Diabetes prevalence and its relationship with education, wealth, and body mass index in twenty-nine low- and middle-income countries

Jacqueline A.  Seiglie; Maja-Emilia  Marcus; Cara Ebert; Nikolaos  Prodromidis; Pascal Geldsetzer; Michaela Theilmann; Kokou Agoudavi; Glennis Andall-Brereton; Krishna K Aryal; Brice Wilfried Bicaba; Pascal Bovet; Garry Brian; Maria Dorobantu; Gladwell Gathecha; Mongal Singh Gurung; David Guwatudde; Mohamed Msaidie; Corine Houehanou; Dismand Houinato; Jutta Mari Adelin Jorgensen; Gibson B Kagaruki; Khem B Karki; Demetre Labadarios; Joao S Martins; Mary T Mayige; Roy Wong McClure; Joseph Kibachio Mwangi; Omar Mwalim; Bolormaa Norov; Sarah Quesnel-Crooks; Bahendeka K Silver; Lela Sturua; Lindiwe Tsabedze; Chea Stanford Wesseh; Andrew Stokes; Rifat Atun; Justine Davies; Sebastian Vollmer; Till W Bärnighausen; Lindsay M Jaacks; James B.  Meigs; Deborah J.  Wexler; Jennifer Manne-Goehler

Diabetes prevalence and its relationship with education, wealth, and body mass index in twenty-nine low- and middle-income countries

Jacqueline A. Seiglie , Maja-Emilia Marcus , Cara Ebert, Nikolaos Prodromidis , Pascal Geldsetzer, Michaela Theilmann, Kokou Agoudavi, Glennis Andall-Brereton, Krishna K Aryal, Brice Wilfried Bicaba, Pascal Bovet, Garry Brian, Maria Dorobantu, Gladwell Gathecha, Mongal Singh Gurung, David Guwatudde, Mohamed Msaidie, Corine Houehanou, Dismand Houinato, Jutta Mari Adelin JorgensenGibson B Kagaruki, Khem B Karki, Demetre Labadarios, Joao S Martins, Mary T Mayige, Roy Wong McClure, Joseph Kibachio Mwangi, Omar Mwalim, Bolormaa Norov, Sarah Quesnel-Crooks, Bahendeka K Silver, Lela Sturua, Lindiwe Tsabedze, Chea Stanford Wesseh, Andrew Stokes, Rifat Atun, Justine Davies, Sebastian Vollmer, Till W Bärnighausen, Lindsay M Jaacks, James B. Meigs , Deborah J. Wexler , Jennifer Manne-Goehler

Applied Health Research

Research output: Contribution to journal › Article › peer-review

Abstract

OBJECTIVE
Diabetes is a rapidly growing health problem in low- and middle-income countries (LMICs), but empirical data on its prevalence and relationship to socioeconomic status are scarce. We estimated diabetes prevalence and the subset with undiagnosed diabetes in 29 LMICs and evaluated the relationship between education, household wealth, body mass index (BMI), and diabetes risk.

RESEARCH DESIGN AND METHODS
We pooled individual-level data from 29 nationally representative surveys conducted between 2008 and 2016, totaling 588,574 participants aged ≥25 years. Diabetes prevalence and the subset with undiagnosed diabetes was calculated overall, by country, World Bank Income Group (WBIG), and geographic region. Multivariable Poisson regression models were used to estimate relative risk (RR).

RESULTS
Overall, prevalence of diabetes in 29 LMICs was 7.5% (95% CI: 7.1% – 8.0%) and of undiagnosed diabetes, 4.9% (4.6% – 5.3%). Diabetes prevalence increased with increasing WBIG: low-income (LICs) 6.7% (5.5% – 8.1%), lower-middle-income (LMIs) 7.1% (6.6% –7.6%), upper-middle-income countries (UMIs) 8.2% (7.5% – 9.0%). Compared with no formal education, greater educational attainment was associated with an increased risk of diabetes across WBIGs, independent of BMI (LICs RR 1.47 [95% CI:1.22–1.78]; LMIs 1.14 [1.06–1.23]; UMIs 1.28 [1.02–1.61]).

CONCLUSIONS
Among 29 LMICs, diabetes prevalence was substantial and increased with increasing WBIG. In contrast to the association seen in high-income countries, diabetes risk was highest among those with greater educational attainment, independent of BMI. LMICs included in this analysis may be at an advanced stage in the nutrition transition but with no reversal in the socioeconomic gradient of diabetes risk.

Original language	English
Journal	Diabetes Care
Publication status	Accepted/In press - 14 Jan 2020

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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Seiglie , J. A., Marcus , M-E., Ebert, C., Prodromidis , N., Geldsetzer, P., Theilmann, M., Agoudavi, K., Andall-Brereton, G., Aryal, K. K., Bicaba, B. W., Bovet, P., Brian, G., Dorobantu, M., Gathecha, G., Singh Gurung, M., Guwatudde, D., Msaidie, M., Houehanou, C., Houinato, D., ... Manne-Goehler, J. (Accepted/In press). Diabetes prevalence and its relationship with education, wealth, and body mass index in twenty-nine low- and middle-income countries. Diabetes Care.

