Assessing Adverse Health Effects of Long-Term Exposure to Low Levels of Ambient Air Pollution: Implementation of Causal Inference Methods.

This report provides a final summary of the principal findings and key conclusions of a study supported by an HEI grant aimed at "Assessing Adverse Health Effects of Long-Term Exposure to Low Levels of Ambient Air Pollution." It is the second and final report on this topic. The study was designed to advance four critical areas of inquiry and methods development. First, it focused on predicting short- and long-term exposures to ambient fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) at high spatial resolution (1 km × 1 km) for the continental United States over the period 2000-2016 and linking these predictions to health data. Second, it developed new causal inference methods for estimating exposure-response (ER) curves (ERCs) and adjusting for measured confounders. Third, it applied these methods to claims data from Medicare and Medicaid beneficiaries to estimate health effects associated with short- and long-term exposure to low levels of ambient air pollution. Finally, it developed pipelines for reproducible research, including approaches for data sharing, record linkage, and statistical software. Our HEI-funded work has supported an extensive portfolio of analyses and the development of statistical methods that can be used to robustly understand the health effects of short- and long-term exposure to low levels of ambient air pollution. Our Phase 1 report (Dominici et al. 2019) provided a high-level overview of our statistical methods, data analysis, and key findings, grouped into the following five areas: (1) exposure prediction, (2) epidemiological studies of ambient exposures to air pollution at low levels, (3) sensitivity analysis, (4) methodological contributions in causal inference, and (5) an open access research data platform. The current, final report includes a comprehensive overview of the entire research project.Considering our (1) massive study population, (2) numerous sensitivity analyses, and (3) transparent assessment of covariate balance indicating the quality of causal inference for simulating randomized experiments, we conclude that conditionally on the required assumptions for causal inference, our results collectively indicate that long-term PM2.5 exposure is likely to be causally related to mortality. This conclusion assumes that the causal inference assumptions hold and, more specifically, that we accounted adequately for confounding bias. We explored various modeling approaches, conducted extensive sensitivity analyses, and found that our results were robust across approaches and models. This work relied on publicly available data, and we have provided code that allows for reproducibility of our analyses.Our work provides comprehensive evidence of associations between exposures to PM2.5, NO2, and O3 and various health outcomes. In the current report, we report more specific results on the causal link between long-term exposure to PM2.5 and mortality, even at PM2.5 levels below or equal to 12 µg/m3, and mortality among Medicare beneficiaries (ages 65 and older). This work relies on newly developed causal inference methods for continuous exposure.For the period 2000-2016, we found that all statistical approaches led to consistent results: a 10-µg/m3 decrease in PM2.5 led to a statistically significant decrease in mortality rate ranging between 6% and 7% (= 1 - 1/hazard ratio [HR]) (HR estimates 1.06 [95% CI, 1.05 to 1.08] to 1.08 [95% CI, 1.07 to 1.09]). The estimated HRs were larger when studying the cohort of Medicare beneficiaries that were always exposed to PM2.5 levels lower than 12 µg/m3 (1.23 [95% CI, 1.18 to 1.28] to 1.37 [95% CI, 1.34 to 1.40]).Comparing the results from multiple and single pollutant models, we found that adjusting for the other two pollutants slightly attenuated the causal effects of PM2.5 and slightly elevated the causal effects of NO2 exposure on all-cause mortality. The results for O3 remained almost unchanged.We found evidence of a harmful causal relationship between mortality and long-term PM2.5 exposures adjusted for NO2 and O3 across the range of annual averages between 2.77 and 17.16 µg/m3 (included >98% of observations) in the entire cohort of Medicare beneficiaries across the continental United States from 2000 to 2016. Our results are consistent with recent epidemiological studies reporting a strong association between long-term exposure to PM2.5 and adverse health outcomes at low exposure levels. Importantly, the curve was almost linear at exposure levels lower than the current national standards, indicating aggravated harmful effects at exposure levels even below these standards.There is, in general, a harmful causal impact of long-term NO2 exposures to mortality adjusted for PM2.5 and O3 across the range of annual averages between 3.4 and 80 ppb (included >98% of observations). Yet within low levels (annual mean ≤53 ppb) below the current national standards, the causal impacts of NO2 exposures on all-cause mortality are nonlinear with statistical uncertainty.The ERCs of long-term O3 exposures on all-cause mortality adjusted for PM2.5 and NO2 are almost flat below 45 ppb, which shows no statistically significant effect. Yet we observed an increased hazard when the O3 exposures were higher than 45 ppb, and the HR was approximately 1.10 when comparing Medicare beneficiaries with annual mean O3 exposures of 50 ppb versus those with 30 ppb.institutions, including those that support the Health Effects Institute; therefore, it may not reflect the views or policies of these parties, and no endorsement by them should be inferred.A list of abbreviations and other terms appears at the end of this volume.

