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.

Introduction

White middle-aged Americans have been found to suffer from greater rates of diabetes, hypertension, heart disease, stroke and cancer than their UK counterparts.¹ This finding was supported by similar differences in underlying physiological markers of risk.¹ Within each country, the risk of disease was strongly inversely associated with socio-economic status (SES). The between-country difference was greatest in low SES groups but was evident at all levels of SES. Some risk factors (for example, smoking) were similarly distributed between the two populations, whereas others differed systematically. Americans have substantially higher rates of obesity categorized by body mass index (BMI), and the between-population difference in obesity prevalence was greatest in those of low-income status.¹ Obesity is a well-established risk factor for the metabolic syndrome,^{2, 3} cancer ⁴ and poor lung function.⁵ The prevalence of obesity in the US rose from 15 to 31% between 1980 and 2003, whereas in the UK it increased from 7 to 23%.⁶

Within the United States, additional studies have highlighted differences between the three main ethnic groups (white, African American and Hispanic) in morbidity and mortality. African Americans have a lower prevalence of the metabolic syndrome than the other groups,⁶ but higher rates of cardiovascular mortality.^{7, 8} In contrast, Hispanics have a higher prevalence of the metabolic syndrome, especially in women,⁶ but lower rates of cardiovascular mortality.^{8, 9} Physiological studies indicate that the same level of BMI confers different metabolic risks in the three groups,^{10, 11} hence it is unclear about the extent to which obesity categorized in this way can explain ethnic disparities in health, as opposed to other factors such as SES.¹²

Recognition of the limitations of BMI as an obesity index has led to proposals for ethnic-specific cutoffs,¹³ and incorporation of data on waist girth, again with ethnic-specific cutoffs.¹⁴ BMI provides a simple estimate of relative weight, whereas the health impact of obesity is disproportionately because of central abdominal fat. While visceral fat is strongly associated with markers of disease risk,¹⁵ reflected by the strong association between risk of mortality and waist–hip ratio within narrow BMI bands,¹⁶ thigh girth appears protective.^{17, 18, 19} Epidemiological studies are therefore increasingly focusing on body shape as a more sensitive marker of disease risk.

Conventionally, body shape is categorized on a simple basis, such as waist girth, or the waist–hip ratio. Such measurements are simple to make, but may be considered invasive due to the need for the measurer to touch the body. 3D photonic scanning has recently emerged as a more sophisticated approach for the measurement of human body shape.^{20, 21} Whole-body scans of surface topography can be captured in a few seconds using a customized photo booth, after which software automatically extracts digital information on a variety of parameters of body shape. During 2001–2003, two large sizing surveys were conducted in the United States and United Kingdom. Using identical protocols, these surveys allow comparison of body shape between and within populations. Here, we describe (a) differences between British and American white adults, and (b) differences between ethnic groups within Americans, taking into account variability in education and income status.

Methods

The two National Sizing Surveys, SizeUK and SizeUSA, were conducted using identical instrumentation, study design and recruitment strategy. Data were collected in the United Kingdom during 2001–2002, in eight cities (Birmingham, Cardiff, Edinburgh, Leeds, London, Manchester, Nottingham, Southampton). Data were collected in the United States during 2002–2003, in 12 cities (Cary, NC; Columbia, MO; Dallas, TX; Miami, FL; New York, NY; Los Angeles, CA; San Francisco, CA; Portland, OR; Chattanooga, TN; Atlanta, GA; Lawrence, MA; Glendale, CA). In each survey, recruitment was conducted on the basis of minimum cell sizes for each sex in specific age bands, stratified further by SES (education and income criteria) and ethnicity. Cell sizes were calculated to estimate mean height in each cell with a confidence interval of 1 cm, equivalent to a standard error of 0.5 cm. Participants signed a consent form allowing use of their anonymized data in statistical analyses. Ethical approval for analysis of the data for medical purposes was granted by the Ethics Committee of Great Ormond Street Hospital NHS Trust and the Institute of Child Health, London.

