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ORIGINAL RESEARCH COMMUNICATION |
1 From the Department of Human Nutrition and Division of Epidemiology and Biostatistics, University of Illinois at Chicago (YW); the Departments of Nutrition and Epidemiology, Harvard School of Public Health, Boston (EBR, FBH, MJS, and WCW); the Channing Laboratory, Department of Medicine, Harvard Medical School and Brigham and Women's Hospital, Boston (MJS, WCW, and EBR).
2 Supported by the National Institutes of Health (CA55075, HL35464, HL65582, and P30DK064408). YW was supported in part by NIH grant R01DK63383. 3 Address reprint requests to Y Wang, Center for Human Nutrition, Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, 615 North Wolfe Street, Baltimore, MD 21205. E-mail: youfwang{at}uic.edu.
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Objective: The objective was to compare body mass index (BMI), WC, and WHR in predicting type 2 diabetes.
Design: A prospective cohort study (Health Professionals Follow-Up Study) of 27 270 men was conducted. WC, WHR, and BMI were assessed at baseline. Covariates and potential confounders were assessed repeatedly during the follow-up.
Results: During 13 y of follow-up, we documented 884 incident type 2 diabetes cases. Age-adjusted relative risks (RRs) across quintiles of WC were 1.0, 2.0, 2.7, 5.0, and 12.0; those of WHR were 1.0, 2.1, 2.7, 3.6, and 6.9; and those of BMI were 1.0, 1.1, 1.8, 2.9, and 7.9 (P for trend < 0.0001 for all). Multivariate adjustment for diabetes risk factors only slightly attenuated these RRs. Adjustment for BMI substantially attenuated RRs for both WC and WHR. The receiver operator characteristic curve analysis indicated that WC and BMI were similar and were better than WHR in predicting type 2 diabetes. The cumulative proportions of type 2 diabetes cases identified according to medians of BMI (
24.8), WC (94 cm), and WHR (0.94) were 82.5%, 83.6%, and 74.1%, respectively. The corresponding proportions were 78.9%, 50.5%, and 65.7% according to the recommended cutoffs.
Conclusions: Both overall and abdominal adiposity strongly and independently predict risk of type 2 diabetes. WC is a better predictor than is WHR. The currently recommended cutoff for WC of 102 cm for men may need to be reevaluated; a lower cutoff may be more appropriate.
Key Words: Obesity • abdominal adiposity • waist circumference • waist-to-hip ratio • body mass index • type 2 diabetes
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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A growing consensus suggests that WC should be used rather than WHR to assess fat distribution (11–15). In a recent statement by the National Institutes of Health and the North American Association for the Study of Obesity, WHR was said to provide no advantage over WC alone (11); a WC cutoff of 40 inches (102 cm) for men and of 35 inches (88 cm) for women were recommended. However, this issue remains inconclusive. For example, the Iowa Women's Health Study, a 12-y prospective cohort study of 31 702 Iowa women aged 55–69 y who were free of cancer, heart disease, and diabetes at baseline, indicated that WHR is a better anthropometric predictor of total mortality than are BMI and WC (16). In a 9-y study that followed a large cohort (n = 12 814) of African-American and white men and women, Stevens et al (17) reported that WC, WHR, and BMI were equivalent in their ability to predict type 2 diabetes. Another important issue concerns the appropriate cutoffs for elevated WC. The cutoffs for WC (102 cm for men and 88 cm for women) and WHR (0.95 for men and 0.88 for women) were recommended by the American Heart Association (18) and the US Department of Agriculture (19). However, lower WC cutoffs of 94 cm for men and of 80 cm for women have also been suggested (20–22).
To look into this question further, we compared the predictive power of WC, WHR, and BMI in diagnosing type 2 diabetes in a large cohort of men (The Health Professionals Follow-Up Study) and evaluated the effect of different cutoffs for WC, WHR, and BMI. We also studied the independent and additive associations of overall obesity (reflected by BMI) and abdominal adiposity (WC and WHR) with risk of type 2 diabetes.
