|
|
||||||||
1 Dept of Epidemiology, Harvard School of Public Health, Boston, MA, 2 Epidemiology and Biomarkers Branch, US Environmental Protection Agency/National Health and Environmental Effects Research Laboratory, Human Studies Division, Chapel Hill, NC, 3 Dept of Epidemiology and Environmental Health, Harvard School of Public Health, Boston, MA, 4 Dept of Pediatrics, Case Western Reserve University, Rainbow Babies & Children's Hospital, Cleveland, OH and 5 Dept of Public Health Biology and Epidemiology, University of California, Berkeley, CA, USA
CORRESPONDENCE: K.M. Mortimer, School of Public Health, 1918 University Ave, University of California, Berkeley, CA 94720-7370, USA. Fax: 15 106430239. E-mail: kmort@uclink4.berkeley.edu
Keywords: air pollution, asthma, generalized estimating equations, inner-city, mixed linear models
Received: July 9, 2001
Accepted December 16, 2001
The NCICAS research was supported by grants U01 AI-30751, AI-30752, AI-30756, AI-30772, AI-30773, AI-30777, AI-30779, AI30780, and AI-15105 from NIAID, NIH.
| Abstract |
|---|
|
|
|---|
Daily air pollution concentrations were extracted from the Aerometric Information Retrieval System database from the Environment Protection Agency in the USA. Mixed linear models and generalized estimating equation models were used to evaluate the effects of several air pollutants (ozone, sulphur dioxide (SO2), nitrogen dioxide (NO2) and particles with a 50% cut-off aerodynamic diameter of 10 µm (PM10) on peak expiratory flow rate (PEFR) and symptoms in 846 children with a history of asthma (ages 49 yrs).
None of the pollutants were associated with evening PEFR or symptom reports. Only ozone was associated with declines in morning % PEFR (0.59% decline (95% confidence interval (CI) 0.131.05%) per interquartile range (IQR) increase in 5-day average ozone). In single pollutant models, each pollutant was associated with an increased incidence of morning symptoms: (odds ratio (OR)=1.16 (95% CI 1.021.30) per IQR increase in 4-day average ozone, OR=1.32 (95% CI 1.031.70) per IQR increase in 2-day average SO2, OR=1.48 (95% CI 1.022.16) per IQR increase in 6-day average NO2 and OR=1.26 (95% CI 1.01.59) per IQR increase in 2-day average PM10.
This longitudinal analysis supports previous time-series findings that at levels below current USA air-quality standards, summer-air pollution is significantly related to symptoms and decreased pulmonary function among children with asthma.
Much of the evidence for the effect of air pollution on respiratory health 18 is based on time-series analyses of repeated measurements in closed cohorts, which create a daily summary of responses across all study individuals. Fluctuations in this summary measure are evaluated relative to daily fluctuations in air pollution. Therefore, these approaches are not well suited to investigations of individual-level factors related to heterogeneity of response. Time-series analyses require that the distribution of individual-level factors in the study population remain stable over time 9 or that data on changes in these characteristics are included in the model. This limits their usefulness in studying populations which do not remain fixed during the study period.
Longitudinal analysis techniques such as mixed linear models and generalized estimating equations provide a more statistically powerful alternative by incorporating individual level outcomes and covariates. They permit estimation of individual mean effects and individual change over time as well as population mean effects over the entire study period. These methods require no assumptions about stability of population characteristics over time and subjects with incomplete data can be included in the analysis 10. Therefore these methods are well-suited for epidemiological studies.
These methods were used to evaluate air pollution-related health effects in a large cohort of inner-city children with asthma. Individual-level risk factors that modified the response to ozone in this cohort have been reported previously 11. In particular, it was found that asthmatic children born prematurely (<37 weeks) or with a low birth weight (<2.5 kg) had a significantly greater response to increases in ozone. This study compares these results to time-series and other analyses and presents multipollutant models.
| Design and methods |
|---|
|
|
|---|
30% of residents was below the federal poverty level. Study children had either: 1) parental report of physician-diagnosed asthma and symptoms in the past 12 months or 2) respiratory symptoms consistent with asthma, such as cough, wheezing or shortness of breath, that lasted >6 weeks during the previous year, together with increased symptoms with exercise or cold air exposure or a family history of asthma. The protocol included an in-person baseline interview, a home survey, three brief telephone follow-up interviews at three-month intervals, and two-week peak expiratory flow rate (PEFR) and symptom diaries after the baseline interview and prior to each follow-up interview. To reduce confounding by temperature and seasonal infectious disease, this analysis is restricted to those children who returned at least one diary during JuneAugust of 1993.
