AIR POLLUTION, AIRWAYS HYPERREACTIVITY, AND PULMONARY FUNCTION MEASUREMENTS IN ASTHMA by Sheldon L. Spector and Robert A. Kinsman Melissa Dunning James Murphy Richard Jones James P. Lodge Helen Rose National Jewish Hospital and Research Center Denver, Colorado 80206 Environmental Protection Agency Contract No. 68-02-2517 Project Officer Charles Stevens Office of Air Programs Environmental Protection Agency Denver, Colorado National Jewish Hospital and Research Center 3800 East Colfax Avenue Denver, Colorado 80206 ------- DISCLAIMER This report has been reviewed by the G'FFlCB OF f{[R PRO(S^/4/^lS , U. S. Environmental Protection Agency, and approved for publication. Approval does not signify that the contents necessarily reflect the views and policies of the U. S. Environmental Protection Agency, nor does mention of trade names or commercial products constitute endorsement or recommendation for use. ------- ACKNOWLEDGEMENT We gratefully acknowledge the statistical assistance of Helen Rose, and the assistance of Sharon Robinson and Jolene Fukuhara during various aspects of the study. Carolyn Wangaard and Cynthia Westmoreland dedicated consider- able time assembling large amounts of medical information for the patients studied. The Colorado Department of Health Air Pollution Surveillance Section cooperated consistently throughout this project, providing technical advice and all daily air pollution data for the study. We particularly appreciate the cooperation of Mr. Robert D. Siek, Assistant Director for Environmental Affairs, and Dave Rose and Steve Arnold, Senior Air Pollution Specialists from that office. Indoor-outdoor air pollution monitoring was provided by Pedco Environ- mental Specialists, Inc. of Cincinnati, Ohio working under EPA contract No. 68-02-2294. Larry Elfers of Pedco supervised this work and S. David Shearer, Director of the Environmental Monitoring and Support Laboratory of EPA faci- litated cooperation between these projects. Finally, the Department of Biometrics of the University of Colorado Medical Center, headed by Dr. Strother Walker, provided invaluable statistical expertise for the analyses of the data. ii ------- CONTENTS Page Disclaimer i Acknowledgement ii List of Tables iv 1. Abstract 1 2. Introduction 2 3. Methods 3 3.1 Periods of Study 3 3.2 Patient Characteristics 4 3.3 Measures 4 3.3.1 Air Pollution and Meterologic Variables 4 3.3.2 Pulmonary Function Measurements 5 3.3.3 Indices of Airways Hyperreactivity 6 3.4 Statistical Analyses 7 4. Results 8 4.1 Air Pollution and Meterologic Variables 8 4.2 Pulmonary Function Measruements 12 4.3 Pulmonary Function Measurements and Air Pollution/Meterologic Variables 15 4.3.1 Univariate Regression Analyses IS 4.3.2 Multivariate Regression Analyses 16 5. Discussion 26 6. Recommendations 30 7. References 31 iii ------- LIST OF TABLES Page 4.1 Means and Standard Deviations for All Air Pollution and Metero- logic Variables by Month for the Summer (A) and Winter (B) Periods ........ 9 4.2 Frequency Distributions of Air Pollution and Meterologic Variables for Summer and Winter Periods 10 4.3 Intercorrelations Among Air Pollution and Meterologic Variables for the Summer (A) and Winter (B) Periods 11 4.4 Frequency Distributions of Mean Pulmonary Function Measurements for Patients During Summer and Winter Periods . 12 4.5 Means and Standard Deviations of the Correlations Among Pulmonary Function Measurements for the Summer and Winter Periods 13 4.6 Frequency Distributions of Correlations Between Pulmonary Function Measurements and Day of Study for Summer and Winter Periods .... 14 4.7 Univariate Regression Analyses Summary Table for Individual Regressions 15 4.8 Variables Included in the Leaps and Bounds Multiple Linear Regres- sion Analyses 17 4.9 Summary Table for Leaps and Bounds Multiple Linear Regression Analyses for Individual Patients 18 4.10 Leaps and Bounds Multiple Linear Regression Analyses Summary Table for Summer Period Summarizing Best Regressions for Airways Hyper- reactivity Groups . 20 4.11 Leaps and Bounds Multiple Linear Regression Analyses Summary Table for Winter Period Summarizing Best Regressions for Airways Hyper- reactivity Groups 23 iv ------- 1. ABSTRACT This study evaluated the relationship between spirometric pulmonary func- tion measures (FEVj, FEVjyFVC%, and PEFR) and air pollution and meterologic variables (CO, SO2, total hydrocarbons, O3, coefficient of haze, minimum temperature, and barometric pressure)for adult asthmatic inpatients in an urban, long-term intensive treatment center. Two groups of 67 patients were studied during a late spring-summer (May 1 through August 12, 1975) and a late fall-winter (November IS, 1975 through March 31, 1975) period. Patients were classified according to the role of allergic factors and the degree of airways hyperreactivity. In all analyses, 24-hour average levels of air pollution preceding pul- monary function measurement were related to subsequent 8:00 am pulmonary func- tions. Multiple linear regression analyses by leaps and bounds for individuals and groups, defined by reaginic factors and airways hyperreactivity, failed to identify a systematic effect for any air pollution variable upon any pul- monary function measure. The lack of any relationship does not appear attri- butable to limited exposure to air pollution variables, but may be affected by as-needed (PRN) medication usage, type of pulmonary function measurement employed, and periods selected for analyses. The relative strengths and limitations of the study are discussed. This report was submitted in fulfillment of Contract No. 68-02-2517 by National Jewish Hospital and Research Center under the sponsorship of the U.S. Environmental Protection Agency. This report describes work completed during the contract period September 1, 1976 to March 1, 1977. 1 ------- 2. INTRODUCTION Air pollution has often been implicated in aggravating respiratory ill- ness, but its effect upon asthmatic patients may be particularly significant due to the hyperreactivity of their airways. Airways hyperreactivity has been regarded as among the definitive features of asthma, predisposing these patients to react to a wide range of known irritants with increased airway obstruction.1,2 Histamine and methacholine inhalation challenges enable dif- ferentiation of asthmatics from patients who wheeze due to other causes, and permit classification of patients according to the degree of airways hyper- reactivity.3"5 The degree of airways hyperreactivity has been related to exercise-induced asthma,amount of oral corticosteroids prescribed at dis- charge from long-term treatment,4 and the response to bronchoconstrictive suggestion.® Likewise, those patients with the most hyperreactive airways may be affected most by irritant air pollution variables (e.g., SO2 and O3). There is a considerable literature on the effects of air pollution upon respiratory illness. Many early studies have been epidemiologic, enumerating clinic and hospital visits and morbidity during periods of significant urban air pollution. ~12 These epidemiological studies have often made retrospective determinations of the incidence of respiratory illness and lack precise infor- mation about the types of patients affected, but they have generally agreed that increased clinic and hospital visits and morbidity are associated with episodes of heightened urban air pollution.9"12 In contrast, Greenberg, et al. found no increase in difficulties among asthmatics (as indexed by clinic and hospital visits and morbidity) in New York City for a high pollution period in the fall of 1952 during which the observed increase in air pollution levels could not be related to pollens, SO2, COH, or CO.13 Such negative findings may sometimes result from the mode of analyses. For example, Ribon, Glasser, and Sudhivoraseth14 observed no increase in medical visits and morbidity during a period of high air pollution in New York City. However, they related clinic and office visits to air pollution levels on the same day and thereby may have failed to allow for the delay in symptom appearance and the subsequent decision or need to seek treatment. Lawther and Waller13,^ have noted that the physio- logical response to air pollution may lag, exacerbating bronchitis only after a period of relatively prolonged exposure to high levels of urban smog. Increased medical visits have also been associated with periods of low temperatures or decreases in temperature.1?-1® Laboratory studies with asth- matic patients have suggested that inhalation of cold air, and not mere cold exposure, results in increased airway resistance.2® Additionally, Salvaggio and his colleagues have suggested that seasonal factors, such as low tempera- tures and airborne pollens, may lead to increased asthma attack rates in New Orleans, an effect easily misattributable to increased levels of air pollutants. 