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SUBJECTS AND METHODS |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Diagnosis of type 2 diabetes
A supplementary questionnaire regarding symptoms, diagnostic tests, and hypoglycemic therapy was mailed to men who indicated on any biennial questionnaire that they had been diagnosed with diabetes. A case of diabetes was considered confirmed if at least one of the following was reported on the supplementary questionnaire: 1) one or more classic symptoms (excessive thirst, polyuria, weight loss, or hunger) plus a fasting plasma glucose concentration of 140 mg/dL (7.8 mmol/L) or a random plasma glucose concentration of 200 mg/dL (11.1 mmol/L), 2) 2 elevated plasma glucose concentrations on different occasions [fasting concentration of 140 mg/dL (7.8 mmol/L), random concentration of 200 mg/dL (11.1 mmol/L), or concentration 200 mg/dL after 2 h of oral-glucose-tolerance testing] in the absence of symptoms, or 3) treatment with hypoglycemic medication (insulin or oral hypoglycemic agent).
Our criteria for diabetes classification are consistent with those proposed by the National Diabetes Data Group (23) for 1986–1996. The validity of self-report of type 2 diabetes has been verified in a subsample of 71 men from the Health Professionals Follow-Up Study cohort (24). A physician blinded to the information reported on the supplementary questionnaire reviewed the medical records according to the diagnostic criteria. Of the 59 cases with complete medical records, the diagnosis of type 2 diabetes was confirmed in 57 (97%). One patient denied the diagnosis and another lacked evidence of diabetes in his submitted records. Similarly, 98% of diabetic cases reported by the supplementary questionnaire were confirmed by medical record review in a subsample of participants (n = 62) in the Nurses' Health Study (25).
Anthropometric measures
Self-reported body weights and heights were recorded at baseline in 1986, and self-reported body weights alone were reported in later biennial questionnaire surveys. Information on WC and HC was collected in a brief follow-up questionnaire sent out in 1987 and was collected again in 1996. We included paper tape measures, detailed instructions, and illustrations to assist the men in self-reporting their WC and HC. The participants were instructed to take measurements while standing and to avoid measuring over bulky clothing. The subjects were asked to measure their WCs at the umbilicus and to take their hip measures as the largest circumference between the waist and thighs. Along with the directions, illustrations were included (5). Self-reported waist, hip, and weight measures were found to be reasonably valid when compared with standardized measurements by a technician in a subset of this cohort (26). The crude Pearson's correlation coefficient between self-reported and measured WC was 0.95; the analogous correlation for HC was 0.88. The differences in mean circumference (measured – reported measure) were 0.91 cm (0.36 inches) for the waist and –1.98 cm (–0.78 inches) for the hip. The correlation between measured and self-reported WHR was 0.69 with a mean difference of 0.027. Self reported and measured weights were strongly correlated (r = 0.97), and the difference (–1.06 kg, or –2.34 lb) was relatively small (26). We calculated BMI [weight (kg)/height squared (m)]) and WHR [waist(cm)/hip(cm)] for each subject.
Assessment of other main covariates
The measurements of other main covariates and potential confounders (such as age, dietary intake, smoking, physical activity, family history of type 2 diabetes, and alcohol consumption) that were collected during the questionnaire-based follow-up were described elsewhere (24). Physical activity, smoking, and alcohol consumption were assessed every 2 y, and information on dietary intake was collected every 4 y.
Statistical analysis
We calculated incidence rates and age-adjusted RRs according to the WC and WHR quintiles. Person-time for each participant was calculated from the date of return of the 1987 questionnaires to the date of type 2 diabetes diagnosis, death from any cause, or 31 January 2000, whichever came first. Incidence rates of type 2 diabetes were obtained by dividing the number of cases by person-years in each category of WC, WHR, or BMI. Age-adjusted RRs were computed as the incidence rate in a specific category of WC and WHR divided by that in the reference category, with adjustment for 5-y age categories. Tests for linear trend across increasing categories of WC and WHR were conducted by treating the categories as a continuous variable with the use of the midpoint value for each category.
Next, using Cox proportional hazards models, we estimated multivariate-adjusted RRs for the whole sample and stratified the results by age (<65 or 65), BMI (<25 or 25), and family history of type 2 diabetes (yes or no). In the Cox models, we adjusted simultaneously for potential confounders, including age (40–44, 45–49, 50–54, 55–59, 60–64, 65–69, and 70 y), smoking [never, past, or current (1–14, 15–24, or 25 cigarettes/d)], alcohol consumption (0–4, 5–9, 10–14, 15–29, or 30 g/d), parental history of diabetes, physical activity (quintiles), cereal fiber intake (quintiles), and trans fat intake (quintiles). In further analyses, we included updated BMI (<23, 23–24.9, 25–26.9, 27–29.9, or 30) in the models. Note that in our analysis we also tested glycemic load and the ratio of polyunsaturated to saturated fat as potential confounders, but they were not confounders and thus were not controlled for.
