Development and Cross-Validation of a Simple Model to Estimate Percent Body Fat in Persons with Multiple Sclerosis

Persons with multiple sclerosis (MS) have higher body composition variability compared with the general population. Monitoring body composition requires accurate methods for estimating percent body fat (%BF). We developed and cross-validated an equation for estimating %BF from body mass index (BMI) and sex in persons with MS.

Seventy-seven adults with MS represented the sample for the equation development. A separate sample of 33 adults with MS permitted the equation cross-validation. Dual-energy x-ray absorptiometry (DXA) provided the criterion %BF.

The model including BMI and sex (mean ± SD age: women, 49.2 ± 8.8 years; men, 48.6 ± 9.8 years) had high predictive ability for estimating %BF (P < .001, R = 0.77, standard error of estimate = 4.06%). Age, MS type, Patient-Determined Disease Steps score, and MS duration did not improve the model. The equation was %BF = 3.168 + (0.895 × BMI) - (10.191 × sex); sex, 0 = woman; 1 = man. The equation was cross-validated in the separate sample (age: women, 48.4 ± 9.4 years; men, 43.8 ± 15.4 years) based on high accuracy as indicated by strong association (r = 0.89, P < .001), nonsignificant difference (mean: 0.2%, P > .05), small absolute error (mean: 2.7%), root mean square error (3.5%), and small differences and no bias in Bland-Altman analysis (mean difference: 0.2%, 95% CI: -6.98 to 6.55, r = -0.07, P = .702) between DXA-determined and equation-estimated %BF.

Health care providers can use this developed and cross-validated equation for estimating adiposity in persons with MS when DXA is unavailable.