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      Associations of BMI with all-cause mortality in normoglycemia, impaired fasting glucose and type 2 diabetes mellitus among an elderly Chinese population: a cohort study

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          Abstract

          Aim

          To explore the associations of body mass index (BMI) and mortality among people with normal fasting glucose (NFG), impaired fasting glucose (IFG), and type 2 diabetes mellitus (T2DM) in an elderly Chinese population. 

          Methods

          A retrospective cohort study was conducted that included 59,874 elderly people who were aged 60 and older at baseline. Data for the study came from a health check-up program in China between 2011 and 2019. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using multivariable Cox proportional hazard models of BMI categories by glycemic status.

          Results

          During the median of 5.96 years of follow-up, 7928 participants died (6457/49057 with NFG, 712/5898 with IFG and 759/4919 with T2DM). In adjusted Cox models, risk of mortality showed a decreasing trend with BMI < 18.5 kg/m 2, 24 ≤ BMI < 28 kg/m 2, and BMI ≥ 28 kg/m 2 compared to 18.5 ≤ BMI < 24 kg/m 2: HR (95% CI): 1.33 (1.18 to 1.49), 0.88 (0.83 to 0.93), and 0.90 (0.82 to 0.98), respectively, for NFG; 0.89 (0.55 to 1.46), 0.84 (0.71 to 0.99), and 0.88 (0.70 to 1.11), respectively, for IFG; and 1.42 (0.88 to 2.29), 0.75 (0.64 to 0.89), and 0.76 (0.62 to 0.93), respectively, for T2DM. There were curvilinear-shaped associations between BMI and mortality in the NFG and T2DM groups ( P overall < 0.001 and P overall < 0.001, respectively; P nonlinearity < 0.001 and P nonlinearity = 0.027, respectively) and no significantly association between BMI and all-cause mortality was observed in the IFG group ( P overall = 0.170).

          Conclusion

          High BMI compared to normal BMI was associated with decreased mortality, especially in the old populations with NFG and T2DM. Future studies are needed to explain the obesity paradox in elderly patients with T2DM.

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          Most cited references34

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          Overweight, obesity, and mortality in a large prospective cohort of persons 50 to 71 years old.

          Obesity, defined by a body-mass index (BMI) (the weight in kilograms divided by the square of the height in meters) of 30.0 or more, is associated with an increased risk of death, but the relation between overweight (a BMI of 25.0 to 29.9) and the risk of death has been questioned. We prospectively examined BMI in relation to the risk of death from any cause in 527,265 U.S. men and women in the National Institutes of Health-AARP cohort who were 50 to 71 years old at enrollment in 1995-1996. BMI was calculated from self-reported weight and height. Relative risks and 95 percent confidence intervals were adjusted for age, race or ethnic group, level of education, smoking status, physical activity, and alcohol intake. We also conducted alternative analyses to address potential biases related to preexisting chronic disease and smoking status. During a maximum follow-up of 10 years through 2005, 61,317 participants (42,173 men and 19,144 women) died. Initial analyses showed an increased risk of death for the highest and lowest categories of BMI among both men and women, in all racial or ethnic groups, and at all ages. When the analysis was restricted to healthy people who had never smoked, the risk of death was associated with both overweight and obesity among men and women. In analyses of BMI during midlife (age of 50 years) among those who had never smoked, the associations became stronger, with the risk of death increasing by 20 to 40 percent among overweight persons and by two to at least three times among obese persons; the risk of death among underweight persons was attenuated. Excess body weight during midlife, including overweight, is associated with an increased risk of death. Copyright 2006 Massachusetts Medical Society.
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            Body-mass index and risk of 22 specific cancers: a population-based cohort study of 5·24 million UK adults

