European Review of Aging and Physical Activity最新文献

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.

Background: Age-related decline in physical and cognitive capacity increases older adults' risk of disability, long-term care placement, and mortality rate. Functional training, which uses activities of daily living or simulated movements to complete activities as the intervention medium, could be more effective than rote exercise, which uses repetitive movements without added purpose, in preventing late-life disability in older people. With a growing number of studies in this area, systematically studying the effect of functional training is needed. The purpose of this systematic review was to examine the effects of functional training on the outcomes of activities of daily living, physical functioning, and cognitive function in community-dwelling older adults.

Methods: Literature published between January 2010 and April 2024 in 10 electronic databases were searched and screened. This timeframe was established to include studies published within the last 15 years. Each identified article was screened and reviewed by two authors independently. The methodological quality of the included studies was evaluated using the PEDro Scale. Key findings were synthesized according to participants' characteristics and intervention types.

Results: The review included 32 studies. In the general community-dwelling older adult population (20 studies), studies that applied functional training as a single-component approach showed a positive effect on activities of daily living. However, the training effect on balance and mobility was not superior to that of other exercise programs. Moreover, the effect was mixed when functional training was combined with other intervention components. In older adults with mild cognitive impairment (5 studies), Simulated Functional Tasks Exercise, a single-component training, consistently demonstrated positive effects on the activities of daily living and cognitive functions. In older adults with dementia (4 studies) or frailty (3 studies), the effect was mixed across the single- and multi-component approaches.

Conclusion: Functional training alone is effective in preventing late-life disability in general community-dwelling older adults. When training activities challenge both motor and cognitive abilities, the effect seems to improve the performance of activities of daily living and cognitive functions in older adults with mild cognitive impairment. Additional studies of functional training in older adults with cognitive impairment or frailty are recommended.

Background: Physical activity (PA) is fundamental to nursing home residents' health. Likewise, physical capacity (PC) is essential to carry out activities of daily living. Although PC and PA are associated, misalignment has been reported in specific subgroups. Increased PC is oftentimes not linked to high PA (i.e., Can do - don't do) and vice versa (i.e., Can't do - do do). Therefore, identifying other contextual factors influencing PA in misaligned groups is important. This study aimed to identify contextual factors in nursing home residents with aligned or misaligned PA and PC.

Methods: In total, 180 nursing home residents (≥ 65 years, 79.4% females) were divided into four quadrants (Q1: Can do - do do; Q2: Can do - don't do; Q3: Can't do - do do; Q4: Can't do - don't do) based on thresholds for PA (≥ or < 2,500 steps/day) and PC (≤ or > 0.5 m/s gait speed). Kruskal-Wallis H test and effect sizes (ES) were applied to analyze quadrants' differences regarding PA (steps per day), objective motor capacity, life-space mobility, activities of daily living (ADL), psychosocial well-being, cognition, subjective mobility-related concerns, and spatial orientation.

Results: Specific contextual factors differed significantly between the groups. Compared to Q1, Q2 presents a significantly lower life-space mobility (ES: 0.35) and objective motor capacity (ES: 0-36-0.49); Q3 has a lower objective motor capacity (ES: 0.55-1.10); Q4 shows lower independence in ADL (ES: 0.57), life-space mobility (ES: 0.48), subjective mobility-related concerns (ES: 0.38) and objective motor capacity (ES: 0.99-1.08). No significant group differences were found for psychosocial well-being, cognition, and spatial orientation.

Conclusions: This study provides new insights into PA behavior of nursing home residents. Key variables linked to PA are objective motor capacity, life-space mobility, ADL, and subjective mobility-related concerns. Surprisingly, some potentially impactful variables such as cognition, orientation, and psychosocial well-being did not differ between the groups. This may suggest that these variables may not represent key targets for interventions aiming to improve PA. This study builds the foundation for further research into the underlying mechanisms behind PA behaviors and supports future efforts to plan specific, targeted interventions for nursing home residents.

