Body-mass index and diabetes risk in 57 low-income and middle-income countries: a cross-sectional study of nationally representative, individual-level data in 685 616 adults - PubMed (original) (raw)

. 2021 Jul 17;398(10296):238-248.

doi: 10.1016/S0140-6736(21)00844-8.

Jacqueline A Seiglie 2, Pascal Geldsetzer 3, Michaela Theilmann 1, Maja E Marcus 4, Cara Ebert 5, William Andres Lopez Arboleda 1, Kokou Agoudavi 6, Glennis Andall-Brereton 7, Krishna K Aryal 8, Brice Wilfried Bicaba 9, Garry Brian 10, Pascal Bovet 11, Maria Dorobantu 12, Mongal Singh Gurung 13, David Guwatudde 14, Corine Houehanou 15, Dismand Houinato 15, Jutta M Adelin Jorgensen 16, Gibson B Kagaruki 17, Khem B Karki 18, Demetre Labadarios 19, Joao S Martins 20, Mary T Mayige 17, Roy Wong McClure 21, Joseph Kibachio Mwangi 22, Omar Mwalim 23, Bolormaa Norov 24, Sarah Crooks 7, Farshad Farzadfar 25, Sahar Saeedi Moghaddam 26, Bahendeka K Silver 27, Lela Sturua 28, Chea Stanford Wesseh 29, Andrew C Stokes 30, Utibe R Essien 31, Jan-Walter De Neve 1, Rifat Atun 32, Justine I Davies 33, Sebastian Vollmer 4, Till W Bärnighausen 34, Mohammed K Ali 35, James B Meigs 36, Deborah J Wexler 2, Jennifer Manne-Goehler 37

Affiliations

Body-mass index and diabetes risk in 57 low-income and middle-income countries: a cross-sectional study of nationally representative, individual-level data in 685 616 adults

Felix Teufel et al. Lancet. 2021.

Abstract

Background: The prevalence of overweight, obesity, and diabetes is rising rapidly in low-income and middle-income countries (LMICs), but there are scant empirical data on the association between body-mass index (BMI) and diabetes in these settings.

Methods: In this cross-sectional study, we pooled individual-level data from nationally representative surveys across 57 LMICs. We identified all countries in which a WHO Stepwise Approach to Surveillance (STEPS) survey had been done during a year in which the country fell into an eligible World Bank income group category. For LMICs that did not have a STEPS survey, did not have valid contact information, or declined our request for data, we did a systematic search for survey datasets. Eligible surveys were done during or after 2008; had individual-level data; were done in a low-income, lower-middle-income, or upper-middle-income country; were nationally representative; had a response rate of 50% or higher; contained a diabetes biomarker (either a blood glucose measurement or glycated haemoglobin [HbA1c]); and contained data on height and weight. Diabetes was defined biologically as a fasting plasma glucose concentration of 7·0 mmol/L (126·0 mg/dL) or higher; a random plasma glucose concentration of 11·1 mmol/L (200·0 mg/dL) or higher; or a HbA1c of 6·5% (48·0 mmol/mol) or higher, or by self-reported use of diabetes medication. We included individuals aged 25 years or older with complete data on diabetes status, BMI (defined as normal [18·5-22·9 kg/m2], upper-normal [23·0-24·9 kg/m2], overweight [25·0-29·9 kg/m2], or obese [≥30·0 kg/m2]), sex, and age. Countries were categorised into six geographical regions: Latin America and the Caribbean, Europe and central Asia, east, south, and southeast Asia, sub-Saharan Africa, Middle East and north Africa, and Oceania. We estimated the association between BMI and diabetes risk by multivariable Poisson regression and receiver operating curve analyses, stratified by sex and geographical region.

