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

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. In this cross-sectional study, we pooled individual-level data...

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Veröffentlicht in:The Lancet (British edition) 2021-07, Vol.398 (10296), p.238-248
Hauptverfasser: Teufel, Felix, Seiglie, Jacqueline A, Geldsetzer, Pascal, Theilmann, Michaela, Marcus, Maja E, Ebert, Cara, Arboleda, William Andres Lopez, Agoudavi, Kokou, Andall-Brereton, Glennis, Aryal, Krishna K, Bicaba, Brice Wilfried, Brian, Garry, Bovet, Pascal, Dorobantu, Maria, Gurung, Mongal Singh, Guwatudde, David, Houehanou, Corine, Houinato, Dismand, Jorgensen, Jutta M Adelin, Kagaruki, Gibson B, Karki, Khem B, Labadarios, Demetre, Martins, Joao S, Mayige, Mary T, McClure, Roy Wong, Mwangi, Joseph Kibachio, Mwalim, Omar, Norov, Bolormaa, Crooks, Sarah, Farzadfar, Farshad, Moghaddam, Sahar Saeedi, Silver, Bahendeka K, Sturua, Lela, Wesseh, Chea Stanford, Stokes, Andrew C, Essien, Utibe R, De Neve, Jan-Walter, Atun, Rifat, Davies, Justine I, Vollmer, Sebastian, Bärnighausen, Till W, Ali, Mohammed K, Meigs, James B, Wexler, Deborah J, Manne-Goehler, Jennifer
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container_end_page 248
container_issue 10296
container_start_page 238
container_title The Lancet (British edition)
container_volume 398
creator Teufel, Felix
Seiglie, Jacqueline A
Geldsetzer, Pascal
Theilmann, Michaela
Marcus, Maja E
Ebert, Cara
Arboleda, William Andres Lopez
Agoudavi, Kokou
Andall-Brereton, Glennis
Aryal, Krishna K
Bicaba, Brice Wilfried
Brian, Garry
Bovet, Pascal
Dorobantu, Maria
Gurung, Mongal Singh
Guwatudde, David
Houehanou, Corine
Houinato, Dismand
Jorgensen, Jutta M Adelin
Kagaruki, Gibson B
Karki, Khem B
Labadarios, Demetre
Martins, Joao S
Mayige, Mary T
McClure, Roy Wong
Mwangi, Joseph Kibachio
Mwalim, Omar
Norov, Bolormaa
Crooks, Sarah
Farzadfar, Farshad
Moghaddam, Sahar Saeedi
Silver, Bahendeka K
Sturua, Lela
Wesseh, Chea Stanford
Stokes, Andrew C
Essien, Utibe R
De Neve, Jan-Walter
Atun, Rifat
Davies, Justine I
Vollmer, Sebastian
Bärnighausen, Till W
Ali, Mohammed K
Meigs, James B
Wexler, Deborah J
Manne-Goehler, Jennifer
description 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. 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. 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 age
doi_str_mv 10.1016/S0140-6736(21)00844-8
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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. 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. 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. Harvard T H Chan School of Public Health McLennan Fund: Dean's Challenge Grant Program.</description><identifier>ISSN: 0140-6736</identifier><identifier>EISSN: 1474-547X</identifier><identifier>DOI: 10.1016/S0140-6736(21)00844-8</identifier><identifier>PMID: 34274065</identifier><language>eng</language><publisher>England: Elsevier Ltd</publisher><subject>Adult ; Biomarkers ; Body Mass Index ; Body weight ; Cross-Sectional Studies ; Datasets ; Developing Countries - statistics &amp; numerical data ; Diabetes ; Diabetes mellitus ; Diabetes Mellitus - diagnosis ; Diabetes Mellitus - epidemiology ; Empirical analysis ; Fasting ; Female ; Global Health ; Glucose ; Glycated Hemoglobin - analysis ; Health risks ; Health Surveys ; Hemoglobin ; Humans ; Income ; Infectious diseases ; Low income groups ; Male ; Men ; Metabolism ; Middle Aged ; Obesity ; Obesity - epidemiology ; Overweight ; Plasma ; Polls &amp; surveys ; Population ; Poverty ; Prevalence ; Public health ; Screening ; Sex ; Thresholds ; Trends ; Women</subject><ispartof>The Lancet (British edition), 2021-07, Vol.398 (10296), p.238-248</ispartof><rights>2021 Elsevier Ltd</rights><rights>Copyright © 2021 Elsevier Ltd. All rights reserved.