To assess the joint and independent effects of overall obesity (assessed with BMI) and central obesity (WC and WHR) on the risk of type 2 diabetes, we fit Cox models stratified by BMI categories (< 25, 25–29, or 30). Considering the cutoffs recommended for WHR and WC and the distribution of the study sample, the categories of >0.90, 0.90–0.94, and 0.95 were used for WHR, and <90, 90–99, and 100 were used for WC (cm). Thus, on the basis of these BMI and WC categories, the subjects were classified into 9 groups, which were coded with 8 dummy variables. We included these variables in the Cox models along with other potential confounders to estimate the adjusted RRs. Then, similar analyses were conducted to test the joint and independent effects of BMI and WHR.
Finally, we compared the predictive power of baseline WC, WHR, and BMI deciles on risk of type 2 diabetes through receiver operator characteristic (ROC) curve analysis (27). ROC curve is a graphic representation of the relation between sensitivity and specificity for a diagnostic test. It provides a simple tool for comparing the predictive power of different tests or measures, which can assist with the choice of one test over the others. ROC curves are drawn by plotting the sensitivity (true-positive rate) against the false-positive rate (1 – specificity) for several measures or choices. The measure with a ROC curve that is closest to the upper left corner has the highest sensitivity and specificity and, thus, is the best measure. All data analyses were performed with SAS (version 8.2; SAS Inc, Cary, NC).
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RESULTS |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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, Table 2 , and Table 3, respectively. Participants with higher WC, WHR, or BMI values tended to be older, were less active, and were more likely to have hypertension and high cholesterol. As expected, BMI and WC were positively correlated, as were BMI and WHR.
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. The risk of diabetes was already significant at the second decile for both WC and WHR and increased more dramatically from the 9th to the 10th decile. A high WC (upper decile) was a strong risk factor for type 2 diabetes (RR: 20.4; 95% CI: 12.3, 33.8), which was much higher than that for the WHR decile (RR: 8.7; 95% CI: 5.8, 13.0) or BMI (RR: 16.5; 95% CI: 10.4, 26.3).
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, the age-adjusted RRs across quintiles of WC at baseline were 1.0, 2.0, 2.7, 5.0, and 12.0, respectively (P for trend < 0.0001). Further adjustment for physical activity, smoking, parental history of diabetes, dietary intakes of trans fat and cereal fiber, and other covariates only slightly attenuated these RRs. This positive association between WC and the risk of type 2 diabetes remained strong even after adjustment for current BMI (updated in each survey year). RRs across quintiles of WC were 1.0, 1.7, 2.0, 3.0, and 4.5, respectively (P for trend < 0.0001).
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). The age-adjusted RRs across quintiles of WHR were 1.0, 2.1, 2.7, 3.6, and 6.9 (P for trend < 0.0001). Adjustment for potential confounders did not change these RRs materially. Further adjustment for current BMI attenuated the association considerably, but the RRs (1.6, 2.0, 2.1, and 2.8) remained significant (P < 0.001).
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). The association was weaker than that for WC but was stronger than that for WHR. The age-adjusted RRs across BMI quintiles were 1.0, 1.1, 1.8, 2.9, and 7.9 (P for trend < 0.001). Adjustment for potential confounders only changed the RRs slightly. Further adjustment for baseline WC attenuated the association considerably, whereas adjustment for baseline WHR resulted in much smaller changes in the RRs. For example, with these adjustments, the RR for the top BMI quintile dropped from 7.9 to 6.5, 2.7, and 4.8, respectively.
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The joint relation between overall (BMI) and abdominal (WC and WHR) adiposity and risk of type 2 diabetes is shown in Figure 2. Those with a BMI < 25 and a WHR < 0.90 were the reference group. Within each BMI category (<25, 25–29, and 30), increased WC (<90, 90–99, and 100) predicted a greater risk of type 2 diabetes. The RR increased from 1.0 to 2.4 in those with a BMI < 25, from 2.2 to 5.9 in those with a BMI of 25-29, and from 6.1 to 14.9 in those with a BMI 30. Similar patterns were observed for WHR.
