Data inputs for analysis of how BMI influences TB incidence

This is a collated set of data input collated from public sources for use in an analysis of the influence of BMI on TB incidence (https://github.com/petedodd/bmitb). We used estimates for 2022 of BMI by country, sex, and age from the NCD-RisC consortium,1 which were downloaded from https://ncdrisc.org/data-downloads-adiposity.html on 14/Feb/2024. In particular, we used the files: NCD_RisC_Lancet_2024_BMI_child_adolescent_country.csv NCD_RisC_Lancet_2024_BMI_female_age_specific_country.csv NCD_RisC_Lancet_2024_BMI_male_age_specific_country.csv For the adolescent group aged 15-19 years, we also made use of WHO reference tables to convert NCD-RisC estimates of z-scores into BMIs. These were downloaded from https://www.who.int/tools/growth-reference-data-for-5to19-years/indicators/bmi-for-age on 27/Nov/2023. In particular, we used the files: bmi-boys-z-who-2007-exp.xlsx bmi-girls-z-who-2007-exp.xlsx We used WHO estimates of TB incidence, which were downloaded from https://www.who.int/teams/global-programme-on-tuberculosis-and-lung-health/data on 30/Oct/2024. In particular, we used the files: TB_burden_age_sex_2024-10-30.csv TB_notifications_2024-10-30.csv We used World Population Prospects 2024 demographic estimates from the United Nations Population Division, downloaded from https://population.un.org/wpp/ on 19/August/2025. These were aggregated into relevant age categories for 2023 and included as the file: N8523.Rdata We also used coefficients and variance covariance matrices from the regression in Saunders et al.: general_population_vcov_matrix.csv general_population_piecewise_parameters.csv 1. NCD Risk Factor Collaboration (NCD-RisC). Worldwide trends in underweight and obesity from 1990 to 2022: a pooled analysis of 3663 population-representative studies with 222 million children, adolescents, and adults. Lancet 2024; 403: 1027–50.