Literature DB >> 21085910

Waist-to-height ratio, an optimal predictor for obesity and metabolic syndrome in Chinese adults.

J Shao1, L Yu, X Shen, D Li, K Wang.   

Abstract

OBJECTIVE: Anthropometric indices to obesity were evaluated as predictors of metabolic syndrome risk factors. Our purpose was to explore an optimal or more reliable anthropometric indicator and optimal cut-off points for obesity on metabolic syndrome in Chinese adults. PARTICIPANTS AND METHODS: The survey was conducted involving 2947 participants, aged 20 or above with cross-sectional study of population. The predictive validity and optimal cut-off values were analyzed by receiver operating characteristic (ROC) curves, area under curve (AUC) and the largest Youden's index (sensitivity + specificity - 1) by gender group, respectively. Kappa value showed diagnostic consistency.
RESULTS: According to the criteria of CDS 2004, IDF 2005 and AHA/NHLBI 2005, the prevalence of metabolic syndrome was 10.32%, 9.64% and 16.12% respectively, which indicated that the prevalence was higher in men than in women and increased with age (P < 0.05). The BMI, WC, WHR and WHtR in metabolic syndrome patients were greater than those in healthy volunteers and the indices in men were higher than those in women. With adjusted age and gender, the partial correlation coefficient for BMI-WC, BMI-WHR and BMI-WHtR was 0.7991, 0.5278 and 0.8196, respectively (P < 0.05). The area under curves (AUCs) of receiver operating characteristic (ROC) curves for WHtR was larger (P < 0.05) than that for WC and WHR. The cut-point of WHtR was approximately 0.5 in both genders with a satisfactory balance between sensitivity and specificity, where the Kappa (k) value for WHtR-BMI was higher than that for WHtR-WHR, and WHtR-WC.
CONCLUSIONS: The results indicated that WHtR might be an optimal anthropometric predictor of metabolic syndrome risk factors and the cut-point of WHtR was approximately 0.50 in both genders of Chinese adults.

Entities:  

Mesh:

Year:  2010        PMID: 21085910     DOI: 10.1007/s12603-010-0106-x

Source DB:  PubMed          Journal:  J Nutr Health Aging        ISSN: 1279-7707            Impact factor:   4.075


  29 in total

1.  DXA measurements confirm that parental perceptions of elevated adiposity in young children are poor.

Authors:  Jody C Miller; Andrea M Grant; Bernadette F Drummond; Sheila M Williams; Rachael W Taylor; Ailsa Goulding
Journal:  Obesity (Silver Spring)       Date:  2007-01       Impact factor: 5.002

2.  The role of abdominal obesity and weight gain since adolescence in early atherosclerosis.

Authors:  Turgay Celik; Atila Iyisoy; U Cagdas Yuksel; Ersoy Isik
Journal:  Int J Cardiol       Date:  2007-07-24       Impact factor: 4.164

3.  Obesity and the metabolic syndrome.

Authors:  Kathryn Buchanan Keller; Louis Lemberg
Journal:  Am J Crit Care       Date:  2003-03       Impact factor: 2.228

4.  Obesity and the risk of myocardial infarction in 27,000 participants from 52 countries: a case-control study.

Authors:  Salim Yusuf; Steven Hawken; Stephanie Ounpuu; Leonelo Bautista; Maria Grazia Franzosi; Patrick Commerford; Chim C Lang; Zvonko Rumboldt; Churchill L Onen; Liu Lisheng; Supachai Tanomsup; Paul Wangai; Fahad Razak; Arya M Sharma; Sonia S Anand
Journal:  Lancet       Date:  2005-11-05       Impact factor: 79.321

5.  The prospective association of general and central obesity variables with incident type 2 diabetes in adults, Tehran lipid and glucose study.

Authors:  Farzad Hadaegh; Azadeh Zabetian; Hadi Harati; Fereidoun Azizi
Journal:  Diabetes Res Clin Pract       Date:  2006-12-04       Impact factor: 5.602

6.  Index of central obesity - A novel parameter.

Authors:  Rakesh M Parikh; Shashank R Joshi; Padmavathy S Menon; Nalini S Shah
Journal:  Med Hypotheses       Date:  2006-12-06       Impact factor: 1.538

7.  Comparisons between anthropometric indices for predicting the metabolic syndrome in Japanese.

Authors:  Masayuki Kato; Yoshihiko Takahashi; Manami Inoue; Shoichiro Tsugane; Takashi Kadowaki; Mitsuhiko Noda
Journal:  Asia Pac J Clin Nutr       Date:  2008       Impact factor: 1.662