Seasonality of suicide: a multi-country multi-community observational study.

AIMS: We aimed to investigate the heterogeneity of seasonal suicide patterns among multiple geographically, demographically and socioeconomically diverse populations. METHODS: Weekly time-series data of suicide counts for 354 communities in 12 countries during 1986-2016 were analysed. Two-stage analysis was performed. In the first stage, a generalised linear model, including cyclic splines, was used to estimate seasonal patterns of suicide for each community. In the second stage, the community-specific seasonal patterns were combined for each country using meta-regression. In addition, the community-specific seasonal patterns were regressed onto community-level socioeconomic, demographic and environmental indicators using meta-regression. RESULTS: We observed seasonal patterns in suicide, with the counts peaking in spring and declining to a trough in winter in most of the countries. However, the shape of seasonal patterns varied among countries from bimodal to unimodal seasonality. The amplitude of seasonal patterns (i.e. the peak/trough relative risk) also varied from 1.47 (95% confidence interval [CI]: 1.33-1.62) to 1.05 (95% CI: 1.01-1.1) among 12 countries. The subgroup difference in the seasonal pattern also varied over countries. In some countries, larger amplitude was shown for females and for the elderly population (≥65 years of age) than for males and for younger people, respectively. The subperiod difference also varied; some countries showed increasing seasonality while others showed a decrease or little change. Finally, the amplitude was larger for communities with colder climates, higher proportions of elderly people and lower unemployment rates (p-values < 0.05). CONCLUSIONS: Despite the common features of a spring peak and a winter trough, seasonal suicide patterns were largely heterogeneous in shape, amplitude, subgroup differences and temporal changes among different populations, as influenced by climate, demographic and socioeconomic conditions. Our findings may help elucidate the underlying mechanisms of seasonal suicide patterns and aid in improving the design of population-specific suicide prevention programmes based on these patterns.

Assessing Adverse Health Effects of Long-Term Exposure to Low Levels of Ambient Air Pollution: Phase 1.

INTRODUCTION: This report provides a summary of major findings and key conclusions supported by a Health Effects Institute grant aimed at "Assessing Adverse Health Effects of Long-Term Exposure to Low Levels of Ambient Pollution." Our study was designed to advance four critical areas of inquiry and methods development. METHODS: First, our work focused on predicting short- and long-term exposures to ambient PM2.5 mass (particulate matter ≤ 2.5µm in aerodynamic diameter) and ozone (O3) at high spatial resolution (1 km × 1 km) for the continental United States during the period 2000-2012 and linking these predictions to health data. Second, we developed new causal inference methods for exposure-response (ER) that account for exposure error and adjust for measured confounders. We applied these methods to data from the New England region. Third, we applied standard regression methods using Medicare claims data to estimate health effects that are associated with short- and long-term exposure to low levels of ambient air pollution. We conducted sensitivity analyses to assess potential confounding bias due to lack of extensive information on behavioral risk factors in the Medicare population using the Medicare Current Beneficiary Survey (MCBS) (nationally representative sample of approximately 15,000 Medicare enrollees per year), which includes abundant data on individual-level risk factors including smoking. Finally, we have begun developing tools for reproducible research - including approaches for data sharing, record linkage, and statistical software. RESULTS: Our HEI-funded work has supported an extensive portfolio of analysis and the development of statistical methods that can be used to robustly understand the health effects of long- and short-term exposure to low levels of ambient air pollution. This report provides a high-level overview of statistical methods, data analysis, and key findings, as grouped into the following four areas: (1) Exposure assessment and data access; (2) Epidemiological studies of ambient exposures to air pollution at low levels; (3) Methodological contributions in causal inference; and (4) Open science research data platform. CONCLUSION: Our body of work, advanced by HEI, lends extensive evidence that short- and long-term exposure to PM2.5 and O3 is harmful to human health, increasing the risks of hospitalization and death, even at levels that are well below the National Ambient Air Quality Standards (NAAQS).

