Hostname: page-component-78c5997874-m6dg7 Total loading time: 0 Render date: 2024-11-07T08:35:33.327Z Has data issue: false hasContentIssue false
  • English
  • Français

Laboratory and field measurements of body composition

Published online by Cambridge University Press:  02 January 2007

NG Norgan
NG Norgan*
Affiliation:
Department of Human Sciences, Loughborough University, Loughborough, LE11 3TU, UK
*
*Corresponding author: Email [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
Objective

This background paper was prepared in response to a request to review the concepts related to measurement of body composition, to discuss laboratory and field methods of assessing body composition and to discuss the practical applications of the methods – how they might be used singly or in combination to provide data for a selected population.

Design

The common laboratory and field methods are described and discussed, with particular attention to the assumptions involved and the applicability of the methods to the different population groups. Most measurements of body composition are made in the field, at the bedside or clinic as opposed to in the laboratory. The laboratory methods have a role to play in their own right, in research into new concepts, models and methods. However, they are particularly important in establishing the accuracy of the field methods.

Setting

Field, bedside and laboratory studies.

Subjects

Children, adults, the elderly, ethnic groups.

Results

Laboratory estimates of body compositions are best performed by multi-component methods or by 2-component methods adjusted for to the populations under investigation. There is a scarcity of data for most of the populations in the world.

Conclusions

Energy requirements based on body weight are an approximation since they do not take into account differences in body composition, which will better determine the true requirements. The measurement of body composition occurs in many branches of biology and medicine. It is used in the assessment of nutritional and growth status and in disease states and their treatment. Energy stores, skeletal muscle and protein content can be determined and changes monitored. In human energetics, body composition is widely used for the standardisation of other variables, such as basal metabolic rate (BMR), in the assessments of ethnic and environmental differences and of variability and adaptation to different levels of nutrition. Choosing a method is very problematic. Users want simple, inexpensive, rapid, safe accurate methods to measure body composition but speed and simplicity come at the expense of accuracy. Recommendations are made for age, sex, and in some cases, fatness and ethnic specific methods.

Keywords

Body compositionAnthropometryChildrenAdultsElderlyEthnicity
Type
Research Article
Information
Public Health Nutrition , Volume 8 , Issue 7a , October 2005 , pp. 1108 - 1122
Copyright
Copyright © The Author 2005

