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Author Notes:

Jianzhao Bi, Department of Environmental & Occupational Health Sciences, University of Washington, 4225 Roosevelt Way NE, Seattle, WA 98105 USA. Email:jbi6@uw.edu

This research was supported by funding from the National Institute of Environmental Health Sciences (NIEHS) of the National Institutes of Health (NIH) under award numbers R01ES027892 and P30ES019776. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. We are grateful for the support of the health data sources listed below and their contributing hospitals. The data used to produce this publication were acquired from the: Arizona Department of Health Services (years 2010–2014); California Office of Statewide Planning and Development, now California Department of Health Care Access and Information (years 2005–2014); Georgia Hospital Association (years 2011–2014); Maryland Department of Health, Health Services Cost Review Commission (years 2005–2014); Missouri Department of Health and Senior Services (years 2005–2014); Nevada Division of Health Care Financing and Policy (DJCFP), released through the Center for Health Information Analysis (CHIA) of the University of Nevada, Las Vegas (years 2009–2014); New Jersey Department of Health, Center for Health Statistics & Informatics, Trenton, New Jersey (years 2005–2014); New York State Department of Health, Statewide Planning and Research Cooperative System (years 2005–2014); North Carolina Hospital (inpatient, ambulatory surgery/outpatient, emergency room) Discharge Database (Truven Health Analytics, years 2007–2014) from the Cecil G. Sheps Center for Health Services Research and the North Carolina Division of Health Service Regulation; and Utah Department of Health, Office of Health Care Statistics (years 2005–2014).

The contents of this publication, including data analysis, interpretation, conclusions derived, and the views expressed herein are solely those of the authors and do not represent the conclusions or official views of data sources listed above. Authorization to release this information does not imply endorsement of this study or its findings by any of these data sources. The data sources, their employees, officers, and agents make no representation, warranty, or guarantee as to the accuracy, completeness, currency, or suitability of the information provided here.

Subject:

Keywords:

  • Science & Technology
  • Life Sciences & Biomedicine
  • Environmental Sciences
  • Public, Environmental & Occupational Health
  • Toxicology
  • Environmental Sciences & Ecology
  • EXPOSURE MEASUREMENT ERROR
  • STRATIFIED CASE-CROSSOVER
  • TERM OZONE EXPOSURE
  • TIME-SERIES
  • HOSPITAL ADMISSIONS
  • DISTRIBUTED LAG
  • UNITED-STATES
  • ASSOCIATIONS
  • MORBIDITY
  • POLLUTANTS

Acute Effects of Ambient Air Pollution on Asthma Emergency Department Visits in Ten US States

Tools:

Journal Title:

ENVIRONMENTAL HEALTH PERSPECTIVES

Volume:

Volume 131, Number 4

Publisher:

, Pages 47003-47003

Type of Work:

Article | Final Publisher PDF

Abstract:

BACKGROUND: Previous studies of short-term ambient air pollution exposure and asthma morbidity in the United States have been limited to a small number of cities and/or pollutants and with limited consideration of effects across ages. OBJECTIVES: To estimate acute age group-specific effects of fine and coarse particulate matter (PM), major PM components, and gaseous pollutants on emergency department (ED) visits for asthma during 2005-2014 across the United States. METHODS: We acquired ED visit and air quality data in regions surrounding 53 speciation sites in 10 states. We used quasi-Poisson log-linear time-series models with unconstrained distributed exposure lags to estimate site-specific acute effects of air pollution on asthma ED visits overall and by age group (1-4, 5-17, 18-49, 50-64, and formula presented y), controlling for meteorology, time trends, and influenza activity. We then used a Bayesian hierarchical model to estimate pooled associations from site-specific associations. RESULTS: Our analysis included formula presented asthma ED visits. We observed positive associations for multiday cumulative exposure to all air pollutants examined [e.g., 8-d exposure to formula presented : rate ratio of 1.016 with 95% credible interval (CI) of (1.008, 1.025) per formula presented increase, formula presented : 1.014 (95% CI: 1.007, 1.020) per formula presented increase, organic carbon: 1.016 (95% CI: 1.009, 1.024) per formula presented increase, and ozone: 1.008 (95% CI: 0.995, 1.022) per formula presented increase]. formula presented and ozone showed stronger effects at shorter lags, whereas associations of traffic-related pollutants (e.g., elemental carbon and oxides of nitrogen) were generally stronger at longer lags. Most pollutants had more pronounced effects on children (formula presented y old) than adults; formula presented had strong effects on both children and the elderly (formula presented y old); and ozone had stronger effects on adults than children. CONCLUSIONS: We reported positive associations between short-term air pollution exposure and increased rates of asthma ED visits. We found that air pollution exposure posed a higher risk for children and older populations. https://doi.org/10.1289/EHP11661.
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