For participants in SizeUSA, data were available on duration of schooling and income. Income was classified according to the following categories in ascending order: <USD25k, USD25–50k, USD50–75k, USD75–100k, >USD100k. The duration of schooling was categorized as 'less high school', 'high school', or 'college'. Age was categorized in both samples into six groups: 18–25.99; 26–35.99; 36–45.99; 46–55.99; 56–65.99; 66 years. Overweight and obesity were categorized using BMI cutoffs of 25 and 30 kg/m² respectively.

Whole body scans were obtained using a [TC]² scanner (Cary, NC, USA; www.tc2.com), with the subject standing motionless wearing close-fitting underwear. The manufacturer's software automatically extracts key body landmarks and uses these to determine a variety of girths and distances. For our analyses, we used the girths of the mid-upper arm, bust (women only), chest, waist, hips and mid-thigh. Technical precision of all measurements was within 0.5 cm. For further details, see our previous report on SizeUK.²⁰

General linear models were constructed to compare the mean values of different populations or ethnic groups, adjusting for confounders as appropriate. Owing to differences in purchasing power and educational systems between the United Kingdom and the United States, the comparison of whites between these populations was not adjusted for income or education. However, use of the same recruitment strategy in both populations ensured that the social composition of the samples was equivalent. Comparisons between ethnic groups within the United States were adjusted for education and income. The body shape of white Americans was assessed using white British as the reference group. Numbers of non-white adults in SizeUK were too few within some age groups for effective statistical analysis, hence only data on white British individuals were considered here. The body shape of African or Hispanic Americans was assessed using white Americans as the reference group. Scheffe's post hoc test was used to describe the increase or reduction in each anthropometric variable attributed to the group under investigation.

Previous studies have often used ratios of girths to describe body shape in more detail. For example, the waist–hip ratio is often calculated to adjust the abdominal circumference for physique. Such ratios offer a convenient approach for routine clinical application, but may not be optimal for large-scale statistical analyses. Many ratios are statistically flawed, since dividing one variable by another does not necessarily achieve an appropriate adjustment of the numerator for the denominator, as discussed previously.²² The approach we adopted was as follows. First, girth data were log-transformed using natural logarithms. When multiplied by 100, the resulting coefficients are equivalent to the percentage difference between groups.²³ Second, selected girths were adjusted for a further girth (for example, waist for hip) in the linear models.

We investigated several indices of body shape using this general approach. Waist girth was adjusted for hip girth, thigh girth and in women, bust girth. Thigh girth was adjusted for hip girth and arm girth. Collectively, these analyses indicate relative distributions of weight across the torso and limbs.

Results

Raw data for SizeUK and SizeUSA are given in Table 1. Rates of obesity were significantly greater in African and Hispanic Americans, especially African-American women, than in white Americans. Obesity rates were around 10% lower in white British than in white Americans.

Table 1 - Description of adults in SizeUK and SizeUSA.

Full table

For SizeUSA, Table 2 shows associations between indices of social status (income and education categories) and either height or waist girth adjusted for height and hip girth, all data further adjusted for age category and whichever of income or education was not the dependent variable. In white and Hispanic Americans, increasing social status was directly associated with height. The equivalent associations were not apparent in African Americans. In white and African Americans, increasing social status was inversely associated with waist girth, except for income status in African-American males. In Hispanic Americans, waist girth was inversely associated with education level but not income.

Table 2 - Associations between social status and height or waist girth in white, African and Hispanic Americans.

Full table

Table 3 presents comparisons of white men and women from the United Kingdom and the United States. In both sexes, after adjusting for age and height, Americans had significantly greater weight, BMI and girths than their UK counterparts. However, when waist girth was adjusted for hip or thigh girth, the between-country difference varied by gender. American white men had larger waist relative to physique than UK white men, whereas American white women had smaller waist girth than UK white women. American white men had larger thigh girth, even after adjusting for hip girth, whereas in women there was no difference after adjusting for hip girth. American white men had larger arm girth, while thigh girth adjusted for arm girth did not differ between the populations. In contrast, American white women had smaller thigh relative to arm girth. These between-country differences are summarized in Figure 1.

