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Correlation and prediction of trunk fat mass with four anthropometric indices in Chinese males

Published online by Cambridge University Press:  08 March 2007

Su-Mei Xiao ,
Shu-Feng Lei ,
Xiang-Ding Chen ,
Man-Yuan Liu ,
Wei-Xia Jian ,
Hong Xu ,
Li-Jun Tan ,
Fei-Yan Deng ,
Yan-Jun Yang  and
Yan-Bo Wang
...Show all authors
Su-Mei Xiao
Affiliation:
Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan 410081, P. R. China
Shu-Feng Lei
Affiliation:
Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan 410081, P. R. China
Xiang-Ding Chen
Affiliation:
Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan 410081, P. R. China
Man-Yuan Liu
Affiliation:
Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan 410081, P. R. China
Wei-Xia Jian
Affiliation:
Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan 410081, P. R. China
Hong Xu
Affiliation:
Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan 410081, P. R. China
Li-Jun Tan
Affiliation:
Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan 410081, P. R. China
Fei-Yan Deng
Affiliation:
Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan 410081, P. R. China
Yan-Jun Yang
Affiliation:
Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan 410081, P. R. China
Yan-Bo Wang
Affiliation:
Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan 410081, P. R. China
Xiao Sun
Affiliation:
Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan 410081, P. R. China
Cheng Jiang
Affiliation:
Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan 410081, P. R. China
Yan-Fang Guo
Affiliation:
Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan 410081, P. R. China
Jing-Jing Guo
Affiliation:
Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan 410081, P. R. China
Yuan-Neng Li
Affiliation:
Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan 410081, P. R. China
Hui Jiang
Affiliation:
Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan 410081, P. R. China
Xue-Zhen Zhu
Affiliation:
The Key Laboratory of Biomedical Information Engineering of Ministry of Education and Institute of Molecular Genetics, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, P. R. China
Hong-Wen Deng*
Affiliation:
Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan 410081, P. R. China Department of Orthopedic Surgery, School of Medicine, University of Missouri-Kansas City, 2411 Holmes Street, Kansas City, MO 64108, USA
*
*Corresponding author: Dr Hong-Wen Deng, Hunan Normal University, fax +86 731 8872791, email [email protected]
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Abstract

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To increase our understanding of the relationships of trunk fat mass (FMtrunk) and four anthropometric indices in Chinese males, 1090 males aged 20–40 years were randomly recruited from the city of Changsha, China. Waist circumference (WC) and hip circumference (HC) were measured using standardized equipment, and three other anthropometric indices of BMI, waist:hip ratio (WHR) and conicity index (CoI) were calculated using weight, height, HC and WC. FMtrunk (in kg) was measured using a Hologic QDR 4500 W dual-energy X-ray absorptiometry scanner. There was an increasing trend of FMtrunk, %FMtrunk (percentage of FMtrunk) and BMI, WC, WHR, CoI in successively older age groups (e.g. the mean FMtrunk values were 4·63 (sd 2·58), 5·39 (sd 2·74), 5·93 (sd 2·82), 6·57 (sd 2·94) in four 5-year age groups, respectively). FMtrunk and %FMtrunk were significantly correlated with four anthropometric indices with the Pearson's correlation coefficients ranging from 0·25 to 0·86. Principal component analysis was performed to form three principal components that interpreted over 99·5% of the total variation of four related anthropometric indices in all age groups, with over 65% of the total variation accounted by principal component 1. Multiple regression analyses showed that three principal components explained a greater variance (R2 70·0–80·1%) in FMtrunk than did BMI or WC alone (R2 57·8–74·1%). The present results suggest that there is an increasing trend of FMtrunk and four anthropometric indices in successively older age groups; that age has important effects on the relationships of FMtrunk and studied anthropometric indices; and that the accuracy of predicting FMtrunk using four anthropometric indices is higher than using BMI or WC alone.

