Literature DB >> 20706202

The prevalence of metabolically healthy obese subjects defined by BMI and dual-energy X-ray absorptiometry.

Jennifer L Shea1, Edward W Randell, Guang Sun.   

Abstract

Nearly one-third of obese (OB) people are reported to be metabolically healthy based on BMI criteria. It is unknown whether this holds true when more accurate adiposity measurements are applied such as dual-energy X-ray absorptiometry (DXA). We compared differences in the prevalence of cardiometabolic abnormalities among adiposity groups classified using BMI vs. DXA criteria. A total of 1,907 adult volunteers from Newfoundland and Labrador participated. BMI and body fat percentage (%BF; measured using DXA) were measured following a 12-h fasting period. Subjects were categorized as normal weight (NW), overweight (OW), or OB based on BMI and %BF criteria. Cardiometabolic abnormalities considered included elevated triglyceride, glucose, and high-sensitivity C-reactive protein (hsCRP) levels, decreased high-density lipoprotein (HDL) cholesterol levels, insulin resistance, and hypertension. Subjects were classified as metabolically healthy (0 or 1 cardiometabolic abnormality) or abnormal (≥ 2 cardiometabolic abnormalities). We found low agreement in the prevalence of cardiometabolic abnormalities between BMI and %BF classifications (κ = 0.373, P < 0.001). Among NW and OW subjects, the prevalence of metabolically healthy individuals was similar between BMI and %BF (77.6 vs. 75.7% and 58.8 vs. 62.5%, respectively) however, there was a pronounced difference among OB subjects (34.0 vs. 47.7%, P < 0.05). Similar trends were evident using three additional definitions to characterize metabolically healthy individuals. Our findings indicate that approximately one-half of OB people are metabolically healthy when classified using %BF criteria which is significantly higher than previously reported using BMI. Caution should therefore be taken when making inferences about the metabolic health of an OB population depending on the method used to measure adiposity.

Entities:  

Mesh:

Year:  2010        PMID: 20706202     DOI: 10.1038/oby.2010.174

Source DB:  PubMed          Journal:  Obesity (Silver Spring)        ISSN: 1930-7381            Impact factor:   5.002


  38 in total

1.  A new predictive equation for evaluating women body fat percentage and obesity-related cardiovascular disease risk.

Authors:  A De Lorenzo; A Nardi; L Iacopino; E Domino; G Murdolo; C Gavrila; D Minella; G Scapagnini; L Di Renzo
Journal:  J Endocrinol Invest       Date:  2014-01-24       Impact factor: 4.256

Review 2.  Origins of metabolic complications in obesity: adipose tissue and free fatty acid trafficking.

Authors:  Bettina Mittendorfer
Journal:  Curr Opin Clin Nutr Metab Care       Date:  2011-11       Impact factor: 4.294

Review 3.  Molecular mechanisms of fatty liver in obesity.

Authors:  Lixia Gan; Wei Xiang; Bin Xie; Liqing Yu
Journal:  Front Med       Date:  2015-08-19       Impact factor: 4.592

4.  "Metabolically Healthy" Obesity and Hyperuricemia Increase Risk for Hypertension and Diabetes: 5-year Japanese Cohort Study.

Authors:  Masanari Kuwabara; Remi Kuwabara; Ichiro Hisatome; Koichiro Niwa; Carlos A Roncal-Jimenez; Petter Bjornstad; Ana Andres-Hernando; Yuka Sato; Thomas Jensen; Gabriela Garcia; Minoru Ohno; James O Hill; Miguel A Lanaspa; Richard J Johnson
Journal:  Obesity (Silver Spring)       Date:  2017-09-18       Impact factor: 5.002

5.  Metabolically normal obese people are protected from adverse effects following weight gain.

Authors:  Elisa Fabbrini; Jun Yoshino; Mihoko Yoshino; Faidon Magkos; Courtney Tiemann Luecking; Dmitri Samovski; Gemma Fraterrigo; Adewole L Okunade; Bruce W Patterson; Samuel Klein
Journal:  J Clin Invest       Date:  2015-01-02       Impact factor: 14.808

6.  Methylation of imprinted IGF2 regions is associated with total, visceral, and hepatic adiposity in postmenopausal women.

Authors:  Min-Ae Song; Thomas Ernst; Maarit Tiirikainen; Jörg Tost; Lynne R Wilkens; Linda Chang; Laurence N Kolonel; Loïc Le Marchand; Unhee Lim
Journal:  Epigenetics       Date:  2018-10-02       Impact factor: 4.528

7.  Invited commentary: limitations and usefulness of the metabolically healthy obesity phenotype.

Authors:  Patrick T Bradshaw; June Stevens
Journal:  Am J Epidemiol       Date:  2015-09-12       Impact factor: 4.897

8.  Metabolic health reduces risk of obesity-related cancer in framingham study adults.

Authors:  Lynn L Moore; Susan Chadid; Martha R Singer; Bernard E Kreger; Gerald V Denis
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2014-07-10       Impact factor: 4.254

Review 9.  Metabolically healthy obesity: definitions, determinants and clinical implications.

Authors:  Catherine M Phillips
Journal:  Rev Endocr Metab Disord       Date:  2013-09       Impact factor: 6.514

Review 10.  New obesity classification criteria as a tool for bariatric surgery indication.

Authors:  Antonino De Lorenzo; Laura Soldati; Francesca Sarlo; Menotti Calvani; Nicola Di Lorenzo; Laura Di Renzo
Journal:  World J Gastroenterol       Date:  2016-01-14       Impact factor: 5.742

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.