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ABSTRACT: Few, if any, published time series studies have evaluated the effects of particulate matter air exposures by combining hospital admissions with medical visit data for smaller populations. We investigated the relationship between daily particulate matter (<10 microm in aerometric diameter or PM10) exposures with admissions and medical visits (emergency room, urgent care, and family practice) for respiratory and cardiovascular disease in Pocatello and Chubbuck, Idaho (population about 60,000), from November 1994 through March 2000. Within generalized linear models, time, weather, influenza, and day-of-week effects were controlled. In single-pollutant models, respiratory disease admissions and visits increased (7.1-15.4% per 50 microg/m3 PM10) for each age group analyzed, with the highest increases in two groups, children and especially the elderly. Statistical analyses suggest that the results probably did not occur by chance. Sensitivity analyses did not provide strong evidence that the respiratory disease effect estimates were sensitive to reasonable changes in the final degrees of freedom choice for time and weather effects. No strong evidence of confounding by NO2 and SO2 was found from results of multi-pollutant models. Ozone and carbon monoxide data were not available to include multi-pollutant models, but evidence suggests that they were not a problem. Unexpectedly, evidence of an association between PM10 with cardiovascular disease was not found, possibly due to the lifestyles of the mostly Mormon study population. Successful time series analyses can be performed on smaller populations if diverse, centralized databases are available. Hospitals that offer urgent or other primary care services may be a rich source of data for researchers. Using data that potentially represented a wide-range of disease severity, the findings provide evidence that evaluating only hospital admissions or emergency room visit effects may underestimate the overall morbidity due to acute particulate matter exposures. Further work is planned to test this conclusion.
Journal of Exposure Science and Environmental Epidemiology 09/2007; 17(5):478-87. · 3.19 Impact Factor