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American Journal of Epidemiology 2005 162(1):80-88; doi:10.1093/aje/kwi157
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American Journal of Epidemiology Copyright © 2005 by the Johns Hopkins Bloomberg School of Public Health All rights reserved

ORIGINAL CONTRIBUTIONS

Are the Acute Effects of Particulate Matter on Mortality in the National Morbidity, Mortality, and Air Pollution Study the Result of Inadequate Control for Weather and Season? A Sensitivity Analysis using Flexible Distributed Lag Models

Leah J. Welty and Scott L. Zeger

From the Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD

Correspondence to Dr. Leah J. Welty, Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, 680 North Lake Shore Drive, Suite 1120, Chicago, IL 60611 (e-mail: lwelty{at}northwestern.edu).

Time-series studies have linked daily variations in nonaccidental deaths with daily variations in ambient particulate matter air pollution, while controlling for qualitatively larger influences of weather and season. Although time-series analyses typically include nonlinear terms for weather and season, questions remain as to whether models to date have completely controlled for these important predictors. In this paper, the authors use two flexible versions of distributed lag models to control extensively for the confounding effects of weather and season. One version builds on the current approach to controlling for weather, while the other version offers a new approach. The authors conduct a comprehensive sensitivity analysis of the particulate matter–mortality relation by applying these methods to the recently updated National Morbidity, Mortality, and Air Pollution Study database that comprises air pollution, weather, and mortality time series from 1987 to 2000 for 100 US cities. They combine city-specific estimates of the short-term effects of particulate matter on mortality using a Bayesian hierarchical model. They conclude that, within the broad classes of models considered, national average estimates of particulate matter relative risk are consistent with previous estimates from this study and are robust to model specification for weather and seasonal confounding.

air pollution; longitudinal studies; mortality; regression analysis; seasons; temperature; weather


Abbreviations: APHEA, Air Pollution and Health: a European Approach; NMMAPS, National Morbidity, Mortality, and Air Pollution Study; PM10, particulate matter of less than 10 µm in aerodynamic diameter


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