YI-CHOU CHUANG, KUANG-HUNG HSU, CHORNG-JER HWANG, PAI-MIN HU, TZU-MIAO LIN, AND WEN-KO CHIOU

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1 Waist-to-Thigh Ratio Can also be a Better Indicator Associated with Type 2 Diabetes Than Traditional Anthropometrical Measurements in Taiwan Population YI-CHOU CHUANG, KUANG-HUNG HSU, CHORNG-JER HWANG, PAI-MIN HU, TZU-MIAO LIN, AND WEN-KO CHIOU PURPOSE: Using three-dimensional (3D) scanning data along with other existing subject s medical profiles to search for better anthropometric markers in association with type 2 Diabetes Mellitus (DM). METHODS: In this cross-sectional study with 6007 subjects undergoing health examination in a period of 3 years, the authors adopted data from 3D scanning with hundreds of body measures and conducted factor analysis to search for practical indicators better associated with type 2 DM. A multiple logistic regression model was used to analyze strength of association between indicators and presence of type 2 DM. RESULTS: The trunk component derived from factor analysis was positively associated with type 2 DM, regardless of obesity status. However, lower limbs component was found to be negatively associated with type 2 DM in the same stratifications. Waist was thus found as the strongest indicator among practical measures of trunk component. The strength of association between thigh and type 2 DM was found to be the highest among practical measures of lower limbs component. A marker from taking the ratio of waist to thigh (WTR) was derived from the approach which was found to be the best indicator for association with type 2 DM while comparing to body-mass index, waist circumference, or waist hip ratio. CONCLUSION: This study offers a low-cost, noninvasive practical marker that is better associated with the presence of type 2 DM. WTR, with further study, may be used in clinical practice, epidemiological study, and preventive medicine in the future. Ann Epidemiol 2006;16: Ó 2006 Elsevier Inc. All rights reserved. KEY WORDS: Obesity, Body Mass Index, Type 2 Diabetes Mellitus, Preventive Measures. INTRODUCTION Epidemiological studies indicate that overweight and obesity increase the risk of various chronic diseases such as hypertension, diabetes mellitus (DM); coronary heart disease (CHD); stroke, sleep apnea and respiratory problems; and cancers of breast, prostate, and colon. Obesity and overweight are also associated with human longevity and increasing of all-cause mortality (1 5). Among the related From the Department Of Health Care Management, Chang Gung University, Taiwan (Y.-C.C., K.-H.H., C.-J.H., P.-M.H, T.-M.L.) and Department Of Industrial Design, Chang Gung University, Taiwan (W.-K.C.). Address correspondence to: Yi-Chou Chuang, Department of Health Care Management, Chang Gung University, No.259, Wen-Hwa 1st Rd, Kwei-Shan, Tao-Yuan, Taiwan. Tel.: , ext. 5486; fax: jane@mail.cgu.edu.tw. We are grateful for the funds (NSC P ; NSC P ; NSC P ; NSC H ; NSC H ) from the National Science Council (NSC) of Taiwan, ROC. Received April 2005; accepted July chronic diseases, DM receives more and more attentions by the facts in both clinical significance and public health importance. The medical cost of a DM patient was estimated as 2.4 times higher than that of a non-dm patient (6). The reasons for consuming high medical cost of a diabetes patient are found in the nature that DM plays as a major risk factor for death and numerous nonfatal complications (7). Currently, there are 135 million people who suffer from diabetes, and the number of sufferers is expected to rise to 300 million worldwide by the year of In the United States, people affected by DM are estimated around 18.2 million, about 6.3% of the population. According to the studies, one third of these suffers are unable to be diagnosed. In Taiwan, DM was listed as one of top ten leading causes of death for the past decades (8 10). The nationwide prevalence rate of diabetes was 7.8% in 2002, which was even higher than most of western countries. According to previous documents, most studies using body mass index (BMI) as an indicator for expressing obesity and overweight found to be significantly associated with type 2 DM. Many evidences have demonstrated that the distribution of fat was the factor directly associated with risk of developing Ó 2006 Elsevier Inc. All rights reserved /06/$ see front matter 360 Park Avenue South, New York, NY doi: /j.annepidem

