BACKGROUND: Obesity is common in women with breast cancer. The risk of obesity-induced metabolic syndrome is higher in Asians than in Caucasians. Excessive body fat accumulation has been associated with a worse prognosis. However, the most popular clinical indicator of obesity is not fat itself, but body mass index (BMI). OBJECTIVES: The purposes of this study were to determine the consistency of BMI and body fat percentage (BF%) in determining obesity and to identify the best BMI cutoffs for identifying obesity in Taiwanese women with breast cancer. METHODS: Body fat and fat-free mass were measured by bioelectrical impedance 1 day before breast surgery for 200 women with breast cancer. BMI was calculated as weight (in kilograms) divided by height (in meters) squared. RESULTS: BMI and BF% were highly correlated (r=0.91; p<0.001). However, BMI exhibited poor sensitivity for identifying obesity (47%). The sensitivity of BMI to detect obesity was better in women over age 60. The best BMI cutoff for obesity was 22.3 kg/m2 with a sensitivity and specificity of 89% (95% CI=83-94%) and 87% (95% CI=77-93%) respectively, and the total accuracy rate improved from 65% to 89%. CONCLUSIONS: Using BMI to identify obesity in Taiwanese women with breast cancer requires careful attention to the diagnostic criterion chosen. The World Health Organization criterion tends to underestimate the prevalence of obesity, especially for younger women with breast cancer (under age 40). Copyright (c) 2010 Elsevier Ltd. All rights reserved.
BACKGROUND:Obesity is common in women with breast cancer. The risk of obesity-induced metabolic syndrome is higher in Asians than in Caucasians. Excessive body fat accumulation has been associated with a worse prognosis. However, the most popular clinical indicator of obesity is not fat itself, but body mass index (BMI). OBJECTIVES: The purposes of this study were to determine the consistency of BMI and body fat percentage (BF%) in determining obesity and to identify the best BMI cutoffs for identifying obesity in Taiwanese women with breast cancer. METHODS: Body fat and fat-free mass were measured by bioelectrical impedance 1 day before breast surgery for 200 women with breast cancer. BMI was calculated as weight (in kilograms) divided by height (in meters) squared. RESULTS: BMI and BF% were highly correlated (r=0.91; p<0.001). However, BMI exhibited poor sensitivity for identifying obesity (47%). The sensitivity of BMI to detect obesity was better in women over age 60. The best BMI cutoff for obesity was 22.3 kg/m2 with a sensitivity and specificity of 89% (95% CI=83-94%) and 87% (95% CI=77-93%) respectively, and the total accuracy rate improved from 65% to 89%. CONCLUSIONS: Using BMI to identify obesity in Taiwanese women with breast cancer requires careful attention to the diagnostic criterion chosen. The World Health Organization criterion tends to underestimate the prevalence of obesity, especially for younger women with breast cancer (under age 40). Copyright (c) 2010 Elsevier Ltd. All rights reserved.