8.  Obesity criteria for identifying metabolic risks.

Authors:  Jin-wen Wang; Da-yi Hu; Yi-hong Sun; Jia-hong Wang; Gui-lian Wang; Jiang Xie; Zi-qiang Zhou
Journal:  Asia Pac J Clin Nutr       Date:  2009       Impact factor: 1.662

9.  Relationships between indices of obesity and its cardiovascular comorbidities in a Chinese population.

Authors:  Rui Li; Wei Lu; Jian Jia; Shengnian Zhang; Liang Shi; Yanyun Li; Qundi Yang; Haidong Kan
Journal:  Circ J       Date:  2008-06       Impact factor: 2.993

10.  Which is the best anthropometric technique to identify obesity: body mass index, waist circumference or waist-hip ratio?

Authors:  Ersin Akpinar; Ibrahim Bashan; Nafiz Bozdemir; Esra Saatci
Journal:  Coll Antropol       Date:  2007-06
View more
  33 in total

1.  Ethnic disparities in the association of body mass index with the risk of hypertension and diabetes.

Authors:  Robert J Wong; Christina Chou; Sidhartha R Sinha; Ahmad Kamal; Aijaz Ahmed
Journal:  J Community Health       Date:  2014-06

Review 2.  Obesity and non-alcoholic fatty liver disease: Disparate associations among Asian populations.

Authors:  Robert J Wong; Aijaz Ahmed
Journal:  World J Hepatol       Date:  2014-05-27

3.  Environmental, Dietary, and Behavioral Factors Distinguish Chinese Adults with High Waist-to-Height Ratio with and without Inflammation.

Authors:  Amanda L Thompson; Linda Adair; Penny Gordon-Larsen; Bing Zhang; Barry Popkin
Journal:  J Nutr       Date:  2015-05-06       Impact factor: 4.798

4.  Comparison of effects of obesity and non-alcoholic fatty liver disease on incidence of type 2 diabetes mellitus.

Authors:  Wei-Dong Li; Kun-Fa Fu; Gui-Mei Li; Yan-Shu Lian; Ai-Min Ren; Yun-Jue Chen; Jin-Rong Xia
Journal:  World J Gastroenterol       Date:  2015-08-28       Impact factor: 5.742

5.  Secular change in the association between urbanisation and abdominal adiposity in China (1993-2011).

Authors:  Yosuke Inoue; Annie Green Howard; Amanda L Thompson; Penny Gordon-Larsen
Journal:  J Epidemiol Community Health       Date:  2018-03-07       Impact factor: 3.710

6.  Obesity in young-adult Nigerians: variations in prevalence determined by anthropometry and bioelectrical impedance analysis, and the development of % body fat prediction equations.

Authors:  Chukwunonso Ecc Ejike; Ifeoma I Ijeh
Journal:  Int Arch Med       Date:  2012-07-20

7.  Limit your waist size to half of your height.

Authors:  Rakesh M Parikh
Journal:  Indian J Endocrinol Metab       Date:  2011-07

8.  Adiposity and pathogen exposure: An investigation of response to iron supplementation and hypothesized predictors in anemic pre-school-aged children living in a dual burden environment.

Authors:  Achsah F Dorsey; Mary E Penny; Amanda L Thompson
Journal:  Am J Phys Anthropol       Date:  2021-04-14       Impact factor: 2.963

9.  Risk of type 2 diabetes according to traditional and emerging anthropometric indices in Spain, a Mediterranean country with high prevalence of obesity: results from a large-scale prospective cohort study.

Authors:  José María Huerta; María-José Tormo; María-Dolores Chirlaque; Diana Gavrila; Pilar Amiano; Larraitz Arriola; Eva Ardanaz; Laudina Rodríguez; María-José Sánchez; Michelle Mendez; Diego Salmerón; Aurelio Barricarte; Rosana Burgui; Miren Dorronsoro; Nerea Larrañaga; Esther Molina-Montes; Conchi Moreno-Iribas; José Ramón Quirós; Estefanía Toledo; Noémie Travier; Carlos A González; Carmen Navarro
Journal:  BMC Endocr Disord       Date:  2013-02-06       Impact factor: 2.763

10.  Waist to height ratio is associated with an increased risk of mortality in Chinese patients with heart failure with preserved ejection fraction.

Authors:  Jianqiao Chen; Man Li; Benchuan Hao; Yulun Cai; Huiying Li; Wenli Zhou; Yujian Song; Shiqi Wang; Hongbin Liu
Journal:  BMC Cardiovasc Disord       Date:  2021-05-28       Impact factor: 2.298

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.