The Swiss Study on Air Pollution and Lung Diseases in Adults (SAPALDIA) |
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ABSTRACT |
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ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
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The present analysis was directed at investigating associations between short-term variations in air pollutant levels (NO2, total suspended particulates [TSP], O3) and cross-sectional lung function (FVC, FEV1, and forced expiratory flow at 25% to 75% of FVC [FEF25-75]) within a random sample of 3,912 adult never-smokers from eight areas of Switzerland (i.e., participants in the Swiss Study on Air Pollution and Lung Diseases in Adults [SAPALDIA] cross-sectional study, 1991). Within each local data set, the logarithms of FVC, FEV1, and FEF25-75 were regressed against the 24-h-means of NO2 and TSP and the 8-h mean of O3 (10:00 A.M. to 6:00 P.M.) on the examination day, with control for subjects' sex, age, height and weight, seasonal fluctuations and weekly cycles and meteorologic factors. On average, a 10-µg/m3 increment in the daily level of NO2, TSP, and O3 was associated with decrements in FEV1 of 0.67% (95% confidence interval [CI]: 0.13% to 1.21%), 0.46% (95% CI: 0.14% to 0.78%), and 0.51% (95% CI: 0.13% to 0.88%), respectively. Moreover, 10-µg/m3 increments in NO2 and TSP were associated with decrements in FVC of 0.73% (95% CI: 0.22% to 1.23%) and 0.36% (95% CI: 0.06% to 0.66%), respectively, and a 10-µg/m3 increment in O3 was associated with a decrement in FEF25-75 of 1.04% (95% CI: 0.22% to 1.85%). Our results suggest that FVC, FEV1, and FEF25-75 vary with the daily level of NO2, TSP, and O3, but that these measures of lung function do not allow separation of the effects of particulates from those of NO2.
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INTRODUCTION |
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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A variety of study designs exist for assessing short-term effects of air pollution on parameters of respiratory health, and many studies with this focus have been done in recent years, mainly among children (1). In general, diary studies with panels of asthmatic individuals or members of special professional groups are conducted for this purpose. The health parameters assessed on a daily basis in such studies usually include peak flow, respiratory symptoms, and medication use. In the present investigation we used lung function data from a large, cross-sectional multicenter study (Swiss Study on Air Pollution and Lung Diseases in Adults [SAPALDIA], 1991) to examine whether the daily local means of three lung function parameters: FVC, FEV1, and mean forced expiratory flow between 25% and 75% of FVC (FEF25-75), were associated with concurrent changes in air pollutant levels within our adult study sample. Our study was restricted to lifetime nonsmokers in order to avoid uncontrolled variability in lung function caused by individual differences in smoking intensity and/or smoking history. The SAPALDIA cross-sectional study was primarily conducted to assess prevalences of respiratory and allergic diseases among adults in Switzerland, and to study potential long-term effects of air pollution on respiratory health (2). So far, one of the major findings in the study has been a negative association between long-term exposure to air pollution and average lung function across study areas (3, 4). However, the large sample size and the fact that cross-sectional health examinations were uniformly and randomly distributed over the entire year of the study suggested the additional need for study of short-term associations between daily levels of air pollution and pulmonary function in the study population described here.
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METHODS |
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ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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Study Design
SAPALDIA is a multicenter study designed to examine associations between air pollution and respiratory health (2, 5). The eight study areas (Aarau, Basel, Davos, Geneva, Lugano, Montana, Payerne, and Wald) were chosen so as to represent the range of urbanization, air pollution, meteorologic conditions, and altitude of Swiss communities. A random sample of 2,500 adults aged 18 to 60 yr was drawn from the registry of inhabitants of each area (1,500 in Davos and Montana, respectively). The order in which subjects were contacted by the local SAPALDIA fieldworkers was randomly determined, and health examinations were evenly distributed over the entire year of the cross-sectional study (1991). A total of 9,651 subjects (i.e., 59% of all potential participants) were recruited for the study. They were given a standardized computerized interview based on an expanded version of the European Community Respiratory Health Survey questionnaire (6). The health examination also included a skin prick test for eight inhaled allergens, a blood test to assess total and specific IgE, a detailed lung function test, and a bronchial challenge test. The general methodology of the SAPALDIA cross-sectional study and the characteristics of the study population have been described in detail elsewhere (2).
