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Pereira et al. (Confidential draft).

Ratio of Waist Circumference to Body Weight as a Marker of Relative Abdominal Adiposity: Comparisons Between Asian Indian and U.S. Men and Women

Mark A. Pereira, Ph.D. Harpreet S. Bajaj, M.D. Mohan Anjana, M.B.B.S. Viswanathan Mohan, M.D., M.R.C.P., Ph.D., F.R.C., D.S.C Gundu V. Rao, Ph.D. Myron D. Gross, Ph.D.

AFFILIATIONS HERE…

Correspondence to:

Mark A. Pereira, Ph.D. Assistant Professor Division of Epidemiology & Community Health University of Minnesota 1300 South Second Street Suite 300 Minneapolis, MN 55454 Phone: 612-624-4173 Fax: 612-624-0315 Email: [email protected]

Pereira et al. (Confidential draft).

ABSTRACT

Background: Relative to Europids, Asian Indians appear to have higher rates of type 2 diabetes and cardiovascular disease despite a low prevalence of general obesity. Whether differences in body composition, including fat distribution, may underlie these population differences in chronic disease remains unclear. We propose that the waist circumference to weight ratio (WW) might reflect propensity towards storage of energy as visceral body fat relative to subcutaneous fat, and therefore we hypothesized that WW would be higher in Asians than in the U.S.

Methods: We compared directly measured anthropometric data from the CURES (Chennai

Urban Rural Epidemiologic Study) survey of Southern Indians (I) with those from three U.S. ethnic groups (Caucasians- C, African Americans- A and Mexican Americans- M) from

NHANES III (Third National Health and Nutrition Examination Survey). A total of 15,733 subjects from CURES and 5,975 from NHANES III met the inclusion criteria (age 20-39, no known diabetes).

Results: Asian Indian men and women had substantially lower height, weight, waist circumference, hip circumference, waist-hip ratio (WHR) and body surface area relative to U.S. ethnic groups (all sex-specific p-values <0.0001, except similar WHR for I and A men and for I and M women). The BMIs of I men (mean ± se = 21.8 ± 3.80) and women (22.4 ± 4.45) were also substantially lower (p<0.0001) than all three sex-stratified U.S. ethnic groups (the lowest among the U.S. groups being Caucasian women with mean BMI = 25.0 ± 6.08). The mean (±se)

WW were significantly higher (p<0.001) in I (men 1.35 ± 0.002 and women 1.45 ± 0.002) than in all the U.S. groups (1.09, 1.21, 1.14 in A, M and C men, 1.23, 1.33, 1.26 in A, M and C women [se ranged from 0.005 to 0.006]). Consistent with these mean differences, large Pereira et al. (Confidential draft). differences in the WW median, 75th, and 90th percentiles were observed between Asian Indians and the other ethnic groups. Adjustment for age and height had minimal impact on these differences.

Conclusions: Chronic disease rate differences between Asian Indian and U.S. populations may not be explained by traditional anthropometric parameters. It appears that the waist-to-weight ratio might be a simple anthropometric index capturing population differences in propensity for intraabdominal fat storage, while appearing to account for confounding influences of overall body size and general adiposity. Pereira et al. (Confidential draft).

INTRODUCTION

Nutrition research in India has historically focused on the problem of undernutrition.

With India undergoing a demographic, epidemiologic and nutrition transition, the economic costs of overnutrition related disorders are set to overtake the undernutrition costs by 2025.1

This point is illustrated by the fact that the estimated prevalence of type 2 diabetes in India is highest in the world and projected to increase 150% by the year 2030, when the projected 80 million cases will comprise almost a quarter of the world’s diabetic population.2 It is difficult to forecast the public health and economic burden this looming epidemic of chronic diseases will place on this developing country.

A number of studies have documented very high rates of type 2 diabetes (2-6 fold higher)3-9and cardiovascular disease (2-4 fold higher)10-13 in Indians compared to Caucasians of

European ancestry. These differences are paradoxical in light of India’s relatively low prevalence of general obesity, based on body mass index, compared to the Caucasian Europeans.

The prevalence of general overweight and obesity in India is estimated to be less than 25%,17,18 compared to about 65% in the U.S. population.19 Alternatively, it has been hypothesized that

South Asians have a propensity towards central (intra-abdominal or visceral) obesity and associated insulin resistance at relatively low body weight.5, 16, 20-23 Indeed, clinical studies have suggested that associations between general adiposity and insulin sensitivity may differ between

South Asians and Caucasians, with Indians having lower insulin sensitivity after accounting for overall adiposity.15,24(BrandMiller) Might variations in fat patterning between these populations, after accounting for differences in total adiposity, explain these findings? Pereira et al. (Confidential draft).