</rights><rights>COPYRIGHT 2021 Elsevier B.V.</rights><rights>2021. Elsevier Ltd</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c537t-be22ba82677a955ee57c044897df59d554290bd1a62485f8d34c2ae7c4ba35ab3</citedby><cites>FETCH-LOGICAL-c537t-be22ba82677a955ee57c044897df59d554290bd1a62485f8d34c2ae7c4ba35ab3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/2552016701?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,776,780,3536,27903,27904,64361,64363,64365,65309,72215</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34274065$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Teufel, Felix</creatorcontrib><creatorcontrib>Seiglie, Jacqueline A</creatorcontrib><creatorcontrib>Geldsetzer, Pascal</creatorcontrib><creatorcontrib>Theilmann, Michaela</creatorcontrib><creatorcontrib>Marcus, Maja E</creatorcontrib><creatorcontrib>Ebert, Cara</creatorcontrib><creatorcontrib>Arboleda, William Andres Lopez</creatorcontrib><creatorcontrib>Agoudavi, Kokou</creatorcontrib><creatorcontrib>Andall-Brereton, Glennis</creatorcontrib><creatorcontrib>Aryal, Krishna K</creatorcontrib><creatorcontrib>Bicaba, Brice Wilfried</creatorcontrib><creatorcontrib>Brian, Garry</creatorcontrib><creatorcontrib>Bovet, Pascal</creatorcontrib><creatorcontrib>Dorobantu, Maria</creatorcontrib><creatorcontrib>Gurung, Mongal Singh</creatorcontrib><creatorcontrib>Guwatudde, David</creatorcontrib><creatorcontrib>Houehanou, Corine</creatorcontrib><creatorcontrib>Houinato, Dismand</creatorcontrib><creatorcontrib>Jorgensen, Jutta M Adelin</creatorcontrib><creatorcontrib>Kagaruki, Gibson B</creatorcontrib><creatorcontrib>Karki, Khem B</creatorcontrib><creatorcontrib>Labadarios, Demetre</creatorcontrib><creatorcontrib>Martins, Joao S</creatorcontrib><creatorcontrib>Mayige, Mary T</creatorcontrib><creatorcontrib>McClure, Roy Wong</creatorcontrib><creatorcontrib>Mwangi, Joseph Kibachio</creatorcontrib><creatorcontrib>Mwalim, Omar</creatorcontrib><creatorcontrib>Norov, Bolormaa</creatorcontrib><creatorcontrib>Crooks, Sarah</creatorcontrib><creatorcontrib>Farzadfar, Farshad</creatorcontrib><creatorcontrib>Moghaddam, Sahar Saeedi</creatorcontrib><creatorcontrib>Silver, Bahendeka K</creatorcontrib><creatorcontrib>Sturua, Lela</creatorcontrib><creatorcontrib>Wesseh, Chea Stanford</creatorcontrib><creatorcontrib>Stokes, Andrew C</creatorcontrib><creatorcontrib>Essien, Utibe R</creatorcontrib><creatorcontrib>De Neve, Jan-Walter</creatorcontrib><creatorcontrib>Atun, Rifat</creatorcontrib><creatorcontrib>Davies, Justine I</creatorcontrib><creatorcontrib>Vollmer, Sebastian</creatorcontrib><creatorcontrib>Bärnighausen, Till W</creatorcontrib><creatorcontrib>Ali, Mohammed K</creatorcontrib><creatorcontrib>Meigs, James B</creatorcontrib><creatorcontrib>Wexler, Deborah J</creatorcontrib><creatorcontrib>Manne-Goehler, Jennifer</creatorcontrib><title>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</title><title>The Lancet (British edition)</title><addtitle>Lancet</addtitle><description>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. 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. 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. 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. Harvard T H Chan School of Public Health McLennan Fund: Dean's Challenge Grant Program.