Lung Function Measurements
Pulmonary function measurements were made with computerized spirometers (2200 SP; SensorMedics, Bilthoven, The Netherlands). This device uses an open sensor that meets American Thoracic Society (ATS) criteria (7). The spirometers displayed an error code after each pulmonary maneuver to inform the technician about the acceptability and reproducibility of the trials for the maneuver according to ATS quality criteria (7). Between three and eight trials were performed with each subject until two reproducible and acceptable, error-free trials were obtained. Calibration was done at least once a day. All technicians were trained to follow a standardized protocol and were examined for its use with volunteers. More details of the SAPALDIA spirometry methodology are given elsewhere (8, 9).
Air Pollution
Air pollutants were monitored at fixed stations in each of the eight regions in which the study was done. Concentrations of SO2, NO2, and O3 were determined as half-hourly means, and those of TSP as 24-h means, as previously described (10). The environmental variables considered in the air pollution analyses were daily levels of NO2 and TSP (24-h concentration means between 00:00 A.M. and 12:00 P.M.) and the daily 8-h level of O3 (i.e., the daily mean of O3 concentration between 10:00 A.M. and 6:00 P.M.). These variables were used to define the levels of exposure to the respective pollutants on the day of pulmonary function testing and on the preceding days. Thus, all persons who were examined on the same day and at the same place were assigned the same exposure values.
Study Population
In order to avoid additional variation in lung function related to current and/or past smoking, the investigation was restricted to a subsample of 3,912 lifetime nonsmokers with FVC and FEV1 values conforming to ATS criteria. Table 1 shows the characteristics of this subsample as compared with the characteristics of the complementary subsample (i.e., former and current smokers) by sex.
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Data Analysis
For each of the eight local population samples, the natural logarithms of FVC, FEV1, and FEF25-75 were regressed against the individual predictor variables of female sex, ln(age), ln(age)2, ln(height), ln(weight), dummy variables for the different days of the week, the 24-h means of temperature (T) and relative humidity (RH) on the examination day, along with the squares of these latter two variables, T2 and RH2, and their product T · RH, as well as eight local cubic polynomials in time (regression splines), and a single pollutant variable (NO2, TSP, and 8-h O3, respectively). The spline functions and the variables for day of the week served to control for potential trends and seasonal and weekly fluctuations in average lung function, and for potential nonrandom fluctuations in the mix of participants among different days of the week and during the course of the study. Analyses involving the 8-h mean of O3 were restricted to the period from May to September. We used the same seasonal, meteorologic, and day-of-the-week variables as in the models of lung function parameters to compute predicted daily pollutant levels, and differences between observed and predicted values are referred to as "adjusted daily pollutant levels." The use of this concept is motivated by the need to interpret our effect estimates as gradients between adjusted lung function values and these adjusted pollutant levels. Since there was no indication that residuals were heteroscedastic, and daily local residual means were neither overdispersed nor serially correlated, the use of ordinary least-squares models could be justified, and standard errors did not have to be adjusted. Summary estimates for the entire sample were then derived from the local estimates, using the method of DerSimonian and Laird (11).
A few sensitivity analyses were run, with control for potential confounder variables. In a first analysis, we included the local grass and birch pollen counts of the day and their interactions with a linear time-trend variable as additional model covariates. In a second analysis, we additionally included one dummy variable for subjects who had reported taking asthma medication or having experienced wheezing, tightness of the chest, dyspnea at rest, or an asthma attack in the 12 mo preceding the examination, and a second dummy variable for subjects who reportedly had experienced exercise-related shortness of breath. We further examined whether associations with ozone were sensitive to the inclusion in the model of concurrent levels of NO2 or TSP.
