Yang Zhao 1,2 , Yu Liu 2 , Haohang Sun 3 , Xizhuo Sun 2 , Zhaoxia Yin 2 , Honghui Li 2 , Yongcheng Ren 1 , Bingyuan Wang 1 , Dongdong Zhang 1,2,3 , Xuejiao Liu 1,2,3 , Dechen Liu 1,2,3 , Ruiyuan Zhang 1 , Feiyan Liu 2 , Xu Chen 1,2 , Leilei Liu 1,2 , Cheng Cheng 1,2 , Qionggui Zhou 2 , Dongsheng Hu 1 , Ming Zhang 1 Show Affiliations »
Abstract
BACKGROUND: Previous evidence of an association between body mass index (BMI) and mortality in patients with diabetes was inconsistent. The BMI-mortality association with normal fasting glucose (NFG), impaired fasting glucose (IFG) and prevalent diabetes is still unclear in the Chinese population. METHODS: We analysed data for 17 252 adults from the Rural Chinese Cohort Study during 2007-2008 and followed for mortality during 2013-2014. Participants were classified with NFG, IFG and diabetes according to baseline measurement values of fasting glucose and self-reported diabetes. Multivariable Cox proportional hazard models were used to calculate HRs and 95% CIs across BMI categories by glycemic status. RESULTS: During the 6-year follow-up, 1109 participants died (563/10 181 with NFG, 349/5572 with IFG and 197/1499 with diabetes). The BMI-mortality association was curvilinear, with low BMI (even in normal range) associated with increased mortality regardless of glycemic status. In adjusted Cox models, risk of mortality showed a decreasing trend with BMI≤18 kg/m2, 18<BMI≤20 kg/m2 and 20<BMI≤22 kg/m2 vs 22<BMI≤24 kg/m2: HR 2.83 (95% CI 1.78 to 4.51), 2.05 (1.46 to 2.87) and 1.45 (1.10 to 1.90), respectively, for NFG; 2.53 (1.25 to 5.14), 1.36 (0.86 to 2.14) and 1.09 (0.76 to 1.57), respectively, for IFG; and 4.03 (1.42 to 11.50), 2.00 (1.05 to 3.80) and 1.52 (0.88 to 2.60), respectively, for diabetes. The risk of mortality was lower for patients with diabetes who were overweight or obese versus normal weight. CONCLUSIONS: Low BMI was associated with increased mortality regardless of glycemic status. Future studies are needed to explain the 'obesity paradox' in patients with diabetes. © Author(s) (or their employer(s)) 2018. No commercial re-use. See rights and permissions. Published by BMJ.
BACKGROUND: Previous evidence of an association between body mass index (BMI) and mortality in patients with diabetes was inconsistent. The BMI-mortality association with normal fasting glucose (NFG), impaired fasting glucose (IFG) and prevalent diabetes is still unclear in the Chinese population. METHODS: We analysed data for 17 252 adults from the Rural Chinese Cohort Study during 2007-2008 and followed for mortality during 2013-2014. Participants were classified with NFG, IFG and diabetes according to baseline measurement values of fasting glucose and self-reported diabetes . Multivariable Cox proportional hazard models were used to calculate HRs and 95% CIs across BMI categories by glycemic status. RESULTS: During the 6-year follow-up, 1109 participants died (563/10 181 with NFG, 349/5572 with IFG and 197/1499 with diabetes ). The BMI-mortality association was curvilinear, with low BMI (even in normal range) associated with increased mortality regardless of glycemic status. In adjusted Cox models, risk of mortality showed a decreasing trend with BMI≤18 kg/m2, 18<BMI≤20 kg/m2 and 20<BMI≤22 kg/m2 vs 22<BMI≤24 kg/m2: HR 2.83 (95% CI 1.78 to 4.51), 2.05 (1.46 to 2.87) and 1.45 (1.10 to 1.90), respectively, for NFG; 2.53 (1.25 to 5.14), 1.36 (0.86 to 2.14) and 1.09 (0.76 to 1.57), respectively, for IFG; and 4.03 (1.42 to 11.50), 2.00 (1.05 to 3.80) and 1.52 (0.88 to 2.60), respectively, for diabetes . The risk of mortality was lower for patients with diabetes who were overweight or obese versus normal weight. CONCLUSIONS: Low BMI was associated with increased mortality regardless of glycemic status. Future studies are needed to explain the 'obesity paradox' in patients with diabetes . © Author(s) (or their employer(s)) 2018. No commercial re-use. See rights and permissions. Published by BMJ.
Entities: Chemical
Disease
Species
Keywords:
body mass index; cohort study; diabetes; dose-response; mortality
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Year: 2018
PMID： 30042126 DOI： 10.1136/jech-2017-210277
Source DB: PubMed Journal: J Epidemiol Community Health ISSN： 0143-005X Impact factor: 3.710