Literature DB >> 25819369

The discriminative ability of waist circumference, body mass index and waist-to-hip ratio in identifying metabolic syndrome: Variations by age, sex and race.

Kee C Cheong1, Sumarni M Ghazali2, Lim K Hock3, Soobitha Subenthiran2, Teh C Huey3, Lim K Kuay3, Feisul I Mustapha4, Ahmad F Yusoff2, Amal N Mustafa2.   

Abstract

OBJECTIVES: Many studies have suggested that there is variation in the capabilities of BMI, WC and WHR in predicting cardiometabolic risk and that it might be confounded by gender, ethnicity and age group. The objective of this study is to examine the discriminative abilities of body mass index (BMI), waist circumference (WC) and waist-hip ratio (WHR) to predict two or more non-adipose components of the metabolic syndrome (high blood pressure, hypertriglyceridemia, low high density lipoprotein-cholesterol and high fasting plasma glucose) among the adult Malaysian population by gender, age group and ethnicity.
METHODS: Data from 2572 respondents (1044 men and 1528 women) aged 25-64 years who participated in the Non Communicable Disease Surveillance 2005/2006, a population-based cross sectional study, were analysed. Participants' socio-demographic details, anthropometric indices (BMI, WC and WHR), blood pressure, fasting lipid profile and fasting glucose level were assessed. Receiver operating characteristics curves analysis was used to evaluate the ability of each anthropometric index to discriminate MetS cases from non-MetS cases based on the area under the curve.
RESULTS: Overall, WC had better discriminative ability than WHR for women but did not perform significantly better than BMI in both sexes, whereas BMI was better than WHR in women only. Waist circumference was a better discriminator of MetS compared to WHR in Malay men and women. Waist circumference and BMI performed better than WHR in Chinese women, men aged 25-34 years and women aged 35-44 years.
CONCLUSIONS: The discriminative ability of BMI and WC is better than WHR for predicting two or more non-adipose components of MetS. Therefore, either BMI or WC measurements are recommended in screening for metabolic syndrome in routine clinical practice in the effort to combat cardiovascular disease and type II diabetes mellitus.
Copyright © 2015 Diabetes India. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Adult; Body mass index; Metabolic syndrome; Waist circumference; Waist–hip ratio

Mesh:

Substances:

Year:  2015        PMID: 25819369     DOI: 10.1016/j.dsx.2015.02.006

Source DB:  PubMed          Journal:  Diabetes Metab Syndr        ISSN: 1871-4021


  19 in total

Review 1.  Is there any connection between choroidal thickness and obesity?

Authors:  Farshad Askarizadeh; Mohsen Heirani; Masoud Khorrami-Nejad; Foroozan Narooie-Noori; Mehdi Khabazkhoob; Alireza Ostadrahimi
Journal:  Ther Adv Ophthalmol       Date:  2022-06-30

2.  Relationship between aerobic capacity and cardiovascular disease risk factors in Thai men and women with normolipidemia and dyslipidemia.

Authors:  Jatuporn Wichitsranoi; Suphannika Ladawan; Suchart Sirijaichingkul; Nongnuch Settasatian; Naruemon Leelayuwat
Journal:  J Phys Ther Sci       Date:  2015-11-30

3.  Longitudinal Associations between Triglycerides and Metabolic Syndrome Components in a Beijing Adult Population, 2007-2012.

Authors:  Li-Xin Tao; Kun Yang; Xiang-Tong Liu; Kai Cao; Hui-Ping Zhu; Yan-Xia Luo; Jin Guo; Li-Juan Wu; Xia Li; Xiu-Hua Guo
Journal:  Int J Med Sci       Date:  2016-06-01       Impact factor: 3.738

4.  The importance of waist circumference and body mass index in cross-sectional relationships with risk of cardiovascular disease in Vietnam.

Authors:  Nga Thi Thu Tran; Christopher Leigh Blizzard; Khue Ngoc Luong; Ngoc Le Van Truong; Bao Quoc Tran; Petr Otahal; Mark Nelson; Costan Magnussen; Seana Gall; Tan Van Bui; Velandai Srikanth; Thuy Bich Au; Son Thai Ha; Hai Ngoc Phung; Mai Hoang Tran; Michele Callisaya
Journal:  PLoS One       Date:  2018-05-29       Impact factor: 3.240

5.  Including selective metabolic components in current diagnostic criteria does not improve discriminative validity for metabolic syndrome: a risk score approach.

Authors:  Huan-Cheng Chang; Sheng-Pyng Chen; Hao-Jan Yang
Journal:  J Int Med Res       Date:  2019-01-24       Impact factor: 1.573

6.  Network Modeling Sex Differences in Brain Integrity and Metabolic Health.

Authors:  Janelle T Foret; Maria Dekhtyar; James H Cole; Drew D Gourley; Marie Caillaud; Hirofumi Tanaka; Andreana P Haley
Journal:  Front Aging Neurosci       Date:  2021-06-29       Impact factor: 5.750

7.  Correlation of Cardiovascular Risk Factors with Central Obesity and Multiple Body Mass Index in Korea.

Authors:  Bora Yoo; Hosuk Nam; In Cheol Hwang; Youngmin Park
Journal:  Korean J Fam Med       Date:  2017-11-14

Review 8.  The Global Epidemic of the Metabolic Syndrome.

Authors:  Mohammad G Saklayen
Journal:  Curr Hypertens Rep       Date:  2018-02-26       Impact factor: 5.369

9.  Associations of Obesity With Incident Hospitalization Related to Peripheral Artery Disease and Critical Limb Ischemia in the ARIC Study.

Authors:  Caitlin W Hicks; Chao Yang; Chiadi E Ndumele; Aaron R Folsom; Gerardo Heiss; James H Black; Elizabeth Selvin; Kunihiro Matsushita
Journal:  J Am Heart Assoc       Date:  2018-08-21       Impact factor: 5.501

10.  Age-specific waist circumference cutoff-points for abdominal obesity diagnosis: a personalized strategy for a large Venezuelan population.

Authors:  Valmore Bermudez; Juan Salazar; María Sofía Martínez; Luis Carlos Olivar; Manuel Nava; Milagros Rojas; Ángel Ortega; Roberto Añez; Alexandra Toledo; Joselyn Rojas; Maricarmen Chacín; Johel E Rodríguez; Luis D'Marco; Clímaco Cano
Journal:  J Diabetes Metab Disord       Date:  2021-01-16
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.