To take into account air pollution exposure on the days preceding spirometry, we repeated our analyses, using the 4-d means (examination day and three preceding days) of NO2 and TSP, respectively, as pollutant variables. The extent to which each of the 4 d additively contributed to these associations was estimated through second-degree polynomial distributed lag models (an excellent description of this method is given in Reference 12).
Additionally, we computed two-pollutant models for NO2 and TSP (i.e., simultaneously including the levels of these two pollutants on the examination day).
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RESULTS |
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ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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Table 2 shows the means and variations of the three daily pollutant measures across the eight study areas. The table also describes the distribution of the adjusted daily levels (see METHODS) of the three study pollutants. For NO2 and 8-h O3, these adjusted values show considerably less variation than the original unadjusted daily pollutant levels. Adjusted daily levels of NO2 and TSP were positively correlated with one another in all study areas, with local correlation coefficients ranging from 0.25 to 0.65 and positive correlations prevailed even when we compared adjusted daily levels of NO2 and TSP with the corresponding adjusted levels of 8-h O3 during the period from May to September (results not shown).
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Table 3 shows that the daily means of FVC and FEV1 in our cross-sectional sample of lifetime nonsmokers varied with the adjusted daily levels of NO2 and TSP, respectively. Although the magnitude of these associations was small (with an estimated average decrement in FVC and FEV1 of about 0.7% for a 10 µg/m3 increase in the adjusted daily level of NO2, and of about 0.4% for a 10 µg/m3 increase in the corresponding TSP level), they reached statistical significance. For FEF25-75, associations with adjusted daily levels of NO2 and TSP were also consistently negative, as for FVC and FEV1, but did not reach statistical significance.
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Fluctuations in average FEV1 and FEF25-75 showed a significant negative association with the adjusted daily level of 8-h O3 (with estimated average decrements in FEV1 and FEF25-75 of about 0.5% and 1.0%, respectively, for a 10 µg/m3 increase in the adjusted level of 8-h O3 (Table 3). The magnitude of these associations increased slightly when grass and birch pollen variables were included in the regression model or with additional control for NO2 exposure. However, they remained unchanged upon inclusion of TSP exposure (results not shown). Associations with 8-h O3 were also consistently negative for FVC, but they did not reach statistical significance.
Increased average levels of TSP over a 4-d period (including the examination day) were significantly associated with decrements in FVC, FEV1, and FEF25-75, but a significant association with the 4-d average NO2 concentration was found only for FEF25-75 (Table 4). That increased exposure to TSP over a period of several days might have a stronger impact on lung volume parameters than might increased cumulative exposure to NO2 is not only suggested by these results, but also by Figures 1 and 2, which show contributions from several days to the overall effect for TSP but not for NO2. On the other hand, Figure 3 shows very similar patterns of concurrent and lagged effects on FEF25-75 for both pollutant variables. In the two-pollutant models including NO2 and TSP levels on the examination day, increased levels of TSP appeared to be more predictive of decrements in FEV1 and FEF25-75 than did increased levels of NO2, whereas the estimated effects on FVC were similar for the two pollutant variables (Table 5).
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DISCUSSION |
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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In the random, cross-sectional sample of adult never-smokers examined in the present study, significant associations were found between daily levels of NO2 and TSP, respectively, and daily means of FVC and FEV1 after adjustment for seasonal variation and potential weekly cycles in average lung function, and for short-term effects of temperature and relative humidity. Moreover, daily average concentrations of O3 between 10:00 A.M. and 6:00 P.M. were found to be significantly associated with daily sample means of FEV1 and FEF25-75 during the period from May to September.