2 322 Chuang et al. AEP Vol. 16, No. 5 WAIST-TO-THIGH RATIO AND TYPE 2 DM May 2006: Selected Abbreviations and Acronyms 3D Z three dimensional ANOVA Z analysis of variance AUC Z area under curve BMI Z body-mass index CHD Z coronary heart disease CI Z confidence interval CT Z computed tomography DM Z diabetes mellitus ROC Z receiver-operator-calibration curve WC Z waist circumference WHR Z waist-hip ratio WTR Z waist-thigh ratio diabetes. Visceral fat accumulation was one of the most important causes for people to get diabetes (11 15). The measures of visceral fat such as waist circumference (WC), waist-hip ratio (WHR), and waist-thigh ratio (WTR) were shown closely associated with diabetes while comparing with BMI (16 19). In addition, there are many other techniques of assessing body composition for overweight and obesity, such as dual energy X-ray absorptionmetry and computed tomography (CT) (12, 20 22). Although these techniques can precisely measure fat tissue allocation in body areas, the cost of these tools hampered the applicability. Therefore, a simple and practical anthropometrics markers, such as BMI, WC, WHR, was necessary in gathering large epidemiological data. A serial review has demonstrated that different cutpoints are required for BMI to correlate with risk of diseases in various races (23, 24). Some recent documents have also pointed out the imperfection of rationalizing the measures with the presence of diseases. Studies from various populations have shown negative correlation of thigh circumference with occurrence of diseases such as diabetes, hyperlipidemia, and possible hypertension (19, 21, 25, 26). Although the previous documents covered various ethnicities, the data from oriental populations was limited so far. The argument whether incorporating measures of thigh into the consideration for future indicator development is in need of gathering more data from diverse populations. This study has collected samples from Taiwan population in which three dimensional (3D) body surface scanning was used to collect anthropometrics measures from each examinee in department of health examination of Chang Gung Memorial Hospital, a non-profit organization (27). The perspective of this study is to construct a better anthropometrics marker, one that is practical and better associated with type-2 DM than conventional ones. The indicator derived from this study is valuable, as it was obtained from a large number of samples with comprehensive information. Therefore, the findings provide us better understanding of the mechanisms for anthropometrics markers in association with type-2 DM. METHODS Study Subjects A total of 6007 subjects (2934 men, 3073 women) were recruited from department of health examination from those who were seeking health check up annually at the Chang Gung Memorial Hospital, Taiwan. The mean age of study subjects was in a range from 17 to 95 years old. The average age of men and women was found to be similar at and 53.02, respectively. The distribution of study subjects by gender was close to half of each: males (49.1%), females (50.9%). The overall smoking rate was as high as 26.0% in this study population. The smoking rate for women was low, at 5.0%, while the prevalence of smoking for men was as high as 48.1%. The percentage of regular alcohol consumption was at the rate of 25.4%. Similar to differences in female-male rates of cigarette smoking, the rate of alcohol drinking was low in women (7.2%) and much higher (44.4%) in men. Both personal and family histories of disease were collected from medical charts and questionnaires. The prevalence of type-2 DM in this study population was 11.2%, while it was found to be 13.0% in men and 9.4% in women. The prevalence of hypertension among the study population was 31.6%, and the prevalence rate among study subject s family members was 30.6%. The personal histories of hypercholesterolemia and hypertriglyceriemia were as high as 14.4% and 14.3%, respectively. The study period covered 36 months, running from February 2000 to January Anthropometrical Parameters A three dimensional body surface measurement was performed according to the methods developed by the laboratory of Chang Gung whole body 3D Laser Scanning (see Appendix) (27). The standard scanning apparel for both men and women included light gray cotton biker shorts, and a gray sports bra for women. Latex caps were used to cover the hair on subjects heads. Standardization of measurement (see Appendix) for a total of about 280 measurement results was calculated from the scan data. Thirty-two measures were used for this study, including waist profile area, waist circumference, waist width, breast profile area, breast width, breast circumference, hip profile area, hip circumference, hip width, trunk surface area, trunk volume, body weight, volume of left leg, surface area of left leg, circumference of left leg, volume of right leg, surface area of right leg, circumference of right leg, left thigh circumference, right thigh circumference, body height, volume of left arm, surface area of left arm, circumference of left arm, volume of right arm, surface area of right arm, circumference of right arm, volume of head, surface area of

