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Non-Obese Diabetes and Its Associated Factors in an Underdeveloped Area of South China, Guangxi

Author

Listed:
  • Zhenzhu Tang

    (Guangxi Center for Disease Prevention and Control, 18 Jinzhou Road, Nanning 530028, China
    These authors contributed equally to this work.)

  • Zhifeng Fang

    (Guangxi Center for Disease Prevention and Control, 18 Jinzhou Road, Nanning 530028, China
    These authors contributed equally to this work.)

  • Wei Huang

    (Guangxi Center for Disease Prevention and Control, 18 Jinzhou Road, Nanning 530028, China)

  • Zhanhua Liu

    (Guangxi Center for Disease Prevention and Control, 18 Jinzhou Road, Nanning 530028, China)

  • Yuzhu Chen

    (Guangxi Center for Disease Prevention and Control, 18 Jinzhou Road, Nanning 530028, China)

  • Zhongyou Li

    (Guangxi Center for Disease Prevention and Control, 18 Jinzhou Road, Nanning 530028, China)

  • Ting Zhu

    (Guangxi Center for Disease Prevention and Control, 18 Jinzhou Road, Nanning 530028, China)

  • Qichun Wang

    (Guangxi Center for Disease Prevention and Control, 18 Jinzhou Road, Nanning 530028, China)

  • Steve Simpson

    (Menzies Institute for Medical Research, University of Tasmania, Hobart 7001, Australia
    Turning Point, Monash University, Fitzroy 3065, Australia)

  • Bruce V. Taylor

    (Menzies Institute for Medical Research, University of Tasmania, Hobart 7001, Australia)

  • Rui Lin

    (Guangxi Center for Disease Prevention and Control, 18 Jinzhou Road, Nanning 530028, China)

Abstract

Background: Little research has been conducted on the prevalence of diabetes mellitus in underdeveloped areas in China, especially stratified into obesity and non-obese diabetes. The aim of the present study was to investigate the prevalence and associated factors of non-obese diabetes in an underdeveloped area in South China, Guangxi. Methods: Data derived from the Chinese Health and Nutrition Survey 2010–2012 involved a sample of 3874 adults from Guangxi. Questionnaires and oral glucose-tolerance tests were conducted, and fasting and 2-h glucose levels and serum lipids were measured. Logistic regression analysis was performed to assess associated factors for non-obese diabetes. Results: 68.2% and 62.2% of instances of newly detected diabetes were those of non-obese diabetes based on BMI (NODB) and based on WC (NODW), respectively. The male sex, an age older than 50 years, lower education, hypertension, and hypertriglyceridemia were significantly associated with a higher risk of both NODB and NODW, while some associated factors for NODB were found different from those associated with NODW, and an interaction effect was found to increase the risk of NODW. Conclusions: Our study indicated that non-obese diabetes was highly prevalent in an underdeveloped area of South China. Non-obese diabetes should be considered for increased public attention in these areas.

Suggested Citation

  • Zhenzhu Tang & Zhifeng Fang & Wei Huang & Zhanhua Liu & Yuzhu Chen & Zhongyou Li & Ting Zhu & Qichun Wang & Steve Simpson & Bruce V. Taylor & Rui Lin, 2016. "Non-Obese Diabetes and Its Associated Factors in an Underdeveloped Area of South China, Guangxi," IJERPH, MDPI, vol. 13(10), pages 1-12, September.
    • Handle: RePEc:gam:jijerp:v:13:y:2016:i:10:p:976-:d:79689
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    References listed on IDEAS

    as
    1. John R B Perry & Benjamin F Voight & Loïc Yengo & Najaf Amin & Josée Dupuis & Martha Ganser & Harald Grallert & Pau Navarro & Man Li & Lu Qi & Valgerdur Steinthorsdottir & Robert A Scott & Peter Almgr, 2012. "Stratifying Type 2 Diabetes Cases by BMI Identifies Genetic Risk Variants in LAMA1 and Enrichment for Risk Variants in Lean Compared to Obese Cases," PLOS Genetics, Public Library of Science, vol. 8(5), pages 1-14, May.
    2. Tony Scully, 2012. "Diabetes in numbers," Nature, Nature, vol. 485(7398), pages 2-3, May.
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