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Background Tuberculosis (TB) treatment outcomes are influenced not only by disease-specific programs but also by broader health system capacity and population-level vulnerabilities. This study examined the determinants of TB treatment success in low- and lower-middle-income countries and assessed whether these associations differed across income groups. Methods An unbalanced country-year panel dataset comprising 1,216 observations from 56 low- and lower-middle-income countries between 2001 and 2023 was analyzed. The dependent variable was the treatment success rate among new TB cases. The independent variables included infectious disease service coverage, TB case detection rate, TB incidence, health expenditure, out-of-pocket health expenditure, immunization coverage, undernutrition, HIV prevalence, malaria incidence, population growth, and life expectancy. Associations were estimated using a two-way fixed-effects model with Driscoll–Kraay robust standard errors. Robustness checks and income-group subgroup analyses were also conducted. Results Infectious disease service coverage ( β = 0.0925; p = 0.003), immunization coverage ( β = 0.0845; p = 0.002), population growth ( β = 0.9145; p = 0.012), and life expectancy ( β = 0.3911; p = 0.001) were positively associated with TB treatment success. Per capita health expenditure showed a positive but marginally significant association ( β = 1.4590; p = 0.053). Undernutrition was also positively associated with treatment success ( β = 0.2911; p < 0.001); however, this unexpected ecological finding should not be interpreted as evidence of a protective effect. In low-income countries, infectious disease service coverage and TB case detection were positively associated with treatment success, whereas HIV prevalence was negatively associated with it. In lower-middle-income countries, health expenditure, immunization coverage, undernutrition, population growth, and life expectancy showed positive associations. Conclusion TB treatment success is associated with broader health system conditions, although its determinants vary across income groups. Strengthening infectious disease service coverage, case detection, TB–HIV service integration, routine preventive health services, and the effective use of health resources may contribute to improved treatment outcomes. The unexpected macro-level association observed for undernutrition warrants further investigation using multilevel and patient-level data.
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Dindar et al. (2026) studied this question.
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