Return
United States
Environmental Proiection
Environmenial Monitoring
Sysu*?!*s Laboratory
P.O. Box 93478
Las Vegas NV 89193-3478
EPA/600/4-91/006
February 1991
Prei&sue Copy
Research and Development
In Activities,
©cations, and
Microenvironments:
A California-
National Comparison
Project Report
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Time Spent In Activities, Locations, and
Microenvironments: A California-National
Comparison
Prepared by:
John P. Robinson
SURVEY RESEARCH CENTER
University of Maryland
College Park, Maryland 20742
Jacob Thomas
GENERAL SCIENCES CORPORATION
Laurel, Maryland 20707
Contract No. 68-01-7325, Delivery Order 12
Project Officer
Joseph V. Behar
Exposure Assessment Research Division
Environmental Monitoring Systems Laboratory
U. S. Environmental Protection Agency
Las Vegas, Nevada 89114
January 1991
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Notice
The information in this document has been funded wholly or in part by the United
States Environmental Protection Agency under contract 68-01-7325, Delivery order
12 to General Sciences Corporation. It has been subject to the Agency's peer and
administrative review, and it has been approved for publication as an EPA document.
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TABLE OF CONTENTS
Page
Abstract vi
1.0 Background 1-1
2.0 Report Objectives 2-1
3.0 General Methodological Considerations 3-1
4.0 Methodology of the 1985 American's use
of Time Project 4-1
5.0 Methodology of the California (CARB) Study 5-1
6.0 Results of Comparisons of Overall Averages 6-1
7.0 Synopsis of National-California Differences 7-1
8.0 Constructing a Code for Microenvironments 8-1
9.0 California-National Comparisons on
Microenvironments 9-1
10.0 Summary and Conclusions 10-1
List of References R-l
Appendices
A Activity Codes for 1985 National Study A-l
B Original Location Codes for 1985 National Study B-l
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LIST OF TABLES
Tables Page
3-1 Activity Codes for the CARB Study 3-5
3-2 CARB Study Location Codes 3-7
5-1 Summary Comparison of CARB and 1985 National
Studies 5-2
6-1 Difference in Average Time Spent in Different
Activities Between California and National Studies 6-2
6-2 Differences in Average Time Per Day Spent in
Activities Between California and National Studies by Gender . 6-5
6-3 Difference in Average Time Per Day in Different
Location, Total Sample and by Gender Between
California and National Samples 6-9
6-4 Revised Location Codes for Time Diaries (New
Codes Noted with Capitals and with Asterisk) 6-13
6-5 Location Recede Results 6-15
6-6 Revised Time Spent in Different Locations in National Study
Compared to California Study 6-17
6-7 Proportion of All Time Spent Outdoors at or Near
Home by Activity (1985 National Data) 6-19
8-1 Collapsed Activity Codes Used to Construct
Microenvironments Code 8-2
8-2 Collapsed Location Codes Used to Construct
Microenvironments Code 8-4
8-3 Derived Microenvironments for National and
CARB Data 8-5
IV
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LIST OF TABLES (cont'd)
8-4 Time Indoor, Outdoor and In-Vehicle California vs.
National 8-7
9-1 Time in Various Activities, Locations, and
Microenvironments California vs. National 9-2
9-2 Time Spent in Various Microenvironments By
Gender 9-3
9-3 Time Spent in Various Microenvironments By
Type of Day 9-7
9-4 Time Spent in Various Microenvironments By
Age Groups 9-9
LIST OF ILLUSTRATIONS
Figure Page
3-1 Sample Time Diary Page 3-3
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ABSTRACT
In this report, we review data on the methodological background and results from
the 1987-88 California Air Resources Board (CARB) time activity study and from
a similar 1985 national study of Americans' Use of Time conducted at the University
of Maryland, College Park. In order to facilitate comparisons, data from the
national study were receded to be as comparable as possible to the CARB code
categories. For the same reason, these initial comparative analyses were restricted
to the 18-64 age group "working population" in the two samples.
In general, the data on average distributions of time in activities matched up rather
well across the two samples. Californians tended to report more average time at
work and commuting to work in the diaries than was true nationally. They also
reported less average time doing housework and caring for children than was found
nationally. Time spent shopping in the CARB study was slightly higher. In general,
the above differences in family care activities were greater among women than
among men across the two samples. CARB respondents also reported more time
sleeping and eating meals away from home, less time eating meals at home, less
time grooming and less time on non-ascertained activities.
Californians also reported more time spent at fairs and other entertainment events,
and more time reading than was true in the national sample, and these differences
were also more pronounced among women in the two samples. California women
reported less time doing domestic craft activities and in conversation. At the same
time, Californians also reported more time traveling and these differences were
mainly found among men.
Despite these differences, the two data sets overall showed remarkably similar
patterns of activity. That was less true for the location codes, however. Several
sources of discrepancy were found in the comparison of these data, including time
spent in automobiles vs. other modes of transit. A receding of the location data
from the national study provided some resolution of the differences that were
found, but several differences remained—particularly the greater amounts of time
spent at home and in the yard in the national sample.
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The strong similarities of the average time for the activity data indicate that the
California data could be used to generate a better set of location codings for the
national data. This is particularly true for estimates of outdoor time spent doing
paid work, which was not differentiated in the 1985 national data. It also means
that the supplemental CARD data on specific exposure (e.g., passive cigarette
smoke, gasoline and service station visitations) may have national implications.
Nevertheless, a separate national study that could build and expand upon the
developmental work initiated in the CARD study and oriented to exposure
assessment is needed.
Microenvironments
A major reason for analyzing time-diary data is to estimate time spent in various
microenvironments. Microenvironments refer neither solely to activities nor solely
to locations but to the combination of activities and locations that yield potential
exposures. For this report, 16 separate microenvironments (combinations of
location and activity) were defined for the purpose of comparing the estimates from
the U.S. national and CARB studies. These were based on a collapsing of the
original 34 and 44 location codes to 10 and the activity codes from 90 + to 10. This
revised list of locations include residences (both indoor and outdoor), work
locations, restaurants and bars, travel modes, and places automobiles are parked
serviced and maintained. Similarly, activity distinctions include family care,
shopping, work/study, recreation and travel. Known sources of carbon monoxide,
benzene, and other VOC's also were reflected in our classifications.
Notable differences were found in the estimates from the national and California
data for the microenvironment codes created for this report. These resulted mainly
from differences in the location coding schemes used in the two studies. Many of
these gaps were closed by the receding of selected location codes in the national
study, but that exercise also produced some new divergences. Most notably, these
receded data suggest that Californians spend most of their outdoor time in
away-from-home settings in contrast to the greater time spent in yards and other
at-home outdoor environments in the national study. Although this would be
consistent with an image of more cramped outdoor living environments in
Vll
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California (or of more attractive outdoor environments away from home), this
result needs confirmation from independent data sources.
Many of the location coding differences, therefore, seem to account for the
differences in microenvironments. This includes the greater times reported in
California inside garages (autoplaces), restaurants/bars, and motor vehicles. It also
includes the longer time spent doing physical activities in outdoor locations and
travel by other transit modes mainly done outdoor in the form of walking or waiting
for buses. On the other hand, we find Californians reporting less time in such
microenvironments as work/school locations, kitchens, and family care settings for
house chores, child care and shopping activities.
Nonetheless, some of the differences in microenvironments that occur appear to
be related to location coding differences in the two studies rather than to actual
differences in activity patterns. Indeed, the relation of microenvironmental time
and gender, age, and type of day were remarkably similar in the two data sets,
indicating that they do tap the same basic elements of time expenditure.
vm
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1.0 BACKGROUND
The standard approach to monitoring environmental pollutants in the air has been
fixed-site monitoring, which consists of taking readings from air monitoring
equipment that measures concentrations of pollutants in outdoor air at specific
fixed locations in urban areas. This monitoring approach has certain fundamental
problems for exposure assessment, chief among them being that humans spend the
majority of their time indoors, a component of exposure that fixed-site monitoring
fails to take into account. To provide a completely realistic and comprehensive
assessment of population exposure, the pollutants generated by indoor sources
must be measured.
To determine this important component of human pollutant exposure, the U. S.
Environmental Protection Agency (EPA) conducted two field studies in the cities
of Denver, Colorado and Washington, D.C. in the winter of 1982-1983 to measure
the personal carbon monoxide (CO) exposure for a randomly-selected population
from both cities (Akland and Ott, 1984; Akland et al., 1985; Hartwell et al., 1984;
Johnson, 1984). This involved having the study participants carry miniaturized
Personal Exposure Monitors (PEMs) as they went about their normal daily
activities over a one- to two-day period of time. Additional field studies were
carried out in other cities to determine indoor human exposure to Volatile Organic
Compounds (VOCs). The studies indicated that a large percentage of exposure to
CO and VOC was generated by sources in a person's immediate surroundings
(referred to as "microenvironments"), such as the home, office, and car (Pellizzari
et al., 1987a; 1987b; Wallace, 1987).
Unfortunately, although the PEM studies provide a direct and more realistic means
of assessing the total human exposure, they do not permit predictions to be made.
Therefore, a complimentary method is required to calculate the total air pollution
exposure through computerized mathematical models (Behar, et al, 1989; Duan,
1982; Johnson, et al, 1984; Ott, 1984; Ott et al, 1988). The models, utilizing activity
pattern data and the concentration data in various microenvironments, predict
pollutant exposure based on the time spent in these microenvironments. The
estimates of the concentrations of pollutants in various microenvironments come
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either from knowledge of the source and emission rates of the pollutants or from
empirical measurements of concentration distributions.
The key factor in this complimentary, "indirect" approach is the activity patterns of
representative populations around the country which provide the basic input to the
simulation models. The activity pattern data used in the indirect approach come
from various time-diary studies (Johnson, 1986; Juster and Stafford, 1985;
Robinson and Wiley, 1990).
As the indirect approach grows in popularity and more simulation models are
developed, it becomes important to examine these time-diary studies, and the
activity data they provide, in more detail. This is necessary not only to quantify and
refine the procedures used to gather the activity data and to obtain more up-to-date
and precise activity data but also to objectively assess the value of the data provided.
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2.0 REPORT OBJECTIVES
This report presents a general comparison of the activity and location time
expenditures in a 1985 national time-diary study with parallel data on Californians'
activity patterns that were collected in a 1987-88 study conducted by the California
Air Resources Board (CARD). It provides an initial examination of the average
amounts of time spent in various activities and various locations in the two studies.
The primary goal of this report is to determine whether these two surveys, although
conducted from different perspectives and using different methods of gathering the
data (but with common activity codes), could identify convergent patterns of time
spent on various activities, in various locations and in various microenvironments.
This report is a preliminary effort to answer this important question. By nature, the
analyses that are carried out are limited and the report is mainly descriptive in
nature. Of major concern is the fact that the activity and location data in this report
are compared using only population averages. The majority of the comparisons
made involve times spent hi various activities and locations over all the days of the
week and across the entire population, which includes the many "zero" values for
people who did not participate in particular activities or who did not spend any time
in a particular location. This kind of direct comparison of gross population averages
is needed as a first step to determine whether or not further comparative work is
warranted.
In Section 9 of this report, the data are compared hi a manner that is more relevant
to exposure assessment: by examining the proportions of the population who do
and who do not report spending time in a given activity or a given location, and the
means of those groups within each of the data sets who do spend time in these
activities and locations. An attempt is made to identify those activities and locations
most relevant to pollutant exposure in these two data sets. The limitation of
examining only population averages is that similar population averages between the
California and national data sets could still reflect extremely different exposure
patterns between the two groups. For example, one group could have a higher
proportion of its members spending a little time in a given activity or location, while
the other population could have just a few members spending a great deal of time
2-1
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in that activity or location. This situation would yield similar population averages,
and yet the two groups' exposure patterns are clearly and meaningfully different.
This difference is critical in exposure assessment since the duration of exposure
directly determines dose and the accompanying adverse health effect. Therefore,
relevant frequency distributions should be compared using more sophisticated
statistics than is presented here. In addition, comparisons based on specific factors
known to affect exposure for the pollutants of immediate interest are needed.
An attempt is made in the concluding sections of this report to illustrate how time
spent in certain microenvironments can be estimated from these two data sets. The
16-category coding scheme we developed for microenvironments, however, is
mainly an attempt to obtain a standard set of microenvironments to compare these
two data sets from large representative sample bases.
In the CARB time-diary study, a probability cross-section sample of 1762 residents
aged 12 and over in telephone households across the state of California provided
detailed generalizable data on the following items:
• Time spent in 44 various locations, with special attention given to the
rooms of the home in which activities occur and to specific
microenvironments that are espe. Jly likely sites of pollution exposure
(e.g. garages, kitchens).
• Time spent in various activities, initially broken down into more than 90
discrete types of activities. These types have been identified and coded
in more detail in previous studies, as hi the 1985 national study in which
more than 250 codes were employed (see Appendix A).
• Time spent on an associated facet of these daily activities that has great
implications for air pollution exposure, namely the presence of smokers.
Since no data were collected on this latter aspect of activities in the 1985 national
study, only the first two aspects (location and activity) are examined in this report.
As in the national study, CARB interviews were distributed across all days of the
week and across different months of the year—although not across all months as in
the 1985 national study and with greater frequency on weekend days. In addition,
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demographic and other background data were collected for each respondent in the
survey. This included a series of questions related to work and household sources
of air pollution that were especially developed for the CARB study. More details
on the CARB study procedures are described in Section 5 of this report.
An important breakthrough in the CARB study was that these data were collected
and coded at the University of California at Berkeley using the computer-assisted
telephone interviewing system (CATI) developed at that institution's Survey
Research Center to process complicated data. The CAT! system greatly facilitated
the data collection efforts and assured greater standardization of activity reporting.
Using already-developed computer processing programs at the University of
Maryland, these complex variable-length records were simplified for analysis on
mainframe computers and on personal computers.
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3.0 GENERAL METHODOLOGICAL CONSIDERATIONS
Most surveys study people's activities in isolation from the natural temporal context
in which they are embedded. Thus, most survey activity questions ask people to
compress their actual behavioral experiences by telling interviewers whether they
"often" or "usually" do something, n-.ner than examining these activities as they
naturally and sequentially occur in daily life.
This is one of the main reasons why studies of the actual use of time represent such
an important and needed advance in understanding the nature of everyday activity.
Studies of time use provide the opportunity to study human activities in "real
time"—as individuals are actually involved in the stream of daily behavior.
The most general technique for the study of time use is the "time diary." Time
diaries can be seen as a prime example of the "micro-behavioral" approach to
survey research. This micro-behavioral approach recognizes the limited ability of
respondents to report very complex behavior in a survey context. Following this
approach, survey questions are limited to the most elementary experiences about
which respondents can accurately report. For example, a micro-behavioral
approach would ask about the details of a recent unhappy episode at work or in
marriage, rather than just a global question on job or marital dissatisfaction. It
would ask for accounts of activities that happened "yesterday" and not "in general"
or "typically," which are phrasings that can occasion different meanings and frames
of reference across respondents. It would combine direct questions concerning a
respondent's specific information about a topic with questions about that
respondent's specific mass media usage over a short time period—rather than
expecting respondents to give a meaningful response to a single question about
"main sources" of information about all the things happening in the world.
The micro-behavioral approach thus provides researchers with a more basic,
complex, comprehensive and flexible data base from which to draw conclusions
about virtually all human activity. The time diary is a micro-behavioral technique
for collecting self-reports of an individual's daily behavior in an open-ended fashion
on an activity-by-activity basis. Individual respondents keep or report on these
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activity accounts for a short, manageable period such as a day or a week—usually
across the full 24 hours of a single day.
In that way, the technique capitalizes on the most attractive measurement
properties of the tune variable; i.e.:
• All daily activity is potentially recorded (including that which occurs in
early morning hours when most people may be asleep).
• All 1440 minutes of the day are equally distributed across respondents
(thus allowing certain "tradeoffs" between activities to be examined).
• Respondents are allowed to use a time frame and accounting variable
that is maximally understandable to them and accessible to memory.
The open-ended nature of activity reporting means these activity accounts are
automatically geared to detecting new and unanticipated activities, (e.g., aerobic
exercises, use of new household products involving chemicals), as well as capturing
the context and sequences of how daily life is experienced.
In a typical diary instrument, respondents report on each activity in which they
engage across the full 24 hours of the day, as well as where they were and various
aspects of each activity. Figure 3-1 shows a sample time-diary page from the
self-completion form used in the 1985 mail-back study and illustrates the basic
structure of the diary instrument. As adapted for the CARD telephone study, this
structure was stored in the computer without the "with whom" or "secondary
activity" information; this information was replaced with information on the
presence of smokers. Respondents filled out one such entry line for each activity
in which they engaged over the 24-hour period.
Prior to the 1987-88 California study, four national time-diary studies had been
conducted using this general approach. The four studies and the organizations
involved are as follows:
• Mutual Broadcasting Corporation (1954) study, in which more than 8000
American adults 15-59 kept time diaries for a two day period (more exact
details are given in De Grazia, 1962).
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WHAT YOU DID FROM MIDNIGHT UNTIL 9 IN THE MORNING
Time
Mid
1
2i
3;
41
5;
6>
7>
8A
night
MA
«iM
\M
*M
\M
VM
VM
M
What did you do?
Tim*
Began
Tim*
Endod
Where
Ust Other
Persons
With You
Doing
Anything
Else?
Figure 3-1. Sample Time Diary Page
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• Survey Research Center, University of Michigan (1965) study, in which
1244 adult respondents aged 18-64 kept a single- day diary of activities,
mainly in the Fall of that year. Respondents living in rural and
non-employed household were excluded (Robinson, 1977).
• Survey Research Center, University of Michigan (1975) study, in which
1519 adult respondents aged 18 and over reported their activities for a
single day in the Fall of that year (Robinson, 1976). In addition, diary
accounts were obtained from 788 spouses of these designated
respondents. These respondents became part of a panel who were
subsequently reinterviewed in the Winter, Spring and Summer months
of 1976; about 1500 respondents remained in this four wave panel. Some
677 of these respondents were reinterviewed in 1981, again across all four
seasons of the year (Juster and Stafford, 1985).
• Survey Research Center, University of Maryland (1985) study, in which
single day diaries were collected from more than 5000 respondents aged
12 and over across the entire calendar year of 1985. Three modes of diary
collection were used for comparison: mailback, telephone, and personal,
with little difference in obtained estimates (Robinson, 1988).
Comparison across certain of these studies—mainly to detect trends in time usage,
particularly in relation to this latest (1985) national survey—is the topic of another
report of this series.
These open-ended diary entries were coded and arranged in a variety of ways. The
most widely-used activity coding scheme was the one developed for the 1965
Multinational Time Budget Research Project (as described in Szalai et. al, 1972).
As shown in outline form in Table 3-1 (as adapted for the CARB study), the Szalai
et. al. code first divides activities into non-free activities and free- time activities.
Non-free time activities are further subdivided into paid work, family care and
personal care, with free time activities being further subdivided under the five
general headings of adult education, organizational activity, social life, recreation
and communication.
Activities are coded to identify the actual activity and not its purpose or benefits.
