Appathurai Balamurugan1, Robert Delongchamp, Joseph H Bates, Jawahar L Mehta. 1. Arkansas Department of Health, Little Rock; Department of Family and Preventive Medicine and Department of Internal Medicine, Division of Cardiology, University of Arkansas for Medical Sciences College of Medicine, Little Rock; and Department of Epidemiology, University of Arkansas for Medicine for Medical Sciences College of Public Health, Little Rock.
Abstract
BACKGROUND: The excess stroke mortality in the southeastern states of the United States (stroke-belt states) is well known; however, the factors associated with this pattern have not been fully elucidated. We measured the contribution of several demographic factors by analyzing stroke mortality data (2005-2009) at the census block group (BG) level in the state of Arkansas. METHODS AND RESULTS: Census BGs were used as proxies for neighborhoods. BGs were stratified using 5 census measures: poverty (percent of population below federal poverty level), population density (population per square mile), education (percent of population aged >25 years who did not graduate from high school), population mobility (percent of population who resided at the same address 1 year ago), and the percent of non-Hispanic blacks (percent of population that is black). Generalized additive models were used to estimate the variation in stroke mortality among BGs and to assess the impact of different demographic variables. From 2005 to 2009, there were 8930 stroke deaths in Arkansas. There was considerable variation in the relative risk even between adjacent BGs within a single county. The geographically weighted regression analyses indicated that 4.5% to 9% of deviance in stroke mortality among BGs could be explained by poverty, education, population density, and population mobility. Race/ethnicity (non-Hispanic blacks) explains <2% of the deviance in stroke mortality among BGs. CONCLUSIONS: Our study shows that primordial risk factors such as poverty and education drive disparities in stroke mortality among neighborhoods in Arkansas.
BACKGROUND: The excess stroke mortality in the southeastern states of the United States (stroke-belt states) is well known; however, the factors associated with this pattern have not been fully elucidated. We measured the contribution of several demographic factors by analyzing stroke mortality data (2005-2009) at the census block group (BG) level in the state of Arkansas. METHODS AND RESULTS: Census BGs were used as proxies for neighborhoods. BGs were stratified using 5 census measures: poverty (percent of population below federal poverty level), population density (population per square mile), education (percent of population aged >25 years who did not graduate from high school), population mobility (percent of population who resided at the same address 1 year ago), and the percent of non-Hispanic blacks (percent of population that is black). Generalized additive models were used to estimate the variation in stroke mortality among BGs and to assess the impact of different demographic variables. From 2005 to 2009, there were 8930 stroke deaths in Arkansas. There was considerable variation in the relative risk even between adjacent BGs within a single county. The geographically weighted regression analyses indicated that 4.5% to 9% of deviance in stroke mortality among BGs could be explained by poverty, education, population density, and population mobility. Race/ethnicity (non-Hispanic blacks) explains <2% of the deviance in stroke mortality among BGs. CONCLUSIONS: Our study shows that primordial risk factors such as poverty and education drive disparities in stroke mortality among neighborhoods in Arkansas.
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