1 2 ------- More recently, prospective studies in Salt Lake City and New York City have measured the effect of specific pollutants (notably SO2, particulates, and sus- pended sulfates) on the reports of asthma attacks within preselected groups of asthmatic patients,22, 23 in these studies, increased asthma attack rates were associated with cooler temperatures, increased suspended particulates, and sul- fates. Surprisingly, cooler temperatures did not increase the impact of air pollution levels in either study, but instead the effect of sulfates and par- ticulates were more pronounced on warmer than cooler days. Since both air pollutants and temperature appear to affect asthma attacks, this apparent paradox may be due to decreased outdoor exposure on cold days. For both studies, SO2 levels were not clearly related to attack rates. However, when a major plant producing SO2 in Salt Lake City was closed during a strike, SO2 levels decreased abruptly and were accompanied by a pronounced decrease in the asthma attack rates.22 These observations agree with those of others that SO2 appears to contribute to bronchoconstriction among individuals with hyperreac- tive airways.24, 25 Systematic studies such as these have produced the clearest findings about asthmatic symptoms and air pollution. However, neither study controlled for the seasonal effect of airborne pollens, which alone could exacerbate symptoms for patients with an allergic Ci*e•j reaginic) component to their asthma,21* -5 Furthermore, objective pulmonary functions have not yet been related to air pollutants for a well-defined group of asthmatics with documented airways hyperreactivity. The need for objective measurement is emphasized by studies of subjective symptomatology in asthma,26, 27 which document the variety of ways asthmatic patients report their distress. As a preliminary project, this proposed study attempted to contribute use- ful information by Q-) using a well-defined asthmatic population, C2) classi- fying patients according to the role of reaginic factors and airways hyper- reactivity, C3) considering the effect of temperature and barometric pressure in all analyses, (4) using daily spirometric pulmonary functions as objective measures of airway obstruction, and C5) minimizing the influence of airborne pollens by studying separately nonallergic asthmatics as determined by skin testing and antigen inhalation challenges.^-5 3. METHODS 3.1 PERIODS OF STUDY Asthmatic inpatients were studied throughout two periods, May 1 through August 12, 197S (spring-summer) and November 15, 1975 through March 31, 1976 Cfall-winter). For both periods, daily 8:00 a.m. spirometric pulmonary tions and medications were available for all patients throughout treatment. 8 These periods were selected to maximize the range and variability of air pollution and meteTologic variables. The principal variable of interest dur- ing the late spring-summer period was ozone (O3), which achieves its maximum levels during summer.29 Levels of all other air pollutants are highest during the late fall-winter period, while lower temperatures also occur dur- ing this period. During both periods, 67 patients were in residence at the hospital for continuous periods of not less than two weeks. In addition, 3 ------- these patients included only those without significant gaps in their pulmonary function data. 3.2 PATIENT CHARACTERISTICS The patients were well-defined groups of 67 asthmatics for both the summer and winter periods admitted to the intensive long-term treatment program at National Jewish Hospital and Research Center (NJHRC) in Denver, Colorado. Patients within periods were comparable with respect to age (mean +SD; 36 +_ 16 and 40 16, for summer and winter respectively) and sex (46 females and 48 females). Reaginic factors, identified by skin testing and antigen inhala- tion challenges, were determined to be involved in the asthma of 37 patients for the summer and 26 patients for the winter period.5,30 Tests for airways hyperreactivity were available for all patients during the summer and 60 patients during the winter period. Of these, with the exception of 4 patients during summer and 3 during winter, all had hyperreactive airways as deter- mined by methacholine and histamine inhalation challenges.3-5 Experience with these patients has indicated that nearly all (86%) could be expected to have asthma exacerbated by infection.31 Skin testing and/or antigen inhalation challenges were available for 62 patients during the summer and 63 patients during the winter period. Since only patients with asthma mediated by allergic (i.e., reaginic) factors should be affected by increased airborne allergens, all analyses were performed with- in groups of patients classified according to the role of reaginic factors in their asthma. Specifically, patients were categorized into three groups: (A) reaginic asthma, as determined by skin testing and antigen inhalation challenges (summer: 14 patients, winter: 3 patients); (B) possibly reaginic asthma, as determined by skin test results alone (summer: 23 patients; winter: 23 patients); and (C) not reaginic asthma (summer: 25 patients, winter: 37 patients). Testing was unavailable for 5 patients during summer and 4 patients during the winter period; these patients were treated separately in all sub- sequent analyses. 3.3 MEASURES 3-3.1 Air Pollution and Meterologic Variables All air pollution variables were monitored at the Colorado Department of Health Air Pollution Surveillance Substation located on the hospital grounds. This substation was approximately 100 yards from the Andrew Goodman Building where the adult asthmatic patients resided during treatment. Two weather variables were also available on a daily basis: 8:00 am barometric pressure, obtained from the NJHRC Pulmonary Function Laboratory and temperature (daily average and minimum) obtained from two substations, Overland Park Golf Course and Welby, approximately two miles southwest and northwest of NJHRC, respec- tively. Therefore, average values from both substations were used. In summary, the air pollution and meterologic variables studied were: 4 ------- Measure Source Units 1. Coefficient of haze (COH) NJHRC Substation 2. Carbon Monoxide (CO) NJHRC Substation 3. Sulfur Dioxide (SO2) NJHRC Substation 4. Total Hydrocarbons (THC) NJHRC Substation 5. Ozone (O3) NJHRC Substation 6. Minimum Temperature Welby + Overland 7. Barometric Pressure (BP) NJHRC (8:00 am) COHs/lOOO feet parts per million (ppm) parts per million (ppm) parts per million (ppm) parts per million (ppm) degrees Celsius (C°) mm of mercury (mmHg) For coefficient of haze (COH), measurements were taken every two hours. For all other air pollution variables, hourly measurements were available. An initial step in data preparation involved calculating the mean level of the air pollution variables for the 24-hour period preceding 8:00 am pulmonary func- tion measurement. Fot temperature, the average and minimum values (Tmin) for the same 24-hour period were used. The objective was to capture any cumulative effect of air pollution for the 24-hour period immediately pre- ceding pulmonary function measurement. 3.3.2 Pulmonary Function Measurements For all patients, spirometric pulmonary function measurements (Vertek 5000 VF Lung Function Analyzer; Hewlett-Packard, Boston, Mass.; calibrated biweekly with a 1.5 liter syringe) were obtained twice daily (8:00 am and 4:00 pm) throughout treatment. These measurements, which provide objective indices of airway obstruction, include Forced Vital Capacity (FVC), measuring the volume of air (liters) expired forcefully following a full inspiration; First Second Forced Expiratory Volume (FEVj), measuring the volume of air (liters) expired during the first second of FVC; and Peak Expiratory Flow Rate (PEFR), measuring the maximum flow rate (liters/sec) attained during FVC. Of these, FEV^ and PEFR are used as indices of airway obstruction. As an additional index, FEVj was expressed as a percentage of FVC (FEVi/FVC%). Normal values of FEV^/FVC% are generally between 75% to 85%, indicating that this percentage of FVC is expired during the first second. As airways obstruction increases, the decrease in the diameter of the airways serves to reduce FEV]/FVC%, while FVC may remain unaffected. All pulmonary function measurements, summarized below, were based on at least two reprodu- cible determinations to insure stable and reliable measures for each occasion: Measure 1. First Second Forced Expiratory Volume (FEV^) 2. FEVj as a percentage of Forced Expiratory Volume (FVC) (FEVx/FVC%) 3. Peak Expiratory Flow Rate (PEFR) Units Liters Percent Liters/Second On a daily basis, all measurements are verified and added to the computer files of the Clinical Data Management System (CDMS) and subsequently available for retrieval. 5 ------- 3.3.3 Indices of Airways Hyperreactivity Airways hyperreactivity was indexed by histamine and methacholine in- halation challenges, performed following the recommendation of the National Institute of Allergy and Infectious Disease panel on Standardization of Bronchial Inhalation Challenge Procedures.