Keywords

Anthropometric indexTrunk fat massPercentage of trunk fat massPrincipal component analysis
Type
Research Article
Information
British Journal of Nutrition , Volume 96 , Issue 5 , November 2006 , pp. 949 - 955
Copyright
Copyright © The Nutrition Society 2006

References

Bertin, E, Marcus, C, Ruiz, JC, Eschard, JP & Leutenegger, M (2000) Measurement of visceral adipose tissue by DXA combined with anthropometry in obese humans. Int J Obes Relat Metab Disord 24, 263–270.Google Scholar
Bjorntorp, P (1996) The regulation of adipose tissue distribution in humans. Int J Obes Relat Metab Disord 20, 291–302.Google Scholar
Brambilla, P, Bedogni, G, Moreno, LA, Goran, MI, Gutin, B, Fox, KR, Peters, DM, Barbeau, P, Simone, MD & Pietrobelli, A (2006) Crossvalidation of anthropometry against magnetic resonance imaging for the assessment of visceral and subcutaneous adipose tissue in children. Int J Obes (Lond) 30, 23–30.CrossRefGoogle ScholarPubMed
Corpas, E, Harman, SM & Blackman, MR (1993) Human growth hormone and human aging. Endocr Rev 14, 20–39.Google Scholar
Deng, HW, Shen, H, Xu, FH, Deng, HY, Conway, T, Zhang, HT & Recker, RR (2002) Tests of linkage and/or association of genes for vitamin D receptor, osteocalcin, and parathyroid hormone with bone mineral density. J Bone Miner Res 17, 678–686.CrossRefGoogle ScholarPubMed
Deurenberg, P, Yap, M & van Staveren, WA (1998) Body mass index and percent body fat: a meta analysis among different ethnic groups. Int J Obes Relat Metab Disord 22, 1164–1171.Google Scholar
Duncan, E, Schofield, G, Duncan, S, Kolt, G & Rush, E (2004) Ethnicity and body fatness in New Zealanders. N Z Med J 117, U913.Google Scholar
Folsom, AR, Prineas, RJ, Kaye, SA & Munger, RG (1990) Incidence of hypertension and stroke in relation to body fat distribution and other risk factors in older women. Stroke 21, 701–706.Google Scholar
Freedman, DS, Jacobsen, SJ, Barboriak, JJ, Sobocinski, KA, Anderson, AJ, Kissebah, AH, Sasse, EA & Gruchow, HW (1990) Body fat distribution and male/female differences in lipids and lipoproteins. Circulation 81, 1498–1506.Google Scholar
Glickman, SG, Marn, CS, Supiano, MA & Dengel, DR (2004) Validity and reliability of dual-energy X-ray absorptiometry for the assessment of abdominal adiposity. J Appl Physiol 97, 509–514.Google Scholar
Goodpaster, BH, Krishnaswami, S, Harris, TB, Katsiaras, A, Kritchevsky, SB, Simonsick, EM, Nevitt, M, Holvoet, P & Newman, AB (2005) Obesity, regional body fat distribution, and the metabolic syndrome in older men and women. Arch Intern Med 165, 777–783.Google Scholar
Goran, MI, Gower, BA, Treuth, M & Nagy, TR (1998) Prediction of intra-abdominal and subcutaneous abdominal adipose tissue in healthy pre-pubertal children. Int J Obes Relat 22, 549–558.Google Scholar
Green, PE (1978) Analyzing Multivariate Data. Hinsdale, IL: The Dryden Press.Google Scholar
Han, TS, Kelly, IE, Walsh, K, Greene, RM & Lean, ME (1997) Relationship between volumes and areas from single transverse scans of intra-abdominal fat measured by magnetic resonance imaging. Int J Obes Relat Metab Disord 21, 1161–1166.CrossRefGoogle ScholarPubMed
Harman, SM & Blackman, MR (2004) Use of growth hormone for prevention or treatment of effects of aging. J Gerontol A Biol Sci Med Sci 59, 652–658.Google Scholar
