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Effects of Body Mass Index, Waist Circumference, Waist-to-Height Ratio and Their Changes on Risks of Dyslipidemia among Chinese Adults: The Guizhou Population Health Cohort Study

Author

Listed:
  • Li Cao

    (Key Laboratory of Public Health Safety & NHC Key Laboratory of Health Technology Assessment, School of Public Health, Fudan University, Shanghai 200032, China
    These authors contributed equally to this work.)

  • Jie Zhou

    (Guizhou Center for Disease Control and Prevention, Guiyang 550004, China
    These authors contributed equally to this work.)

  • Yun Chen

    (Key Laboratory of Public Health Safety & NHC Key Laboratory of Health Technology Assessment, School of Public Health, Fudan University, Shanghai 200032, China)

  • Yanli Wu

    (Guizhou Center for Disease Control and Prevention, Guiyang 550004, China)

  • Yiying Wang

    (Guizhou Center for Disease Control and Prevention, Guiyang 550004, China)

  • Tao Liu

    (Guizhou Center for Disease Control and Prevention, Guiyang 550004, China)

  • Chaowei Fu

    (Key Laboratory of Public Health Safety & NHC Key Laboratory of Health Technology Assessment, School of Public Health, Fudan University, Shanghai 200032, China)

Abstract

This study aimed to assess the effects of different anthropometric indices and their changes on the risk of incident dyslipidemia among the Chinese population. From the Guizhou population health cohort study, 2989 Chinese adults without dyslipidemia at baseline were followed up. Anthropometric parameters including waist circumference (WC), body mass index (BMI), waist-to-height ratio (WHtR), and their changes in the latter two indices, and serum lipids were tested after at least 8 h fasting. Hazard ratio (HR), adjusted hazard ratio (aHR), and 95% confidential interval (CI) were calculated to estimate the association between anthropometric parameters and dyslipidemia risk using multivariate Cox regression. A total of 2089 (69.98%) new dyslipidemia cases were identified over an average follow-up of 7.0 years. Baseline BMI (aHR = 1.12, 95%CI 1.01, 1.23) and WHtR (aHR = 1.06, 95%CI 1.00, 1.13) were positively associated with higher risks of incident dyslipidemia but not WC. Each 5.0 kg/m 2 increment of BMI or 0.05-unit increment of WHtR was significantly associated with 43% or 25% increased risk of incident dyslipidemia, respectively. The aHRs (95%CI) of incident dyslipidemia for subjects maintaining or developing general obesity were 2.19 (1.53, 3.12) or 1.46 (1.22, 1.75), and 1.54 (1.23, 1.82) or 1.30 (1.06, 1.60) for subjects maintaining or developing abdominal obesity, respectively. Linear trends for aHRs of BMI, WHtR change, and BMI change were observed ( p for trend: 0.021, <0.001, <0.001, respectively). BMI, WHtR, and their changes were closely associated with the incidence of dyslipidemia for Chinese adults. Loss in BMI and WHtR had protective effects on incident dyslipidemia, whereas gain of BMI or WHtR increased the dyslipidemia risk. Interventions to control or reduce BMI and WHtR to the normal range are important for the early prevention of dyslipidemia, especially for participants aged 40 years or above, male participants, and urban residents with poor control of obesity.

Suggested Citation

  • Li Cao & Jie Zhou & Yun Chen & Yanli Wu & Yiying Wang & Tao Liu & Chaowei Fu, 2021. "Effects of Body Mass Index, Waist Circumference, Waist-to-Height Ratio and Their Changes on Risks of Dyslipidemia among Chinese Adults: The Guizhou Population Health Cohort Study," IJERPH, MDPI, vol. 19(1), pages 1-14, December.
    • Handle: RePEc:gam:jijerp:v:19:y:2021:i:1:p:341-:d:713765
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    References listed on IDEAS

    as
    1. Wenwang Rao & Yingying Su & Guang Yang & Yue Ma & Rui Liu & Shangchao Zhang & Shibin Wang & Yingli Fu & Changgui Kou & Yaqin Yu & Qiong Yu, 2016. "Cross-Sectional Associations between Body Mass Index and Hyperlipidemia among Adults in Northeastern China," IJERPH, MDPI, vol. 13(5), pages 1-10, May.
    2. Yangwen Yu & Yun Chen & Yiying Wang & Lisha Yu & Tao Liu & Chaowei Fu, 2021. "Is the Efficiency Score an Indicator for Incident Hypertension in the Community Population of Western China?," IJERPH, MDPI, vol. 18(19), pages 1-8, September.
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    Cited by:

    1. Kuen-Suan Chen & Tzung-Hua Hsieh, 2022. "Novel Physical Fitness Fuzzy Evaluation Model for Individual Health Promotion," IJERPH, MDPI, vol. 19(9), pages 1-12, April.

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