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Situation of Diabetes and Related Disease Surveillance in Rural Areas of Jilin Province, Northeast China

Author

Listed:
  • Rui Wang

    (Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun 130021, Jilin, China)

  • Peng Zhang

    (Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun 130021, Jilin, China)

  • Xin Lv

    (Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun 130021, Jilin, China)

  • Lingling Jiang

    (Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun 130021, Jilin, China)

  • Chunshi Gao

    (Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun 130021, Jilin, China)

  • Yuanyuan Song

    (Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun 130021, Jilin, China)

  • Yaqin Yu

    (Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun 130021, Jilin, China)

  • Bo Li

    (Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun 130021, Jilin, China)

Abstract

Background: Several studies have investigated the prevalence and awareness of diabetes mellitus (DM) in China, but little is known about the situation of DM in the northeastern rural areas. Our present study investigated the prevalence, awareness and associated characteristics of DM in rural areas of Jilin Province, aiming to suggest more efforts for the prevention and control of DM. Methods: A multistage stratified random cluster sampling design was used in this cross-sectional study which took place in 2012. Data were collected by face-to-face interviews and physical examinations. Rao-Scott Chi-square test, t test and multivariate logistic regression analysis were used. Results: The estimated prevalence of DM in rural areas of Jilin province was 7.2%. DM was positively associated with age, Body mass index (BMI), hypotension, dyslipidemia and was high in participants with a family history of diabetes and those who exercise frequently, but low for high education level and married participants. 69.0% participants with DM were aware of their diabetes status, 88.2% of whom received treatment and 34.4% of whom had received treatment controlled their DM status. Conclusions: We observed a high prevalence and low awareness status of DM among the rural residents in Jilin Province, but the rate of effective control in those who have received treatment was considerable. The low rate of disease surveillance should draw health authority’s attention.

Suggested Citation

  • Rui Wang & Peng Zhang & Xin Lv & Lingling Jiang & Chunshi Gao & Yuanyuan Song & Yaqin Yu & Bo Li, 2016. "Situation of Diabetes and Related Disease Surveillance in Rural Areas of Jilin Province, Northeast China," IJERPH, MDPI, vol. 13(6), pages 1-10, May.
    • Handle: RePEc:gam:jijerp:v:13:y:2016:i:6:p:538-:d:70994
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    References listed on IDEAS

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    1. Anjali G. Hinch & Arti Tandon & Nick Patterson & Yunli Song & Nadin Rohland & Cameron D. Palmer & Gary K. Chen & Kai Wang & Sarah G. Buxbaum & Ermeg L. Akylbekova & Melinda C. Aldrich & Christine B. A, 2011. "The landscape of recombination in African Americans," Nature, Nature, vol. 476(7359), pages 170-175, August.
    2. Jiqiang Yue & Xuhua Mao & Kun Xu & Lingshuang Lü & Sijun Liu & Feng Chen & Jianming Wang, 2016. "Prevalence, Awareness, Treatment and Control of Diabetes Mellitus in a Chinese Population," PLOS ONE, Public Library of Science, vol. 11(4), pages 1-15, April.
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    Cited by:

    1. Xin Guo & Li Shen & Jing Dou & Yaogai Lv & Anning Zhang & Fanchao Shi & Zhiqiang Xue & Yaqin Yu & Lina Jin & Yan Yao, 2017. "Associations of Fasting Blood Glucose with Influencing Factors in Northeast China: A Quantile Regression Analysis," IJERPH, MDPI, vol. 14(11), pages 1-11, November.

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