Literature DB >> 20642876

Optimal cut-off values and population means of waist circumference in different populations.

Zhiqiang Wang1, Jun Ma, Damin Si.   

Abstract

Abdominal obesity is a risk factor for cardiometabolic disease, and has become a major public health problem in the world. Waist circumference is generally used as a simple surrogate marker to define abdominal obesity for population screening. An increasing number of publications solely rely on the method that maximises sensitivity and specificity to define 'optimal' cut-off values. It is well documented that the optimal cut-off values of waist circumference vary across different ethnicities. However, it is not clear if the variation in cut-off values is a true biological phenomenon or an artifact of the method for identifying optimal cut-off points. The objective of the present review was to assess the relationship between optimal cut-offs and population waist circumference levels. Among sixty-one research papers, optimal cut-off values ranged from 65·5 to 101·2 cm for women and 72·5 to 103·0 cm for men. Reported optimal cut-off values were highly correlated with population means (correlation coefficient: 0·91 for men and 0·93 for women). Such a strong association was independent of waist circumference measurement techniques or the health outcomes (dyslipidaemia, hypertension or hyperglycaemia), and existed in some homogeneous populations such as the Chinese and Japanese. Our findings raised some concerns about applying the sensitivity and specificity approach to determine cut-off values. Further research is needed to understand whether the differences among populations in waist circumference were genetically or environmentally determined, and to understand whether using region-specific cut-off points can identify individuals with the same absolute risk levels of metabolic and cardiovascular outcomes among different populations.

Entities:  

Mesh:

Year:  2010        PMID: 20642876     DOI: 10.1017/S0954422410000120

Source DB:  PubMed          Journal:  Nutr Res Rev        ISSN: 0954-4224            Impact factor:   7.800


  15 in total

1.  Definition and Diagnostic Criteria for Sarcopenic Obesity: ESPEN and EASO Consensus Statement.

Authors:  Lorenzo M Donini; Luca Busetto; Stephan C Bischoff; Tommy Cederholm; Maria D Ballesteros-Pomar; John A Batsis; Juergen M Bauer; Yves Boirie; Alfonso J Cruz-Jentoft; Dror Dicker; Stefano Frara; Gema Frühbeck; Laurence Genton; Yftach Gepner; Andrea Giustina; Maria Cristina Gonzalez; Ho-Seong Han; Steven B Heymsfield; Takashi Higashiguchi; Alessandro Laviano; Andrea Lenzi; Ibolya Nyulasi; Edda Parrinello; Eleonora Poggiogalle; Carla M Prado; Javier Salvador; Yves Rolland; Ferruccio Santini; Mireille J Serlie; Hanping Shi; Cornel C Sieber; Mario Siervo; Roberto Vettor; Dennis T Villareal; Dorothee Volkert; Jianchun Yu; Mauro Zamboni; Rocco Barazzoni
Journal:  Obes Facts       Date:  2022-02-23       Impact factor: 4.807

2.  The performance of obesity screening tools among young Thai adults.

Authors:  Panita Limpawattana; Thepkhachi Kengkijkosol; Prasert Assantachai; Orapitchaya Krairit; Jiraporn Pimporm
Journal:  J Community Health       Date:  2014-12

3.  Corresponding waist circumference and body mass index values based on 10-year absolute type 2 diabetes risk in an Australian Aboriginal community.

Authors:  Odewumi Adegbija; Wendy E Hoy; Zhiqiang Wang
Journal:  BMJ Open Diabetes Res Care       Date:  2015-09-16

4.  Contribution of Different Phenotypes of Obesity to Metabolic Abnormalities from a Cross-Sectional Study in the Northwest China.

Authors:  Xixuan Lu; Qiang Wang; Haiyan Liang; Li Xu; Liping Sha; Yuemei Wu; Liting Ma; Ping Yang; Hong Lei
Journal:  Diabetes Metab Syndr Obes       Date:  2021-07-07       Impact factor: 3.168

5.  Relationship between waist circumference, visceral fat and metabolic syndrome in a Congolese community: further research is still to be undertaken.

Authors:  Philippe Bianga Katchunga; Michel Hermans; Bertrand Akonkwa Bamuleke; Patrick Cimusa Katoto; Jeff Maotela Kabinda
Journal:  Pan Afr Med J       Date:  2013-01-14

6.  Prevalence of the metabolic syndrome and determination of optimal cut-off values of waist circumference in university employees from Angola.

Authors:  Pedro Magalhães; Daniel P Capingana; José G Mill
Journal:  Cardiovasc J Afr       Date:  2014 Jan-Feb       Impact factor: 1.167

7.  Waist circumference cutoff points to predict obesity, metabolic syndrome, and cardiovascular risk in Turkish adults.

Authors:  Alper Sonmez; Fahri Bayram; Cem Barcin; Muge Ozsan; Ahmet Kaya; Vedia Gedik
Journal:  Int J Endocrinol       Date:  2013-11-27       Impact factor: 3.257

8.  Neck circumference as a measure of neck fat and abdominal visceral fat in Chinese adults.

Authors:  Hong-Xing Li; Fen Zhang; Dong Zhao; Zhong Xin; Shu-Qin Guo; Shu-Mei Wang; Jian-Jun Zhang; Jun Wang; Yan Li; Guang-Ran Yang; Jin-Kui Yang
Journal:  BMC Public Health       Date:  2014-04-04       Impact factor: 3.295

9.  Waist circumference values equivalent to body mass index points for predicting absolute cardiovascular disease risks among adults in an Aboriginal community: a prospective cohort study.

Authors:  Odewumi Adegbija; Wendy E Hoy; Zhiqiang Wang
Journal:  BMJ Open       Date:  2015-11-13       Impact factor: 2.692

10.  High Discrepancy in Abdominal Obesity Prevalence According to Different Waist Circumference Cut-Offs and Measurement Methods in Children: Need for Age-Risk-Weighted Standardized Cut-Offs?

Authors:  Alice Monzani; Anna Rapa; Flavia Prodam; Nicola Fuiano; Giuliana Diddi; Antonella Petri; Simonetta Bellone; Gianni Bona
Journal:  PLoS One       Date:  2016-01-08       Impact factor: 3.240

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