</description><subject>Adult</subject><subject>Biomarkers</subject><subject>Body Mass Index</subject><subject>Body weight</subject><subject>Cross-Sectional Studies</subject><subject>Datasets</subject><subject>Developing Countries - statistics &amp; numerical data</subject><subject>Diabetes</subject><subject>Diabetes mellitus</subject><subject>Diabetes Mellitus - diagnosis</subject><subject>Diabetes Mellitus - epidemiology</subject><subject>Empirical analysis</subject><subject>Fasting</subject><subject>Female</subject><subject>Global Health</subject><subject>Glucose</subject><subject>Glycated Hemoglobin - analysis</subject><subject>Health risks</subject><subject>Health Surveys</subject><subject>Hemoglobin</subject><subject>Humans</subject><subject>Income</subject><subject>Infectious diseases</subject><subject>Low income groups</subject><subject>Male</subject><subject>Men</subject><subject>Metabolism</subject><subject>Middle Aged</subject><subject>Obesity</subject><subject>Obesity - epidemiology</subject><subject>Overweight</subject><subject>Plasma</subject><subject>Polls &amp; surveys</subject><subject>Population</subject><subject>Poverty</subject><subject>Prevalence</subject><subject>Public health</subject><subject>Screening</subject><subject>Sex</subject><subject>Thresholds</subject><subject>Trends</subject><subject>Women</subject><issn>0140-6736</issn><issn>1474-547X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNqFkcuKFDEUhgtRnHH0EZSAICNYmqRyqXYj4-ANBlyo4C6cSk4PGVOVNkm10zuXvo3v5JOY7p6ZhRtXgZ_v5CT_1zQPGX3OKFMvPlEmaKt0p445e0ppL0Tb32oOmdCilUJ_vd0c3iAHzb2cLyilQlF5tznoBNeCKnnY_H4d3aYdIWfiJ4eXBCZHnIcBC2aSfP5WcyI1CfFH6ycbR9who3cu4HVi4zyV5DG_JEBsijm3GW3xcYJAcpndhsQlmWCfhA1JuEqYcSo1WuOz7W6_9m6G0AZcYyAOCmw3q17--flLMUXAzaHk-82dJYSMD67Oo-bL2zefT9-3Zx_ffTg9OWut7HRpB-R8gJ4rrWEhJaLUlgrRL7RbyoWTUvAFHRwDxUUvl73rhOWA2ooBOglDd9Qc7-9dpfh9xlzM6LPFEGDCOGfDpex410lBK_r4H_Qizqn-c0fxKktTVqkne-ocApptb1PBy3IOc87GnCjVKymZ4hWUe3DXY8KlWSU_QtoYRs1WvdmpN1uvhjOzU2_6Ovfo6hnzMKK7mbp2XYFXewBrb2uPyWTrcbLofKqyjIv-Pyv-AmOBvxk</recordid><startdate>20210717</startdate><enddate>20210717</enddate><creator>Teufel, Felix</creator><creator>Seiglie, Jacqueline A</creator><creator>Geldsetzer, Pascal</creator><creator>Theilmann, Michaela</creator><creator>Marcus, Maja E</creator><creator>Ebert, Cara</creator><creator>Arboleda, William Andres Lopez</creator><creator>Agoudavi, Kokou</creator><creator>Andall-Brereton, Glennis</creator><creator>Aryal, Krishna K</creator><creator>Bicaba, Brice Wilfried</creator><creator>Brian, Garry</creator><creator>Bovet, Pascal</creator><creator>Dorobantu, Maria</creator><creator>Gurung, Mongal Singh</creator><creator>Guwatudde, David</creator><creator>Houehanou, Corine</creator><creator>Houinato, Dismand</creator><creator>Jorgensen, Jutta M Adelin</creator><creator>Kagaruki, Gibson B</creator><creator>Karki, Khem B</creator><creator>Labadarios, Demetre</creator><creator>Martins, Joao S</creator><creator>Mayige, Mary T</creator><creator>McClure, Roy Wong</creator><creator>Mwangi, Joseph Kibachio</creator><creator>Mwalim, Omar</creator><creator>Norov, Bolormaa</creator><creator>Crooks, Sarah</creator><creator>Farzadfar, Farshad</creator><creator>Moghaddam, Sahar Saeedi</creator><creator>Silver, Bahendeka K</creator><creator>Sturua, Lela</creator><creator>Wesseh, Chea Stanford</creator><creator>Stokes, Andrew C</creator><creator>Essien, Utibe R</creator><creator>De Neve, Jan-Walter</creator><creator>Atun, Rifat</creator><creator>Davies, Justine I</creator><creator>Vollmer, Sebastian</creator><creator>Bärnighausen, Till W</creator><creator>Ali, Mohammed K</creator><creator>Meigs, James B</creator><creator>Wexler, Deborah J</creator><creator>Manne-Goehler, Jennifer</creator><general>Elsevier Ltd</general><general>Elsevier B.V</general><general>Elsevier Limited</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>0TT</scope><scope>0TZ</scope><scope>0U~</scope><scope>3V.