Reduction of misclassification rates of obesity by body mass index using dual-energy X-ray absorptiometry scans to improve subsequent prediction of per cent fat mass in a Caucasian population
Research output: Contribution to journal › Journal article › Research › peer-review
Recognition is increasing for the errors of body mass index (BMI) in classification of excess body fat. Dual-energy X-ray absorptiometry (DXA) is accurate to assess body fat mass per cent (%FM), but is underutilized clinically. We examined the prevalence of obesity misclassification by BMI in comparison to body %FM by DXA scanning, and whether there is a time-stable individual relation between the %FM and the BMI in patients scanned several times. We aimed to develop a formula where, based on a single DXA scan, %FM could be predicted following a change in weight, and a patient-specific BMI threshold could be calculated (BMIT), above which the patient would be obese by %FM criteria. Data were collected from individuals who had a DXA scan as part of a nutritional research study at the University of Copenhagen. BMI incorrectly classified 48/329 (14.6%) of men and 52/589 (8.8%) of women. The majority of men with BMI 25–27 kg m-2 and women with BMI 24–26 kg m-2 were misclassified. Using multiple scan data (189 men, 311 women) and calculating the patient-specific constant C = (1 - %FM/100)3/2 ¥ BMI from baseline BMI and %FM, misclassification rates were halved for both genders when a personal threshold, BMIT, was used ([BMIT = C/(0.75)3/2] for men and [BMIT = C/(0.65)3/2] for women). We conclude that simple formulae allow evaluation of fatness of individual patients more accurately than BMI, with the use of one baseline DXA scan, and enable the establishment of patient-specific obesity treatment targets in clinical practice.
|Number of pages||8|
|Publication status||Published - 2011|
- Former LIFE faculty