Literature DB >> 26965719

Variations in Diabetes Prevalence in Low-, Middle-, and High-Income Countries: Results From the Prospective Urban and Rural Epidemiological Study.

Gilles R Dagenais1, Hertzel C Gerstein2, Xiaohe Zhang2, Matthew McQueen2, Scott Lear3, Patricio Lopez-Jaramillo4, Viswanathan Mohan5, Prem Mony6, Rajeev Gupta7, V Raman Kutty8, Rajesh Kumar9, Omar Rahman10, Khalid Yusoff11, Katarzyna Zatonska12, Aytekin Oguz13, Annika Rosengren14, Roya Kelishadi15, Afzalhussein Yusufali16, Rafael Diaz17, Alvaro Avezum18, Fernando Lanas19, Annamarie Kruger20, Nasheeta Peer21, Jephat Chifamba22, Romaina Iqbal23, Noorhassim Ismail24, Bai Xiulin25, Liu Jiankang26, Deng Wenqing27, Yue Gejie28, Sumathy Rangarajan2, Koon Teo2, Salim Yusuf2.   

Abstract

OBJECTIVE: The goal of this study was to assess whether diabetes prevalence varies by countries at different economic levels and whether this can be explained by known risk factors. RESEARCH DESIGN AND METHODS: The prevalence of diabetes, defined as self-reported or fasting glycemia ≥7 mmol/L, was documented in 119,666 adults from three high-income (HIC), seven upper-middle-income (UMIC), four lower-middle-income (LMIC), and four low-income (LIC) countries. Relationships between diabetes and its risk factors within these country groupings were assessed using multivariable analyses.
RESULTS: Age- and sex-adjusted diabetes prevalences were highest in the poorer countries and lowest in the wealthiest countries (LIC 12.3%, UMIC 11.1%, LMIC 8.7%, and HIC 6.6%; P < 0.0001). In the overall population, diabetes risk was higher with a 5-year increase in age (odds ratio 1.29 [95% CI 1.28-1.31]), male sex (1.19 [1.13-1.25]), urban residency (1.24 [1.11-1.38]), low versus high education level (1.10 [1.02-1.19]), low versus high physical activity (1.28 [1.20-1.38]), family history of diabetes (3.15 [3.00-3.31]), higher waist-to-hip ratio (highest vs. lowest quartile; 3.63 [3.33-3.96]), and BMI (≥35 vs. <25 kg/m(2); 2.76 [2.52-3.03]). The relationship between diabetes prevalence and both BMI and family history of diabetes differed in higher- versus lower-income country groups (P for interaction < 0.0001). After adjustment for all risk factors and ethnicity, diabetes prevalences continued to show a gradient (LIC 14.0%, LMIC 10.1%, UMIC 10.9%, and HIC 5.6%).
CONCLUSIONS: Conventional risk factors do not fully account for the higher prevalence of diabetes in LIC countries. These findings suggest that other factors are responsible for the higher prevalence of diabetes in LIC countries.
© 2016 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.

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Year:  2016        PMID: 26965719     DOI: 10.2337/dc15-2338

Source DB:  PubMed          Journal:  Diabetes Care        ISSN: 0149-5992            Impact factor:   19.112


  54 in total

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Journal:  Endocrine       Date:  2020-01-11       Impact factor: 3.633

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3.  Diabetes Prevalence and Its Relationship With Education, Wealth, and BMI in 29 Low- and Middle-Income Countries.

Authors:  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 Msaidié; 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 I Davies; Sebastian Vollmer; Till W Bärnighausen; Lindsay M Jaacks; James B Meigs; Deborah J Wexler; Jennifer Manne-Goehler
Journal:  Diabetes Care       Date:  2020-02-12       Impact factor: 19.112

Review 4.  Gaps in Guidelines for the Management of Diabetes in Low- and Middle-Income Versus High-Income Countries-A Systematic Review.

Authors:  Mayowa O Owolabi; Joseph O Yaria; Meena Daivadanam; Akintomiwa I Makanjuola; Gary Parker; Brian Oldenburg; Rajesh Vedanthan; Shane Norris; Ayodele R Oguntoye; Morenike A Osundina; Omarys Herasme; Sulaiman Lakoh; Luqman O Ogunjimi; Sarah E Abraham; Paul Olowoyo; Carolyn Jenkins; Wuwei Feng; Hernán Bayona; Sailesh Mohan; Rohina Joshi; Ruth Webster; Andre P Kengne; Antigona Trofor; Lucia Maria Lotrean; Devarsetty Praveen; Jessica H Zafra-Tanaka; Maria Lazo-Porras; Kirsten Bobrow; Michaela A Riddell; Konstantinos Makrilakis; Yannis Manios; Bruce Ovbiagele
Journal:  Diabetes Care       Date:  2018-05       Impact factor: 19.112

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Authors:  Bernadette Thomas
Journal:  Curr Diab Rep       Date:  2019-03-02       Impact factor: 4.810

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7.  Improved Detection of Abnormal Glucose Tolerance in Africans: The Value of Combining Hemoglobin A1c With Glycated Albumin.

Authors:  Arsene F Hobabagabo; Nana H Osei-Tutu; Thomas Hormenu; Elyssa M Shoup; Christopher W DuBose; Lilian S Mabundo; Joon Ha; Arthur Sherman; Stephanie T Chung; David B Sacks; Anne E Sumner
Journal:  Diabetes Care       Date:  2020-08-14       Impact factor: 19.112

8.  Assessment of α-amylase and α-glucosidase inhibitory potential of Citrus reticulata peel extracts in hyperglycemic/hypoglycemic rats.

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Journal:  3 Biotech       Date:  2021-03-15       Impact factor: 2.406

9.  The Influence of Religious Participation and Use of Traditional Medicine on Type 2 Diabetes Control in Urban Ghana.

Authors:  Marian Botchway; Rachel E Davis; Lambert T Appiah; Spencer Moore; Anwar T Merchant
Journal:  J Relig Health       Date:  2021-01-30

10.  Implementation and Outcomes of a Comprehensive Type 2 Diabetes Program in Rural Guatemala.

Authors:  David Flood; Sandy Mux; Boris Martinez; Pablo García; Kate Douglas; Vera Goldberg; Waleska Lopez; Peter Rohloff
Journal:  PLoS One       Date:  2016-09-01       Impact factor: 3.240

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