Effects of multicomponent training and detraining on the fitness of older adults with or at risk of frailty: results of a 10-month quasi-experimental study

Effects of Multicomponent Training Followed by a Detraining Period on Frailty Level and Functional Capacity of Older Adults with or at Risk of Frailty: Results of 10-Month Quasi-Experimental Study

This study aimed: To analyze the effects of 6-month multicomponent training (MCT) and 4-month detraining on functional capacity and frailty among older adults with/at risk of frailty and to analyze the influence of frailty status on training and detraining adaptations. A total of 106 older adults (80.5 ± 6.0 years) were divided into a control (CON) or training group (TRAIN). The TRAIN performed a 6-month MCT (Eelder-fit), while CON continued their usual lifestyle. Functional capacity was assessed by the Short Physical Performance Battery (SPPB), while frailty was evaluated through Fried (FP) and the short version of the Frailty Trait Scale (FTS-5). Linear mixed models were performed to analyze group effects and to compare differences in changes within and between groups. TRAIN showed improvements in SPPB (3.2 ± 2.4), FP (-0.7 ± 1.3), and FTS-5 (-5.9 ± 5.8), whereas CON improved in SPPB (0.7 ± 2.9) and deteriorated in FTS-5 (2.8 ± 7.6) (all p < 0.05). Group effects favorable to TRAIN were found for all scales during this period (all p < 0.05). After detraining, TRAIN worsened in SPPB (-1.2 ± 2.7) and FTS-5 (4.1 ± 6.1) (both p < 0.05). No relevant differences were observed, accounting for frailty status between TRAIN subgroups. Eelder-fit improved the functional capacity and frailty of this population, whereas 4-months of detraining caused a drop of these variables except in FP.

The Effectiveness of a Hybrid Exercise Program on the Physical Fitness of Frail Elderly

BACKGROUND

Frailty is a serious physical disorder affecting the elderly all over the world. However, the frail elderly have low physical fitness, which limits the effectiveness of current exercise programs. Inspired by this, we attempted to integrate Baduanjin and strength and endurance exercises into an exercise program to improve the physical fitness and alleviate frailty among the elderly. Additionally, to achieve the goals of personalized medicine, machine learning simulations were performed to predict post-intervention frailty.

METHODS

A total of 171 frail elderly individuals completed the experiment, including a Baduanjin group (BDJ), a strength and endurance training group (SE), and a combination of Baduanjin and strength and endurance training group (BDJSE), which lasted for 24 weeks. Physical fitness was evaluated by 10-meter maximum walk speed (10 m MWS), grip strength, the timed up-and-go test (TUGT), and the 6 min walk test (6 min WT). A one-way analysis of variance (ANOVA), chi-square test, and two-way repeated-measures ANOVA were carried out to analyze the experimental data. In addition, nine machine learning models were utilized to predict the frailty status after the intervention.

RESULTS

In 10 m MWS and TUGT, there was a significant interactive influence between group and time. When comparing the BDJ group and the SE group, participants in the BDJSE group demonstrated the maximum gains in 10 m MWS and TUGT after 24 weeks of intervention. The stacking model surpassed other algorithms in performance. The accuracy and precision rates were 75.5% and 77.1%, respectively.

CONCLUSION

The hybrid exercise program that combined Baduanjin with strength and endurance training proved more effective at improving fitness and reversing frailty in elderly individuals. Based on the stacking model, it is possible to predict whether an elderly person will exhibit reversed frailty following an exercise program.