RESUMO
BACKGROUND: Social protection can reduce poverty and act on the determinants of tuberculosis (TB). OBJECTIVE: To evaluate the impact of the Family Health Strategy (FHS) and the Bolsa Família Programme on TB-related mortality in Brazil. METHODS: This was an ecological study in which the units of analysis were Brazilian municipalities between 2001 and 2012. The principal independent variables were the levels of coverage of the primary health care system and the conditional cash transfer programme. The dependent variable was TB mortality rate (obtained from national databases). Descriptive analysis and negative binomial regression based on panel data using fixed-effects models were performed. Crude and adjusted estimates were calculated for continuous and categorical variables. RESULTS: A high FHS coverage was significantly associated with a reduction in the TB mortality rate (RR 0.80, 95%CI 0.72-0.89). An increase in the coverage of the Brazilian cash transfer programme was significantly associated with a reduction in the TB mortality rate (RR 0.87, 95%CI 0.81-0.96). CONCLUSION: FHS and the Bolsa Família conditional cash transfer programme had a positive impact on the TB mortality rate in Brazil. Public policies should include economic support combined with health promotion.
Assuntos
Saúde da Família/economia , Assistência Pública/estatística & dados numéricos , Tuberculose/mortalidade , Brasil/epidemiologia , Cidades , Hospitalização/tendências , Humanos , Incidência , Vigilância da População , Pobreza , Atenção Primária à Saúde/economia , Assistência Pública/tendências , Análise de Regressão , Tuberculose/economia , Tuberculose/prevenção & controleRESUMO
BACKGROUND: Tackling the social determinants of Tuberculosis (TB) through social protection is a key element of the post-2015 End TB Strategy. However, evidence informing policies are still scarce. Mathematical modelling has the potential to contribute to fill this knowledge gap, but existing models are inadequate. The S-PROTECT consortium aimed to develop an innovative mathematical modelling approach to better understand the role of social protection to improve TB care, prevention and control. METHODS: S-PROTECT used a three-steps approach: 1) the development of a conceptual framework; 2) the extraction from this framework of three high-priority mechanistic pathways amenable for modelling; 3) the development of a revised version of a standard TB transmission model able to capture the structure of these pathways. As a test case we used the Bolsa Familia Programme (BFP), the Brazilian conditional cash transfer scheme. RESULTS: Assessing one of these pathways, we estimated that BFP can reduce TB prevalence by 4% by improving households income and thus their nutritional status. When looking at the direct impact via malnutrition (not income mediated) the impact was 33%. This variation was due to limited data availability, uncertainties on data transformation and the pathway approach taken. These results are preliminary and only aim to serve as illustrative example of the methodological challenges encountered in this first modelling attempt, nonetheless they suggest the potential added value of integrating TB standard of care with social protection strategies. CONCLUSIONS: Results are to be confirmed with further analysis. However, by developing a generalizable modelling framework, S-PROTECT proved that the modelling of social protection is complex, but doable and allowed to draw the research road map for the future in this field.
Assuntos
Modelos Teóricos , Política Pública , Tuberculose/prevenção & controle , Brasil/epidemiologia , Humanos , Renda , Estado Nutricional , Determinantes Sociais da Saúde , Tuberculose/epidemiologiaRESUMO
OBJECTIVE: To evaluate the impact of the Brazilian cash transfer programme (Bolsa Família Programme, BFP) on tuberculosis (TB) incidence in Brazil from 2004 to 2012. DESIGN: We studied tuberculosis surveillance data using a combination of an ecological multiple-group and time-trend design covering 2458 Brazilian municipalities. The main independent variable was BFP coverage and the outcome was the TB incidence rate. All study variables were obtained from national databases. We used fixed-effects negative binomial models for panel data adjusted for selected covariates and a variable representing time. RESULTS: After controlling for covariates, TB incidence rates were significantly reduced in municipalities with high BFP coverage compared with those with low and intermediate coverage (in a model with a time variable incidence rate ratio = 0.96, 95%CI 0.93-0.99). CONCLUSION: This was the first evidence of a statistically significant association between the increase in cash transfer programme coverage and a reduction in TB incidence rate. Our findings provide support for social protection interventions for tackling TB worldwide.