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. 2018 Mar;41(3):494-502.
doi: 10.2337/dc17-1852. Epub 2018 Jan 3.

Associations of General and Central Adiposity With Incident Diabetes in Chinese Men and Women

Affiliations

Associations of General and Central Adiposity With Incident Diabetes in Chinese Men and Women

Fiona Bragg et al. Diabetes Care. 2018 Mar.

Abstract

Objective: We assess associations of general and central adiposity in middle age and of young adulthood adiposity with incident diabetes in adult Chinese and estimate the associated population burden of diabetes.

Research design and methods: The prospective China Kadoorie Biobank enrolled 512,891 adults 30-79 years of age from 10 localities across China during 2004-2008. During 9.2 years of follow-up, 13,416 cases of diabetes were recorded among 482,589 participants without diabetes at baseline. Cox regression yielded adjusted hazard ratios (HRs) for incident diabetes associated with measures of general (e.g., BMI and BMI at 25 years) and central (e.g., waist circumference [WC]) adiposity.

Results: The mean (SD) BMI was 23.6 kg/m2 (3.4 kg/m2), and 3.8% had a BMI ≥30 kg/m2. Throughout the range examined (19-32 kg/m2), BMI showed a positive log-linear relationship with diabetes, with adjusted HRs per SD higher usual BMI greater in men (1.98; 95% CI 1.93-2.04) than in women (1.77; 1.73-1.81) (P for heterogeneity <0.001). For WC, HRs per SD were 2.13 (95% CI 2.07-2.19) in men and 1.91 (1.87-1.95) in women (P for heterogeneity <0.001). Mutual adjustment attenuated these associations, especially those of BMI. BMI at age 25 years was weakly positively associated with diabetes (men HR 1.09 [95% CI 1.05-1.12]; women 1.04 [1.02-1.07] per SD), which was reversed after adjustment for baseline BMI. In China, the increase in adiposity accounted for ∼50% of the increase in diabetes burden since 1980.

Conclusions: Among relatively lean Chinese adults, higher adiposity-general and central-was strongly positively associated with the risk of incident diabetes. The predicted continuing increase in adiposity in China foreshadows escalating rates of diabetes.

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Conflict of interest statement

Declaration of interests All authors declare no competing interests

Figures

Figure 1
Figure 1. Adjusted hazard ratios (95% CI) for diabetes by BMI and waist circumference
Basic adjustment results are stratified by age and study area and adjusted for education, household income, occupation, smoking, alcohol consumption, physical activity and family history of diabetes. Squares represent the HR with area inversely proportional to the variance of the log HR and error bars indicate the 95% CI. Adjusted HRs are plotted against mean BMI and waist circumference (WC) levels in each category. To avoid overlap of 95% CI lines, the boxes and their 95% CIs for the reference groups were moved apart slightly from the actual positions. Continuous associations reflect sex-specific BMI and waist circumference SDs.
Figure 2
Figure 2. Adjusted hazard ratios for diabetes and diabetes cases due to excess adiposity (BMI 25+ kg/m2)
(A) Adjusted HR for diabetes associated with excess adiposity (BMI ≥25 kg/m2) by age and sex. Hazard ratios (HRs) are calculated for overweight or obese (BMI ≥25 kg/m2) participants vs absence of overweight or obesity (BMI <25 kg/m2) participants. HRs are stratified by age and study area and adjusted for education, household income, occupation, smoking, alcohol consumption, physical activity and family history of diabetes. Squares represent the HR with area inversely proportional to the variance of the log HR and error bars indicate the 95%CI. (B) Diabetes cases attributable to excess adiposity (BMI ≥25 kg/m2) in 2010. Age- and sex-specific prevalence of overweight and obesity in the CKB are comparable with contemporaneous nationally representative surveys (32), and the population attributable fraction was calculated as P(HR-1) divided by HR, where P is the prevalence of excess adiposity among those who developed incident diabetes. By applying age- and sex-specific HRs to nationally representative, age- and sex-specific diabetes prevalence (4), we estimated the number of diabetes cases attributable to high adiposity.

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