The Concentration-Response Relation Between PM2.5_{2.5} and Daily Deaths.

Particulate air pollution at commonly occurring concentrations is associated with daily deaths. Recent attention has focused on the shape of the concentration-response curve, particularly at low doses. Several recent articles have reported that particulate matter with aerodynamic diameter $\leq 10 \mu$m PM$_{10}$) was associated with daily deaths with no evidence of a threshold. These reports have used smoothing or spline methods in individual cities and pooled the results across multiple cities to obtain estimates that are more robust. To date, fine particulate matter (aerodynamic diameter $\leq 2.5 \mu$m; PM$_{2.5}$), a component of PM$_{10}$, has not been examined in this regard. We examined this association in a hierarchical model in six U.S. cities. In the first stage, we fit log-linear models including smooth functions of PM$_{2.5}$ in each city, controlling for season, weather, and day of the week. These smooth functions allowed for nonlinearities in the city-specific associations. We combined the estimated curves across cities using a hierarchical model that allows for heterogeneity. We found an essentially linear relationship down to 2 $\mu$g/m$_3$. The same approach was applied to examine the concentration response to traffic particles, controlling for particles from other sources. Once again, the association showed no sign of a threshold. The magnitude of the association suggests that controlling fine particle pollution would result in thousands of fewer early deaths per year

Influenza epidemics, seasonality, and the effects of cold weather on cardiac mortality

Background: More people die in the winter from cardiac disease, and there are competing hypotheses to explain this. The authors conducted a study in 48 US cities to determine how much of the seasonal pattern in cardiac deaths could be explained by influenza epidemics, whether that allowed a more parsimonious control for season than traditional spline models, and whether such control changed the short term association with temperature. Methods: The authors obtained counts of daily cardiac deaths and of emergency hospital admissions of the elderly for influenza during 1992–2000. Quasi-Poisson regression models were conducted estimating the association between daily cardiac mortality, and temperature. Results: Controlling for influenza admissions provided a more parsimonious model with better Generalized Cross-Validation, lower residual serial correlation, and better captured Winter peaks. The temperature-response function was not greatly affected by adjusting for influenza. The pooled estimated increase in risk for a temperature decrease from 0 to −5°C was 1.6% (95% confidence interval (CI) 1.1-2.1%). Influenza accounted for 2.3% of cardiac deaths over this period. Conclusions: The results suggest that including epidemic data explained most of the irregular seasonal pattern (about 18% of the total seasonal variation), allowing more parsimonious models than when adjusting for seasonality only with smooth functions of time. The effect of cold temperature is not confounded by epidemics

The Effect of Particulate Air Pollution on Emergency Admissions for Myocardial Infarction: A Multicity Case-Crossover Analysis

Recently, attention has focused on whether particulate air pollution is a specific trigger of myocardial infarction (MI). The results of several studies of single locations assessing the effects of ambient particular matter on the risk of MI have been disparate. We used a multicity case-crossover study to examine risk of emergency hospitalization associated with fine particulate matter (PM) with aerodynamic diameter < 10 μm (PM(10)) for > 300,000 MIs during 1985–1999 among elderly residents of 21 U.S. cities. We used time-stratified controls matched on day of the week or on temperature to detect possible residual confounding by weather. Overall, we found a 0.65% [95% confidence interval (CI), 0.3–1.0%] increased risk of hospitalization for MI per 10 μg/m(3) increase in ambient PM(10) concentration. Matching on apparent temperature yielded a 0.64% increase in risk (95% CI, 0.1–1.2%). We found that the effect size for PM(10) doubled for subjects with a previous admission for chronic obstructive pulmonary disease or a secondary diagnosis of pneumonia, although these differences did not achieve statistical significance. There was a weaker indication of a larger effect on males but no evidence of effect modification by age or the other diagnoses. We also found that the shape of the exposure–response relationship between MI hospitalizations and PM(10) is almost linear, but with a steeper slope at levels of PM(10) < 50 μg/m(3). We conclude that increased concentrations of ambient PM(10) are associated with increased risk of MI among the elderly

The effect of weather on respiratory and cardiovascular deaths in 12 U.S. cities.