The World Health Organization has addressed this paradox of low obesity and high chronic disease risk in Asian populations by setting lower thresholds of BMI to identify those who may be at high risk.25 However, some have suggested that BMI has a negligible association with chronic disease prevalence26,27(INTERHEART04&05) and with visceral abdominal fat 28 in Asian

Indians. As alternative measures, studies in various populations, including Asian Indians,28,29,15,27 the U.S.,30 and elsewhere,31 suggest that either waist circumference alone28,30 or waist-hip ratio15,27,29,31 may be a better single anthropometric marker of chronic disease risk, as compared to

BMI, because they may more specifically reflect abdominal body fatness. However, waist circumference alone does not reflect lean body mass, which is known to be protective, 32 and fails to allow comparisons between subjects and populations due to confounding by body size and weight. Indeed, evidence that high waist-hip ratio may contribute to the high incidence of diabetes in Asian Indians is equivocal.16,33-36

To address the potential influence on chronic disease risk of high abdominal fatness relative to total body fatness in Asian Indians, we propose the ratio of waist circumference to body weight. We theorize that the waist-weight ratio, as a single continuous index, might distinguish large differences between cultures in the propensity to store fat in the visceral depots, consistent with differences in insulin resistance, diabetes, and CVD. Therefore, we hypothesized that the waist-weight ratio would be higher in Indian men and women than in U.S. men and women. This hypotheses was tested by comparing anthropometric characteristics between young adults of the National Health and Nutrition Examination Survey (NHANES) III)37 to young adults of the Chennai Urban Rural Epidemiologic Study (CURES).38 Pereira et al. (Confidential draft).

SUBJECTS AND METHODS

Study populations

The Third National Health and Nutrition Examination Survey (NHANES III)29 is a large cohort representative of the U.S. population, with minority groups over-sampled. It

was conducted by the National Center For Health Statistics and the Center For Disease Control

And Prevention on a nationwide probability sample of approximately 33,994 persons 2 months and over from mid-1988 to mid-1994. The cross-sectional survey was designed to obtain nationally representative information on the health and nutritional status of the population of the

United States through interviews and direct physical examinations. Written informed consent was obtained from all participants and the National Center For Health Statistics approved the protocol. Full details of the study design, recruitment and procedures are available from the US

Department of Health And Human Services.29

The Chennai Urban Rural Epidemiologic Study (CURES)30 is a large cross-sectional field survey of representative samples of the area in and around Chennai, the largest city in South

India and the fourth largest in India. This study randomly sampled the study population of

26,000 from the whole of Chennai (representing the urban component) and villages around

Chennai (representing the rural component). The study commenced in August 2001 with the objective of comparing the prevalence of various components of Insulin Resistance Syndrome and various diabetes related complications. Ethical committee approval was obtained prior to the start of the study and an informed consent was obtained from all the study subjects. Details on the study design, recruitment and phases of the survey can be requested from Dr. Mohans' M.V.

Diabetes Specialities Centre, Gopalapuram, Chennai, India.30 Pereira et al. (Confidential draft).

Anthropometric assessments

In NHANES III, heightwas measured to the nearest 0.1 cm with calibrated stadiometer, without shoes. Weight was measured to the nearest 0.1 kg with calibrated scale, allowing light clothing. Waist circumference was measured to the nearest cm with tape measure at the highest point on the iliac crest, while the subject was at minimum respiration, allowing light clothing.

Hip circumference was measured to the nearest cm with a tape measure at maximum extension of the buttocks, allowing light clothing.

In CURES, height was measured to thenearest cm with a tape measure, subjects standing upright without shoes. Weight was measured to the nearest 0.5 kg with a calibrated scale, allowing light clothing. Waist was measured to the nearest cm with a tape measure at the smallest horizontal girth between the costal margins and the iliac crest at minimal respiration.

Hip was taken as the greatest circumference at the level of greater trochanters (the widest portion of the hip) on both sides. It was measured to the nearest cm with a tape measure.

In order to compare the sex-specific prevalence of overweight and obesity among the four ethnic groups, we used the currently accepted definitions based on BMI and waist circumference cutoffs.[NHLBI, 1998; NCEP; IDF] These include lower cutoffs for Asian

Indians recommended by WHO for BMI (ref) and IDF for waist circumference (ref).

Exclusion criteria and final sample sizes

In order to minimize the likelihood of bias due to age-cohort effects and the potential impact of clinical or subclinical illness on anthropometry, we implemented the following exclusion criteria: 1) Missing or aberrant values for anthropometric variables (excluded 7,824) Pereira et al. (Confidential draft). from NHANES III and 446 from CURES). 2) Missing race/ethnicity or race/ethnicity other than

African American, Caucasian or Mexican American (excluded an additional 1,130 from

NHANES III), 3) Age < 20 or > 30 (excluded an additional 18,735 from NHANES III and 9,270 from CURES), 4) blood sugar < 50 mg/dL or > 200 or known diabetes (excluded an additional

329 from NHANES III and 462 from CURES), 4) BMI < 14 kg/m2 (excluded none from

NHANES III and an additional 93 from CURES). There were a total of 21,705 subjects (5,975

(5,976) from NHANES III and 15,729 from CURES) who met the inclusion criteria.

Statistical methods

All analysis were sex-stratified and performed using SAS version 9.1 (Cary, NC). We compared the unadjusted prevalence of overweight and obesity, based on BMI and waist categories, between Asian Indians and the three U.S. race groups using chi-square analysis.

General linear regression models were used to estimate unadjusted and adjusted least squares means (± se) of the anthropometric variables (dependent) by race and sex group. All p-values are 2-sided. Estimates were not weighted according to the NHANES sampling scheme because our aim was to make comparisons to the CURES population sample and not to make estimations for the entire U.S. population.

RESULTS

Race- and sex-stratified sample sizes and unadjusted anthropometric characteristics are shown in Table 1. Briefly, Asian Indian men and women had substantially lower height, weight, body mass index, waist circumference, hip circumference, and body surface area relative to all

U.S. ethnic groups (all sex-specific p values <0.0001). Asian Indian men had a lower mean Pereira et al. (Confidential draft). waist-to-hip ratio compared to the Caucasian and Mexican American men (p<0.0001), but slightly larger mean waist-to-hip ratio than the African American men (p=0.03). Asian Indian women had a higher mean waist-to-hip ratio compared to the African American and Caucasian women (p<0.0001), but similar to the Mexican American women (p=0.43).

Ethnic variations in BMI and WC categories

In men and women alike, as shown in Figure 1 based on BMI criteria, the frequency of

Asian Indians in the normal weight category (84.2% for men, 77.4% for women) was significantly greater, and the frequency of overweight and obesity lower, than any other ethnic group (p<0.0001 for all sex-stratified comparisons). This remained true even after applying lower cutoffs for the Asians Indians as suggested by the WHO Expert Committee recommendations,25 except for the frequency of overweight Asian Indian women which was similar to the African American women (p-value = 0.69), slightly less than Mexican American women (p-value = 0.03) and significantly less than Caucasian women (p-value <0.0001). In

Figure 2, the Asian Indian men and women have lower central obesity meeting NCEP’s

Metabolic syndrome cutoff values for waist circumference than all other groups (p<0.0001).

When applying the ethnicity driven IDF cutoffs, the differences between the Asian Indians and other groups were attenuated, but remained statistically significant (p<0.0001), even with the lower cutoffs suggested for the Asian Indian men.

Correlations Among Anthropometric variables

Table 2 (Men) and Table 3 (Women) include the unadjusted sex- and population-specific

Pearson correlations among the various anthropometric variables. We pooled the U.S. race- Pereira et al. (Confidential draft). groups within sex because the correlations did not vary in important ways among U.S. race groups. The magnitudes of these correlations were all lower, without exception, in the Asian

Indians compared to the U.S., with most of the Asian-U.S. differences being large. For example, the magnitude of the correlations between waist and either body weight or BMI ranged from 0.56 to 0.63 in Chennai men and women, compared to 0.90 to 0.93 in U.S. men and women. The scattergrams in Figure 3, shown for men, demonstrate the considerable population differences in the association between waist and BMI between Chennai and U.S. Caucasian men. For any given BMI in Asian Indians there was considerably more inter-individual variation in the waist than is observed in the U.S. Very similar results were observed for women and for the other U.S. ethnic groups (data not shown).

Of note, age and height adjustment did not seem to considerably alter the correlations in magnitude or direction (data not presented). In contrast, as presented in Tables 2 and 3, weight adjustment altered correlations between hip and waist as well as between hip and waist-hip ratio among the US population. The strong correlations between hip and waist were considerably attenuated by adjusting for weight in both genders in the US population, whereas this adjustment had little effect in the Asian Indian population (Tables 2 and 3). Of particular note was the different direction of the correlation between hips and waist-hip ratio for Asian Indians (-0.12 for men, -0.23 for women) compared to U.S. (0.40 for men, 0.26 for women). However, in the U.S. the correlation between hips and waist-hip ratio was confounded by the high correlation between waist and weight. As such, further adjustment for weight reversed the direction of this correlation in the U.S. (-0.37 for men, -0.53 for women). Weight-adjustment marginally strengthened the magnitude of the correlation in the Asian Indians, but because the correlation Pereira et al. (Confidential draft). between waist and weight is relatively low, the direction of the association remained inverse (-

0.29 in men, -0.36 in women).

The waist-to-weight ratio

To further evaluate possible differences between populations in central adiposity while taking into account differences in total body mass, we computed the waist circumference to body weight ratio. The waist-to-weight ratio (WW) followed a normal distribution for all sex and population groups. Box plots for the waist to weight ratio by sex and population are displayed in

Figures 4 and 5. The median WW was highest among men and women from Chennai, and was in fact higher than the 75th%ile of all other groups. The means of WW before and after adjustment for height are shown in Table 4. As can be seen, WW was significantly higher

(p<0.0001) in the Asian Indians than in the U.S. for both sexes. The attenuation of these differences by age and height adjustment was minimal.

DISCUSSION

The present study compares a number of traditional anthropometric factors between young adults of the U.S. representative NHANES III survey, including three race/ethnic groups, and the population-based CURES survey of Asian Indians. Our observations confirm the findings of others, that the Asian Indians tend to be much smaller than the U.S. population in all traditional respects – body weight, body height, body mass index, body surface area, hips and waist circumference. In contrast, we observed the WHR, which some studies have found to be higher in Asian Indians than in other groups27, 29,31 to be somewhat higher in Asian Indian women compared to U.S. women, but not different, or in fact lower, among Asian Indian men compared Pereira et al. (Confidential draft). to U.S. men. In our analyses, the differences between means of WHR, though significantly higher in Asian Indian women compared to Caucasian and African American women, were small.

It is possible, therefore, that if Asian Indians have a propensity towards excess accumulation of visceral body fat, it is being masked, perhaps especially in the men, by large differences in overall body size between populations. Based on the findings of the present study, it appears that our novel waist to weight ratio (WW) might me a simple anthropometric index capturing population differences in propensity for intra-abdominal fat storage. The WW would appear to sufficiently account for the large confounding influence of overall body size and general adiposity. For any given body weight, larger waist circumferences should reflect larger intra-abdominal fat depots. Individuals with relatively high body weights who tend to carry much of their weight in muscle and subcutaneous fat depots peripherally would be expected to have lower WW, and lower risk for diabetes and CVD, hypothetically. Based on our observations, the distribution of WW in young adults from Chennai, India, is considerably shifted to the right in comparisons to similarly aged adults from four race/ethnic groups of the

U.S. population.

An intriguing observation from the comparisons of the present study was the vastly different correlation between waist circumference and body mass index between young adults of

Chennai, India compared to those from three U.S. race/ethnic groups. In the U.S. over 80% of the variation (r=~0.9) in waist circumference is explained by BMI, whereas in Chennai, India, these two parameters shared less than 40% common variance (r=~0.60). This observation helps us to understand the basis for the higher WW in Chennai than in the U.S. That is, at any given body mass index there is clearly much more variation in the waist circumference of Asian Indian Pereira et al. (Confidential draft). young adults, than in U.S. young adults. That is, the basis for these differences in correlations between WW may be greater variability in visceral fat, relative to overall body size, in India than the U.S. Indeed, the variance of WW in the Chennai men and women was three-fold higher than that of the U.S. men and women (0.03 vs. 0.01).

Strengths of the WW are that it retains simplicity in measurement and calculation, making it desirable over WHR in this regard, and allows comparisons between people and populations varying in overall body size, making it desirable to the waist circumference alone.

Some authors20,42 have suggested an interaction between upper-body adiposity, as measured by

WHR, and general adiposity, as measured by BMI, and have suggested the use of these ratios in tandem for the Asian Indian populations. Using the WW, in addition, gets away with setting different cutoffs for BMI and WC for different ethnic populations, which in any case may not be as helpful (refer to Figures 1 and 2). Possible limitations of WW ratio are that it does not adjust for height (and age). To look further into the usefulness of height, we did compute (data not presented) a waist circumference to BMI ratio (WBR). This ratio differentiated the two populations on an ecological level, similar to our WW. Using such a ratio did not seem to provide any added benefit to the WW, while it may be fraught with a number of conceptual and statistical problems as discussed by others.44,45 Another conceivable limitation of the WW is that the denominator (weight) is highly correlated with the numerator in many populations (See

Tables 2 and 3). When an index is derived in the form A/(A+B), and where B>A, it tends to converge on 1/B at high values of B, and hence to show an inverse correlation with B. It is not clear if this mathematical relation would be applicable to WW (cm/kg), given that it has cm as numerator. Pereira et al. (Confidential draft).