Exposure measures
Air pollutant concentrations were obtained from the Aerometric Information Retrieval System of the Environmental Protection Agency in the USA. Daily pollutant metrics were calculated by averaging hourly readings for selected periods, based on peak occurrences, which are noted in the section on each pollutant. Multiday metrics were calculated by averaging these daily metrics. Children within the same urban area were assigned common daily and multiday values for each pollutant, calculated by averaging the pollutant concentrations from all monitors in the corresponding county. Single and multipollutant models are presented. Pollutants are often highly correlated, and consequently this report focuses on ozone as a good marker for summer air pollution in the NCICAS cities. Weather data were obtained from local airports.
Outcome measures
Children were trained in the use of a mini-Wright peak flow meter (Clement Clarke, Columbus, OH, USA). PEFR and symptoms (cough, chest tightness, wheeze) were reported in the morning upon rising, and before bedtime, prior to use of any inhaled medications. The maximum of three manoeuvres, performed while standing, was recorded. NCICAS was not an intervention and parents were not instructed on the interpretation of PEFR. Values <70 or >450 L·min1 (0.4% and 2.5% of readings, respectively) were considered to be implausible (e.g. errors in transcription) and were deleted.
Three outcome measures were evaluated separately for morning and evening: 1) daily per cent change from the diary-specific median PEFR; 2) the incidence of
10% decline from the diary-specific median PEFR; 3) the incidence of any symptom. Changes in PEFR (rather than mean levels) and incidence (rather than prevalence) were evaluated to focus on the impact of air-pollution level on changes in morbidity.
Statistical methods
The per cent change in PEFR was analysed using linear mixed effect models (SAS Proc Mixed 13), while the incidence of symptoms and incidence of a 10% decline in median PEFR were modelled with generalized estimating equations, using a logistic link. Change-in-estimate criteria and likelihood ratio tests were used to determine the choice of covariates, with an alpha level of 0.05. Akaike's Information Criteria (AIC) was used to evaluate the best correlation structure and to determine if a covariate should be entered as a fixed or random effect. Models with the AIC closest to zero were considered to best fit the data. Standard errors were insensitive to the use of several covariance structures, therefore results from models assuming the most simple structure (independence) were reported.
Lagged air pollution effects were evaluated using moving averages, unrestricted distributed lags, and polynomial distributed lags. Within-model lag-specific estimates were combined to create a cumulative effect over a specified interval and estimates were then compared across models.
| Results |
|---|
|
|
|---|
2 asthma medications in the previous three months (an indicator of asthma severity) were more likely to have returned diaries (table 1
|
|
|
No association was seen between single or multiday ozone metrics and any evening outcome measure (table 2
). The effect of ozone on morning outcomes increased over several days and the strongest association was seen for multiday moving averages. A 15 ppb increase in 5-day moving average ozone was associated with a 0.59% decline in morning PEFR (95% CI 0.131.05) and with the incidence of a
10% decline in morning PEFR (OR=1.14, 95% CI 1.021.27). The incidence of morning symptoms was most strongly associated with a 4-day moving average (OR=1.16, 95% CI 1.021.30.) The effect of the corresponding multiday lags on each evening outcome is presented for comparison purposes (i.e. average of lag 04 for evening measures can be compared to the average of lag 15 for morning measures).
For morning PEFR, cumulative effects from unrestricted lag, second degree polynomial distributed lag, and moving average models were nearly identical (cumulative declines=0.54%, 0.51%, and 0.59%). Unrestricted lag models suggested that the ozone exposures from 35 days prior have a greater impact on morning %PEFR than more immediate exposures. The 5-day average (lags 15) showed a slightly greater effect than a 3-day average (lags 35) or 4-day average (lags 25) (data not shown), despite the fact that the estimates from models using lags 1 and 2 suggested little increased risk. For morning symptoms, unrestricted lag, polynomial distributed lag, and moving average models yielded similar cumulative estimates (OR=1.13, 1.14, 1.14, respectively).
