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J Expo Sci Environ Epidemiol. 2014 Jul;24(4):365-71. doi: 10.1038/jes.2014.7. Epub 2014 Feb 5.

The impact of source contribution uncertainty on the effects of source-specific PM2.5 on hospital admissions: a case study in Boston, MA.

Author information

1
Department of Environmental Health, Harvard School of Public Health, Boston, Massachusetts, USA.
2
Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, USA.
3
Department of Health Sciences, Northeastern University, Boston, Massachusetts, USA.

Abstract

Epidemiologic studies of particulate sources and adverse health do not account for the uncertainty in the source contribution estimates. Our goal was to assess the impact of uncertainty on the effect estimates of particulate sources on emergency cardiovascular (CVD) admissions. We examined the effects of PM2.5 sources, identified by positive matrix factorization (PMF) and absolute principle component analysis (APCA), on emergency CVD hospital admissions among Medicare enrollees in Boston, MA, during 2003-2010, given stronger associations for this period. We propagated uncertainty in source contributions using a block bootstrap procedure. We further estimated average across-methods source-specific effect estimates using bootstrap samples. We estimated contributions for regional, mobile, crustal, residual oil combustion, road dust, and sea salt sources. Accounting for uncertainty, same-day exposures to regional pollution were associated with an across-methods average effect of 2.00% (0.18, 3.78%) increase in the rate of CVD admissions. Weekly residual oil exposures resulted in an average 2.12% (0.19, 4.22%) increase. Same-day and 2-day exposures to mobile-related PM2.5 were also associated with increased admissions. Confidence intervals when accounting for the uncertainty were wider than otherwise. Agreement in PMF and APCA results was stronger when uncertainty was considered in health models. Accounting for uncertainty in source contributions leads to more stable effect estimates across methods and potentially to fewer spurious significant associations.

PMID:
24496220
PMCID:
PMC4063325
DOI:
10.1038/jes.2014.7
[Indexed for MEDLINE]
Free PMC Article

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