Horber, FF, Gruber, B, Thomi, F, Jensen, EX & Jaeger, P (1997) Effect of sex and age on bone mass, body composition and fuel metabolism in humans. Nutrition 13, 524–534.Google Scholar
Jakicic, JM, Wing, RR & Lang, W (1998) Bioelectrical impedance analysis to assess body composition in obese adult women: effect of ethnicity. Int J Obes Relat Metab Disord 22, 243–249.CrossRefGoogle ScholarPubMed
James, WPT & Ralph, A (1999) New understanding in obesity research. Proc Nutr Soc 58, 385–393.Google Scholar
Janssen, I, Heymsfield, SB, Allison, DB, Kotler, DP & Ross, R (2002) Body mass index and waist circumference independently contribute to the prediction of nonabdominal, abdominal subcutaneous and visceral fat. Am J Clin Nutr 75, 683–688.Google Scholar
Jensen, MD, Kanaley, JA, Reed, JE & Sheedy, PF (1995) Measurement of abdominal and visceral fat with computed tomography and dual-energy x-ray absorptiometry. Am J Clin Nutr 61, 274–278.Google Scholar
Johannsson, G, Marin, P, Lonn, L, Ottosson, M, Stenlof, K, Bjorntorp, P, Sjostrom, L & Bengtsson, BA (1997) Growth hormone treatment of abdominally obese men reduces abdominal fat mass, improves glucose and lipoprotein metabolism, and reduces diastolic blood pressure. J Clin Endocrinol Metab 82, 727–734.Google Scholar
Kamel, EG, McNeill, G, Han, TS, Smith, FW, Avenell, A, Davidson, L & Tothill, P (1999) Measurement of abdominal fat by magnetic resonance imaging, dual-energy X-ray absorptiometry and anthropometry in non-obese men and women. Int J Obes Relat Metab Disord 23, 686–692.Google Scholar
Kamel, EG, McNeill, G & Van Wijk, MC (2000) Usefulness of anthropometry and DXA in predicting intra-abdominal fat in obese men and women. Obes Res 8, 36–42.Google Scholar
Kohrt, WM (1995) Body composition by DXA: tried and true?. Med Sci Sports Exerc 27, 1349–1353.CrossRefGoogle ScholarPubMed
Larsson, B, Bengtsson, C, Bjorntorp, P, Lapidus, L, Sjostrom, L, Svardsudd, K, Tibblin, G, Wedel, H, Welin, L & Wilhelmsen, L (1992) Is abdominal body fat distribution a major explanation for the sex difference in the incidence of myocardial infarction? The study of men born in 1913 and the study of women. Goteborg, Sweden. Am J Epidemiol 135, 266–273.Google Scholar
Lean, ME, Han, TS & Morrison, CE (1995) Waist circumference as a measure for indicating need for weight management. Br Med J 15, 158–161.Google Scholar
Lemieux, S, Prud'homme, D, Moorjani, S, Tremblay, A, Bouchard, C, Lupien, PJ & Despres, JP (1995) Do elevated levels of abdominal visceral adipose tissue contribute to age-related differences in plasma lipoprotein concentrations in men?. Atherosclerosis 118, 155–164.Google Scholar
Lindsay, RS, Hanson, RL, Roumain, J, Ravussin, E, Knowler, WC & Tataranni, PA (2001) Body mass index as a measure of adiposity in children and adolescents: relationship to adiposity by dual energy x-ray absorptiometry and to cardiovascular risk factors. J Clin Endocrinol Metab 86, 4061–4067.Google Scholar
McKeigue, PM, Pierpoint, T, Ferrie, JE & Marmot, MG (1992) Relationship of glucose intolerance and hyperinsulinemia to body fat pattern in South Asians and Europeans. Diabetologia 35, 785–791.Google Scholar
Mitchell, D, Haan, MN, Steinberg, FM & Visser, M (2003) Body composition in the elderly: the influence of nutritional factors and physical activity. J Nutr Health Aging 7, 130–139.Google Scholar