Excluding days when ozone was >80 ppb (proposed US Federal Standard) provided estimates which were nearly identical findings to those obtained using all of the days (0.70% decline in PEFR (95% CI 0.121.29%), OR=1.15 (95% CI 0.991.33) for a 10% decline in morning PEFR, OR=1.17 (95% CI 1.011.35) for the incidence of morning symptoms).
The consistency of urban area-specific estimates was evaluated by adding an "ozone by urban area" interaction term to each model. Interaction terms were null. In fact, with the exception of the Baltimore centre, the estimates for morning %PEFR were strikingly similar across urban areas (table 3
). In all areas except St. Louis, the increase in ozone was associated with an increase in the incidence of morning symptoms.
|
Co-pollutants
Sulphur dioxide (SO2), nitrogen dioxide (NO2), and particles with a 50% cut-off aerodynamic diameter of 10 µm (PM10) were evaluated using models similar to the ozone models described earlier. Estimates for evening effects were null (data not shown). Only morning %PEFR and symptom incidence findings are presented (table 4
).
|
Daily NO2 was available in seven urban areas (nearly 10,000 child days), with an average intradiary range of 32 ppb. The correlation between 8-h mean ozone and 4-h NO2 (06:0010:00 h) was 0.27. NO2 was not associated with declines in %PEFR and the greatest effect on morning symptoms was for a 6-day moving average. Joint modelling of NO2 and ozone slightly reduced the estimates for each pollutant.
Daily PM10 was measured only in Chicago, Cleveland and Detroit (>3,000 child days,) with an average intradiary range of 53 µg·m3. The correlation between 24-h average PM10 and 8-h average ozone was 0.51. Although there were no statistically significant effects of PM10 on morning %PEFR, estimates were negative and of similar magnitude to those found for ozone (0.89% decline per 25 µg·m3 increase in 6-day moving average, 95% CI 0.542.31% decline). Significant effects on evening %PEFR were found only at much greater lags (8 days). None of the lags of PM10 were associated with the incidence of evening symptoms. In a single-pollutant model, the strongest association with morning symptoms was seen for a 2-day average. Entering PM10 and ozone in the model simultaneously resulted in a slight reduction in the PM10 estimate, but a larger reduction in the ozone estimate and wider confidence intervals (table 4
).
Each individual pollutant was associated significantly with an increase in the incidence of morning symptoms. Multiday lags with the strongest associations in each of the single-pollutant models were simultaneously entered into a model. When restricted to the seven urban areas with complete data for ozone, SO2 and NO2, only SO2 remained significantly associated with morning symptoms. Models with all four pollutants were restricted to the three urban areas with complete data. Estimates for most pollutants were positive, however the confidence intervals were wide due to the substantially smaller sample size and colinearity among pollutants.
| Discussion |
|---|
|
|
|---|
Small declines in PEFR may be of questionable clinical significance. There were, however, significant associations with the incidence of
10% declines in PEFR and symptoms that clearly have clinical importance to asthma morbidity 22. The consistency of these effects suggests that despite known limitations 23, the peak flow data effectively captured important decrements in pulmonary function. Nondifferential misclassification of outcome and exposure data may have contributed to an underestimate of the effects. Also, a report published previously 10 has identified subgroups with more clinically important responses to air pollution. Future analyses of the health effects of air pollution would benefit from the inclusion of individual-level risk factors, which can greatly modify the size of the health effect.
The effects on PEFR and symptoms were limited primarily to morning measures. Morning values are better indicators of asthmatics who are susceptible to airway narrowing 24, and, therefore, focusing on morning measures may identify children at greater risk for adverse health outcomes. The most severe bronchoconstriction occurs in the morning, when measurable differences between and within individuals may be greatest. Alternatively, the lack of association with evening measures may be due to the use of asthma medication during the day, which may attenuate the association with air pollution and daily peak flow and symptom reports 1, 25. The lack of evening effects may reflect misclassification due to an inability to adjust for time the child spent outdoors or exercising, both of which affect respiratory dose 26. Controlling for these factors may improve the estimates 4.