Thus, very enjoyable aspects of work are still coded as work, and visiting or TV
viewing done as work or school obligation is still coded as a free-time activity. An
actor in a play is working, while an audience member watching his performance is
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Table 3-1. Activity Codes for the CARB Study
00-40
00- 00
00
O1
02
03
04
OS
08
O7
06
00
10-18
10
11
12
13
14
15
16
17
18
IB
20-29
20
21
22
23
24
25
28
27
28
28
30-38
30
31
32
33
34
35
38
37
38
38
40-48
40
41
42
43
44
45
46
47
4«
48
NON-FREE TIME
PAID WORK
(notUMd)
Maln|ob
Unemployment
Travel during work
(not used)
Second fob
Eating
Before/after work
Breaks
Travel to/from work
HOUSEHOLD WORK
Food preparation
Meal cleanup
Cleaning house
Outdoor cleaning
Clother* care
Car repair/maintenance (by R)
Other repair* (by R)
Plant car*
Animal car*
Other houMhokJ
CHILD CARE
Baby car
ChHdcare
HwpfnQ/tetKninQ
Talking/reeding
Indoor playing
Outdoor playing
Medical care-child
Other child cam
(At dry cleaner*)
Travel, child cam
OBTAINING GOODS, SERVICES
Everyday •hopping
Durable/house (hop
Personal ssrvfce*
Medical appointment*
Oovi/nnancial esrvke*
Car repair service*
Other repair eenlcm
Other services
Errands
Travel, good* and sendee*
PERSONAL NEEDS AND CARE
Washing, etc.
Medical car*
Help and care
Meals at home
Meals out
Night sleep
Naps/day sleep
Dressing, etc.
NA. activities
Travel, personal care
50-88 FREE TIME
00-88
SO
51
52
53
54
55
56
57
58
58
00-68
60
61
62
63
64
66
66
67
66
68
70-78
70
71
72
73
74
75
76
77
76
78
60-68
80
81
82
83
84
85
66
87
88
88
80-88
80
81
82
83
04
85
08
87
OB
80
EDUCATIONAL
Students' clasees
Other classes
(not used)
(not used)
Homework
Library
Other education
(notussd)
(not used)
Travel, education
ORGANIZATIONAL
Professional/union
Special Interest
PomicaVcMc
Volunteer/helping
Religious group*
Religious practice
Fraternal
Chltd/youth/family
Other organizations
Travel, organizational
ENTERTAINMENT/SOCIAL
Sports events
Entertainment
Movie*
Theatre
Museum*
Visiting
Parties
Bars/lounge*
Other social
Travel, social
RECREATION
Active sports
Outdoor
Walking/hiking
Hobbies
Domestic craft*
Art
Music/drama/dance
Same*
Computer use
Travel, recreation
COMMUNICATIONS
Radio
TV
Records/tape*
Read books
Magazines/etc.
Reading newspaper
Conversations
Writing
Think, relax
Travel, communication
3-5
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engaged in a free time activity. More fine- grained distinctions within these
categories were captured in the more than 250 categories developed in the 1985
national study (as shown in Appendix A) that reveal further distinctions under these
broader headings. Appendix A also shows certain important differences in the
California and national activity codes. The main value of this open-ended diary
approach, then, is that these various activities can be receded or recombined
depending on the analyst's unique assumptions or purposes.
The Table 3-1 (and Appendix A) code has several attractive features: (1) it has been
tested and found reliable in several countries around the world; (2) extensive prior
national normative data are available for comparison purposes; and (3) it can be
easily adapted to include new code categories of interest to environmental
researchers.
Nonetheless, the Table 3-1 division of activities is focused more on economic or
social distinctions than on environmental features, such as proximity to pollutant
sources or personal inhalation rates. One does not know from the present data
whether meal preparation involves cooking with gas stoves or simply consists of
making a sandwich or pouring a glass of milk. This leads to some serious difficulties
in relating activities to microenvironments or situations of crucial interest to
exposure research. These could be flagged in future studies by the use of a third or
fourth digit in the activity or location code.
Locations as described in the "where" category of the diary can now be coded into
one of the 44 basic location categories developed for the CARB study, as shown in
Table 3-2. The coding can easily be aggregated to estimate aggregate time spent in
travel or time spent outdoors, both important parameters for exposure estimation
purposes.
These new CARB codes were developed to distinguish the type of room in the home
(kitchen, TV room, bedroom, etc.) and to distinguish between various types of other
indoor and outdoor locations — especially for locations known to be likely areas of
high pollution (such as parking garages or automobile repair shops). The codes were
developed with the help of the California Air Resources Board staff, and perhaps
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Table 3-2. CARS Study Location Codes
A. Whara In your houaa wara you?
1 Wlehan
2 LMng mi, family room, dan
3 Dining room
4 Bathroom
5 BtorooRt
6 ttuoyoffica
7 Gang*
5 Baaamant
8 Utmty/Uundty room
10 Pool, Spa (outslda)
11 Yard,Ps»io,otnaroulsidahousa
12 Moving from room to room In tha houaa
13 dm* (SPECIFY)
B. Wtwranwnyou?(Knothome)?
21 Cfllea buNding, bank, poM offica
22 InduMrM p>*r*, factory
23 Qrooxy Hora (corwvniwie* tlora to tupwmanut)
24 Shopping mall or (non-groc*ry) ttor*
as School
M PutaKc bids, (library, muMum, thMt*0
27 Hoapiul. hMXh cant facility, or Df.'t offie*
2* RMtaurant
29 Bar, nightclub
30 Church
31 Indoor gym, (pom or haarlh dub
32 Olnar paopto'i horn*
33 Auto npair shop, Indoor parking gang*, gasatallon
34 Park, playground, (ports Hadlum (outdoor)
36 HoM,moM
38 Orydaanan
37 B**uty parior, taarbar shop; hairdranan
3* Wonc no tpaclfic main location; moving among location*
30 Othw indoor. (SPECIFY)
40 other outdoors (SPECIFY)
C. How wara you traveling? Wara you in » car, wmlMng, in a truck, or umathing alia?
51
82
S3
54
as
Car
Pick-up truck or wi
Wafting
BuMraM/rlda Hop
Bus
96
57
58
SB
80
61
Train/rapid transit
Othar truck
Airplana
Btcyd*
Motoreycla, Kootar
Othar (SPECIFY)
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should be seen as the major focus of the time diary, unlike earlier time-diary studies
which have focused mainly on activities.
The full location codings for the 1985 national study are shown in Appendix B. A
more restricted set of codes was used for the telephone part of the national study,
because of its greater demand on interviewer; these interviewers were not able to
work with a full CATI diary instrument, such as that developed for the CARB study.
When aggregated, such open-ended diary data have been shown to provide
generalizable national estimates of the full range of alternative daily activities in a
society: from "contracted" time (e.g., work or the commute to work), to
"committed" time (e.g., family care), to personal care (e.g., sleeping, eating,
hygiene), and to all the types of activities that occur in free time. The multiple uses
and perspectives afforded by time-diary data have led to a recent proliferation of
research and literature in this field. Comparable national time-diary data have
been collected in over 25 countries over the last two decades, including most all
Eastern and Western European countries, usually by the main governmental
statistical agency in each country.
Reliability: Time-diary estimates thus far have been able to produce rather reliable
and replicable results at the aggregate level. For example, Robinson (1977) found
a .95 correlation between time use patterns found in the 1965-66 national time
diaries (n = 1244) and the aggregate figures for the single site of Jackson, Michigan
(n = 788). Similar high correspondence was found for the American data and for
time-diary data from Canada, both in 1971 and in 1982 (Harvey and Elliot, 1983).
A correlation of .85 was found between time expenditure patterns (found in the
U.S. and Jackson portions of the 1965-66 time study) using the "day after" approach
and time expenditure for a random tenth of the samples who also filled out a "day
3-8
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before" diary1. In a smaller replication study in Jackson in 1973, an aggregate
correlation of .88 was obtained.
Validity: Almost all diary studies depend on the self- report method rather than on
some form of observation. This is unfortunate because it leaves these self-report
data open to basic questions of validity, in the sense of being verifiable by some
independent method of observation or report. However, there are encouraging
signs from those observational studies that have been done.
Several studies bear more directly on the validity of the time diary, in the sense of
there being an independent source or quasi-observer of reported behavior. The
first of these studies did not involve the time diary directly, but rather the conclusion
from the time diaries that standard television rating service figures on TV time
expenditure provided high estimates of viewing behavior. In this small scale study
(Bechtel, Achepohl and Akers, 1972), the TV viewing behavior of a sample of 20
households was monitored over a week's time by means of a video camera; the
camera was mounted on top of that set, and the video camera/microphone recorded
all behavior in front of the TV screen. Household members also kept rating service
"viewing diaries," in which they recorded the names and times of all TV programs
they had watched.
The results of this study, as in the earlier camera monitoring of TV audiences by
Allen (1968), indicated that both rating-service methods of TV exposure (the
audiometers and the viewing diaries) produced estimates of viewing that were 20
to 50 percent higher than primary or secondary activities reported in time diaries.
In brief, the study provided considerable support for an explana tion of the lower
viewing times reported in time diaries than by commercial rating services. It also
illustrated the need for a complete open-end diary rather than one focused on a
specific set of activities (like television or child care).
1 These results provided the rationale for using the much less expensive day "yesterday" diary approach in the 1975
study rather than the more expensive tomorrow diary approach in which the respondent fills out the diary for the
following day and which requires a separate second visit to the respondent's home. The tomorrow approach did pick
up less detailed activities, but only about 10% less detail. At the same time, telephone diaries include much less
missing data, since interviewers have more control over the activity reporting process.
3-9
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Three more general validity studies subsequent to Bechtel et. al. provided further
evidence bearing on the validity of tune-diary data. These examined the full range
of activities (and not just television viewing) and employed larger and more
representative samples. However, none involved the independent observations of
behavior as had the Bechtel et. al. study.
In the first study (Robinson, 1985), a 1973 random sample of 60 residents of Ann
Arbor and Jackson, Michigan kept beepers for a one-day period and reported their
activity whenever the beeper was activated (some 30 to 40 times across the day).
Averaged across all 60 respondents, the correlation of activity durations from the
beeper and from the diaries was .81 for the Ann Arbor sample and .68 for the
Jackson sample (across the non-sleep periods of the day).
In a second study, a telephone sample of 249 respondents were interviewed as part
of a 1973 national panel survey. These respondents were asked to report their
activities for a particular "random hour" during which they were awake that
day—with no hint from the interviewer about what they had previously reported
for that hour in their diary. An overall correlation of .81 was found between the
two aggregate sets of data, that is between the activities reported in the random
hours and in the full-time diary entries for those same random hours (Robinson
1985).
In a more recent study, Juster (1985) compared the "with whom" reports in the
1975-76 diaries of respondents with those of their spouses across the same day.
Juster found that in over 80% of the diary entries, these independently-obtained
husband and wife diaries agreed that their spouses were present or absent. In a
separate analysis of these 1975 data, Hill (1985) found a .93 correlation between
time spent on various home energy-related activities and aggregate time-of-day
patterns of energy use derived from utility meters.
In conjunction with the reliability studies, then, the data from these studies provide
a considerable degree of assurance about the basic generalizability of time diary
data. This has been the case as well in methodological studies conducted in other
countries (e.g., Gershuny et. al., 1985; Michelson, 1978). Nonetheless, a definitive
3-10
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well- controlled study has yet to be conducted. It is especially needed for the
specific types of locations and activities of interest to exposure assessment
researchers.
3-11
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4.0 METHODOLOGY OF THE 1985 AMERICANS' USE OF TIME PROJECT
The 1985 Americans' Use of Time study employed the same basic open-ended diary
approach as the 1965 and 1975 national studies. In the 1985 study, however, an
explicit attempt was made to spread the collection of diary days across the entire
calendar year—from January through December of 1985 for the two main data
collection methods: mailback and telephone. A representative national sample of
personal interviews also was conducted beginning in September of 1985 and
continuing though May of 1986.
The methods for the three different samples were as follows:
1) Mail-back Sample: The data for the main (mail-back) study were collected from
a sample of Americans who were first contacted by telephone, using the
random-digit-dial (RDD) method of selecting telephone numbers. All calls were
made from the central telephone facility at the Survey Research Center of the
University of Maryland, College Park.
Once a working telephone household was contacted, one respondent aged 18 and
older in each household was selected at random. That person was given a brief (2-5
minute) orientation interview, followed by an invitation to participate in the
diary/mail-out part of the study. If that respondent agreed, diaries were then mailed
out for each member of the participating household aged 12 and above to complete
for a particular day for the subsequent week.
Brief Call-2 and Call-3 interviews were made 4-6 days later to ensure that
respondents had received these materials and understood how to complete them.
After respondents completed these diaries, they then mailed all their completed
forms back to the University of Maryland for coding and analysis. Some 3349 diaries
were returned using this mail-out procedure during the full 12 months of 1985.
However, it is the diaries obtained from adults aged 18 to 64 with less than two
hours of missing diary data (1980 in number) that form the data base for the analyses
described in the first part of this report. Other 1985 data not examined in this report
included parallel diary reports from 809 additional respondents interviewed in a
separate personal interview sample in the Fall of 1985 through the Spring of 1986,
4-1
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and from an additional 1210 "yesterday" diaries obtained by telephone as part of
the initial contact for the mail-back diaries.
Collection of the mail-back data, then, was obtained using basically the same
"tomorrow" approach as employed in the 1965-66 study. In this "tomorrow"
approach, respondents know and agree ahead of time that they will be keeping the
diary, rather than the "yesterday" approach used in the telephone portion of the
study. The main procedural difference was that a personal interviewer was not
present to check on the adequacy of diary entries. This check was instead performed
when the diaries were received at the University of Maryland for coding and
analysis. If any discrepancies were detected (e.g. significant gaps of missing times
or indecipherable diary entries), the respondent involved was recontacted by
telephone to clarify any ambiguities.
Households were given special monetary incentives and gifts (a pen with a digital
watch) to ensure that all family members in the selected households over the age
of 11 participated in keep ing a diary. This also ensured that the sample would be
approximately self-weighting (for individuals over the age 11), as well as covering
approximately an entire year's activities.
In addition to the estimates of daily time use from the diary, the study also obtained
information on the employment status, age, education, race and sex on each
member of the household. Additional questions ascertained the presence of
certain home appliance technology available in the household as well as certain
physical characteristics of the dwelling unit.
The sample was designed to represent all telephone households in the contiguous
United States. The sample first covered 173 area codes/three-digit prefixes
selected at random from a master random-digit-dial sampling frame of 500 base
numbers prepared by the Sampling Department of the Institute for Social Research
at the University of Michigan to represent all telephone households in the United
States. If that base number located a working household telephone number, it was
then used to generate additional clusters of random numbers within that area code
and prefix. The initial list of 500 numbers had been stratified by geographical region
4-2
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of the country. This ensured that the sample telephone numbers had an adequate
representation from all regions of the country. The sample was designed to yield
about 1800 households (and 4000 individuals) across the calendar year.
2) Telephone Sample: Additional diary data were obtained from a national
telephone sample that consisted of a random sample of the U.S. population who
were contacted in the first phase of the mail-back procedure. This telephone
sample consisted of the randomly-selected adult (aged 18 and older) who
responded to the first interview. In the telephone interviews conducted in the first
six months of 1985 (January through June), each third respondent in this initial
telephone contact was also asked to complete a diary for the prior day's activities.
In the second six-month period of the study, all telephone respondents completed
the prior day's diary.
A problem arose for those respondents who agreed to complete the diary forms but
subsequently did not return the forms to the Center. When contacted, most of these
respondents claimed to have returned the forms—even though none ever arrived
at the Center. That meant that several important demographic variables (e.g.
family size and composition, age) were missing for this portion of the telephone
sample. It is for that reason that the telephone sample is excluded from this analysis.
Some 67% of respondents initially contacted by telephone, however, did complete
a day-before diary over the telephone. This was the highest response rates for any
of the three data collection modes. The response rate for the mail-back was less
than 50% (about 3/4 of those contacted by telephone) and for the personal mode
just about 60 %.
3) Personal Sample: In addition to the mail-back and telephone diaries, a separate
national sample of 809 diaries were collected by personal in-home interviews. This
sample was drawn from a subset of 20 primary sampling units (PSUs) of counties
or metropolitan areas, which were selected using a random probability methods
from the continuing national samples of the Institute for Survey Research at Temple
University in Philadelphia. This stratified sample was further stratified and
subjected to a "controlled selection" to ensure that the subset of 20 PSUs retained
4-3
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sufficient representation of rural-urban-suburban character within each of the four
regions of the country. (The urban-rural factor could not be controlled through
stratification either in the telephone portion of the sample or in the mail-back
portion of the sample. Nonetheless, the final representation of rural and urban
areas does not appear to be problematic in these three national surveys.)
Respondents in this sample were asked to follow much the same procedures as on
the initial telephone sample. One adult selected at random was to complete a
retrospective diary from memory for the previous day. The interviewer then left
diaries for all adult respondents in the household to complete for the following day.
The interviewer returned the day following that day to collect the diaries and to
ensure that they were filled out adequately and accurately. For example, if the
interviewer contacted the household on a Tuesday, the random adult respondent
first filled out a retrospective diary for Monday; the interviewer then left diary forms
for that respondent and other household adults to fill out for Wednesday, and the
interviewer returned to collect those completed forms and ask additional questions
about the household on Thursday. As in the mail-back diary procedure,
respondents were given monetary and other incentives for participating.
Diary Coding: In the first page of the 1985 time-diary form presented in Figure 3-1,
it can be seen that each respondent is expected to write out each primary activity
in which they engaged, the time that the activity began and ended, where it took
place, who was present during the activity and what other activities were performed
during this same time period as well. In this way, the diary form remained basically
the same as that used in the 1965 and 1975 studies.
In order to illustrate the types of activities and level of detail that was expected of
the respondents in their completed diaries, an example of a completed diary form
was enclosed in each packet mailed to the household (or left behind in the personal
mode). This example form was filled out in considerable detail, with several
hand-written comments by the presumed "diary keeper" to help the interpretation
of unusual diary entries (e.g. going home during work; caring for children while
playing sports). In general, this was intended to ensure that respondents would
include enough detail in their diaries; that measure seems successful in that
4-4
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mail-back diaries contained about the same number of primary activities (about 26
per day) as found in the 1965 "tomorrow" diaries.
Once received and checked, these diaries were then entered into a PDF 1144
computer by trained coding staff using the direct data entry features of the
University of California at Berkeley CATI system. Activities were coded into one
of more than 250 activity codes, shown in Appendix A, which were elaborated from
the 174 categories developed at the University of Michigan for the 1975 data; this
in turn represented an elaboration of the 96 basic code categories that Szalai et. al.
(1972) had developed for their 1965 Multinational Time-Use Project.
The Table 3-1 scheme described above shows the adapted activity coding scheme
that was developed from that multinational project and that applies to the activity
data tables in this report. Nonetheless, this is not the only activity category scheme
that has been developed, and the value of the open-end diary approach (as well as
the Table 3-1 scheme) is that activities can be receded or recombined depending
on the researchers' unique assumptions or purposes.
The Table 3-1 activity code for the CARD study mainly differs from the one used
in the 1985 national study in the following respects:
• Code 03 (travel during work> was coded as part of regular work (code
00) in the 1985 study.
