Theresa L Osypuk1, Amy Ehntholt2, J Robin Moon2, Paola Gilsanz2, M Maria Glymour2. 1. From the Division of Epidemiology & Community Health, University of Minnesota School of Public Health, Minneapolis (T.L.O.); Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA (A.E., P.G., M.M.G.); SBH Health System, Bronx Partners for Healthy Communities, NY (J.R.M.); and Department of Epidemiology & Biostatistics, University of California, San Francisco (P.G., M.M.G.). tosypuk@umn.edu. 2. From the Division of Epidemiology & Community Health, University of Minnesota School of Public Health, Minneapolis (T.L.O.); Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA (A.E., P.G., M.M.G.); SBH Health System, Bronx Partners for Healthy Communities, NY (J.R.M.); and Department of Epidemiology & Biostatistics, University of California, San Francisco (P.G., M.M.G.).
Abstract
BACKGROUND: Post-stroke mortality is higher among residents of disadvantaged neighborhoods, but it is not known whether neighborhood inequalities are specific to stroke survival or similar to mortality patterns in the general population. We hypothesized that neighborhood disadvantage would predict higher poststroke mortality, and neighborhood effects would be relatively larger for stroke patients than for individuals with no history of stroke. METHODS AND RESULTS: Health and Retirement Study participants aged ≥50 years without stroke at baseline (n=15 560) were followed ≤12 years for incident stroke (1715 events over 159 286 person-years) and mortality (5325 deaths). Baseline neighborhood characteristics included objective measures based on census tracts (family income, poverty, deprivation, residential stability, and percent white, black, or foreign-born) and self-reported neighborhood social ties. Using Cox proportional hazard models, we compared neighborhood mortality effects for people with versus people without a history of stroke. Most neighborhood variables predicted mortality for both stroke patients and the general population in demographic-adjusted models. Neighborhood percent white predicted lower mortality for stroke survivors (hazard ratio, 0.75 for neighborhoods in highest 25th percentile versus below, 95% confidence interval, 0.62-0.91) more strongly than for stroke-free adults (hazard ratio, 0.92; 95% confidence interval, 0.83-1.02; P=0.04 for stroke-by-neighborhood interaction). No other neighborhood characteristic had different effects for people with versus without stroke. Neighborhood-mortality associations emerged within 3 months after stroke, when associations were often stronger than among stroke-free individuals. CONCLUSIONS: Neighborhood characteristics predict mortality, but most effects are similar for individuals without stroke. Eliminating disparities in stroke survival may require addressing pathways that are not specific to traditional poststroke care.
BACKGROUND: Post-stroke mortality is higher among residents of disadvantaged neighborhoods, but it is not known whether neighborhood inequalities are specific to stroke survival or similar to mortality patterns in the general population. We hypothesized that neighborhood disadvantage would predict higher poststroke mortality, and neighborhood effects would be relatively larger for stroke patients than for individuals with no history of stroke. METHODS AND RESULTS: Health and Retirement Study participants aged ≥50 years without stroke at baseline (n=15 560) were followed ≤12 years for incident stroke (1715 events over 159 286 person-years) and mortality (5325 deaths). Baseline neighborhood characteristics included objective measures based on census tracts (family income, poverty, deprivation, residential stability, and percent white, black, or foreign-born) and self-reported neighborhood social ties. Using Cox proportional hazard models, we compared neighborhood mortality effects for people with versus people without a history of stroke. Most neighborhood variables predicted mortality for both stroke patients and the general population in demographic-adjusted models. Neighborhood percent white predicted lower mortality for stroke survivors (hazard ratio, 0.75 for neighborhoods in highest 25th percentile versus below, 95% confidence interval, 0.62-0.91) more strongly than for stroke-free adults (hazard ratio, 0.92; 95% confidence interval, 0.83-1.02; P=0.04 for stroke-by-neighborhood interaction). No other neighborhood characteristic had different effects for people with versus without stroke. Neighborhood-mortality associations emerged within 3 months after stroke, when associations were often stronger than among stroke-free individuals. CONCLUSIONS: Neighborhood characteristics predict mortality, but most effects are similar for individuals without stroke. Eliminating disparities in stroke survival may require addressing pathways that are not specific to traditional poststroke care.
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