References

1Lohman, TG. Advances in Body Composition Assessment. Champaign, Illinois: Human Kinetics Publications, 1992.Google Scholar
2Wang, ZM, Pierson, RN, Heymsfield, SB. The five-level model: a new approach to organizing body-composition research. American Journal of Clinical Nutrition 1992; 56: 19–28.CrossRefGoogle Scholar
3Wang, ZM, Heshka, S, Pierson, RN, Heymsfield, SB. Systematic organization of body-composition methodology: an overview with emphasis on component-based methods. American Journal of Clinical Nutrition 1995; 61: 457–65.CrossRefGoogle ScholarPubMed
4Keys, A, Brozek, J. Body fat in adult man. Physiological Reviews 1953; 33: 245–345.CrossRefGoogle ScholarPubMed
5Brozek, J. Body composition parts I and II. Annals of the New York Academy of Sciences 1963; 110: 1–1018.Google Scholar
6Brozek, J. Human Body Composition: Approaches and Applications. Oxford: Pergamon Press, 1965.Google Scholar
7Behnke, AR, Wilmore, JK. Evaluation and Regulation of Body Build and Composition. Englewood Cliffs: Prentice-Hall Inc, 1974.Google Scholar
8Lukaski, HC. Methods for the assessment of human body composition: new and traditional. American Journal of Clinical Nutrition 1987; 46: 537–56.Google Scholar
9Forbes, GB. Human Body Composition: Growth, Aging, Nutrition, and Activity. New York: Springer-Verlag, 1987.Google Scholar
10Coward, WA, Parkinson, SS, Murgatroyd, PR. Body composition measurements for nutrition research. Nutrition Research Reviews 1998; 1: 115–24.CrossRefGoogle Scholar
11Elia, M. Body composition analysis: an evaluation of 2 component models, multicomponent models and bedside techniques. Clinical Nutrition 1992; 11: 114–27.CrossRefGoogle ScholarPubMed
12Jebb, SA, Elia, M. Techniques for the measurement of body composition: a practical guide. International Journal of Obesity 1993; 17: 611–21.Google Scholar
13Davies, PSW, Cole, TJ. Body Composition Techniques in Health and Disease. Cambridge: Cambridge University Press, 1995.CrossRefGoogle Scholar
14Roche, AF, Heymsfield, SB, Lohman, TG. Human Body Composition. Champaign, Illinois: Human Kinetics, 1996.Google Scholar
15Heyward, VH, Stolarczyk, LM. Applied Body Composition Assessment. Champaign, Illinois: Human Kinetics, 1996.Google Scholar
16Norton, K, Olds, T. Anthropometrica. Sydney: UNSW Press, 1966.Google Scholar
17Heymsfield, SB, Wang, ZM, Withers, RT. Multicomponent molecular level models of body composition analysis. In: Roche, AF, Heymsfield, SB, Lohman, TG, eds. Human Body Composition. Champaign, Illinois: Human Kinetics, 1996, 129–47.Google Scholar
18Yasmura, S, Wang, J, Pierson, RN Jr, eds. In vivo body composition studies. Annals of the New York Academy of Sciences 2000; 904: 1–631.Google Scholar
19Lohman, TG, Harris, M, Teixeira, PJ, Weiss, L. Assessing body composition and changes in body composition. Another look at dual-energy X-ray absorptiometry. Annals of the New York Academy of Sciences 2000; 904: 45–54.CrossRefGoogle Scholar
20Ellis, KJ. Human body composition: in vivo methods. Physiological Reviews 2000; 80(2): 649–80.CrossRefGoogle ScholarPubMed
21FAO/WHO/UNU. Energy and Protein Requirements. Geneva: World Health Organization, 1985.Google Scholar
22Schofield, WN, Schofield, C, James, WPT. Basal metabolic rate-review and prediction, together with an annotated bibliography of source material. Human Nutrition Clinical Nutrition 1985; 39C: 1–96.Google Scholar
23Cunningham, JJ. A reanalysis of the factors influencing basal metabolic rate in normal adults. American Journal of Clinical Nutrition 1980; 33: 2372–4.CrossRefGoogle ScholarPubMed
24Garby, L, Garrow, JS, Jorgensen, B, Lammert, O, Madsen, K, Sorensen, P, Webster, J. Relation between energy expenditure and body composition in man: specific energy expenditure in vivo of fat and fat-free tissue. European Journal of Clinical Nutrition 1988; 42: 301–5.Google Scholar
25Garby, L, Lammert, O. An explanation for the non-linearity of the relation between energy expenditure and fat-free mass. European Journal of Clinical Nutrition 1992; 46: 235–6.Google ScholarPubMed
26Weinsier, RL, Schutz, Y, Braco, D. Re-examination of the relationship of resting metabolic rate to fat-free mass and to the metabolically active compartment. American Journal of Clinical Nutrition 1992; 55: 790–4.Google Scholar