3 AEP Vol. 16, No. 5 May 2006: Chuang et al. WAIST-TO-THIGH RATIO AND TYPE 2 DM 323 head, circumference of head, and circumference of both legs. Diagnosis of Disease The diagnosis of type-2 DM was based on one of the following criteria: (1) definite history of diagnosis by physicians and shown in medical records, (2) current use of medication to control blood glucose prescribed by physicians, and (3) a fasting glucose greater than 126 mg/dl or a postprandial glucose greater than 200 mg/dl for those without history of diagnosis was defined at current health examination. The diagnostic criteria were consistent over the entire study period. Controlled Confounders Age, sex, cigarette smoking, alcohol drinking, personal history of disease, and family history of disease (such as hypertension, DM, heart disease) were collected from questionnaires or abstracted from medical charts. For those without history of hypertension, a blood pressure was measured with a mercury sphygmomanometer on the left arm after a 20-minute rest while seated. Hypertension was defined as a systolic blood pressure of 140 mmhg or greater or a diastolic blood pressure of 90 mmhg or greater (28). Statistical Analyses Continuous variables were displayed as mean (standard deviation) and categorical variables as frequency and percentage. ANOVA and Chi-square test were used to compare the differences of continuous variables and categorical variables, respectively, among different body types of study subjects. All 3D body measures were transformed with z score before statistical analyses. Factor analysis was applied to construct components derived from 32 parameters of 3D measurement. The Bartlett s test of sphericity and Kaiser-Meyer-Olkin measure of sampling adequacy were used with principle component analysis to draw conclusions on factors of body measures. In consideration of applicability, the study abstracted 16 measures with one dimension unit such as centimeter for further analyses of anthropometrics markers. A multiple logistic regression was used to derive strength of association between each component and prevalence of type 2 DM expressed in odds ratio controlling by variables of age, cigarette smoking, alcohol drinking, personal history of diseases (hypercholesterolemia and hypertriglyceridemia), and family history of diseases (such as hypertension, and DM). A receiveroperator calibration curve (ROC) was used to compare the predictivity of indicators associated with type 2 DM. The area under curve (AUC) was calculated to differentiate accuracy among indicators. Tests were carried out by bootstrapping. The SPSS 11.0 was used as statistical software for the analyses of the research. RESULTS Descriptive Epidemiology The age of this study population is centered at of age, with 78% of the samples ranged from 40 to 69. The age distribution between men and women was similar. Traditional body measures such as BMI and WHR were measured to shown the characteristics of anthropometrical body shape in different stratum of age-gender specific group. The BMI of this study population was in the average of 24.91, with standard deviation of 3.48, ranged from to (data not shown). The average BMI in men was 25.2 higher than women s (p Z 0.000). Both BMI and WHR were likely to increase while age was increasing (Table 1). Factor Analysis Factor analysis on the three dimensional body surface measures was demonstrated in Table 2. There were five dimensions abstracted from 32 measures. The description was in the order of percentage of variation. The first TABLE 1. Age-gender specific anthropometric measures of BMI and WHR Variables Males (n Z 2934) Females (n Z 3073) Total (n Z 6007) Age n (%) BMI Mean (SD) WHR Mean (SD) n (%) BMI Mean (SD) WHR Mean (SD) n (%) BMI Mean (SD) WHR Mean (SD)!20 2 (0.1) (4.93) 0.81 (0.051) 4 (0.1) 19.8 (1.14) 0.78 (0.016) 6 (0.1) (3.30) 0.78 (0.036) (2.5) (3.85) 0.83 (0.064) 98 (3.2) (3.21) 0.82 (0.076) 172 (2.9) (3.59) 0.82 (0.071) (9.5) (3.38) 0.87 (0.064) 251 (8.2) (3.29) 0.83 (0.056) 531 (8.8) (3.49) 0.85 (0.064) (26.4) (3.34) 0.90 (0.067) 845 (27.5) (3.54) 0.84 (0.066) 1619 (27.0) (3.53) 0.87 (0.071) (28.2) (3.058) 0.92 (0.065) 978 (31.8) (3.33) 0.88 (0.073) 1805 (30.0) (3.21) 0.89 (0.073) (21.4) (3.087) 0.92 (0.067) 622 (20.2) (3.77) 0.92 (0.076) 1249 (20.8) (3.46) 0.92 (0.072) O (11.9) (3.23) 0.94 (0.076) 275 (8.9) (3.77) 0.94 (0.087) 625 (10.4) (3.46) 0.94 (0.081) Subtotal 2934 (48.8) (3.24)* 0.91 (0.071) y 3073 (51.2) (3.67)* 0.88 (0.081) y (3.48) 0.89 (0.078) *p Z.000 with two sample t-test of BMI between genders. y p Z.000 with two sample t-test of WHR between genders.

