Literature DB >> 16768846

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

Anja Bosy-Westphal1, Sandra Danielzik, Corinna Geisler, Simone Onur, Oliver Korth, Oliver Selberg, Maria Pfeuffer, Jürgen Schrezenmeir, Manfred J Müller.   

Abstract

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 a population of 335 adults (191 females and 144 males; mean age 53 (SD 13.9) years) with a high prevalence of obesity (27%) and metabolic syndrome (30%) we derived FFM:WC(3) 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 height(3) yielding height(3):WC(3) as an easily applicable anthropometric index. Significant inverse relationships of height(3):WC(3) to metabolic risk factors were observed for both sexes. They slightly exceeded those of conventional anthropometric indices such as BMI, WC or WC:hip ratio in women but not in men. The exponential character of the denominator WC(3) implies that at a given FFM with gradually increasing WC the increase in metabolic risk is lower than proportional. Further studies are needed to evaluate height(3):WC(3) as an anthropometric index for health risk assessment.

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Year:  2006        PMID: 16768846     DOI: 10.1079/bjn20061763

Source DB:  PubMed          Journal:  Br J Nutr        ISSN: 0007-1145            Impact factor:   3.718


  4 in total

1.  Waist circumference and related anthropometric indices are associated with metabolic traits in severely obese subjects.

Authors:  Runa Zazai; Britta Wilms; Barbara Ernst; Martin Thurnheer; Bernd Schultes
Journal:  Obes Surg       Date:  2014-05       Impact factor: 4.129

2.  Associations of age, gender and body mass with 1H MR-observed brain metabolites and tissue distributions.

Authors:  A A Maudsley; V Govind; K L Arheart
Journal:  NMR Biomed       Date:  2011-08-19       Impact factor: 4.044

3.  Different anthropometric adiposity measures and their association with cardiovascular disease risk factors: a meta-analysis.

Authors:  S B van Dijk; T Takken; E C Prinsen; H Wittink
Journal:  Neth Heart J       Date:  2012-05       Impact factor: 2.380

4.  Body shape indices are predictors for estimating fat-free mass in male athletes.

Authors:  Yohei Takai; Miyuki Nakatani; Toru Aoki; Daisuke Komori; Kazuyuki Oyamada; Kensuke Murata; Eiji Fujita; Takuya Akamine; Yoshihisa Urita; Masayoshi Yamamoto; Hiroaki Kanehisa
Journal:  PLoS One       Date:  2018-01-18       Impact factor: 3.240

  4 in total

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