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Use of height3:waist circumference3 as an index for metabolic risk assessment?

Published online by Cambridge University Press:  08 March 2007

Anja Bosy-Westphal*
Affiliation:
Institut für Humanernährung und LebensmittelkundeChristian-Albrechts-Universitä t zu KielDüsternbrooker Weg 17D-24105 KielGermany
Sandra Danielzik
Affiliation:
Institut für Humanernährung und LebensmittelkundeChristian-Albrechts-Universitä t zu KielDüsternbrooker Weg 17D-24105 KielGermany
Corinna Geisler
Affiliation:
Institut für Humanernährung und LebensmittelkundeChristian-Albrechts-Universitä t zu KielDüsternbrooker Weg 17D-24105 KielGermany
Simone Onur
Affiliation:
Institut für Humanernährung und LebensmittelkundeChristian-Albrechts-Universitä t zu KielDüsternbrooker Weg 17D-24105 KielGermany
Oliver Korth
Affiliation:
Institut für Humanernährung und LebensmittelkundeChristian-Albrechts-Universitä t zu KielDüsternbrooker Weg 17D-24105 KielGermany
Oliver Selberg
Affiliation:
Städtisches Klinikum BraunschweigAbt. Klinische ChemieBraunschweigGermany
Maria Pfeuffer
Affiliation:
Bundesforschungsanstalt für Ernährung und Lebensmittel (BfEL)KielGermany
Jürgen Schrezenmeir
Affiliation:
Bundesforschungsanstalt für Ernährung und Lebensmittel (BfEL)KielGermany
Manfred J. Müller
Affiliation:
Institut für Humanernährung und LebensmittelkundeChristian-Albrechts-Universitä t zu KielDüsternbrooker Weg 17D-24105 KielGermany
*
*Corresponding author: Dr Matthias Brandsch, fax +49 04318805679, email abosyw@nutrfoodsc.uni-kiel.de
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Abstract

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Current anthropometric indices for health risk assessment are indirect measures of total or visceral body fat mass that do not consider the inverse relationship of lean body mass to metabolic risk as well as the non-linear relationship between central obesity and insulin resistance.We examined a new anthropometric index that reflects the relationship of waist circumference (WC) as a risk factor to fat-free mass (FFM) as a protective parameter of body composition. In apopulation of 335 adults (191 females and 144 males; mean age 53 (sd 13·9) years) with ahigh prevalence of obesity (27%) and metabolic syndrome (30%) we derived FFM:WC3 from the best fit of the relationship with metabolic risk factors (plasma triacylglycerol levels and insulin resistance by homeostasis model assessment index). Because FFM is known to be proportional to the cube of height, FFM was subsequently replaced by height3 yielding height3:WC3 as an easily applicable anthropometric index. Significant inverse relationships of height3:WC3 to metabolic risk factorswere observed for both sexes. They slightly exceeded those of conventional anthropometric indicessuch as BMI, WC or WC:hip ratio in women but not in men. The exponential character of the denominator WC3 implies that at a given FFM with gradually increasing WC the increasein metabolic risk is lower than proportional. Further studies are needed to evaluate height3:WC3 as an anthropometric index for health risk assessment.