We carried out time-series analyses in 12 U.S. cities to estimate both the acute effects and the lagged influence of weather on respiratory and cardiovascular disease (CVD) deaths. We fit generalized additive Poisson regressions for each city using nonparametric smooth functions to control for long time trend, season, and barometric pressure. We also controlled for day of the week. We estimated the effect and the lag structure of both temperature and humidity based on a distributed lag model. In cold cities, both high and low temperatures were associated with increased CVD 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 day before. For myocardial infarctions (MI), the effect of hot days was twice as large as the cold-day effect, whereas for all CVD deaths the hot-day effect was five times smaller than the cold-day effect. The effect of hot days included some harvesting, because we observed a deficit of deaths a few days later, which we did not observe for the cold-day effect. In hot cities, neither hot nor cold temperatures had much effect on CVD or pneumonia deaths. However, for MI and chronic obstructive pulmonary disease deaths, we observed lagged effects of hot temperatures (lags 4-6 and lags 3 and 4, respectively). We saw no clear pattern for the effect of humidity. In hierarchical models, greater variance of summer and winter temperature was associated with larger effects for hot and cold days, respectively, on respiratory deaths

Associations of Fine Particulate Matter Species with Mortality in the United States: A Multicity Time-Series Analysis

Background: Epidemiological studies have examined the association between PM2.5 and mortality, but uncertainty remains about the seasonal variations in PM2.5-related effects and the relative importance of species. Objectives: We estimated the effects of PM2.5 species on mortality and how infiltration rates may modify the association. Methods: Using city–season specific Poisson regression, we estimated PM2.5 effects on approximately 4.5 million deaths for all causes, cardiovascular disease (CVD), myocardial infarction (MI), stroke, and respiratory diseases in 75 U.S. cities for 2000–2006. We added interaction terms between PM2.5 and monthly average species-to-PM2.5 proportions of individual species to determine the relative toxicity of each species. We combined results across cities using multivariate meta-regression, and controlled for infiltration. Results: We estimated a 1.18% (95% CI: 0.93, 1.44%) increase in all-cause mortality, a 1.03% (95% CI: 0.65, 1.41%) increase in CVD, a 1.22% (95% CI: 0.62, 1.82%) increase in MI, a 1.76% (95% CI: 1.01, 2.52%) increase in stroke, and a 1.71% (95% CI: 1.06, 2.35%) increase in respiratory deaths in association with a 10-μg/m3 increase in 2-day averaged PM2.5 concentration. The associations were largest in the spring. Silicon, calcium, and sulfur were associated with more all-cause mortality, whereas sulfur was related to more respiratory deaths. County-level smoking and alcohol were associated with larger estimated PM2.5 effects. Conclusions: Our study showed an increased risk of mortality associated with PM2.5, which varied with seasons and species. The results suggest that mass alone might not be sufficient to evaluate the health effects of particles. Citation: Dai L, Zanobetti A, Koutrakis P, Schwartz JD. 2014. Associations of fine particulate matter species with mortality in the United States: a multicity time-series analysis. Environ Health Perspect 122:837–842; http://dx.doi.org/10.1289/ehp.130756

A national case-crossover analysis of the short-term effect of PM2.5 on hospitalizations and mortality in subjects with diabetes and neurological disorders

Background: Diabetes and neurological disorders are a growing burden among the elderly, and may also make them more susceptible to particulate air matter with aerodynamic diameter less than 2.5 μg (PM2.5). The same biological responses thought to effect cardiovascular disease through air pollution-mediated systemic oxidative stress, inflammation and cerebrovascular dysfunction could also be relevant for diabetes and neurodegenerative diseases. Methods: We conducted multi-site case-crossover analyses of all-cause deaths and of hospitalizations for diabetes or neurological disorders among Medicare enrollees (>65 years) during the period 1999 to 2010 in 121 US communities. We examined whether 1) short-term exposure to PM2.5 increases the risk of hospitalization for diabetes or neurological disorders, and 2) the association between short-term exposure to PM2.5 and all-cause mortality is modified by having a previous hospitalization of diabetes or neurological disorders. Results: We found that short term exposure to PM2.5 is significantly associated with an increase in hospitalization risks for diabetes (1.14% increase, 95% CI: 0.56, 1.73 for a 10 μg/m3 increase in the 2 days average), and for Parkinson’s disease (3.23%, 1.08, 5.43); we also found an increase in all-cause mortality risks (0.64%, 95% CI: 0.42, 0.85), but we didn’t find that hospitalization for diabetes and neurodegenerative diseases modifies the association between short term exposure to PM2.5 and all-cause mortality. Conclusion: We found that short-term exposure to fine particles increased the risk of hospitalizations for Parkinson’s disease and diabetes, and of all-cause mortality. While the association between short term exposure to PM2.5 and mortality was higher among Medicare enrollees that had a previous admission for diabetes and neurological disorders than among Medicare enrollees that did not had a prior admission for these diseases, the effect modification was not statistically significant. We believe that these results provide useful insights regarding the mechanisms by which particles may affect the brain. A better understanding of the mechanisms will enable the development of new strategies to protect individuals at risk and to reduce detrimental effects of air pollution on the nervous system

