Evidence map›Paper›PMID 41448810›Full record

ArticleBMJ global health2025

Estimating the impact of nutritional transition and ending hunger on tuberculosis in 12 high-burden countries: a model-based scenario analysis.

Chieh-Yin Wu, Chu-Chang Ku, Christopher Finn McQuaid, Knut Lönnroth, J Peter Cegielski, James Bentham, Majid Ezzati, Hsien-Ho Lin

Abstract read
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Article in BMJ global health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Chieh-Yin WuNational Taiwan University, Taipei City, Taiwan.ORCID 0000-0001-6024-6174
Chu-Chang KuDepartment of Infectious Disease Epidemiology and Dynamics, London School of Hygiene & Tropical Medicine, London, UK.ORCID 0000-0002-4719-117X
Christopher Finn McQuaidDepartment of Infectious Disease Epidemiology and Dynamics, London School of Hygiene & Tropical Medicine, London, UK.ORCID 0000-0001-6199-0931
Knut LönnrothDepartment of Global Public Health, Karolinska Institute, Stockholm, Sweden.ORCID 0000-0001-6944-0256
J Peter CegielskiDepartment of Epidemiology, Emory University Rollins School of Public Health, Atlanta, Georgia, USA.
James BenthamSchool of Mathematics, Statistics and Physics, Newcastle University, Newcastle upon Tyne, UK.ORCID 0000-0001-5733-9417
Majid EzzatiSchool of Public Health, Imperial College London, London, UK.
Hsien-Ho LinNational Taiwan University, Taipei City, Taiwan hsienho@ntu.edu.tw.ORCID 0000-0002-7481-6016

Funding

Emory/Georgia TB Research Advancement Center (TRAC)P30AI168386 · NIAID · EMORY UNIVERSITY · PI Jeffrey M Collins · 2022 to 2026
$5.8M
NIAID NIH HHS P30 AI168386
6 · The paper itself

Abstract

backgroundNutrition is a critical determinant of tuberculosis (TB), providing a protective effect at high body mass index (BMI) and incurring an increased risk of TB disease at low BMI. Global nutritional transition and interventions to end hunger could directly affect the TB epidemic in high TB burden countries.

methodsWe constructed dynamic TB transmission models for 12 high TB burden countries with low HIV prevalence. We explicitly accounted for the effects of BMI on TB disease progression and treatment outcomes using a meta-analysis of longitudinal cohort studies, incorporating the effect of BMI mediated through diabetes. The models were calibrated to historical trends in TB epidemiology and mean BMI. We estimated potential changes in TB incidence and mortality between 2015 and 2030 under different scenarios of population nutrition.

findingsCompared with a scenario where mean BMI remained at 2015 levels, if past trends in mean BMI continued then by 2030 TB incidence and mortality would decline by a cumulative 14.7% (95% credible interval: 12.7%-16.7%) and 15.6% (12.5%-19.2%), respectively. In comparison, achieving zero hunger by 2030 would reduce incidence and mortality by 32.0% (20.0%-43.8%) and 37.3% (26.1%-49.6%), respectively. If past trends continued and zero hunger was also achieved, incidence and mortality would be reduced by 38.2% (27.0%-49.1%) and 42.4% (32.1%-53.5%), respectively, equivalent to preventing 20.6 million people developing TB disease and averting 5.4 million TB deaths over 15 years in the 12 high-burden countries.

conclusionsNutrition transitions and interventions to end hunger could have a major impact on the future epidemiology of TB in high-burden countries. Investment is urgently required to implement and scale up nutritional interventions.

Indexed as

HungerNutritional StatusTuberculosisBody Mass IndexGlobal HealthHumansIncidenceLongitudinal StudiesNutritionTuberculosis

Identifiers

PMID41448810
PMCPMC12742055

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.