Type
Research Article
Copyright
Copyright © The Nutrition Society 2006

References

Allison, DB, Paultre, F, Goran, MIPoehlman, ET&Heymsfield, SBStatistical considerations regarding the use of ratios to adjust data. Int J Obes 1995 19 644652Google ScholarPubMed
Allison, DB, Zhu, SK, Plankey, MFaith, MS&Heo, MDifferential associations of body mass index and adiposity with all-cause mortality among men in the first and second National Health and Nutrition Examination Surveys (NHANES I and NHANESII) follow-up studies. Int J Obes Relat Disord 2002 26 410416CrossRefGoogle Scholar
Ashwell, M, Chinn, S, Stalley, S&Garrow, JSFemale fat distribution: a photographic and cellularity study. Int J Obes Relat Disord 1978 2 289302Google ScholarPubMed
Aubert, H, Frere, C, Aillaud, MF, Morange, PEJuhan-Vague, IAlessi, MCWeak and non-independent association between plasma TAFI antigen levels and the insulin resistance syndrome. J Thromb Haemost 2003 1 791797CrossRefGoogle ScholarPubMed
Balkau, B&Charles, MAComment on the provisional report from the WHO consultation. European Group for the Study of Insulin Resistance (EGIR). Diabet Med 1999 16 442444Google Scholar
Bigaard, JFrederiksen, KTjonneland, AThomsen, BLOvervad, KHeitmann, BL&aSorensen, TIWaist and hip circumferences and all-cause mortality: usefulness of the waist-to-hip ratio?. Int J Obes Relat Metab Disord 2004a 28 741747CrossRefGoogle ScholarPubMed
Bigaard, J, Frederiksen, KTjonneland, AThomsen, BLOvervad, KHeitmann, BL&Sorensen, TIBody fat and fat-free mass and all-cause mortality. Obes Res 2004b 12 10421049CrossRefGoogle ScholarPubMed
Bigaard, J, Thomsen, BL, Tjonneland, ADoes waist circumference alone explain obesity-related health risk? Am J Clin Nutr 2004c 80 790792CrossRefGoogle ScholarPubMed
Bigaard, J, Tjonneland, A, Thomsen, BL, Overvad, K, Heitman, BL&Sorensen, TIAWaist circumference, BMI, smoking, and mortality in middle-aged men and women. Obes Res 2003 11 895903CrossRefGoogle Scholar
Bosy-Westphal, A, Eichhorn, C, Kutzner, D, Illner, K, Heller, M&Müller, MJThe age-related decline in resting energy expenditure in humans is due to the loss of fat-free mass and to alterations in its metabolically active components. J Nutr 2003a 133 23562362CrossRefGoogle Scholar
Bosy-Westphal, A, Geisler, C, Onur, S, Korth, O, Selberg, O, Schrezenmeir, JMüller, MJValue of body fat mass vs. anthropometric obesity indices in the assessment of metabolic risk factors Int J Obes 2006 30 475483CrossRefGoogle Scholar
Bosy-Westphal, A, Mast, M, Eichhorn, C, Becker, CKutzner, D, Heller, MMüller, MJValidation of air-displacement plethysmography for estimation of body fat mass in healthy elderly subjects. Eur J Nutr 2003b 42 207216CrossRefGoogle ScholarPubMed
Brauer, GW&Prior, IAA prospective study of gout in New Zealand Maoris. Ann Rheum Dis 1978 37 466472CrossRefGoogle ScholarPubMed
Chan, DC, Watts, GF, Barrett, PH&Burke, VWaist circumference, waist-to-hip ratio and body mass index as predictors of adipose tissue compartments in men. QJM 2003 96 441447CrossRefGoogle ScholarPubMed
Cnop, M, Landchild, MJ, Vidal, J et al. , The concurrent accumulation of intra-abdominal and subcutaneous fat explains the association between insulin resistance and plasma leptin concentrations: distinct metabolic effects of two fat compartments Diabetes 2002 51 10051015CrossRefGoogle ScholarPubMed
Danielzik, S, Czerwinski-Mast, M, Langnäse, K, Dilba, B & Müller, MJParental overweight, socioeconomic status and high birth weight are the major determinants of overweight and obesity in 5-7y-old children: baseline data of the Kiel Obesity Prevention Study Int J Obes Relat Disord 2004 28 14941502CrossRefGoogle Scholar
Eng, J (2002). ROC analysis: web-based calculator for ROC curves. Johns Hopkins University, Baltimore. Accessed 19 February 2006. http://www.rad.jhmi.edu/roc.Google Scholar
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 2002 258 24862497Google Scholar
Forbes, GBStature and lean body mass. Am J Clin Nutr 1974 27 595602CrossRefGoogle Scholar