4 324 Chuang et al. AEP Vol. 16, No. 5 WAIST-TO-THIGH RATIO AND TYPE 2 DM May 2006: TABLE 2. Factor analysis of 3D body surface measures Variables Components Original values Mean (SD) Factors (% of variation) Waist profile area (cm 2 ) (142.01) Trunk (56.89%) Waist circumference (cm) (10.95) Waist width (cm) (3.11) Trunk volume (cm 3 ) ( ) Breast profile area (cm 2 ) (114.17) Body weight (Kg) (11.04) Breast width (cm) (2.54) Hip profile area (cm 2 ) (98.71) Hip circumference (cm) (6.85) Trunk surface area (cm 2 ) (829.77) Breast circumference (cm) (11.45) Hip width (cm) (2.17) Left leg volume (cm 3 ) ( ) Lower limbs (9.71%) Right leg volume (cm 3 ) ( ) Left leg surface area (cm 2 ) (250.54) Right leg surface area (cm 2 ) (253.20) Left thigh circumference (cm) (4.69) Right thigh circumference (cm) (4.68) Right leg circumference (cm) (3.06) Left leg circumference (cm) (3.06) Body height (cm) (8.29) Body height (8.29%) Right upper arm circumference (cm) ÿ (3.92) Upper limbs (5.01%) Left upper arm circumference (cm) ÿ (4.05) Right far arm circumference (cm) ÿ (2.63) Left far arm circumference (cm) ÿ (2.67) Left arm volume (cm 3 ) ÿ (451.29) Right arm volume (cm 3 ) ÿ (460.73) Left arm surface area (cm 2 ) ÿ (168.76) Right arm surface area (cm 2 ) ÿ (168.19) Head volume (cm 3 ) (469.71) Head (3.61%) Head surface area (cm 2 ) (103.08) Head circumference (cm) (2.04) dimension was called the trunk component, which consisted of waist measures, breast measures, hip measures, trunk measures, and body weight. The second dimension was named the lower limbs component, which was formed with leg and thigh. The third dimension consisted of only one measure of body height. The forth dimension was named the upper limbs component, which was constructed from arm measures such as volume, surface area, and circumference of both arms. The fifth dimension of this study was termed the head measures and was based on volume, surface area, and circumference of the head. Searching For Anthropometrics Markers By using BMI cutoff points suggested by Department of Health of Taiwan to perform multiple logistic regression analysis of anthropometrics measures with prevalence of type 2 DM, the study has categorized subjects into three body types: normal (BMI < 24), overweight (24! BMI < 27), and obese (BMIO27). The significant associations were found in the parts of trunk and lower limbs. Among the measures of trunk, waist circumference has shown higher association with prevalence of type 2 DM than other measures. Both right and left thigh circumference measures were significantly more highly associated with type 2 DM among measures of lower limbs. The strength of association was found higher in the right thigh circumference than that of the left thigh (Table 3). Stratified analyses with tertiles of both waist circumference and right thigh circumference were found to have interactive effects on odds ratio of type 2 DM. The status of type 2 DM was observed as the highest among subjects with high tertiles of waist circumference and low tertiles of right thigh circumference, the odds ratio of this particular population was 15.02, 15.59, and in total population, male subjects, and female subjects, respectively (Table 4). Comparison Among Indicators In accordance, WTR was consequently constructed from Table 4 because the reverse correlation with type 2 DM was observed on waist circumference and right-thigh