Trial registration: The trial was prospectively registered at DRKS.de with registration number DRKS00021423 on April 16, 2020.

Background: A more fragmented, less stable rest-activity rhythm (RAR) is emerging as a risk factor for health. Accelerometer devices are increasingly used to measure RAR fragmentation using metrics such as inter-daily stability (IS), intradaily variability (IV), transition probabilities (TP), self-similarity parameter (α), and activity balance index (ABI). These metrics were proposed in the context of long period of wear but, in real life, non-wear might introduce measurement bias. This study aims to determine the minimum number of valid days to obtain reliable fragmentation metrics.

Methods: Wrist-worn accelerometer data were drawn from the Whitehall accelerometer sub-study (age: 60 to 83 years) to simulate different non-wear patterns. Pseudo-simulated data with different numbers of valid days (one to seven), defined as < 1/3 of non-wear during both day and night periods, and with omission or imputation of non-wear periods were compared against complete data using intraclass correlation coefficient (ICC) and mean absolute percent error (MAPE).

Results: Five days with valid data (97.8% of participants) and omission of non-wear periods allowed an ICC ≥ 0.75 and MAPE ≤ 15%, acceptable cut points for reliability, for IS and ABI; this number was lower for TPs (two-three days), α and IV (four days). Overall, imputation of data did not provide better estimates. Findings were consistent across age and sex groups.

Conclusions: The number of days of wrist accelerometer data with at least 2/3 of wear time for both day and night periods varies from two (TPs) to five (IS, ABI) days for reliable RAR measures among older adults.

Background: Due to poorer exercise tolerance, it may be challenging for frail older adults to engage in moderate- or vigorous-intensity exercise. While low-intensity exercise interventions may be more feasible, its effectiveness for such population group remains unclear. We examined the effectiveness and implementation of community-based Baduanjin Qigong, a low-intensity exercise program in older adults with varying frailty status.

Methods: A two-arm, multicenter assessor-blind parallel group randomized controlled trial was conducted at three local senior activity centers. Fifty-six community-dwelling older adults with low handgrip strength were randomly allocated to either the intervention (IG) or wait-list control (CG) group. The IG underwent a supervised 16-week Baduanjin exercise program at a frequency of 2-3 × 60 min sessions/week. The CG was instructed to maintain their usual activity and received a monthly health education talk. The primary outcome measures were knee extension strength, vital exhaustion, and fear of falling. Secondary outcome measures include physiological falls risk, handgrip strength, gait speed, timed up and go test, 30-second sit-to-stand, quality of life, depression, and frailty. All outcome measures were assessed at baseline and 4-month follow-up.

Results: Overall, there were no statistically significant differences in all outcome measures between CG and IG at 4-month follow-up. However, in exploratory compliance analysis, a statistically significant group x time interaction was found for vital exhaustion (B = -3.65, 95% CI [-7.13, -0.16], p = .047) among participants with at least 75% attendance. In post-hoc within-group comparisons, IG showed improved vital exhaustion by 4.31 points (95% CI [1.41, 7.20], d = 0.60). The average participant attendance rate was 81.3%. No major adverse events occurred, and all participants reported positive experiences with the exercise intervention.

Conclusions: Our study demonstrated that Baduanjin is a safe, feasible, and acceptable exercise program that can be successfully implemented in community settings for older adults with varying frailty status. With good adherence, Baduanjin exercise could potentially be effective in alleviating vital exhaustion. However, the effectiveness of Baduanjin on physical performance, psychological measures and frailty in community-dwelling older adults remains equivocal.

Trial registration: ClinicalTrials.gov NCT04549103. Registered September 16, 2020.

Background: With the rapid aging of the global population, identifying lifestyle patterns that effectively delay aging and reduce mortality risk is of paramount importance. This study utilizes the UK Biobank to analyze the associations of the Dietary Inflammatory Index, physical activity, and sleep on biological aging and all-cause mortality.

