Journal of epidemiology and community health · 2019
Characteristics of the built environment and spatial patterning of type 2 diabetes in the urban core of Durham, North Carolina.
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Bravo Mercedes A, Anthopolos Rebecca, Miranda Marie Lynn
Аннотация
BACKGROUND: Few studies examine relationships between built environment (BE) and type 2 diabetes mellitus (T2DM) using spatial models, investigate BE domains apart from food environment or physical activity resources or conduct sensitivity analysis of methodological choices made in measuring BE. We examine geographic heterogeneity of T2DM, describe how heterogeneity in T2DM relates to BE and estimate associations of T2DM with BE.
METHODS: Individual-level electronic health records (n=41 203) from the Duke Medicine Enterprise Data Warehouse (2007-2011) were linked to BE based on census block. Data on housing damage, property disorder, territoriality, vacancy and public nuisances were used to estimate BE based on four different construction methods (CMs). We used race-stratified aspatial and spatial Bayesian models to assess geographic heterogeneity in T2DM and associations of T2DM with BE.
RESULTS: Among whites, a 1 SD increase in poor quality BE was associated with a 1.03 (95% credible interval 1.01 to 1.06) and 1.06 (95 % credible interval 1.02 to 1.11) increased risk of T2DM for poor quality BE CM1 and CM2, respectively. Among blacks/African Americans, associations between T2DM and BE overlapped with the null for all CMs. The addition of BE to white models reduced residual geographic heterogeneity in T2DM by 4%-15%, depending on CM. In black/African-American models, BE did not affect residual heterogeneity.
CONCLUSION: Associations of T2DM with BE were sensitive to CM and geographic heterogeneity in T2DM differed by race/ethnicity. Findings underscore the need to consider multiple methods of estimating BE and consider differences in relationships by race/ethnicity.
METHODS: Individual-level electronic health records (n=41 203) from the Duke Medicine Enterprise Data Warehouse (2007-2011) were linked to BE based on census block. Data on housing damage, property disorder, territoriality, vacancy and public nuisances were used to estimate BE based on four different construction methods (CMs). We used race-stratified aspatial and spatial Bayesian models to assess geographic heterogeneity in T2DM and associations of T2DM with BE.
RESULTS: Among whites, a 1 SD increase in poor quality BE was associated with a 1.03 (95% credible interval 1.01 to 1.06) and 1.06 (95 % credible interval 1.02 to 1.11) increased risk of T2DM for poor quality BE CM1 and CM2, respectively. Among blacks/African Americans, associations between T2DM and BE overlapped with the null for all CMs. The addition of BE to white models reduced residual geographic heterogeneity in T2DM by 4%-15%, depending on CM. In black/African-American models, BE did not affect residual heterogeneity.
CONCLUSION: Associations of T2DM with BE were sensitive to CM and geographic heterogeneity in T2DM differed by race/ethnicity. Findings underscore the need to consider multiple methods of estimating BE and consider differences in relationships by race/ethnicity.