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Fat distribution and risk factors

Fat distribution and risk factors

CAS PubMed PubMed Central Google Scholar. Morrell DS, Pearson Facgors, Sauser DD. Copyright Metabolic health goals by the American Diabetes Fat distribution and risk factors. Furthermore, more aggressive screening idstribution Fat distribution and risk factors factosr likely did not bias our results as the prevalence of reported symptoms at diagnosis and the frequency of visits did not vary by body mass index 9. Rothman KJ, Greenland S. Mandavilli ACyranoski D Asia's big problem. We also examined in multiple logistic regression whether physical activity and diet modified the associations between regional fat distribution and metabolic syndrome. Fat distribution and risk factors

Fat distribution and risk factors -

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The Asia-Pacific perspective: redefining obesity and its treatment Download references. This work was supported by a grant from the SNUH Research Fund Number The funding organizations had no role in the design or conduct of the study; in the collection, management, analysis, or interpretation of the data; or in the preparation, review, or approval of the manuscript.

Department of Family Medicine, Healthcare Research Institute, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, Korea. Department of Internal Medicine, Healthcare Research Institute, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, Korea.

Division of Gastroenterology and Hepatology, Stanford University School of Medicine, Stanford, California, United States. You can also search for this author in PubMed Google Scholar. Study concept and design: D. and H. Acquisition of data: H. and D. Analysis and interpretation of data: D.

and J. K Drafting of the manuscript: H. Critical revision of the manuscript for important intellectual content: D. Statistical analysis: D. Obtaining funding: H. Study supervision: D. Correspondence to Donghee Kim. Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Open Access This article is licensed under a Creative Commons Attribution 4. Reprints and permissions. Kwon, H. Body Fat Distribution and the Risk of Incident Metabolic Syndrome: A Longitudinal Cohort Study. Sci Rep 7 , Download citation. Received : 20 February Accepted : 18 July Published : 08 September Anyone you share the following link with will be able to read this content:.

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Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily. Skip to main content Thank you for visiting nature. nature scientific reports articles article. Download PDF. Subjects Metabolic syndrome Obesity. Abstract The effect of visceral adipose tissue VAT and subcutaneous adipose tissue SAT area on metabolic syndrome MS has been debated.

Results General characteristics of the study population As outlined in the Methods section, of the 5, subjects in the baseline cohort, 2, Full size table.

Table 4 Incidence of each component of MS by the VAT and SAT areas at baseline. Discussion In this large prospective study, the VAT area was longitudinally associated with incident MS and its components during a 5-year follow-up period.

Methods Study subjects and design This longitudinal study was performed using a previously described cohort 8. Anthropometric and laboratory measurements The methods applied in this cohort have been described in detail elsewhere 8 , 35 , Measurement of abdominal adipose tissue Detailed descriptions of the methods used to measure the abdominal adipose tissue area have been published previously Statistical analysis The outcome of this study was the development of MS.

References World Health Organization. Article CAS PubMed PubMed Central Google Scholar Lakka, H. Article PubMed Google Scholar Wang, J. Article PubMed Google Scholar Oh, S. Article PubMed PubMed Central Google Scholar Mozumdar, A.

Article PubMed Google Scholar Alberti, K. CAS Google Scholar Yim, J. Article PubMed PubMed Central Google Scholar Neeland, I. CAS PubMed PubMed Central Google Scholar Oka, R. Article CAS PubMed Google Scholar McLaughlin, T. Article CAS PubMed PubMed Central Google Scholar Fox, C.

Article PubMed Google Scholar Porter, S. Article PubMed PubMed Central Google Scholar Liu, J. Article CAS PubMed PubMed Central Google Scholar Wildman, R. Article CAS PubMed PubMed Central Google Scholar Nakao, Y.

Article ADS Google Scholar Despres, J. Article ADS CAS PubMed Google Scholar Ibrahim, M. Article PubMed Google Scholar Kim, S. Obesity, fat distribution, and weight gain as risk factors for clinical diabetes in men.

pdf 1. Access Status Full text of the requested work is not available in DASH at this time "restricted access". For more information on restricted deposits, see our FAQ. Metadata Show full item record. Citation Chan, J. Rimm, G. Colditz, M. Stampfer, and W.

Abstract OBJECTIVE- To investigate the relation between obesity, fat distribution, and weight gain through adulthood and the risk of non-insulin-dependent diabetes mellitus NIDDM.

RESEARCH DESIGN AND METHODS- We analyzed data from a cohort of 51, U. male health professionals, years of age in , who completed biennial questionnaires sent out in , , , and During 5 years of follow-up , cases of NIDDM were diagnosed among men without a history of diabetes, heart disease, and cancer in and who provided complete health information.

Relative risks RRs associated with different anthropometric measures were calculated controlling for age, and multivariate RRs were calculated controlling for smoking, family history of diabetes, and age.

RESULTS- We found a strong positive association between overall obesity as measured by body mass index BMI and risk of diabetes.

Risj M ChanFactrs Fat distribution and risk factors RimmDisgribution A RisoMeir J Balancing dietary needsWalter C Willett; Obesity, Fat distribution and risk factors Distribution, and Weight Gain as Risk Factors for Clinical Diabetes in Men. Diabetes Care 1 September ; 17 9 : — To investigate the relation between obesity, fat distribution, and weight gain through adulthood and the risk of non-insulin-dependent diabetes melli-tus NIDDM. We analyzed data from a cohort of 51, U. male health professionals, years of age inwho completed biennial questionnaires sent out in,and Collections SPH Distributionn Articles []. Contact administrator regarding this item to report mistakes or request changes. Toggle navigation. Login Toggle navigation. View Item DASH Home Harvard T.

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