Usefulness of bioelectrical impedance analysis in multiple sclerosis patients-the interrelationship to the body mass index.

Background: Patients with multiple sclerosis (MS) have many potential factors (disease duration, spasticity, immobilization, or glucocorticoid use) that can deteriorate their nutritional status and impact both the progression and prognosis of the disease. Body mass index (BMI), the most widely used nutritional status assessment tool, has important limitations because it does not provide any data on body composition.

Aim: This study aimed to assess the interrelationship between nutritional status assessment by both body mass index (BMI) and body composition using bioelectrical impedance analysis (BIA) and the consistency of diagnosis for underweight/underfat, normal weight/healthy, overweight/overfat, and obesity/obese MS patients.

Methods: Anthropometric [BMI and waist-to-height ratio (WHtR)] and body composition (BIA) data were evaluated in 176 patients with MS. Patients were categorized into four nutritional status subgroups (underweight, normal weight, overweight, obese according to BMI, and underfat, healthy, overfat, and obese according to fat mass% by BIA). The median Expanded Disability Status Scale score was 4.5. Patients were then divided according to EDSS score as mild (EDSS 1.0-4.0) or moderate (EDSS 4.5-6.5) disability subgroups.

Results: Based on BIA assessment, there was a significantly higher prevalence of overfat than of overweight based on BMI [ = 50 (28.41%) vs.  = 38 (21.59%);  < 0.05]. However, the prevalence of obesity did not differ significantly regardless of the mode of diagnosis and was not significantly lower when assessed using BIA [ = 26 (14.77%) vs.  = 30 (17.05%), respectively]. The overall compatibility rates (CR) of diagnoses made using both BMI and BIA were 75.6, 77.0, and 70.1% for all patients with MS and the mild and moderate subgroups, respectively. The lowest CR was observed in the overweight group. Adiposity significantly underestimated BMI in all subgroups. In the moderate MS subgroup, BMI significantly overcategorized patients with MS as having a normal weight ( < 0.05). Stratification for abdominal obesity (WHtR > 0.5) showed that BMI significantly underestimated the prevalence of MS in overweight and obese vs. overfat and obese patients, as assessed using BIA (60.5 vs. 67%;  < 0.05). Clinical status (EDSS and ΔEDSS) was more closely related to the nutritional status categorized by FAT% assessed using BIA than using BMI cutoff points. However, the relationship was not statistically significant.

Conclusion: Using the BMI cutoff point for nutritional status assessment in patients with MS is associated with a significant underestimation of excess fat mass. BIA-based FAT% based on BIA have a better relationship with abdominal obesity and disability status than with BMI in patients with MS. The highest rate of false-negative diagnoses was based on the BMI in patients with MS and moderate disability. Adiposity assessment using BIA appears to be a useful method for proper nutritional status assessment in the patients group.