• Code 28 was used to isolate activities at a dry cleaning establishment in
the CARD study; this was included along with other personal service
(code 32) in the national study.
• Code 47 in the CARD study included all grooming activities in the
bathroom, not just bathing and washing as in the national study; dressing
activities were included as code 40 in the national study.
• Code 49 in the CARB data included all travel that could not be linked to
a particular other activity or purpose.
Otherwise, the coding categories were virtually identical in the two studies, with the
coding changes and rearrangements designated in Appendix A being used to make
the activity coding as comparable as possible.
4-5
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The location codes in the two studies were, in contrast, rather different. Indeed,
the CARB location codes in Table 3-2 represented a major advance in the coding
of location in time-diary studies. In contrast, the location codes for the 1985 study
are much more ambiguous and less complete—and also varied across the three
study modes in the 1985 study. Ideally, these data can be receded and standardized
in future efforts using the CARB categories.
The University of Maryland coders were extensively trained on the activity code
category system and used the same complete document of coding conventions that
had been developed by the Survey Research Center at the University of Michigan
for its 1975 time diary project. Each activity in the diary was coded descriptively as
a separate block of 21 digits in length. This block comprised the primary activity (a
3-digit code) during the period, the time the activity began and ended coded in
4-digit military time, (e.g. SAM = 0800; 8PM = 2000), location (1 digit), social
partners (2 digits), secondary activity (3 digits), enjoyment level (1 digit) and medu!
use (3 digits). When this 21-digit data entry for all activities in the diary was entered
and computed, the totals were programmed into the machine to ensure that each
day's diary entries added to exactly 1440 minutes (24.0 hours). These
"variable-field" data (i.e. varying depending on the number of activities reported)
were then processed by a special computer program to provide "fixed- field"
compilations of diary time spent on 96 activities for each day, i.e. total daily minutes
spent working, cooking, watching TV, etc. for that respondent for that day.
It is the averages of these fixed-field totals that are presented in the analytic tables
that follow. The daily minute data in these tables have been weighted by day of the
week and by certain demographic factors (sex, household size and region) to ensure
that all days of the week are equally represented in these tables and that the overall
sample figures reflect appropriate 1985 and 1987-88 U.S. Census Bureau figures
for these demographic variables. In other words, if the proportion of the sample
on some characteristic was too high in relation to population figures (as in the case
of females), then that group was multiplied by some number less than 1.0 to make
the proportion match the true population proportion.
4-6
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5.0 METHODOLOGY OF THE CALIFORNIA (CARB) STUDY
All data in the CARB study were collected by telephone. One adult 18 or older in
each contacted household was selected at random and asked to complete a diary
for the previous day's activities. In order to reflect appropriate geographic divisions
in this statewide sample, households in the San Francisco Bay area had twice the
chance of falling into the sample as households in the greater Los Angeles and San
Diego areas and households in the remaining areas of the state were sampled at
four times this rate. The weightings needed to offset these sampling fractions are
applied in the tables that follow; no such geographic sampling differences were used
in the national sample, so that it is self-weighted by region.
Each respondent in the CARB study was asked to describe each activity on the
previous day and the location of that activity. Locations were preceded into the
categories using the CAT! software available on the Berkeley system, so that this
was directly coded into the computer. Activities were coded using the same basic
codes (Table 3-1) as used in the national study (with the amendments noted in the
previous section) and all activity codes were assigned by University of Maryland
coders who had extensive familiarity with the 1985 coding scheme. For each
reported activity, respondents were also asked whether there was a smoker present
during the activity (information which is not reported in the following tables).
Further details are provided in Wiley and Robinson (1990).
Table 5-1 summarizes the main distinguishing features of the CARB and national
surveys. It can be seen that both studies were based on probability
random-digit-dial (RDD) designs in telephone households, one conducted across
the state of California and the other across the nation as a whole. Both were also
spread across the entire year, although certain months were not covered in the
CARB study. However, the national data were mainly collected by prospective
mail-back diaries, while the CARB study employed the retrospective recall of
activities done "yesterday".
The CARB study has a somewhat higher overall response rate, although not higher
than the telephone portion of the national study. The telephone portion of the
national study used essentially the same study approach as the CARB study,
5-1
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Table 5-1. Summary Comparison of CARB and 1985
National Studies
STUDY ASPECT
Year
Months
Sample
Mode
Sample Used in Tables 6-1 thru 6-7
DAYS OF WEEK (18-64)
Weekday
Saturday
Sunday
TOTAL DIARY DAYS
DAILY PERIOD
NUMBER OF DIARY DAYS
DIARY FORMAT
Activities
Location
Time Periods
Social Partners
Special Features
ACTIVITY CODES
LOCATION CODES
TOTAL SAMPLE CHARACTERISTICS
SAMPLE SIZE
AGES
RESPONSE RATES
NUMBER PER HOUSEHOLD
SAMPLE SIZE (Over Age 18)
Female
Female Employed
Male Employed
Married
Child Under 18 in Household
Child Under 5 in Household
Age 65 +
College Graduate
OVERSAMPLES
CARB
1987-88
October - August
Full Probability
RDD Telephone
Aged 18-64
ALL
851 (54%)
223 (14%)
285 (18%)
1359
Full 24 Hours
One
Open
Closed (With Options)
Open
Not Recorded
Smokers Present
90+ (Modified Szalai)
44 New
1762 TOTAL
12 +
61%
One
1579
53%
57%
76%
59%
16%
NA
14%
28%
Portions of state
outside LA/San Diego
area
NATIONAL
1985
January - December
Full Probability
Mail-Back 2762
Telephone 1210 RDD
Personal 809
TOTAL 5358
Mail-Back, Aged 18-64
ALL
1416 (72%)
325 (16%)
239 (12%)
1980
Full 24 Hours
One
Open
Open
Open (Some directed)
Open
Enjoyment
Media Use
270+ (Szalai)
34 (Mail-Back; Personal)
10 (Telephone portion)
5358 TOTAL
12+
51%; 67%; 60%
All; One; All
4940
56%
53%
71%
64%
37%
11%
14%
22%
None
5-2
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although the CARB diaries were all done using automated CATI procedures
developed at the University of California at Berkeley, while the national diaries
were first recorded verbatim by interviewers on paper and only CATI entered after
editing. Moreover, the lack of substantial differences in activity durations across
the three modes (including telephone) in the 1985 national study indicates that
these data could be aggregated for a meaningful comparison with the CARB data
with minimal concern over study design differences. Nonetheless, more detailed
analysis may reveal significant differences once attention focuses on specific
activities or types of activities of relevance for exposure assessment.
The national study had more spread across the year and across days of the week,
while the CARB study oversampled weekend days, especially Sundays. Both
studies used open-end diary entries across the full 24 hours of a single day and
essentially the same basic diary code for activities — although the national study
employed more than twice as many activity codes in the initial coding. The location
codes for the CARB study were more numerous and more systematically organized,
both in general and around exposure assessment needs. The CARB diary was
unique in including data on the presence of smokers for each activity.
The national study interviewed more than three times the number of adult
respondents, both over age 12 (total n = 5358 vs n = 1762 for CARB) and over age
18 (n = 4940 vs. n = 1579 for CARB). The sample characteristics of adults in both
samples were rather similar in terms of proportions of women and of people aged
65 and older. Slightly higher proportions of men and women adult respondents
were employed and had college degrees in the California sample, while more
national respondents were married and presumably had children in the household
(only data on teenage children were collected in the California study, so that
information comparable to the national study are not available on young children
in the household in the CARB sample).
5-3
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6.0 RESULTS OF COMPARISONS OF OVERALL AVERAGES
The overall durations of time spent in various activities and in various locations are
shown in Tables 6-1 through 6-3. The tables are first shown for activities and then
for locations, with the data for the overall sample aged 18-64 described first,
followed by the data for men and then for women. The sample sizes in Table 6-1
(1359 and 1980) are lower than the totals in Table 5-1 be cause respondents aged
65 and older and aged under 18 have been excluded. This was done to standardize
the population base by limiting comparison to the "working segment" of the
population. Only the mailback diaries from the national sample are analyzed.
Data are reported in minutes per day, averaged across seasons of the year and days
of the week so that seasons and days are equivalently represented. The data have
been weighted to be project able to both the California and national population in
terms of days of the week, region, numbers of respondents per household, and for
3 monthly seasons of the year. That means that whatever sampling differences that
occur in the sample that lead to disproportionate numbers of days of the week,
respondents in each region or respondents per household are corrected for in the
calculations.
Before embarking on these analyses, it again needs to be stated that these initial
comparisons are confined to the basic activity categories employed in the study. As
noted in Table 3-1, these categories are based on economic and social distinctions
in activity and are not intended as most relevant for exposure analysis at this stage
of analysis. The subsequent attention to microenvironments in the latter sections
of this report attempts to address parameters of greater potential interest to
exposure researchers. In this section we first look at the activities and then at the
locations that later make up these microenvironments.
Activity: Table 6-1 shows the activity means for the overall sample. It can be seen
that the figures for work are higher in California than in the national study, both
for time at work and for the commute to work. The overall California figures for
work also come out higher because of the 8 minutes per day that CARD respondents
reported as travel activities during work (code 03); this travel activity was not
6-1
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Table 6-1. Differences in Average Time Spent in
Different Activities Between California and National Studies
(Minutes Per Day for Age 18-64)
00-49
OO-O9
00
01
02
03
04
05
08
07
06
OB
10-19
1O
11
12
13
14
IS
18
17
18
19
20-28
20
21
22
23
24
25
26
27
28
29
30-38
30
31
32
33
34
39
36
37
38
38
40-49
4O
41
42
43
44
49
48
47
48
49
NR -
* —
NON-FREE TIME
n-
PAIO WORK
(not used)
Main Job
Unemployment
Travel during work
(not used)
Second Job
Eating
Before/after Work
Breaks
Travel To/From Work
HOUSEHOLD WORK
Food Preparation
Meal Cleanup
Cleaning HOUM
Outdoor Cleaning
doth** Care
Car Repair/Maintenance (by R)
Other Repairs (by B)
Plant Care
Animal Care
Other Household
CHILD CARE
Baby Care
Child care
Helping/Teaching
Talking/Reading
Indoor Playing
Outdoor Playing
Medical care • Care
Other Child care
(At Dry Cleaners)
Travel. Child care
OBTAINING GOODS AND SERVICES
Everyday Shopping
Durable/House Shop
Personal Services
Medical Appointments
Govt/Ftnanctal Service
Car Repair services
Other Repair Services
Other Services
Errands
Trawl, Goods and Services
PERSONAL NEEDS AND CARE
Washing, Etc.
Medical Care
Help and Care
Meals At Home
Meals Out
Night sleep
Nape/Day Sleep
Dressing. Etc.
NA Activity
Travel, Personal Care/NA
Not Recorded In National Survey
Less Than 0.5 Min. Per Day
California
1887-88
03581
224
1
8
-
3
8
1
2
28
29
10
21
8
7
5
8
3
3
7
3
7
2
1
2
2
*
2
*
4
8
18
1
2
3
2
*
2
*
24
21
3
3
44
27
4SO
16
24
2
22
National
1885
(1880)
211
1
NR
-
3
8
2
2
29
38
11
24
7
11
5
6
5
5
a
8
s
1
1
3
1
1
1
NR
4
S
20
1
2
2
1
1
2
1
20
25
1
4
50
20
488
16
32
12
13
90-80 FREE TIME
n-
5048 EDUCATION AND TRAINING
90 Students1 Classes
51 Other Classse
52 (Not Used)
93 (Not Used)
94 Homework
59 Ubcary
M Other Education
97 (Not Used)
98 (Not Used)
9» Travel, Education
OO-68 ORGANIZATIONAL ACTIVITIES
80 Professional/Union
61 Special Interest
82 Political/Civic
63 Volunteer/Helping
64 Religious Groups
66 Religious Practice
66 Fraternal
67 Child/Youth/Famlly
68 Other Organizations
60 Travel, Organiiatkjos
TO-78 EWTEMaNMErWSOOAL ACTIVITIES
70 Sports Events
71 Entertainment, Events
72 Movies
73 Theatre
74 Museums
79 Visiting
76 Parties
77 Bars/Lounges
78 Other Social
78 Travel, Events/Social
80-88 RECREATION
80 Active Sports
81 Outdoor
82 Walking/Hiking
83 Hobbies
84 Domestic Crafts
85 Art
M Music/Drama/Dance
87 Games
88 Computer Use/Other
88 Travel, Recreation
90-98 COMMUNICATION
80 Radio
91 TV
92 Records/Tapes
83 Read Books
94 Reading Magazines/Other
85 Reading Newspaper
98 Conversations
87 Writing
98 Think, Relax
88 Travel, Communication
Total Travel
(Codes 09,29,29,49,58,68,
78. 88, 98)
California
1987-88
(135fl!
9
1
.
8
*
1
3
0
*
0
1
1
5
0
1
2
2
2
3
2
1
1
28
8
4
*
13
15
3
5
1
3
*
3
5
3
S
1
130
3
4
16
11
15
8
9
5
106
National
1885 :
(19801
5
3
7 i
1
1
2
1 j
1
«
1
2
7
*
•
1
4
2
1
3 |
1
« ^
25
7 |
6
t
16
13
7
4
1 |
6
1
2 \
7 I
3
6
3 !
126
1
7
10
9
25
a
6
*
90
6-2
-------
distinguished from other work activities in the national data, so that no comparisons
for the national data are possible.
Time spent doing most household tasks is generally lower in California, especially
cooking, laundry, and house cleaning. The California sample does report more
housework time for outdoor chores (e.g., yard work) and for indoor and outdoor
household maintenance/repair.
Time spent on child care, including chauffeuring them to various of their activities,
is slightly lower in the CARB study. That could be due to smaller numbers of young
children in California households; no data on presence of young children in the
household were collected with CARB study to see what role this might play in the
differences that are observed. This may account for the lower time spent in "baby
care" (code 20) in the CARB data; since age of children was not ascertained, much
of what is coded as "child care" (code 21) could be "baby care" in the CARB data.
On the other hand, time spent on shopping activities, especially for groceries and
other necessities, is slightly higher in California. That is also reflected in the greater
time in travel for shopping in the CARB data.
Personal care activity times show a similarly mixed picture. CARB respondents
reported less time washing and grooming than did national respondents but more
time sleeping. Less time was also reported in eating meals at home in the CARB
data, but more time was spent eating out and its related travel. Non-ascertained
times (code 48) are lower in the CARB data, although this is largely a function of
the telephone mode used in the CARB study; similarly low non-report times are
found in the telephone portion of the national study, indicating that this is a
methodological rather than a regional difference.
Time spent in adult education activities is slightly higher in the CARB data, while
time spent in organizations (especially religious activity) is lower than in the
national data. Time spent in social activities is much the same in both samples
although CARB respondents reported much more time going to fairs and other
entertainment events. Californians reported more time in active sports activities,
6-3
-------
but slightly less time in outdoor activities like hunting and fishing. Reported time
spent in domestic crafts was lower in California.
Finally, with regard to communication activities, reported time spent listening to
radio was lower in the CARB study, but was slightly higher for listening to
recordings. Californians spend more time reading, especially periodicals, but less
time in family telephone conversations. Relaxing and thinking time is slightly
higher in the CARB survey, as is travel related to communication activities.
Overall average travel time is about 18% higher in California than nationally. That
is mainly due to the travel times in connection with work, going to shops and
restaurants and travel related to communication and personal care.
We now turn to an examination of how these differences are related to gender.
Men: The first pairs of columns of Table 6-2 show the same comparisons as Table
6-1 but for the male portion of the two samples; female differences are shown in
the second pair of columns in Table 6-2. It can be seen that the longer work times
in the CARB data hold for men and women, while the greater work travel times
(both to work and during work) are greater in California men but not California
women.
Times reported for doing housework tasks tend to be more similar for men in the
two samples, although still lower in California for cleaning house and for plant care,
and higher for outdoor yard work. A general similarity in national and California
data is found for child care activities and for shopping, although time for shopping,
travel, and obtaining government services is longer in California.
The same differences in personal care in Table 6-1 are found again for men in Table
6-2, with California men spending more time eating out and related travel but less
time in dressing and grooming activities (but not washing activities). Sleep and nap
times are about the same in the two samples.
Adult education and organizational activities are also similar in time expenditure
across the California and national samples of men, and the same holds true for most
6-4
-------
Table 6-2. Differences in Average Time Per Day Spent in
Activities Between California and National Studies by Gender
(Minutes Per Day for Age 18-64)
MEN
00
00
OO
01
02
03
O4
OS
08
07
08
09
10
10
11
12
13
14
15
16
17
18
19
SO
20
21
22
23
24
25
28
27
28
29
30-
30
31
32
33
34
35
38
37
38
38
40-
40
41
42
43
44
49
48
47
48
49
- 49 NON-FREE TIME
-OB PAID WORK
(notuwd)
Main job
Unemployment
Travel during work
(not used)
Second job
Eating
Before/after work
Breaks
Travel to/from work
-19 HOUSEHOLD WORK
Food preparation
Meal clean-up
Cleaning house
Outdoor cleaning
Clothes care
Car repair/maintenance (by Ft)
Other repairs (by R)
Plant ewe
Animal care
Other household
29 CHILD CARE
Baby care
Child care
•Helping/teaching
Talking/reading
Indoor playing
Outdoor playing
Medical care • child
•Other child care
At Dry cleaners
Travel, child care
39 OBTAINING GOODS AND SERVICES
Everyday shopping
Durable/house shop
Personal services
Medical appointments
Govt/nnanclal services
Car repair services
Other repair services
Other services
Errands
Travel, goods and services
48 PERSONAL NEEDS AND CARE
Washing, etc.
Medical care
Help and care
Meals at home
Meals out
Night sleep
Naps/day sleep
Dressing, etc.
N A Activities
Travel, personal care
Calif
1987/88
n - (839)
280
1
13
4
7
2
2
37
13
4
6
13
2
8
10
1
3
8
1
2
1
1
2
2
0
1
*
2
4
13
3
2
0
3
«
21
22
2
2
44
28
471
17
17
2
25
Nat
1985
(921)
271
1
NR
.
4
10
3
3
31
14
4
9
10
2
10
11
7
4
8
2
2
*
1
2
1
*
1
NR
2
5
13
1
2
1
1
1
2
1
17
22
*
4
90
21
469
17
28
12
19
WOMEN
Calif
1987/88
(720)
188
*
3
.
3
4
1
2
19
44
17
38
4
13
3
8
4
4
8
8
12
3
1
3
2
•
4
*
9
12
25
2
2
2
1
*
2
1
28
20
4
5
45
27
489
14
31
2
18
Nat
1985
(10S9)
159
1
NR
2
8
1
2
19
95
18
38
4
19
1
2
4
8
8
13
8
2
2
4
2
1
2
NR
6
10
21
1
3
2
*
1
2
1
21
29
1
5
SO
20
4S8
17
32
11
12
NR - No* Recorded in Nation*! Sunny
* —
Less than 0.5 min. per day
6-5
-------
Table 6-2. Differences in Average Time Per Day Spent in
Activities Between California and National Studies by Gender—cont'd.