Several panel studies of children and a few cohort studies of symptomatic adults have found short-term associations between ambient pollutant levels and peak flow or FEV1 (1, 13- 15). Moreover, many experimental studies have found short-term effects of high O3 or NO2 levels on various parameters of lung function and on bronchial responsiveness (16, 17). However, to our knowledge, short-term effects of ambient air pollution on FVC and FEV1 have not yet been systematically studied in representative population samples of adults.
Clearly, a longitudinal study design (involving repeated measurements of lung function in each subject) would be better suited for investigating short-term associations between air pollution and pulmonary function (14). A gain in statistical efficiency could be obtained with such a description, and control of temporal confounding would be facilitated. However, if a cross-sectional study design guarantees that subjects are enrolled and examined in a random order, and if proper controls for seasonal and weekly patterns of lung function are applied in the data analysis, only a small residual risk of temporal confounding should remain. Since our enrollment scheme was based on randomization, such confounding could only have occurred by chance (e.g., if subjects with subnormal lung function had more often been examined on days with increased air pollutant levels). We therefore ran a sensitivity analysis by additionally controlling for two respiratory conditions potentially related to reduced lung function. Since this had almost no effect on the main estimates, it seems unlikely that our results were noticeably biased by such temporal confounding.
That associations of FEV1 and FEF25-75 with O3 remained stable or increased slightly with adjustment for concurrent effects of TSP and NO2, respectively, makes it unlikely that the effect estimates of the one-pollutant models for O3 were biased upward by some uncontrolled confounding factors related to ambient air pollution. Since pollen exposure is often discussed as another potential confounder of ozone effects, we ran a sensitivity analysis in which we additionally controlled for daily levels of grass and birch pollen (i.e., the two most relevant pollen allergens in Switzerland). Because this led to a slight increase in the O3-effect estimates for FVC, FEV1, and FEF25-75, it is also unlikely that there was major confounding of the original estimates by uncontrolled effects of pollen.
Results of the two-pollutant models suggest that changes in daily TSP levels might be more predictive of variations in lung function than concurrent changes in NO2 levels. However, given the considerable correlation between these two pollutant variables, this finding must be interpreted with caution. In Switzerland, NO2 and TSP have the same major sources, and each of them therefore represents to some extent all constituents of air pollution from these sources. Nevertheless, these constituents may be correlated with NO2 and TSP in different ways, which might explain why average exposure to TSP over several days showed a significant negative association with FVC and FEV1, but why only concurrent levels of NO2 were significantly associated with these lung function parameters. An alternative explanation might be the higher spatial variability of NO2, reflecting heterogeneity of traffic emissions. Recent data show that spatial homogeneity of particulate concentrations is quite high in the city of Basel (18), and that parallel daily measurements of TSP and particulate matter 10 µm in diameter (PM10) at fixed sites are highly correlated in different Swiss cities (19). Moreover, data from The Netherlands have shown considerable correlations among parallel measurements of PM10 made at fixed monitoring sites and with personal samplers (20). Thus, the 24-h mean of TSP concentration at a fixed monitoring site might be a more precise proxy measure for average population exposure to air pollution on a respective day than the corresponding NO2 measure. This might also help to explain why associations of lung volume parameters with NO2 were less consistent across seasons and areas in our study.
Although the associations between daily ambient levels of air pollution and daily means of lung function observed in the present study were statistically significant, they were smaller in magnitude than the associations between annual levels of ambient air pollution and average lung function in previous analyses of the SAPALDIA cross-sectional data (3). If long-term effects of air pollution on lung function exist, as is suggested by our previous results, such differences must be expected, since our present analytic approach is designed to filter out all potential long-term components. However, a clearer separation of short- and long-term effects warrants further study.
Even though the observed short-term effects of air pollution on the daily sample means of FVC, FEV1, and FEF25-75 in the present study were small, they should not be considered irrelevant. Air pollution effects are likely to vary across individuals. Whereas some persons may not be at all sensitive to such effects, others will suffer larger decrements in lung function. In fact, even small changes in the population mean of a health parameter may have a considerable impact on public health (21, 22). The decrease in the population mean of FVC or FEV1 on days with higher levels of air pollution is coherent with other observed short-term effects of air pollution, such as increases in hospital admissions for respiratory illness (23) or in physicians' house calls (24).
