Distinct physical activity and sedentary behavior trajectories in older adults during participation in a physical activity intervention: a latent class growth analysis

Physical activity and the outcome of cognitive trajectory: a machine learning approach

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.

The Effectiveness of Interventions to Reduce Sedentary Time in Different Target Groups and Settings in Germany: Systematic Review, Meta-Analysis and Recommendations on Interventions

BACKGROUND

Sedentary behavior is an important risk factor for several chronic diseases and is associated with an increased risk of mortality. We assessed the effectiveness of interventions to reduce sedentary time in Germany and provide recommendations on interventions to reduce sedentary time in children and adults.

METHODS

We comprehensively searched PubMed, Web of Science and the German Clinical Trials Register up to April 2022 for intervention studies targeting sedentary behavior in Germany. We performed a systematic review and qualitative synthesis of the interventions and a meta-analysis in children.

RESULTS

We included 15 studies comprising data from 4588 participants. The results of included primary studies in adults and children showed inconsistent evidence regarding change in sedentary time, with a majority of studies reporting non-significant intervention effects. The meta-analysis in children showed an increase in sedentary time for children in the control and intervention groups.

CONCLUSION

We found inconsistent evidence regarding the effectiveness of interventions to reduce time spent sedentary and our meta-analysis showed an increase in sedentary time in children. For children, we recommend physical and social environment interventions with an active involvement of families. For adults, we recommend physical environment interventions, such as height-adjustable desks at work.

Web-Based Versus Print-Based Physical Activity Intervention for Community-Dwelling Older Adults: Crossover Randomized Trial

BACKGROUND

Fewer than half of older German adults engage in the recommended levels of endurance training.

OBJECTIVE

The study aim is to compare the acceptance and effectiveness of two interventions for physical activity (PA) promotion among initially inactive community-dwelling older adults ≥60 years in a 9-month, crossover randomized trial.

METHODS

Participants were recruited in person and randomized to one of the following interventions for self-monitoring PA: a print-based intervention (PRINT: 113/242, 46.7%) or a web-based intervention (WEB: 129/242, 53.3%). Furthermore, 29.5% (38/129) of those in the web-based intervention group received a PA tracker in addition to WEB (WEB+). After randomization, the participants and researchers were not blinded. The participants' baseline intervention preferences were retrospectively assessed. All the intervention groups were offered 10 weekly face-to-face group sessions. Afterward, participants could choose to stay in their group or cross over to one of the other groups, and group sessions were continued monthly for another 6 months. 3D accelerometers to assess PA and sedentary behavior (SB) at baseline (T0), 3-month follow-up (T1), and 9-month follow-up (T2) were used. Adherence to PA recommendations, attendance of group sessions, and intervention acceptance were assessed using self-administered paper-based questionnaires. Linear mixed models were used to calculate differences in moderate to vigorous PA (MVPA) and SB between time points and intervention groups.

RESULTS

Of the 242 initially recruited participants, 91 (37.6%) were randomized to the WEB group; 38 (15.7%) to the WEB+ group; and 113 (46.7%) to the PRINT group. Overall, 80.6% (195/242) of the participants completed T1. Only 0.4% (1/242) of the participants changed from the WEB group to the PRINT group and 6.2% (15/242) moved from the PRINT group to the WEB group (WEB-WEB: 103/249, (41.4%); PRINT-PRINT: 76/249, 30.5%) when offered to cross over at T1. Furthermore, 66.1% (160/242) of participants completed T2. MVPA in minutes per day increased between baseline and T1, but these within-group changes disappeared after adjusting for covariates. MVPA decreased by 9 minutes per day between baseline and T2 (βtime=-9.37, 95% CI -18.58 to -0.16), regardless of the intervention group (WEB vs PRINT: βgroup*time=-3.76, 95% CI -13.33 to 5.82, WEB+ vs PRINT: βgroup*time=1.40, 95% CI -11.04 to 13.83). Of the participants, 18.6% (38/204) met the PA recommendations at T0, 16.4% (26/159) at T1, and 20.3% (28/138) at T2. For SB, there were no significant group differences or group-by-time interactions at T1 or T2. Intervention acceptance was generally high. The use of intervention material was high to moderate at T1 and decreased by T2.

CONCLUSIONS

There was little movement between intervention groups at T1 when given the choice, and participation was not associated with increases in PA or decreases in SB over time.

TRIAL REGISTRATION

German Clinical Trials Register DRKS00016073; https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00016073.