Jerome N Rachele1, Billie Giles-Corti2, Gavin Turrell3. 1. School of Public Health and Social Work and Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia. Electronic address: j.rachele@qut.edu.au. 2. McCaughey VicHealth Community Wellbeing Unit, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia. 3. School of Public Health and Social Work and Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia.
Abstract
PURPOSE: This study examines associations between neighborhood socioeconomic disadvantage and self-reported type 2 diabetes and heart disease, occurring separately and concurrently at a single time point (comorbidity). METHODS: This study included 11,035 residents from 200 neighborhoods in Brisbane, Australia. Respondents self-reported type 2 diabetes and heart disease as long-term health conditions. Neighborhood socioeconomic disadvantage was measured using a census-derived composite index. Individual socioeconomic position was measured using education, occupation, and household income. Data were analyzed using multilevel multinomial mixed-effects logistic regression using Markov chain Monte Carlo simulation. RESULTS: Compared with the most advantaged neighborhoods, residents of the most-disadvantaged neighborhoods were more likely to report type 2 diabetes (odds ratio [OR] = 2.21, 95% credible interval [CrI] = 1.55-3.15), heart disease (OR = 1.72, 95% CrI = 1.25-2.38), and comorbidity (OR = 4.38, 95% CrI = 2.27-8.66). This relationship attenuated after adjustment for individual-level socioeconomic position, but remained statistically significant for type 2 diabetes (OR = 1.81, 95% CrI = 1.15-2.83) and comorbidity (OR = 3.00, 95% CrI = 1.49-6.13). CONCLUSIONS: Studies of neighborhood disadvantage that fail to include individual-level socioeconomic measures may inflate associations. Establishing why residents of disadvantaged neighborhoods are more likely to experience the co-occurrence of heart disease and type 2 diabetes independent of their individual socioeconomic position warrants further investigation.
PURPOSE: This study examines associations between neighborhood socioeconomic disadvantage and self-reported type 2 diabetes and heart disease, occurring separately and concurrently at a single time point (comorbidity). METHODS: This study included 11,035 residents from 200 neighborhoods in Brisbane, Australia. Respondents self-reported type 2 diabetes and heart disease as long-term health conditions. Neighborhood socioeconomic disadvantage was measured using a census-derived composite index. Individual socioeconomic position was measured using education, occupation, and household income. Data were analyzed using multilevel multinomial mixed-effects logistic regression using Markov chain Monte Carlo simulation. RESULTS: Compared with the most advantaged neighborhoods, residents of the most-disadvantaged neighborhoods were more likely to report type 2 diabetes (odds ratio [OR] = 2.21, 95% credible interval [CrI] = 1.55-3.15), heart disease (OR = 1.72, 95% CrI = 1.25-2.38), and comorbidity (OR = 4.38, 95% CrI = 2.27-8.66). This relationship attenuated after adjustment for individual-level socioeconomic position, but remained statistically significant for type 2 diabetes (OR = 1.81, 95% CrI = 1.15-2.83) and comorbidity (OR = 3.00, 95% CrI = 1.49-6.13). CONCLUSIONS: Studies of neighborhood disadvantage that fail to include individual-level socioeconomic measures may inflate associations. Establishing why residents of disadvantaged neighborhoods are more likely to experience the co-occurrence of heart disease and type 2 diabetes independent of their individual socioeconomic position warrants further investigation.
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