^ Patients were asymptomatic at the time of the methacholine challenges as indicated by baseline FEV^s of 80% or greater of the highest previously ob- served value. Three minutes following inhalation of 5 breaths of diluent, delivered by a Bell and Gossett Compressor (Model LCHB, Morton Grove, 111.) adjusted to a flow rate of 6 liters per minute using a Vaponefrin nebulizer (Fisons, New Bedford, Mass.), studies were repeated. This diluent value served as a control, and testing proceeded if FEVi was not reduced by 10% or more. Diluent was a sterile aqueous solution (pH - 7.0) of 0.036% potassium phosphate, 0.107% sodium phosphate, 0.40% phenol, and 0.50% sodium chloride obtained from Greer Laboratories, Lenoir, N.C. Pulmonary functions were per- formed with a Medistor spirometer (Simlog Instruments, Redmond, Washington) calibrated with a 1.5 liter syringe. For the methacholine challenge, 5 breaths of serial dilutions of metha- choline were given following the diluent measure. Spirometric measures were made 3 minutes thereafter. A positive test was a greater than 20% reduction in the 3-minute reading from the diluent value. If the test was negative, 5 breaths of the next dilution was given. Eight dilution increments were used: 0.15, 0.31, 0.62, 1.25, 2.5, 5.0, 10.0, and 25.0 mg/ml. The end point was that methacholine concentration producing at least a 20% decrease in FEVi from diluent control. For histamine, 5 breaths of serial dilutions followed the diluent mea- sure. Spirometry was performed 3 minutes thereafter. A positive test was a 3-minute decrease in FEV^ of 20% or greater from the diluent value. If the test was negative, 5 breaths of the next dilution were given. Eight dilution increments were used: 0.06, 0.12, 0.25, 0.50, 1.0, 2.5, 5.0, and 10.0 mg/ml. The end point was that histamine concentration producing at least a 20% de- crease in FEVi from diluent control. Methacholine inhalation challenges were available for all patients during the summer period and 64 patients during the winter period. Using categories established previously, 32 patients were classified during summer as having low thresholds CO•IS and 0.31 mg/ml), 27 moderate thresholds CO.62, 1.25, and 2.5 mg/ml), and 17 as high thresholds C5.0, 10.0, and 25.0 mg/ml), with 4 patients having a negative methacholine challenge. During winter, 25 patients were classified as having low thresholds, 27 moderate, and 7 as high thresholds, with 5 patients having a negative methacholine challenge. Histamine inhalation challenges were available for 66 patients during the summer period and 60 patients during the winter period. During the summer period, 18 patients had low thresholds (0.06 and 0.12 mg/ml), 27 had moderate thresholds (0.25, 0.50, and 1.0 mg/ml) and 17 had high thresholds (2.5, 5.0, 6 ------- and 10.0 mg/ml), with 4 patients having a negative histamine challenge. Dur- ing the winter period, 9 patients were classified as low, 30 as moderate, and 16 as high thresholds with 5 patients having a negative histamine challenge. A final classification was based on the lowest threshold category of both methacholine and histamine inhalation challenges. For this classification, 66 patients had complete testing during the summer period and 58 patients during the winter period. During summer, 36 patients were classified within low, 23 within moderate, and 4 within high threshold categories, with 4 having negative challenges. During winter, 26 patients were classified within low, 24 within moderate, and 5 within high threshold categories, with 3 patients having negative challenges. 3.4 STATISTICAL ANALYSES Separate analyses were performed for patients within both the summer and winter periods. (A) Univariate regression and correlational analyses were performed for each individual within the summer and winter periods, relating each 24 hour air pollution and meterologic variable to the follow- ing 8:00 am pulmonary function measurements. (B) The pattern of significant univariate regressions for individuals was then examined within groups defined by reaginic factors and airways hyperreactivity as indexed by methacholine and histamine challenges. (C) Multivariate regression analyses using all 7 air pollution and meterologic variables and four concommittant variables (intra- veneous bronchodilators given at the time of pulmonary function measurement, bronchodilators taken within 2 hours prior to pul- monary function measurement, bronchodilator treatments taken within one hour prior to pulmonary function measurement, and the previous day's 8:00 am pulmonary function) were performed next for all individuals within the summer and winter periods using leaps and bounds multiple linear regression procedures.32 These analyses identified the best regression, defined as the regression pro- viding the greatest gain in information (compared to no regres- sion) indexed by the Akaike Information Coefficient (AIC).*3 (D) The pattern of best multivariate regressions for individuals were then examined within groups defined by reaginic factors and airways hyperreactivity categories. (E) Finally, multiple linear regression by leaps and bounds was then performed for all groups of patients defined by airways hyper- reactivity and reaginic factors, using all 7 air pollution and meterologic variables and the 4 concommittant variables (see (3) above). For each group, the best regression was identified by the AIC criterion. 7 ------- (F) The pattern of best regressions among groups defined by reaginic factors and airways hyperreactivity was examined to identify the role of air pollution and meterologic variables upon the pulmonary function measurements of subgroups of patients. The final series of leaps and bounds multiple linear regression analyses, both for individuals (C and D) and groups (E and F), were performed for each of the 3 spirometric pulmonary function measures: CI) FEVj, (2) FEVi/FVC%, and (3) PEFR. 4. RESULTS 4.1 AIR POLLUTION AND METEROLOGIC VARIABLES Average monthly levels of each air pollution and meterologic variable studied are presented in Table 4.1 on the following page for the summer and winter periods. Each of the seasonal periods is subdivided into months in order to portray the consistency of the average levels during each period. Table 4.2 shown on page 9 presents frequency distributions for each vari- able during the summer and winter periods, showing a marked increase in vari- ability and the number of high levels for all air pollution variables during the winter period, with the exception of O3. Minimum temperature and baro- metric pressure also showed more variability during winter. In comparison to the summer, mean daily levels for winter were higher for CO (6.25 +_ 2.02 vs 3.16 +_ 0.98 ppm) > THC C2- 95 +_ 0.55 vs 2.33 +_ .24 ppm), SO2 (0*006 +_ 0.004 vs 0.003 +_ 0.003 ppm), and COH (0.59 +_ 0.22 vs 0.25 +_ 0.07), but winter values were clearly lower for O3 than in the summer (0.009 +_ 0.003 vs 0.102 +_ 0.059). SO2 levels were generally low for both periods and showed little variability. Mean daily minimum temperature was 16C° lower during winter (-4.09C0) than summer (11.95C0), with much greater variability represented in the winter values. Mean barometric pressure was slightly lower and varied more widely during winter (627.3 +_ 4.3) than summer (629 +_ 2.9). Table 4.3 shown on page 10 presents the intercorrelations among all variables for each period. For both summer and winter periods, there were moderate to high correlations among SO2, THC, and CO. For summer, O3 was nearly independent of all other air pollution and meterologic variables, while in winter 03 was inversely related to CO, SO2, and THC. The index of particulates, COH, was positively related to CO, SO2, and THC during the winter period, but inversely related to O3. In contrast, during summer COH was essentially independent of SO2 (r = .05) and O3 (r = .07). Finally, as would be expected, minimum temperature was essentially unrelated to the air pollution variables during summer, but negatively related to COH during winter (r = -.30). Scatterplots did not indicate anything other than a linear trend in any of the data. 8 ------- TABLE 4.1. MEANS AND STANDARD DEVIATIONS FOR ALL AIR POLLUTION AND MOTEROLOGIC VARIABLES BY MONTll FOR THE SUWER (A) AND WINTER (I) PERIODS Total Barooetric Carbon Monoxide Sulphur Dioxide Hydrocarbons Ozone Coef. of llaze Pressure (CO) (S02) (TilC) (Oj) (COfl) Hin Tenp (BP) ppm ppm ppa ppa COtls/IOOO ft C° oaHg A. Suaaer Period N Mean SI) Mean SD Mean SD Mean SD Mean SI) Mean SD Mean SD May 1, l97S-Hay 31, 197S 31 2.960 1.107 0.003 0.005 2.26S 0.284 0.107 0.057 0.230 0.073 6.403 3.562 627.46 4.164 June I, 1975-June 30, 197S 30 J. 25* 1.128 0.002 0.003 2.283 0.165 0.095 0.050 0.226 0.067 11.S83 3.187 629.44 2.533 July 1, 1975-July 31. 197S 31 3.OSS 0.S80 0.003 0.002 2.3S2 0.198 0.100 0.068 0.270 0.062 H.226 1.564 632.05 2.040 Aug. 1, 197S-Aug. 12, 197S 12 3.629 1.289 0.004 0.002 2.384 0.287 0.114 0.063 0.283 O.US 16.167 1.723 631.13 2.45? B. Winter Period Nov. IS, 1975-K'ov. 30, , 1975 16 6.168 1.97S 0.009 0.006 3.093 0.691 0.008 0.002 0.6*6 0.242 -6.187 5.645 62T.3S s.rsr Dec. I, 1975-Dec. 31, 197S • 25 7.129 2.407 0.007 0.003 3.300 0.619 0.005 0.002 0.700 0.218 -2.900 S.605 629.12 4.100 Jan. I, 1976-Jan. 31, 1976 30 7.247 2.592 0.008 0.007 3.200 1.187 0.006 0.003 0.719 0.298 -6.900 6.073 629.12 4.124 Feb. 1, 1976-Fcb. 29, 1976 29 S.B02 1.9S0 0.005 0.003 2.712 0.355 0.010 0.004 0.422 0.146 -2.414 S.622 626.39 3.504 Mar. I, 1976-Mar. 31. 