Literature DB >> 33765000

The association between body composition and metabolically unhealthy profile of adults with normal weight in Northwest China.

Ling Fan1,2, Jiangwei Qiu1,2, Yu Zhao1,2, Ting Yin1,2, Xiaoxia Li1,2, Qingan Wang1,2, Jinyun Jing1,2, Jiaxing Zhang1,2, Faxuan Wang1,2, Xiuying Liu1,2, Lan Liu1,2, Yi Zhao1,2, Yuhong Zhang1,2.   

Abstract

OBJECTIVE: Related evidences of metabolically unhealthy profile of adults with normal weight are not well characterized in the Chinese population. This is because they cannot be effectively identified by regular measurements (such as body mass index [BMI]). To overcome this gap in literature, this study aimed at investigating the association between body composition and metabolically unhealthy profile in Chinese adults with normal weight.
METHODS: A total of 5427 individuals with normal-weight were recruited from 15820 people living in Ningxia Hui Autonomous Region in Northwest China. Normal-weight was defined as a BMI of 18.5-23.9 kg/m2. Metabolically unhealthy profile was assessed by the National Cholesterol Education Program Adult Treatment Panel III (ATP III). Metabolically unhealthy normal-weight (MUHNW) profile was defined in individuals who had normal weight and at least two cardiometabolic risk factors. Generalized linear model was used to investigate the association between body composition measured by bioelectrical impedance and metabolically unhealthy profile in adults with normal-weight.
RESULTS: The percentage of metabolically unhealthy profile was 35.86% in adults with normal weight. Different MUHNW distributions were found between males and females depending on age. The percentage of the MUHNW profile significantly increased in women after the age of 55, contrary to men. The association between body composition and MUHNW was affected by age and sex. The increased adiposity indices (fat mass index [FMI], visceral fat level [VFL], waist circumference [WCF]), and reduced skeletal muscle mass ratio [SMR] showed significant differences between MUHNW and metabolically healthy with normal weight (MHNW) (p < 0.05).
CONCLUSION: The distribution of MUHNW differed between ages and sexes. FMI, VFL, WCF and SMR could be responsible for the MUHNW adults, providing a new insight into the potential metabolic risks for the adults with normal weight in China. This directs us in the management of the MUHNW for their early prevention.

Entities:  

Year:  2021        PMID: 33765000      PMCID: PMC7993598          DOI: 10.1371/journal.pone.0248782

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


  35 in total

1.  Obesity and diabetes in the developing world--a growing challenge.

Authors:  Parvez Hossain; Bisher Kawar; Meguid El Nahas
Journal:  N Engl J Med       Date:  2007-01-18       Impact factor: 91.245

2.  Transition from metabolic healthy to unhealthy phenotypes and association with cardiovascular disease risk across BMI categories in 90 257 women (the Nurses' Health Study): 30 year follow-up from a prospective cohort study.

Authors:  Nathalie Eckel; Yanping Li; Olga Kuxhaus; Norbert Stefan; Frank B Hu; Matthias B Schulze
Journal:  Lancet Diabetes Endocrinol       Date:  2018-05-31       Impact factor: 32.069

3.  Comparisons of body-composition prediction accuracy: a study of 2 bioelectric impedance consumer devices in healthy Chinese persons using DXA and MRI as criteria methods.

Authors:  Li Xu; Xiaoguang Cheng; Jiguang Wang; Qiyun Cao; Tetsuya Sato; Maoying Wang; Xingshan Zhao; Wei Liang
Journal:  J Clin Densitom       Date:  2011-08-10       Impact factor: 2.617

4.  Metabolic health and weight: Understanding metabolically unhealthy normal weight or metabolically healthy obese patients.

Authors:  Hannah Mathew; Olivia M Farr; Christos S Mantzoros
Journal:  Metabolism       Date:  2015-10-23       Impact factor: 8.694

5.  Prevalence of metabolically obese but normal weight (MONW) and metabolically healthy but obese (MHO) in Chinese Beijing urban subjects.

Authors:  Yan Zhang; Jing Fu; Shuwen Yang; Ming Yang; Annan Liu; Leilei Wang; Suyan Cao; Xue Sun; Fang Wang; Deping Liu
Journal:  Biosci Trends       Date:  2017-07-24       Impact factor: 2.400

6.  Predictive values of body mass index and waist circumference for risk factors of certain related diseases in Chinese adults--study on optimal cut-off points of body mass index and waist circumference in Chinese adults.

Authors:  Bei-Fan Zhou
Journal:  Biomed Environ Sci       Date:  2002-03       Impact factor: 3.118

7.  Relative muscle mass is inversely associated with insulin resistance and prediabetes. Findings from the third National Health and Nutrition Examination Survey.

Authors:  Preethi Srikanthan; Arun S Karlamangla
Journal:  J Clin Endocrinol Metab       Date:  2011-07-21       Impact factor: 5.958

8.  [Bioelectrical impedance and visceral fat: a comparison with computed tomography in adults and elderly].

Authors:  Michaela Eickemberg; Carolina Cunha de Oliveira; Anna Karla Carneiro Roriz; Gardênia Abreu Vieira Fontes; Adriana Lima Mello; Lílian Ramos Sampaio
Journal:  Arq Bras Endocrinol Metabol       Date:  2013-02

9.  Increased visceral fat and serum levels of triglyceride are associated with insulin resistance in Japanese metabolically obese, normal weight subjects with normal glucose tolerance.

Authors:  Akira Katsuki; Yasuhiro Sumida; Hideki Urakawa; Esteban C Gabazza; Shuichi Murashima; Noriko Maruyama; Kohei Morioka; Kaname Nakatani; Yutaka Yano; Yukihiko Adachi
Journal:  Diabetes Care       Date:  2003-08       Impact factor: 19.112

10.  The utility of fat mass index vs. body mass index and percentage of body fat in the screening of metabolic syndrome.

Authors:  Pengju Liu; Fang Ma; Huiping Lou; Yanping Liu
Journal:  BMC Public Health       Date:  2013-07-03       Impact factor: 3.295

View more
  2 in total

1.  Metabolic abnormalities, liver and body fat in American versus Chinese patients with non-alcoholic fatty liver disease.

Authors:  Wei Zhang; Grace L Su; Kaza Sravanthi; Rui Huang; Yi Wang; Huiying Rao; Lai Wei; Anna S Lok
Journal:  JGH Open       Date:  2022-05-23

2.  Sex differences in the associations between adiposity distribution and cardiometabolic risk factors in overweight or obese individuals: a cross-sectional study.

Authors:  Yide Yang; Ming Xie; Shuqian Yuan; Yuan Zeng; Yanhui Dong; Zhenghe Wang; Qiu Xiao; Bin Dong; Jun Ma; Jie Hu
Journal:  BMC Public Health       Date:  2021-06-26       Impact factor: 3.295

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.