4.7 Article

Distributed Lag Analyses of Daily Hospital Admissions and Source-Apportioned Fine Particle Air Pollution

Journal

ENVIRONMENTAL HEALTH PERSPECTIVES
Volume 119, Issue 4, Pages 455-460

Publisher

US DEPT HEALTH HUMAN SCIENCES PUBLIC HEALTH SCIENCE
DOI: 10.1289/ehp.1002638

Keywords

cardiovascular; distributed lag model; generalized linear models; hospital admissions; New York City; particulate matter; positive matrix factorization; respiratory; source apportionment; time series; trace element species; traffic

Funding

  1. New York University-National Institute of Environmental Health Sciences Environmental Health Center [5P30ES000260]
  2. New York University-U.S. Environmental Protection Agency (EPA) Particulate Matter Health Research Center [R827351]
  3. U.S. EPA [R827997010]

Ask authors/readers for more resources

BACKGROUND: Past time-series studies of the health effects of fine particulate matter [aerodynamic diameter <= 2.5 mu m (PM2.5)] have used chemically nonspecific PM2.5 mass. However, PM2.5 is known to vary in chemical composition with source, and health impacts may vary accordingly. OBJECTIVE: We tested the association between source-specific daily PM2.5 mass and hospital admissions in a time-series investigation that considered both single-lag and distributed-lag models. METHODS: Daily PM2.5 speciation measurements collected in midtown Manhattan were analyzed via positive matrix factorization source apportionment. Daily and distributed-lag generalized linear models of Medicare respiratory and cardiovascular hospital admissions during 2001-2002 considered PM2.5 mass and PM2.5 from five sources: transported sulfate, residual oil, traffic, steel metal works, and soil. RESULTS: Source-related PM2.5 (specifically steel and traffic) was significantly associated with hospital admissions but not with total PM2.5 mass. Steel metal works-related PM2.5 was associated with respiratory admissions for multiple-lag days, especially during the cleanup efforts at the World Trade Center. Traffic-related PM2.5 was consistently associated with same-day cardiovascular admissions across disease-specific subcategories. PM2.5 constituents associated with each source (e. g., elemental carbon with traffic) were likewise associated with admissions in a consistent manner. Mean effects of distributed-lag models were significantly greater than were maximum single-day effect models for both steel-and traffic-related PM2.5. CONCLUSIONS: Past analyses that have considered only PM2.5 mass or only maximum single-day lag effects have likely underestimated PM2.5 health effects by not considering source-specific and distributed-lag effects. Differing lag structures and disease specificity observed for steel-related versus traffic-related PM2.5 raise the possibility of distinct mechanistic pathways of health effects for particles of differing chemical composition.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available