1976 31 5.032 1.262 0.004 0.003 2.582 0.365 0.014 0.005 0.487 0.1BS -2.806 5.927 624.90 4.712 * Six days at the end of December were excluded (Deccaber 25 through December 31). ------- TABLE 4.2. FREQUENCY DISTRIBUTIONS (DAYS) OF AIR POLLUTION AND HETEROLOG1C VARIABLES FOR SUWER AND WINTER PERIODS Carbon Monoxide (CO) Sulfur Dioxide (SO?) Coefficient of Haze (001!) Total Hydrocarbons (THC) PPa Summer Winter EE" Sumter Winter COHS/1000 ft Sumner Winter ppm Sumner Winter 5.6 - 6.0 0 1 1.5 - 1.6 0 2 S.l - 5.5 0 0 IJ.O - 14.0 0 4 .026 - .030 1 1 1.3 - 1.4 0 0 4.6 - 5.0 0 5 U.O - 12.0 0 2 .021 - .025 0 2 1.1 - 1.2 0 8 4.1 - 4.5 0 4 9.0 - 10.0 0 26 .016 - .020 0 S .9 - 1.0 0 9 3.6 - 4.0 0 9 7.0 - 8.0 2 43 .011 - .01S 0 13 .7 - .a 0 27 3.1 - 3.5 1 25 S.O - 6.0 i: 35 .006 • .010 9 39 .5 - .6 0 42 2.6 - 3.0 9 43 3.0 - 4.0 77 20 .0(11 - .005 82 67 .3 - .4 50 42 2.1 - 2.5 SS 43 0.0 - 2.0 •0 1 Zero __? 4 .1 - .2 SI 1 1.6 - 2.0 _3 1 No. of days 101 131 No. of days 101 131 Ha. of days 101 131 No. of days 101 131 * + SD J. 16^.98 6. 25+2.02 X + SD . 00 J+. 003 006+.004 I ~ SD 2S+.07 .59+.22 X+SD 2.J3+.24 2.95+.S5 Ozone fOt) Minimum Temperature (T) Barometric Pressure (BP) EE™ Stunner Winter £ Sumer Winter ¦nut Sumer Winter +16 - +20 32 0 .21 - .26 2 0 <~11 - +15 34 1 .19 - .22 t 0 ~ 6 - +10 19 4 .15 - .IS 20 0 ~ 1 - ~ 5 15 33 633 - 636 16 14 .11 - .14 IS 0 - 4 - 0 1 44 629 - 632 59 44 .0" - .10 26 0 - 9 - - S 0 19 625 - 628 21 43 •OS - .Oft IS 3 -14 - -10 0 23 621 - 624 2 20 .00 - .02 13 128 -19 - -IS 0 7 617 - 620 J 10 So. of days 101 131 Ho. of days 101 131 No. of days 101 131 X + SD .102*.060 .009*.003 T ~ SD ~11.95+2. 65 -4.09+5.SO * + SD 629.8+2.9 627.3+4.3 ------- TABLE 4.3. INTERCORRELATIONS AMONG AIR POLLUTION AND METEROLOGIC VARIABLES FOR THE SUMMER (A) AND WINTER (B) PERIODS A. Summer Period CO so2 THC 03 COH Avtemp Mintemp S02 .42** THC .69** .42** °3 .00 .20* -.04 COH .50** .05 .62** .07 Avtemp .10 .10 .08 -.01 .16 Mintemp .10 .07 .10 -.01 .18 .95** Barometric Pressure -.04 -.16 .16 -.16 .18 .29** .31** B. Winter Period CO so2 THC 03 COH Avtemp Mintemp so2 .44** THC .71** .56** °3 -.58** -.34** -.49** COH .76** .64** .73** -.54** Avtemp .21* -.17 -.09 .11 -.30** Mintemp .20* -.18 -.11 .12 -.30** .95** Barometric Pressure .08 -.03 .12 -.24* .08 -.20* -.18 *P<. 05. **P<.01. 11 ------- 4.2 PULMONARY FUNCTION MEASUREMENTS Table 4.4 below presents the distributions of the mean pulmonary functions for both periods. For the separate groups of 67 patients within both periods, the pulmonary functions were distributed in a similar way: FEVj (2.04 +_ .57 vs 2.08 +_ .72 liters, for summer and winter, respectively), PEFR (6.22 +_ 1.69 vs 6.17 +_ 1.97 liters/sec), and FEVx/FVC% (73.97 + 9.54 vs 72.25 +_ 9.97 per cent). TABLE 4.4. FREQUENCY DISTRIBUTIONS OF MEAN PULMONARY FUNCTION MEASURES FOR PATIENTS DURING SUMMER AND WINTER PERIODS First Second Forced Expiratory Volume FEVi as a Percent of Forced Vital Capacity (FEVx) (FEVy/FVC*.) Liters Simmer Winter Percent Summer Winter 96 - 100 1 0 91 - 35 2 1 4.51 - 5.00 0 1 86 - 90 3 7 4.01 - 4.50 0 0 81 - 85 10 6 3.51 - 4.00 0 2 76 - 80 16 9 3.01 - 3.SO 2 2 71 - 75 11 18 2.SI - 3.00 13 9 66 - 70 10 10 2.01 - 2.50 19 21 61 - 65 8 5 1.51 - 2.00 22 19 56 - 60 5 9 1.01 - 1.50 9 10 51 - 55 1 1 .51 - 1.00 _2 _3 46 - SO _0 N/Period 67 67 N/Period 67 67 X +_ SD 2.04*.57 2.08^.72 X +_ SD 74.0+9.5 72.2+10.0 Peak Expiratory Flow Rate (PEFR] Liters/Sec Summer Winter 12.01 - 13.00 0 1 11.01 - 12.00 1 0 10.01 - 11.00 0 3 9.01 - 10.00 1 3 8.01 - 9.00 5 3 7.01 - 8.00 16 5 6.01 - 7.00 15 18 5.01 - 6.00 13 17 4.01 - S.00 10 10 3.01 - 4.00 5 6 2.01 - 3.00 0 0 1.01 - 2.00 _1_ N/Pcriod 67 67 X + SD 6.22+1.69 6.17+1.97 12 ------- To evaluate the relationships among the three pulmonary function measures, correlations were performed for each patient using all available days within the respective periods. The average correlations, and standard deviations, are presented in Table 4.5 for the summer and winter periods. For patients TABLE 4.5. MEANS AND STANDARD DEVIATIONS OF THE CORRELATION COEFFICIENTS AMONG PULMONARY FUNCTION MEASUREMENTS FOR THE SUMMER AND WINTER PERIODS* Period Pulmonary Function FEV2 FEVj/FVC% PEFR FEVj . 54+_. 32 Summer FEVi/FVC% PEFR FEVj . 59+. 36 Winter FEVx/FVC*. PEFR * Data are expressed as Mean +_ SD. within both periods, the pattern of the mean correlations is similar: FEV^ and PEFR are highly related, while the relationships among FEVj/FVC% and the other measures are only moderate. Since the pulmonary function measurements were not uniformly highly related and since no single pulmonary function was clearly preferable, analyses relating pulmonary functions to air pollution and metero- logic variables were subsequently performed using each measure. It had been anticipated that patients would show generally improving pulmonary function levels throughout hospitalization. Preliminary correla- tional analyses, relating pulmonary functions to day of study were performed 84+.15 48+.31 .78+.25 .50+.33 13 ------- to evaluate this expected trend. Table 4.6 summarizes the distribution of these correlations for each pulmonary function measure for patients within both summer and winter periods. Correlations within both periods varied widely and TABLE 4.6. FREQUENCY DISTRIBUTIONS OF CORRELATIONS BETWEEN PULMONARY FUNCTION MEASURES AND DAY OF STUDY FOR SUMMER AND WINTER PERIODS Pulmonary Function Measurements* Correlation FEVi FEVi/FVC% PEFR Summer Winter Summer Winter Summer Winter .81 to 1.00 0 4 0 1 1 1 .61 to .80 9 4 8 3 9 12 .41 to .60 9 14 13 16 13 12 .21 to .40 13 7 14 10 15 5 . 01 to .20 17 7 9 6 14 7 -.19 to .00 10 6 7 8 10 13 -.39 to -.20 7 8 9 7 3 5 -.59 to -.40 2 10 6 9 1 7 -.79 to -.60 0 6 1 7 1 3 -.99 to -.80 _0 _1 _0 _0 _0 _1 N/Period 67 67 67 67 67 67 X + SD .19+.32 .05+.50 .16+.39 .04+.45 .25+.36 .13+.46 * FEV} = First Second Forced Expiratory Volume; FEVi/FVC% = FEVi as a % of Forced Vital Capacity; PEFR = Peak Expiratory Flow Rate. were not consistently positive. For example, for PEFR, 15 correlations were in the range of 0 to -.60 for the summer period, while 29 were within this range for the winter period. These analyses confirmed visual examination of individual plots of pulmonary functions made across days of treatment, and indicated that a wide range of patterns - random, increasing, decreasing, etc. existed. Specific patterns could not be attributable to patients within groups defined by airways hyperreactivity or reaginic factors. 14 ------- 4.3 PULMONARY FUNCTIONS IN RELATION TO AIR POLLUTION AND METEROLOGIC FACTORS 4.3.1 Univariate Regression Analyses Simple regressions were performed to provide an initial impression of the relationship between pulmonary function measures (FEVj/FVC%) and the air pollution/raeterologic variables. All analyses were performed on individual patients, thereby providing a matrix of regression equations for the summer and winter periods defined by 67 patients per period and 7 air pollution and meterologic variables. Scatterplots indicated no trends beyond the linear in the data. Table 4.7 summarizes the significant regressions for each variable. Air pollution variables failed to show a consistent relationship to FEVj/FVC% TABLE 4.7. UNIVARIATE REGRESSION ANALYSES SUMMARY TABLE FOR INDIVIDUAL REGRESSIONS Air Pollution - Meterologic Variable Period Regression Coefficient CO S02 THC 03 COH T* BP Positive 1 5 3 1 4 6 13 Summer Negative 2 3 1 3 1 3 2 Not Significant + 64 59 63 63 62 58 52 N/Period = 67 Positive 5 2 3 5 8 5 2 Winter Negative 1 2 4 11 6 7 3 Not Significant + 61 63 60 51 53 55 62 N/Period = 67 * Minimum Temperature. + P<.05. 15 ------- measurements. For example, during the winter period COH was significantly- related to FEVj/FVC% foT 14 patients; but of these, 8 regression coefficients were positive (higher values of COH associated with higher values of FEVi/ FVC%) while only 6 were in the expected negative direction. Surprisingly, ozone (O3) was significant for 14 individuals during winter; however, 5 of these 14 individuals had higher FEVi/FVC% associated with higher levels of O3. There were no differences in age, sex, airways hyperreactivity or reaginic factors among patients with positive, negative, or nonsignificant regressions for any air pollution variable. Barometric pressure was significantly associated with FEVi/FVC% during the summer period for 15 patients with 13 of these patients having higher FEVi/FVC% on days of higher barometric pressure. No consistent differences could be found between patients apparently affected by barometric pressure and others. During the winter period, barometric pressure exerted virtually no consistent effect upon FEVi/FVC%. Minimum temperature was unrelated to FEVi/ FVC% either during the summer or winter periods. 