Methods: A prospective cohort study was conducted using data from over half a million UK Biobank participants. Two datasets were created by subjective and objective measurements of physical activity: the Subjective Physical Activity (SPA) and Objective Physical Activity (OPA) datasets. Lifestyle patterns, including diet habits, exercise levels, and sleep quality, were assessed within these datasets. Biological aging was quantified using validated methods, including Homeostatic Dysregulation, Klemera-Doubal Method Biological Age, Phenotypic Age, and Telomere Length. All-cause mortality data were obtained from the National Health Service. Statistical analyses included weighted linear regression and Cox proportional hazard models, adjusted for a range of covariates.

Results: The findings indicate that, in most cases, maintaining an anti-inflammatory diet, engaging in at least moderate physical activity, and ensuring healthy sleep conditions are associated with delayed physiological aging (Cohen's d ranging from 0.274 to 0.633) and significantly reduced risk of all-cause mortality (HR-SPA: 0.690, 95% CI: 0.538, 0.884; HR-OPA: 0.493, 95% CI: 0.293, 0.828). These effects are particularly pronounced in individuals under 60 years of age and in women. However, it was observed that the level of physical activity recommended by the World Health Organization (600 MET-minutes/week) does not achieve the optimal effect in delaying biological aging. The best effect in decelerating biological aging was seen in the high-level physical activity group (≥ 3000 MET-minutes/week). The study also highlights the potential of biological age acceleration and telomere length as biomarkers for predicting the risk of mortality.

Conclusions: Choosing healthy lifestyle patterns, especially an anti-inflammatory diet, at least moderate physical activity, and healthy sleep patterns, is crucial for delaying aging and reducing mortality risk. These findings support the development of targeted interventions to improve public health outcomes. Future research should focus on objective assessments of lifestyle to further validate these associations.

Background: Although a high C-reactive protein-to-albumin ratio (CAR) is believed to increase mortality risk, the association between the physical activity (PA), CAR, and mortality among cancer survivors has not been investigated. This study aimed to examine this association among cancer survivors in the United States.

Methods: This cohort study used data from the National Health and Nutrition Examination Survey from 1999 to 2010. PA was self-reported using the Global Physical Activity Questionnaire, and C-reactive protein and albumin levels were obtained from laboratory data files. Mortality data were obtained by linkage of the cohort database to the National Death Index as of December 31, 2019. The analysis was conducted from November 1 to December 31, 2023. We used Cox proportional hazards multivariable regression to assess hazard ratios (HRs) and 95% confidence interval (CIs) for total and cancer-specific mortality risks attributable to PA and CAR.

Results: Among 2,232 cancer survivors, 325 (14.6%) reported no PA with a high CAR. During a follow-up of up to 20.75 years (median, 12.3 years; 27,453 person-years), 1,174 deaths occurred (cancer, 335; other, 839). A high CAR was observed to be consistently associated with the highest risks of total (HR, 1.59; 95% CI, 1.37-1.85) and cancer-specific (HR, 2.06; 95% CI, 1.55-2.73) mortality compared with a low CAR in a series of adjusted models. Multivariable models showed that PA was associated with a lower risk of all-cause (HR, 0.60; 95% CI, 0.52-0.69) and cancer-specific (HR, 0.64; 95% CI, 0.49-0.84) mortality compared with no PA. In the joint analyses, survivors with PA ≥ 600 metabolic equivalent min/wk and a low CAR were more likely to reduce the risk of total (HR, 0.41; 95% CI, 0.32-0.51) and cancer-specific (HR, 0.32; 95% CI, 0.20-0.50) mortality by 59% and 68% compared with those with no PA and a high CAR.

Conclusion: The pairing of adequate PA and a low CAR was significantly associated with reduced all-cause and cancer-related mortality risks.