Gan, SK, Kriketos, AD, Poynten, AM, Furler, SM, Thompson, CH, Kraegen, EW, Campbell, LV&Chrisholm, DJInsulin action, regional fat, and myocyte lipid: altered relationships with increased adiposity. Obes Res 2003 11 12951305CrossRefGoogle ScholarPubMed
Guo, Z, Hensrud, DD, Johnson, CM, Jensen, MDRegional postprandial fatty acid metabolism in different obesity phenotypes. Diabetes 1999 48 15861592CrossRefGoogle ScholarPubMed
Han, TS, McNeill, G, Seidell, JC&Lean, ME(1997) Predicting intra-abdominal fatness from anthropometric measures: the influence of stature. Int J Obes Relat Disord 1997 21 587593CrossRefGoogle ScholarPubMed
Hansen, RDAllen, BJHabitual physical activity, anabolic hormones, and potassium content of fat-free mass in postmenopausal women. Am J Clin Nutr 2002 75 314320CrossRefGoogle ScholarPubMed
Hara, MSaitou, EIwata, FOkada, THarada, KWaist-to-height ratio is the best predictor of cardiovascular disease risk factors in Japanese schoolchildren. J Atheroscler Thromb 2002 9 127132CrossRefGoogle ScholarPubMed
He, QHeo, MHeshka, SWang, JPierson, RNAlbu, J Jr Wang, ZHeymsfield, SBGallagher, DTotal body potassium differs by sex and race across the adult age span. Am J Clin Nutr 2003 78 7277CrossRefGoogle Scholar
Heitmann, BLErikson, HEllsinger, BMMikkelsen, KLLarsson, BMortality associated with body fat, fat-free mass and body mass index among 60-year-old Swedish men – a 22-year follow-up. The study of men born in 1913.Int J Obes Relat Metab Disord 2000 24 3337CrossRefGoogle Scholar
Henriksson, KMLindblad, UAgren, BNilsson-Ehle, PRastam, LAssociations between body height, body composition and cholesterol levels in middle-aged men. The Coronary Risk Factor study in southern Sweden (CRISS). Eur J Epidemiol 2001 17 521526CrossRefGoogle ScholarPubMed
Hsieh, SDMuto, TThe superiority of waist-to-height ratio as an anthropometric index to evaluate clustering of coronary risk factors among non-obese men and women. Prev Med 2005 40 216220CrossRefGoogle Scholar
Hsieh, SDYoshinaga, HMuto, TWaist-to-height ratio, a simple and practical index for assessing central fat distribution and metabolic risk in Japanese men and women. Int J Obes Relat Disord 2003 27 610616CrossRefGoogle ScholarPubMed
International Diabetes Federation (2005). The IDF consensus worldwide definition of the metabolic syndrome. International Diabetes Federation, Brussels, Belgium. Accessed 18 February 2006. http://www.idf.org.Google Scholar
Janssen, IKatzmarzyk, PTRoss, RWaist circumference and not body mass index explains obesity-related health risk. Am J Clin Nutr 2004 79 379384CrossRefGoogle Scholar
Kotler, DPWang, JPierson, RNBody composition studies in patients with the acquired immunodeficiency syndrome. Am J Clin Nutr 1985 42 12551265CrossRefGoogle ScholarPubMed
Kronmal, RASpurious correlation and the fallacy of the ratio standard revisited. J Roy Stat Soc 1992 156 379392CrossRefGoogle Scholar
Kuk, JLLee, SHeymsfield, SBRoss, RWaist circumference and abdominal adipose tissue distribution: influence of age and sex. Am J Clin Nutr 2005 81 13301334CrossRefGoogle ScholarPubMed
Lapidus, LBengtsson, CLarsson, BPennert, KRybo, ESjostrom, LDistribution of adipose tissue and risk of cardiovascular disease and death; a 12 year follow up of participants in the population study of women in Gothenburg, Sweden. BMJ 1984 289 12571260CrossRefGoogle Scholar
Larsson, BSvardsudd, KWelin, LWilhelmsen, LBjorntorp, PTibblin, GAbdominal adipose tissue distribution, obesity and risk of cardiovascular disease and death: 13 year follow up of participants in the study of men born in 1913. BMJ 1984 288 14011404CrossRefGoogle Scholar
Lewis, GFUffelmang, KDSzeto, LWWeller, BSteiner, GInteraction between free fatty acids and insulin in the acute control of very low density lipoprotein production in humans. J Clin Invest 1995 95 158166CrossRefGoogle ScholarPubMed
Lissner, LBjorkelund, CHeitmann, BLSeidell, JCBergtsson, CLarger hip circumference independently predicts health and longevity in a Swedish female cohort. Obes Res 2001 9 644646CrossRefGoogle Scholar
Lofren, IHerron, KZern, TWest, KPatalay, MShachter, NSKoo, SIFernandez, MLWaist circumference is a better predictor than body mass index for coronary heart disease risk in overweight premenopausal women. J Nutr 2004 134 10711076CrossRefGoogle Scholar