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25 or 30), WC (102 cm), and WHR (0.95). The subjects were separated into 8 exclusive groups in which each group had 0, 1, 2, or 3 of the 3 features. Seven dummy variables were created to represent these groups and were tested in a Cox model with adjustment for potential confounders. As shown in Figure 3, men who had both a high BMI (eg, 25) and a high WC (102 cm) had the highest risk (RR: 8.7), compared with those who had low BMI and WC, but they had an increased risk almost identical to that in those who also had a WHR 0.95 (RR: 8.6); ie, for those with a high BMI and WC, WHR added no predictive power. In general, participants who had a high BMI or a high WC had similar increased risks of type 2 diabetes.
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) indicate that WC and BMI were similar, but were better than WHR in predicting type 2 diabetes. The cumulative proportion (%) of type 2 diabetes cases that could be identified according to BMI, WHR, and WC deciles is shown in Table 7. If the medians of BMI (24.8), WC (94 cm), and WHR (0.94) were used, 82.5%, 83.6%, and 74.1%, respectively, of the type 2 diabetes cases could be identified. In contrast, if the currently recommended cutoffs (ie, 25 for BMI, 102 cm for WC, and 0.95 for WHR) were used, the proportions would be 78.9%, 50.5%, and 65.7%, respectively. We also calculated the population-attributable fractions for these cutoffs, which were 54.6%, 34.5%, and 35.1%, respectively.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Controversies remain regarding the cutoffs for WC that should be used in clinical practice. The influence of abdominal fatness on a health risk such as type 2 diabetes is a continuous one, and, thus, any cutoffs are arbitrary (17). Our findings and those of others suggest that the current recommended WC cutoffs in the United States need to be reevaluated in light of this new evidence. A lower WC cutoff (eg, 95 rather than 102 cm) for men may be more appropriate. Lower WC cutoffs have been recommended by other researchers. Most recently, on the basis of findings from the third National Health and Nutrition Examination Survey, Zhu et al (22) recommended cutoffs of 90 cm for men and 83 cm for women. They examined the associations between WC, BMI, and obesity-associated risk factors such as low HDL cholesterol, high LDL cholesterol, high blood pressure, and high glucose in white study participants and found that the WC (cm) cutoffs that corresponded to the ORs of BMI of 25 and 30 were 90 and 100 for men and 83 and 93 for women, respectively. Previously, Lean et al (21) proposed the use of the following categories to indicate low risk, increased risk, and substantially increased risk, respectively: <94 cm, 94–101 cm, and 102 cm for men and <80 cm, 80–87 cm, and 88 cm for women. These cutoffs were based on data collected in a random sample of 2183 men and 2698 women aged 20–59 from the Netherlands (20, 21) and were adopted in a World Health Organization (35).
We found that only 
66% of the type 2 diabetes cases had a WC 102 cm, the recommended cutoff for elevated WC (Table 7
). The WC cutoff that corresponds to a BMI of 25 (a widely accepted classification of overweight) was 95 cm in this cohort, and 80% of the type 2 diabetes cases had a WC 95 cm. The population-attributable fractions for a BMI of 25 and a WC of 102 cm were 54.6% and 34.5%, respectively. A WC of 102 cm corresponds to the lower limit of the upper quintile, ie, only 20% of our subjects had central obesity according to this cutoff. In contrast, about half of the subjects were overweight or obese (BMI 25).
We also tested the independent and joint effects of abdominal adiposity (measured with WC and WHR) and overall body fatness (BMI). Baseline BMI was correlated with WC (r = 0.77) and WHR (r = 0.64) in this cohort (note that these correlations might be weaker than those in other reports because BMI was measured 1 y earlier than WC and WHR). When all 3 baseline anthropometric measures (BMI, WC, and WHR) were included in the model simultaneously, they remained significant predictors of risk of type 2 diabetes. In our multivariate analysis we controlled for updated BMI, but the adjustment only moderately attenuated the RRs for type 2 diabetes across categories of these WC and WHR measures. Our stratified analyses (Figure 2) showed that the risk increased with WC or WHR within each category of baseline BMI (<25, 25–30, and 30). Subjects who had both a high BMI (30) and a high WC (102 cm) had more than twice the risk of those who only had a high BMI or a high WC (RR: 8.4 compared with 3.3; Figure 3).