4.3.2 Multivariate Regression Analyses In these final series of analyses, extensive efforts were made to account for variables which could obscure a real relationship between air pollution/ meterologic variables and pulmonary function measures. A total of eleven variables were involved in leaps and bounds multiple linear regression analyses,-^ using all 7 air pollution/meterologic variables and 4 concomittant variables shown in Table 4.8. The concomittant variables included (1) intraveneous bronchodilators given at the time of the pulmonary function measurement, (2) the previous day's pulmonary function value, (3) bronchodilator medications taken within 2 hours prior to pulmonary function measurement, and (4) bronchodilator treatments taken within 1 hour prior to pulmonary function measurement. The previous day's pulmonary function measure- ment was included to account for the usual variations noted across time in the level of airway obstruction, while each of the remaining 3 variables could in- fluence airway calibre directly. As described in the Methods section, identical analyses were performed for FEVi, FEVi/FVC%, and for PEFR for (A) individual patients within each period, (B) patient groups defined by the role of reaginic factors in their asthma, and (C) patient groups defined by airways hyperreactivity, indexed by methacholine and histamine challenges. A summary table for the leaps and bounds multiple linear regression analy- ses for individual patients is presented in Table 4.9. The table shows the fre- quency with which each variable appeared within the best regression equation selected according to the AIC criterion.^3 As expected, prior bronchodilator treatments clearly influenced subsequent pulmonary function measures, appearing most often within the best regression for all pulmonary function measures for both periods. With few exceptions, prior bronchodilator treatment was positively related to pulmonary function levels. The next strongest variable was the presence of 16 ------- TABLE 4.8. VARIABLES INCLUDED IN THE LEAPS AND BOUNDS MULTIPLE LINEAR REGRESSION ANALYSES Variable No. Name Value Description 6 7 8 9 10 11 Intraveneous bronchodilators 1,0 Previous day's function Raw value Prior bronchodilators 1,0 Prior treatment 1,0 Carbon monoxide (CO) ppm Sulfur dioxide (S02) ppm Total hydrocarbons (THC) ppm Ozone (Oj) ppm Coefficient of haze (COH) COHs/lOOO ft Minimum temperature (T) C° Barometric pressure (BP) mmllg Intraveneous bronchodilators given at time of pulmonary function measurement 8:00 am pulmonary function for the preceding day Bronchodilators taken within two hours pre- ceding pulmonary function measurement Inhaled bronchodllator treatment taken within 1 hour preceding pulmonary function measurement 24-hour average preceding 8:00 am pulmonary function ------- TABLE 4.9. SU>MARY TABLE FOR LEAPS AND BOUNDS MULTIPLE LINEAR REGRESSION ANALYSES FOR INDIVIDUAL PATIENTS Sumner Period Winter Period Variable FEVj FEVj/FVC% PEFR FEVj FEVj/FVC* PEFR Number Variable Name +¦ - No* ~ - No ~ - No - No ~ - No + - No 1 Intraveneous Bronchodilators 3 IS 49 7 10 SO 3 16 48 3 17 47 6 11 50 4 13 50 2 Previous Function 1 9 57 4 5 58 0 8 59 1 6 60 3 6 58 2 7 SB 3 Prior Bronchodilators 3 15 49 2 10 55 6 14 47 1 12 54 8 6 S3 2 9 56 4 Prior Treatments 29 3 3S 16 S 46 31 4 32 27 4 36 21 9 37 28 6 33 S CO 3 5 59 6 7 54 5 4 58 3 5 59 6 3 58 5 S 57 6 so2 4 3 60 3 5 59 4 4 59 4 9 54 2 6 59 3 7 57 7 nic 3 1 63 4 3 60 3 3 61 2 6 59 2 4 61 5 6 56 8 °3 11 2 54 2 6 59 7 2 58 5 9 53 1 6 60 9 8 50 9 con 7 3 57 7 3 57 5 1 61 11 4 52 7 6 54 10 S 52 10 Temperature 14 3 50 14 2 51 13 1 53 8 4 55 2 fi 57 5 7 55 U Barometric Pressure 8 0 59 7 3 57 7 0 60 2 2 63 5 3 59 4 2 61 * Header labels indicate: + * positive regression coefficient (P<.05); - ¦ negative regression coefficient (P<.05); No « not significant. ------- intraveneous bronchodilators at the time of pulmonary function measurement; it was generally associated with lower pulmonary functions since patients are typically placed on these intensive regimens when experiencing major breathing difficulties. More importantly, the difficulty in constructing a general model is appa- rent. No consistent relationship between any air pollution/meterologic variables and any of the pulmonary function measures were found. When air pollution vari- ables appeared within the best regression, they were nearly evenly distributed between positive and negative regression coefficients. For the meterologic variables, minimum temperature appeared with a positive regression coefficient 14 times during the summer period for each pulmonary function measure, and with a negative coefficient rarely. Unexpectedly, temperature was less con- sistently related to pulmonary function during the winter period, suggesting that limited exposure may occur to the outdoors on cold winter days. Baro- metric pressure was generally positive when it appeared during summer, but not consistently related to pulmonary functions for the winter period. Finally, Table 4.9 indicates that there were patients within both seasonal periods where no best regression could be identified on the basis of the AIC criterion. Supplementary analyses indicated that the presence or absence of reaginic factors in asthma, and degree of airways hyperreactivity (indexed by metha- choline and histamine challenges) could not differentiate between patients having or not having significant negative regression coefficients for air pollution or temperature within the best regressions. Tables 4.10 and 4.11, shown on the following pages, summarize the final leaps and bounds multiple linear regression analyses for the summer and winter periods, performed for groups of patients defined according to airways hyper- reactivity. Analyses for groups defined according to reaginic factors re- vealed no systematic differences among these groups, and reaginic factors were therefore disregarded as a basis for subsequent grouping. In agreement with the parallel analyses for individuals, prior broncho- dilator treatments taken within one hour before pulmonary function measurement (Var. #4) appeared most often within the best regression of these groups, and invariably with a positive regression coefficient. Intraveneous bronchodilators (Var. #1), in contrast, invariably had a negative regression coefficient with- in the best regressions, indicating that patients are generally experiencing breathing difficulty when placed on these Tegimens. The 5 air pollution variables appeared rarely within the best regression for these groups, and typically later than the medication variables. While the pattern of results is generally similar for all pulmonary function measures, careful examination of the table reveals inconsistencies in the direction of the relationships. For example, when O3 (Var. #8) appeared, it was generally negatively related in winter. The only time it appeared in summer (for FEVi), O3 was positively related to the pulmonary function measurement. For CO 19 ------- TABLE 4.10. LEAPS AND BOUNDS MULTIPLE LINEAR REGRESSION ANALYSES SUMMARY TABLE FOR SUMMER PERIOD SUMMARIZING BEST REGRESSIONS FOR AIRWAYS HYPERREACTIVITY GROUPS* Variable A Variable B Variable C Variable D Group Coefficient of Determination N R2 Regression Var. Coef. P Regression Var. Coef. P Regression Var. Coef. P Regression Var. Coef. P Variable E 6 (F) Regression Var. Coef. P A. FEVj Methachollne Missing 0 10 ~ <.001 11 ~ <.01 Low 32 4.365 1 <.001 2 + <.0S 4 + <.05 Moderate 27 5.379 1 <.01 4 + <.001 9 ~ <.0S High 5 2.362 1 <.10 4 ~ <.001 Negative 3 6.419 4 <•05 8 ~ <¦01 9 + <.01 Histamine Missing 1 2S.6S 4 + <.001 10 * <.05 low 18 3.749 1 - <.01 4 ~ <.001 B ~ <.05 10 ~ <.001 11 ~ <.01 Moderate 27 3.917 1 - <.001 4 ~ <.001 10 + <•001 High 17 4.492 1 - <.001 4 + <.001 10 + <•001 Negative Lowest No regression is best Missing 1 25.65 4 ~ <.001 10 ~ <.05 Low 36 3.727 1 <.001 2 ~ <.05 4 ~ <.001 10 ~ <•001 Moderate 23 6.237 1 <.001 4 ~ <.001 9 ~ <.05 10 ~ <.05 High 4 1.917 1 <.10 4 ~ <.01 Negative 3 6.419 4 <-05 8 * <.01 9 <.01 11 <.01 ------- TABLE 4.10. continued Group N Coefficient of Determination R2 Variable A Variable B Variable c Variable D Variable E 6 (F) Var. Regression Coef. P Var. Regression Coef. P Var. Regression Coef. P Var. Regression Coef. P Regression Var. Coef. P B. FGVj/FVC* Methacholine Missing 0 Low 32 2.S24 3 - <•01 4 + <.001 5 - <.01 6 + <.10 106(11) ~(~) <.001 Moderate 27 1.239 1 - <.01 4 + <.001 10 + <.05 11 + <.10 6 (<. 