Seasonal analyses of air pollution and mortality in 100 US cities
Abstract
Time series models relating short-term changes in air pollution levels to daily mortality counts typically assume that the effects of air pollution on the log relative rate of mortality do not vary with time. However, these short-term effects might plausibly vary by season. Changes in the sources of air pollution and meteorology can result in changes in characteristics of the air pollution mixture across seasons. The authors developed Bayesian semiparametric hierarchical models for estimating time-varying effects of pollution on mortality in multisite time series studies. The methods were applied to the database of the National Morbidity and Mortality Air Pollution Study, which includes data for 100 US cities, for the period 1987-2000. At the national level, a 10-microg/m(3) increase in particulate matter less than 10 microm in aerodynamic diameter at a 1-day lag was associated with 0.15% (95% posterior interval (PI): -0.08, 0.39), 0.14% (95% PI: -0.14, 0.42), 0.36% (95% PI: 0.11, 0.61), and 0.14% (95% PI: -0.06, 0.34) increases in mortality for winter, spring, summer, and fall, respectively. An analysis by geographic region found a strong seasonal pattern in the Northeast (with a peak in summer) and little seasonal variation in the southern regions of the country. These results provide useful information for understanding particle toxicity and guiding future analyses of particle constituent data.
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National average estimates are robust to model specification for weather and seasonal confounding.
“Sensitivity analyses and characteristics of the first-stage statistical model for confounding adjustment have been explored for particulate matter (PM), with results indicating that national average estimates are robust to model specification for weather and seasonal confounding (Peng et al. 2005; Welty and Zeger 2005).”
From The Exposure–Response Curve for Ozone and Risk of Mortality and the Adequacy of Current Ozone Regulations (2006) · cites this paper as Peng et al. 2005
The Sensitivity analyses section (page unavailable) reports that added temperature terms did not noticeably change the overall seasonal PM10 pattern, and estimates appeared stable with stronger control for seasonality and long-term trends. But it also reports considerable deviations with only 3 degrees of freedom per year, so the unqualified claim of robustness across model specifications overstates the findings. (LLM, conf=0.84)
Experimental — accuracy not yet measuredA lag of 1 day for PM variables provided the most significant and largest effect in previous studies.
“A lag of 1 day was used for PM variables because this lag structure provided the most significant and largest effect in previous studies (Peng et al. 2005).”
From Potential confounding of particulate matter on the short-term association between ozone and mortality in multisite time-series studies (2007) · cites this paper as Peng et al. 2005
Effect estimates for PM2.5 and hospital admissions show temporal and spatial patterns, with the largest effects in the Northeast in summer.
“Effect estimates for PM2.5 and hospital admissions show temporal and spatial patterns (Domenici et al. 2006), with the largest effects in the Northeast in summer (Peng et al. 2005), which could be the result of differential toxicity of particles.”
From Potential confounding of particulate matter on the short-term association between ozone and mortality in multisite time-series studies (2007) · cites this paper as Peng et al. 2005
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- Authors
- Peng, R. D., Dominici, F., Pastor-Barriuso, R., Zeger, S. L., & Samet, J. M.
- Affiliations
- Johns Hopkins University (US)
- Corresponding author
- Peng, R. D.
- Venue
- American Journal of Epidemiology
- Publisher
- Oxford University Press (OUP)
- Published
- 2005-03-03
- Volume
- 161
- Issue
- 6
- Pages
- 585-594
- ISSN
- 0002-9262 (ISSN-L)
- 1476-6256
- OpenAlex
- W2097183694
- Cited by
- 450
- References
- 29
- Citations by year
- 2026: 13 · 2025: 10 · 2024: 7 · 2023: 15 · 2022: 18 · 2021: 30 · 2020: 20 · 2019: 22 · 2018: 27 · 2017: 20 · 2016: 31 · 2015: 35 · 2014: 18 · 2013: 29 · 2012: 33
- FWCI
- 14.08
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- American Journal of Epidemiology (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Collection of Biostatistics Research Archive (submittedVersion)
- Funders
- Health Effects Institute
- Instituto de Salud Carlos III
- National Heart, Lung, and Blood Institute (T32 HL 07024, T32HL007024)
- National Institute of Environmental Health Sciences (P30 ES03819, R01ES012054, P30ES003819)
- Topics
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Air Quality and Health Impacts
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Climate Change and Health Impacts
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Keywords
- air pollution, mortality, seasonal variation, particulate matter, PM10, time-dependent effects, particle toxicity, regional variation
- MeSH terms
- Air Pollution, Bayes Theorem, Humans, Mortality, Seasons, United States, Urban Population, Models, Statistical
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