(Minutes Per Day for Age 18-64)
MEN
Calif Nat
50
50
60
70
80
00
-99
•SO
so
31
52
S3
54
55
58
57
58
50
-89
SO
81
82
83
64
85
88
67
68
68
-70
70
71
72
73
74
75
76
77
78
70
-80
80
81
82
83
84
85
88
87
88
80
•98
OO
01
02
83
84
85
08
87
88
88
FREE TIME
EDUCATION AND TRAINING
Students' elUM*
Other classes
(nolUMd)
(not used)
Homework
Ubrary
Other education
(nolUMd)
(notuMd)
Travtl, education
ORGANIZATIONAL ACTIVITIES
Professional/union
Special Inter**
Political/civic
Volunteer/helping
Religious group*
Religiou* practice
Fraternal
Child/ youth/tamily
Other organizations
Travel, organizations
ENTERTAINMENT/SOCIAL ACTIVITIES
Sports events
Entertainment, events
Movies
Theatre
Museums
Visiting
Parties
Bars/lounges
Other social
Travel, events/social
RECREATION
Active sports
Outdoor
Walking/hiking
Hobbies
Domestic crafts
Art
Mutic/drama/dance
Games
Computer uee
Travel, recreation
COMMUNICATION
Radio
TV
ReeordsAapes
Read books
Reading magazines/other
Reading newspaper
Conversations
Writing
Think, relax
Travel, communication
87/88
n- (838)
10
1
.
.
10
*
1
.
.
3
0
*
0
1
*
s
0
*
2
3
3
2
1
•
*
26
5
6
*
14
20
S
6
1
1
1
4
4
4
7
1
120
3
3
12
12
11
8
0
4
1885
(021)
7
3
.
.
8
•
1
.
.
2
•
1
0
A
1
5
*
0
1
3
2
2
2
1
*
24
8
8
1
17
30
10
4
3
2
1
2
6
2
8
4
137
1
5
11
10
17
6
6
*
WOMEN
Calif Nat
87/88
(720)
8
1
7
»
1
.
3
0
*
0
1
2
4
0
1
3
2
1
2
4
1
1
25
7
2
•
12
8
2
3
*
S
•
2
6
3
4
1
132
2
6
20
11
20
8
0
5
1885
(1058)
4
3
.
8
1
*
.
.
2
1
1
*
\
3
9
*
«
1
4
2
1
4
1
*
28
8
4
1
15
8
4
3
*
8
2
\
8
4
4
2
117
1
8
8
8
31
10
8
•
Total Travel
(Codes 08,28, 38, 48, SO. 80, 70, 88, 89)
lie
6-6
-------
social activities. California men do report more time at bars and lounges than the
men in the national sample, as well as less time in fishing-hunting type outdoor
activities and in hobbies and crafts activities.
California men report a little less time watching television than men nationally, and
less time listening to the radio as a primary activity; they report more time listening
to records and tapes and relaxing. Conversation time is also lower in the CARB
data.
California men spent almost 20% more time in all categories of travel time than do
men in the national sample.
Women: The second pairs of columns in Table 6-2 show the parallel comparisons
for women. It can be seen that California women report more time working than
in the national sample, but about the same time commuting to work. They also
report less time in housework activities, particularly cooking and doing laundry and
in caring for children than women nationally. On the other hand, women in the
CARB sample spend slightly more time in repair and maintenance activities
(especially for non-grocery items) and in shopping-related travel.
Patterns of time spent in various personal care activities are much the same as they
are in Table 6-1 for men and women together, although with much less time on
washing as well as on grooming. As in Table 6-1, women in California report more
time eating out and less time eating meals at home. Unlike the situation for men,
women in California spend more time sleeping.
California women report slightly more time taking classes than women nationally.
They spend much less time on religious activities, but they spend much more time
going to entertainment events than women nationally. They report less time than
women nationally on sewing and other domestic hobbies and on hunting- fishing
type outdoor activities.
California women report more 15 minutes more time watching television per day
than women in the national sample. Unlike the men in the California sample, they
spend somewhat more time reading; but like California men, they report less time
6-7
-------
on family and telephone conversations than is true nationally and also more time
in relaxing and thinking activity than is true for women nationally.
Women in California spend about 10% more time traveling than women in the
nation as a whole.
In summary, many of the patterns of differences found for the California and
national samples in Table 6-1 are replicated in the separate patterns of time
durations found for men and women in Table 6-2. Both male and female
respondents in the CARB study report more time doing work, eating meals at home,
dressing and grooming, engaging in family and telephone conversations, and
thinking/relaxing than is found nationally. Male and female California respondents
also reported more time eating meals away from home and in travel. The greater
travel times were related to travel for shopping, for eating out and for
communication and not-ascertained activities for both men and women.
On the other hand, some marked gender differences were found in Table 6-2. The
lower housework, washing, domestic crafts, and religious activities in California are,
however, primarily found among women. This is also true for the higher shopping
and sleeping times—and the higher adult education, TV viewing, and reading
times —in the California data. On the other hand, the greater time spent
commuting to work and listening to the radio and lower time in plant care are mainly
concentrated within the male portion of the CARB sample. The differential •;
overall travel times in the California and national data sets are twice as high among
California men as among California women.
Location Differences: The data on time spent in various locations in the California
and national samples are shown in Table 6-3. The first pair of columns shows the
overall California and national comparisons. The next pair of columns (third and
fourth) shows the comparison for the male portion of the sample and the final pair
of columns (fifth and sixth) for the female portion. In general, the rows of location
time are divided into three general categories: time at home (CARB codes
WC01-13), time away from home (CARB codes 21-40) and travel time (CARB
codes 51-61).
6-8
-------
Table 6-3. Difference in Average Time Per Day in Different
Location, Total Sample and by Gender
Between California and National Samples (Minutes Per Day Age 18-64)
TOTAL
AT HOME
Kitchen
Living Room
Dining Room
Bathroom
Bsdroom
Study
Oarage
Basement
Utility Room
Pool, Spa
Yard
Room to Room
Other NR Room
Total At Home
AWAY FROM HOME
Office
Plant
Oroceiy Store
Shopping Mall
School
Other Public Places
Hospital
Restaurant
Bar-Night dub
Church
Indoor Gym
Other's Home
Auto Repair
Playground
Hotel-Motel
Dry Cleaners
Beauty Parlor
Other Locations
Other Indoor
Other Outdoor
Total Away
TRAVEL
Car
Van
Walking
But Wop
Bus
Rapid Train
Other Travel
Airplane
Bicycle
Motorcycle
Other or Missing
Total In Travel
Not ascertained
TOTAL
* Less than 0.9 minutes per day
NR - not reported
Variable
WC01
WC02
WC03
WC04
wcos
wcoe
wcor
wcoe
wcoe
wcio
WC11
WC12
WC13
WC01 • ia
WC21
WC22
WC23
WC24
WCM
WCM
WC27
WCM
WCM
WCSO
WC31
WC32
WC33
WC34
WCM
WCM
WC37
WCM
WCM
WC40
WC21-40
WCS1
WCS2
WC93
WCM
WC9B
WCM
WCS7
WCM
WCM
WCOO
WC81
WCS1-81
WCM
California
1987-88
(n- 1388)
72
180
18
33
9M
7
10
*
2
1
27
21
3
ieT
88
42
13
M
27
14
17
30
10
8
4
61
11
12
8
1
2
2
12
_az_
430
78
20
8
1
4
1
1
1
1
1
1
118
2
1440
National
1889
(n- 1880)
M
•*£-
14
M
903
8
3
5
fv:
13T
894
204
y *
18
12
NR
~V 20
•f
10
NR
44
NR
16
NR
NR
NR
NR
32
-22.
384
\ «
/ ^
\
\
\
V
V ,3
/
I
J
84
e
1440
MEN
California
1M7-88
(n-838)
48
181
18
27
481
8
14
•
1
1
33
8
3
822
78
73
12
30
29
18
8
39
19
7
4
80
18
10
7
*
*
3
17
80
487
78
30
1O
*
8
1
2
1
1
2
1
130
1
1440
National
1989
(n- 921)
96
138
10
27
478
10
9
4
0
NR
80
888
~}MI
}•«
13
13
NR
J
8
NR
42
NR
27
NR
NR
NR
NR
41
NR
449
-.
1 M
\
\
\
V 15
/
/
101
8
1440
WOMEN
California
1987-M
(n-720)
M
1M
22
M
934
a
6
*
3
t
21
34
4
983
84
19
l*t
14
40
29
10
24
29
5
s
4
81
4
8
8
1
4
1
7
13
371
77
11
8
1
2
2
1
*
*
*
1O2
4
1440
National
1989
(n- 1059)
139
180
43
931
7
1
6
9
NR
S
\^
/"8
1022
\199
>33
NR
J- 18
11
NR
49
NR
16
NR
NR
NR
NR
• 24
NR
324
„
77
\
\
V
V ,0
(
i
87
7
1440
6-9
-------
In terms of time spent at home, respondents in the national sample report almost
half an hour more time in the kitchen of the home, while the California sample
reports about a half hour more time in the living room or den. The two samples
show rather similar times spent in dining rooms, in bathrooms, in bedrooms and in
an office/study in the home. Times spent in laundry rooms or utility rooms are also
about the same.
The California sample reported considerably more time in garages and basements
than the national sample. The little time spent in laundry/utility rooms are about
the same in the two samples.
Times spent outdoors and in other indoor locations in or near the home (code 00
in the national study location code, as shown in Appendix B) are very difficult to
compare in these data sets, because, as noted above, time spent in outdoor locations
was not clearly distinguished in the national survey. Some 124 minutes per day was
coded in location code 00, which included outdoor as well as general or unspecified
locations near the home. Overall, all such times in such residual categories (which
includes indoor as well as outdoor activities) is far greater in the national sample
(137 minutes = 124 in code 00 + 3 in code 09 + 10 in code 19) than in the California
sample (27 minutes). This residual code, in fact, accounts for most of the 58 minute
greater time in all at-home locations in the national sample (954 minutes) than in
California (894 minutes).
Turning to time spent away from home (exclusive of its related travel), time
reported in offices and plants is considerably higher at general "work" locations in
the national sample. Much of this difference, however, is due to certain coding
conventions employed in the CARB study; respondent work times while employed
at stores, restaurants, etc. in the CARB study were coded in terms of these specific
locations rather than as at "the work place". This, in turn, would account for the
larger times in California spent in grocery stores and shopping malls. Time spent
in schools and other educational settings are higher in California while the reported
time spent at other public places is about the same. (All of the above patterns could
change if one were to analyze these location differences using both the location and
activity data in combination—an analysis task that is outside the scope of the present
6-10
-------
report and of our intention here to highlight the differences in the straightforward
univariate coding of the two data sets.)
Time reported in restaurants and bars is higher in California, consistent with the
activity findings for eating out in Table 6- 1. Time spent in other people's homes
is also higher in California. Time spent in churches and other religious buildings is
less in California than nationally, consistent with the Table 6-1 averages reported
for religious activity time in the California sample.
Comparisons of time in the remaining away-from-home location categories are very
difficult to make between the two surveys, given the large differences in coding
conventions in the two studies. Nonetheless, the data suggests that Californians
spend overall more than 40 minutes more each day in these away-from- home
locations than is found nationally.
Consistent with their greater travel activity times hi Table 6-1, Californians also
spend more time in transit than is true nationally. Most of this seems to be
accounted for by time spent inside automobiles or motor vehicles. The travel times
in Table 6-3 are greater than in Table 6-1 because travel as part of other activities
( e.g., work, taking a walk) is included as travel in the "where" code.
In general, these overall findings in the first two columns of Table 6-3 are replicated
for the separate figures for both men and women as shown in the last four columns
of Table 6-3. The times spent at home between women in the national and
California samples (59 minutes difference = 1022-963) is about the same as among
men (64 minute difference, 886-822). The same gap is true for time spent in "other"
outdoor locations away from home, with California men spending far more time
there than is found nationally. The greater male-female gap is also true for time
spent traveling; main factors here are the greater times California men spent in
travel while doing work, and in walking/jogging; both are again coded as travel
locations in the CARB study and are not broken out separately in the national study.
Revised Location Codes: The Table 6-3 analysis of the many gaps in the location
data for the Table 6-3 data stands in marked contrast to the basic similarities found
for the activity data in Tables 6-1 and 6-2. This suggests the need for a reanalysis
6-11
-------
of the location data from the national survey with these differences in mind. In
order to make the location coding for the 1985 study more consistent with that used
in the California study, the location data for the mail-back diaries in this study were
subjected to a limited receding at the Survey Research Center of the University of
Maryland during the spring and summer of 1990. This was not done for the
telephone and personal interviews because of the different coding procedures and
the irretrievability of certain data from the telephone and personal diaries.
For this receding exercise, a new and expanded coding scheme was developed.
While largely based on the original code, the new code had a clearly defined and
mutually-exclusive category for activities done outside in yards and other outdoor
locations at or near the home. This is the new code 00 shown at the top of Table
6-4; Table 6-4 also shows the other new code categories alongside the old ones, with
new categories designated in capital letters and noted with an asterisk in this table.
In this receding exercise, it was necessary for coders to use the activity reports as a
guide to understanding where the activity was likely to have taken place. To make
the exercise maximally interpretable, strong assumptions were made about certain
activities. As shown in Table 6-4 in parentheses, unless otherwise specifically noted
by the respondent, all personal hygiene was coded as taking place in a bathroom,
all sleeping and grooming in a bedroom, all TV in a family room, all cooking and
eating in a kitchen, and all clothes care in a laundry/utility room. To the extent that
these assumptions are not accurate, the results of the subsequent analyses are
subject to question. Nonetheless, these are not unreasonable assumptions and
represent the best current estimate of where vast amounts of unclear location time
was spent.
It can be seen that in addition to the new category for at-home outdoor activities,
at-home activities done in hallways (code 14), in "other" rooms in the home (code
17), and in multiple rooms or the whole house (code 18) are also distinguished. A
final at-home category (code 19) was added to identify activities for which the
coders could not tell whether the activity was done inside or outside the home.
Further distinctions were added for other travel modes —buses (code 23),
6-12
-------
Table $4. Revised Location Codes lor Time Diaries
(New Codes Noted with Capitals and with Asterisk)
HOME
•00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
17
18
19
RESPONDENTS YARD/DRIVEWAY/GENERAL /OUTDOOR
Basement/Cellar
Bathroom (Washing, Shower, Etc.)
Bedroom (Stop, Getting Ready, Etc.)
Dining Room
Computer Room
Dan
Family Room/Front Room/ Living Room (TV, Etc.)
Gameroom/Recreation Room
Garage
Kitchen (Eating, Cooking)
Laundry/Utility Room (Washing Clothes, Etc.)
Office/Study
Porch
HALL
OTHER ROOM INSIDE HOUSE
SEVERAL ROOMS/WHOLE HOUSE
OTHER HOME-UNCLEAR INDOOR/OUTDOOR
TRAVEL
20
21
22
23
24
25
26
27
Transit (N A Mode)
Car
Truck/Van
BUS
TRAIN/SUBWAY
WALKING, HIKING, JOGGING, BIKING
OTHER MODE
AIRPLANE
OTHER
* 30 - WORK, PLACE NOT KNOWN
* 31 - OFFICE
" 32 - FACTORY, PLANT
* 33 - INDOOR WORK SITE
* 34 « OUTDOOR WORK SITE
* 35 - HOSPITAL
* 36 - CONSTRUCTION SITE
* 40 - FRIEND'S/RELATIVE'S HOME - INSIDE
* 41 - FRIEND'S/RELATIVE'S HOME - OUTSIDE
50 - Restaurant/Bar/Fast Food Place
60 - Indoor Place ol Leisure (Hotel)
70 - Outdoor Race of Leisure (Park)
*79 - MISSING
80 - School
81 - Church
82 » Stores/Shopping Centers/Beauty Parlors, Etc.
83 - Banks/Offices/Library, Etc.
• 84 - REPAIR SHOP
* 88 - OTHER - OUTDOOR
* 89 - OTHER - INDOOR
« 90 - CANNOT TELL INDOOR/OUTDOOR
•99 - NA-REF (ABSOLUTELY CANNOT TELL OR GUESS)
6-13
-------
trains/subways (code 24), walking and biking and the like (code 25), airplanes (code
27) and other modes (code 26).
An attempt was also made to refine work location codes into offices (code 31),
factories or plants (code 32), other indoor work sites (code 33) and hospitals (code
36); construction sites (codes 36) and other outdoor workplaces (code 34) were also
distinguished. Time spent inside (code 40) qnd outside (code 41) at another
person's home were distinguished, as well as time spent at repair shops (code 84).
Finally, uncertain or missing codes were assigned either as missing (code 79), other
outdoors (code 88), other indoors (code 89), unclear about whether indoors or
outdoors (code 90) and not ascertained/refused (code 99).
This revised code was then applied in receding locations that had been coded into
one of the nine most ambiguous categories in the original 1985 coding: 00
(outdoors and non-specified rooms at home), 09 (garages), 13 (porches), 20 (transit
mode not ascertained), 22 (other transit), 30 (work), 40 (friends'/relatives' homes)
and 89 (other). These locations were identified through computer sorting and the
coders reexamined the original handwritten diary for each respondent and receded
the location for that respondent's activity into the most appropriate of the
categories in Table 6-4. That code was then added to the new data file for each
respondent, making it possible to sort these revised location codes by the old code,
by activity or any other factor originally coded.
The results of this receding exercise are shown in Table 6-5 where the entries
represent aggregate minutes per day across the 18-64 age sample of 1980 mail-back
diaries. Thus, the entry 113,591 (minutes) in the first row and column of that table
indicates that this is the total number of minutes after receding that was spent in
outdoor activities at or near the home; that is, it was coded both as 00 in the original
code and as 00 in the revised code. That is the second largest entry in Table 6-5,
with a slightly larger entry (125,474 minutes) being found in Table 6-5 for multiple
rooms inside the home (code 18). Additional large entries are found in the first
column of Table 6-5 for bedrooms (mainly for the activity of sleeping), for family
rooms (mainly for TV viewing), for the kitchen (mainly for cooking) and for missing
6-14
-------
Table 6-5. Location Rccode Results
Total Minutes Per Day (n=1980)
Original Cod**
O
1
2
a
4
6
8
7
B
8
10
11
ia
13
14
17
18
18
20
21
22
23
24
25
28
27
30
31
32
33
34
35
36
4O
41
00
00
70
79
60
•1
«2
as
•4
M
w
80
88
Revised
Cod*
Outdoor
Basement
Bathroom
Bedroom
Otntng
Computer
Den
Family
Qanwoom
Oarage
KHetwn
Laundry
Study
Porch
Hall
Other
Multiple norm
OftMT
TrarwH
Car
Truck/Van
Bui
Subway
Walking, ate.
Other mod*
Airplane
Work
Office
Factory
Indoor Site
Outdoor SHe
Hospital
Construction
Inalde Friend'* House
Outside FicwxTi Houie
Reaturant
Hotel, etc.
Park. etc.
