- Metabolic Risk/Epidemiology
- Impact of Older Age Adiposity on Incident Diabetes: A Community-Based Cohort Study in China
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Anthony Chen, Weiju Zhou, Jian Hou, Alan Nevill, Yuanlin Ding, Yuhui Wan, Rebecca Jester, Xia Qin, Zhi Hu, Ruoling Chen
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Diabetes Metab J. 2022;46(5):733-746. Published online April 29, 2022
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DOI: https://doi.org/10.4093/dmj.2021.0215
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 Abstract
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- 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.
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Citations
Citations to this article as recorded by  - Investigating Gender and Age Variability in Diabetes Prediction: A Multi-Model Ensemble Learning Approach
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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
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