05 ) High S 2.309 1 - <.10 4 + <.01 10 + <.05 Negative 3 1.725 S - <.10 9 ~ <.05 Histamine Missing 1 19.36 4 ~ <.01 10 + <.01 Low 18 3.435 1 - <.10 4 + <.001 6 - <.10 10 + <.001 11 ~ <.01 Moderate 27 .589 1 - <.05 4 ~ <.01 10 + < .05 High 17 3.031 1 - <.001 2 + <.10 4 + <.001 5 - <.04 10 ~ <.001 Negative 4 2.252 4 * <.01 Lowest t Missing 1 19.36 4 * <.01 10 + <.01 Low 36 2.716 1 - <.001 2 + <.05 4 + <.001 5 - <.01 10 * <.001 Moderate 23 0.702 1 - <.05 4 + <.001 9 4- <.10 11 ~ <.01 High 4 2.275 1 - <.20 4 + <.05 10 + <.05 Negative 3 1.72S 5 - <.10 9 * <.05 ------- TABLE 4.10. continued Group N Coefficient of Determination R2 Variable A Variablo B Variable C Variable D Variable E 6 (F) Var. Regression Coef. P Var. Regression Cocf. P Var. Regression Coef. P Var. Regression Coef. P Regression Var. Coef. P C. PEFR Metli.icholine Missing 0 Low 32 4.998 1 - <.001 2 + <.0S 4 + <.001 10 ~ <.001 11 ~ <.01 Moderate 27 6.086 1 - <.001 4 ~ <.001 10 + <.001 High 5 1.383 4 ~ <•01 Vnnit 2 «/#» 3 U/% roorikcclnn 4c kf>ct iM ^il i. 1 ¥C " (111 1 C5IV391UII * 9 Uv •> L Histamine Mi ssing 1 45.24 1 - <.01 4 + <.001 10 + <¦05 l.ow 18 4.498 1 - <-001 4 + <.001 10 4 <.001 11 ~ <.05 Moderate 27 4.863 1 - <.001 4 <.001 10 + <.001 High 17 3.786 1 - <.001 4 + <.001 10 + <.01 11 ~ <.10 Kegat ive 4 2.918 4 ~ <.001 Lowest Missing t 1 45.24 1 - <.01 4 + <.001 10 «¦ <.05 Low 36 4.311 1 - <.001 2 + <.05 4 <.001 10 ~ <.001 11 ~ <.01 Moderate 23 6.688 1 - <.001 4 + <.001 10 * <.001 High 4 0.928 4 ~ <.10 Negative 3 2.596 3 - <.10 7 + <.10 10 - <•10 * Variable Code: 1 « Intravcneous bronchodilators; 2 = previous day's pulmonary function; 3 « prior bronchodilators; 4 » prior treatments; 5 « CO; 6 ¦ SOj; 7 » TJIC; 8 =¦ O3; 9 » COM; 10 « minimum temperature; 11 • barometric pressure. t Note - This is the same group as missing histamine above. ------- TABLE 4.11. LEAPS AND BOUNDS MULTIPLE LINEAR REGRESSION ANALYSES SUMMARY TABLE FOR WINTER PERIOD SHOWING BEST REGRESSIONS FOR AIRWAYS HYPERREACTIVITY GROUPS * Variable A Variable B Variable C Variable D Variable E 4 (P) Coefficient of Determination Regression Regression Regression Regression Regression Group N R^ Var. Coef. P Var. Coef. P Var. Coef. P Var. Coef. P Var. Coef. P A. FEX'! Methactioline Missing 3 2.323 4 ~ <.10 8 - <.05 Low 25 1.417 1 - <.001 2 - <.10 4 <.001 5 <.0S 9 ~ Moderate 27 2.706 1 - <.001 4 ~ <.001 High 7 8.319 1 - <.001 4 + <.001 8 - <.05 Negat ive 5 20.973 3 - <.fl01 4 ~ <.001 Histamine Missing 7 8.880 1 - <.05 2 - <.01 4 + <.001 5 <.10 9«(I0) ~(~) Low 9 2.202 1 - <.01 4 ~ <.001 6 - <.05 8 ~ <.10 9 ~ Moderate 30 0.882 1 - <.001 4 + <.001 High 16 5.593 1 - <.001 4 ~ <•001 11 + <.0S Negative S 9.424 1 - <.001 4 ~ <.001 8 - <.0S Lowest Missing 9 5.673 1 - <.01 4 ~ <.001 9 + <.01 Low 26 .554 I - <.001 4 ~ <.001 Moderate 24 3.129 I - <.001 4 ~ <.001 High 5 9.379 1 - <.001 4 <.001 8 - <.0S Negative 3 22.420 3 - <.001 4 ~ <¦001 <.01 <.001 S(< .01) <.os ------- TABLE 4.11. continued Variable A Variable B Variable C Variable D Coefficient of Group N Determination R2 Var. Regression Coef. P Var. Regression Coef. P Var. Regression Coef. P B. FEVj/FVC% Methacholine Missing 3 0.8BS 10 <.10 Low 25 0.764 1 <.001 4 ~ <.001 10 <.0S Moderate 27 0.980 3 <.001 4 + <.001 8 <.05 High 7 0.479 11 + <.05 Negative S 7.800 1 <.001 4 ~ <.001 Regression Var. Coef. P Variable E S (F) Regression Var. Coef. P Histamine Missing Low Moderate High Negat ive Lowest 7 9 30 16 5 0.525 0.855 2.323 <.05 <.001 <.001 — No regression is best ~ <.001 5 ~ <.001 11 + -- No regression is best <.05 <.01 Missing 9 0.736 8 <.01 Low 26 0.736 1 <.001 4 ~ <.001 10 <.01 Moderate 24 1.059 3 <.001 4 ~ <.001 8 <.10 High 5 0.933 1 <.10 4 ~ <.05 Negative 3 9.847 1 <.001 4 + <•001 <.0S 95(11) ~{-) <.25 «(<-01) ------- TABLE 4.11. continued Croup N Coefficient of Determination n2 Variable A Variable B Variable C Variable D Variable E ( (F) Var. Regression Coef. P Regression Var. Coef. P Var. Regression Coef. P Var. Regression Coef. P Regression Var. Coef. P C. PI-FR Methacholine Missing 3 4.748 1 - <.05 4 ~ <.01 8 - <.05 Low 25 1.198 1 - <.001 4 + <.001 7 - <•05 8 ~ <.05 9 ~ <.001 Moderate 27 1.858 1 - <.001 4 + <.001 High 7 6.038 1 ~ <.001 4 + <.001 Negative 5 10.SIS 1 - <.01 4 + <•001 8 ~ <.01 9 ~ <.05 Histamine Missing 7 8.199 2 - <.001 4 + <.001 9 + <.001 Low 9 1.725 1 - <.001 4 + <•001 Moderate 30 0.479 1 - <.05 <.10 4 ~ <.001 High 16 4.512 1 - <.001 4 ~ <.001 11 + <.01 Negative 5 7.629 3 - <.001 4 + <.001 6 - <.05 8 <.001 Lowest Missing 9 7.515 2 - <.001 4 + <.001 8 - <.0S 9 ~ <.01 Low 26 0.329 1 - <•05 4 ~ <.01 8 <.10 Moderate 24 2.138 1 - <.001 4 ~ <.001 High 5 7.449 1 - <.001 4 ~ <.001 Negative 3 15.481 1 <.001 4 ~ <.001 8 ~ <.05 9 ~ <.05 * Variable Code: 1 ¦ intraveneous bronchodilators; 2 = previous day's pulmonary function; 3 = prior bronchodilators; 4 ¦ prior treatments; 5 = CO; 6 « SO2; 7 =» TllC; 8 » Oj; 9 » COII; 10 » minimum temperature; 11 » barometric pressure. ------- (Var. #5), the pattern was somewhat more consistent, appearing twice as a negatively related variable in winter (for FEVi/FVC% and FEV^) and several times during summer (for FEVj/FVC%). SO2 (Var. #6) appeared twice (for FEVj and PEFR) with a negative regression coefficient in winter and twice in summer (on FEVi/FVC%), but with a positive and a negative regression coefficient. THC (Var. #7) appeared only once in winter and with a negative regression co- efficient (PEFR), and not at all for summer. Finally, COH (Var. #9) which appeared several times during summer (FEVi and PEFR) and winter (FEVi/FVC% and FEVi), always had a positive regression coefficient. Patient groups defined according to airways hyperreactivity were not consistently influenced by air pollution variables in the same way. The regression equations could only account for a relatively small amount of the variability in the pulmonary function scores. For the meterologic variables, minimum temperature (Var. #10) and baro- metric pressure (Var. #11), the results are also equivocal. Temperature and barometric pressure appeared rarely during the winter period, and with nega- tive and positive regression coefficients. In contrast, during the summer period, minimum temperature appeared frequently and always with positive regression coefficiants, but this effect was not attributable to any group or groups defined by airways hyperreactivity. In summary, the specific in- fluence of air pollution variables when they appeared, was small, variable in direction, inconsistent for groups defined by airways hyperreactivity, and inconsistent across pulmonary function measures (FEV]/FVC%, FEVi, and PEFR). S. DISCUSSION The results do not support the hypothesis that the air pollution vari- ables studied within a metropolitan area affect the pulmonary functions of asthmatic patients. Neither univariate or multivariate regression analyses for individuals and groups identified any consistent effect. In addition, there were no subgroups of asthmatic patients defined according to airways hyperreactivity or the role of reaginic factors in their asthma who appeared to be affected more than others. Failure to identify any systematic relation- ships ruled out specification of a general model. Importantly, this inability to specify a general model occurred despite elaborate attempts to account for extraneous factors that could influence pulmonary function measurements, in- cluding the presence or absence of intraveneous medications at the time of measurement, bronchodilators or treatments taken before measurement, and the previous day's pulmonary function measurement. This paucity of clear results occurred for all spirometric pulmonary function measurements studied, inclu- ding FEVi, FEVj/FVC*, and PEFR. The Tesults must, however, be viewed in relation to the strengths and limitations of the study. There are several notable strengths. First, the study focused upon objective pulmonary function measurements indexing airway obstruction, and studied several of these. This focus is in contrast to 26 ------- epidemiologic studies (based on clinic and hospital records of treatment) or studies dealing exclusively with subjectively reported breathing difficulties. Second, a well-defined group of asthmatic patients, with moderately severe illness, were studied. Documentation about their asthma was extensive in re- gard to history, role of allergic (reaginic) factors, and airways hyperreac- tivity. At each step, analyses proceeded with regard to subclassification based on reaginic factors (thereby minimizing the influence of seasonal air- borne pollens upon pulmonary function) and airways hyperreactivity, the degree of which could logically affect the response to air pollution variables in crucial ways. By defining the asthmatic groups in such a detailed way, the study also avoids problems inherent in grouping diverse respiratory illnesses arbitrarily. Third, the final series of analyses considered those factors which could obscure potential relationships between air pollution variables and pulmonary function measures. Using the Clinical Data Management System,^ it was possible to retrieve not only the pulmonary function data, but per- mitted verified information about any intraveneous medications or bronchodila- tor medications and treatments taken before pulmonary function measurement, and the time at which these were taken. These variables, particularly prior bronchodilator treatments, were found to influence pulmonary function measure- ment importantly. This effect was documented and accounted for within the final series of analyses. Fourth,.two periods of study were selected to maxi- mize the potential impact of all air pollution and meterologic variables. The differences in average levels and variability of the air pollution/meterologic variables contrasted in the expected fashion between the seasonal periods. Finally, the number of available patients within each period was fairly large, providing ample opportunity for any systematic effect of air pollution to be documented. Nonetheless, the study has a number of real or potential limitations. One potential limitation, regarding the indoor-outdoor air pollution rela- tionships, was more apparent than real. Unlike typical hospitalization, patients at NJHRC are not confined to the building or even the hospital grounds, but are encouraged to move about the Denver area freely - shopping, attending sporting and cultural events