Felix Teufel1, Jacqueline A Seiglie2, Pascal Geldsetzer3, Michaela Theilmann1, Maja E Marcus4, Cara Ebert5, William Andres Lopez Arboleda1, Kokou Agoudavi6, Glennis Andall-Brereton7, Krishna K Aryal8, Brice Wilfried Bicaba9, Garry Brian10, Pascal Bovet11, Maria Dorobantu12, Mongal Singh Gurung13, David Guwatudde14, Corine Houehanou15, Dismand Houinato15, Jutta M Adelin Jorgensen16, Gibson B Kagaruki17, Khem B Karki18, Demetre Labadarios19, Joao S Martins20, Mary T Mayige17, Roy Wong McClure21, Joseph Kibachio Mwangi22, Omar Mwalim23, Bolormaa Norov24, Sarah Crooks7, Farshad Farzadfar25, Sahar Saeedi Moghaddam26, Bahendeka K Silver27, Lela Sturua28, Chea Stanford Wesseh29, Andrew C Stokes30, Utibe R Essien31, Jan-Walter De Neve1, Rifat Atun32, Justine I Davies33, Sebastian Vollmer4, Till W Bärnighausen34, Mohammed K Ali35, James B Meigs36, Deborah J Wexler2, Jennifer Manne-Goehler37. 1. Heidelberg Institute of Global Health, Faculty of Medicine and University Hospital, Heidelberg University, Heidelberg, Germany. 2. Diabetes Unit, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA. 3. Heidelberg Institute of Global Health, Faculty of Medicine and University Hospital, Heidelberg University, Heidelberg, Germany; Department of Medicine, Division of Primary Care and Population Health, Stanford University, Stanford, CA, USA. 4. Department of Economics and Centre for Modern Indian Studies, University of Goettingen, Göttingen, Germany. 5. RWI-Leibniz Institute for Economic Research, Essen (Berlin Office), Germany. 6. Togo Ministry of Health, Lome, Togo. 7. Caribbean Public Health Agency, Port of Spain, Trinidad and Tobago. 8. Nepal Health Sector Programme 3, Monitoring Evaluation and Operational Research Project, Abt Associates, Kathmandu, Nepal. 9. Institut National de Santé Publique, Ministère de la santé, Ouagadougou, Burkina Faso. 10. The Fred Hollows Foundation New Zealand, Auckland, New Zealand. 11. Ministry of Health, Victoria, Seychelles; University Center for Primary Care and Public Health, Lausanne, Switzerland. 12. University of Medicine and Pharmacy Carol Davila, Bucharest, Romania. 13. Health Research and Epidemiology Unit, Ministry of Health, Thimphu, Bhutan. 14. Department of Epidemiology and Biostatistics, School of Public Health, Makerere University, Kampala, Uganda. 15. Laboratory of Epidemiology of Chronic and Neurological Diseases, Faculty of Health Sciences, University of Abomey-Calavi, Cotonou, Benin. 16. Department of Public Health, University of Copenhagen, Copenhagen, Denmark. 17. National Institute for Medical Research, Dar es Salaam, Tanzania. 18. Department of Community Medicine and Public Health, Institute of Medicine, Tribhuvan University, Kathmandu, Nepal. 19. Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch, South Africa. 20. Faculty of Medicine and Health Sciences, Universidade Nacional Timor Lorosae, Rua Jacinto Candido, Dili, Timor-Leste. 21. Epidemiology Office and Surveillance, Caja Costarricense de Seguro Social, San Jose, Costa Rica. 22. Division of Non-Communicable Diseases, Ministry of Health, Nairobi, Kenya; Faculté de Médecine, Université de Genève, Geneva, Switzerland. 23. Zanzibar Ministry of Health, Mnazi Mmoja, Zanzibar, Tanzania. 24. National Center for Public Health, Ulaanbaatar, Mongolia. 25. Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran. 26. Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran. 27. St Francis Hospital, Nsambya, Kampala, Uganda. 28. Non-Communicable Diseases Department, National Center for Disease Control and Public Health, Tbilisi, Georgia; Petre Shotadze Tbilisi Medical Academy, Tbilisi, Georgia. 29. Liberia Ministry of Health, Monrovia, Liberia. 30. Department of Global Health, Boston University School of Public Health, Boston, MA, USA. 31. Division of General Internal Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Center for Health Equity Research and Promotion, Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, PA, USA. 32. Department of Global Health and Population, Harvard T H Chan School of Public Health, Harvard University, Boston, MA, USA; Department of Global Health and Social Medicine, Harvard University, Boston, MA, USA. 33. Department of Global Health, Centre for Global Surgery, Stellenbosch University, Stellenbosch, South Africa; MRC/Wits Rural Public Health and Health Transitions Research Unit, School of Public Health, University of Witwatersrand, Johannesburg, South Africa; Institute of Applied Health Research, University of Birmingham, Birmingham, UK. 34. Heidelberg Institute of Global Health, Faculty of Medicine and University Hospital, Heidelberg University, Heidelberg, Germany; Department of Global Health and Population, Harvard T H Chan School of Public Health, Harvard University, Boston, MA, USA; Africa Health Research Institute, Somkhele, South Africa. 35. Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA; Department of Family and Preventive Medicine, School of Medicine, Emory University, Atlanta, GA, USA. 36. Department of General Internal Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA. 37. Medical Practice Evaluation Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA; Division of Infectious Diseases, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. Electronic address: jmanne@partners.org.
