Identifying sex-specific anthropometric measures and thresholds for dysglycemia screening in an HIV-endemic rural South African population

• Type of Material: Article
• Authors: Alison C. Castle, Harvard University; Susanne S. Hoeppner, Harvard University; Jennifer M. Manne-Goehler, Harvard University; Stephen Olivier, Africa Health Research Institute; Itai M. Magodoro, Emory University; Urisha Singh, University of KwaZulu-Natal; Johnathan A. Edwards, Emory University; Frank Tanser, University of Lincoln; Ingrid V. Bassett, Harvard University; Emily B. Wong, University KwaZulu-Natal; Mark J. Siedner, Harvard University
• Language: English
• Date: 2023-10-27
• Publisher: PLOS
• Publication Version: Final Published Version
• Copyright Statement: © 2023 Castle et al
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): https://doi.org/10.1371%2Fjournal.pgph.0001698
• Title of Journal or Parent Work: PLOS Global Public Health
• Volume: 3
• Issue: 10
• Start Page: 3
• End Page: 10
• Grant/Funding Information: Research reported in this publication was supported by the Fogarty International Center (D43 TW010543; R21 TW011687) and the National Institute of Allergy and Infectious Diseases (T32 AI007433, K24 AI141036, K24 HL166024), of the National Institutes of Health. This research was funded in whole, or in part, by Wellcome [Grant number Wellcome Strategic Core award: 201433/Z/16/A]. For the purpose of open access, the author has applied a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission.
• Keywords: diabetes testing; Sex-specific anthropometric measures; South African; dysglycemia
• Research Categories: Health Sciences, General

Abstract

Valid screening and diagnostic algorithms are needed to achieve 2030 targets proposed by the WHO’s Global Diabetes Compact. We explored anthropometric thresholds to optimally screen and refer individuals for diabetes testing in rural South Africa. We evaluated screening thresholds for waist circumference (WC), body mass index (BMI), and waist-hip ratio (WHR) to detect dysglycemia based on a glycated hemoglobin (HbA1C) ≥6.5% among adults in a population-based study in South Africa using weighted, non-parametric ROC regression analyses. We then assessed the diagnostic validity of traditional obesity thresholds, explored optimal thresholds for this population, and fit models stratified by sex, age, and HIV status. The prevalence of dysglycemia in the total study population (n = 17,846) was 7.7%. WC had greater discriminatory capacity than WHR to detect dysglycemia in men (p-value<0.001) and women (p<0.001). WC had greater discriminatory capacity than BMI to detect dysglycemia in women (p<0.001). However, BMI and WC performed similarly for men (p = 0.589). Whereas traditional WC thresholds for women (>81cm) performed well (sensitivity 91%, positive predictive value [PPV] 14.9%), substantially lower thresholds were needed to achieve acceptable sensitivity and PPV among men (traditional >94cm, derived >79.5cm). WC outperforms BMI as an anthropometric screening measure for dysglycemia in rural South Africa. Whereas WC guideline thresholds are appropriate for women, male-derived WC cutoffs performed better at lower thresholds. In this rural South African population, thresholds that maximize specificity and PPV for efficient resource allocation may be preferred.