Our findings that increased WC predicted increased risk within BMI categories are consistent with those of Janssen et al's (36), which are based on the National Health and Nutrition Examination Survey data. Although WC and BMI are highly correlated, they measure different aspects of body fatness. BMI tends to indicate overall fatness but not body fat distribution, whereas WC assesses abdominal adiposity. WC can also contribute information about overall adiposity independent of BMI because the latter cannot separate lean from fat mass. Janssen et al (37) reported that WC and BMI independently contributed to the prediction of abdominal subcutaneous, visceral, and nonabdominal fat. They found that WC was a better predictor of visceral fat than was BMI in white men and women. They recommended the use of both WC and BMI in clinical practice.
Finally, it is worth noting that the associations between overall obesity, central adiposity, and the risk of different health outcomes may vary. For example, WC may be more closely associated with the risk of type 2 diabetes than with CVD, possibly because visceral fat is a greater risk factor for type 2 diabetes (6). Overall adiposity may be a more important indicator of risk of coronary heart disease among men younger than 65 y, although central obesity seemed to be a stronger predictor of risk than BMI among men older than 65 y (4). Moreover, further research is needed to understand the ethnic and racial differences in WC and its association with health risks (38–43). To gain a full understanding of the related issues for developing appropriate guidelines for clinical practice, evidence regarding different health outcomes using studies including different ethnic and racial groups should be thoroughly evaluated.
One limitation of the present study is that we followed a homogeneous cohort of health professionals, who were predominately white. Our data did not allow for testing the possible ethnic differences in the relation between WC and the risk of type 2 diabetes. A second limitation is that these participants were likely to have healthier lifestyles and were thinner than the general US public. Thus, the associations we present may be an underestimate of the true risks associated with central obesity.
In conclusion, the present study provides further evidence that abdominal adiposity measured with the use of WC and WHR is a strong risk factor for type 2 diabetes, independent of overall obesity assessed by BMI. WC is a better measure of central obesity than is WHR for predicting the risk of type 2 diabetes. Both BMI and WC are useful for assessing health risk and should be measured in clinical settings and epidemiologic research whenever possible. Our results suggest that the currently recommended cutoff for WC in men needs to be reevaluated on the basis of this new evidence and that a lower cutoff may be more appropriate for guiding individuals to monitor their body weight, assisting overweight individuals to reduce their body weight, and facilitating public health efforts to fight the obesity epidemic.
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ACKNOWLEDGMENTS |
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YW and FBH were responsible for the study concept and design. YW was responsible for the data analysis and interpretation and the draft of the manuscript. YW, EBR, MJS, WCW, and FBH were responsible for the critical revision of the manuscript for important intellectual content. None of the authors had a conflict of interest.
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REFERENCES |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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 L. de Koning, A. T. Merchant, J. Pogue, and S. S. Anand Waist circumference and waist-to-hip ratio as predictors of cardiovascular events: meta-regression analysis of prospective studies Eur. Heart J., April 2, 2007; (2007) ehm026v1. [Abstract] [Full Text] [PDF]
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J. C. Wells, P. Treleaven, and T. J Cole BMI compared with 3-dimensional body shape: the UK National Sizing Survey Am. J. Clinical Nutrition, February 1, 2007; 85(2): 419 - 425. [Abstract] [Full Text] [PDF]
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K. A. Neville, R. J. Cohn, K. S. Steinbeck, K. Johnston, and J. L. Walker Hyperinsulinemia, Impaired Glucose Tolerance, and Diabetes Mellitus in Survivors of Childhood Cancer: Prevalence and Risk Factors J. Clin. Endocrinol. Metab., November 1, 2006; 91(11): 4401 - 4407. [Abstract] [Full Text] [PDF]
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 J. Uribarri and K. R. Tuttle Advanced Glycation End Products and Nephrotoxicity of High-Protein Diets Clin. J. Am. Soc. Nephrol., November 1, 2006; 1(6): 1293 - 1299. [Abstract] [Full Text] [PDF]
