Strong effect of demographic changes on Tuberculosis susceptibility in South Africa

Bibliographic Data

ID19591649
AuthorsOshiomah P Oyageshio (0009-0009-7891-2505, University of California, Davis, corresponding author), Justin W Myrick (University of California, Davis, corresponding author), Jamie Saayman (South African Medical Research Council, corresponding author), Lena van der Westhuizen (South African Medical Research Council, corresponding author), Dana R Al-Hindi (University of California, Davis, corresponding author), Austin W Reynolds (0000-0002-7154-1379, University of North Texas, corresponding author), Noah Zaitlen (0000-0002-3553-3670, University of California, Los Angeles, corresponding author), Eileen G Hoal (0000-0002-6444-5688, South African Medical Research Council, corresponding author), Caitlin Uren (0000-0003-2358-0135, South African Medical Research Council, corresponding author), Marlo Möller (0000-0002-0805-6741, South African Medical Research Council, corresponding author), Brenna M Henn (0000-0003-4998-287X, University of California, Davis, corresponding author)
EditorsIndira Govender (0000-0003-0598-7388)
Year2024
Volume4
Issue7
Pagese0002643
Publication date2024-07-23
Open AccessYes
TypeARTICLE
VenuePLOS Global Public Health (JOURNAL)
Journal identifiersISSN: 2767-3375 • E-ISSN: 2767-3375
PublisherPublic Library of Science (PLoS) (PUBLISHER)
DOI10.1371/journal.pgph.0002643
PMID39042651
OpenAlexW4400908030
LanguageEN
Citations received1
References cited42

South Africa is among the world’s top eight tuberculosis (TB) burden countries, and despite a focus on HIV-TB co-infection, most of the population living with TB are not HIV co-infected. The disease is endemic across the country, with 80–90% exposure by adulthood. We investigated epidemiological risk factors for (TB) in the Northern Cape Province, South Africa: an understudied TB endemic region with extreme TB incidence (926/100,000). We leveraged the population’s high TB incidence and community transmission to design a case-control study with similar mechanisms of exposure between the groups. We recruited 1,126 participants with suspected TB from 12 community health clinics and generated a cohort of 774 individuals (cases = 374, controls = 400) after implementing our enrollment criteria. All participants were GeneXpert Ultra tested for active TB by a local clinic. We assessed important risk factors for active TB using logistic regression and random forest modeling. We find that factors commonly identified in other global populations tend to replicate in our study, e.g. male gender and residence in a town had significant effects on TB risk (OR: 3.02 [95% CI: 2.30–4.71]; OR: 3.20 [95% CI: 2.26–4.55]). We also tested for demographic factors that may uniquely reflect historical changes in health conditions in South Africa. We find that socioeconomic status (SES) significantly interacts with an individual’s age ( p = 0.0005) indicating that protective effect of higher SES changed across age cohorts. We further find that being born in a rural area and moving to a town strongly increases TB risk, while town birthplace and current rural residence is protective. These interaction effects reflect rapid demographic changes, specifically SES over recent generations and mobility, in South Africa. Our models show that such risk factors combined explain 19–21% of the variance (r 2 ) in TB case/control status

Cohort · Environmental health · Logistic regression · Pathology · Population · Public health · Residence · Socioeconomic status · Tuberculosis · Demography · HIV/AIDS Impact and Responses · Medicine · Pneumonia and Respiratory Infections · Tuberculosis Research and Epidemiology · Epidemiology · Gerontology · Internal Medicine

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