European Review of Aging and Physical Activity最新文献

Objectives: To identify the modifiable determinants targeted in interventions involving older adults, and to determine which of these interventions effectively increased physical activity (PA) and/or reduced sedentary behaviour (SB). Additionally, to explore whether the effects of these interventions vary based on the implementation setting.

Methods: A search of randomized controlled trials (RCTs) and controlled trials (CTs) was performed in Medline, APA PsycArticles, SPORTDiscus, and Web of Science. Risk of bias assessment was performed with Cochrane's tool. Modifiable determinants were narratively synthesized, and random-effects models were performed to meta-analyse studies reporting device-measured physical activity or sedentary behaviour. Moderator analyses were performed to investigate the role of implementation setting. Standardized between-group mean difference (SMD) with 95% confidence interval (CI) was used to indicate effect sizes.

Results: From 31,727 individual records, 52 eligible studies published between 2012-2022 were identified, 30 and 22 studies from community and health care settings, respectively. Determinants within the category physical health and wellbeing (n = 23) were most frequently reported while only one study reported determinants within a social or cultural context. Eighteen studies were included in the meta-analysis. Interventions targeting physical health and wellbeing revealed an increase in steps (SMD = 0.46; 95%CI: 0.15 to 0.77) and minutes of moderate-to-vigorous intensity physical activity (SMD = 0.41; 95%CI: 0.19 to 0.64) among intervention participants compared to controls, whereas interventions targeting psychological or behavioural determinants showed no between-group differences in steps (SMD = 0.10; 95%CI: -0.12 to 0.32) and moderate-to-vigorous intensity physical activity (SMD = 0.26; 95%CI: -0.24 to -0.75). Interventions targeting physical health and wellbeing showed significant heterogeneity (p < 0.0001; I² = 73.10%). Subgroup analyses showed a significant effect on device-measured physical activity for the eight community-based interventions (SMD = 0.42; 95%CI: 0.07 to 0.77), while no significant effect was found for the eight studies performed in healthcare settings (SMD = 0.26; 95%CI; -0.10 to 0.62).

Conclusion: Interventions targeting physical health and wellbeing may increase PA in older adults, with community-based studies appearing more effective than studies in healthcare settings. The significant heterogeneity of study findings indicates that further research is needed to fully understand the influence of PA and SB determinants across settings, particularly those related to psychological, behavioural, social, and cultural factors.

Systematic review registration: PROSPERO: CRD42022287606.

Background: The inability to appropriately react to balance perturbations is a common cause of falls. Perturbation-based balance training (PBT) is especially beneficial for improving reactive balance and shows high potential for fall prevention. However, its dose-response relationship, feasibility, and acceptability remain to be determined among older adults at risk of falling. The FEATURE study aimed to compare the efficacy of two treadmill PBT protocols with different session numbers to improve reactive balance, and to evaluate their feasibility and acceptability in this population.

Methods: In this randomized controlled pilot trial, 36 older adults at risk of falling were allocated to receive either six (6PBT) or two treadmill PBT sessions (2PBT). Reactive balance in standing (Stepping Threshold Test [STT]) and walking (Dynamic Stepping Threshold Test [DSTT]) was assessed as primary outcome at baseline (T1), post-intervention (T2), and 6-week follow-up (T3). Secondary outcomes included measures on physical, psychological, and cognitive functioning. Feasibility was assessed via PBT adherence, planned perturbations completed, and adverse events; acceptability via questionnaire. Between-group changes over time were compared using repeated-measures analyses of variance with Bonferroni-corrected post-hoc tests. Data analyses followed the intention-to-treat principle.

Results: A significant time effect was observed for the DSTT (p = 0.008), with both groups significantly improving from T1 to T2 (ps < 0.01). A significant interaction effect (p = 0.027) revealed that only the 6PBT group maintained these improvements (T1 vs. T3: p < 0.001) and scored significantly higher than the 2PBT group at T3 (p = 0.015). No significant interaction effects were found for the STT or any secondary outcome, but improvements over time were observed for dynamic balance, gait capacity, functional mobility, physical activity, concerns about falling, and executive functioning (time effects: ps < 0.05). PBT adherence, planned perturbations completed, and acceptability were high in both groups, with no significant between-group differences. No intervention-related serious adverse events were reported.

Conclusions: Findings suggest that a low number of treadmill PBT sessions can lead to task-specific improvements in reactive balance during walking, with a higher practice dose enhancing sustainability. Treadmill PBT appears feasible and well-accepted among older adults at risk of falling, regardless of sessions received.

Trial registration: DRKS00030805 ; prospectively registered December 14, 2022.

Objective: This meta-analysis explored the relationship between various exercise prescription variables and their effects on fall risk reduction in older adults, enabling the selection of targeted and evidence-based intervention prescription variables tailored to individual risk-assessment results.