            Summary Background High body-mass index (BMI) predisposes to several site-specific cancers, but a large-scale systematic and detailed characterisation of patterns of risk across all common cancers adjusted for potential confounders has not previously been undertaken. We aimed to investigate the links between BMI and the most common site-specific cancers. Methods With primary care data from individuals in the Clinical Practice Research Datalink with BMI data, we fitted Cox models to investigate associations between BMI and 22 of the most common cancers, adjusting for potential confounders. We fitted linear then non-linear (spline) models; investigated effect modification by sex, menopausal status, smoking, and age; and calculated population effects. Findings 5·24 million individuals were included; 166 955 developed cancers of interest. BMI was associated with 17 of 22 cancers, but effects varied substantially by site. Each 5 kg/m2 increase in BMI was roughly linearly associated with cancers of the uterus (hazard ratio [HR] 1·62, 99% CI 1·56–1·69; p<0·0001), gallbladder (1·31, 1·12–1·52; p<0·0001), kidney (1·25, 1·17–1·33; p<0·0001), cervix (1·10, 1·03–1·17; p=0·00035), thyroid (1·09, 1·00–1·19; p=0·0088), and leukaemia (1·09, 1·05–1·13; p≤0·0001). BMI was positively associated with liver (1·19, 1·12–1·27), colon (1·10, 1·07–1·13), ovarian (1·09, 1.04–1.14), and postmenopausal breast cancers (1·05, 1·03–1·07) overall (all p<0·0001), but these effects varied by underlying BMI or individual-level characteristics. We estimated inverse associations with prostate and premenopausal breast cancer risk, both overall (prostate 0·98, 0·95–1·00; premenopausal breast cancer 0·89, 0·86–0·92) and in never-smokers (prostate 0·96, 0·93–0·99; premenopausal breast cancer 0·89, 0·85–0·94). By contrast, for lung and oral cavity cancer, we observed no association in never smokers (lung 0·99, 0·93–1·05; oral cavity 1·07, 0·91–1·26): inverse associations overall were driven by current smokers and ex-smokers, probably because of residual confounding by smoking amount. Assuming causality, 41% of uterine and 10% or more of gallbladder, kidney, liver, and colon cancers could be attributable to excess weight. We estimated that a 1 kg/m2 population-wide increase in BMI would result in 3790 additional annual UK patients developing one of the ten cancers positively associated with BMI. Interpretation BMI is associated with cancer risk, with substantial population-level effects. The heterogeneity in the effects suggests that different mechanisms are associated with different cancer sites and different patient subgroups. Funding National Institute for Health Research, Wellcome Trust, and Medical Research Council.
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              The global burden of disease attributable to high body mass index in 195 countries and territories, 1990–2017: An analysis of the Global Burden of Disease Study

              Background Obesity represents an urgent problem that needs to be properly addressed, especially among children. Public and global health policy- and decision-makers need timely, reliable quantitative information to develop effective interventions aimed at counteracting the burden generated by high body mass index (BMI). Few studies have assessed the high-BMI-related burden on a global scale. Methods and findings Following the methodology framework and analytical strategies used in the Global Burden of Disease Study (GBD) 2017, the global deaths and disability-adjusted life years (DALYs) attributable to high BMI were analyzed by age, sex, year, and geographical location and by Socio-demographic Index (SDI). All causes of death and DALYs estimated in GBD 2017 were organized into 4 hierarchical levels: level 1 contained 3 broad cause groupings, level 2 included more specific categories within the level 1 groupings, level 3 comprised more detailed causes within the level 2 categories, and level 4 included sub-causes of some level 3 causes. From 1990 to 2017, the global deaths and DALYs attributable to high BMI have more than doubled for both females and males. However, during the study period, the age-standardized rate of high-BMI-related deaths remained stable for females and only increased by 14.5% for males, and the age-standardized rate of high-BMI-related DALYs only increased by 12.7% for females and 26.8% for males. In 2017, the 6 leading GBD level 3 causes of high-BMI-related DALYs were ischemic heart disease, stroke, diabetes mellitus, chronic kidney disease, hypertensive heart disease, and low back pain. For most GBD level 3 causes of high-BMI-related DALYs, high-income North America had the highest attributable proportions of age-standardized DALYs due to high BMI among the 21 GBD regions in both sexes, whereas the lowest attributable proportions were observed in high-income Asia Pacific for females and in eastern sub-Saharan Africa for males. The association between SDI and high-BMI-related DALYs suggested that the lowest age-standardized DALY rates were found in countries in the low-SDI quintile and high-SDI quintile in 2017, and from 1990 to 2017, the age-standardized DALY rates tended to increase in regions with the lowest SDI, but declined in regions with the highest SDI, with the exception of high-income North America. The study’s main limitations included the use of information collected from some self-reported data, the employment of cutoff values that may not be adequate for all populations and groups at risk, and the use of a metric that cannot distinguish between lean and fat mass. Conclusions In this study, we observed that the number of global deaths and DALYs attributable to high BMI has substantially increased between 1990 and 2017. Successful population-wide initiatives targeting high BMI may mitigate the burden of a wide range of diseases. Given the large variations in high-BMI-related burden of disease by SDI, future strategies to prevent and reduce the burden should be developed and implemented based on country-specific development status.
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                Author and article information

                Contributors
                zzussh@126.com
                Journal
                BMC Geriatr
                BMC Geriatr
                BMC Geriatrics
                BioMed Central (London )
                1471-2318
                21 August 2022
                21 August 2022
                2022
                : 22
                : 690
                Affiliations
                GRID grid.207374.5, ISNI 0000 0001 2189 3846, Department of Epidemiology and Health Statistics, College of Public Health, , Zhengzhou University, ; 100 Kexue Avenue, Zhengzhou, Henan 450001 People’s Republic of China
                Article
                3382
                10.1186/s12877-022-03382-z
                9392914
                35987565
                e6fdc627-3f22-46ad-bcae-52a33293ddf1
                © The Author(s) 2022

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 24 February 2022
                : 10 August 2022
                Funding
                Funded by: National Key Research and Development Program “Research on prevention and control of major chronic noncommunicable diseases” of China
                Award ID: 2017YFC1307705
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2022

                Geriatric medicine
                body mass index,fasting plasma glucose,type 2 diabetes mellitus,mortality,elderly population

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