</scope><scope>7QL</scope><scope>7QP</scope><scope>7RV</scope><scope>7TK</scope><scope>7U7</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88A</scope><scope>88C</scope><scope>88E</scope><scope>88G</scope><scope>88I</scope><scope>8AF</scope><scope>8AO</scope><scope>8C1</scope><scope>8C2</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AN0</scope><scope>ASE</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FPQ</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K6X</scope><scope>K9-</scope><scope>K9.</scope><scope>KB0</scope><scope>KB~</scope><scope>LK8</scope><scope>M0R</scope><scope>M0S</scope><scope>M0T</scope><scope>M1P</scope><scope>M2M</scope><scope>M2O</scope><scope>M2P</scope><scope>M7N</scope><scope>M7P</scope><scope>MBDVC</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PSYQQ</scope><scope>Q9U</scope><scope>S0X</scope><scope>7X8</scope></search><sort><creationdate>20210717</creationdate><title>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</title><author>Teufel, Felix ; Seiglie, Jacqueline A ; Geldsetzer, Pascal ; Theilmann, Michaela ; Marcus, Maja E ; Ebert, Cara ; Arboleda, William Andres Lopez ; Agoudavi, Kokou ; Andall-Brereton, Glennis ; Aryal, Krishna K ; Bicaba, Brice Wilfried ; Brian, Garry ; Bovet, Pascal ; Dorobantu, Maria ; Gurung, Mongal Singh ; Guwatudde, David ; Houehanou, Corine ; Houinato, Dismand ; Jorgensen, Jutta M Adelin ; Kagaruki, Gibson B ; Karki, Khem B ; Labadarios, Demetre ; Martins, Joao S ; Mayige, Mary T ; McClure, Roy Wong ; Mwangi, Joseph Kibachio ; Mwalim, Omar ; Norov, Bolormaa ; Crooks, Sarah ; Farzadfar, Farshad ; Moghaddam, Sahar Saeedi ; Silver, Bahendeka K ; Sturua, Lela ; Wesseh, Chea Stanford ; Stokes, Andrew C ; Essien, Utibe R ; De Neve, Jan-Walter ; Atun, Rifat ; Davies, Justine I ; Vollmer, Sebastian ; Bärnighausen, Till W ; Ali, Mohammed K ; Meigs, James B ; Wexler, Deborah J ; Manne-Goehler, Jennifer</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c537t-be22ba82677a955ee57c044897df59d554290bd1a62485f8d34c2ae7c4ba35ab3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Adult</topic><topic>Biomarkers</topic><topic>Body Mass Index</topic><topic>Body weight</topic><topic>Cross-Sectional Studies</topic><topic>Datasets</topic><topic>Developing Countries - statistics &amp; 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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. 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. 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. Harvard T H Chan School of Public Health McLennan Fund: Dean's Challenge Grant Program.</abstract><cop>England</cop><pub>Elsevier Ltd</pub><pmid>34274065</pmid><doi>10.1016/S0140-6736(21)00844-8</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record>
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source MEDLINE; Elsevier ScienceDirect Journals; ProQuest Central UK/Ireland
subjects Adult
Biomarkers
Body Mass Index
Body weight
Cross-Sectional Studies
Datasets
Developing Countries - statistics & numerical data
Diabetes
Diabetes mellitus
Diabetes Mellitus - diagnosis
Diabetes Mellitus - epidemiology
Empirical analysis
Fasting
Female
Global Health
Glucose
Glycated Hemoglobin - analysis
Health risks
Health Surveys
Hemoglobin
Humans
Income
Infectious diseases
Low income groups
Male
Men
Metabolism
Middle Aged
Obesity
Obesity - epidemiology
Overweight
Plasma
Polls & surveys
Population
Poverty
Prevalence
Public health
Screening
Sex
Thresholds
Trends
Women
title 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
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