Method: Databases including PubMed, Embase, Web of Science, and the Cochrane Library were systematically searched for randomized controlled trials that investigated the impact of exercise intervention on fall prevention. Study quality was assessed using the Cochrane risk-of-bias tool. Meta-analyses, subgroup analyses, sensitivity analyses, and assessments of publication bias were performed using Stata 16.0.

Results: A total of 43 articles comprising 51 studies and involving 2,743 participants were included. The results indicated significant improvements in fall risk assessment indices due to Mind-body Exercise (MBE), Multi-component Physical Activity (MCPA), and Muscle-strengthening Activity(MSA). Subgroup analyses revealed differential optimal type, cycle (week), frequency (day/week), and session time (minutes) across assessment tools, such as the unipedal stance test with eyes open (MCPA, < 8, 3, 45 ≤ Time < 60), functional reach (MCPA, < 8, < 3, ≥ 60), the "get-up and go" test (MSA, ≥ 24, < 3, 30 ≤ Time < 45), Berg balance scale (MBE, 8 ≤ Time < 12, 3, 30 ≤ Time < 45), Five stands sit-to-stand (MCPA, ≥ 24, > 3, 30 ≤ Time < 45), the 30-s chair-stand test (MSA, 12 ≤ Time, < 3, 45 ≤ Time < 60), short physical performance battery (MCPA, 12 ≤ Time < 24, < 3, ≥ 60), and Falls Efficacy Scale-International (MBE, 8 ≤ Time < 12, < 3, 45 ≤ Time < 60).

Conclusion: The findings suggest that prescription variables combining MCPA and MBE, ≥ 8-week programs, and ≥ 30-min sessions, effectively reduce fall risk through concurrent enhancement of balance, strength, and self-efficacy; their integration into community-based protocols with individualized resistance-balance combinations optimizes functional outcomes in older adults.

Background: Body composition and functional capacity are both related to physical activity, but the interplay is complex, as different body tissue types contribute differently on physical activity and functional capacity. To clarify the role of body composition and functional capacity as determinants of physical activity in aging, we investigated the associations of different body tissue types, muscle strength, and walking capacity with physical activity in middle-aged and older adults.

Methods: This cross-sectional study involved 1158 women aged 47-55 years, and community-dwelling 289 women and 196 men aged 75, 80, or 85 years. Their physical activity was assessed with accelerometers, muscle mass and muscle-free mass with bioelectrical impedance analysis, walking performance with a six-minute walking test, and muscle strength with maximal isometric knee extension test. The associations of muscle mass, muscle-free mass, walking performance, and muscle strength with physical activity were studied separately for middle-aged women, older women, and older men using linear regression and structural equation models.

Results: Total body mass and absolute muscle-free mass were inversely associated with the level of physical activity in all study groups. Furthermore, walking performance, muscle strength, and muscle mass relative to body weight, but not absolute muscle mass, were directly associated with the level of physical activity. The associations between the measures of body composition and physical activity were fully explained by the differences in functional capacity, as defined by both walking performance and muscle strength, in structural equation models. Functional capacity was strongly associated with higher levels of physical activity regardless of body composition, especially among older people: β = 0.70, SE = 0.10 for older women, β = 0.92, SE = 0.27 for older men, and β = 0.41, SE = 0.10 for middle-aged women.

Conclusions: Reduced functional capacity may be a key factor limiting physical activity, with its impact becoming more pronounced as functional capacity declines with age. Based on these findings, maintaining and improving functional capacity is essential for promoting an active lifestyle in older adults.

Background: Myelin, which insulates neurons, speeds up information transfer and provides the necessary conditions for cognitive and motor functioning. The direct link between physical performance and the total brain myelin volume remains unclear.

Methods: This study involved 87 healthy participants (71 women, 16 men) with a mean age of 69.3 ± 3.14 years and a mean body mass index of 27.83 ± 3.93 kg/m². Several measures of physical fitness (isometric muscle strength, handgrip strength, and cardiopulmonary exercise testing) were examined for their correlations with the total brain myelin volume using Synthetic MRI, an FDA-approved myelin assessment software.

Results: A high maximal respiratory exchange ratio and low maximal heart rate achieved during cardiopulmonary exercise testing were associated with higher estimated brain myelin content. In addition, the handgrip strength test performance as well as the peak and average peak torque were associated with higher brain parenchymal myelin volumes.

Conclusions: We demonstrated that higher brain myelin content was positively associated with better cardiorespiratory fitness and higher upper and lower limb muscle strength in older individuals. These findings provide new insights into the development of improved rehabilitation and exercise schemes to preserve cognitive health in the older adult population.

Background: Exercise-induced fatigue is a common consequence of physical activities. Particularly in older adults, it can affect gait performance. Due to a wide variety in fatiguing protocols and gait parameters used in experimental settings, pooled effects are not yet clear. Furthermore, specific elements of fatiguing protocols (i.e., intensity, duration, and type of activity) might lead to different changes in gait parameters. We aimed to systematically quantify to what extent exercise-induced fatigue alters gait in community-dwelling older adults, and whether specific elements of fatiguing protocols could be identified.