Findings: Our pooled dataset from 58 nationally representative surveys in 57 LMICs included 685 616 individuals. The overall prevalence of overweight was 27·2% (95% CI 26·6-27·8), of obesity was 21·0% (19·6-22·5), and of diabetes was 9·3% (8·4-10·2). In the pooled analysis, a higher risk of diabetes was observed at a BMI of 23 kg/m2 or higher, with a 43% greater risk of diabetes for men and a 41% greater risk for women compared with a BMI of 18·5-22·9 kg/m2. Diabetes risk also increased steeply in individuals aged 35-44 years and in men aged 25-34 years in sub-Saharan Africa. In the stratified analyses, there was considerable regional variability in this association. Optimal BMI thresholds for diabetes screening ranged from 23·8 kg/m2 among men in east, south, and southeast Asia to 28·3 kg/m2 among women in the Middle East and north Africa and in Latin America and the Caribbean.

Interpretation: The association between BMI and diabetes risk in LMICs is subject to substantial regional variability. Diabetes risk is greater at lower BMI thresholds and at younger ages than reflected in currently used BMI cutoffs for assessing diabetes risk. These findings offer an important insight to inform context-specific diabetes screening guidelines.

Funding: Harvard T H Chan School of Public Health McLennan Fund: Dean's Challenge Grant Program.

Copyright © 2021 Elsevier Ltd. All rights reserved.

PubMed Disclaimer

Conflict of interest statement

Declaration of interests MKA reports receiving a grant from Merck and Co awarded to Emory University, outside the submitted work. DJW reports serving on a data monitoring committee for Novo Nordisk SOUL and FLOW trials. JBM reports serving as an academic associate for the American clinical laboratory, Quest Diagnostics. All other authors declare no competing interests.

Figures

Figure 1.

Figure 1.

Geographic region-sex stratified generalized additive models of body mass index and diabetes in 57 low- and middle-income countries Notes: Figure shows generalized additive models of body mass index and proportion with diabetes for women (left panel) and men (right panel). All analyses were stratified by world regions. Grey areas represent 95% confidence intervals.

Figure 2.

Figure 2.

Geographic region-sex stratified risk ratios of body mass index categories and diabetes in 57 low- and middle-income countries Notes: Figure shows adjusted risk ratios from multivariable Poisson regression models in the pooled sample and by world region, separately for women (left panel) and men (right panel). The outcome was diabetes based on measured biomarkers and the exposure measured body-mass index (BMI) grouped into five categories: underweight (<18.5 kg/m2; not displayed), normal (18.5 to <23 kg/m2; reference category), upper-normal (23 to <25 kg/m2), overweight (25 to <30 kg/m2), and obese (>30 kg/m2). All models controlled for age (years) and included country-level fixed effects. Error bars represent 95% confidence intervals.

Figure 3.

Figure 3.

Geographic region-sex stratified ROC curves for body mass index and diabetes in 57 low- and middle-income countries Notes: Figure shows receiver operating characteristic (ROC) curves of BMI as a classifier for diabetes. Analysis stratified by sex and world region. Each country was weighed equally. Geographic region abbreviations: Latin America and the Caribbean (LA & CA), Europe and Central Asia (E & CA), East/Southeast Asia (ESA), Sub-Saharan Africa (SSA), Middle East and North Africa (ME & NA), and Oceania (OCN).

Comment in

References

    1. Obesity and overweight [Internet]. [cited 2020 Jun 11]. Available from: https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight
    1. Chooi YC, Ding C, Magkos F. The epidemiology of obesity. Metabolism. 2019. March 1;92:6–10. - PubMed
    1. Di Cesare M, Bentham J, Stevens GA, Zhou B, Danaei G, Lu Y, et al. Trends in adult body-mass index in 200 countries from 1975 to 2014: A pooled analysis of 1698 population-based measurement studies with 19.2 million participants. The Lancet. 2016. April 2;387(10026):1377–96. - PMC - PubMed
    1. Popkin BM, Slining MM. New dynamics in global obesity facing low- and middle-income countries. Vol. 14, Obesity Reviews. NIH Public Access; 2013. p. 11–20. - PMC - PubMed
    1. Trends in obesity and diabetes across Africa from 1980 to 2014: an analysis of pooled population-based studies - PubMed [Internet]. [cited 2020 Jul 29]. Available from: https://pubmed-ncbi-nlm-nih-gov.ezp-prod1.hul.harvard.edu/28582528/ - PMC - PubMed

Publication types

MeSH terms

Substances

Grants and funding

LinkOut - more resources