5 AEP Vol. 16, No. 5 May 2006: Chuang et al. WAIST-TO-THIGH RATIO AND TYPE 2 DM 325 TABLE 3. Multivariate-adjusted odds ratio for each normalized 3D indicator with prevalence of type 2 diabetes among three different body size! O27.00 BMI Odds Ratio* (95% CI) Odds Ratio* (95% CI) Odds Ratio* (95% CI) Trunk Waist circumference (cm) (1.064, 1.696)* (1.106, 1.857) y (1.518, 2.265) y Waist width (cm) (0.984, 1.538) (0.901, 1.509) (1.420, 2.135) y Breast width (cm) (1.039, 1.624)* (1.171, 1.841) y (1.395, 2.017) y Hip circumference (cm) (0.693, 1.091) (0.525, 0.928)* (0.964, 1.302) Breast circumference (cm) (0.973, 1.396) (0.846, 1.276) (1.120, 1.469) y Hip width (cm) (0.644, 0.957)* (0.691, 1.037) (1.041, 1.408)* Lower limbs Left thigh circumference (cm) (0.403, 0.600) y (0.334, 0.542) y (0.709, 1.008) Right thigh circumference (cm) (0.385, 0.577) y (0.320, 0.519) y (0.721, 1.018) Right leg circumference (cm) (0.588, 0.872) y (0.759, 1.129) (0.972, 1.342) Left leg circumference (cm) (0.581, 0.854) y (0.827, 1.233) (0.984, 1.363) Body height (cm) (0.859, 1.229) (0.948, 1.333) (1.060, 1.450) y Upper limbs Right upper arm circumference (cm) (0.660, 0.969)* (0.786, 1.058) (0.966, 1.288) Left upper arm circumference (cm) (0.676, 0.983)* (0.804, 1.172) (0.965, 1.293) Right far arm circumference (cm) (0.764, 1.099) (0.815, 1.207) (0.893, 1.249) Left far arm circumference (cm) (0.767, 1.098) (0.840 Z 1.240) (0.914, 1.271) Head Head circumference (cm) (0.674, 0.917) y (0.739, 1.013) (0.805, 1.071) Multivariate-adjusted odds ratios with variables of age, cigarette smoking, alcohol drinking, personal history of diseases (hypercholesterolemia and hypertriglyceridemia), and family history of diseases (such as hypertension and DM). *p value!.05 with two-sided test. y p value!.01 with two-sided test. circumference. While comparing with frequently used indicators such as BMI, WC, and WHR, the data has demonstrated that WTR was best correlated with type 2 DM. The area under curve of WTR, WHR, WC, and BMI that was analyzed in males was 0.749, 0.675, 0.634, and 0.574, while 0.775, 0.727, 0.683, was the area in females, respectively. The statistical test of AUC of all indicators was significant, with null hypothesis of AUC Z 0.5 (p! ) (Fig. 1A& 1B). The multivariate-adjusted odds ratios of type 2 DM with selected indicators, such as BMI, WC, WHR, and WTR, were 1.176, 1.354, 1.431, and 1.811, respectively. The strength of association among four indicators with type 2 DM was found to be the highest in WTR for both genders (Table 5). DISCUSSION In the beginning of this study, we tried to find the association of type 2 DM with hundreds of measurements determined by 3D body surface scanning. Then, through the process of exploring the association of the body shape (macro-measures) with type 2 DM, to consolidating the measures to micro-level, such as waist and thigh circumference, to investigating the relationship with type 2 DM; an indicator-wtr was found to associate highly with type 2 DM. The findings on association of WTR with type 2 Diabetes were beyond our expectations but coincident with previous reports from other ethnicity groups (21, 25, 29, 30). TABLE 4. Stratified analyses on multivariate-adjusted odds ratios by tertiles of waist circumference and right thigh circumference Waist circumference (Tertiles) Right thigh circumference (Tertiles) Total High Median Low Low * 0.39 II (0.13, 1.23) 4.20 II (1.82, 9.69) Median 1.53 (0.61, 3.79) 3.17 II (1.34, 10.49) II (5.45, 28.80) High 6.75 II (2.95, 5.43) II (4.78, 25.32) II (6.45, 34.96) Males High Median Low Low * 0.65 (0.15, 2.74) 4.75 II (1.47, 15.40) Median 1.32 (0.36, 4.80) 4.32 y (1.31, 14.28) II (3.96, 41.73) High 6.07 II (1.88, 9.57) II (3.56, 37.43) II (4.66, 52.13) Females High Median Low Low * 0.14 (0.02, 1.30) 3.22 (0.97, 10.70) Median 1.74 (0.48, 6.25) 1.67 (0.46, 6.00) II (3.69, 38.85) High 7.36 II (2.29, 3.71) 9.86 II (3.02, 32.22) II (4.62, 49.50) *Reference group. y p value!.05 with two-sided test. II p value!.01 with two-sided test.

6 326 Chuang et al. AEP Vol. 16, No. 5 WAIST-TO-THIGH RATIO AND TYPE 2 DM May 2006: FIGURE 1. A ROC curve of DM among 4 indicators of BMI, WC, WHR, and WTR in males. -B ROC curve of DM among 4 indicators of BMI, WC, WHR, and WTR in females. Overweight and obesity have become serious public health issues worldwide, and these issues were investigated and found to be highly associated with numerous metabolic complications, such as DM, dysfunctional lipidemia, and cardiovascular diseases (2 5, 17). To manage overweight/ obesity and DM is becoming a major issue for the government s health administration in most developed countries. In clinical practice, there is no accurate and precise measure existed for body composition. Although indicators such as BMI, WC, and WHR are frequently used by health practitioners to evaluate a person s health, many studies have shown that the cutoff points of these anthropometrical measures were varied across ethnic groups and in need of further revisions (20, 23, 24, 31, 32). BMI seems to have limitations in interpretation of association between obesity and its related diseases due to its inadequacy on representing body fat. Some researches have shown that a high proportion of abdominal fat, particularly visceral fat, is a major risk factor for type 2 DM and coronary heart disease (12 15, 33). Waist circumference and WHR are frequently used to estimate the abdominal adipose tissue. Waist circumference provides a crude index for absolute amount of abdominal adipose tissue, whereas WHR provides index for relative accumulation of abdominal fat to a reference size of body. Although high imaging techniques, such as CT, can distinguish visceral fat from subcutaneous fat, they are too costly to apply in clinical settings as a screening tool for potential patients. Studies found a simple measurement, WC, was the best anthropometric variable to proximate the amount of visceral fat (34, 35). A study of fat distribution by Janssen and his colleagues found the combination of BMI and WC explained a greater variance in nonabdominal fat (total fatÿabdominal fat), abdominal subcutaneous, and visceral fat than did either BMI or WC alone in white men and women. Waist circumference was reported more closely related to cardiovascular disease than BMI in Whites (36) and was a better predictor than BMI of CHD risk in overweight premenopausal women (37). Because WC is related to many risk factors of chronic diseases, physicians favor using WC as a part of physical examination in their office practices (18). However, WC is considered as one of the absolute values without correction of body size. Further modification in order to reflect better association with DM was rooming for future researches. In our study, the use of 3D scanning technology to classify body shape has advantages over traditional anthropometrical measurements. First, it reduces guesswork on determining which body parts to be measured. Second, it TABLE 5. Comparison of multivariate-adjusted odds ratios among indicators of BMI, WC, WHR, WTR (after normalization (z transformation)) Male Female Total Odds Ratio (95% CI) p value Odds Ratio (95% CI) p value Odds Ratio (95% CI) p value BMI (1.053, 1.341) (1.047, 1.353) (1.078, 1.283).000 WC (1.239, 1.641) (1.113, 1.446) (1.233, 1.487).000 WHR (1.305, 1.687) (1.231, 1.625) (1.304, 1.570).000 WTR (1.760, 2.310) (1.442, 1.925) (1.64, 1.997).000 *Multivariate-adjusted odds ratios (95% CI for OR) controlled with variables of age, cigarette smoking, alcohol drinking, personal history of diseases (hypercholesterolemia and hypertriglyceridemia), and family history of diseases (such as hypertension and DM).

