Do Measures of Body Fat Distribution Provide Information on the Risk of Type 2 Diabetes in Addition to Measures of General Obesity?

Abstract

OBJECTIVE -To investigate which anthropometric measurements of obesity best predict type 2 diabetes in a population of Pima Indians and whether additional information on diabetes risk could be obtained by combining measures of general obesity with measures of body fat distribution.RESEARCH DESIGN AND METHODS -We conducted a prospective study of 624 men and 990 nonpregnant women Ͼ18 years of age without diabetes. Subjects were followed a mean of 5.25 years for the development of type 2 diabetes (using 1997 American Diabetes Association criteria).RESULTS -A total of 322 new cases of type 2 diabetes (107 men and 215 women) were diagnosed during follow-up. Baseline obesity measurements were highly correlated and predicted diabetes in proportional hazards models adjusted for age. BMI had the highest hazard ratio in men and women, with age-adjusted hazard ratios per SD of 1.73 (95% CI 1.44 -2.07) and 1.67 (1.45-1.91), respectively. According to receiver-operating characteristic analysis, BMI and waist-to-height ratio were the best predictors of diabetes in men, while in women BMI, waistto-height ratio, waist circumference, and waist-to-thigh ratio were the best predictors. The predictive abilities of models containing BMI were not significantly improved by including other measures of general obesity or measures of the body fat distribution.CONCLUSIONS -Throughout its range, BMI was an excellent predictor of type 2 diabetes risk in Pima Indians and was not significantly improved by combining it with other measures of general adiposity or body fat distribution. Diabetes Care 26:2556 -2561, 2003G eneral measures of obesity (weight, BMI, and percent body fat) and measures of central fat distribution (waist circumference, waist-to-hip ratio, waist-to-thigh ratio, and waist-to-height ratio) predict the risk of type 2 diabetes in prospective studies regardless of age or ethnicity (1-8).The strong association between the quantity of intra-abdominal fat and metabolic disorders, however, has led some to suggest that anthropometric measurements that describe central fat distribution (such as waist circumference) may be better than general measures of obesity as predictors of diabetes. For example, in the San Antonio Heart Study (5), the waist circumference was the best predictor of diabetes risk in a population of Mexican Americans among the variables BMI, waist-to-hip ratio, hip circumference, and the sum of skinfold thicknesses. In other prospective studies (3,4,7) the risk of diabetes increased with increasing quantities of central fat within a BMI category, suggesting that both measures are important in predicting the risk of diabetes. Two studies have demonstrated that the effect of these measures of body fat distribution depends on the value of BMI (5,6). The San Antonio study showed a stronger effect of body fat distribution on diabetes risk in subjects with a BMI Ͻ27 kg/m 2 (odds ratio per 1-SD difference ϭ 6.0; 95% CI 1.8 -20.1) compared with those with a BMI Ͼ27 kg/m 2 (1.7, 1.1-2.7) (5). However, Ohlson (6) demonstrat...

Value of body fat mass vs anthropometric obesity indices in the assessment of metabolic risk factors

“…This observation is in line with previous studies, [8][9][10][11][12] but contrary to others. [13][14][15] However, in all these studies, [8][9][10][11][12][13][14][15] %FM was determined by the use of bioelectrical impedance analysis. Thus, the inaccuracies of impedance measurements may add to the observed discrepancies.…”

“…This is in accordance with two other studies, showing that BMI, %FM, WC and WC/ht were equivalent in their ability to predict type II diabetes in Pima Indians. 11,12 Taken together, all these results suggest that, at the population level, BMI is an adequate index of obesity-related metabolic risk that does not lag behind direct assessment of adiposity. However, this does not challenge the issue that indirect estimates of body composition are useful for groups but simultaneously unreliable in individuals.…”

“…7 However, studies comparing the values of BMI and %FM in the prediction of metabolic risk are contradictory. [8][9][10][11][12][13][14][15] Some authors found that when compared to %FM BMI was similar or even more closely associated to cardiovascular risk factors, for example, lipid profile, blood pressure or insulin resistance (IR). [8][9][10][11][12] By contrast, the value of %FM exceeded BMI in other studies.…”

“…[8][9][10][11][12][13][14][15] Some authors found that when compared to %FM BMI was similar or even more closely associated to cardiovascular risk factors, for example, lipid profile, blood pressure or insulin resistance (IR). [8][9][10][11][12] By contrast, the value of %FM exceeded BMI in other studies. [13][14][15] One explanation of these discrepant results may be that the data suffer from methodological drawbacks of field methods used for body composition analysis (e.g.…”

Betel nut chewing and other risk factors associated with obesity among Taiwanese male adults

“…10 Obesity is an important risk factor for a legion of chronic diseases, such as diabetes mellitus, cardiovascular diseases, and hypertension. [11][12][13][14][15][16][17] However, the number of researches studying the relationship between betel nut chewing and body size remains fairly limited. As Taiwan is marked by a high prevalence rate of betel nut chewing 18 and has witnessed an increasing incidence of the above-mentioned chronic diseases, our research has accordingly examined the relationship between betel nut chewing and body build.…”