Methods: This systematic review and meta-analysis was conducted in accordance with the PRISMA guidelines. In April 2023, PubMed, Web of Science, Scopus, Cochrane and CINAHL databases were searched. Two independent researchers screened and assessed articles using ASReview, Rayyan, and ROBINS-I. The extracted data related to spatio-temporal, stability, and variability gait parameters of healthy older adults (55 +) before and after a fatiguing protocol or prolonged physical exercise. Random-effects meta-analyses were performed on both absolute and non-absolute effect sizes in RStudio. Moderator analyses were performed on six clusters of gait parameters (Dynamic Balance, Lower Limb Kinematics, Regularity, Spatio-temporal Parameters, Symmetry, Velocity).

Results: We included 573 effect sizes on gait parameters from 31 studies. The included studies reflected a total population of 761 older adults (57% female), with a mean age of 71 (SD 3) years. Meta-analysis indicated that exercise-induced fatigue affected gait with a standardized mean change of 0.31 (p < .001). Further analyses showed no statistical differences between the different clusters, and within clusters, the effects were non-uniform, resulting in an (indistinguishable from) zero overall effect within all clusters. Elements of fatiguing protocols like duration, (perceived) intensity, or type of activity did not moderate effects.

Discussion: Due to the (mainly) low GRADE certainty ratings as a result of the heterogeneity between studies, and possible different strategies to cope with fatigue between participants, the only conclusion that can be drawn is that older adults, therapist, and researchers should be aware of the small to moderate changes in gait parameters as a result of exercise-induced fatigue.

Background: Pathological aging can impair sensory information, leading to postural control disorders in older adults. Compensatory sensorial mechanisms are emerging to preserve balance function. The objective of the study was to identify sensory profiles in functionally impaired older adults, and determine if they are linked to the frequently observed cervical proprioceptive disorders in this population.

Methods: Fifty-one older adults (76.9 ± 7.6 years) were divided into 2 Functional Groups (FG-/FG+) according to a composite score that included 3 variables (gait speed, grip strength and fear of falling). All the participants completed the modified clinical test of sensory interaction on balance (m-CTSIB) and the cervical joint sense position error (CJPSE) test. Exploratory factor analysis was used to identify common factors among the variables. Pearson correlation was used to examine relationships between variables.

Results: As expected, conditions 2 and 3 of the m-CTSIB were both challenging to balance, whereas condition 4 was too difficult for several patients. Factor analysis revealed that the stabilometric variables were grouped together in factor one, and proprioceptive performance (CJPSE) and the mean CoP velocity in m-CTSIB condition 3 formed another second factor. Moreover, a significant correlation was highlighted between stability in Condition 3 and CJPSE in the FG-.

Conclusion: Our results revealed the predominance of both visual and podal information in functionally impaired adults to control their posture. We speculate that the observed podal preference could be consecutive to a less efficient cervical proprioceptive system.

Background: Physical activity (PA) may have an impact on cognitive function. Machine learning (ML) techniques are increasingly used in dementia research, e.g., for diagnosis and risk stratification. Less is known about the value of ML for predicting cognitive decline in people with dementia (PwD). The aim of this study was to use an ML approach to identify variables associated with a multimodal PA intervention that may impact cognitive changes in PwD, i.e., by distinguishing between cognitive decliners and non-decliners.

Methods: This is a secondary, exploratory analysis using data from a Randomized Controlled Trial that included a 16-week multimodal PA intervention for the intervention group (IG) and treatment as usual for the control group (CG) in nursing homes. Predictors included in the ML models were related to the intervention (e.g., adherence), physical performance (e.g., mobility, balance), and pertinent health-related variables (e.g., health status, dementia form and severity). Primary outcomes were global and domain-specific cognitive performance (i.e., attention/ executive function, language, visuospatial skills, memory) assessed by standardized tests. A Support Vector Machine model was used to perform the classification of each primary outcome into the two classes of decline and non-decline. GridSearchCV with fivefold cross-validation was used for model training, and area under the ROC curve (AUC) and accuracy were calculated to assess model performance.

Results: The study sample consisted of 319 PwD (IG, N = 161; CG, N = 158). The proportion of PwD experiencing cognitive decline, in the different domains measured, ranged from 27-48% in CG, and from 23-49% in IG, with no statistically significant differences and no time*group effects. ML models showed accuracy and AUC values ranging from 40.6-75.6. The strongest predictors of cognitive decline or non-decline were performance of activities of daily living in IG and CG, and adherence and mobility in IG.

Conclusions: ML models showed moderate performance, suggesting that the selected variables only had limited value for classification, with adherence and performance of activities of daily living appearing to be predictors of cognitive decline. While the study provides preliminary evidence of the potential use of ML approaches, larger studies are needed to confirm our observations and to include other variables in the prediction of cognitive decline, such as emotional health or biomarker abnormalities.