or movies - as they would at home. Adolescent patients, for example, continue to walk to school during treatment. The high school is nearly eight blocks away from the hospital. For most patients, therefore, exposure to air pollution should be comparable to people residing at home. Since the study involved retrospective data, no information was available to document time spent outdoors by various patients. Reduced exposure to outdoors on cold days may have limited the relationship between minimum temperature and pulmonary functions in winter. In the Salt Lake City study by Finklea, et_al_. ,22 there was also indication that reduced exposure on cold days may have influenced the relationship between temperature and attack rates for asthmatics living at home. Additional information was acquired about the indoor-outdoor air pollu- tion relationships for the patient floors. The patients resided on the second and third floors of a new 10-story building. The intake for the ventilation system of the building drew in outside air at a rate of 180,000 cu ft/min. and provided a minimum of six air exchanges per hour for the building's total volume of 1,800,000 cubic feet. Each patient room had 27 ------- individual input and exhaust ducts, with additional exhausts located in halls. There are no operating rooms within the hospital and no smoking is permitted on the patient floors or elevators. Research laboratories are located above the patient floors, with each laboratory with any potential for generating fumes provided with hoods over the laboratory areas, and having rooms exhausted at rates exceeding the rest of the building. None of these laboratories are located on the patient floors. For four days during November, 1976 (November 10 through November 14), a mobile unit from Pedco Environmental Specialists (Cincinnati, Ohio) moni- tored indoor-outdoor air pollution levels for three patient rooms (two on the third floor and one on the second floor). Examination of this data indicated that for NO, N02, CO, THC, and SO2 the indoor-outdoor air pollution levels are highly comparable, both in regard to time and absolute magnitude. For O3, which is known to break down rapidly, the indoor levels were consistently near zero despite changes in the outdoor levels. Due to the rapid air exchange in the patient building the time lag was small and on the order of 20 minutes. The unusually high rate of air exchange for the patient building was confirmed by the timed disappearance of tracer gas released in the patient rooms. Addi- tional in-place monitoring of NO and CO described a daily pattern associated with periods of high automobile traffic. Thus, with the exception of O3 and COH, even those patients remaining exclusively within the building would be exposed to CO, SO2, and THC. The absence of an effect of these air pollution variables upon pulmonary functions cannot be attributed to lack of exposure resulting from patient behavior and low indoor-outdoor air pollution relation- ships . There are, however, certain real limitations of the study. First, all of these patients were inpatients on around-the-clock bronchodilator regimens, while most were also taking oral corticosteroids either on a daily or alter- nate day basis. These medication regimens are prescribed to increase the tolerance of patients' airways to irritants capable of aggravating the asthma. Therefore, it is possible that considerable protection was afforded by medica- tions against the adverse affect of air pollution variables. Patients on more minimal medication schedules may therefore be more appropriate to study. Second, only spirometric pulmonary function measurements were used. If the effect of relatively transient changes in air pollution is slight, specific conductance (SGaw), or airway resistance (Raw) may be preferable indices of airway obstruction.34 Third", if the effect of air pollution upon asthmatic airways depends upon more prolonged exposure, or if, conversely, the effect is very transient, this study would be expected to fail to document such effects. The study considered only average levels of the air pollution variables for 24 hours preceding pulmonary function measurement. Fourth, these results were limited to the specific air pollution variables studied, as well as the levels achieved during the two seasonal periods. In comparison to the Salt Lake City and New York studies,22>the levels of SO2 were very low: On only one day during the winter period did SO2 achieve a level near 79 qg/m,3 whereas weekly averages for high exposure patients in the earlier studies occasionally exceeded this level. The levels of SO2 were consistently below levels suggested as producing significant harm in asthmatics.In contrast, 28 ------- CO levels are generally high, but its effect is principally hematologic and would not be expected to trigger airway obstruction directly by an irritant effect. Related to these considerations, in-place monitoring and indoor-out- door air pollution monitoring by PEDCO indicated that the highest levels of THC, NO and CO occurred twice daily, near 9:00 am and 6:00 pm. These times of maximum appear to be associated with usual traffic patterns in the area. If the effect is transient, then 8:00 am pulmonary function measurement represents a poor choice. In future studies, pulmonary function measurement should follow times of peak air pollution levels closely. Finally, the full range of patient medication behavior could not be con- sidered. It is of particular interest that patients often take as-needed (PRN) treatments (usually nebulized bronchodilators) when experiencing breath- ing difficulty.^ During periods of high air pollution, more PRNs may be taken and overusage of aerosolized treatments has been related to death in asthma.37-39 jf SOj usage may serve to increase pulmonary functions and obscure any direct relationship between air pollution and pulmonary function measurement. By monitoring PRN behavior continuously among nonhospitalized asthmatics, using adapted nebulizers with mini-storage units,40'41 it may be possible to objectify the impact of air pollution upon this behavior of out- patients. 29 ------- 6. RECOMMENDATIONS This preliminary project has enabled better delineation of the factors which could obscure potential relationships between air pollution variables and airway obstruction in metropolitan, asthmatic populations. Further re- search should be based on the following recommendations. First, since oral corticosteroid and around-the-clock bronchodilator medications may afford significant protection against the effect of air pollutants, periodically medicated asthmatic patients who are not on these intensive regimens should be studied. Second, if possible, pulmonary function measurements reflecting changes in the large airways, such as airway or total lung resistance, should be used together with spirometric measures. Third, as-needed (PRN) use of aerosolized bronchodilators should be carefully monitored during any study of these patients, since most patients tend to titrate their use of these PRN medications in relation to breathing difficulty. Fourth, in studies of patients not on around-the-clock medications, it would be most desirable tn obtain pulmonary function measurements at a time closely following peak daily levels of the air pollution variables. Fifth, lag time for summarizing the air pollution levels should be varied in the analyses, permitting, for exam- ple, 8-hour and 24-hour air pollution scores to be related to changes in subsequent pulmonary function measurements, with longer lags also considered. It is not yet known how transient or time dependent any effect of air pollu- tion is upon changes in airway calibre in asthma. Finally, further studies might best be conducted on a prospective basis, permitting stringent control of such factors as medications taken prior to pulmonary function measurement and exposure to the outdoors. It is hoped that the present study has served as a useful model for the development of these future studies. 30 ------- 7. REFERENCES 1. Nadel, J.: Airways: Autonomic regulation and airway responsiveness, in Bronchial Asthma: Mechanisms and Therapeutics, E. B. Weiss and M. S. Segal, eds., Little, Brown and Co., Boston, 1976, p. 155. 2. Nadel, J. A.: Structure-function relationships in the airways: Broncho- constriction mediated via vagus nerves on bronchial arteries, peripheral lung constriction mediated via pulmonary arteries, Med Thorac, 1965, 22, 231. 3. Spector, S. L. and Farr, R. S.: Bronchial provocation tests, in Bronchial Asthma: Mechanisms and Therapeutics, E. B. Weiss and M. S. Segal, eds., Little, Brown and Co., Boston, 1976, p. 639. 4. Spector, S. L. and Farr, R. S.: A comparison of methacholine and histamine inhalations in asthmatics, J Allergy Clin Immunol, 1975, 56, 308. 5. Spector, S. L. and Farr, R. S.: Bronchial inhalation challenge procedures in asthmatics, Med Clin North Am, 1974, 58, 71. 6. Kiviloog, J.: Bronchial reactivity to exercise and methacholine in bron- chial asthma, Scand J Respir Dis, 1973, 54, 347. 7. Mellis, C. M., Katten, M., Keens, T. G., Mansell, A., and Levison, H.: Histamine and exercise provocation compared, Am Rev Respir Dis, 1977, 115, 285. 