Determinants of tuberculosis in Brazil: from conceptual framework to practical application

Abstract

Objective: To leverage a conceptual analytical model for TB determination to identify factors that influence emergence of new cases of tuberculosis (TB) and poor TB treatment outcomes in Brazil.

Methods: This was a cross-sectional study based on data from Brazil's Notifiable Disease Surveillance System database (SINAN). It included all confirmed, incident TB cases reported in Brazil in 2007 - 2011: a total of 432 958 TB cases, of which 318 465 cases with complete data on treatment outcomes were included. Analysis to explain the causal network that influences TB treatment outcomes was based on a theoretical model for determining TB. Adjusted analyses were used to assess the model fit. Hierarchical logistic regression was used to model the dichotomous TB outcome; hierarchical polytomous regression was used for multinomial TB outcome.

Results: Of the 318 465 TB cases included, 222 186 (69.8%) were classified as "cured" and 96 279 (30.2%) as "treatment failure." Among the latter, 37 604 (11.8%) abandoned treatment; 13 193 (4.1%) died due to TB; 15 440 (4.8%) died due to causes other than TB; 28 848 (9.1%) were transferred to another municipality; and 1 194 (0.4%) developed multidrug-resistant TB. The dichotomous models were more likely to show spurious associations when compared with the polytomous model. In the polytomous model, individuals assigned to Directly Observed Treatment Short-course were more likely to be cured than others.

Conclusions: Theoretical models are dynamic structures that need ongoing re-evaluation according to new findings; therefore, this is not a definitive proposal for a TB determination model or analysis plan, but rather a proposal that, at present, is adequate in Brazil and has the potential to be extrapolated or adapted to other areas.