Parsons, TJ, Power, C & Manor, O (2005) Physical activity, television viewing and body mass index: a cross-sectional analysis from childhood to adulthood in the 1958 British cohort. Int J Obes (Lond) 29, 1212–1221.Google Scholar
Pi-Sunyer, FX (2004) The epidemiology of central fat distribution in relation to disease. Nutr Rev 62, S120–S126.Google Scholar
Rexrode, K, Carey, V, Hennekens, C, Walters, EE, Colditz, GA, Stampfer, MJ, Willett, WC & Manson, JE (1998) Abdominal adiposity and coronary heart disease in women. JAMA 280, 1843–1848.Google Scholar
Ross, R, Shaw, KD, Rissanen, J, Martel, Y, de Guise, J & Avruch, L (1994) Sex differences in lean and adipose tissue distribution by magnetic resonance imaging: anthropometric relationships. Am J Clin Nutr 59, 1277–1285.Google Scholar
Shimokata, H, Tobin, JD, Muller, DC, Elahi, D, Coon, PJ & Andres, R (1989) Studies in the distribution of body fat: I. Effects of age, sex and obesity. J Gerontol 44, M66–73.Google Scholar
Snijder, MB, Dekker, JM, Visser, M, Bouter, LM, Stehouwer, CD, Yudkin, JS, Heine, RJ, Nijpels, G, Seidell, JC & Hoorn, Study(2004) Trunk fat and leg fat have independent and opposite association with fasting and postload glucose levels. Diebetes Care 27, 372–377.Google Scholar
Svendsen, OL, Hassager, C, Bergmann, I & Christiansen, C (1993) Measurement of abdominal and intra-abdominal fat in postmenopausal women by dual energy X-ray absorptiometry and anthropometry: comparison with computerized tomography. Int J Obes Relat Metab Disord 17, 45–51.Google Scholar
Taylor, RW, Jones, IE, Williams, SM & Goulding, A (2000) Evaluation of waist circumference, waist-to-hip ratio, and the conicity index as screening tools for high trunk fat mass, as measured by dual-energy X-ray absorptiometry, in children aged 3–19 y. Am J Clin Nutr 72, 490–495.Google Scholar
Taylor, RW, Keil, D, Gold, EJ, Williams, SM & Goulding, A (1998) Body mass index, waist girth, and waist-to-hip ratio as indices of total and regional adiposity in women: evaluation using receiver operating characteristic curves. Am J Clin Nutr 67, 44–49.Google Scholar
Treuth, MS, Hunter, GR & Kekes-Szabo, K (1995) Estimating intraabdominal adipose tissue in women by dual energy X-ray absorptiometry. Am J Clin Nutr 62, 527–532.Google Scholar
Vague, J, Vague, P, Meignen, JM, Jubelin, J & Tramoni, M (1985) Android and gynoid obesities. Past and present. In Metabolic Complications of Human Obesities, pp. 3–11 [Vague, J, Bjorntorp, P, Guy Grand, B, Refuffe-Scrive, M and Vague, P, editors]. Amsterdam: Excerpta Medica.Google Scholar
Valdez, R, Seidell, JC, Ahn, YI & Weiss, KM (1993) A new index of abdominal adiposity as an indicator of risk for cardiovascular disease. A cross-population study. Int J Obes Relat Metab Disord 17, 77–82.Google Scholar
Van Pelt, RE, Evans, EM, Schechtman, KB, Ehsani, AA & Kohrt, WM (2002) Contributions of total and regional fat mass to risk for cardiovascular disease in older women. Am J Physiol Endocrinol Metab 282, E1023–E1028.Google Scholar
Vapnik, V (1998) Statistical Learning Theory. New York: Wiley.Google Scholar
Vickery, SR, Cureton, KJ & Collins, MA (1988) Prediction of body density from skinfolds in black and white yong men. Hum Biol 60, 135–149.Google Scholar
Zamboni, M, Armellini, F, Harris, T, Turcato, E, Micciolo, R, Bergamo-Andreis, IA & Bosello, O (1997) Effects of age on body fat distribution and cardiovascular riskfactors in women. Am J Clin Nutr 66, 111–115.Google Scholar