Only three of the urban areas had daily PM10 monitors, making the sample size too small to allow for unambiguous assessment of multipollutant models. In these three cities, however, a stronger association was seen for PM10 than ozone, and, as others have reported PM10 was more strongly associated with asthma symptoms rather than PEFR 3. Delfino et al. 1 reported that 8-h maximum PM10 was more highly associated with morbidity than the 24-h PM10 measurements. It was not possible to test that hypothesis with existing monitoring data.
Biological mechanisms for delayed effects on pulmonary function include increased bronchial reactivity secondary to airway inflammation associated with irritant exposures. Animal and chamber studies suggest that exposure to air pollution may augment airway cellular infiltration and cellular activation, enhance release of cytotoxic inflammatory mediators, alter membrane permeability, and alter mucociliary clearance 2729. Given the lengthy lag times for ozone, PM10 and NO2 effects, ambient pollutants may not only be acting as a direct trigger of asthma attacks, but may also act indirectly as a primer for a subsequent antigen exposure 30, 31. While ozone was most influential on PEFR, NO2 had the strongest effect on symptoms. NO2 may be a better marker for the summer-pollutant mix in these cities, largely east of the Mississippi, in that it is related to the photochemistry of ozone and the emissions of hydrocarbons that accompany particle pollutants released from automobiles.
These findings are not likely to be confounded by asthma risk factors such as allergen sensitization and housing characteristics since they do not vary within the two-week monitoring interval. Medication or air conditioner use and exposure to tobacco smoke may vary daily, however, those data were not available. The similarity of the quantitative group mean estimates to those from time-series analyses discussed earlier, however, suggests that confounding does not explain the results.
In conclusion, summer-time air pollution is associated with increased asthma morbidity and decreased pulmonary function among inner-city children with asthma in the USA. These findings from generalized estimating equations and mixed models support previously published reports from time-series analysis, and those reported from less urban populations. The impact of pollution was not immediate, but developed over several days, with the largest effects seen on morning outcomes. Nitrogen dioxide, sulphur dioxide, and particles with a 50% cut-off aerodynamic diameter of 10 µm were associated with increases in symptoms, with nitrogen dioxide exhibiting the strongest influence. Ozone was most influential on peak expiratory flow rate. Adverse respiratory effects were observed in all cities, at levels below proposed USA air quality standards.
| Acknowledgements |
|---|
|
|
|---|
The contents of this report are solely the responsibility of the authors and do not necessarily represent the official views of the Environmental Protection Agency (EPA). The research described in this article has been subject to EPA's peer and administrative review and it has been approved for publication.
| References |
|---|
|
|
|---|
This article has been cited by other articles:
![]() |
Z J Andersen, S Loft, M Ketzel, M Stage, T Scheike, M N Hermansen, and H Bisgaard Ambient air pollution triggers wheezing symptoms in infants Thorax, August 1, 2008; 63(8): 710 - 716. [Abstract] [Full Text] [PDF] |
||||
![]() |
F. Forastiere and A. Faustini Are we understanding the respiratory effects of traffic related airborne particles? Thorax, July 1, 2008; 63(7): 574 - 576. [Full Text] [PDF] |
||||
![]() |
J. S. Schildcrout and P. J. Heagerty On outcome-dependent sampling designs for longitudinal binary response data with time-varying covariates Biostat., March 27, 2008; (2008) kxn006v1. [Abstract] [Full Text] [PDF] |
||||
![]() |
J. S. Schildcrout, L. Sheppard, T. Lumley, J. C. Slaughter, J. Q. Koenig, and G. G. Shapiro Ambient Air Pollution and Asthma Exacerbations in Children: An Eight-City Analysis Am. J. Epidemiol., September 15, 2006; 164(6): 505 - 517. [Abstract] [Full Text] [PDF] |
||||
![]() |
F. D. Martinez Toward Asthma Prevention -- Does All That Really Matters Happen before We Learn to Read? N. Engl. J. Med., October 9, 2003; 349(15): 1473 - 1475. [Full Text] [PDF] |
||||
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |