Abstract
Background:
Recent studies indicate differences between British and American white adults, and between income and ethnic groups within the United States, in the population distribution of lifestyle diseases. Differential prevalence of obesity has been suggested as a contributing factor; however, the conventional approach to categorizing obesity, body mass index, is confounded by ethnic variability in physique.
Objective:
To compare indices of shape between white British and American adults, and between white, African and Hispanic American adults.
Design:
Analysis of two large National Sizing Surveys, using identical study design and three-dimensional (3D) body-scanning instrumentation, on adults aged 17+ years from the UK (3907M and 4710F white), and from the USA (1744M and 3329F white, 709M and 1106F African and 639M and 839F Hispanic).
Outcome measures:
Weight, height, body circumferences.
Results:
In the United States, socio-economic status was associated with increasing height and decreasing waist girth in white and Hispanic, but not African Americans. Compared to white British, white Americans had larger weight and girths, especially waist girth in men. Relative to white Americans, African Americans had smaller relative waist girth, but larger thigh girth, whereas Hispanic Americans had larger relative waist girth.
Conclusions:
Body shape of white American adults differs from that of their UK counterparts. Within Americans, ethnic differences in body shape closely track reported differences in prevalence of the metabolic syndrome, implicating variability in central abdominal fat as a key contributing factor. 3D photonic scanning offers a novel approach for categorizing risk of the metabolic syndrome and monitoring treatment success.
This is a preview of subscription content, access via your institution
Access options
Subscribe to this journal
Receive 12 print issues and online access
$259.00 per year
only $21.58 per issue
Buy this article
- Purchase on Springer Link
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
References
Banks J, Marmot M, Oldfield Z, Smith JP . Disease and disadvantage in the United States and in England. JAMA 2006; 295: 2037–2045.
Bray GA, Bellanger T . Epidemiology, trends, and morbidities of obesity and the metabolic syndrome. Endocrine 2006; 29: 109–117.
Mokdad AH, Ford ES, Bowman BA, Dietz WH, Vinicor F, Bales VS et al. Prevalence of obesity, diabetes, and obesity-related health risk factors, 2001. JAMA 2003; 289: 76–79.
McTiernan A . Obesity and cancer: the risks, science, and potential management strategies. Oncology 2005; 19: 871–881.
Canoy D, Luben R, Welch A, Bingham S, Wareham N, Day N et al. Abdominal obesity and respiratory function in men and women in the EPIC-Norfolk Study, United Kingdom. Am J Epidemiol 2004; 159: 1140–1149.
Park YW, Zhu S, Palaniappan L, Heshka S, Carnethon MR, Heymsfield SB . The metabolic syndrome: prevalence and associated risk factor findings in the US population from the Third National Health and Nutrition Examination Survey, 1988–1994. Arch Intern Med 2003; 163: 427–436.
Gillum RF . Cardiovascular disease in the United States: an epidemiologic overview. In: Saunders E, (ed). Cardiovascular Diseases in Blacks. Philadelphia: FA Davis, 1991. pp 3–16.
Mensah GA, Mokdad AH, Ford ES, Greenlund KJ, Croft JB . State of disparities in cardiovascular health in the United States. Circulation 2005; 111: 1233–1241.
Palaniappan L, Wang Y, Fortmann SP . Coronary heart disease mortality for six ethnic groups in California, 1990-2000. Ann Epidemiol 2004; 14: 499–506.
Dowling HJ, Pi-Sunyer FX . Race-dependent health risks of upper body obesity. Diabetes 1993; 42: 537–543.
Bacha F, Saad R, Gungor N, Janosky J, Arslanian SA . Obesity, regional fat distribution, and syndrome X in obese black versus white adolescents: race differential in diabetogenic and atherogenic risk factors. J Clin Endocrinol Metab 2003; 88: 2534–2540.
Matthews KA, Sowers MF, Derby CA, Stein E, Miracle-McMahill H, Crawford SL et al. Ethnic differences in cardiovascular risk factor burden among middle-aged women: Study of Women's Health Across the Nation (SWAN). Am Heart J 2005; 149: 1066–1073.
Pan WH, Flegal KM, Chang HY, Yeh WT, Yeh CJ, Lee WC . Body mass index and obesity-related metabolic disorders in Taiwanese and US whites and blacks: implications for definitions of overweight and obesity for Asians. Am J Clin Nutr 2004; 79: 31–39.
Zhu S, Heymsfield SB, Toyoshima H, Wang Z, Pietrobelli A, Heshka S . Race-ethnicity-specific waist circumference cutoffs for identifying cardiovascular disease risk factors. Am J Clin Nutr 2005; 81: 409–415.
Fujioka S, Matsuzawa Y, Tokunaga K, Tauri S . Contribution of intra-abdominal fat accumulation to the impairment of glucose and lipid metabolism in human obesity. Metabolism 1987; 36: 54–59.
Yusuf S, Hawken S, Ounpuu S, Bautista L, Franzosi MG, Commerford P et al. Obesity and the risk of myocardial infarction in 27 000 participants from 52 countries: a case-control study. Lancet 2005; 366: 1640–1649.
Kahn HS, Austin H, Williamson DF, Arensberg D . Simple anthropometric indices associated with ischemic heart disease. J Clin Epidemiol 1996; 49: 1017–1024.
Snijder MB, Visser M, Dekker JM, Goodpaster BH, Harris TB, Kritchevsky SB et al. Low subcutaneous thigh fat is a risk factor for unfavourable glucose and lipid levels, independently of high abdominal fat. The Health ABC Study. Diabetologia 2005; 48: 301–308.
Snijder MB, Dekker JM, Visser M, Bouter LM, Stehouwer CD, Kostense PJ et al. Associations of hip and thigh circumferences independent of waist circumference with the incidence of type 2 diabetes: the Hoorn Study. Am J Clin Nutr 2003; 77: 1192–1197.
Wells JCK, Treleaven P, Cole TJ . BMI compared with 3D body shape: The UK National Sizing Survey. Am J Clin Nutr 2007; 85: 419–425.
Wang J, Gallagher D, Thornton JC, Yu W, Horlick M, Pi-Sunyer FX . Validation of a 3-dimensional photonic scanner for the measurement of body volumes, dimensions, and percentage body fat. Am J Clin Nutr 2006; 83: 809–816.
Wells JCK, Victora CG . Indices of whole-body and central adiposity for evaluating the metabolic load of obesity. Int J Obes 2005; 29: 483–489.
Cole TJ . Sympercents: symmetric percentage differences on the 100 log(e) scale simplify the presentation of log transformed data. Stat Med 2000; 19: 3109–3125.
Landman J, Cruickshank JK . A review of ethnicity, health and nutrition-related diseases in relation to migration in the United Kingdom. Pub Health Nutr 2001; 4: 647–657.
Chowdhury TA, Grace G, Kopelman PG . Preventing diabetes in south Asians. BMJ 2003; 327: 1059–1060.
Bhopal R, Hayes L, White M, Unwin N, Harland J, Ayis S et al. Ethnic and socio-economic inequalities in coronary heart disease, diabetes and risk factor in Europeans and South Asians. J Pub Health Med 2002; 24: 95–105.
Deurenberg-Yap M, Chew SK, Deurenberg P . Elevated body fat percentage and cardiovascular risks at low body mass index levels among Singaporean Chinese, Malays and Indians. Obes Rev 2002; 3: 209–215.
Turcato E, Bosello O, Di Francesco V, Harris TB, Zoico E, Bissoli L et al. Waist circumference and abdominal sagittal diameter as surrogates of body fat distribution in the elderly: their relation with cardiovascular risk factors. Int J Obes 2000; 24: 1005–1010.
Ohrvall M, Berglund L, Vessby B . Sagittal abdominal diameter compared with other anthropometric measurements in relation to cardiovascular risk. Int J Obes 2000; 24: 497–501.
Empana JP, Ducimetiere P, Charles MA, Jouven X . Sagittal abdominal diameter and risk of sudden death in asymptomatic middle-aged men: the Paris Prospective Study I. Circulation. 2004; 110: 2781–2785.
Riserus U, Arnlov J, Brismar K, Zethelius B, Berglund L, Vessby B . Sagittal abdominal diameter is a strong anthropometric marker of insulin resistance and hyperproinsulinemia in obese men. Diabetes Care 2004; 27: 2041–2046.
Zamboni M, Turcato E, Armellini F, Kahn HS, Zivelonghi A, Santana H et al. Sagittal abdominal diameter as a practical predictor of visceral fat. Int J Obes 1998; 22: 655–660.
van der Kooy K, Leenen R, Seidell JC, Deurenberg P, Visser M . Abdominal diameters as indicators of visceral fat: comparison between magnetic resonance imaging and anthropometry. Br J Nutr 1993; 70: 47–58.
Smith DA, Ness EM, Herbert R, Schechter CB, Phillips RA, Diamond JA et al. Abdominal diameter index: a more powerful anthropometric measure for prevalent coronary heart disease risk in adult males. Diabetes Obes Metab 2005; 7: 370–380.
Goodpaster BH, Krishnaswami S, Harris TB, Katsiaras A, Kritchevsky SB, Simonsick EM et al. Obesity, regional body fat distribution, and the metabolic syndrome in older men and women. Arch Intern Med 2005; 165: 777–783.
Dorling D . The fading of the dream: widening inequalities in life expectancy in America. Int J Epidemiol 2006; 35: 979–980.
Singh GK, Siahpush M . Widening socioeconomic inequalities in US life expectancy, 1980-2000. Int J Epidemiol 2006; 35: 969–978.
Ford ES, Giles WH, Dietz WH . Prevalence of the metabolic syndrome among US adults: findings from the third National health and Nutrition Examination Survey. JAMA 2002; 287: 356–359.
Despres JP, Couillard C, Gagnon J, Bergeron J, Leon AS, Rao DC et al. Race, visceral adipose tissue, plasma lipids, and lipoprotein lipase activity in men and women: the Health, Risk Factors, Exercise Training, and Genetics (HERITAGE) Family Study. Arterioscler Thromb Vasc Biol 2000; 20: 1932–1938.
Tittelbach TJ, Berman DM, Nicklas BJ, Ryan AS, Goldberg AP . Racial differences in adipocyte size and relationship to the metabolic syndrome in obese women. Obes Res 2004; 12: 990–998.
Albu JB, Murphy L, Frager DH, Johnson JA, Pi-Sunyer FX . Visceral fat and race-dependent health risks in obese nondiabetic premenopausal women. Diabetes 1997; 46: 456–462.
Acknowledgements
JW analyzed the data with TC, and wrote the first draft of the manuscript. PT directed SizeUK, and DB directed SizeUSA. PT and DB extracted appropriate data and advised on analyses. All authors contributed to revising the manuscript. PT is the director of Bodymetrics, a company specializing in 3D applications for the clothing industry. DB is vice president of [TC]2, a non-profit organization that uses 3D scanning instrumentation in clothing applications.
This work uses data from Sizing Surveys funded by Retailers and the UK Department of Trade and Industry.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Wells, J., Cole, T., Bruner, D. et al. Body shape in American and British adults: between-country and inter-ethnic comparisons. Int J Obes 32, 152–159 (2008). https://doi.org/10.1038/sj.ijo.0803685
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/sj.ijo.0803685
Keywords
This article is cited by
-
The smart body concept as a demonstration of the overarching utility and benefits of 3D avatars in retail, health and wellbeing: an accuracy study of body measures from 3D reconstruction
Multimedia Tools and Applications (2023)
-
Prevalence of overweight and metabolic syndrome, and associated sociodemographic factors among adult Ecuadorian populations: the ENSANUT-ECU study
Journal of Endocrinological Investigation (2021)
-
Body shape classification of Korean middle-aged women using 3D anthropometry
Fashion and Textiles (2020)
-
Evolution of total body and regional adiposity from late adolescence to early adulthood in a birth cohort study
Nutrition & Metabolism (2019)
-
Body shape by 3-D photonic scanning in Thai and UK adults: comparison of national sizing surveys
International Journal of Obesity (2012)