@article{5edf92883263465b9ab91e6f90f2fd74,

title = "Diabetes prevalence and its relationship with education, wealth, and body mass index in twenty-nine low- and middle-income countries",

abstract = "OBJECTIVE Diabetes is a rapidly growing health problem in low- and middle-income countries (LMICs), but empirical data on its prevalence and relationship to socioeconomic status are scarce. We estimated diabetes prevalence and the subset with undiagnosed diabetes in 29 LMICs and evaluated the relationship between education, household wealth, body mass index (BMI), and diabetes risk.RESEARCH DESIGN AND METHODS We pooled individual-level data from 29 nationally representative surveys conducted between 2008 and 2016, totaling 588,574 participants aged ≥25 years. Diabetes prevalence and the subset with undiagnosed diabetes was calculated overall, by country, World Bank Income Group (WBIG), and geographic region. Multivariable Poisson regression models were used to estimate relative risk (RR). RESULTSOverall, prevalence of diabetes in 29 LMICs was 7.5% (95% CI: 7.1% – 8.0%) and of undiagnosed diabetes, 4.9% (4.6% – 5.3%). Diabetes prevalence increased with increasing WBIG: low-income (LICs) 6.7% (5.5% – 8.1%), lower-middle-income (LMIs) 7.1% (6.6% –7.6%), upper-middle-income countries (UMIs) 8.2% (7.5% – 9.0%). Compared with no formal education, greater educational attainment was associated with an increased risk of diabetes across WBIGs, independent of BMI (LICs RR 1.47 [95% CI:1.22–1.78]; LMIs 1.14 [1.06–1.23]; UMIs 1.28 [1.02–1.61]). CONCLUSIONSAmong 29 LMICs, diabetes prevalence was substantial and increased with increasing WBIG. In contrast to the association seen in high-income countries, diabetes risk was highest among those with greater educational attainment, independent of BMI. LMICs included in this analysis may be at an advanced stage in the nutrition transition but with no reversal in the socioeconomic gradient of diabetes risk.",

author = "Seiglie, {Jacqueline A.} and Maja-Emilia Marcus and Cara Ebert and Nikolaos Prodromidis and Pascal Geldsetzer and Michaela Theilmann and Kokou Agoudavi and Glennis Andall-Brereton and Aryal, {Krishna K} and Bicaba, {Brice Wilfried} and Pascal Bovet and Garry Brian and Maria Dorobantu and Gladwell Gathecha and {Singh Gurung}, Mongal and David Guwatudde and Mohamed Msaidie and Corine Houehanou and Dismand Houinato and Jorgensen, {Jutta Mari Adelin} and Kagaruki, {Gibson B} and Karki, {Khem B} and Demetre Labadarios and Martins, {Joao S} and Mayige, {Mary T} and McClure, {Roy Wong} and Mwangi, {Joseph Kibachio} and Omar Mwalim and Bolormaa Norov and Sarah Quesnel-Crooks and Silver, {Bahendeka K} and Lela Sturua and Lindiwe Tsabedze and Wesseh, {Chea Stanford} and Andrew Stokes and Rifat Atun and Justine Davies and Sebastian Vollmer and B{\"a}rnighausen, {Till W} and Jaacks, {Lindsay M} and Meigs, {James B.} and Wexler, {Deborah J.} and Jennifer Manne-Goehler",

year = "2020",

month = jan,

day = "14",

language = "English",

journal = "Diabetes Care",

issn = "0149-5992",

publisher = "American Diabetes Association",

}

Seiglie , JA, Marcus , M-E, Ebert, C, Prodromidis , N, Geldsetzer, P, Theilmann, M, Agoudavi, K, Andall-Brereton, G, Aryal, KK, Bicaba, BW, Bovet, P, Brian, G, Dorobantu, M, Gathecha, G, Singh Gurung, M, Guwatudde, D, Msaidie, M, Houehanou, C, Houinato, D, Jorgensen, JMA, Kagaruki, GB, Karki, KB, Labadarios, D, Martins, JS, Mayige, MT, McClure, RW, Mwangi, JK, Mwalim, O, Norov, B, Quesnel-Crooks, S, Silver, BK, Sturua, L, Tsabedze, L, Wesseh, CS, Stokes, A, Atun, R, Davies, J, Vollmer, S, Bärnighausen, TW, Jaacks, LM, Meigs , JB, Wexler , DJ & Manne-Goehler, J 2020, 'Diabetes prevalence and its relationship with education, wealth, and body mass index in twenty-nine low- and middle-income countries', Diabetes Care.

TY - JOUR

T1 - Diabetes prevalence and its relationship with education, wealth, and body mass index in twenty-nine low- and middle-income countries

AU - Seiglie , Jacqueline A.

AU - Marcus , Maja-Emilia

AU - Ebert, Cara

AU - Prodromidis , Nikolaos

AU - Geldsetzer, Pascal

AU - Theilmann, Michaela

AU - Agoudavi, Kokou

AU - Andall-Brereton, Glennis

AU - Aryal, Krishna K

AU - Bicaba, Brice Wilfried

AU - Bovet, Pascal

AU - Brian, Garry

AU - Dorobantu, Maria

AU - Gathecha, Gladwell

AU - Singh Gurung, Mongal

AU - Guwatudde, David

AU - Msaidie, Mohamed

AU - Houehanou, Corine

AU - Houinato, Dismand

AU - Jorgensen, Jutta Mari Adelin

AU - Kagaruki, Gibson B

AU - Karki, Khem B

AU - Labadarios, Demetre

AU - Martins, Joao S

AU - Mayige, Mary T

AU - McClure, Roy Wong

AU - Mwangi, Joseph Kibachio

AU - Mwalim, Omar

AU - Norov, Bolormaa

AU - Quesnel-Crooks, Sarah

AU - Silver, Bahendeka K

AU - Sturua, Lela

AU - Tsabedze, Lindiwe

AU - Wesseh, Chea Stanford

AU - Stokes, Andrew

AU - Atun, Rifat

AU - Davies, Justine

AU - Vollmer, Sebastian

AU - Bärnighausen, Till W

AU - Jaacks, Lindsay M

AU - Meigs , James B.

AU - Wexler , Deborah J.

AU - Manne-Goehler, Jennifer

PY - 2020/1/14

Y1 - 2020/1/14

N2 - OBJECTIVE Diabetes is a rapidly growing health problem in low- and middle-income countries (LMICs), but empirical data on its prevalence and relationship to socioeconomic status are scarce. We estimated diabetes prevalence and the subset with undiagnosed diabetes in 29 LMICs and evaluated the relationship between education, household wealth, body mass index (BMI), and diabetes risk.RESEARCH DESIGN AND METHODS We pooled individual-level data from 29 nationally representative surveys conducted between 2008 and 2016, totaling 588,574 participants aged ≥25 years. Diabetes prevalence and the subset with undiagnosed diabetes was calculated overall, by country, World Bank Income Group (WBIG), and geographic region. Multivariable Poisson regression models were used to estimate relative risk (RR). RESULTSOverall, prevalence of diabetes in 29 LMICs was 7.5% (95% CI: 7.1% – 8.0%) and of undiagnosed diabetes, 4.9% (4.6% – 5.3%). Diabetes prevalence increased with increasing WBIG: low-income (LICs) 6.7% (5.5% – 8.1%), lower-middle-income (LMIs) 7.1% (6.6% –7.6%), upper-middle-income countries (UMIs) 8.2% (7.5% – 9.0%). Compared with no formal education, greater educational attainment was associated with an increased risk of diabetes across WBIGs, independent of BMI (LICs RR 1.47 [95% CI:1.22–1.78]; LMIs 1.14 [1.06–1.23]; UMIs 1.28 [1.02–1.61]). CONCLUSIONSAmong 29 LMICs, diabetes prevalence was substantial and increased with increasing WBIG. In contrast to the association seen in high-income countries, diabetes risk was highest among those with greater educational attainment, independent of BMI. LMICs included in this analysis may be at an advanced stage in the nutrition transition but with no reversal in the socioeconomic gradient of diabetes risk.

AB - OBJECTIVE Diabetes is a rapidly growing health problem in low- and middle-income countries (LMICs), but empirical data on its prevalence and relationship to socioeconomic status are scarce. We estimated diabetes prevalence and the subset with undiagnosed diabetes in 29 LMICs and evaluated the relationship between education, household wealth, body mass index (BMI), and diabetes risk.RESEARCH DESIGN AND METHODS We pooled individual-level data from 29 nationally representative surveys conducted between 2008 and 2016, totaling 588,574 participants aged ≥25 years. Diabetes prevalence and the subset with undiagnosed diabetes was calculated overall, by country, World Bank Income Group (WBIG), and geographic region. Multivariable Poisson regression models were used to estimate relative risk (RR). RESULTSOverall, prevalence of diabetes in 29 LMICs was 7.5% (95% CI: 7.1% – 8.0%) and of undiagnosed diabetes, 4.9% (4.6% – 5.3%). Diabetes prevalence increased with increasing WBIG: low-income (LICs) 6.7% (5.5% – 8.1%), lower-middle-income (LMIs) 7.1% (6.6% –7.6%), upper-middle-income countries (UMIs) 8.2% (7.5% – 9.0%). Compared with no formal education, greater educational attainment was associated with an increased risk of diabetes across WBIGs, independent of BMI (LICs RR 1.47 [95% CI:1.22–1.78]; LMIs 1.14 [1.06–1.23]; UMIs 1.28 [1.02–1.61]). CONCLUSIONSAmong 29 LMICs, diabetes prevalence was substantial and increased with increasing WBIG. In contrast to the association seen in high-income countries, diabetes risk was highest among those with greater educational attainment, independent of BMI. LMICs included in this analysis may be at an advanced stage in the nutrition transition but with no reversal in the socioeconomic gradient of diabetes risk.

M3 - Article

SN - 0149-5992

JO - Diabetes Care

JF - Diabetes Care

ER -

Diabetes prevalence and its relationship with education, wealth, and body mass index in twenty-nine low- and middle-income countries

Abstract

UN SDGs

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