Matthews, DRHosker, JPRudenski, ASNaylor, BATreacher, DFTurner, RCHomeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985 28 412419CrossRefGoogle ScholarPubMed
Müller, MJBosy-Westphal, AKutzner, DHeller, MMetabolically active components of fat-free mass and resting energy expenditure in humans: recent lessons from imaging technologies. Obes Rev 2002 3 113122CrossRefGoogle Scholar
Nakanishi, NNakamura, KSuzuki, KMatsuo, YTatara, KAssociations of body mass index and percentage body fat by bioelectrical impedance analysis with cardiovascular risk factors in Japanese male office workers. Ind Health 2000 38 273279CrossRefGoogle ScholarPubMed
Nielsen, SGuo, ZKJohnson, MHensrud, DDJensen, MDSplanchnic lipolysis in human obesity. J Clin Invest 2004 113 15821588CrossRefGoogle ScholarPubMed
Onat, AAvci, GSBarlan, MMUyarel, HUzunlar, BSansoy, VMeasures of abdominal obesity assessed for visceral adiposity and relation to coronary risk. Int J Obes Relat Metab Disord 2004 28 10181025CrossRefGoogle ScholarPubMed
Piers, LSSoares, MJ, Frandsen, SLO'Dea, KIndirect estimates of body composition are useful for groups but unreliable in individuals. Int J Obes Relat Metab Disord 2000 24 11451152CrossRefGoogle ScholarPubMed
Richelsen, BPedersen, SB(1995) Associations between different anthropometric measurements of fatness and metabolic risk parameters in non-obese, healthy, middle-aged men. Int J Obes Relat Metab Disord 1995 19 169174Google ScholarPubMed
Sayeed, MAMahtab, HLatif, ZAKhanam, PAAhsan, KABanu, AAzad, Khan AKWaist-to-height ratio is a better obesity index than body mass index and waist-to-hip ratio for predicting diabetes, hypertension and lipidemia. Bangladesh Med Res Counc Bull 2003 29 110Google ScholarPubMed
Seidell, JCHan, TSFeskens, EJLean, MENarrow hips and broad waist circumferences independently contribute to increased risk of non-insulin-dependent diabetes mellitus. J Intern Med 1997 242 401406CrossRefGoogle Scholar
Seidell, JCPersse, LDespres, J-PBouchard, C(2001) Waist and hip circumference have independent and opposite effects on cardiovascular disease risk factors: the Quebec Family Study. Am J Clin Nutr 2001 74 315321CrossRefGoogle ScholarPubMed
Siri, WE (1961) Body composition from fluid spaces and density: analysis of methods. In Techniques for Measuring Body Composition, pp. 223244 [Siri, Brozek JHenschel, A editors]. Washington, DC National Academy of SciencesGoogle Scholar
Snijder, MBDekker, JMVisser, MYudkin, JSStehouwer, CDBouter, LMHeine, RJNijpels, GSeidell, JCLarger thigh and hip circumferences are associated with better glucose tolerance: the Hoorn Study. Obes Res 2003 11 104111CrossRefGoogle ScholarPubMed
Snijder, MBZimmet, PZVisser, MDekker, JMSeidell, JCShaw, JEIndependent and opposite associations of waist and hip circumferences with diabetes, hypertension and dyslipidemia: the AusDiab Study. Int J Obes Relat Metab Disord 2004 28 402409CrossRefGoogle ScholarPubMed
Tai, ESHo, SCFok, ACTan, CEMeasurement of obesity by anthropometry and bioelectric impedance analysis: correlation with fasting lipids and insulin resistance in an Asian population. Ann Acad Med Singapore 1999 28 445450Google Scholar
Terry, RBWood, PDHaskell, WLStefanick, MLKrauss, RM(1989) Regional adiposity patterns in relation to lipids, lipoprotein cholesterol, and lipoprotein subfraction mass in men. J Clin Endocrinol Metab 1989 68 191199CrossRefGoogle ScholarPubMed
Tulloch-Reid, MKWilliams, DELooker, HCHanson, RLKnowler, WCDo measures of body fat distribution provide information on the risk of type 2 diabetes in addition to measures of general obesity? – Comparison of anthropometric predictors of type 2 diabetes in Pima Indians. Diabetes Care 2003 26 25562561CrossRefGoogle ScholarPubMed
Warne, DKCharles, MAHanson, RLJacobsen, LTHMcCane, DRKnowler, WCPettitt, DJComparison of body size measurements as predictors of NIDDM in Pima Indians. Diabetes Care 1995 18 435439CrossRefGoogle ScholarPubMed
Wellen, KEHotamisligil, GSObesity-induced inflammatory changes in adipose tissue. J Clin Invest 2003 112 17851788CrossRefGoogle ScholarPubMed