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Background: In air pollution time-series studies, the temporal pattern of the association of fine particulate matter (PM_2.5; particulate matter ≤ 2.5 µm in aerodynamic diameter) and health end points has been observed to vary by disease category. The lag pattern of PM_2.5 chemical constituents has not been well investigated, largely because daily data have not been available.

Objectives: We explored the lag structure for hospital admissions using daily PM_2.5 chemical constituent data for 5 years in the Denver Aerosol Sources and Health (DASH) study.

Methods: We measured PM_2.5 constituents, including elemental carbon, organic carbon, sulfate, and nitrate, at a central residential site from 2003 through 2007 and linked these daily pollution data to daily hospital admission counts in the five-county Denver metropolitan area. Total hospital admissions and subcategories of respiratory and cardiovascular admissions …