Mining
School
Church
Stone
Bank*
Repair
Outdoor, other
Indoor, other
Unclear
Not Ascertained
• Appendix B
00
113881
504
5587
51710
2328
IS
1202
30884
130
334
19583
2175
245
1185
343
2486
125474
18448
1118
578
38
42
17
1180
0
0
2540
120
0
0
590
0
0
ISM
$10
255
205
341
0
355
70
80S
30
130
3230
820
515
8872
381380
08
0
15
480
80
0
O
275
140
0
8870
30
0
0
0
0
0
115
0
0
10
0
0
0
0
0
0
330
0
0
0
0
0
0
85
0
0
0
0
0
0
0
O
0
24O
0
0
0
113
8893
13
0
0
0
10
30
0
80
105
0
0
80
30
0
10120
0
0
5
0
0
0
0
0
0
O
0
0
0
0
0
0
0
0
0
0
30
0
0
0
0
O
0
0
0
O
0
0
0
0
1045O
20
0
5
170
125
S3
0
0
so
0
0
75
0
0
0
10
15
155
10
34478
808
18
175
0
418
0
0
1045
10
0
0
0
0
0
132
0
386
0
165
0
33
O
180
0
0
15
127
0
140
38307
22
0
O
40
122
0
0
0
324
0
0
188
0
0
0
0
0
88
0
2388
588
24887
7145
1157
3508
721
8080
820
0
0
0
0
0
0
11
0
198
25
53
0
0
0
0
0
O
80
0
0
0
42781
30
0
0
880
185
10
O
0
480
0
0
1000
345
0
0
0
1871
180
0
20
810
480
845
O
585
785
O
380502
47502
10157
0
888
4540
2053
2120
0
5147
2734
0
0
3718
+8O
8414
880
2082
1300
570
0
80
481284
40
0
135
237
1872
55
0
75
2417
O
45
411
0
0
0
0
0
588
0
256
50
0
40
0
5
0
0
0
0
0
0
0
10
0
127534
1332
53
880
30
0
0
0
45
120
0
0
60
0
0
138008
88
25
0
15
975
0
0
0
150
0
0
21O
1OS
0
0
0
15
305
0
285
45
0
30
0
125
0
0
870
185
375
0
600
1768
35
107
150
15
10263
885
0
675
285
1573
538
240
3155
27983
2370
180
54658
6-15
-------
locations (mainly when the location was completely unclear either from the location
or activity information provided in the original diary).
This first column of Table 6-5 is of major interest because it helps to pinpoint how
the 124 minutes of "unclear at home" location time in the 1985 national survey
(which is part of the bracketed residual home category in the second column of
Table 6- 3) was spent. Taking the 113,591 minute per day figure and dividing by
the column total of 391,390 minutes gives a proportion of roughly 30% of all time
in this original code 00 category that was receded as being actually outdoors.
Multiplying this 30% by the 124 minutes gives a new figure of about 37 minutes in
yards and other outdoor locations at home. Similarly calculated, the new estimated
figures for time spent in multiple rooms in the home works out to 40 minutes, for
the bedroom to about an addi tional 17 minutes per day, for the family room or
living room to an additional 10 minutes per day, for kitchens to an additional 5
minutes per day and for still unclear locations (code 19) to an additional 5 minutes
per day.
The changes for the other eight originally ambiguous categories (categories 09,13,
20, 22, 30,40 and 89) in Table 6-5 are not as dramatic as those for code 00. Thus,
79% (6970/8853) of the time originally coded as being spent in garages was receded
as garages, as was 97% of the time coded as porches and almost 90% of the time
spent in non-ascertained vehicles. Most (58%) of the "other vehicle" code was
receded as time spent in trucks or vans. Most (79%) of the times spent at work
locations again could not be sorted into more exact categories — and of those that
could, relatively little was spent at construction sites or other outdoor locations. Of
time spent at friends' and relatives' homes, 94% was recoded as inside that
residence and only 1% as outdoors. Most (51%) of the "other" location times
remained as "other indoor"; in terms of its indoor/outdoor character, abut 6% of
those that could be sorted fell into one of the outdoor types of facilities (mainly in
the "other outdoor category").
The end result of all these recodings as far as the overall location coding is
concerned is shown in Table 6-6. The main general result is that time spent
outdoors at the home is actually larger in the national study (37 minutes per day)
6-16
-------
Table 6-6. Revised Time Spent in Different Locations in
National Study Compared to California Study
(Minutes Per Day for Age 18-64)
TOTAL
Kitchen
Living Room
Dining Room
Bathroom
Bedroom
Study
Garage
Basement
Utility Room
Pool, Spa
Yard
Room To Room
Other NR Room
TOTAL AT HOME
Office
Rant
Grocery Store
Shopping Mall
School
Other Public Place
Hospital
Restaurant
Bar-Nightclub
Church
Indoor Gym
Other's Home (Inside)
Auto Repair
Rayground, Park
Hotel-Motel
Dry Cleaners
Beauty Parlor
Varying Locations
Other Indoor
Other Outdoor
TOTAL AWAY
Car
Van/Truck
Walking
Bus Stop
Bus
Rapid Train
Other Travel
Airplane
Bicycle
Motorcycle
Other Or Missing
TOTAL IN TRAVEL
Not ascertained
TOTAL
Time Outdoors
Variable
WC01
WC02
WC03
WC04
WC05
WC06
WC07
WC08
WC09
WC10
WC11
WC12
WC13
WC01-13
WC21
WC22
WC23
WC24
WC25
WC26
WC27
WC28
WC29
WC30
WC31
WC32
WC33
WC34
WC35
WC36
WC37
WC38
WC39
WC40
WC21-40
WC51
WC52
WC53
WC54
WC55
WC56
WC57
WC58
WC59
WC60
WC61
WC51-61
California
1987-88
-------
than in California (27 minutes per day), as is time spent in multiple rooms in the
home (40 minutes vs. 21 minutes in California). The gap in time spent in kitchens
increases (72 to 104 minutes nationally), but the gaps in other locations tend to
close: by 10 minutes for living rooms (189 vs. 158 minutes nationally), by 1 minute
for dining rooms (19 vs. 15 minutes) as is true for bedrooms (508 vs. 521 minutes
nationally) because the greater sleeping time picked up in the receding process.
The times spent in away-from-home locations in Table 6-6 are much the same as
they were in Table 6-3, mainly because so little further distinction could be made
for these other codes after the receding process.
One new calculation is shown at the bottom of Table 6-6 and that is for the total
time spent at outdoor locations. It is the sum of WCs (Where Codes 10,11,34,40,
53, 54, 59, 60, and 61). This sum works out to 88 minutes per day for the CARS
data and only to 70 minutes for the national data. However, examination of the
individual categories shows that virtually the entire 30 minutes difference is
accounted for in the "other outdoor" category in the CARB data. A very large
portion of the 37 minutes per day in the CARB data can be linked to time spent
working in outdoor locations in that data set. Including such outdoor work activity
in the national data set may well have closed the gap. Such a step can only be done
approximately from the national data (e.g., by extrapolating from the respondent's
occupation), since no such indoor-outdoor distinctions were requested of
respondents in the 1985 national study.
Table 6-7 shows these receded location data from the national sample from a
somewhat different perspective, by demonstrating the unexpectedly wide range of
activities that are performed in outdoor locations near the home. It brings home
the difficulty that analysts fare in predicting locations from activities. This
cross-tabulation of activities by location does show that most of the types of
activities that one expects to be outdoor activities are, in fact, the one most likely
to be performed outdoors. Thus, among household activities (which take up more
than half the time spent outdoors near the home), yard work (15%) and plant/pet
care (16%) are the activities that fall mainly into the outdoor category. However,
almost as much "indoor-type" as outdoor-type housework activity is done
6-18
-------
Table 6-7. Proportion of All Time Spent Outdoors at or Near
Home by Activity (1985 National Data)
Activity
Percent of
Outdoor Tim*
By Activity
Sub Total (%)
00-08 Work
10 Cooking
11-12 Cleaning
13 Yard work
14 Laundry
15-16 Repairs, Maintenance
17-18 Pet/plant care
19 Other household
TOTAL HOUSEWORK
20-28 Child care
1
5
15
2
11
16
6
56
3
30-39
Shopping
40-42 Personal care
43-44 Eating
45-46 Sleeping
TOTAL PERSONAL
50-58
Education
60-68
Organizations
70-74 Cultural events
75-78 Visiting/social
TOTAL CULTURE AND SOCIAL
80-82 Sports/Walking
83-88 Hobbies
TOTAL SPORTS AND HOBBIES
91 TV
90,92-95 Reading
96-99 Talking
gg Relaxing
TOTAL COMMUNICATION
* Less than 0.5%
3
5
6
2
3
3
14
TOTAL 100
6-19
-------
outdoors—such as cooking outside (1%), cleaning carpets and other Household
objects outside (5%), putting laundry out to dry or other clothes care (2%),
repairing appliances/other household objects outside (11%) and performing
household management tasks outside (6%).
As expected, one also finds a fair amount of outdoor time near the home in Table
6-7 spent on sports activities (3%), on (mainly play) activities with children (2%),
on meals (2%) and on relaxing (3%). But more outdoor time is on hobby activities
(5%), and watching TV (6%) than on any of these "usual" outdoor activities. Six
percent of home outdoor/yard time is even spent sleeping and 7% doing paid work,
which further illustrates how little these "usual outdoor" activities take up the time
that people spend outdoors near the home.
6-20
-------
7.0 SYNOPSIS OF NATIONAL-CALIFORNIA DIFFERENCES
In this report, we have reviewed data on the methodological background and results
from the California (CARB) time activity study and from the 1985 national study
of Americans' Use of Time conducted at the University of Maryland, College Park.
In order to facilitate comparisons, data from the national study were receded to be
as comparable as possible to the California code categories. For the same reason,
analysis was restricted to the 18-64 age group.
In general, the data on average durations of activity matched up rather well across
the two samples. Californians tended to report more average time at work and
commuting to work in their diaries than was true nationally. They also reported
less aver age time doing housework and caring for children than was found
nationally. Time spent shopping in the CARB study was slightly higher. In general,
the above California-national differences in family care activities (housework, child
care, sleeping) were higher among women than among men across the two samples.
CARB respondents also reported more time sleeping and eating meals away from
home than respondents in the national sample. CARB respondents reported less
time working and grooming and eating meals at home; they also reported less
not-ascertained time, mainly due to the telephone method of data collection.
These differences also tended to be greater among women than among men.
Californians also spent more time in attending fairs and other entertainment and
reading than was true in the national sample, and these differences were also more
pronounced among women in the two samples. At the same time, Californians also
reported more time traveling. This difference was mainly found among men.
Despite these differences, the two data sets showed remarkably similar overall
patterns of activity. This was less true for the location codes. Several sources of
discrepancy were found in the comparisons of these data, including time spent in
automobiles vs. other modes of transit. In terms of time spent at home, CARB
respondents reported about an hour less time at home per day than national
respondents, with about 40 minutes more time in away- from-home locations and
20 minutes more time in travel. CARB respondents report more time at home in
7-1
-------
living rooms/family rooms and garages and less time in kitchens and basements than
was true in the national sample.
A receding of the location data from the national study provided some resolution
of the differences that were found, but several anomalies remained—particularly
the greater amounts of time spent in yards and other outdoor sites at the home in
the national study. That could be explained by smaller yards or more crowded
housing conditions in California, but the result clearly needs further study. Overall,
however, CARB respondents reported more time outdoors (about 88 minutes per
day vs. 70 minutes for the national sample), but much of this greater time appeared
as paid work outdoors which was not ascertained from the national data. The only
way to retrieve estimates of the total amount of paid work time that was spent
outdoors from the diaries is to make some strong assumptions based on the
respondents' reported occupations.
The strong comparability of the figures on average time for the activity data do
indicate that the California data could be used to generate a better set of location
codings for the national data. It also means that the CARB data on specific
exposure (e.g. passive cigarette smoke, gasoline and service station visitations)
collected in California may have national implications. Nonetheless, the only way
to be certain of this conclusion would be to conduct a separate new national
study—one that could build and expand upon the developmental work initiated in
the California study that designed a diary specifically oriented to exposure
assessment needs.
One might also conduct further analyses of these existing data sets to further
examine differences, but to control (as covariates in analysis of variance and
covariance) for the respondent's occupation, household composition (e.g.,
children) and other demographic differences. The relationships between spec, .c
exposures and activities and locations reported in the CARB study could also be
analyzed.
The analyses thus far described in this report are for the total durations of time
spent in each location/activity category. Also important for exposure assessment
7-2
-------
and modeling is the identification of the specific time(s) of day when these activities
occur. Many outdoor air pollutants exhibit diurnal patterns and peak periods and
it is important to know whether exposures occurred during morning/evening peak
traffic periods (for exposure to CO, NO2, and probably benzene) or during the
mid-day (for 03 and other photochemical species). Further analyses of this kind
should be feasible with the existing data sets.
More can also be learned by cross-tabulating the activities with locations to identify
the rare combinations and those that are not of interest from an exposure
perspective. This has the advantage of also identifying combinations that are
unlikely or that may indicate errors in reporting or in coding.
7-3
-------
8.0 CONSTRUCTING A CODE FOR MICROENVIRONMENTS
A major reason for analyzing time-diary data is to estimate time spent in various
microenvironments. Microenvironments refer neither solely to activities nor solely
to locations but to the combinations of activities and locations that yield potential
exposures. In some cases, it is the activity that is the more important determinant
of likely exposure (as in activities that likely require more exertion or that involve
use of pollutants). In other cases, it is the location that is more important (as in
locations in which pollutant concentrations are likely to be higher—such as being
in automobiles, dry cleaning establishments, bars and kitchens).
In the analysis below, a set of 16 separate microenvironments were defined for the
purpose of comparing the estimates from the U.S. national and CARD studies. It
needs to be emphasized that this 16-category set of distinctions is intended only as
an initial, exploratory breakdown for general comparison purposes. It is in no way
intended as a definitive or ideal coding scheme, since that will vary with the
particular pollutants under consideration or the particular behavioral assumptions
the analyst wishes to make.
Thus, in our Table 8-1 collapsed activity code, we group all child-care activity with
housework, even though some of these child-related activities may involve
strenuous play activity (activities 24 and 25) or medical care (activity 26). Similarly,
we group attending sports events, playing music and doing hobbies with TV viewing,
even though these may involve higher breathing rates or more physical exertion
than TV. We leave such distinctions to future analysts, who will be in a better
position to judge which assumptions they feel comfortable in making or which
pollutants they wish to model.
In the same way, we have included bathrooms and basements with "other rooms"
in the house —even though, for modeling VOC exposures, time in the bathroom
should be treated separately and even though time spent in basements is crucial for
modeling radon exposures. In much the same way, analysts may wish to separate
hospitals and beauty parlors from "other indoor" locations when modeling
exposure to benzene or other pollutants.
8-1
-------
Table 8-1. Collapsed Activity Codes Used to Construct
Microenvironments Code
Activity
0 Travel
1 Sleep
2 Family &
Personal
Care
3 Cook
4 Eat
5 Shopping/
Errands
6 Work/School
7 TV-Read-Resting
8 Physical
Activities
9 Social/
Cultural
1985
National Codes
09, 29, 39, 49, 59,
69,79, 89, 99
45,46
11-19,20-28,40,
41,48
10
06, 43, 44
30-38
00-02. 05, 07, 08
50-58
90-95, 97, 98,
70-74. 83-88
80-82
75-78, 96, 87.
60-68, 42
^1987-88
CARS Codes
03, 09. 29, 39, 49.
59, 69, 79. 89, 99
45,46
11-19,20-28,
40,41,47.48,
124. 165-169
474, 971
10
06, 43, 44, 914. 954
30-38
01,02,05,07
08, 50-58
90-95.97.98. 70-74.
83-88,939-940
80-82,801-830
75-78, 96, 87,
60-68, 42
Relevance for
Exposure Assessment
Potential exposure to
carbon monoxide and
benzene
Potential exposure to
smoke and gas from
cooking
Highly elevated
breathing rate
8-2
-------
The set of 16 microenvironments derived in Table 8-3 from Tables 8-1 and 8-2, then,
are proposed as an initial illustrative set of microenvironments rather than as the
optimal set that could be constructed.
These 16 microenvironments were based on a collapsing of the original activity
codes (see Table 3-1 and Appendix A) in the two studies from 90 + to 10 (in Table
8-1) and a collapsing of the original 34 - 44 location codes (see Table 3-2 and
Appendix B) to 10 (in Table 8-2). The collapsing scheme for activities is shown in
Table 8-1 and the 10 collapsed codes are shown in the ten rows of the table along
with the applicable codes from the national and CARB studies. The parallel
location reduced codes are shown in Table 8-2. A brief rationale for certain
distinctions is given in the final columns of Tables 8-1 and 8-2.
Cooking and eating activities are distinguished based on their likely proximity to
smoke and gas used for cooking. Travel activities are isolated because of their
higher likelihood of proximity to carbon monoxide and other by-products of
internal combustion engines. Sports and physical activities are separated because
of their elevated breathing rates.
The basis for the ten collapsed location codes is shown in Table 8-2, along with the
specific location codes from the national and California studies. The first five codes
refer to indoor locations. As the most likely sites for cooking activities and their
by-products, the kitchen is the first environment that is distinguished. All other
rooms inside a home are grouped in the next category, including rooms in friend's
and other's homes that the respondent was visiting. Workplace locations comprise
the third location code and bars/restaurants, etc. comprise the fourth—particularly
because of the high likelihood of exposure to cigarette smoke and other smoke and
gas. The fifth and final indoor location code includes a wide variety of "other"
locations, including stores, churches, schools, offices and hotels; until more is
learned about the likely exposure levels in these locations, there seems little reason
to differentiate them here.
The next set of location codes includes outdoor settings. The main divisions here
are between those activities that occur at or near home (mainly in the yard of one's
8-3
-------
Table 8-2. Collapsed Location Codes Used to Construct
Microenvlronments Code
Location
INDOOR
0 Garage/Auto Repair/
Dry Cleaners
1 Kitchen
2 Other Rooms
3 Workplace
4 Restaurant/Bar
5 Other Indoor
OUTDOOR
6 Yard, Outside
Residence
7 Parks/Other
IN VEHICLE
8 Vehicle - Internal
Combustion
9 Other
Vehicle
1985
National* Codes
09
01
01,02,03,04,05,
06,07,08,11,12.
13, 14, 17
30-39,80
50
40,60,81,82,83,
89,99,79
00,19
41,70,88,90,25
20,21,22,23,
24, 26, 27
1987-88
CARS Codes
07, 33. 36, 37
01
02.03,04,05,06,
08,09, 12, 13
21,22,25.27
22,28.29
23, 24, 26, 27, 30,
31,32.35,37,38,39
10, 11
34, 40, 53, 54, 59, 60
51,52.55
56, 57, 58, 61
Relevance for
Exposure Assessment
Potential high exposure
CO and VOCs
Potential exposure to
smoke and gas
Potential exposure to
several pollutants
depending on job duties
High potential exposure
to cigarette smoke,
other smoke and gas
Ambient exposure
Ambient exposure
Potential exposure to
carbon monoxide and
benzene
* Reduced Location Codes for Microenvironment
8-4
-------
Table 8-3. Derived Microenvironments for National
and CARB Data
Activity (0-8)
Travel
Sleep
Household
Work-Child
Cook
Eat
Shop/Errands
Work/Study
Leisure/Commun.
Physical Activity
Cultural/Social
Location (0-8)
Auto-
placM
1
1
1
0
1
1
1
1
1
1
Kitchen
Rnidnca
0
0
10
g
10
0
10
10
0
10
RM.