Prenatal and early life exposure to traffic pollution and cardiometabolic health in childhood.

BACKGROUND: Prenatal exposure to traffic pollution has been associated with faster infant weight gain, but implications for cardiometabolic health in later childhood are unknown. METHODS: Among 1418 children in Project Viva, a Boston-area pre-birth cohort, we assessed anthropometric and biochemical parameters of cardiometabolic health in early (median age 3.3 years) and mid- (median age 7.7 years) childhood. We used spatiotemporal models to estimate prenatal and early life residential PM2.5 and black carbon exposure as well as traffic density and roadway proximity. We performed linear regression analyses adjusted for sociodemographics. RESULTS: Children whose mothers lived close to a major roadway at the time of delivery had higher markers of adverse cardiometabolic risk in early and mid-childhood. For example, total fat mass was 2.1 kg (95%CI: 0.8, 3.5) higher in mid-childhood for children of mothers who lived <50 m vs. ≥200 m from a major roadway. Black carbon exposure and traffic density were generally not associated with cardiometabolic parameters, and PM2.5 exposure during the year prior was paradoxically associated with improved cardiometabolic profile. CONCLUSIONS: Infants whose mothers lived close to a major roadway at the time of delivery may be at later risk for adverse cardiometabolic health.

Effects of airborne fine particles (PM2.5 ) on deep vein thrombosis admissions in the northeastern United States.

BACKGROUND: Literature relating air pollution exposure to deep vein thrombosis (DVT) and pulmonary embolism (PE), despite biological plausibility, is sparse. No comprehensive study examining associations between both short- and long-term exposure to particulate matter (PM)2.5 and DVT or PE has been published. Using a novel PM2.5 prediction model, we study whether long- and short-term PM2.5 exposure is associated with DVT and PE admissions among elderly across the northeastern United States. METHODS: We estimated daily exposure of PM2.5 in each ZIP code. We investigated the long- and short-term effects of PM2.5 on DVT and PE hospital admissions. There were 453,413 DVT and 151,829 PE admissions in the study. For short-term exposure, we performed a case crossover analysis matching month and year and defined the hazard period as lag 01 (exposure of day of admission and previous day). For the long-term association, we used a Poisson regression. RESULTS: A 10-µg m(-3) increase in short-term exposure was associated with a 0.63% increase in DVT admissions (95% confidence interval [CI] = 0.03% to 1.25%) and a 6.98% (95% CI = 5.65% to 8.33%) increase in long-term exposure admissions. For PE, the associated risks were 0.38% (95% CI = -0.68% to 1.25%) and 2.67% (95% CI = 5.65% to 8.33%). These results persisted when analyses were restricted to location-periods meeting the current Environmental Protection Agency annual standard of 12 µg m(-3) . CONCLUSIONS: Our findings showed that PM2.5 exposure was associated with DVT and PE hospital admissions and that current standards are not protective of this result.

The temporal pattern of mortality responses to ambient ozone in the APHEA project.