27Garby, L, Lammert, O. Between-subject variation in energy expenditure: estimation of the effect of variation in organ size. European Journal of Clinical Nutrition 1994; 48(Suppl.): 376–8.Google Scholar
28Gallagher, D, Visser, M, Wang, Z, Harris, T, Pierson, RN, Heymsfield, SB. Metabolically active component of fat-free body mass: influence of age, adiposity, and gender. Metabolism 1996; 45: 927–92.CrossRefGoogle ScholarPubMed
29Gallagher, D, Belmonte, D, Deurenberg, P, Wang, Z, Krasnow, N, Pi-Sunyer, FX, Heymsfield, SB. Organ-tissue mass measurement allows modeling of REE and metabolically active tissue mass. American Journal of Physiology 1998; 275: E258.Google ScholarPubMed
30Poehlman, ET, Berke, EM, Joseph, JR, Gardener, AW, Katzman-Rooks, SM, Goran, MI. Influence of aerobic capacity, body composition, and thyroid hormones on the age-related decline in resting metabolic rate. Metabolism 1992; 41: 915–21.Google Scholar
31Hunter, GR, Weinsier, RL, Darnell, BE, Zuckerman, PA, Goran, MI. Racial differences in energy expenditure and aerobic fitness in premenopausal women. American Journal of Clinical Nutrition 2000; 71: 500–6.CrossRefGoogle ScholarPubMed
32Gallagher, D, Heymsfield, SB, Heo, M, Jebb, SA, Murgatroyd, PR, Sakamoto, Y. Healthy percentage body fat ranges: an approach for developing guidelines based on body mass index. American Journal of Clinical Nutrition 2000; 72: 694–701.CrossRefGoogle ScholarPubMed
33Henry, CJK, Rees, DG. New predictive equations for the estimation of basal metabolic rate in tropical peoples. European Journal of Clinical Nutrition 1991; 45: 177–85.Google ScholarPubMed
34Lawrence, M, Thongprasert, K, Durnin, JVGA. Between-group differences in basal metabolic rates: an analysis of data collected in Scotland. The Gambia and Thailand. European Journal of Clinical Nutrition 1988; 42: 877–91.Google ScholarPubMed
35Soares, MJ, Francis, DG, Shetty, PS. Predictive equations for basal metabolic rates of Indian males. European Journal of Clinical Nutrition 1993; 47: 389–94.Google ScholarPubMed
36Soares, MJ, Piers, LS, O'Dea, K, Shetty, PS. No evidence for an ethnic influence on basal metabolism: an examination of data from India and Australia. British Journal of Nutrition 1998; 79: 333–41.Google Scholar
37Wong, WW, Butte, NF, Ellis, KJ, Hergenroeder, AC, Hill, RB, Stuff, JE, Smith, EO. Pubertal African-American girls expend less energy at rest and during physical activity than Caucasian girls. Journal of Clinical Endocrinology and Metabolism 1999; 84: 906–11.Google Scholar
38Gannon, B, Dipietro, L, Poehlman, ET. Do African Americans have lower energy expenditure than Caucasians? International Journal of Obesity 2000; 24: 4–13.Google Scholar
39Yanovski, JA. Resting energy expenditure in African American and white children. American Journal of Clinical Nutrition 2001; 73: 149–50.CrossRefGoogle ScholarPubMed
40Schofield, WN. Predicting basal metabolic rate; new standards and review of previous work. Human Nutrition Clinical Nutrition 1985; 39C: 5–41.Google Scholar
41Livesey, G, Elia, M. Estimation of energy expenditure, net carbohydrate utilization, and net fat oxidation and synthesis by indirect calorimetry: evaluation of errors with special reference to the detailed composition of fuels. American Journal of Clinical Nutrition 1988; 47: 608–28.CrossRefGoogle Scholar
42Sutcliffe, JF, Knight, GS, Pinilla, JC, Hill, JC. New and simple equations to estimate the energy and fat contents and energy density of humans in sickness and health. British Journal of Nutrition 1993; 69: 631–44.CrossRefGoogle Scholar
43Siri, WE. Body composition from fluid spaces and density: analysis of methods. In: Brozek, J, Henschel, A, eds. Techniques for Measuring Body Composition. Washington, DC: National Academy of Sciences, National Research Council, 1961, 223–80.Google Scholar
44Norgan, NG. In: Fidanza, F, ed. Nutritional Status Assessment: A Manual for Population Studies. London: Chapman and Hall, 1991, 64–70.Google Scholar
45Going, SB. Densitometry. In: Roche, AF, Heymsfield, SB, Lohman, TG, eds. Human Body Composition. Champaign, Illinois: Human Kinetics, 1996, 3–23.Google Scholar