Figure 1.

Percentage difference in height, body girths and weight of white American men and women relative to white British men and women. All outcomes (except height) adjusted for height ^*P<0.01; ^**P<0.0001.

Full figure and legend (56K)

Table 3 - Differences in shape between white adults from SizeUK and SizeUSA, expressed as % difference of Americans relative to their UK counterparts.

Full table

Table 4 presents comparisons of African or Hispanic Americans against white Americans, adjusting for age, income, education and (where relevant) height. African Americans were similar in height to white Americans, but had greater BMI. African-American women had larger girths than their white counterparts, however African-American men had smaller waist girth but greater arm and thigh girth. Taking into account physique, African-American men had smaller waist relative to hip or thigh, and larger thigh relative to arm. African-American women had smaller waist relative to thigh, but smaller thigh relative to arm. This sex difference in thigh–arm ratio could be attributed to the much greater increase in arm girth of African Americans relative to white Americans in women compared to men. Hispanic Americans were shorter than white Americans, and had greater BMI. They had larger girths, except of the thigh. Taking into account physique, Hispanic Americans had greater waist relative to hip or thigh, or bust in women. In Hispanic women, but not men, thigh girth was smaller relative to the arm. The differences relative to white Americans are summarized in Figure 2 for males and Figure 3 for females. These figures illustrate that female Hispanics and African Americans tend to differ from their white counterparts in similar directions, but with different magnitudes. In contrast, male Hispanics and African Americans tend to differ from their white counterparts in both direction and magnitude.

Figure 2.

Percentage difference in height, body girths and weight of African and Hispanic American men relative to white American men. All outcomes adjusted for age, income and education categories and (except height) height. ^*P<0.01; ^**P<0.001.

Full figure and legend (51K)

Figure 3.

Percentage difference in height, body girths and weight of African and Hispanic American women relative to white American women. All outcomes adjusted for age, income and education categories and (except height) height. ^*P<0.05; ^**P<0.001.

Full figure and legend (49K)

Table 4 - Differences between ethnic groups in SizeUSA, expressed as % difference compared to US whites.

Full table

Discussion

Our analyses have revealed significant differences in size and body shape between ethnic groups and social categories within the US population, and have further demonstrated significant differences in body shape between US and UK white adults. These differences may prove to play a key role in accounting for differences in morbidity and mortality between these populations and social groups.

A substantial body of evidence now links the increasing prevalence of obesity in industrialized populations with an increased burden of disease, especially in relation to the metabolic syndrome.^{2, 3} However, what is less clear is the extent to which variability in the prevalence of obesity can account for variability in morbidity and mortality in relation to SES and ethnicity.

A major factor hindering investigation of this issue has been the use of a crude approach to categorizing obesity. While standardized cutoffs for obesity facilitate broad between-population comparisons, BMI provides only a poor proxy for the central fat mass most strongly associated with disease risk. BMI has undoubtedly been of value in predicting morbidity and mortality within populations, and within any ethnic group, high levels of BMI are associated with poorer health. However, individuals within and between ethnic groups differ in their regional distribution of excess weight, hence BMI is confounded by variability in physique and remains a relatively crude index of risk. For example, Asians are now known to have both greater disease risk ^{24, 25, 26} and greater body fatness ²⁷ than Europeans for any given BMI level, which has led to proposals for ethnic-specific BMI cutoffs to identify overweight and obesity.¹³ In our own analyses, population differences in BMI did not match those in body shape. For example, whereas African-American men were significantly heavier than their white counterparts, their waist girth was smaller and their thigh girth larger. Hispanic men and women had lower rates of obesity according to BMI compared to African Americans, but had larger waist and smaller thigh girth.

