Interactions among obesity and age-related effects on the gait pattern and muscle activity across the ankle joint.

Objective: The purposes of this study were to investigate the combined effects of age and obesity on gait and to analyze the relationship between age and obesity on ankle muscle activities during walking.

Materials And Methods: 4 groups; the young non-obese control group (CG, n = 50, age = 31.8 ± 4.5 years; BMI = 21.4 ± 2.2 kg/m), the young obese group (OB, n = 30, age = 35.4 ± 4.1 years; BMI = 38.6 ± 3.5 kg/m), the non-obese older adults group (OA, n = 20, age = 76.1 ± 3.5 years; BMI = 24.4 ± 1.1 kg/m) and the obese older adults group (OBOA, n = 20, age = 79.6 ± 5.7 years; BMI = 35.5 ± 2.7 kg/m) walked on an instrumented gait analysis treadmill at their preferred walking speed. Spatiotemporal parameters, walking cycle phases, Vertical ground reaction force (GRFv) and center of pressure (CoP) velocity were sampled from the treadmill software. Electromyography (EMG) activity of the gastrocnemius medialis (GM), the soleus (SOL) and tibialis anterior (TA) were also collected during the walking test. A forward stepwise multiple regression analysis was performed to determine if body weight or age could predict ankle muscle activities during the different walking cycle phases.

Results: Compared to OB, OBOA walked with higher CoP velocity, shorter stride, spending more time in support phase (p < .05). These manifestations were associated with higher TA and SOL activities during the 1st double support (1st DS) and higher TA activity during the single support (SS) (p < .05). Compared to OA, OBOA walked with lower GRFv, shorter and wider stride and spend more time in SU (p < .05). Moreover, SOL, TA and GM activities of OBOA were higher compared to OAG during 1st DS, SS and 2nd Double support (2nd DS), respectively (p < .05). During the 1ST DS, the stepwise multiple regression revealed that age accounted for 87% of the variance of TA activity. The addition of age contributed a further 16% to explain the variance TA activity. During the SS, age accounted for 64% and 46% of the variance of SOL and TA activity respectively. The addition of the body weight added further 15% and 66% of the variation of SOL and TA activity respectively. During the 2nd DS, body weight accounted for 86% of the variance and the addition of the body weight added a further 17% to explain the high level of GM.

Conclusion: Age in obese adults and obesity in older adults should be considered separately to evaluate neuromuscular responses during walking and, subsequently, optimize the modality of treatment and rehabilitation processes in obese individuals in order to reduce and/or prevent the risk of falls.