8. Horton, D. J., Suda, W. L., Kinsman, R. A., Souhrada, J., and Spector, S. L.: Bronchoconstrictive suggestion in asthma: A role for airways hyperreactivity and emotions, NJHRC Psychophysiology Research Labora- tories Report No. 43, Denver, Colorado, July, 1977. 9. Lave, L. B. and Seskin, E. P.: Air pollution and human health, Science, 1970, 169, 723. 10. Heiman, H.: Episodic air pollution in metropolitan Boston: A trial epidemiological study, Arch Environ Med, 1970, 20, 230. 11. Schrenk, H. H., Heiman, H., Clayton, C. D., Gafafer, IV. M., and Wexler, H.: Air pollution in Donora, Pa.: Epidemiology of unusual smog episode of October, 1948, Public Health Bull. 306, Washington, D. C., 1948. 12. Drinker, P. Deaths during the severe fog in London and Environs, December 5 to 9, 1952, Arch Ind Hyg, 1953, 7, 275. 31 ------- 13. Greenburg, L., Field, F., Reed, J. I., and Erhardt, C.: Air pollution and morbidity in New York City, JAMA, 1962, 182, 161. 14. Ribon, A., Glasser, M., and Sudivoraseth, N.: Bronchial asthma in child- ren and its relationship to weather and air pollution, Ann Allergy, 1972, 30, 276. 15. Lawther, P. J., Brooks, A. G. F., Lord, P. W., and Waller, R. E.: Day to day changes in ventilatory function in relation to the environment, Environ Res, 1974, 8, 119. 16. Lawther, P. J., Waller, R. W., and Henderson, M.: Air pollution and exacerbation of bronchitis, Thorax, 1970, 25, 525. 17. Tromp, S.: Influence of weather and climate on asthma and bronchitis, Rev Allergy, 1968, 22, 1027. 18. Girsh, L. S., Shubin, E., Dick, C., and Shulanek, R. A.: A study on the epidemiology of asthma in children in Philadelphia, J Allergy, 1967, 39, 347. 19. Lewis, R., Gilkerson, M. M., Jr., and McCaldin, R. 0.: Air pollution and New Orleans asthma, Public Health Rep, 1962, 77, 947. 20. Wells, R.: Effects of cold air on respiratory air flow resistance in patients with respiratory tract disease, N Engl J Med, 1960, 263, 268. 21. Salvaggio, J., Hasselblad, V., Seabury, J., and Heiderscheit, L. T.: New Orleans asthma. II. Relationship of climatologic and seasonal factors to outbreaks, J Allergy, 1970, 45, 257. 22. Finklea, J. F., Calafiore, D. C., Nelson, C. J., Riggan, W. B., and Hayes, C. G.: Aggravation of asthma by air pollutants: 1971 Salt Lake Basin studies. In Health Consequences of Sulfur Oxides: A Report from CHESS, 1970-1971. EPA Report 650/1-74-004. 23. Finklea, J. F., Farmer, J. H., Love, C. J., Califiore, D. C., and Sovocool, G. W.: Aggravation of asthma by air pollutants: 1970-1971 New York studies. In Health Consequences of Sulfur Oxides: A Report from CHESS, 1970-1971. EPA Report 650/1-74-004. 24. Nadel, J. S., Salem, H., Tamplin, B., and Tokiwa, Y.: Mechanism of bronchoconstriction during inhalation of sulfur dioxide, J Appl Physiol, 1965, 20, 164. 25. Lopez, M., Wessels, F., and Salvaggio, J. E.: Environmental influences in asthma, in Bronchial Asthma: Mechanisms and Therapeutics, E. B. Weiss and M. S. Segal, eds., Little, Brown and Co., Boston, 1976, p. 503. 26. Kinsman, R. A., Luparello, T., 0'Banion, K., Spector, S. L.: Multidi- mensional analysis of the subjective symptomatology of asthma, Psychosom Med, 1973, 35, 250. 32 ------- 27. Kinsman, R. A., Spector, S. L., Shucard, D. W., and Luparello, T. J.: Observations on patterns of subjective symptomatology of acute asthma, Psychosom Med, 1974, 36, 129. 28. Kinsman, R. A., Murphy, J. R., Dunning, M., Spector, S. L., Walker, S., and Farr, R. S.: A clinical data management system for residential treat- ment in asthma. NJHRC Psychophysiology Research Laboratories Report No. 24, Denver, Colorado, 1976. 29. Assessment of air quality: Metro Denver region. Report of Air Pollution Control Division, Colorado Department of Health, August, 1975. 30. Chai, H., Farr, R. S., Froelich, L. A., Mathison, D. A., McLean, J. A., Rosenthal, R. R., Sheffer, A. L., Spector, S. L., and Townley, R. G.: Standardization of bronchial inhalation challenge procedures, J Allergy Clin Immunol, 1975, 56, 323. 31. Kinsman, R. A., Dahlem, N. W., Spector, S. L., and Staudenmayer, H. : Observations on subjective symptomatology, coping behavior, and medical decisions in asthma, Psychosom Med, 1977, 39, 102. 32. Fumival, G. M., and Wilson, R. W., Jr.: Regression by leaps and bounds, Technometrics, 1974, 16, 499. 33. Akaike, H.: Information theory and an extension of the maximum likelihood principal in Second International Symposium on Information Theory, B. N. Petroy and F. Csaki, eds., Akademia Kaido, Budapest, p. 267. 34. Bouhuys, A. and van de Woestijone, K. P.: Respiratory mechanics and dust exposure in byssinosis, J Clin Invest, 1970, 49, 106. 35. Love, G. J., Sharp, C. R., Finklea, J. F., Shy, C. M., and Knelson, J. H. : Atmospheric levels of air pollution producing significant harm. In- House Technical Report, Division of Health Effects Research, EPA, Research Triangle Park, N.C., June, 1972. 36. Dahlem, N. W., Kinsman, R. A., and Horton, D.: Panic-Fear in asthma; Requests for as-needed (PRN) medications in relation to pulmonary func- tion measurements, J Allergy Clin Immunol, in press. 37. Inman, W. H. M. and Adelstein, A. M.: Rise and fall of asthma mortality in England and Wales in relation to the use of pressurized aerosols, Lancet, 1969, 2, 279. 38. Fraser, P. M., Speizer, F. E., Waters, S. D. M., Doll, R.t and Mann, N. M.: The circumstances preceding death from asthma in young people in 1968 to 1969, Br J Dis Chest, 1971, 65, 71. 39. Segal, N. S.: Death in bronchial asthma, in Bronchial Asthma: Mechanisms and Therapeutics, E. B. Weiss and M. S. Segal, eds., Little, Brown and Co., Boston, 1976, p. 1124. 33 ------- 40. Hahn, P. M., and Yee, R. D.: Medication chronolog, Biotelemetry II, 2nd Int. Symp., Davos 1974, pp. 71-73. 41. Yee, R. D., Hahn, P. M., and Christensen, R. E.: Medication monitor foT opthalmology, Am J Opthalmol, 1974, 78, 774. 34 ------- INSTRUCTIONS 1. REPORT NUMBER Insert the EPA report number as it appears on the cover of the publication. 2. LEAVE BLANK 3. RECIPIENTS ACCESSION NUMBER Reserved for use by each report recipient. 4. TtTLE AND SUBTITLE Title should indicate clearly and briefly the subject coverage of the report, and be displayed prominently. Set subtitte, if used, in smaller type or otherwise subordinate it to main title. When a report is prepared in more than one volume, repeat the primary title, add volume number and include subtitle for the specific title. 5. REPORT DATE Each report shall carry a date indicating at least month and year. Indicate the basis on which it was selected (e.g., date of issue, date of approval, date of preparation, etc.). 6. PERFORMING ORGANIZATION CODE Leave blank. 7. AUTHORISI Give name(s) in conventional order (John R. Doe, J. Robert Doe, etc.). 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EPA Form 2220—1 (Rev. 4-771 (Reverse) ------- TECHNICAL REPORT DATA (Please read Instructions on the reverse before completingj 1. REPORT NO. 2. EPA-90S/1-77-004 3. RECIPIENT'S ACCESSION NO. 4' WAIRWAYS HYPERSENSITIVITY, AND PULMONARY FUNCTION MEASUREMENTS IN ASTHMA 5. REPORT DATE October, 1977 6. PERFORMING ORGANIZATION CODE 7'^jTcfon L. Spector, Robert A. Kinsman, Melissa Dunni ng 8. PERFORMING ORGANIZATION REPORT NO. 9. PERFORMING ORGANIZATION NAME AND ADDRESS National Jewish Hospital and Research Center 3800 East Colfax Denver, CO 80206 10. PROGRAM ELEMENT NO. 11. CONTRACT/GRANT NO. 68-02-2517 12. SPONSORING AGENCY NAME AND ADDRESS Office of Air Programs U.S. Environmental Protection Agency 1860 Lincoln Street Denver, CO 80295 13. TYPE OF REPORT AND PERIOD COVERED 14. SPONSORING AGENCY CODE 15. SUPPLEMENTARY NOTES 16. ABSTRACT This study evaluated the relationship between spirometric pulmonary function measures and air pollution and meterologic variables for adult asthmatic in-patients in an urban, long-term intensive treatment center. Two groups of 67 patients were studied during a late spring-summer period and a late fall-winter period. Patients were classified according to the role of allergic factors and the degree of airways hyperreactivity. In all analyses, 24-hour average levels of air pollution preceding pulmonary function measurement were related to sub- sequent 8:00AM pulmonary functions. Multiple linear regression analyses by leaps and bounds for individuals and groups, defined by reaginic factors and airways hyperre- activity, failed to identify a systematic effect for any air pollution variable upon any pulmonary function measure. The lack of any relationship does not appear attri- butable to limited exposure to air pollution variables, but may be affected by as- needed (PRN) medication usage, type of pulmonary function measurement employed, and periods selected for analyses. The relative strengths and limitations of the study are discussed. 17. KEY WORDS AND DOCUMENT ANALYSIS a. DESCRIPTORS b.IDENTIFIERS/OPEN ENDED TERMS c. COSATI Field/Group Air pollution Human health Lung diseases Asthma Denver, CO 18. DISTRIBUTION STATEMENT Distribution unlimited 19. SECURITY CLASS (This Report) unclassified 21. NO. OF PAGES 39 20. SECURITY CLASS (Thispage) unclassified 22. PRICE EPA Fo»m 2220-1 (R«v. 4-77) previous edition is obsolete ------- |