46McCrory, MA, Gomez, TD, Bernauer, EM, Mole, PA. Evaluation of a new air displacement plethysmograph for measuring human body composition. Medicine and Science in Sports and Exercise 1995; 27: 1686–91.CrossRefGoogle ScholarPubMed
47Fields, DA, Hunter, GR, Goran, MI. Validation of the BOD POD with hydrostatic weighing: influence of body clothing. International Journal of Obesity and Related Metabolic Disorders 2000; 24: 200–5.CrossRefGoogle ScholarPubMed
48Higgins, PB, Fields, DA, Hunter, GR, Gower, BA. Effect of scalp and facial hair on air displacement plethysmography estimates of percentage of body fat. Obesity Research 2001; 9: 326–30.Google Scholar
49Wells, JCK, Fuller, NJ. Precision of measurement and body size in whole-body air-displacement plethysmography. International Journal of Obesity 2001; 25: 1161–7.CrossRefGoogle ScholarPubMed
50Du Bois, D, Du Bois, EF. A formula to estimate the approximate surface area if height and weight be known. Archives of Internal Medicine 1916; 17: 863–71.CrossRefGoogle Scholar
51Fogelholm, M, van Marken, L. Comparison of body composition methods: a literature analysis. European Journal of Clinical Nutrition 1997; 51: 495–503.CrossRefGoogle ScholarPubMed
52Schoeller, DA. Hydrometry. In: Roche, AF, Heymsfield, SB, Lohman, TG, eds. Human Body Composition. Champaign, Illinois: Human Kinetics, 1996, 25–44.Google Scholar
53Lohman, TG. Dual energy X-ray absorptiometry. In: Roche, AF, Heymsfield, SB, Lohman, TG, eds. Human Body Composition. Champaign, Illinois: Human Kinetics, 1996, 63–78.Google Scholar
54Roubenoff, R, Kehsyias, JJ, Dawson-Hughes, B, Heymsfield, SB. Use of dual-energy X-ray absorptiometry in body composition studies: not yet a gold standard. American Journal of Clinical Nutrition 1993; 58: 589–91.Google Scholar
55Jebb, SA. Measurement of soft tissue composition by dual energy X-ray absorptiometry: a review. British Journal of Nutrition 1997; 77: 151–63.Google Scholar
56Modlesky, CM, Evans, EM, Millard-Stafford, ML, Collins, MA, Lewis, RD, Cureton, KJ. Impact of bone mineral estimates on percent fat estimates from a four-component model. Medicine and Science in Sports and Exercise 1999; 31: 1861–8.Google Scholar
57Despres, J-P, Ross, R, Lemieux, S. Imaging techniques applied to the measurement of body composition. In: Roche, AF, Heymsfield, SB, Lohman, TG, eds. Human Body Composition. Champaign, Illinois: Human Kinetics, 1996, 149–66.Google Scholar
58van der Kooy, K, Seidell, JC. Techniques for measurement of visceral fat: a practical guide. International Journal of Obesity 1993;17: 187–96.Google Scholar
59Ross, R, Goodpaster, B, Kelley, D, Boeing, H. Magnetic resonance imaging in human body composition research: from quantitative to qualitative tissue measurement. New York Academy of Sciences 2000; 904: 12–17.Google Scholar
60Elia, M, Fuller, NJ, Hardingham, CR, Graves, M, Screaton, N, Dixon, AK, Ward, LC. Modeling leg sections by bioelectrical impedance analysis, dual energy X-ray absorptiometry, and anthropometry: assessing skeletal muscle volume using magnetic resonance imaging as a reference. Annals of the New York Academy of Sciences 2000; 904: 298–305.Google Scholar
61Lee, RC, Wang, Z-M, Heo, M, Ross, R, Janssen, I, Heymsfield, SB. Total body skeletal muscle mass: development and cross-validation of anthropometric prediction models. American Journal of Clinical Nutrition 2000; 72: 796–803.Google Scholar
62Shih, R, Wang, Z, Heo, M, Wang, W, Heymsfield, SB. Lower limb skeletal muscle mass: development of dual-energy X-ray absorptiometry prediction model. Journal of Applied Physiology 2000; 89: 1380–6.Google Scholar
63Mitsiopoulos, N, Baumgartner, RN, Heymsfield, SB, Lyons, W, Gallagher, D, Ross, RK. Cadaver validation of skeletal muscle measurement by magnetic resonance imaging and computerized tomography. Journal of Applied Physiology 1998; 85: 115–22.Google Scholar
64Fuller, NJ, Hardingham, CR, Graves, M, Screaton, N, Dixon, AK, Ward, LC, Elia, M. Assessment of limb muscle and adipose tissue by dual-energy X-ray absorptiometry using magnetic resonance imaging for comparison. International Journal of Obesity 1999; 23: 1295–302.CrossRefGoogle ScholarPubMed
