Transactions of the Royal Society of Tropical Medicine and Hygiene · 2020
Impact of incarceration on tuberculosis incidence and its interaction with income distribution inequality in Brazil.
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Pelissari Daniele Maria, Diaz-Quijano Fredi Alexander
Аннотация
BACKGROUND: Deteriorated conditions in the non-prison population can lead to an approximation of its tuberculosis (TB) risk to that in the prison population. We evaluated the association between incarceration and TB incidence rate and its interaction with population income distribution inequality in Brazilian municipalities (2013-2015).
METHODS: We included 954 municipalities with at least one prison. Interaction between the Gini coefficient and prison exposure was analysed in a multiple regression model. We estimated the fraction of TB in the population attributable fraction (PAF) to exposure to prisons according the Gini coefficient.
RESULTS: Compared with the non-prison population, the prisoners had 22.07 times (95% confidence interval [CI] 20.38 to 23.89) the risk of TB in municipalities where the Gini coefficient was <0.60 and 14.96 times (95% CI 11.00 to 18.92) the risk where the Gini coefficient was ≥0.60. A negative interaction in the multiplicative scale was explained by a higher TB incidence in the non-prison population in municipalities with a Gini coefficient ≥0.60. The PAF ranged from 50.06% to 5.19% in municipalities with Gini coefficients <0.40 and ≥0.60, respectively.
CONCLUSIONS: Interventions to reduce prison exposure would have an ostensible impact in population TB incidence rates mainly in settings with lower Gini coefficients. In those with extreme inequality in income distribution, strategies focused on mitigating the effects of socio-economic factors should also be prioritized.
METHODS: We included 954 municipalities with at least one prison. Interaction between the Gini coefficient and prison exposure was analysed in a multiple regression model. We estimated the fraction of TB in the population attributable fraction (PAF) to exposure to prisons according the Gini coefficient.
RESULTS: Compared with the non-prison population, the prisoners had 22.07 times (95% confidence interval [CI] 20.38 to 23.89) the risk of TB in municipalities where the Gini coefficient was <0.60 and 14.96 times (95% CI 11.00 to 18.92) the risk where the Gini coefficient was ≥0.60. A negative interaction in the multiplicative scale was explained by a higher TB incidence in the non-prison population in municipalities with a Gini coefficient ≥0.60. The PAF ranged from 50.06% to 5.19% in municipalities with Gini coefficients <0.40 and ≥0.60, respectively.
CONCLUSIONS: Interventions to reduce prison exposure would have an ostensible impact in population TB incidence rates mainly in settings with lower Gini coefficients. In those with extreme inequality in income distribution, strategies focused on mitigating the effects of socio-economic factors should also be prioritized.