Particulate Air Pollution, Progression, and Survival after Myocardial Infarction

OBJECTIVE: Several studies have examined the effect of particulate pollution (PM) on survival in general populations, but less is known about susceptible groups. Moreover, previous cohort studies have been cross-sectional and subject to confounding by uncontrolled differences between cities. DESIGN: We investigated whether PM was associated with progression of disease or reduced survival in a study of 196,000 persons from 21 U.S. cities discharged alive following an acute myocardial infarction (MI), using within-city between-year exposure to PM. We constructed city-specific cohorts of survivors of acute MI using Medicare data between 1985 and 1999, and defined three outcomes on follow-up: death, subsequent MI, and a first admission for congestive heart failure (CHF). Yearly averages of PM(10) (particulate matter with aerodynamic diameter < 10 μm) were merged to the individual annual follow-up in each city. We applied Cox’s proportional hazard regression model in each city, with adjustment for individual risk factors. In the second stage of the analysis, the city-specific results were combined using a meta-regression. RESULTS: We found significant associations with a hazard ratio for the sum of the distributed lags of 1.3 [95% confidence interval (CI), 1.2–1.5] for mortality, a hazard ratio of 1.4 (95% CI, 1.2–1.7) for a hospitalization for CHF, and a hazard ratio of 1.4 (95% CI, 1.1–1.8) for a new hospitalization for MI per 10 μg/m(3) PM(10). CONCLUSIONS: This is the first long-term study showing a significant association between particle exposure and adverse post-MI outcomes in persons who survived an MI

Hierarchical Bivariate Time Series Models: A Combined Analysis of the Effects of Particulate Matter on Morbidity and Mortality

In this paper we develop a hierarchical bivariate time series model to characterize the relationship between particulate matter less than 10 microns in aerodynamic diameter (PM10) and both mortality and hospital admissions for cardiovascular diseases. The model is applied to time series data on mortality and morbidity for 10 metropolitan areas in the United States from 1986 to 1993. We postulate that these time series should be related through a shared relationship with PM10. At the first stage of the hierarchy, we fit two seemingly unrelated Poisson regression models to produce city-specific estimates of the log relative rates of mortality and morbidity associated with exposure to PM10 within each location. The sample covariance matrix of the estimated log relative rates is obtained using a novel generalized estimating equation approach that takes into account the correlation between the mortality and morbidity time series. At the second stage, we combine information across locations to estimate overall log relative rates of mortality and morbidity and variation of the rates across cities. Using the combined information across the 10 locations we find that a 10 mu g/m3 increase in average PM10 at the current day and previous day is associated with a 0:26% increase in mortality (95% posterior interval -0:37; 0:65), and a 0:71% increase in hospital admissions (95% posterior interval 0:35; 0:99). The log relative rates of mortality and morbidity have a similar degree of heterogeneity across cities: the posterior means of the between-city standard deviations of the mortality and morbidity air pollution effects are 0:42 (95% interval 0:05; 1:18), and 0:31 (95% interval 0:10; 0:89), respectively. The city-specific log relative rates of mortality and morbidity are estimated to have very low correlation, but the uncertainty in the correlation is very substantial (posterior mean = 0:20; 95% interval -0:89; 0:98). With the parameter estimates from the model, we can predict the hospitalization log relative rate for a new city for which hospitalization data are unavailable, using that city\u27s estimated mortality relative rate. We illustrate this prediction using New York as an example