To describe the spatial distribution of tuberculosis-diabetes comorbidity and identify the social determinants of the double burden of disease in the period from 2012 to 2018 in Brazil.
In the present ecological study, municipalities were the unit of analysis. All cases of tuberculosis reported from 2012 to 2018 to the National Notifiable Disease Information System SINAN were included. Socioeconomic variables covering employment, income, and development, and the primary care coverage indicator were analyzed as determinants. The global Moran’s I statistic was used to verify spatial autocorrelation in the comorbidity rate. The local Moran statistic was used to delimit tuberculosis-diabetes clusters: high/high cluster (municipalities with high rates of tuberculosis-diabetes comorbidity with neighboring municipalities also presenting high comorbidity rates) and low/low cluster (municipalities with tuberculosis-diabetes comorbidity below the mean, surrounded by municipalities with low comorbidity rates).
A high proportion of tuberculosis-diabetes was detected in most Brazilian regions. Spatial autocorrelation was observed for tuberculosis-diabetes comorbidity, as well as a high-high comorbidity cluster encompassing 88 municipalities located mostly in the Northeast, Southeast, and South, with mean tuberculosis-diabetes prevalence of 28.04%. The variables “percent population living in households with more than two people per bedroom,” “percent unemployment in the population above 18 years of age” and “per capita income” were associated with the presence of comorbidity.
The results showed a non-random distribution of tuberculosis-diabetes comorbidity, with high-risk areas and associated explanatory variables. The findings underscore the need to operationalize cooperation between tuberculosis and diabetes programs, with the aim of controlling both the individual diseases and the tuberculosis-diabetes syndemic.