BACKGROUND: The temporal pattern of effects of summertime ozone (O(3)) in total, cardiovascular and respiratory mortality were investigated in 21 European cities participating in the APHEA-2 (Air Pollution and Health: a European Approach) project, which is fundamental in determining the importance of the effect in terms of life loss. METHODS: Data from each city were analysed separately using distributed lag models with up to 21 lags. City-specific air pollution estimates were regressed on city-specific covariates to obtain overall estimates and to explore sources of possible heterogeneity. RESULTS: Stronger effects on respiratory mortality that extend to a period of 2 weeks were found. A 10 microg/m(3) increase in O(3) was associated with a 0.36% (95% CI -0.21% to 0.94%) increase in respiratory deaths for lag 0 and with 3.35% (95% CI 1.90% to 4.83%) for lags 0-20. Significant adverse health effects were found of summer O(3) (June-August) on total and cardiovascular mortality that persist up to a week, but are counterbalanced by negative effects thereafter. CONCLUSIONS: The results indicate that studies on acute health effects of O(3) using single-day exposures may have overestimated the effects on total and cardiovascular mortality, but underestimated the effects on respiratory mortality.

Indoor NO2 air pollution and lung function of professional cooks.

Studies of cooking-generated NO2 effects are rare in occupational epidemiology. In the present study, we evaluated the lung function of professional cooks exposed to NO2 in hospital kitchens. We performed spirometry in 37 cooks working in four hospital kitchens and estimated the predicted FVC, FEV1 and FEF(25-75), based on age, sex, race, weight, and height, according to Knudson standards. NO2 measurements were obtained for 4 consecutive days during 4 different periods at 20-day intervals in each kitchen. Measurements were performed inside and outside the kitchens, simultaneously using Palm diffusion tubes. A time/exposure indicator was defined as representative of the cumulative exposure of each cook. No statistically significant effect of NO2 exposure on FVC was found. Each year of work as a cook corresponded to a decrease in predicted FEV1 of 2.5% (P = 0.046) for the group as a whole. When smoking status and asthma were included in the analysis the effect of time/exposure decreased about 10% and lost statistical significance. On predicted FEF(25-75), a decrease of 3.5% (P = 0.035) was observed for the same group and the inclusion of controllers for smoking status and asthma did not affect the effects of time/exposure on pulmonary function parameter. After a 10-year period of work as cooks the participants of the study may present decreases in both predicted FEV1 and FEF(25-75) that can reach 20 and 30%, respectively. The present study showed small but statistically significant adverse effects of gas stove exposure on the lung function of professional cooks.

Indoor NO2 air pollution and lung function of professional cooks

Studies of cooking-generated NO2 effects are rare in occupational epidemiology. In the present study, we evaluated the lung function of professional cooks exposed to NO2 in hospital kitchens. We performed spirometry in 37 cooks working in four hospital kitchens and estimated the predicted FVC, FEV1 and FEF25-75, based on age, sex, race, weight, and height, according to Knudson standards. NO2 measurements were obtained for 4 consecutive days during 4 different periods at 20-day intervals in each kitchen. Measurements were performed inside and outside the kitchens, simultaneously using Palm diffusion tubes. A time/exposure indicator was defined as representative of the cumulative exposure of each cook. No statistically significant effect of NO2 exposure on FVC was found. Each year of work as a cook corresponded to a decrease in predicted FEV1 of 2.5 percent (P = 0.046) for the group as a whole. When smoking status and asthma were included in the analysis the effect of time/exposure decreased about 10 percent and lost statistical significance. On predicted FEF25-75, a decrease of 3.5 percent (P = 0.035) was observed for the same group and the inclusion of controllers for smoking status and asthma did not affect the effects of time/exposure on pulmonary function parameter. After a 10-year period of work as cooks the participants of the study may present decreases in both predicted FEV1 and FEF25-75 that can reach 20 and 30 percent, respectively. The present study showed small but statistically significant adverse effects of gas stove exposure on the lung function of professional cooks.

Effects of exposure to air pollution on blood coagulation.

