; Weinkam, J. (1987) Never-smoker lung cancer risks from exposure to
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Badre, R.; Guillerm, R.; Abran, N.; Bourdin, M.; Dumas, C. (1978) Atmospheric pollution by
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Baker, R.R.;  Proctor, C.J. (1990) The origins and properties of environmental tobacco smoke.
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                                            R-l
-------
Basrur, P.K.; McClure, S.; Zilkey, B. (1978) A comparison of short-term bioassay results with
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Bellofiore, S.; Eidelman, D.H.; Macklem, P.T.; Martin, J.G. (1989) Effects of elastase-induced
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Benner, C.L.; Bayona, J.M.; Caka, P.M.; Tang, H.; Lewis, L.; Eatough, D.J. (1989) Chemical
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Bergman, A.B.; Wiesner, B.A. (1976) Relationship of passive cigarette smoking to sudden infant
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Berkey, C.S.; Ware, J.H.; Dockery, D.W.; Ferris, B.G., Jr.; Speizer, F.E. (1986) Indoor air pollution
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