A large study of data from 52 countries demonstrated markedly greater sensitivity of the waist–hip ratio compared to BMI in predicting myocardial infarction.¹⁶ However, these measurements may themselves not be the most sensitive indicator of risk. Several recent studies of adults have found that sagittal diameter is a superior predictor of cardiovascular risk, risk of the metabolic syndrome and mortality.^{28, 29, 30, 31} This may be attributed to the fact that sagittal diameter is likewise more closely associated with visceral fat than waist circumference.^{32, 33} Other studies suggest that certain fat depots may be protective against disease risk. In a case–control study of ischemic heart disease, the ratio of sagittal diameter to thigh girth was the strongest positive predictor of risk, while thigh girth was negatively predictive.¹⁷ Other studies have likewise found sagittal diameter adjusted for thigh girth to be the strongest predictor of cardiovascular disease,³⁴ and confirmed the protective association of thigh adiposity with cardiovascular risk ^{18, 35} and type 2 diabetes.¹⁹

Within Americans, our analyses showed that increasing social status, as represented by income or years of education, was broadly associated with greater height and a smaller waist girth adjusted for hip girth. However, African Americans did not show such associations for height, while Hispanic Americans did not show such associations for education level and waist girth. The lack of such associations may be due to insufficient time having elapsed for improvements in living conditions and opportunities to impact fully on growth. Both short stature and central adiposity are associated with poor growth patterns in early life, implying that improved circumstances need to persist over generations to confer significant benefits on the current generation. A further factor may have been the small numbers of African- and Hispanic Americans in high-income categories, reducing the statistical power for detecting associations with shape. Nevertheless, the broad presence of such trends demonstrates the importance of adjusting for socio-economic variables when comparing body shape between ethnic groups, and furthermore indicates the importance of social environmental factors in exposure to the obesogenic environment. Although studies on this issue are rare in the United States,³⁶ a recent analysis demonstrated increasing disparity in life expectancy between rich and poor Americans.³⁷

Our comparison of white adults from the United Kingdom and United States revealed a sex difference. American males had greater waist circumference than British men, whether or not adjusted for hip or thigh girth. In contrast, American women had smaller waist girth than British women after adjusting for hip or thigh girth, although they had greater absolute waist, hip and bust girths, 4% greater BMI and 10% greater prevalence of obesity categorized by BMI. It is probable therefore that the reduced hip-adjusted waist girth does not imply reduced cardiovascular risk in the US white women, and is rather simply an artefact of their excess weight being located in hips and bust as well as waist. Consistent with this assumption, there was no sex difference in markers of ill-health in the previous between-country analysis of morbidity (Marmot M, personal communication).

Our findings in relation to ethnic groups within the American population show some consistency with the results of the third National Health and Nutrition Examination Survey, which found that African Americans had slightly lower prevalence of the metabolic syndrome than whites, while Mexican Americans had the highest prevalence.³⁸ Underlying these overall trends, however, individual components of the metabolic syndrome showed more dramatic differences, with white and Mexican Americans having significantly higher rates of hypertriglyceridemia and low high density lipoprotein concentration, whereas African Americans had higher rates of hypertension.³⁸ More detailed studies have revealed ethnic differences in the amount of visceral fat present at a given waist circumference, and in the metabolic activity of this fat depot. For example, African Americans have been found to have lower absolute levels of visceral adiposity ^{39, 40, 41} but to be relatively more insulin resistant nonetheless.¹¹ Despite their apparently healthier shape, especially in males, African Americans show the highest incidence of cardiovascular disease.^{7, 8} Ethnic variability in the physiological impact of abdominal versus peripheral fat depots on metabolic risk therefore needs to be taken into account, and our data on body shape match more closely with the ethnic distribution of the metabolic syndrome than with that of cardiovascular mortality.

The inter-relationships between ethnicity, body shape and risk of disease are therefore complex. Collectively, our findings highlight the potential for 3D body scanning to contribute to the categorization of risk and the monitoring of patients, in particular addressing ethnic differences in physique and physiology. Providing a wealth of information about body shape at a fraction of the cost of MRI scanning, 3D photonic scans combined with ethnic-specific reference data have the potential to identify those at high risk of the metabolic syndrome, and to track the response of such individuals to treatment.