65Baumgartner, RN. Electrical impedance and total body electrical conductivity. In: Roche, AF, Heymsfield, SB, Lohman, TG, eds. Human Body Composition. Champaign, Illinois: Human Kinetics, 1996, 79–108.Google Scholar
66Ramirez, ME. Measurement of subcutaneous adipose tissue using ultrasound images. American Journal of Physical Anthropology. 1992; 89: 347–57.CrossRefGoogle ScholarPubMed
67Edholm, OG, Adams, JM, Best, TW. Day-to-day weight changes in young men. Annals of Human Biology 1974; 1: 3–12.Google Scholar
68Shetty, PS, James, WPT. Body Mass Index: A measure of chronic energy deficiency in adults. FAO Food and Nutrition Paper No. 56. Rome: Food and Agricultural Organization, 1994.Google Scholar
69WHO. Physical Status: The Use and Interpretation of Anthropometry. WHO Technical Report Series No. 854 Geneva: World Health Organization, 1995.Google Scholar
70Deurenberg, P, Weststrate, JA, Seidell, JC. Body mass index as a measure of body fatness: age- and sex-specific prediction formulas. British Journal of Nutrition 1991; 65: 105–14.CrossRefGoogle ScholarPubMed
71Norgan, NG. Body mass index and body energy stores in developing countries. European Journal of Clinical Nutrition 1990; 44: 79–84.Google ScholarPubMed
72Norgan, NG. Population differences in body composition in relation to the body mass index. European Journal of Clinical Nutrition 1994; 48: S10–27.Google ScholarPubMed
73Gallagher, D, Visser, M, Sepulveda, D, Pierson, RN, Harris, T, Heymsfield, SB. How useful is body mass index for comparison of body fatness across age, sex, and ethnic groups? American Journal of Epidemiology 1996; 143: 228–39.Google Scholar
74Deurenberg, P, Deurenberg-Yap, M, Wang, J, Lin, FP, Schmidt, G. The impact of body build on the relationship between body mass index and percent body fat. International Journal of Obesity 1999; 23: 537–42.CrossRefGoogle ScholarPubMed
75James, WPT, Mascie-Taylor, GCN, Norgan, NG, Bistrian, BR, Shetty, PS, Ferro-Luzzi, A. The value of arm circumference measurements in assessing chronic energy deficiency in third world adults. European Journal of Clinical Nutrition 1994; 48: 883–94.Google Scholar
76Oppliger, RA, Spray, JA. Skinfold measurement variability in body density prediction. Research Quarterly in Exercise and Sports 1987; 58: 178–83.CrossRefGoogle Scholar
77Heyward, VH. Practical body composition assessment for children, adults, and older adults. International Journal of Sports Nutrition 1998; 8: 285–307.Google Scholar
78Norgan, NG, Ferro-Luzzi, A, The estimation of body density in men: Are general equations general?. Annals of Human Biology 1985; 12: 1–15.CrossRefGoogle ScholarPubMed
79Guo, SS, Chumlea, WC. Statistical methods for the development and testing of predictive equations. In: Roche, AF, Heymsfield, SB, Lohman, TG, eds. Human Body Composition. Champaign, Illinois: Human Kinetics, 1996, 191–202.Google Scholar
80Durnin, JVGA, Womersley, J, Body fat assessed from total body density and its estimation from skinfold thicknesses: measurements on 481 men and women from 16 to 72 years. British Journal of Nutrition 1974; 32: 77–97.Google Scholar
81Fuller, NJ, Jebb, SA, Laskey, MA, Coward, WA, Elia, M. Four component model for the assessment of body composition in humans: comparison with the alternative methods, and evaluation of density and hydration of fat-free mass. Clinical Science 1992; 82: 687–93.CrossRefGoogle ScholarPubMed
82Segal, KR, Van Loan, MD, Fitzgerald, PI, Hodgdon, JA, Van Itallie, TB. Lean body mass estimation by bioelectrical impedance analysis: a four site cross-validation study. American Journal of Clinical Nutrition 1988; 47: 7–14.Google Scholar
83Deurenberg, P, Westerterp, KR, Velhuis-Te Wierk, EJM. Between-laboratory comparison of densitometry and bio-electrical impedance measurements. British Journal of Nutrition 1994; 71: 309–16.CrossRefGoogle ScholarPubMed
84Jebb, SA, Cole, TJ, Doman, D, Murgatroyd, PR, Prentice, AM. Evaluation of the novel Tanita body-fat analyser to measure body composition by comparison with a four-component model. British Journal of Nutrition 2000; 83: 115–22.Google Scholar
85Yanovski, JA, Hubbard, VS, Heymsfield, SB, Lukaski, HC. Bioelectrical impedance analysis. American Journal of Clinical Nutrition 1996; 64: 387S–532S.Google Scholar