7 AEP Vol. 16, No. 5 May 2006: Chuang et al. WAIST-TO-THIGH RATIO AND TYPE 2 DM 327 reduces measuring variability produced from observer bias (27). Third, the data and indicators discovered by this process are deemed as more reliable and representative for association between the indicators and type 2 DM. In this study, WTR was abstracted from body parts and has proven to be associated with type 2 DM more often than currently established markers, such as BMI, WC, and WHR. The applications and physiological significance are both justified and warranted for future usage. There are various documents providing mechanisms for interpreting the association between WC and type 2 DM. The measurement of thighs proposed by Snijder and his colleagues was found to be negatively correlated with type 2 DM and was evidenced by various ethnic groups (19, 21, 25, 30, 38). The thigh circumference in this study was measured in the middle line of thigh, which was performed by a 3D scanner with calculations made by computer software (27). This method of measuring thigh circumference was deemed to be similar to previous documents. Should there be any discrepancy between our measuring and that of others, the bias is categorized as nondifferential misclassification among our study groups. The observation on association between thigh circumference and type 2 DM were found coincident with previous documents; however, further explanations were warranted. From our perspectives, the thigh circumference represents both the subcutaneous fat of lower limbs and the muscular enlargement effected by exercise. The latter demonstrated the role of exercise on occurrence of type 2 DM and the impact of adipose tissue distribution on insulin resistance. Seidell and his colleagues have demonstrated that the main target organ for insulin and site of insulin resistance were found in skeletal muscles. Hips, thighs, and legs were highly correlated with each other and counted as the largest portion of body skeletal muscle. Therefore, narrow hips or small legs/thighs were related to higher levels of insulin resistance (39, 40). Since the measures of hips were confounded anatomically by the lower part of the pelvis, the measures of thighs were considered more advantageous than those of hips in association with type 2 DM. Exercise was reported as a key factor of weight control in general. However, previous documents have proposed that the subsequent weight loss by increasing exercise was only one sufficient dimension for circulatory fitness from a host of factors, such as controlling calorie diet, increasing physical activity, and positive behavior changes (41, 42). A variation occurred depending on how these factors were clustered in the same person. In addition, evidence showed that exercise could improve the metabolic rate and transportation of blood glucose into cells, hence decreasing the risk of metabolic diseases. The possible reason for WTR to be a better indicator than BMI, WC, or WHR in association with type 2 DM is that WTR is a represantative for the result of interaction between exercises, behaviors, and the clustering factors. Although the findings of this study are impressive in many ways, the study has some limitations to be addressed. First, the design itself lent itself to cross-sectional data collection. A study demonstrating that weight loss due to exercise effected a reduction of adipose tissue of experimental subjects provided causative explanations for our observations (22). A prospective design for subjects with longitudinal changes on either waist circumference or thigh circumference was required for confirmation of the findings. Second, the samples were subjected to ethnical constraints; namely, the population was primarily from Chinese/ Taiwanese tributes. The generalizability of the findings should be viewed with caution but considered worthy of indepth studies. A series of studies showing similar results from different ethnicities gave the evidence of coherence for the findings (21, 25, 30). Third, although the 3D surface scanning was an indirect measure of adipose tissue distribution in circumference markers of this study, the same limitation existed in all currently used makers, such as BMI, WC, and WHR. However, costly and invasive methods, such as CT scanning and MRI, presented some practical problems. In practice, WTR seems to be a better marker than most well known markers for association with type 2 DM. CONCLUSION Through the analyses of body shape to specific anthropometric measurements determined by highly precise 3D scanning, the study has demonstrated that WTR is a better indicator than BMI, WC, and WHR in constructing an association between anthropometric measures and type 2 DM. Thus, WTR can be used as an inexpensive screening tool for approximating unhealthy body shapes and hence to provide clues for future preventive medicine.