Biological explanation for lean-fat phenotype of Asian Indians has been an area of intense interest and debate for years. The current diabetes epidemic is usually attributed to a thrifty genotype, proposed by Neel46 in 1962, which helped survival in the distant past when food supply was scarce and irregular, but these genes have become detrimental in contemporary conditions of plentiful food and sedentary lifestyles. An extension of this idea has been proposed by researchers by suggesting a thrifty phenotype at birth, resulting from fetal undernutrition, predicts adult diabetes.47 Indeed, Yajnik et al.48 described preserved body fatness despite other anthropometric measurements in Indian babies being smaller compared to UK Caucasian babies.

As for the specific genetic mechanisms involved, recent unpublished data49 suggest that decreased activity of the PPAR gene in the Asian Indian population may be the causative factor for their high insulin resistance. Other genetic factors, including HNF1alpha,50 ENPP1 K121Q polymorphism51 and telomere shortening52 have also been suggested as contributing to the genetic susceptibility of the Asian Indian population to type 2 diabetes. Better economic conditions in India in recent times are thought to have produced changes in diet habits and decreased physical activities, conditions favorable for expression of diabetes in the population, which already has a racial and genetic susceptibility to chronic diseases. Danforth53 has suggested, based on recent animal research,54,55 that failure of adipocyte differentiation may lead to central obesity and hence type 2 diabetes. It is hence conceivable that in the presence of excess energy, Asian Indians may not respond with adequate amounts of adipocyte proliferation and differentiation. Therefore, the adipose tissue in this population may only differentiate in the central region, causing excess non-esterified fatty acid (NEFA) levels, leading to type 2 diabetes.

56,57 Pereira et al. (Confidential draft).

Strengths of this study are multiple. It is population-based and done on a large sample of

Asian Indians who have a high risk of diabetes; comparing them with the US NHANES population, oversampling for minorities. The high quality standardization of anthropometric measurements in both the cohorts minimizes measurement errors and biases. Despite several practical advantages of ecologic studies, including low cost, there exist several methodological limitations to any ecological study in its ability to make causal inferences.58 Ecological studies often suffer from biases (ecological fallacy or aggregation bias), which represents the failure of expected ecological effect estimates to reflect the effect at the individual level. A potential strategy suggested for minimizing ecological bias is to use smaller units in order to make the groups more homogeneous with respect to the exposure.58 For this reason, we included only non- diabetic young adults who were not underweight, which also helps minimize the effects of temporal ambiguity (presence of disease effecting body habitus) and different cohort effects between populations.

Other limitations of this study originate from the somewhat different anthropometic measurement standards, as described in the methods section. Given that these differences were small, we believe that the results are not materially biased by misclassification due to such measurement differences. The fact that CURES survey was conducted in and around the

Southern Indian city of Chennai begs the question whether these results can be generalized to the whole Asian Indian population. Given the common origins of the Indian population, we speculate that the WW may be helpful in other Indian populations as well.

We believe that our findings in this study are provocative and should stimulate further research into novel anthropometic features that may differentiate populations at very high risk for chronic disease, despite relatively low total adiposity. The findings should motivate future Pereira et al. (Confidential draft). coordinated research on complex exposures, their social and behavioral determinants, and their interventions where cross-population differences will prove as informative as similarities. The

WW should be investigated in other studies in order to address possible influences of age, ethnicity, gender and nutritional status and its relation to chronic diseases and mortality. More sophisticated clinical studies are required to address the concerns raised in the limitations above.

Also, WW should be evaluated in diverse populations to test its utility as being a risk-stratifying tool. The WW should be validated using more precise clinical methods of measuring fat depots, including DEXA and CT scan.

Much needs to be done in India from a public health standpoint to avert the looming epidemic of insulin resistance and its complications. Research59 shows that majority (71%) of type 2 diabetic subjects remain asymptomatic and opportunistic screening for diabetes would be required for early diagnosis of the disorder. A first in this regard could be to identify individuals who are at highest risk and help them reduce their vulnerability to chronic disease by diet and exercise. In certain high-risk populations, such as India and elsewhere in Asia, WW may play an important role in this process.

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