86Ellis, KJ, Bell, SJ, Chertow, GM, Chumlea, WC, Knox, TA, Kotler, DP, Lukaski, HC, Schoeller, DA. Bioelectrical impedance methods in clinical research: a follow-up to the NIH Technology Assessment Conference. Nutrition 1999; 15: 874–80.Google Scholar
87Pichard, C, Kyle, UG, Bracco, D, Slosman, DO, Morabia, A, Schutz, Y. Reference values of fat-free masses by electrical impedance analysis in 3393 health subjects. Nutrition 2000; 16: 245–54.Google Scholar
88De Lorenzo, A, Andreoli, A, Matthie, J, Withers, P. Predicting body cell mass with bioimpedance by using theoretical methods: a technological review. Journal of Applied Physiology 1997; 82: 1542–58.Google Scholar
89Gudivaka, R, Schoeller, DA, Kushner, RF, Bolt, MJG. Single- and multifrequency models for bioelectrical impedance analysis of body water compartments. Journal of Applied Physiology 1999; 87: 1087–96.CrossRefGoogle ScholarPubMed
90Kyle, UG, Genton, L, Karsegard, L, Slosman, DO, Pichard, C. Single prediction equation for bioelectrical impedance analysis in adults aged 20–94 years. Nutrition 2001; 17: 248–53.CrossRefGoogle ScholarPubMed
91Stolarczyk, LM, Heyward, VH, Van, LM, Hicks, VL, Wilson, WL, Reano, LM. The fatness-specific bioelectrical impedance analysis equations of Segal et al. are they generalizable and practical? American Journal of Clinical Nutrition 1997; 66: 8–17.Google Scholar
92Chumlea, WC, Baumgartner, RN, Roche, AF. Specific resistivity used to estimate fat-free mass from segmental body measures of bioelectric impedance. American Journal of Clinical Nutrition 1988; 48: 7–15.CrossRefGoogle ScholarPubMed
93Organ, LW, Bradham, GB, Gore, DT, Lozier, SL. Segmental bioelectrical impedance analysis: theory and application of a new technique. Journal of Applied Physiology 1994; 77: 98–112.CrossRefGoogle ScholarPubMed
94Heymsfield, SB, Gallagher, D, Grammes, J, Nunez, C, Wang, J, Pietrobelli, A. Upper extremity muscle mass: potential of measurement with single frequency bioimpedance analysis. Applied radiation and Isotopes 1998; 49: 473–4.Google Scholar
95Pietrobelli, A, Morrison, CE, Battistini, N, Chiumello, G, Nunez, C, Heymsfield, SB. Appendicular skeletal muscle mass: prediction from multiple frequency segmental bioimpedance analysis. European Journal of Clinical Nutrition 1998; 52: 507–11.Google Scholar
96Nunez, C, Gallagher, D, Grammes, J, Baumgartner, RN, Ross, R, Wang, J, Thornton, JC, Heymsfield, SB. Bioimpedance analysis: potential for measuring lower limb skeletal muscle mass. Journal of Parenteral and Enteral Nutrition 1999; 23: 96–103.Google Scholar
97Janssen, I, Heymsfield, SB, Baumgartner, RN, Ross, R. Estimation of skeletal muscle mass by bioelectrical impedance analysis. Journal of Applied Physiology 2000; 89: 465–71.Google Scholar
98Lukaski, HC. Estimation of muscle mass. In: Roche, AF, Heymsfield, SB, Lohman, TG, eds. Human Body Composition. Champaign, Illinois: Human Kinetics, 1996, 109–28.Google Scholar
99Jebb, SA, Murgatroyd, PR, Goldberg, GR, Prentice, AM, Coward, WA. In vivo measurements of changes in body composition: description of methods and their validation against 12-d continuous whole-body calorimetry. American Journal of Clinical Nutrition 1993; 58: 455–62.CrossRefGoogle ScholarPubMed
100Forbes, GB, Simon, W, Amatruda, JM. Is bioimpedance a good predictor of body-composition change? American Journal of Clinical Nutrition 1992; 56: 4–6.Google Scholar
101Macbeth, H. Defining an ethnic group: important and impossible. In: Macbeth, H, Shetty, P, eds. Health and Ethnicity. London: Taylor and Francis, 2001, 1–20.Google Scholar
102Bhopal, R. Ethnicity and race as epidemiological variables: centrality of purpose and context. In: Macbeth, H, Shetty, P, eds. Health and Ethnicity. London: Taylor and Francis, 2001, 21–40.Google Scholar
103McKenzie, K, Crowcroft, NS. Describing race, ethnicity and culture in medical research. British Medical Journal 1996; 312: 1054.CrossRefGoogle ScholarPubMed
104Anonymous. Style matters: ethnicity, race and culture; guidelines for research, audit and publication. British Medical Journal 1996; 312: 1094.CrossRefGoogle Scholar
105Wagner, DR, Heyward, VH. Measures of body composition in blacks and whites: a comparative review. American Journal of Clinical Nutrition 2000; 71: 1392–402.Google Scholar