In summary, analyses of two large surveys of body shape using 3D photonic scanning have shown significant differences between nations in a single ethnic group, and significant differences within a nation between groups categorized according to social status or ethnicity. The pattern of variability in body shape closely tracks the pattern of variability in incidence of the metabolic syndrome, implicating central abdominal fat as an important contributing factor to health disparities. Detailed measurement of body shape, using ethnic-specific reference data, therefore has the capacity to improve the categorization of risk of the metabolic syndrome, and could potentially prove equally valuable for monitoring response to treatment.

References

1. Banks J, Marmot M, Oldfield Z, Smith JP. Disease and disadvantage in the United States and in England. JAMA 2006; 295: 2037–2045. | Article | PubMed | ISI | ChemPort |
2. Bray GA, Bellanger T. Epidemiology, trends, and morbidities of obesity and the metabolic syndrome. Endocrine 2006; 29: 109–117. | Article | PubMed | ISI | ChemPort |
3. 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. | Article | PubMed | ISI |
4. McTiernan A. Obesity and cancer: the risks, science, and potential management strategies. Oncology 2005; 19: 871–881. | PubMed | ISI |
5. 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. | Article | PubMed | ISI | ChemPort |
6. 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. | Article | PubMed | ISI |
7. 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.
8. 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. | Article | PubMed | ISI |
9. Palaniappan L, Wang Y, Fortmann SP. Coronary heart disease mortality for six ethnic groups in California, 1990-2000. Ann Epidemiol 2004; 14: 499–506. | Article | PubMed | ISI |
10. Dowling HJ, Pi-Sunyer FX. Race-dependent health risks of upper body obesity. Diabetes 1993; 42: 537–543. | Article | PubMed | ISI | ChemPort |
11. 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. | Article | PubMed | ISI | ChemPort |
12. 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. | Article | PubMed | ISI |
13. 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. | PubMed | ISI | ChemPort |
14. 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. | PubMed | ISI | ChemPort |
15. 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. | Article | PubMed | ISI | ChemPort |
16. 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. | Article | PubMed | ISI |
17. Kahn HS, Austin H, Williamson DF, Arensberg D. Simple anthropometric indices associated with ischemic heart disease. J Clin Epidemiol 1996; 49: 1017–1024. | Article | PubMed | ISI | ChemPort |
18. 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. | Article | PubMed | ISI | ChemPort |
19. 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. | PubMed | ISI | ChemPort |
20. 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. | PubMed | ISI | ChemPort |
21. 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. | PubMed | ISI | ChemPort |
22. 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. | Article | ISI | ChemPort |
23. 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. | Article | PubMed | ISI | ChemPort |
24. 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. | ChemPort |
25. Chowdhury TA, Grace G, Kopelman PG. Preventing diabetes in south Asians. BMJ 2003; 327: 1059–1060. | Article | PubMed |
26. 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. | Article | ISI |
27. 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. | Article | PubMed | ChemPort |
28. 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. | Article | ISI | ChemPort |
29. 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. | Article | ISI | ChemPort |
30. 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. | Article | PubMed | ISI | ChemPort |
31. 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. | Article | PubMed | ISI |
32. 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. | Article | ISI | ChemPort |
33. 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. | Article | PubMed | ChemPort |
34. 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. | Article | PubMed | ISI | ChemPort |
35. 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. | Article | PubMed | ISI |
36. Dorling D. The fading of the dream: widening inequalities in life expectancy in America. Int J Epidemiol 2006; 35: 979–980. | Article | PubMed | ISI |
37. Singh GK, Siahpush M. Widening socioeconomic inequalities in US life expectancy, 1980-2000. Int J Epidemiol 2006; 35: 969–978. | Article | PubMed | ISI |
38. 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. | Article | PubMed | ISI |
39. 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. | PubMed | ISI | ChemPort |
40. 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. | PubMed | ISI |
41. 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. | Article | PubMed | ISI | ChemPort |

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.