Table 1.
Summary of study population.
Table 2.
Percent body fat and BMI for all patients.
Figure 1.
BMI versus Percent Body Fat in Scatter Plot.
Women (red) who fall above red line are obese according to American Society of Bariatric Physicians criteria (DXA percent body fat: ≥30%). Men (blue) who fall above blue horizontal line are obese according to American Society of Bariatric Physicians criteria (DXA percent body fat: ≥25%). The upper left quadrant bordered by red horizontal line (body fat percent = 30%) and black vertical line (BMI = 30) demonstrates large number of women misclassified as “non-obese” by BMI yet “obese” by percent body fat.
Figure 2.
Percent Misclassified as Non-obese by BMI Statified by Age, and Sex (n = 539).
Women demonstrate clear correlation between advancing age and increasing percent misclassification, with over half misclassified by age 60–69. This association is not apparent for men.
Figure 3.
Receiver Operating Characteristic (ROC) Curve for Using BMI to Predict Obesity for Women.
The area under the curve increases when stratified by sex. Numbers indicate the BMI cutoff value that corresponds to sensitivity/specificity along ROC curve. The BMI cutoff value that maximizes sensitivity and specificity is 24 for females (79% sensitivity and 87% specificity) and 28 for males (72% sensitivity and 83% specificity).
Figure 4.
Comparison of Mean Leptin and Mean Insulin Across Percent Body Fat Categories.
There is strong relationship between increased leptin and increased percent body fat, and no relationship between insulin and percent body fat. Error bars represent 95% confidence intervals for mean.
Table 3.
BMI score adjustment based on female's leptin level and age to optimize the estimate of percent body fat.
Table 4.
Summary statistics for various BMI cut-off values predicting obesity as defined by percent body fat of >25% for men and >30% for women.