BACKGROUND: Consistent evidence has indicated that air pollution increases the risk of cardiovascular diseases. The underlying mechanisms linking air pollutants to increased cardiovascular risk are unclear. OBJECTIVES: We investigated the association between the pollution levels and changes in such global coagulation tests as the prothrombin time (PT) and the activated partial thromboplastin time (APTT) in 1218 normal subjects from the Lombardia Region, Italy. Plasma fibrinogen and naturally occurring anticoagulant proteins were also evaluated. METHODS: Hourly concentrations of particulate (PM10) and gaseous pollutants (CO, NO2, SO2, and O3) were obtained from 53 monitoring sites covering the study area. Generalized additive models were applied to compute standardized regression coefficients controlled for age, gender, body mass index, smoking, alcohol, hormone use, temperature, day of the year, and long-term trends. RESULTS: The PT became shorter with higher ambient air concentrations at the time of the study of PM10 (coefficient = -0.06; P < 0.05), CO (coefficient = -0.11; P < 0.001) and NO2 (coefficient =-0.06; P < 0.05). In the 30 days before blood sampling, the PT was also negatively associated with the average PM(10) (coefficient = -0.08; P < 0.05) and NO2 (coefficient = -0.08; P < 0.05). No association was found between the APTT and air pollutant levels. In addition, no consistent relations with air pollution were found for fibrinogen, antithrombin, protein C and protein S. CONCLUSIONS: This investigation shows that air pollution is associated with changes in the global coagulation function, suggesting a tendency towards hypercoagulability after short-term exposure to air pollution. Whether these changes contribute to trigger cardiovascular events remains to be established.

Air pollution and inflammation in type 2 diabetes: a mechanism for susceptibility.

BACKGROUND: Particulate air pollution has been associated with several adverse cardiovascular health outcomes, and people with diabetes may be especially vulnerable. One potential pathway is inflammation and endothelial dysfunction-processes in which cell adhesion molecules and inflammatory markers play important roles. AIM: To examine whether plasma levels of soluble intercellular adhesion molecule 1 (ICAM-1), vascular cell adhesion molecule 1 (VCAM-1) and von Willebrand factor (vWF) were associated with particle exposure in 92 Boston area residents with type 2 diabetes. METHODS: Daily average ambient levels of air pollution (fine particles (PM2.5), black carbon (BC) and sulphates) were measured approximately 500 m from the patient examination site and evaluated for associations with ICAM-1, VCAM-1 and vWF. Linear regressions were fit to plasma levels of ICAM-1, VCAM-1 and vWF, with the particulate pollutant index, apparent temperature, season, age, race, sex, glycosylated haemoglobin, cholesterol, smoking history and body mass index as predictors. RESULTS: Air pollutant exposure measures showed consistently positive point estimates of association with the inflammatory markers. Among participants not taking statins and those with a history of smoking, associations between PM(2.5), BC and VCAM-1 were particularly strong. CONCLUSIONS: These results corroborate evidence suggesting that inflammatory mechanisms may explain the increased risk of air pollution-associated cardiovascular events among those with diabetes.

Short term effects of particulate matter on cause specific mortality: effects of lags and modification by city characteristics.

BACKGROUND: Consistent evidence has shown increased all-cause mortality, and mortality from broad categories of causes associated with airborne particles. Less is known about associations with specific causes of death, and modifiers of those associations. AIMS: To examine these questions in 20 US cities, between 1989 and 2000. METHODS: Mortality files were obtained from the National Center for Health Statistics. Air pollution data were obtained from the Environmental Protection Agency website. The associations between daily concentrations of particulate matter of aero-diameter < or =10 microm (PM10) and daily mortality from all-cause and selected causes of death, were examined using a case-crossover design. Temporal effects of PM10 were examined using lag models, in first stage regressions. City specific modifiers of these associations were examined in second stage regressions. RESULTS: All-cause mortality increased with PM10 exposures occurring both one and two days prior the event. Deaths from heart disease were primarily associated with PM10 on the two days before, while respiratory deaths were associated with PM10 exposure on all three days. Analyses using only one lag underestimated the effects for all-cause, heart, and respiratory deaths. Several city characteristics modified the effects of PM10 on daily mortality. Important findings were seen for population density, percentage of primary PM10 from traffic, variance of summer temperature, and mean of winter temperature. CONCLUSIONS: There was overall evidence of increased daily mortality from increased concentrations of PM10 that persisted across several days, and matching for temperature did not affect these associations. Heterogeneity in the city specific PM10 effects could be explained by differences in certain city characteristics.