In conclusion, the results of the present study and prior SAPALDIA results for long-term effects of air pollution (3, 4, 25) support the public health significance of both short- and long-term effects of current levels of air pollution.
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Footnotes |
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Correspondence and requests for reprints should be addressed to Dr. Christian Schindler, Institute of Social and Preventive Medicine, University of Basel, Steinengraben 49, CH-4051 Basel, Switzerland. E-mail: christian.schindler{at}bs.ch
(Received in original form November 29, 1999 and in revised form July 14, 2000).
SAPALDIA-Team: Study Director: P. Leuenberger; Programme director: U. Ackermann-Liebrich; P. Alean (am), K. Blaser (a), G. Bolognini (p), J.P. Bongard (p), O. Brändli (p), P. Braun (p), C. Bron (l), M. Brutsche (l), C. Defila (m), G. Domenighetti (p), S. Elsasser (l), L. Grize (s), P. Guldimann (l), P. Hufschmid (l), W. Karrer (p), H. Keller-Wossidlo (o), R. Keller (p), N. Künzli (e), J. C. Luthy (l), B. W. Martin (e), T. G. Medici (p), Ch. Monn (am), A. G. Peeters (pa), A. P. Perruchoud (p), A. Radaelli (l), Ch. Schindler (s), J. Schwartz (s), G. Solari (p), M. H. Schöni (p), J. M. Tschopp (p), B. Villiger (p), B. Wüthrich (a), J. P. Zellweger (p), E. Zemp (e).(a): allergology, (am): air pollution monitoring, (e): epidemiology, (l): local assistant (MD), (m): meteorology, (o): occupational medicine, (p): pneumology, (pa): palynology, (s): statistics.
Acknowledgments: The authors would like to thank Professor J. Schwartz for valuable suggestions. Throughout the study, the SAPALDIA team also received much-appreciated advice from Professor Frank Speizer of the Harvard Medical School. The study could not have been done without the help of the following fieldworkers in the respective local medical teams: Aarau: C. Persoz-Borer, C. Wettstein, G. Giger, H. Grob-Stalder, J. Lohmüller, K. Häfeli, U. Rippstein; Basel: V. Fluri, M. Herrous, G. Imboden, L. Joos; Davos: K. D'Alberti, A. Sönnichsen; Genf: I. Barbey, K. Gegerle, N. Penay; Lugano: M. Astone, E. Haechler, E. Riesen, B. Viscardi; Montana: Dr. C. Hollenstein, E. Borgeat, I. Clivaz; Payerne: S. Menétrey-Jaques, C. Gilomen-Pages, M. C. Collaud; Wald: B. Salzmann, V. Kienast, H. Astone, V. Keller, Ch. Schwalm. Logistic and financial support was also provided by the cantonal governments of Basel-Stadt, Genève, Graubünden, Ticino, Valais, Vaud, and Zürich, and by the associated cantonal offices for air hygiene measurements. The Federal Office for Environmental Protection, Forest and Landscape supported the quality control of air hygiene measurements and the PM10-measurements made in the study. Further support was received from the Swiss Society of Pulmonology, the Lega Ticinese contro la tubercolosi e le malattie polmonari, and from various cantonal offices of public health. The authors also acknowledge the help of many other people and the support of several institutions, and thank the persons who agreed to participate in this study.
Supported by grants 4026-28099 and 3200-042532.94/1 from the Swiss National Science Foundation, by the Federal Office of Education and Science, and by a grant of the Federal Office for Environmental Protection, Forest and Landscape. SAPALDIA is part of the Swiss National Research Programme 26A, and SAPALDIA Basel is part of the European Respiratory Survey.
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References |
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ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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