OUwr
Room*
15
16
11
9
15
12
7
15
6
14
Off/
Fact
15
0
11
0
15
12
8
15
6
14
R««aumt
Bar
0
0
0
0
2
2
2
2
0
2
Indoor
Not
RM.
15
16
11
9
15
12
8
15
6
14
Outdoor
Rn.
13
0
13
9
13
0
13
13
5
13
Outdoor
Not
R«.
13
13
13
0
13
13
13
13
5
13
Int.
Comb
V«hcl«
3
3
3
0
3
3
0
3
0
3
Other
V.hcl*
4
4
0
0
0
0
0
0
0
4
MICROENVIRONMENTS
1 Autoplaces 9 Cooking
2 Restaurant/Bar 10 Oth. Activities In Kitchen
3 In Int. Cmbstn Vehicle 1 1 House Hold Chores/Child Care
4 In Non Int. Cobstn. Vehicle 12 Shop/Errands
5 Physical Activity Outdoor 13 Other activities Outdoor
6 Physical Activity Indoor 14 Social and Cultural Activity
7 Work/Study-Residence 15 Leasure-Eat-Communication Indoor
8 Wrk/Stdy-Not In Residence 16 Sleep/Indoor
8-5
-------
home) and those that occur away from home (mainly at parks and playgrounds).
These away-from- home outdoor locations almost always entail some travel to
reach.
The final two locations concern travel modes. Code 8 contains those travel modes
in which an internal combustion engine is involved — mainly automobiles, vans,
trucks and buses. Code 9 includes all modes of travel that do not involve internal
combustion engines.
When the ten activity codes in Table 8-1 and the ten location codes in Table 8-2
codes are cross-classified, they result in a potential set of 100 microenvironments.
However, for practical purposes, most of these 100 microenvironments are largely
redundant; they are also difficult to keep track of and to remember. Because of
this, a subset of 16 of the microenvironments that stood out as important to
distinguish were identified and these are defined in terms of the cross-classification
of activities and locations in Table 8-3. These microenvironments will be examined
in the remaining tables
in this report.
For this analysis, the total samples—including adolescents aged 12-17 and senior
citizens aged 65 and over in both the CARB study and in the mailback portion of
the national study—are used. The sample sizes rose to 1872 for the CARB study
and to 2762 for the 1985 national study. The national sample was weighted to
provide a ratio of 46.5 males to 53.5 females, in equal proportion for each day of
the week, and for each quarter of the year. The time weights provided for the
CARB study (which adjusts for strata as well as weekday and season) were used in
weighting the California data.
Before embarking on these analyses of microenvironments, it is useful to review
some basic data on three types of locations for exposure analysis: time spent
indoors, time spent outdoors and time spent in travel.
Table 8-4 shows the duration of time for the total age 12 and above sample as
allocated across the three type of locations. It can be seen that the most prevalent
8-6
-------
set of locations are indoor —1255 minutes for the CARB study and 1279 minutes
for the national study. These represent 87-89% of all daily time.
Table 8-4. Time Indoor, Outdoor and In-Vehicle
Calfornia vs. National
(In Minutes Per Day for Population Aged 12+)
CODE DESCRIP
1 INDOOR
2 OUTDOOR
3 IN-VEHICLE
TOTAL
a.
*
Standard Error of
Weighted number
MEAN DURATION
CARB
(n-1762)
1255
86
98
1440
Mean
S . E . a NAT S . E .
(n=2762)
28 1279 21
5 74 4
4 87 2
1440
The California data shows less indoor time and thus more outdoor time and time
in vehicles than in the national sample. Also shown in Table 8-4 is the standard
error of the mean for each of these estimated times. Since the standard errors for
indoor time (21 and 28 minutes) are about the same as the differences between the
two sample means (24 minutes = 1255 - 1279), this difference is not statistically
significant.
However, the greater California times for both outdoor times (12 minutes) and
vehicle times (11 minutes) are more than twice as high as the standard errors,
meaning that they are significant at the .05 level.
8-7
-------
9.0 CALIFORNIA-NATIONAL COMPARISONS ON
MICROENVIRONMENTS
The tables in this section provide a comparison of "doers" proportions and
durations for the two studies. The standard errors are provided in these tables for
the whole sample's comparative durations.
Table 9-1 shows the national and California comparisons, first for the collapsed
activity and location codes described in the previous section, and then for the
16-category code for microenvironments that results from their cross-classification.
Consistent with earlier tables, there is greater convergence in the
national-California figures for activities than there is for locations. As in earlier
tables, these mainly revolve around the lower times reported in California on
family/personal care activity (code 2), cooking (code 3), and social/cultural
activities (code 9), and the greater times Califoraians reported in work (code 6),
sleeping (code 1), eating (code 4), and particularly traveling (code 0). Time spent
in shopping (code 5), physical (code 8) and communication/leisure activities (code
7) are roughly the same in the two samples.
The difference for locations are more pronounced, not only for travel and location
(codes 8 and 9), but for the greater times Californians spend in parks and other
outdoor locations (code 7, mainly including outdoor places of work), in restaurants
and bars (code 4), in other (non-home) indoor areas (code 5), and in autoplaces,
garages, etc (code 0); with respect to this last difference, it is important to remember
that times spent in such locations involving motor vehicles (plus time at
dry-cleaning establishments) was coded specifically for those locations in
California, but is hidden inside other location codes in the national data. This is
responsible for many of the large discrepancies in Table 9-2. As in Table 6-3,
Californians also spend less time in several locations: in kitchens (code 1), in their
yards (code 6) and at work locations (code 3). These lower times at work locations,
of course, are mainly a function of many California work locations being coded more
specifically by type, e.g., working in a store, a school, or a hospital and thus being
recorded in other location categories in Table 9-1.
9-1
-------
Table 9-1. Time in Various Activities, Locations, and
Microenvironments
(In Minutes Per Day For Population Ages 12+)
CODE DESCRIP
ACTIVITY
0 TRAVEL
1 SLEEP
2 HU/CKORE/PER
3 COOK
4 EAT
5 SHOP/ERRNOS
6 WORK/STUDY
7 LEISR/COMH
8 PHYSICAL
9 CULTRE/SOCIAL
LOCATIONS
0 AUTOPLACES
1 IO.RES.KITCH
2 ID. RES. OTHER
3 ID.OFF./FACT/
4 IO.RESTRNT/BA
5 ID. OTHER
6 00. RES
7 00. OTHER
8 INT.CMSSTN
9 OTH.VEH
MICROENVIRONMENTS
1 AUTOPLACES
2 RESTRNT/BAR
3 IN-VEH/IC
4 IN-VEH/OTH
5 PHYSICAL/00
6 PHYSICAL/ID
7 UORK/STDY-RES
8 URK/STD-OTH
9 COOKING
10 OTH.ACTV/KITC
11 CHORES/CHILD
12 SHOP/ERRNO
13 OTHER/00
14 SOC/CULTURAL
15 LESURE-EAT/ID
16 SLEEP/ ID
a S.E. * Standard
* Weighted Nunber
MEAN DURATION
CARB
Cmtt.)
Cn«1762)*
109
504
144
27
89
35
232
211
25
64
20
74
813
145
36
167
28
59
95
3
20
36
95
3
17
7
13
184
27
49
100
31
69
53
237
498
Error of
S.E.-
(mts.)
4
12
5
1
3
2
11
6
2
4
4
3
19
8
3
8
2
5
4
1
4
3
4
1
2
1
2
9
1
2
4
2
5
3
7
12
Mean
NAT
(mts.)
*
87
498
175
35
81
34
207
209
27
89
3
105
814
186
21
150
47
27
87
1
3
21
87
1
17
8
16
179
34
73
123
31
56
73
224
494
S.E.
(mts.)
2
9
5
1
2
2
7
5
2
3
0
3
14
7
1
5
3
3
2
0
0
1
2
0
2
1
1
6
1
2
3
1
4
3
5
9
MEAN DOER
CA
(mts.)
120
505
152
55
93
71
472
230
105
118
108
96
820
368
102
231
91
124
111
94
108
102
111
94
107
68
131
450
55
74
109
70
117
112
250
501
NAT
(mts.)
96
498
176
57
82
69
396
221
115
126
66
120
821
395
77
191
115
140
97
91
66
77
97
91
135
74
142
390
57
88
124
67
120
118
232
495
X DOER
CA
(X)
91
100
95
49
95
49
49
92
24
54
19
77
99
40
35
72
30
47
86
4
19
35
86
4
16
10
10
41
49
67
92
45
59
47
95
99
NAT
(%>
91
100
100
61
98
49
52
94
23
71
5
87
99
47
28
78
41
19
90
1
5
28
90
1
13
11
11
46
61
83
99
46
47
62
97
100
9-2
-------
Table 9-2. Time Spent in Various Microenvironments
By Gender
(In Minutes Per Day For Population Ages 12+)
KEN
CODE DESCRIP
1 AUTOPLACES
2 RESTRKT/BAR
3 IN-VEH/IC
4 IN-VEH/OTH
5 PHYSICAL/00
6 PHYSICAL/ID
7 WORK/STDY-RES
8 URK/STD-OTH
9 COOKING
10 OTH.ACTV/KITC
11 CHORES/CHILD
12 SHOP/ERRNO
13 OTHER/00
14 SOC/CULTURAl
15 LESURE-EAT/ID
16 SLEEP/ID
a S.E. » Standard
* Weighted limber
WOMEN
CODE DESCRIP
1 AUTOPLACES
2 RESTRNT/BAR
3 IN-VEH/IC
4 IN-VEH/OTH
5 PHYSICAL/00
6 PHYSICAL/10
7 WORK/STDY-RES
8 WRK/STD-OTH
9 COOKING
10 OTH.ACTV/KITC
11 CHORES/CHILD
12 SHOP/ERRND
13 OTHER/CO
H SOC/CULTURAL
15 LESURE-EAT/ID
16 SLEEP/ ID
a S.E. » Standard
* Weighted Number
CARB
(IDtS.)
(n»867)*
31
45
105
4
25
8
14
213
12
38
66
21
95
47
223
492
MEAN
S.E
(mts
8
4
7
1
3
1
3
14
1
3
4
3
9
4
10
17
DURATION
.* NAT
.) (mts.)
(n*1284)
5
22
92
1
24
11
17
221
14
54
88
23
70
71
235
491
S.E.
(mts.)
*
1
2
3
1
3
1
2
10
1
3
3
2
6
4
8
14
MEAN
CA
(mts.)
142
106
119
79
131
63
126
398
43
65
75
61
153
112
240
499
DOER
NAT
(mts.)
90
73
99
166
139
84
153
429
35
69
89
56
131
118
241
492
X DOER
CA
(X)
22
42
88
5
19
13
11
54
28
58
88
35
62
42
93
99
NAT
(X)
6
31
92
1
18
13
11
52
41
78
99
42
53
60
97
100
Error of Mean
CARB
(mts.)
(n-895)*
9
28
85
3
8
5
11
156
42
60
134
41
44
59
251
504
MEAN
S.E.
(mts.
2
3
4
2
1
1
2
11
2
4
6
3
4
5
10
15
DURATION
* NAT
S.E.
} (mts.) (mts.)
(n»1478)*
1
20
82
1
11
6
15
142
52
90
153
38
43
75
215
496
0
2
3
0
2
1
2
7
2
4
5
2
4
4
7
11
MEAN
CA
(mts.)
50
86
100
106
86
70
120
383
65
82
140
78
82
114
263
506
DOER
NAT
(mts.)
35
79
94
69
101
57
150
384
67
102
154
74
97
110
224
497
% DOER
CA
(X)
18
32
85
3
10
8
9
41
63
73
95
52
53
51
96
10Q
NAT
(X)
3
26
88
1
11
10
10
37
78
89
100
52
45
68
96
100
Error of Mean
9-3
-------
Many of these location coding differences, then, account for the major differences
in microenvironments found at the bottom of Table 9-1. This includes the greater
times reported in California inside autoplaces (code 1), restaurants/bars (code 2),
and motor vehicles (code 3). On the other hand, we find Californians having much
lower reported times in such microenvironments as kitchens (codes 9, 10), family
care settings for house chores, child care (code 11) and social/cultural settings (code
14). Nonetheless, many of these differences in microenvironments that occur may
be related to coding differences in the two studies rather than to differences in
activity patterns or in locations per se.
With these adjustments for participation taken into account, it can be seen that the
same "leveling" of duration times appears for many other microenvironments, which
have low overall mean figures. The restaurant/bar figures rise to 102 and 77 minutes
in terms of durations per participant. In "other" (non-combustion engine) vehicles
rise to 94 and 91 minutes, while in physical indoor activities, from 68 and 74 minutes,
in work and study at home to 131 and 142 minutes, and in work to 450 and 390
minutes (which translates to 71/2 and 61/2 hours of work per workday). In shopping
they rise to 70 and 67 minutes and in social/cultural activities to 112 and 118 minutes
per day. The largest discrepancy in California and national figures occurs for
autoplaces (102 minutes vs. 66 nationally) and for physical outdoor activities (107
vs. 135 minutes). Otherwise the figures from the two surveys come much more into
line on a per participant basis.
In Tables 9-1 through 9-4, the standard errors have been estimated for the whole
sample estimated average times. In general, when the differences between the
national and California averages exceed the (weighted average of the) standard
errors of the two estimates by afactor of about two (1.96 to be exact), the differences
can be said to be statistically significant beyond a 1 in 20 (5%) chance. Thus, the
22 minute difference in travel activities between the California average (109
minutes) and the national average (87 minutes) is statistically significant because
it is more than 5 times larger than the average standard errors of means (4 and 2
minutes), respectively. On the other hand, the difference in average sleeping times
of only 6 minutes (504-498) is not significantly greater than the 12 and 9 minutes
standard error estimates.
9-4
-------
Table 9-1 also introduces two new statistical parameters associated with each
activity, location and microenvironment code. These are the mean time for
respondents who report participating in the activity and the percentage of
respondents who do report participation. Thus, 91% of both the California and
national samples report at least one episode of travel on the diary day, so that the
mean travel times for those who travel increase to 120 minutes for the CARB data
and to 96 minutes for the national data. On the other hand, only 24% of the
California sample and 23% of the national sample report engaging in sports or other
physical activities during the day so that the average figures per participant rise to
105 and 115 minutes respectively. Note that 100% of both samples report some
sleeping during the diary day so that the original means and means per doers are
identical.
This distinction becomes especially crucial for many of the microenvironment
codes, because many of them involve low participation. Less than 20% of CARB
respondents and only 5% of national respondents, for example, reported being in
"autoplaces". On a per participant basis, however, this translates to 108 minutes per
participant in the CARB study and 66 minutes in the national study, which indicates
more similarity in the two studies than is evident from the sample mean durations.
It also emphasizes the important point of the high durations of times that are
involved for those who go to such places and the greater risk of exposure to
pollutants at those locations.
Gender: Differences between the microenvironment figures for men and women
are shown in Table 9-2, using the same format as in Table 9-1. The major
differences found in Table 9-1 by the larger national vs. California differences again
dominate this table, although there are some striking and non-surprising gender
differences as well. For example, women spend about twice as much time as men
cooking and doing other activities in the kitchen and also much more time doing
chores and other family care in other rooms of the house—as well as shopping—in
both the California and the national data. Men spend much more time in garages
(autoplaces), doing physical activity, and other outdoor locations, at workplaces,
and in motor vehicles in both studies.
9-5
-------
Thus, the most important consistency in Table 9-2 is that the same patterns of
findings are replicated in the two studies. Both sets of data agree that men spend
more time traveling, working, and doing sports/physical activities, while women do
more family/personal care activities, far more cooking, and more shopping as well.
This, then, is reflected in the major microenvironmental consistencies by gender
apparent in the table—men spending much more time in autoplaces, garages, in
motor and other vehicles, in strenuous physical activity outdoors, in other outdoor
sites, and in work locations. In contrast, women spend more time cooking, doing
other activities in the kitchen, and doing other chores and shopping.
Many of these differences remain on a per participant basis. Men who spend time
at autoplaces, at restaurants/bars, in motor vehicles and in physical outdoor
activities still spend more time in such places than women who spend time there.
In tue same way, women still spend more time in cooking, home care and shopping
activities on a per participant basis—as do men in these microenvironments.
There are some areas where the two studies agree less well, however. Men spend
more time in restaurant/bar locations in California, but not in the national data.
That again may be due to the inclusion of workers in such locations in the California
data. Men in California also report less time in communication activities in the
national sample, while women report less such leisure time in the national sample.
The reasons for these differences are not entirely clear and need to be checked by
further, multivariate analysis involving careful statistical controls.
Type of Day: Table 9-3 shows differences in the two samples on a weekday
vs.weekend day basis. Again, leaving the overall California-national differences
aside, the patterns of results are highly similar. Weekends are marked by higher
amounts of time spent in restaurants/bars (in California), in motor vehicles, in
outdoor sporting environments, in other outdoor activities, in social-cultural
settings, in leisure/communication activities and in sleep. All of these differences,
of course, result from the lower times spent at places of paid work activity.
Put more directly, almost all leisure activities increase on the weekend when the
work week is finished for most people. Nonetheless, many of these are not dramatic
9-6
-------
Table 9-3. Time Spent in Various Microenvironments
By Type of Day
(In Minutes Per Day For Population Ages 12 + )
Weekday
CODE DESCRIP
CARB
(Bits.)
MEAN
S.
DURATION
E.* NAT
(rots.) (mts.>
(n*1259)*
1 AUTOPLACES
2 RESTRMT/BAR
3 IN-VEH/IC
4 IN-VEH/OTH
S PHYSICAL/00
6 PHYSICAL/ID
7 WORK/SIDY -RES
8 WRK/STD-OTH
9 COOKING
10 OTH.ACTV/KITC
11 CHORES/CHILD
12 SHOP/ERRNO
13 OTHER/00
14 SOC/CULTURAL
15 LESURE-EAT/ID
16 SLEEP/ID
a S.E. » Standard
* Weighted Number
WEEKEND
CODE OESCRIP
1 AUTOPLACES
2 RESTRHT/BAR
3 IN-VEH/IC
4 IN-VEH/OTH
5 PHYSICAL/00
6 PHYSICAL/ID
7 WORK/STDY-RES
8 URK/STD-OTH
9 COOKING
10 OTH.ACTV/KITC
11 CHORES/CHILD
12 SHOP/ERRNO
13 OTHER/00
14 SOC/CULTURAL
15 LESURE-EAT/ID
16 SLEEP/ID
21
29
90
3
14
7
14
228
27
51
99
30
67
42
230
490
Error of
CARB
-------
differences. Thus, there is virtually no change in time spent in kitchens, in garages,
(autoplaces), and other microenvironments where house and family obligations are
performed. In fact, there is a slight increase in such activities on the weekends in
both samples looked at on a per participant basis; many of these differences thus
become less-pronounced. Most importantly, average work time for those who work
drops from 401-415 minutes per day on weekdays to 328-361 minutes per day on
weekends. Translated into hours, the average workday during the week is just short
of 7 hours per day while on weekends it drops to 5 1/2-6 hours. In contrast, the
durations of social/cultural and of communicative activities rise on the weekends
in both the California and national data sets.