Traffic related pollution and heart rate variability in a panel of elderly subjects.

BACKGROUND: Particulate air pollution has been associated with increased cardiovascular deaths and hospital admissions. To help understand the mechanisms, the types of particles most involved, and the types of persons most susceptible, the association between exposure to summertime air pollution and heart rate variability (HRV) was examined in a panel study of 28 elderly subjects. METHODS: Subjects were seen once a week for up to 12 weeks and HRV (SDNN, r-MSSD, PNN50, low frequency/high frequency ratio (LFHFR)) was measured for approximately 30 minutes at each session using a defined protocol. Temperature, day of the week, and hour of the day were controlled, and dummy variables for each subject were controlled for subject specific risk factors. RESULTS: PM2.5 was associated with r-MSSD (-10.1% change for an interquartile range (IQR) increase in exposure (95% CI -2.8 to -16.9)) and PNN50, but stronger associations were seen with black carbon, an indicator of traffic particles, which was also associated with SDNN (-4.6% per IQR (95% CI -2.0 to -7.2)) and LFHFR. Secondary particles were more weakly associated with r-MSSD, as was ozone. No associations were seen with SO2 or NO2. CO had similar patterns of association to black carbon, which disappeared after controlling for black carbon. Black carbon had a substantially higher effect on SDNN in subjects who had had a previous myocardial infarction (-12.7%, 95% CI -5.7 to -19.25). CONCLUSIONS: Particles, especially from traffic, are associated with disturbances of autonomic control of the heart.

Investigating the dose-response relation between air pollution and total mortality in the APHEA-2 multicity project.

BACKGROUND: Several recent studies have reported significant health effects of air pollution even at low levels of air pollutants, but in most of these studies linear non-threshold relations were assumed. AIMS: To investigate the NO2 mortality dose-response association in nine cities participating in the APHEA-2 project using two different methods: the meta-smooth and the cubic spline method. METHODS: The meta-smooth method developed by Schwartz and Zanobetti is based on combining individual city non-parametric smooth curves; the cubic spline method developed within the APHEA-2 project combines individual city estimates of cubic spline shaped dose-response relations. The meta-smooth method is easier and faster to implement, but the cubic spline method is more flexible for further investigation of possible heterogeneity in the dose-response curves among cities. RESULTS: In the range of the pollutant common to all cities the two methods gave similar and comparable curves. Using the cubic spline method it was found that smoking prevalence acts as an effect modifier with larger NO2 effects on mortality at lower smoking prevalence. CONCLUSIONS: The NO2-mortality association in the cities included in the present analysis, could be adequately estimated using the linear model. However, investigation of the city specific dose-response curves should precede the application of linear models.

The lag structure between particulate air pollution and respiratory and cardiovascular deaths in 10 US cities.

To assess differences in the lag structure pattern between particulate matter < 10 microns/100 microns in diameter (PM10) and cause-specific mortality, we performed a time-series analysis in 10 US cities using generalized additive Poisson regressions in each city; nonparametric smooth functions were used to control for long time trend, weather, and day of the week. The PM10 effect was estimated based on its daily mean, 2-day moving average, and the cumulative 7-day effect by means of an unconstrained distributed lag model. A 10-microgram/m3 increase in the 7-day mean of PM10 was associated with increases in deaths due to pneumonia (2.7%, 95% confidence interval [CI]: 1.5, 3.9), chronic obstructive pulmonary disease (1.7%, 95% CI: 0.1, 3.3), and all cardiovascular diseases (1.0%, 95% CI: 0.6, 1.4). A 10-microgram/m3 increase in the 2-day mean of PM10 was associated with a 0.7% (95% CI: 0.3, 1.1) increase in deaths from myocardial infarction. When the distributed lag was assessed, two different patterns could be observed: respiratory deaths were more affected by air pollution levels on the previous days, whereas cardiovascular deaths were more affected by same-day pollution. These results contribute to the overall efforts so far in understanding how exposure to air pollution promotes adverse health effects.

The time course of weather-related deaths.

