Short term effects of particle exposure on hospital admissions in the Mid-Atlantic states: a population estimate.

BACKGROUND

Many studies report significant associations between PM(2.5) (particulate matter <2.5 micrometers) and hospital admissions. These studies mostly rely on a limited number of monitors which introduces exposure error, and excludes rural and suburban populations from locations where monitors are not available, reducing generalizability and potentially creating selection bias.

METHODS

Using prediction models developed by our group, daily PM(2.5) exposure was estimated across the Mid-Atlantic (Washington D.C., and the states of Delaware, Maryland, New Jersey, Pennsylvania, Virginia, New York and West Virginia). We then investigated the short-term effects of PM(2.5)exposures on emergency hospital admissions of the elderly in the Mid-Atlantic region.We performed case-crossover analysis for each admission type, matching on day of the week, month and year and defined the hazard period as lag01 (a moving average of day of admission exposure and previous day exposure).

RESULTS

We observed associations between short-term exposure to PM(2.5) and hospitalization for all outcomes examined. For example, for every 10-µg/m(3) increase in short-term PM(2.5) there was a 2.2% increase in respiratory diseases admissions (95% CI = 1.9 to 2.6), and a 0.78% increase in cardiovascular disease (CVD) admission rate (95% CI = 0.5 to 1.0). We found differences in risk for CVD admissions between people living in rural and urban areas. For every10-µg/m(3) increase in PM(2.5) exposure in the 'rural' group there was a 1.0% increase (95% CI = 0.6 to 1.5), while for the 'urban' group the increase was 0.7% (95% CI = 0.4 to 1.0).

CONCLUSIONS

Our findings showed that PM(2.5) exposure was associated with hospital admissions for all respiratory, cardio vascular disease, stroke, ischemic heart disease and chronic obstructive pulmonary disease admissions. In addition, we demonstrate that our AOD (Aerosol Optical Depth) based exposure models can be successfully applied to epidemiological studies investigating the health effects of short-term exposures to PM(2.5).