Age: Microenvironmental differences by age are shown in Table 9-4, again after
weighting to control for day-of-the-week and other factors. Once again, the
patterns of results are strikingly similar in the two samples.
Thus, in both samples we find largest amounts of time spent in restaurants and bars
in the 18-24 and 25-44 year-old age groups, and the same is true generally for travel
microenvironments, both for motor vehicles and for other travel modes. The 12-17
age group generally reports most time in both outdoor and indoor sports activities,
and conversely in sleeping. They also report lowest times in family care activities,
like housework and shopping.
The 18-24 age group also reports higher than average times in physical activities,
and in school-related activities as well. This groups reports by far the highest times
on social-cultural microenvironments.
The 25-44 age group, in addition to their higher than average times at
restaurants/bars and in travel, reports higher than average time in work
microenvironments as well. The 45-64 age group is marked only by their higher
than average time spent in kitchens, while not cooking.
The oldest age group, ages 65 and older, reports the highest times in such kitchen
environments, both for cooking and for other activities. They also report highest
times watching television and in other communication activities, but not more time
sleeping.
9-8
-------
Table 9-4. Time Spent in Various Microenvironments
By Age Groups
(In Minutes Per Day For Population Ages 12+)
Age Group * 12-17
CODE DESCRIP
1 AUTOPLACES
2 RESTRNT/BAR
3 IN-VEH/IC
4 IN-VEH/OTH
5 PHYSICAL/00
6 PHYSICAL/ID
7 WORK/STOY-RES
8 WRK/STD-OTH
9 COOKING
10 OTH.ACTV/KITC
11 CHORES/CHILD
12 SHOP/ERRNO
13 OTHER/00
14 SOC/CULTURAL
15 LEI SURE-EAT/ID
16 SLEEP/ID
a S.E. » Standard
* Weighted Number
Age Group « 18-24
CODE DESCRIP
MEAN DURATION
CARS
(flits.)
(n»183)
16
16
78
1
32
20
25
196
3
31
72
14
58
63
260
557
S.E."
*
2
9
79
0
32
15
22
159
11
53
91
26
70
87
237
548
S.E.
(mts.)
1
2
7
0
8
3
4
14
3
4
7
4
13
10
16
31
MEAN
CA
(mts.)
124
44
89
19
110
65
76
339
19
51
77
50
78
109
270
560
DOER
HAT
(mts.)
73
60
88
12
130
87
82
354
40
64
92
68
129
120
242
551
X DOER
CA
(X)
13
36
88
5
29
31
32
58
15
61
93
27
75
57
96
99
NAT
(X)
3
15
89
1
25
18
26
45
27
83
99
38
54
73
98
99
Error of Mean
HE AN DURATION
CARB
(mts.)
S.E.'
(mts.)
*
1 AUTOPLACES
2 RESTRNT/BAR
3 IN-VEH/IC
4 IN-VEH/OTH
5 PHYSICAL/00
6 PHYSICAL/ID
7 WORK/STOY-RES
8 WRK/STD-OTH
9 COOKING
10 OTH.ACTV/KITC
11 CHORES/CHILD
12 SHOP/ERRNO
13 OTHER/00
14 SOC/CULTURAL
15 LESURE-EAT/ID
16 SLEEP/ ID
a S.E. * Standard
* Weighted Number
16
40
111
3
13
5
30
201
14
31
79
35
80
65
211
506
Error
4
8
13
1
3
2
11
24
2
5
8
7
15
10
19
30
NAT
(mts.)
(n=330)
7
28
103
2
17
8
29
207
18
42
124
31
34
100
182
511
S.E.
(mts.
*
2
3
8
1
4
2
6
20
2
3
9
4
4
12
11
26
MEAN
CA
) (mts.)
71
98
122
60
88
77
161
344
40
55
85
71
130
110
234
510
DOER
NAT
(mts.)
137
70
109
160
110
76
185
391
39
55
125
65
84
141
189
512
% DOER
CA
(X)
22
41
91
5
15
7
19
58
36
57
93
49
61
59
90
99
NAT
(X)
5
40
94
1
15
10
16
53
46
76
99
48
40
71
96
100
9-9
-------
Table 9-4. Time Spent in Various Microenvironments
By Age Groups (cortt'd.)
(In Minutes Per Day For Population Ages 12 + )
Age
Group « 24-44
CODE DESCRIP
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
AUTOPLACES
RESTRNT/BAR
IN-VEH/IC
IN-VEH/OTH
PHYSICAL/00
PHYSICAL/ID
UORK/STDY-RES
WRK/STD-OTH
COOKING
OTH.ACTV/KITC
CHORES/CHILD
SHOP/ERRND
OTHER/00
SOC/CULTURAL
LESURE-EAT/ID
SLEEP/10
CARS
(fflts.)
*
25
44
98
5
17
6
7
215
32
43
110
33
68
50
202
487
MEAN DURATION
S.E.*
(mts.)
9
5
5
2
3
1
2
14
2
3
6
4
8
5
9
17
NAT
(fflts.)
(n>1061)
2
25
94
1
19
7
16
220
38
70
133
33
48
56
200
479
S.E.
(mts.)
*
1
3
4
0
4
1
2
11
2
4
6
2
6
3
8
14
MEAN
CA
(mts.)
114
116
111
143
128
61
137
410
59
65
119
71
127
122
215
491
DOER
NAT
(mts.)
43
86
101
80
164
71
181
422
57
86
134
66
105
94
208
480
X DOER
CA
CX)
21
38
88
4
13
9
5
52
54
65
92
47
54
41
94
99
NAT
(X)
4
29
93
1
12
10
9
52
67
81
99
50
46
59
96
100
a S.E. * Standard Error
* Weighted Number
Age
CODE
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
a
*
Group 45-64
OESCRIP
AUTOPLACES
RESTRNT/BAR
IN-VEH/IC
IN-VEH/OTH
PHYSICAL/CO
PHYSICAL/ ID
WORK/STDY-RES
WRK/STD-OTH
COOKING
OTH.ACTV/KITC
CHORES/CHILD
SHOP/ERRNO
OTHER/00
SOC/CULTURAL
LESURE-EAT/ID
SLEEP/ ID
S.E. * Standard
Weighted Nirober
MEAN DURATION
CARS
(mts.)
(n*406)*
20
31
100
2
14
5
10
173
31
62
99
32
76
50
248
485
Error
S.E.'
(mts.)
5
4
11
1
3
1
3
20
3
6
8
3
12
5
15
23
NAT
(rats.)
(n*579)*
4
19
82
1
7
7
9
180
43
90
121
33
60
73
238
472
S.E.
(mts.)
1
2
5
1
1
2
2
13
3
6
6
3
7
6
11
15
MEAN
CA
(mts.)
94
82
117
56
123
77
139
429
68
91
109
77
134
107
261
491
DOER
NAT
(mts.)
73
67
91
198
79
77
169
429
64
101
122
67
118
116
244
472
X DOER
CA
(X)
22
38
86
3
12
7
7
40
46
68
91
41
56
47
95
99
NAT
(X)
6
28
90
1
9
9
5
42
68
90
99
49
51
63
98
100
9-10
-------
Table 9-4. Time Spent in Various Microenvironments
By Age Groups (cont'd.)
(In Minutes Per Day For Population Ages 12 + )
Age
Groip * 65+
CODE OESCRIP
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
b
*
AUTOPLACES
RESTRNT/BAR
IN-VEH/IC
IN-VEH/OTH
PHYSICAL/00
PHYSICAL/10
WORK/STDY-RES
WRK/STD-OTH
COOKING
OTH.ACTV/KITC
CHORES/CHILD
SHOP/ERRHO
OTHER/00
SOC/CULTURAL
LESURE-EAT/1D
SLEEP/ID
S.E. * Standard
Weighted Number
CARS
(mts.)
(n-158)
9
25
63
2
15
3
5
30
41
97
123
35
55
49
386
502
Error
MEAN
S.E
(mts
*
2
7
8
1
4
1
3
11
7
14
15
5
7
7
34
31
DURATION
.* NAT
.) (mts.)
(n»295)
4
20
62
1
15
7
5
35
50
108
119
35
82
85
303
507
S.E.
(mts.)
*
2
5
5
1
4
1
3
6
5
9
7
5
13
8
20
26
MEAN
CA
(rats.)
53
99
89
53
104
48
195
336
69
119
141
76
101
114
394
502
DOER
NAT
(mts.)
57
74
80
277
81
51
297
341
65
119
121
69
140
122
312
509
X DOER
CA
(X)
17
•6
71
3
15
7
3
9
59
82
87
46
55
43
98
100
NAT
(X)
7
28
78
0
19
13
2
10
77
91
99
50
58
70
97
100
9-11
-------
There are some patterns found nationally but not in California, and vice-versa. In
the national sample, family care microenvironments are high for the 65+ age
group, while in California they are below the average. The same pattern is found
for time spent outdoors not doing physical activities or in transit. And among 18-24
year-olds in California, time spent in sleep and in communication activities is well
above average, but that is not found in the national sample.
9-12
-------
10.0 SUMMARY AND CONCLUSIONS
There are some notable differences in the estimates from the national and
California data for the microenvironment codes created for this report. This is
mainly a result of differences in the location coding schemes used in the two studies.
Many of these gaps have been closed by receding of selected location codes in the
national study, but that exercise also produced some new differences. Most notably,
these receded data suggest that Californians spend most of their outdoor time in
away-from-home settings in contrast to the greater time spent in yards and outdoor
environments nearer the home in the national study. While that would be
consistent with an image of more cramped outdoor living environments in
California (or of more attractive outdoor environments away from home), this
result needs confirmation with independent data sources. Further similarities may
appear when a full receding of both the national and California data can be
undertaken. On the other hand, narrowing these gaps for some locations may be
all but impossible. For example, respondents in the national sample were never
asked to break out their work environments by indoor vs. outdoor, restaurant/bar
vs. school vs. factory vs. construction, and the like. The same is true for the specific
codes that were created for the CARB study to identify dry-cleaning establishments,
parking garages (autoplaces), and the like and which were never used nationally.
Such detailed location information, then, can only be obtained from a new data
collection, one that can take advantage of the many technological advances made
in the California study to produce a set of estimates more directly designed for the
needs of exposure assessment research and policy.
10-1
-------
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concepts, purpose, and overview of the Washington, D.C.—Denver, Colorado
field studies. Paper No. 121.1 presented at the 77th Annual Meeting of the Air
Pollution Control Association, San Francisco, California.
Akland, G. G., T. D. Hartwell, T. R. Johnson, and R. W. Whitmore. 1985. Measuring
human exposure to carbon monoxide hi Washington, D. C., and Denver,
Colorado, during the Winter of 1982-83. Environ. Sci. Techno. 19: 911-918.
Allen, C. 1968. Photographing the TV Audience. Journal of Advertising Research.
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Bechtel, R., C. Achepohl, and R. Akers. 1972. Correlations between observed
behavior and questionnaire responses in television viewing. In Television and
social behavior, reports, and papers. Volume 4: Television in a day-to- day life:
patterns and user, ed. E.A. Rubenstein, G.A. Comstock, and J.P. Murray.
Washington, D.C.: U.S. Government Printing Office.
Behar, J.V., J. Thomas, and M.D. Pandian. 1989. Development of the Benzene
Exposure Assessment Model (BEAM). Presented at the EPA/Air and Waste
Management Association International Symposium on Total Exposure
Assessment Methodology: New Horizons. Las Vegas, NV. A&WMA VIP-16.
DeGrazia, S. 1962. Of time, work, and leisure. New York: Twentieth Century Fund.
Duan, N. 1982. Models for Human Exposure to Air Pollution. Environment
International. 8: 305-309.
Gershuny, J. et al. 1986. Time budgets: Preliminary analyses of a national survey.
Quarterly Journal of Social Affairs (2).
Hartwell, T. D., A, C. Carlisle, R. M. Michie Jr., Whitmore, R. W., H. S. Zelon, and
D. A. Whitehurst. 1984. A study of carbon monoxide exposure of residents in
Washington, D. C., and Denver, Colorado. Research Triangle Park, North
R-l
-------
Carolina: Environmental Monitoring Systems Laboratory, U. S. EPA.
EPA-600/S4-84-031, PB 84-183516.
Harvey, A. and D. Elliot. 1983. Time and time again. Ottawa- Hull, Canada:
Employment and Immigration Commission.
Hill, D. 1985. Implications of home production and inventory adjustment processes
for time-of-day demand for electricity. In Time. Goods, and Weil-Being, ed.
F. T. Juster and F. P. Stafford. Ann Arbor, Michigan: Institute for Social
Research, University of Michigan.
Johnson, T. 1984. A study of personal exposure to carbon monoxide in Denver,
Colorado. Paper No. 121.3 presented at the 77th Annual Meeting of the Air
Pollution Control Association, San Francisco, California.
Johnson, T. 1986. A study of human activity patterns in Cincinnati. Ohio. Durham,
North Carolina: PEI Associates.
Johnson, T. and R. A. Paul. 1984. The NAAQS Exposure Model (NEM1 applied to
carbon monoxide. Research Triangle Park, NC: Office of Air Quality Planning
and Standards, U. S. EPA. NTIS PB84-24255L
Juster, F. T. 1985. The validity and quality of time use estimates obtained from recall
diaries. In Time. Goods, and Well-Being. ed. F. T. Juster and F. P. Stafford.
Ann Arbor, Michigan: Institute for Social Research, University of Michigan.
Michelson, W. 1978. Public policy in temporal perspective. The Hague, Netherlands:
Mouton.
Ott, W. R. 1984. Exposure estimates based on computer generated activity patterns.
Journal of Toxicology: Clinical Toxicologyr Special Symposium Issue on
Exposure Assessment: Problems apd Prospects. 21(1 and 2): 97-128.
Ott, W.R., J. Thomas, D. Mage, and L. Wallace. 1988. Validation of the Simulation
of Human Activity and Pollutant Exposure (SHAPE) model using paired days
R-2
-------
from the Denver, CO, carbon monoxide field study. Atmospheric
Environment. 22. 10,2101-2113.
Pellizzari, E.D., K. Perritt, T.D. Hartwell, L.C. Michael, R. Whitmore, R.W. Handy,
D. Smith, and H. Zelon. 1987a Total exposure assessment methodology
(TEAM) study: Elizabeth and Bayonne. New Jersey: Devil's Lake. North
Dakota: and Greensboro. North Carolina. Volume II. Washington D.C.: U.S.
EPA.
Pellizzari, E.D., K. Perritt, T.D. Hartwell, L.C. Michael, R. Whitmore, R.W. Handy,
D. Smith, H. and Zelon. 1987b Total exposure assessment methodology
(TEAM) study: Selected communities in Northern and Southern California^
Volume III. Washington, D.C.: U.S. EPA.
Robinson, J. P. 1977. How Americans use time: A social- psychological analysis of
everyday behavior. New York: Prager. (Further analyses were published in
How Americans used time in 1965-66. Ann Arbor, Michigan: University
Microfilms, Monograph Series.)
Robinson, J. P. 1985. The validity and reliability of diaries versus alternative time use
measure. In Time. Goods, and Welt- Being, ed. F. T. Juster and F. P. Stafford,
33-62. Ann Arbor, Michigan: Institute for Social Research, University of
Michigan.
Robinson, J. P., V. Andreyenkov, and Vasily Petruchev. 1988. The rhythm of
everyday life. Boulder, Colorado: Westview Press.
Robinson, J. P., and J. A. Wiley. 1989. Activity patterns of California Residents: Final
Report. ARB Contract No. A6-177-33. California Air Resources Board.
Berkeley, California: Survey Research Center, University of California.
Szalai, A. et al. 1972. The use of time. The Hague, Netherlands: Mouton Press.
Wallace, L.A. 1987. The total exposure assessment methodology (TEAM^ study:
Summary and analysis. Volume I. Washington D.C.: U. S. EPA.
R-3
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APPENDIX A:
ACTIVITY CODES FOR 1985 NATIONAL TIME DIARIES STUDY
** 2 asterisks next to an activity code indicates the code
is to be used in coding children's diaries only.
00: NO ACTIVITY
000 NO ACTIVITY REPORTED
WORK AND OTHER INCOME PRODUCING ACTIVITIES
CARB
01 Ql: WORK
01 Oil Main job: activities at the main job, travel which is part of the job,
and overtime; "working," "at work."
01 012 Work at home; work activities for pay done in the home when
home is the main workplace. (Include travel as Oil.)
i.e., Self-employed people running a business out of the home.
01 013 Additional work home; additional job (i.e., consulting, cottage
industry).
01 014 Work at home for no pay, work connected with main job.
01 015 Other work at home - general.
01 016 Reading (work brought home).
(formerly 944*)
02 Q2: UNEMPLOYMENT
02 022 Job search; looking for work, including visits to employment
agencies, phone calls to prospective employers, answering want
ads.
02 023 Unemployment benefits; applying for or collecting unemployment
compensation.
02 024 Welfare; food stamps; applying for or collecting welfare food
stamps.
A-l
-------
GARB
03 Q3_: TRAVEL DURING WORK
05 Q5_: SECOND JOB
05 059 Other paid work; second job; paid work activities which are not
part of the main job (use this code when R clearly indicates a
second job or "other" job); paid work for those not having main
job; garage sales, rental property.
(CHILD DEFINITION) Part-time jobs when R is full-time
student.
06 Ojg: EATING
06 068 Eating while working; smoking, drinking coffee as a secondary
activity while working (at work place).
06 069 Lunch at workplace; lunch eaten at work, cafeteria lunchroom
when "where" = work (lunch at a restaurant, code 449; lunch at
home, code 439).
07 Q7: ACTIVITIES AT WORK
07 078 Activities before or after work; activities at the workplace before
starting or after stopping work; include - "conversations," other
work. Do not code secondary activities with this primary activity.
07 079 Other work related.
08 QS: BREAKS
08 089 Coffee breaks and other breaks at the workplace; breaks during
non-work during work hours at the workplace; "took a break;"
"had coffee" (as a primary activity). Do not code secondary
activities with this primary activity.
A-2
-------
GARB
09 0_9_: TRAVEL RELATED TO WORK ACTIVITIES
09 097 Travel related to job search, unemployment benefits, welfare, food
stamp, waiting for related travel.
09 098 Interrupted travel to work; travel to and from workplace when R's
trips to and from work were both interrupted by stops; waiting for
related travel.
09 099 Travel to and from workplace, including time spent waiting for
transportation.
A-3
-------
HOUSEHOLD ACTIVITIES
GARB
10 1Q: FOOD
10 108 Meal preparation; cooking, fixing lunches.
10 109 Serving food, setting table, putting groceries away, unloading car
after grocery shopping.
11 li: CLEANUP
11 118 Doing dishes, rinsing dishes, loading dishwasher.
11 119 Meal cleanup, clearing table, unloading dishwasher.
12 12: CLEANING
12 128 Miscellaneous "work around house"; NA if indoor or outdoor.
12 129 Routine indoor cleaning and chores, picking up, dusting, making
beds, washing windows, vacuuming, "cleaning," "fall/spring
cleaning," "housework."
13 12.: OUTDOOR CLEANING
13 139 Routine outdoor cleaning and chores; yard work, raking leaves,
mowing grass, garbage removal, snow shoveling, putting on storm
windows, cleaning garage, cutting wood.
