Quality-of-life in obese individuals is adversely affected due to limitations in functional mobility.

Purpose:​ The primary purpose of this research study was to determine the differences in functional mobility between normal weight (NW) and overweight/obese(OV/OB) adults. A secondary goal of this research study was to determine which measure of body composition (i.e. fat mass, lean body mass, and BMI) is a better predictor of functional mobility. Furthermore, we proposed to determine the relationship between two measures of muscular strength (isokinetic and isotonic) and functional mobility. Finally, we determined whether body composition or muscular strength was more predictive of functional mobility.

Methods:​ Fifteen subjects participated in this research study. Subjects were categorized into NW and OV/OB groups based on body fat percentage. (NW:​ n=8, Ht:​ 163.63 (11.61) cm, Mass:​ 62.28 (14.09) kg, BF%:​ 21.38 (10.03) %) and OV/OB:​ n=7, Ht:​ 172.14 (7.69cm), Mass:​ 84.14 (11.14) kg, BF%:​ 30.44 (6.57) %). Body composition was measured with a BodPod. Mobility function was subjectively assessed based on the Physical Component Score (PCS) of the SF-36, while objective functional mobility was assessed based on time to complete two common mobility tasks (i.e. sit-to-stand (STS) and 50 meter walk (50MW)). Isokinetic muscular strength was assessed at two testing speeds (i.e. 60 & 240 deg/sec). Isotonic muscular strength was assessed by performing a quarter squat loaded with 60% of subjects’ body weight while standing on a force-plate. An ANOVA was used to determine between group differences (alpha=0.05) in functional mobility. Linear regression analyses were used to determine the relationship of body composition to function (alpha=0.05), and the relationship of muscular strength to function (alpha=0.05). Feed-forward multiple regression analysis was used to determine which variables (i.e. body composition or muscular strength) were more predictive of functional mobility.

Results:​ No significant differences were found between NW and OV/OB groups in the PCS. Significant differences were found in the time to complete the STS, with OV/OB groups taking significantly longer to complete the test (p<0.01) (NM:​ 13.065(1.70)secs vs. OB:​ 17.75(3.16)secs). No significant differences were found between the NW and OV/OB groups in 50MW time. BMI and fat mass were significantly correlated with STS times (r=0.609, r²=0.37, p=0.01 and r=0.55, r²=0.31, p=0.03, respectively). No measure of body composition was significantly related to 50MW time. Neither normalized knee nor hip extension torque was significantly correlated with either STS or 50MW time. In addition, knee and hip rate of torque development was not significantly correlated with either STS or 50MW time. Fatigue of the knee extensors was significantly related to STS time (r=0.63, r²=0.354, p=0.01), yet has no significant correlation with 50MW time. However, fatigue of the hip extensors was not significantly correlated with either STS or 50MW times. Isotonic normalized peak force was not significantly correlated with either STS or 50MW times. The average rate of force development (aRFD) had no significant correlation STS, yet was significantly correlated with 50MW time (r=0.72, r²=0.51,p=0.02). Interestingly, peak rate of force development (pRFD) had no significant correlation with either STS time or 50 MW time. Peak power was not significantly correlated with either STS or 50MW time. Multiple regression analysis revealed that knee extension fatigue was a better predictor of STS time than either BMI or fat mass.

Conclusions:​ In our study population, it appears that STS performance in decreased in OV/OB. Furthermore, as BMI and fat mass increase there is a significant decreased in subjective functional mobility and an increase in time to complete the STS task. Isokinetic fatigue appears to be the most predictive of functional mobility. Further research is necessary to determine how STS is negatively impacted by obesity.