Spatial clusters of type 2 diabetes and their individual and neighborhood socioeconomic characteristics among participants of the ELSA-Brasil Cohort

Background: This study identified spatial clusters of T2DM among participants of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) residing in two cities, and verified individual and neighborhood socioeconomic environmental characteristics associated with spatial clusters of T2DM. Methods: A cross-sectional study, conducted with 4,335 participants in ELSA-Brasil (2,486 from the city of Belo Horizonte; 1,849 from the city of Salvador), using baseline data collected from 2008 to 2010. T2DM was defined as fasting glycaemia ≥ 126 mg/dL (7.0 mmol/L), or oral glucose tolerance test ≥ 200 mg/dL (11.1 mmol/L), or glycated hemoglobin ≥ 6.5% (48 mmol/L); or by antidiabetic drug use; or by the self-reported medical diagnosis of T2DM. The neighborhood socioeconomic characteristics were obtained from the Brazilian census 2011. The levels per geographic area were defined punctually according to the individual’s place of residence. A spatial data analysis was conducted with the SaTScanTM method to detect the T2DM cluster areas. This study also analyzed the individual and neighborhood socioeconomic characteristics of participants living inside and outside of identified T2DM clusters, using the hierarchical logistic regression model. Results: A total of 336 and 343 participants had T2DM in Belo Horizonte (prevalence = 13.5%) and Salvador (prevalence = 18.5%), respectively. Two cluster areas showing a high chance of T2DM were identified in the Northeastern region of Belo Horizonte and the Northern region of Salvador. In the latter city, a cluster area of low chance of T2DM was also identified, located in the Southern region. In both cities, participants living in the high T2DM cluster area were more likely to report brown or black skin color, a low level of education, and a manual work occupation; these were also considered to be low income areas. By contrast, participants in the low T2DM cluster area of Salvador were less likely to be black and to have university degrees; this was considered to be a high income area. Conclusion: More vulnerable individual and neighborhood socioeconomic characteristics were associated with living in clusters of higher occurrence of T2DM, while better individual and contextual profiles were associated with clusters of a lower prevalence of T2DM.