14 14: CLOTHES CARE
14 148 Washing clothes.
14 149 Other clothes care.
A-4
-------
GARB
if: REPAIRS
16 161 Indoor repairs, maintenance, fixing, furnace, plumbing, painting
a room.
16 162 Outdoor repairs; maintenance, exterior; fixing repairs outdoors,
painting the house, fixing the roof, repairing the driveway
(patching).
15 163 Routine car care; necessary repairs and routine care to cars; tune
up.
16 164 Home improvements; additions to and remodeling done to the
house garage; new roof.
16 165 Repairing appliances.
16 166 Repairing furniture.
16 167 Car maintenance; changed oil, changed tires, washed cars;
"worked on car" except when clearly as hobby~(code 832).
16 168 Improvements to grounds around house; repaved driveway.
17 17: PLANT CARE
17 171 Gardening; flower or vegetable gardening; spading, weeding,
composting, picking, "worked in garden."
17 173 Care of house plants
18 IS: PET CARE
18 188 Play with animals (formerly 844*).
18 189 Care of household pets.
19 12: OTHER HOUSEHOLD
19 191 Other indoor chores; NA whether cleaning or repair.
A-5
-------
GARB
19 192 Other outdoor chores; "worked outside," "puttering in garage."
97 193 Household paperwork; paying bills, balancing the check-book,
making lists, getting mail, working on the budget.
19 194** Watching another person do typically female household tasks
(108, 109, 118, 119, 148, 149).
19 195** \\ktching another person do typically male household tasks.
19 196** \\ktching another person do household tasks, not listed above.
19 197 Other household chores; (no travel), picking up things at home,
e.g., "picked up deposit slips" (related travel to purpose).
A-6
-------
CHILD CARE
GARB
20 2Q: BABY CARE
20 209 Baby care; care to children age 4 and under.
21 21: CHILD CARE
21 218 Child care; mixed ages or NA ages of children.
21 219 Care to children ages 5-17.
22 22: HELPING/TEACHING
22 221 Helping/teaching children learn, fix, make things; helping son
bake cookies; helping daughter fix bike.
22 222 Helping kids with homework or supervising homework.
23 22: TALKING/READING
23 236 Giving child orders or instructions; asking them to help; telling
them to behave.
23 237 Disciplining child; yelling at kids, spanking children.
23 238 Reading to child.
23 239 Conversations with household children only; listening to children.
24 21: INDOOR PLAYING
24 248** Playing with babies aged 0-2; "playing with baby," indoors or
outdoors.
24 249 Indoor playing with kids; other indoor activities with children
including games ("playing" unless obviously outdoor games).
A-7
-------
CARB
25 21: OUTDOOR PLAYING
25 258 Leading outdoor activities; coaching, non-organizational activities.
25 259 Outdoor playing with kids; including sports, walks, biking with,
other outdoor games.
26 26: MEDICAL CARE - CHILD
26 269 Medical care at home or outside home; activities associated with
children's health; "took son to doctor," "gave daughter medicine."
27 22: OTHER CHILD CARE
27 277 Coordinating child's social or instructional non-school activities
(travel related code 298).
27 278 Babysitting (unpaid) or child care outside R's home or to children
not residing in HH.
27 279 Other child care, including phone conversations relating to child
care other than medical.
29 22: TRAVEL RELATED TO CHILD CARE
29 298 Travel related to non-school activities.
29 299 Other travel related to child care.
A-8
-------
OBTAINING GOODS AND SERVICES
CARS
2Q: EVERYDAY SHOPPING
30 301 Shopping for food.
31 302 Other shopping; including for clothing, small appliances; at drug
stores, hardware stores, department stores, "downtown" or
"uptown," shopping center, buying gas, window shopping.
31 3JL: DURABLE/HOUSE SHOP
31 311 Shopping for durable goods; shopping for large appliances, cars,
furniture.
31 312 Shopping for house or apartment; activities connected by buying,
selling, renting, looking for house, apartment, including phone
calls; showing house, including traveling around looking at real
estate property (for own use).
22: PERSONAL CARE SERVICES
32 320 Phone calling for goods.
32 321 Phone calling for services.
32 329 Personal care services; beauty, barber shop; hairdressers.
28 At dry cleaners.
33 22: MEDICAL APPOINTMENTS
33 339 Medical care for self.
34 24: GOVT/FINANCIAL SERVICES
34 341 Financial services; activities related to taking care of financial
business; going to the bank, paying utility bills (not by mail),
going to accountant, tax office, loan agency, insurance office.
A-9
-------
GARB
34 342 Other government services; post office, driver's license, sporting
licenses, marriage licenses, police station.
25_: REPAIR SERVICES
35 351 Auto services; repair and other auto services including waiting for
such services.
36 352 Clothes repair and cleaning; cleaners, laundromat, tailor.
36 353 Appliance repair; including furnace, water heater, electric or
batten' operated appliances; including watching repair person.
36 354 Household repair services; including furniture; other repair
services NA type; including watching repair person.
55 26: LIBRARY
55 360 Time spent at library.
55 361 Travel to/from library.
55 369** Getting gifts or money from adult, e.g., got lunch money.
37 3J7: OTHER SERVICES
37 377 Other professional services; lawyer, counseling (therapy).
37 379 Other services; "going to the dump."
38 2S: ERRANDS
38 389 Running errands; NA whether for goods or services; borrowing
goods.
39 29_: TRAVEL RELATED TO GOODS AND SERVICES
39 399 Travel related to obtaining goods.
A-10
-------
PERSONAL NEEDS AND CARE
GARB
4Q: WASHING/DRESSING
40 408 Bathing; washing, showering.
47,40 409 Personal hygiene; getting dressed, packing and unpacking clothes,
going to the bathroom.
41 41: MEDICAL CARE
41 411 Medical care at home to self.
41 412 Medical care to adults in HH.
42 42: HELP AND CARE
42 421 Non-medical care to adults in HH; routine non-medical care to
adults in household; "got my wife up," "ran a bath for my
husband."
42 422 Help to relatives not in HH; helping caring for, providing for
needs of relatives; (except travel) helping move, bringing food,
assisting in emergencies, doing housework for relatives; visiting
when sick.
42 423 Help to neighbors, friends.
42 423 Help to others, NA relationship to R; (same as 422 for others).
43 42: MEALS AT HOME
43 439 Meals at home; including coffee, drinking, smoking, food from a
restaurant eaten at home, "breakfast," "lunch."
44 44: MEALS OUT
44 448 Meals at friend's home; eaten at a friend's home (inc. coffee,
drinking, smoking).
A-ll
-------
GARB
44 449 Meals at restaurants.
45 45_: NIGHT SLEEP
45 458 Longest sleep of the day; including in bed but not asleep (formerly
459*).
45 459 Beginning of longest sleep of next night, night sleep (formerly
460*).
46 4£: NAPS/SLEEP
46 469 Naps and resting.
48 4g: N.A. ACTIVITIES
48 481 Time gap of more than 10-minutes.
48 482 Personal/private; "none of your business."
48 483 Sex, making out.
48 484 Affection between household members: giving and getting hugs,
kisses, sitting on laps.
48 485 Interview/questionnaire; completing time diaries (formerly 978*).
48 487** At babysitters before and after school or if child does not attend
school. (NOTE: all secondary activities should be coded when
this is a primary activity.)
48 488** Receiving child care; child is passive recipient of personal care;
e.g., "Mom braided my hair."
48 489 Other personal care activities; watching personal care activities.
A-12
-------
GARB
49 42: TRAVEL RELATED TO PERSONAL CARE
49 498 Travel related to helping, related to codes 421, 422, 423, 424,
including travel which is the helping activity; waiting for related
travel.
49 499 Other personal travel.
A-13
-------
EDUCATION AND PROFESSIONAL TRAINING
CARS
50 5Q: STUDENTS' CLASSES
50 500 Television-based education.
50 509 Student attending classes full-time; includes daycare, nursery
school for children not in school.
51 5_L: OTHER CLASSES
51 519 Other classes, courses, lectures, academic or professional; R not a
full time student or NA whether a student; being tutored.
54 54: HOMEWORK
54 548 Reading (class related) (formerly 945*).
54 549 Homework, studying, research.
56 5f: OTHER EDUCATION
56 568** At day care/nursery before or after school only (NOTE: all
secondary activities should be coded when this is a primary
activity).
56 569 Other education.
59 52: TRAVEL RELATED TO EDUCATION
59 597** Travel directly from home to school.
59 598** Travel directly from school to home.
(NOTE: 597 and 598 are child codes only.)
59 599 Other school-related travel; waited for related travel; travel to
school not originating from home.
A-14
-------
ORGANIZATIONAL ACTIVITIES
60 £Q: PROFESSIONAL/UNION ORGANIZATIONS
60 601 Meetings of professional/union groups.
60 602 Other activities, professional/union group including social
activities and meals.
61 £1: SPECIAL INTEREST IDENTITY ORGANIZATIONS
Includes groups based on sex, race national origin; NOW,
NAACP, Polish-American Society, neighborhood, block
organizations, CR groups, senior citizens, Weight Watchers, etc.
61 611 Meetings of identity organization.
61 612 Other activities, identity organizations and special interest
groups, including social activities and meals.
62 62: POLITICAL PARTY AND CIVIC PARTICIPATION
62 621 Meetings political/citizen organizations; including city council.
62 622 Other activities, political/citizen organizations, including social
activities, voting, jury duty, helping with election, and meals.
63 6_3_: VOLUNTEER/HELPING ORGANIZATIONS
Hospital volunteer group, United Fund, Red Cross, Big
Brother/Sister.
63 631 Attending meetings of volunteer, helping organizations.
63 632 Officer work; work as an officer or volunteer, helping
organizations, R must indicate he/she is an officer to be coded here.
63 633 Fund raising activities as a member of volunteer helping
organization, collecting, money planning a collection drive.
63 634 Direct voluntary help as a member of volunteer group; visiting,
bringing food, driving.
A-15
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GARB
63 635 Other volunteer activities, including social events and meals.
64 £4: RELIGIOUS PRACTICE
64 641 Meetings of religious helping groups; ladies aid circle, missionary
society, Knights of Columbus.
64 642 Other activities of religious helping groups listed in 641 including
social activities and meals.
64 643 Meetings, other church groups; attending meetings of church
groups which are not primarily helping oriented or NA if helping
oriented.
64 644 Other activities, other church groups; other activities as a
member of church groups which are not helping oriented or NA if
helping, including social activities and meals; choir practice; bible
class.
65 £5_: RELIGIOUS PRACTICE
65 651 Attending services of a church or synagogue, including
participating in the service; ushering, singing in choir, leading
youth group, going to church, funerals.
65 652 Individual practice, or religious practice carried out in a small
group; praying, meditating, Bible study group (not at church),
visiting graves.
66 6£: FRATERNAL ORGANIZATIONS
Moose, VFW, Kiwanis, Lions, Civitan, Chamber of Commerce,
Shriners, American Legion.
66 661 Meetings fraternal organizations.
66 662 Other activities as a member of a fraternal organization including
social activities and helping activities and meals.
A-16
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GARB
67 SI: CHILD/YOUTH/FAMILY ORGANIZATIONS
67 671 Meetings, family/youth/child organizations.
67 672 Other activities as a member of child/youth/family organizations
including social activities and meals.
68 6_8_: OTHER ORGANIZATIONS
68 688** Meetings practices for team sports (formerly 883* and 884*).
68 689 Other organizations; any activities as a member of an
organization not fitting into above categories; (meetings and other
activities included here).
69 £9_: TRAVEL RELATED TO ORGANIZATIONAL ACTIVITY
69 698 Travel related to organizational activities as a member of a
volunteer organization; including travel which is the helping
activity, waiting for related travel.
69 699 Travel related to all other organizational activities; waiting for
related travel.
A-17
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ENTERTAINMENT/SOCIAL ACTIVITIES
GARB
70 7Q: SPORT EVENTS
70 708 Watch other people do active leisure activities (formerly 882*).
70 709 Attending sports events.
71 71: MISCELLANEOUS EVENTS
71 719 Miscellaneous spectacles, events; circus, fairs, rock concerts,
accidents.
72 72: MOVIES
72 729 Attending movies; "went to the show."
73 73_: THEATER
73 739 Theater, opera, concert, ballet.
74 74: MUSEUMS
74 749 Attending museums, zoos, art galleries, exhibitions.
75 75_: VISITING
75 752 Visiting with others; socializing with people other than R's own
HH members either at R's home or another home (visiting on the
phone, code 965); talking/chatting in the context of receiving a
visit or paying a visit.
76 7£: PARTIES
76 768 Picnicking (*new code).
76 769 Party, reception, wedding.
A-18
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GARB
77: BARS/LOUNGES
77 771 At bar, cocktail lounge, nightclub; socializing or hoping to
socialize at bar, lounge.
86 772 Dancing.
78 78_: CITHER EVENTS
78 789 Other events, of socializing that do not fit above.
79 72: TRAVEL RELATED TO EVENTS/SOCIAL ACTIVITIES
79 799 Related travel; waiting for related travel.
A-19
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SPORTS AND ACTIVE LEISURE
GARB
80 SQ: ACTIVE SPORTS
80 800 Lessons in sports (formerly 885*); swimming, golf, tennis,
skating, roller skating (codes 801-807, 811-817, 821-826).
80 801 Football, basketball, baseball, volleyball, hockey, soccer, field
hockey.
80
80
80
80
80
80
80
80
81
81
81
81
81
81
81
81
802
803
804
805
806
807
808
809
SI:
811
812
813
814
815
816
817
Tennis, squash, racquetball, paddleball.
Golf, miniature golf.
Swimming, waterskiing.
Skiing, ice skating, sledding, roller skating.
Bowling, pool, ping-pong, pinball.
Frisbee, catch
Exercises, yoga, weightlifting
Judo, boxing, wrestling.
OUTDOORS
Hunting.
Fishing.
Boating, sailing, canoeing.
Camping, at the beach.
Snowmobiling, dune-buggies.
Gliding, ballooning, flying.
Excursions, pleasure drives (no destination), rides with the family.
A-20
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GARB
82 82: WALKING/BIKING
82 821 Walking for pleasure.
82 822 Hiking.
82 823 Jogging, running.
82 824 Bicycling
82 825 Motorcycling.
82 826 Horseback riding.
83 33_: HOBBIES
83 831 Photography
83 832 Working on cars—not necessarily to their running; customizing,
painting.
83 833 Working on leisure time equipment repair (repairing the boat,
"sorting out fishing tackle").
83 834 Collections, scrapbooks
83 835 Carpentry, woodworking
83 836 Making movies (formerly 925*).
84 34: DOMESTIC CRAFTS
84 841 Preserving foodstuffs (cleaning, pickling).
84 842 Knitting, needle-work, weaving, crocheting (including classes),
crewel, embroidery, quilting, quilling, macrame.
84 843 Sewing.
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GARB
8_5_: ART/LITERATURE
85 851 Sculpture, painting, potting, drawing.
86 852 Literature, poetry, writing (not letters), writing a diary.
86 8_£: MUSIC/DRAMA/DANCE
86 860 Other lessons; (formerly 888*).
(931-835, 841-844, 851-852, 871-888)
86 861 Playing a musical instrument, (include practicing), whistling.
86 862 Singing.
86 863 Acting (rehearsal for play).
86 864 Non-social dancing; ballet, modern dance, body movement.
86 865 Gymnastics.
86 866 Pretend, dress-up.
86 867 Lessons in music, dance, gym, judo, singing, body movement
(formerly 886* and 887*).
(808-809, 864-865, 861-863)
86 869 Other active leisure; "hanging around" (formerly 889*).
87 SI" GAMES
87 871 Playing card games (bridge, poker)
87 872 Playing board games (Monopoly, Yahtzee, Bingo, dominoes,
Trivial Pursuit).
87 873 Playing social games (scavenger hunts), "played games"—NA kind.
87 874 Puzzles.
87 875 Played with toys.
A-22
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GARB
87 876 Played outdoors.
87 877 Played indoors.
88 8£: COMPUTER USE
88 884 Using computer - general (formerly 894*).
88 885 Computer use for education (formerly 895*).
88 886 Computer games - child (formerly 896*).
88 887 Computer games - adult (formerly 897*).
88 888 Other computer use (formerly 898*).
88 889 Other active leisure.
89 S2: TRAVEL RELATED TO ACTIVE LEISURE
89 899 Related travel.
A-23
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PASSIVE LEISURE
GARB
90 2Q_: RADIO USE
90 900 Radio transmitting/CB radio (formerly 910*).
90 909 Radio use.
91 9_1: TV USE
91 914 VCR/Home Movies (formerly 920*).
91 918 Cable TV.
91 919 TV viewing.
92 22: RECORDS/TAPES
92 926 Recording music (formerly 930*).
92 927 Records
92 928 Tapes
92 929 Records, tapes, stereo, listening to music, listening to others
playing a musical instrument.
93 22: READ BOOKS
93 939 Reading books for pleasure.
94 24: READING MAGAZINES/NA
94 941 Reading magazines, reviews, pamphlets.
94 942 Reading NA what; or other.
94 943** Being read to.
A-24
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GARB
95 25: READING NEWSPAPER
95 959 Reading newspaper (formerly 949*).
96 26: CONVERSATIONS
96 960** Receiving instructions (formerly 967*).
96 961 Being disciplined (formerly 966*).
96 962 Other talking/arguing with non-HH members (formerly 962* &
964*).
96 963 Conversations/arguing with HH members (formerly 965* &
963*).
96 964 Local calls placed (formerly 957*).
96 965 Local calls received (formerly 958*).
96 966 Long distance calls placed (formerly 959*).
96 967 Long distance call received (formerly 960*).
96 968 Telephone use for organizational activities.
96 969 Other phone conversations (formerly 961*).
97 27: LETTERS
97 977 Typing (formerly 980*).
97 979 Letters, (reading or writing) reading mail.
98 2S: OTHER PASSIVE LEISURE
98 981 Relaxing.
98 982 Thinking, planning, reflecting.
98 983 Doing nothing.
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GARB
98 984 Activities of others reported.
98 989 Other passive leisure; smoking dope, pestering, teasing, joking
around, messing around, laughing.
99 9_9_: TRAVEL RELATED TO PASSIVE LEISURE
99 997** waiting in car for adult
99 993 ** Travel of cniid with adult when not clear whether child participated
in adult's purpose of trip, e.g., went to bank (with parent) and
waited in car; code travel portion 998.
99 999 Related travel; waiting for related travel.
A-26
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Appendix B: Original Location Codes for National 1985 Mail-Back Study
HOME
00 Respondent's home, rad-general
01 Basement/cellar
02 Bathroom
03 Bedroom
04 Dining room
05 Computer room
06 Den
07 Family room/front room/living room
08 Gameroom/recreation room
09 Garage
10 Kitchen
11 Laundry/utility room
12 Office
13 Porch
14 Hall
19 Other home
A WAY FROM HOME
20 Transit(NA mode)
21 Car transit
22 Other Transit
30 Work
40 Friend's/relative's home
50 Restaurant/bar/fast food
60 Indoor place of leisure
70 Outdoor place of leisure
80 School
81 Church
82 Stores, etc.
83 Banks, office, library
89 Other
99 Na/ref
B-l
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