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.
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.
Authors: Shivani A Patel; Roopa Shivashankar; Mohammed K Ali; R M Anjana; M Deepa; Deksha Kapoor; Dimple Kondal; Garima Rautela; V Mohan; K M Venkat Narayan; M Masood Kadir; Zafar Fatmi; Dorairaj Prabhakaran; Nikhil Tandon Journal: Glob Heart Date: 2016-03
Authors: Kenneth F Adams; Arthur Schatzkin; Tamara B Harris; Victor Kipnis; Traci Mouw; Rachel Ballard-Barbash; Albert Hollenbeck; Michael F Leitzmann Journal: N Engl J Med Date: 2006-08-22 Impact factor: 91.245
Authors: Paul D'Orazio; Robert W Burnett; Niels Fogh-Andersen; Ellis Jacobs; Katsuhiko Kuwa; Wolf R Külpmann; Lasse Larsson; Andrzej Lewenstam; Anton H J Maas; Gerhard Mager; Jerzy W Naskalski; Anthony O Okorodudu Journal: Clin Chem Date: 2005-09 Impact factor: 8.327
Authors: Robert Ross; Ian J Neeland; Shizuya Yamashita; Iris Shai; Jaap Seidell; Paolo Magni; Raul D Santos; Benoit Arsenault; Ada Cuevas; Frank B Hu; Bruce A Griffin; Alberto Zambon; Philip Barter; Jean-Charles Fruchart; Robert H Eckel; Yuji Matsuzawa; Jean-Pierre Després Journal: Nat Rev Endocrinol Date: 2020-02-04 Impact factor: 43.330
Authors: Marie Ng; Tom Fleming; Margaret Robinson; Blake Thomson; Nicholas Graetz; Christopher Margono; Erin C Mullany; Stan Biryukov; Cristiana Abbafati; Semaw Ferede Abera; Jerry P Abraham; Niveen M E Abu-Rmeileh; Tom Achoki; Fadia S AlBuhairan; Zewdie A Alemu; Rafael Alfonso; Mohammed K Ali; Raghib Ali; Nelson Alvis Guzman; Walid Ammar; Palwasha Anwari; Amitava Banerjee; Simon Barquera; Sanjay Basu; Derrick A Bennett; Zulfiqar Bhutta; Jed Blore; Norberto Cabral; Ismael Campos Nonato; Jung-Chen Chang; Rajiv Chowdhury; Karen J Courville; Michael H Criqui; David K Cundiff; Kaustubh C Dabhadkar; Lalit Dandona; Adrian Davis; Anand Dayama; Samath D Dharmaratne; Eric L Ding; Adnan M Durrani; Alireza Esteghamati; Farshad Farzadfar; Derek F J Fay; Valery L Feigin; Abraham Flaxman; Mohammad H Forouzanfar; Atsushi Goto; Mark A Green; Rajeev Gupta; Nima Hafezi-Nejad; Graeme J Hankey; Heather C Harewood; Rasmus Havmoeller; Simon Hay; Lucia Hernandez; Abdullatif Husseini; Bulat T Idrisov; Nayu Ikeda; Farhad Islami; Eiman Jahangir; Simerjot K Jassal; Sun Ha Jee; Mona Jeffreys; Jost B Jonas; Edmond K Kabagambe; Shams Eldin Ali Hassan Khalifa; Andre Pascal Kengne; Yousef Saleh Khader; Young-Ho Khang; Daniel Kim; Ruth W Kimokoti; Jonas M Kinge; Yoshihiro Kokubo; Soewarta Kosen; Gene Kwan; Taavi Lai; Mall Leinsalu; Yichong Li; Xiaofeng Liang; Shiwei Liu; Giancarlo Logroscino; Paulo A Lotufo; Yuan Lu; Jixiang Ma; Nana Kwaku Mainoo; George A Mensah; Tony R Merriman; Ali H Mokdad; Joanna Moschandreas; Mohsen Naghavi; Aliya Naheed; Devina Nand; K M Venkat Narayan; Erica Leigh Nelson; Marian L Neuhouser; Muhammad Imran Nisar; Takayoshi Ohkubo; Samuel O Oti; Andrea Pedroza; Dorairaj Prabhakaran; Nobhojit Roy; Uchechukwu Sampson; Hyeyoung Seo; Sadaf G Sepanlou; Kenji Shibuya; Rahman Shiri; Ivy Shiue; Gitanjali M Singh; Jasvinder A Singh; Vegard Skirbekk; Nicolas J C Stapelberg; Lela Sturua; Bryan L Sykes; Martin Tobias; Bach X Tran; Leonardo Trasande; Hideaki Toyoshima; Steven van de Vijver; Tommi J Vasankari; J Lennert Veerman; Gustavo Velasquez-Melendez; Vasiliy Victorovich Vlassov; Stein Emil Vollset; Theo Vos; Claire Wang; XiaoRong Wang; Elisabete Weiderpass; Andrea Werdecker; Jonathan L Wright; Y Claire Yang; Hiroshi Yatsuya; Jihyun Yoon; Seok-Jun Yoon; Yong Zhao; Maigeng Zhou; Shankuan Zhu; Alan D Lopez; Christopher J L Murray; Emmanuela Gakidou Journal: Lancet Date: 2014-05-29 Impact factor: 79.321
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