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Anthony Chen 1 Article
Metabolic Risk/Epidemiology
Impact of Older Age Adiposity on Incident Diabetes: A Community-Based Cohort Study in China
Anthony Chen, Weiju Zhou, Jian Hou, Alan Nevill, Yuanlin Ding, Yuhui Wan, Rebecca Jester, Xia Qin, Zhi Hu, Ruoling Chen
Diabetes Metab J. 2022;46(5):733-746.   Published online April 29, 2022
DOI: https://doi.org/10.4093/dmj.2021.0215
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AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Background
Obesity classifications vary globally and the impact of older age adiposity on incident diabetes has not been well-studied.
Methods
We examined a random sample of 2,809 participants aged ≥60 years in China, who were free of diabetes at baseline and were followed up for up to 10 years to document diabetes (n=178). The incidence of diabetes was assessed in relation to different cut-off points of body mass index (BMI) and waist circumference (WC) in multiple adjusted Cox regression models.
Results
The diabetic risk in the cohort increased linearly with the continuous and quartile variables of BMI and WC. The BMI-World Health Organization (WHO) and BMI-China criteria analysis did not show such a linear relationship, however, the BMI-Asian/Hong Kong criteria did; adjusted hazards ratio (HR) was 0.42 (95% confidence interval [CI], 0.20 to 0.90) in BMI <20 kg/m2, 1.46 (95% CI, 0.99 to 2.14) in 23–≤26 kg/m2, and 1.63 (95% CI, 1.09 to 2.45) in ≥26 kg/m2. The WC-China criteria revealed a slightly better prediction of diabetes (adjusted HRs were 1.79 [95% CI, 1.21 to 2.66] and 1.87 [95% CI, 1.22 to 2.88] in central obese action levels 1 and 2) than the WC-WHO. The combination of the BMI-Asian/Hong Kong with WC-China demonstrated the strongest prediction. There were no gender differences in the impact of adiposity on diabetes.
Conclusion
In older Chinese, BMI-Asian/Hong Kong criteria is a better predictor of diabetes than other BMI criterion. Its combination with WC-China improved the prediction of adiposity to diabetes, which would help manage bodyweight in older age to reduce the risk of diabetes.

Citations

Citations to this article as recorded by  
  • Investigating Gender and Age Variability in Diabetes Prediction: A Multi-Model Ensemble Learning Approach
    Rishi Jain, Nitin Kumar Tripathi, Millie Pant, Chutiporn Anutariya, Chaklam Silpasuwanchai
    IEEE Access.2024; 12: 71535.     CrossRef
  • Sex-based differences in the associations between abdominal obesity and diabetic retinopathy in diabetic patients with normal weight
    Yuan Liu, Kaiqun Liu, Liqiong Xie, Chengguo Zuo, Lanhua Wang, Wenyong Huang
    Heliyon.2024; 10(17): e36683.     CrossRef
  • Impact of PM2.5 exposure in old age and its interactive effect with smoking on incidence of diabetes
    Anthony Chen, Jiaqian Yin, Ying Ma, Jian Hou, Weiju Zhou, Zhongliang Bai, Xia Qin, Zhi Hu, Yuntao Chen, Eric J. Brunner, Haidong Kan, Ruoling Chen
    Science of The Total Environment.2024; 954: 175219.     CrossRef
  • Association of air pollution with dementia: a systematic review with meta-analysis including new cohort data from China
    Jie Tang, Anthony Chen, Fan He, Martin Shipley, Alan Nevill, Hugh Coe, Zhi Hu, Tao Zhang, Haidong Kan, Eric Brunner, Xuguang Tao, Ruoling Chen
    Environmental Research.2023; 223: 115048.     CrossRef
  • Impact of fish consumption on all-cause mortality in older people with and without dementia: a community-based cohort study
    Aishat T. Bakre, Anthony Chen, Xuguang Tao, Jian Hou, Yuyou Yao, Alain Nevill, James J. Tang, Sabine Rohrmann, Jindong Ni, Zhi Hu, John Copeland, Ruoling Chen
    European Journal of Nutrition.2022; 61(7): 3785.     CrossRef

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