We carried out time-series analysis in 12 U.S. cities to estimate both the acute effects and the lagged influence of weather on total daily deaths. We fit generalized additive Poisson regressions for each city using nonparametric smooth functions to control for long time trend and barometric pressure. We also controlled for day of the week. We estimated the effect and the lag structure of both temperature and humidity on the basis of a distributed lag model. In cold cities, both high and low temperatures were associated with increased deaths. In general, the effect of cold temperatures persisted for days, whereas the effect of high temperatures was restricted to the day of the death or the immediately preceding day and was twice as large as the cold effect. The hot temperature effect appears to be primarily harvesting. In hot cities, neither hot nor cold temperatures had much effect on deaths. The magnitude of the effect of hot temperature varied with central air conditioning use and the variance of summertime temperatures. We saw no clear pattern for humidity effect. These dissimilarities indicate that analysis of the impact of any climatic change should take into account regional weather differences and harvesting.

Are diabetics more susceptible to the health effects of airborne particles?

Convincing evidence now exists that particulate air pollution exacerbates heart and lung disease, leading to increased morbidity and mortality. The populations particularly susceptible to these exposures are still unclear. Recent work on potential mechanisms of action of particulate air pollution point to pathways also influenced by diabetes. We examined whether diabetes modified the effect of airborne particles by looking at the association of PM(10) with hospital admissions for heart and lung disease in persons with or without diabetes as a comorbidity. In addition we stratified by age within persons with and without diabetes. We used Medicare data for Cook County, Illinois for the years 1988-1994, and found that a 10 microg/m(3) increase in PM(10) was associated with a 2.01% (95% CI 1.40-2.62%) increase in admissions for heart disease with diabetes, but only a 0.94% (95% CI 0.61-1.28%) increase in persons without diabetes. Similar effect modification was not seen for lung diseases. When analyzing by age we found twice the PM(10)-associated risk for heart disease in diabetics than nondiabetics in both age groups. We found for pneumonia admissions that diabetes is an effect modifier in the younger age group, and for COPD in the older age group. We conclude that persons with diabetes are a susceptible population.

Health effects of air pollution exposure on children and adolescents in São Paulo, Brazil.

Children and adolescents have been considered more susceptible to the effects of air pollution than adults. In order to investigate the responses of children of different ages to air pollution exposure, daily records of hospital admissions for children in five age groups (equal or less than 2 years of age, 3-5, 6-13, 14-19, and all ages together, i.e., from 0-19 years of age) were obtained from January 1993 to November 1997 in São Paulo, Brazil, and were compared to daily records of PM10, O3, SO2, CO and NO2 concentrations in ambient air. For each age group a generalized additive Poisson regression was fitted controlling for smooth functions of time, temperature, humidity, and days of the week, with an additional indicator for holidays. Polynomial distributed lag models were used to estimate the 7-day cumulative effect of each pollutant. Children 2 years or less were the most susceptible to the effects of all five pollutants with an increase of 9.4% (95% CI: 7.9,10.9) in respiratory admissions associated with each interquartile range increase in PM10. The oldest group was the second most susceptible to air pollutants, with each interquartile range increase in PM10 associated with a 5.1% (95% CI: 0.3,9.8) increase in respiratory admissions. An interquartile range increase in CO was associated with an 11.3% (95% CI: 5.9,16.8) increase in respiratory hospitalizations. When a multipollutant model was used, the effect of PM10 on respiratory admissions for all ages together was unchanged, while the SO2 and the other pollutants effect was substantially reduced. This study showed that daily respiratory hospital admissions for children and adolescents in São Paulo increased with air pollution, and that the largest effects were found for the youngest (2 years or less) and oldest (14-19 years) age groups.

Airborne particles are a risk factor for hospital admissions for heart and lung disease.

