Virginia J Howard1, Leslie A McClure2, Dawn O Kleindorfer2, Solveig A Cunningham2, Amanda G Thrift2, Ana V Diez Roux2, George Howard2. 1. From the Department of Epidemiology (V.J.H.), School of Public Health, University of Alabama at Birmingham; Department of Epidemiology and Biostatistics (L.A.M., G.H.), Dornsife School of Public Health (A.V.D.R.), Drexel University, Philadelphia, PA; Department of Neurology (D.O.K.), University of Cincinnati College of Medicine, OH; Hubert Department of Global Health and Department of Sociology (S.A.C.), Emory University, Atlanta, GA; Epidemiology & Prevention Division (A.G.T.), Stroke and Ageing Research (STARC), Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton; and The Florey Institute of Neuroscience and Mental Health (A.G.T.), Melbourne University, Heidelberg, Australia. vjhoward@uab.edu. 2. From the Department of Epidemiology (V.J.H.), School of Public Health, University of Alabama at Birmingham; Department of Epidemiology and Biostatistics (L.A.M., G.H.), Dornsife School of Public Health (A.V.D.R.), Drexel University, Philadelphia, PA; Department of Neurology (D.O.K.), University of Cincinnati College of Medicine, OH; Hubert Department of Global Health and Department of Sociology (S.A.C.), Emory University, Atlanta, GA; Epidemiology & Prevention Division (A.G.T.), Stroke and Ageing Research (STARC), Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton; and The Florey Institute of Neuroscience and Mental Health (A.G.T.), Melbourne University, Heidelberg, Australia.
Abstract
OBJECTIVE: To assess the relationship between neighborhood socioeconomic characteristics and incident stroke in a national cohort of black and white participants. METHODS: The study comprised black (n = 10,274, 41%) and white (n = 14,601) stroke-free participants, aged 45 and older, enrolled in 2003-2007 in Reasons for Geographic and Racial Differences in Stroke (REGARDS), a national population-based cohort. A neighborhood socioeconomic score (nSES) was constructed using 6 neighborhood variables. Incident stroke was defined as first occurrence of stroke over an average 7.5 (SD 3.0) years of follow-up. Proportional hazards models were used to estimate associations between nSES score and incident stroke, adjusted for demographics (age, race, sex, region), individual socioeconomic status (SES) (education, household income), and other risk factors for stroke. RESULTS: After adjustment for demographics, compared to the highest nSES quartile, stroke incidence increased with each decreasing nSES quartile. The hazard ratio (95% confidence interval) ranged from 1.28 (1.05-1.56) in quartile 3 to 1.38 (1.13-1.68) in quartile 2 to 1.56 (1.26-1.92) in quartile 1 (p < 0.0001 for linear trend). After adjustment for individual SES, the trend remained marginally significant (p = 0.085). Although there was no evidence of a differential effect by race or sex, adjustment for stroke risk factors attenuated the association between nSES and stroke in both black and white participants, with greater attenuation in black participants. CONCLUSIONS: Risk of incident stroke increased with decreasing nSES but the effect of nSES is attenuated through individual SES and stroke risk factors. The effect of neighborhood socioeconomic characteristics that contribute to increased stroke risk is similar in black and white participants.
OBJECTIVE: To assess the relationship between neighborhood socioeconomic characteristics and incident stroke in a national cohort of black and white participants. METHODS: The study comprised black (n = 10,274, 41%) and white (n = 14,601) stroke-free participants, aged 45 and older, enrolled in 2003-2007 in Reasons for Geographic and Racial Differences in Stroke (REGARDS), a national population-based cohort. A neighborhood socioeconomic score (nSES) was constructed using 6 neighborhood variables. Incident stroke was defined as first occurrence of stroke over an average 7.5 (SD 3.0) years of follow-up. Proportional hazards models were used to estimate associations between nSES score and incident stroke, adjusted for demographics (age, race, sex, region), individual socioeconomic status (SES) (education, household income), and other risk factors for stroke. RESULTS: After adjustment for demographics, compared to the highest nSES quartile, stroke incidence increased with each decreasing nSES quartile. The hazard ratio (95% confidence interval) ranged from 1.28 (1.05-1.56) in quartile 3 to 1.38 (1.13-1.68) in quartile 2 to 1.56 (1.26-1.92) in quartile 1 (p < 0.0001 for linear trend). After adjustment for individual SES, the trend remained marginally significant (p = 0.085). Although there was no evidence of a differential effect by race or sex, adjustment for stroke risk factors attenuated the association between nSES and stroke in both black and white participants, with greater attenuation in black participants. CONCLUSIONS: Risk of incident stroke increased with decreasing nSES but the effect of nSES is attenuated through individual SES and stroke risk factors. The effect of neighborhood socioeconomic characteristics that contribute to increased stroke risk is similar in black and white participants.
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