Body fat percentage assessment by ultrasound subcutaneous fat thickness measurements in middle-aged and older adults

Abstract

Background & aims: B-mode ultrasound accurately measures both muscle mass, body density and percent body fat (% BF) in younger adults, but how well it can estimate % BF in middle-aged and older adults using DXA-derived %BF as the criterion is unclear. We sought to develop % BF prediction equations for middle-aged and older adults using ultrasound subcutaneous fat thickness (SFT).

Methods: A cross-sectional study of Japanese adults (n = 414, 50-79 years) where 276 subjects were randomly assigned to a model development group and the other 138 subjects were assigned to a cross-validation group. B-mode ultrasound measured SFT at nine sites. Dual energy X-ray absorptiometry (DXA) measured % BF, arm fat mass (FM) and leg FM. Stepwise multiple linear regression developed prediction equations from anthropometric data (body mass, height, waist and hip circumference) and ultrasound SFT sites. Bland-Altman plots assessed validity of the prediction equations to measure % BF in the cross-validation group.

Results: The best prediction equation for % BF was the following: [% BF = 15.709 + (1.753*anterior trunk SFT) + (5.626*Sex) + (3.635*posterior upper arm SFT) - (4.428*anterior lower leg SFT) - (0.170*height) + (0.264*waist) + (anterior thigh SFT*2.241); r² = 0.809, standard error of the estimate (SEE) = 3.3 kg]. Arm FM and leg FM prediction equations had r² values ranging from 0.690 to 0.812 and SEEs of 0.29 and 0.75 kg. A small mean bias was noted for estimating % BF (-0.14%), but large limits of agreement were found (-8.0-7.7%) and systematic error was noted in all of the equations (r = 0.275 to 0.515, p < 0.05).

Conclusions: Despite high r² values and a small mean bias found between predicted and DXA % BF, wide limits of agreement were found with some systematic error present. Therefore, these prediction equations for middle-aged and older adults may not be sufficiently accurate to use in a clinical setting.

Keywords: Aging; Body composition; Geriatrics; Obesity; Ultrasonography.