A novel cutoff for the waist-to-height ratio predicting metabolic syndrome in young American adults

BMC Public Health

Volumn 16, Issue 1, 2016, Pages

  Bohr, Adam D ^a   Laurson, Kelly ^b   McQueen, Matthew B ^a  

^a UNIVERSITY OF COLORADO   (United States)

^b ILLINOIS STATE UNIVERSITY   (United States)

Author keywords

Cutoff; Epidemiology; Metabolic syndrome; Obesity; Waist to height ratio

Indexed keywords

ADULT; FEMALE; HEALTH SURVEY; HUMAN; LONGITUDINAL STUDY; MALE; METABOLIC SYNDROME X; OBESITY; PREDICTIVE VALUE; RECEIVER OPERATING CHARACTERISTIC; REFERENCE VALUE; REPRODUCIBILITY; UNITED STATES; WAIST TO HEIGHT RATIO; YOUNG ADULT;

ADULT; FEMALE; HEALTH SURVEYS; HUMANS; LONGITUDINAL STUDIES; MALE; METABOLIC SYNDROME X; OBESITY; PREDICTIVE VALUE OF TESTS; REFERENCE VALUES; REPRODUCIBILITY OF RESULTS; ROC CURVE; UNITED STATES; WAIST-HEIGHT RATIO; YOUNG ADULT;

EID: 84977559468     PISSN: None     EISSN: 14712458     Source Type: Journal    
DOI: 10.1186/s12889-016-2964-6     Document Type: Article

References (24)

1. National Center for Health Statistics. National Health and Nutrition Examination Survey. Questionnaires, datasets, and related documentation. Available at http://www.cdc.gov/nchs/nhanes/nhanes-questionnaires.htm.
2. World Health Organization. Preventing chronic diseases: a vital investment. Geneva: WHO Global Report; 2005.
3. Romero-Corral A et al. Association of bodyweight with total mortality and with cardiovascular events in coronary artery disease: a systematic review of cohort studies. Lancet. 2006;368(9536):666-78.
4. Flegal KM et al. Cause-specific excess deaths associated with underweight, overweight, and obesity. Jama. 2007;298(17):2028-37.
5. Flegal KM et al. Excess deaths associated with underweight, overweight, and obesity. Jama. 2005;293(15):1861-7.
6. Ashwell M, Gunn P, Gibson S. Waist-to-Height ratio is a better screening tool than waist circumference and BMI for adult cardiometabolic risk factors: systematic review and meta-analysis. Obes Rev. 2012;13(3):275-86.
7. Schneider HJ et al. The predictive value of different measures of obesity for incident cardiovascular events and mortality. J Clin Endocrinol Metabol. 2010;95(4):1777-85.
8. Cai L et al. Waist-to-Height ratio and cardiovascular risk factors among Chinese Adults in Beijing. PLoS One. 2013;8(7):e69298.
9. Peng YG et al. The Optimal Cut-Off Value of Waist-to-Height Ratio for Detecting Severe Central Obesity and Low Body Weight Adult Chinese Population. Zhonghua xin xue guan bing za zhi. 2013;41(7):607-10.
10. Savva SC, Lamnisos D, Kafatos AG. Predicting Cardiometabolic Risk: Waist-to-Height Ratio Or BMI. A Meta-Analysis. Diabetes Metab Syndr Obes. 2013;6:403-19.
11. Harris KM. The National Longitudinal Study of Adolescent Health (Add Health), Waves I & II, 1994-1996; Wave III, 2001-2002; Wave IV, 2007-2009 [machine-readable data file and documentation]. Chapel Hill, NC: Carolina Population Center, University of North Carolina at Chapel Hill; 2009. doi: 10.3886/ICPSR27021.v9.
12. Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. "Executive Summary of the Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III)." Jama 285.19 (2001): 2486-97
13. Grundy SM et al. Definition of Metabolic Syndrome: Report of the National Heart, Lung, and Blood Institute/American Heart Association Conference on Scientific Issues Related to Definition. Arterioscler Thromb Vasc Biol. 2004;24(2):e13-8.
14. Ervin RB. Prevalence of Metabolic Syndrome among Adults 20 Years of Age and Over, by Sex, Age, Race and Ethnicity, and Body Mass Index: United States, 2003-2006. Natl Health Stat Rep(13). 2009;13:1-7.
15. Schisterman EF et al. Youden Index and the Optimal Threshold for Markers with Mass at Zero. Stat Med. 2008;27(2):297-315.
16. RStudio. RStudio: Integrated development environment for R (Version 0.97.320) [Computer software]. Boston, MA. Retrieved Aug 9, 2012. Available from http://www.rstudio.org/
17. López-Ratón M et al. OptimalCutpoints: An R Package for Selecting Optimal Cutpoints in Diagnostic Tests. J Stat Softw. 2014;61.8:1-36.
18. Chantala K, Tabor J. Strategies to Perform a Design-Based Analysis Using the Add Health Data. 2010. Available at www.cpc.unc.edu.
19. Lumley T. Analysis of complex survey samples. Journal of Statistical Software 9.1. 2004:1-19.
20. Kuk JL et al. Visceral Fat is an Independent Predictor of all-Cause Mortality in Men. Obesity (Silver Spring, Md). 2006;14.2:336-41.
21. Manolopoulos, K. N., F. Karpe, and K. N. Frayn. Gluteofemoral Body Fat as a Determinant of Metabolic Health. Int J Obesity (2005) 34.6 (2010): 949-59
22. Wajchenberg BL et al. Depot-Specific Hormonal Characteristics of Subcutaneous and Visceral Adipose Tissue and their Relation to the Metabolic Syndrome. Horm Metab Res. 2002;34.11-12:616-21.
23. Carr MC, Brunzell JD. Abdominal Obesity and Dyslipidemia in the Metabolic Syndrome: Importance of Type 2 Diabetes and Familial Combined Hyperlipidemia in Coronary Artery Disease Risk. J Clin Endocrinol Metab. 2004;89(6):2601-7.
24. Ford ES, Giles WH, Mokdad AH. Increasing Prevalence of the Metabolic Syndrome among u.s. Adults. Diabetes Care. 2004;27(10):2444-9.