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C. Meisinger, A. Doring, B. Thorand, M. Heier, and H. Lowel Body fat distribution and risk of type 2 diabetes in the general population: are there differences between men and women? The MONICA/KORA Augsburg Cohort Study. Am. J. Clinical Nutrition, September 1, 2006; 84(3): 483 - 489. [Abstract] [Full Text] [PDF]
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S. E. Ramsay, P. H. Whincup, A. G. Shaper, and S. G. Wannamethee The Relations of Body Composition and Adiposity Measures to Ill Health and Physical Disability in Elderly Men Am. J. Epidemiol., September 1, 2006; 164(5): 459 - 469. [Abstract] [Full Text] [PDF]
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A. Schienkiewitz, M. B Schulze, K. Hoffmann, A. Kroke, and H. Boeing Body mass index history and risk of type 2 diabetes: results from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam Study. Am. J. Clinical Nutrition, August 1, 2006; 84(2): 427 - 433. [Abstract] [Full Text] [PDF]
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M. B. Schulze, C. Heidemann, A. Schienkiewitz, M. M. Bergmann, K. Hoffmann, and H. Boeing Comparison of Anthropometric Characteristics in Predicting the Incidence of Type 2 Diabetes in the EPIC-Potsdam Study Diabetes Care, August 1, 2006; 29(8): 1921 - 1923. [Full Text] [PDF]
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J. B. Meigs, P. W. F. Wilson, C. S. Fox, R. S. Vasan, D. M. Nathan, L. M. Sullivan, and R. B. D'Agostino Body Mass Index, Metabolic Syndrome, and Risk of Type 2 Diabetes or Cardiovascular Disease J. Clin. Endocrinol. Metab., August 1, 2006; 91(8): 2906 - 2912. [Abstract] [Full Text] [PDF]
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G. M Reaven The metabolic syndrome: is this diagnosis necessary? Am. J. Clinical Nutrition, June 1, 2006; 83(6): 1237 - 1247. [Abstract] [Full Text] [PDF]
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H. Ohnishi, S. Saitoh, S. Takagi, N. Katoh, Y. Chiba, H. Akasaka, Y. Nakamura, and K. Shimamoto Incidence of Type 2 Diabetes in Individuals With Central Obesity in a Rural Japanese Population: The Tanno and Sobetsu Study Diabetes Care, May 1, 2006; 29(5): 1128 - 1129. [Full Text] [PDF]
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 J.-P. Despres Abdominal obesity: the most prevalent cause of the metabolic syndrome and related cardiometabolic risk Eur. Heart J. Suppl., May 1, 2006; 8(suppl_B): B4 - B12. [Abstract] [Full Text] [PDF]
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H. M. Farin, F. Abbasi, and G. M Reaven Body mass index and waist circumference both contribute to differences in insulin-mediated glucose disposal in nondiabetic adults Am. J. Clinical Nutrition, January 1, 2006; 83(1): 47 - 51. [Abstract] [Full Text] [PDF]
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H. S. Kahn The Lipid Accumulation Product Is Better Than BMI for Identifying Diabetes: A population-based comparison Diabetes Care, January 1, 2006; 29(1): 151 - 153. [Full Text] [PDF]
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 K. J. Reichmuth, D. Austin, J. B. Skatrud, and T. Young Association of Sleep Apnea and Type II Diabetes: A Population-based Study Am. J. Respir. Crit. Care Med., December 15, 2005; 172(12): 1590 - 1595. [Abstract] [Full Text] [PDF]
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G. Heinz, G. T. Ko, and L. J Peterson Waist circumference gain compared with waist circumference as predictors of type 2 diabetes risk Am. J. Clinical Nutrition, November 1, 2005; 82(5): 1134 - 1134. [Full Text] [PDF]
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Y. Wang, E. B Rimm, M. J Stampfer, W. C Willett, and F. B Hu Reply to G Heinz et al Am. J. Clinical Nutrition, November 1, 2005; 82(5): 1135 - 1135. [Full Text] [PDF]
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G. Reaven All obese individuals are not created equal: insulin resistance is the major determinant of cardiovascular disease in overweight/obese individuals Diabetes and Vascular Disease Research, October 1, 2005; 2(3): 105 - 112. [Abstract] [PDF]
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 D. Haslam Include measurement of waist circumference in GP contract BMJ, August 20, 2005; 331(7514): 455 - 456. [Full Text]
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J.-P. Despres Our Passive Lifestyle, Our Toxic Diet, and the Atherogenic/Diabetogenic Metabolic Syndrome: Can We Afford to Be Sedentary and Unfit? Circulation, July 26, 2005; 112(4): 453 - 455. [Full Text] [PDF]
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Endocrinology & Metabolism News, May 2005 J. Clin. Endocrinol. Metab., May 1, 2005; 90(5): 16a - 16a. [Full Text] [PDF]
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 Taking Full Measure of Obesity DOC News, May 1, 2005; 2(5): 14 - 14. [Full Text]
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