106Ortiz, O, Russell, M, Daley, TL, Baumgartner, RN, Waki, M, Lichtman, S, Wang, J, Pierson, RNJ, Heymsfield, SB. Differences in skeletal muscle and bone mineral mass between black and white females and their relevance to estimates of body composition. American Journal of Clinical Nutrition 1992; 55: 8–13.Google Scholar
107Visser, M, Gallagher, D, Deurenberg, P, Wang, J, Pierson, RNJ, Heymsfield, SB. Density of fat-free body mass: relationship with race, age, and level of body fatness. American Journal of Physiology. 1997; 272: E781–7.Google ScholarPubMed
108Werkman, A, Deurenberg-Yap, M, Schmidt, G, Deurenberg, P. A Comparison between Composition and Density of the Fat-Free Mass of Young Adult Singaporean Chinese and Dutch Caucasians. Annals of Nutrition and Metabolism 2000; 44: 235–42.Google Scholar
109Deurenberg-Yap, M, Schmidt, G, van Staveren, WA, Hautvast, JG, Deurenberg, P. Body fat measurement among Singaporean Chinese, Malays and Indians: a comparative study using a four-compartment model and different two-compartment models. British Journal of Nutrition 2001; 85: 491–8.Google Scholar
110Norgan, NG. The assessment of the body composition of populations. In: Davies, PSW, Cole, TJ, eds. Body Composition in Health and Disease. Cambridge: Cambridge University Press, 1995, 195–221.CrossRefGoogle Scholar
111Deurenberg, P, Ge, K, Hautvast, JG, Wang, J. BMI as predictor for body fat: comparison between Chinese and Dutch adult subjects. Asia Pacific Journal of Clinical Nutrition 1997; 6: 102–5.Google Scholar
112Deurenberg, P, Yap, M, van Staveren, WA. Body mass index and percent body fat: a meta-analysis among different ethnic groups. International Journal of Obesity and Related Metabolic Disorders 1998; 22: 1164–71.Google Scholar
113Wang, J, Thornton, JC, Russell, M, Burastero, S, Heymsfield, S, Pierson, RN. Asians have lower body mass index (BMI) but higher percent body fat than do whites: comparisons of anthropometric measurements. American Journal of Clinical Nutrition 1994; 60: 23–8.Google Scholar
114Luke, A, Durazo-Arvizu, R, Rotimi, C, Prewitt, TE, Forrester, T, Wilks, R, Ogunbiyi, OJ, Schoeller, DA, McGee, D, Cooper, RS. Relation between body mass index and body fat in black population samples from Nigeria, Jamaica, and the United States. American Journal of Epidemiology 1997; 145: 620–8.Google Scholar
115Rush, EC, Plank, LD, Laulu, MS, Robinson, SM. Prediction of percentage body fat from anthropometric measurements: comparison of New Zealand European and Polynesian young women. American Journal of Clinical Nutrition 1997; 66: 2–7.Google Scholar
116Gurrici, S, Hartriyanti, Y, Hautvast, JG, Deurenberg, P. Relationship between body fat and body mass index: differences between Indonesians and Dutch Caucasians. European Journal of Clinical Nutrition 1998; 52: 779–83.Google Scholar
117Gurrici, S, Hartriyanti, Y, Hautvast, JG, Deurenberg, P. Differences in the relationship between body fat and body mass index between two different Indonesian ethnic groups: the effect of body build. European Journal of Clinical Nutrition 1999; 53: 468–72.Google Scholar
118Gallagher, D, Allen, A, Wang, Z, Heymsfield, SB, Krasnow, N. Smaller organ tissue mass in the elderly fails to explain lower resting metabolic rate. Annals of the New York Academy of Sciences 2000; 904: 449–55.Google Scholar
119Kuriyan, R, Petracchi, C, Ferro-Luzzi, A, Shetty, PS, Kurpad, AV. Validation of expedient methods for measuring body composition in Indian adults. Indian Journal of Medical Research 1998; 107: 37–45.Google Scholar
120Deurenberg, P, Deurenberg-Yap, M, Wang, J, Lin, FP, Schmidt, G. Prediction of percentage body fat from anthropometry and bioelectrical impedance in Singaporean and Beijing Chinese. Asia Pacific Journal of Clinical Nutrition 2000; 9: 93–8.CrossRefGoogle ScholarPubMed
121Irwin, ML, Ainsworth, BE, Stolarczyk, LM, Heyward, VH. Predictive accuracy of skinfold equations for estimating body density of African-American women. Medicine and Science of Sports and Exercise 1998; 30: 1654–8.Google Scholar
122Jackson, AS, Pollock, ML. Generalized equations for predicting body density of men. British Journal of Nutrition 1978; 40: 497–504.CrossRefGoogle ScholarPubMed
