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Geographic disparity in COPD hospitalization rates among the Texas population
Bradford E Jackson1, Sumihiro Suzuki, Kaming Lo
1Department of Biostatistics, School of Public Health, University of North Texas Health Science Center, 3500 Camp Bowie Blvd, Fort Worth, TX 76107, USA. bjackson@live.unthsc.edu
Background:
Chronic obstructive pulmonary disease (COPD) is a major cause of morbidity and mortality caused by cigarette smoking and other environmental exposures. While variation in exposures may affect COPD morbidity and mortality, little is known about geographic variation, a surrogate of exposures. The objective of this manuscript is to explore the geographic variation in COPD hospitalization rates among the Texas population in 2006.
Methods:
The study population consisted of all Texas residents with COPD hospitalizations in the 2006 Texas Health Care Information Council (THCIC) data. County population estimates stratified by race, age, and gender were linked to THCIC data to calculate county level COPD hospitalization rates per 100,000 admissions. The data were merged with Urban Influence Codes by county, and metropolitan status was determined by United States Department of Agriculture (USDA) criteria. Variation in COPD hospitalization rates were analyzed using Poisson Regression.
Results:
Overall, non Hispanic (NH) Whites had the highest rate of hospitalization, followed by NH Blacks (rate ratio=0.42) and Hispanics (RR=0.17), the 65+ age category had the highest rates of hospitalization. In the metropolitan counties COPD hospitalization rates were lower than non-metropolitan counties, however in metropolitan counties the rates of hospitalization were significantly higher (p<0.0001) in females compared to males. The rates were significantly higher in males in public health regions 10 and 11, which are predominantly non-metropolitan counties.
Conclusions:
In Texas there is substantial geographic variation in hospitalization rates associated with gender and race/ethnicity. Other factors that may contribute to the variation and require further investigation include differences in smoking and exposure to other environmental risk factors, access to primary care, medical practice patterns, and coding practices.
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