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      Body Weight Variability and the Risk of Cardiovascular Outcomes and Mortality in Patients With Type 2 Diabetes: A Nationwide Cohort Study

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          Abstract

          OBJECTIVE

          Obesity and type 2 diabetes are risk factors for cardiovascular diseases and mortality, and they commonly result in weight variabilities. We aimed to investigate the association between body weight variability and risk of major cardiovascular outcomes and mortality in individuals with type 2 diabetes using large-scale, nationwide cohort data on the Korean population.

          RESEARCH DESIGN AND METHODS

          We enrolled 624,237 individuals with type 2 diabetes who underwent health examinations provided by the Korean National Health Insurance System between 2009 and 2010, with three or more body weight measurements within 5 years since enrollment and followed up until the end of 2017. We assessed body weight variability using four indices, including variability independent of the mean (VIM). A multivariate-adjusted Cox proportional hazards regression analysis was performed.

          RESULTS

          During the follow-up, 15,832, 25,038, and 44,716 cases of myocardial infarction (MI), stroke, and all-cause mortality, respectively, were recorded. Body weight variability was associated with increased risks of major cardiovascular outcomes after adjusting for confounding variables. Compared with the hazard ratios (HRs) of the lowest quartile group, the HRs (95% CIs) of the highest quartile group of VIM for body weight were 1.15 (1.10–1.20), 1.22 (1.18–1.26), and 1.58 (1.53–1.62) for MI, stroke, and all-cause mortality, respectively.

          CONCLUSIONS

          Body weight variability was associated with increased risks of MI, stroke, and all-cause mortality in patients with type 2 diabetes and may be a predictor of cardiovascular outcomes in such patients. Appropriate interventions to maintain stable weight could positively influence health outcomes in patients with type 2 diabetes.

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          Most cited references40

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          Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies.

          (2004)
          A WHO expert consultation addressed the debate about interpretation of recommended body-mass index (BMI) cut-off points for determining overweight and obesity in Asian populations, and considered whether population-specific cut-off points for BMI are necessary. They reviewed scientific evidence that suggests that Asian populations have different associations between BMI, percentage of body fat, and health risks than do European populations. The consultation concluded that the proportion of Asian people with a high risk of type 2 diabetes and cardiovascular disease is substantial at BMIs lower than the existing WHO cut-off point for overweight (> or =25 kg/m2). However, available data do not necessarily indicate a clear BMI cut-off point for all Asians for overweight or obesity. The cut-off point for observed risk varies from 22 kg/m2 to 25 kg/m2 in different Asian populations; for high risk it varies from 26 kg/m2 to 31 kg/m2. No attempt was made, therefore, to redefine cut-off points for each population separately. The consultation also agreed that the WHO BMI cut-off points should be retained as international classifications. The consultation identified further potential public health action points (23.0, 27.5, 32.5, and 37.5 kg/m2) along the continuum of BMI, and proposed methods by which countries could make decisions about the definitions of increased risk for their population.
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            Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015