123Jackson, AS, Pollock, ML, Ward, A. Generalized equations for predicting body density of women. Medicine and Science in Sports and Exercise 1980; 12: 175–82.CrossRefGoogle ScholarPubMed
124Brandon, LJ. Comparison of existing skinfold equations for estimating body fat in African-American and white women. American Journal of Clinical Nutrition 1998; 67: 1155–61.Google Scholar
125Wong, WW, Stuff, JE, Butte, NF, Smith, EO, Ellis, KJ. Estimation of body fat in Caucasian and African-American girls: total-body electrical conductivity methodology versus a four-component model. International Journal of Obesity and Related Metabolic Disorders 2000; 24: 1200–6.Google Scholar
126Slaughter, MH, Lohman, TG, Boileau, RA, Horswill, CA, Stillman, RJ, Van, LM, Bemben, DA. Skinfold equations for estimation of body fatness in children and youth. Human Biology 1988; 60: 709–23.Google Scholar
127Wang, J, Thornton, JC, Kolesnik, S, Pierson, RN. Anthropometry in body composition. An overview. Annals of the New York Academy of Sciences 2000; 904: 317–26.Google Scholar
128Stolarczyk, LM, Heyward, VH, Goodman, JA, Grant, DJ, Kessler, KL, Kocina, PS, Wilmerding, V. Predictive accuracy of bioimpedance equations in estimating fat-free mass of Hispanic women. Medicine and Science of Sports Exercise 1995; 27: 1450–6.Google Scholar
129Swinburn, BA, Craig, PL, Daniel, R, Dent, DP, Strauss, BJ. Body composition differences between Polynesians and Caucasians assessed by bioelectrical impedance. International Journal of Obesity and Related Metabolic Disorders 1996; 20: 889–94.Google Scholar
130Swinburn, BA, Ley, SJ, Carmichael, HE, Plank, LD. Body size and composition in Polynesians. International Journal of Obesity and Related Metabolic Disorders 1999; 23: 1178–83.Google Scholar
131Heitmann, BL, Swinburn, BA, Carmichael, H, Rowley, K, Plank, L, McDermott, R, Leonard, D, O'Dea, K. Are there ethnic differences in the association between body weight and resistance, measured by bioelectrical impedance?. International Journal of Obesity and Related Metabolic Disorders 1997; 21: 1085–92.Google Scholar
132Morrison, JA, Barton, BA, Obarzanek, E, Crawford, PB, Guo, SS, Schreiber, GB. Racial differences in the sums of skinfolds and percentage of body fat estimated from impedance in black and white girls, 9 to 19 years of age: the National Heart, Lung, and Blood Institute Growth and Health Study. Obesity Research 2001; 9: 297–305.Google Scholar
133Jakicic, JM, Wing, RR, Lang, W. Bioelectrical impedance analysis to assess body composition in obese adult women: the effect of ethnicity. International Journal of Obesity 1998; 22: 243–9.Google Scholar
134Snijder, MB, Kuyf, BE, Deurenberg, P. Effect of body build on the validity of predicted body fat from body mass index and bioelectrical impedance. Annals of Nutrition and Metabolism 1999;43: 277–85.Google Scholar
135Kushner, RF. Bioelectrical impedance analysis: a review of principles and applications. Journal of the American College of Nutrition 1992; 11: 199–209.Google Scholar
136Houtkooper, LB, Going, SB, Lohman, TG, Roche, AF, Van Loan, MD. Bioelectrical impedance estimation of fat-free body mass in children and youth: a cross-validation study. Journal of Applied Physiology 1992; 72: 366–73.CrossRefGoogle ScholarPubMed
137Morrison, JA, Guo, SS, Specker, B, Chumlea, WC, Yanovski, SZ, Yanovski, JA. Assessing the body composition of 6–17-year-old Black and White girls in field studies. American Journal of Human Biology 2001; 13: 249–54.Google Scholar
138Williams, DP, Going, SB, Lohman, TG, Hewitt, MJ, Haber, AE. Estimation of body fat from skinfold thicknesses in middle-aged and older men and women: a multiple component approach. American Journal of Human Biology 1992; 4: 595–605.Google Scholar
139Baumgartner, RN, Heymsfield, SB, Lichtman, S, Wang, J, Pierson, RNJ. Body composition in elderly people: effect of criterion estimates on predictive equations. American Journal of Clinical Nutrition 1991; 53: 1345–53.Google Scholar
140Fuller, NJ, Sawyer, MB, Laskey, MA, Paxton, P, Elia, M. Prediction of body composition in elderly men over 75 years of age. Annals of Human Biology 1996; 23: 127–47.Google Scholar