We examined the association between particulate matter [less than/equal to] 10 microm; (PM(10)) and hospital admission for heart and lung disease in ten U.S. cities. Our three goals were to determine whether there was an association, to estimate how the association was distributed across various lags between exposure and response, and to examine socioeconomic factors and copollutants as effect modifiers and confounders. We fit a Poisson regression model in each city to allow for city-specific differences and then combined the city-specific results. We examined potential confounding by a meta-regression of the city-specific results. Using a model that considered simultaneously the effects of PM(10) up to lags of 5 days, we found a 2.5% [95% confidence interval (CI), 1.8-3. 3] increase in chronic obstructive pulmonary disease, a 1.95% (CI, 1. 5-2.4) increase in pneumonia, and a 1.27% increase (CI, 1-1.5) in CVD for a 10 microg/m(3) increase in PM(10). We found similar effect estimates using the mean of PM(10) on the same and previous day, but lower estimates using only PM(10) for a single day. When using only days with PM(10) < 50 mg/m(3), the effect size increased by [greater/equal to] 20% for all three outcomes. These effects are not modified by poverty rates or minority status. The results were stable when controlling for confounding by sulfur dioxide, ozone, and carbon monoxide. These results are consistent with previous epidemiology and recent mechanistic studies in animals and humans.

Do respiratory epidemics confound the association between air pollution and daily deaths?

Daily deaths are associated with air pollution. This association might be con*hhy;founded by uncontrolled risk factors. In order to estimate the potential confounding caused by respiratory epidemics of the association between air pollution and health effects, a time series study of air pollution and daily deaths was carried out. Daily records of deaths for all ages were obtained from five US cities: Chicago, IL; Detroit, MI; Minneapolis, MN; Pittsburgh, PA; and Seattle, WA. Daily levels of particles with a 50% cut-off aerodynamic diameter of 10 microm (PM10) and weather measurements were obtained. City-specific analysis was carried out using Poisson regression, adjusting for time trend, ambient temperature, dew point, barometric pressure and day of the week. A cubic polynomial was used for each epidemic period (> or =10 days of excessive pneumonia hospital admissions), and a dummy variable was used to control for isolated epidemic days. A 10-microg x m(-3) increase in PM10 concentration (lag 0-1) was associated with increased daily deaths in Chicago (0.81%, 95% confidence internal (CI) 0.54-1.09); Detroit (0.87%, 95% CI 0.60-1.15), Minneapolis (1.34%, 95% CI 0.78-1.90), Pittsburgh (0.84%, 95% CI 0.51-1.18) and Seattle (0.52%, 95% CI 0.11-0.94). When controlling for respiratory epidemics, small decreases in the PMlo effect were observed (Chicago 9%, Detroit 11%, Minneapolis 3%, Pittsburgh 5%, and Seattle 15%). The overall effect of PM10 concentration was 0.85% (95% CI 0.60-1.10) per 10 microg x m(-3) before controlling for epidemics and 0.78% (95% CI 0.51-1.05) after. This study showed that the association between air pollution and daily deaths is not due to failure to control for influenza or pneumonia epidemics.

Are there sensitive subgroups for the effects of airborne particles?

Recent studies have shown that particulate air pollution is a risk factor for hospitalization for heart and lung disease; however, little is known about what subpopulations are most sensitive to this pollutant. We analyzed Medicare hospital admissions for heart disease, chronic obstructive pulmonary disorders (COPD) and pneumonia in Chicago, Cook County, Illinois, between 1985 and 1994. We examined whether previous admissions or secondary diagnoses for selected conditions predisposed persons to having a greater risk from air pollution. We also considered effect modification by age, sex, and race. We found that the air-pollution-associated increase in hospital admissions for cardiovascular diseases was almost doubled in subjects with concurrent respiratory infections. The risk was also increased by a previous admission for conduction disorders. For COPD and pneumonia admissions, diagnosis of conduction disorders or dysrhythmias increased the risk of particulate matter < 10 microm in aerodynamic diameter (PM(10))-associated admissions. Persons with asthma had twice the risk of a PM(10)-associated pneumonia admission and persons with heart failure had twice the risk of PM(10)-induced COPD admissions. The PM(10) effect did not vary by sex, age, and race. These results suggest that patients with acute respiratory infections or defects in the electrical control of the heart are a risk group for particulate matter effects.