            Background Non-fatal outcomes of disease and injury increasingly detract from the ability of the world's population to live in full health, a trend largely attributable to an epidemiological transition in many countries from causes affecting children, to non-communicable diseases (NCDs) more common in adults. For the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015), we estimated the incidence, prevalence, and years lived with disability for diseases and injuries at the global, regional, and national scale over the period of 1990 to 2015. Methods We estimated incidence and prevalence by age, sex, cause, year, and geography with a wide range of updated and standardised analytical procedures. Improvements from GBD 2013 included the addition of new data sources, updates to literature reviews for 85 causes, and the identification and inclusion of additional studies published up to November, 2015, to expand the database used for estimation of non-fatal outcomes to 60 900 unique data sources. Prevalence and incidence by cause and sequelae were determined with DisMod-MR 2.1, an improved version of the DisMod-MR Bayesian meta-regression tool first developed for GBD 2010 and GBD 2013. For some causes, we used alternative modelling strategies where the complexity of the disease was not suited to DisMod-MR 2.1 or where incidence and prevalence needed to be determined from other data. For GBD 2015 we created a summary indicator that combines measures of income per capita, educational attainment, and fertility (the Socio-demographic Index [SDI]) and used it to compare observed patterns of health loss to the expected pattern for countries or locations with similar SDI scores. Findings We generated 9·3 billion estimates from the various combinations of prevalence, incidence, and YLDs for causes, sequelae, and impairments by age, sex, geography, and year. In 2015, two causes had acute incidences in excess of 1 billion: upper respiratory infections (17·2 billion, 95% uncertainty interval [UI] 15·4–19·2 billion) and diarrhoeal diseases (2·39 billion, 2·30–2·50 billion). Eight causes of chronic disease and injury each affected more than 10% of the world's population in 2015: permanent caries, tension-type headache, iron-deficiency anaemia, age-related and other hearing loss, migraine, genital herpes, refraction and accommodation disorders, and ascariasis. The impairment that affected the greatest number of people in 2015 was anaemia, with 2·36 billion (2·35–2·37 billion) individuals affected. The second and third leading impairments by number of individuals affected were hearing loss and vision loss, respectively. Between 2005 and 2015, there was little change in the leading causes of years lived with disability (YLDs) on a global basis. NCDs accounted for 18 of the leading 20 causes of age-standardised YLDs on a global scale. Where rates were decreasing, the rate of decrease for YLDs was slower than that of years of life lost (YLLs) for nearly every cause included in our analysis. For low SDI geographies, Group 1 causes typically accounted for 20–30% of total disability, largely attributable to nutritional deficiencies, malaria, neglected tropical diseases, HIV/AIDS, and tuberculosis. Lower back and neck pain was the leading global cause of disability in 2015 in most countries. The leading cause was sense organ disorders in 22 countries in Asia and Africa and one in central Latin America; diabetes in four countries in Oceania; HIV/AIDS in three southern sub-Saharan African countries; collective violence and legal intervention in two north African and Middle Eastern countries; iron-deficiency anaemia in Somalia and Venezuela; depression in Uganda; onchoceriasis in Liberia; and other neglected tropical diseases in the Democratic Republic of the Congo. Interpretation Ageing of the world's population is increasing the number of people living with sequelae of diseases and injuries. Shifts in the epidemiological profile driven by socioeconomic change also contribute to the continued increase in years lived with disability (YLDs) as well as the rate of increase in YLDs. Despite limitations imposed by gaps in data availability and the variable quality of the data available, the standardised and comprehensive approach of the GBD study provides opportunities to examine broad trends, compare those trends between countries or subnational geographies, benchmark against locations at similar stages of development, and gauge the strength or weakness of the estimates available. Funding Bill & Melinda Gates Foundation.
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              Obesity: global epidemiology and pathogenesis

              The prevalence of obesity has increased worldwide in the past ~50 years, reaching pandemic levels. Obesity represents a major health challenge because it substantially increases the risk of diseases such as type 2 diabetes mellitus, fatty liver disease, hypertension, myocardial infarction, stroke, dementia, osteoarthritis, obstructive sleep apnoea and several cancers, thereby contributing to a decline in both quality of life and life expectancy. Obesity is also associated with unemployment, social disadvantages and reduced socio-economic productivity, thus increasingly creating an economic burden. Thus far, obesity prevention and treatment strategies - both at the individual and population level - have not been successful in the long term. Lifestyle and behavioural interventions aimed at reducing calorie intake and increasing energy expenditure have limited effectiveness because complex and persistent hormonal, metabolic and neurochemical adaptations defend against weight loss and promote weight regain. Reducing the obesity burden requires approaches that combine individual interventions with changes in the environment and society. Therefore, a better understanding of the remarkable regional differences in obesity prevalence and trends might help to identify societal causes of obesity and provide guidance on which are the most promising intervention strategies.
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                Author and article information

                Contributors
                Journal
                Diabetes Care
                American Diabetes Association
                0149-5992
                1935-5548
                September 01 2020
                July 08 2020
                September 01 2020
                July 08 2020
                : 43
                : 9
                : 2234-2241
                Affiliations
                [1 ]Department of Family Medicine, Korea University College of Medicine, Seoul, Republic of Korea
                [2 ]Department of Biostatistics, The Catholic University of Korea, Seoul, Republic of Korea
                [3 ]Department of Statistics and Actuarial Science, Soongsil University, Seoul, Republic of Korea
                Article
                10.2337/dc19-2552
                32641375
                b806c27b-0821-493e-b760-3a30116672df
                © 2020

                https://www.diabetesjournals.org/content/license

                Free to read

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