8 328 Chuang et al. AEP Vol. 16, No. 5 WAIST-TO-THIGH RATIO AND TYPE 2 DM May 2006: APPENDIX The process for 3D scanning: 1. Remove all outer clothes except for underwear preparing for scanning (women with bras in addition to pants). 2. Stand still on the stage for scanning. The definition of the size calculation of 3D human body data (32 Sizes) No. 3D Anthropometrics Definition 1 Head circumference The length of the horizontal section profile on the most protrusion of forehead, which is processed as a convex hull. 2 Breast circumference The length of the horizontal section profile on the most protrusion of breast, which is processed as a convex hull. 3 Waist circumference The length of the horizontal section profile on the belly button, which is processed as a convex hull. 4 Hip circumference The length of the horizontal section profile on the most protrusion of hip, which is processed as a convex hull. 5 Left upper arm circumference The length of the section profile on middle point of left upper arm, which is perpendicular to the axis of humerus and processed as a convex hull. 6 Right upper arm circumference The length of the section profile on middle point of right upper arm, which is perpendicular to the axis of humerus and processed as a convex hull. 7 Left far arm circumference The length of the section profile on middle point of left forearm, which is perpendicular to the axis of left forearm and processed as a convex hull. 8 Right far arm circumference The length of the section profile on middle point of right forearm, which is perpendicular to the axis of right forearm and processed as a convex hull. (continued)

9 AEP Vol. 16, No. 5 May 2006: Chuang et al. WAIST-TO-THIGH RATIO AND TYPE 2 DM 329 APPENDIX (continued) No. 3D Anthropometrics Definition 9 Left thigh circumference The length of the horizontal section profile on 2/3 height. of left thigh, which is processed as a convex hull. 10 Right thigh circumference The length of the horizontal section profile on 2/3 height of right thigh, which is processed as a convex hull. 11 Left leg circumference The length of the horizontal section profile on 2/3 height of left leg, which is processed as a convex hull. 12 Right leg circumference The length of the horizontal section profile on 2/3 height of right leg, which is processed as a convex hull. 13 Breast width The width of the horizontal section profile on the most protrusion of breast, which is processed as a convex hull. 14 Waist width The width of the horizontal section profile on the belly button, which is processed as a convex hull. 15 Hip width The width of the horizontal section profile on the most protrusion of hip, which is processed as a convex hull. 16 Breast profile area The area of the horizontal section profile on the most protrusion of breast, which is processed as a convex hull. 17 Waist profile area The area of the horizontal section profile on the belly button, which is processed as a convex hull. 18 Hip profile area The area of the horizontal section profile on the most protrusion of hip, which is processed as a convex hull. 19 Head volume The summation of the area of horizontal section profiles of head multiplied by the height of sectional profiles. 20 Head surface area The summation of the length of horizontal section profiles of trunk multiplied 21 Trunk volume The summation of the area of horizontal section profiles of trunk multiplied by the height of sectional profiles. 22 Trunk surface area The summation of the length of horizontal section profiles of trunk multiplied 23 Left arm volume The summation of the area of horizontal section profiles of left arm multiplied 24 Left arm surface area The summation of the length of horizontal section profiles of left arm multiplied 25 Right arm volume The summation of the area of horizontal section profiles of right arm multiplied 26 Right arm surface area The summation of the length of horizontal section profiles of right arm multiplied 27 Left leg volume The summation of the area of horizontal section profiles of left leg multiplied by the height of sectional profiles. 28 Left leg surface area The summation of the length of horizontal section profiles of left leg multiplied 29 Right leg volume The summation of the area of horizontal section profiles of right leg multiplied 30 Right leg surface area The summation of the length of horizontal section profiles of right leg multiplied 31 Body height The length of vertical distance between the calvaria and standing ground. 32 Body weight The vertical force exerted by a mass as a result of gravity.

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