Longitudinal trajectories of physical activity in women using latent class growth analysis: The WIN Study

Seasonal changes in daily steps of community-dwelling older individuals with and without lifestyle-related diseases: a retrospective cohort study

[Purpose] Physical activity helps prevent diseases and mitigate their severity in older individuals with lifestyle-related conditions. We investigated whether seasonal factors and existing diseases affect physical activity in this demographic to identify lifestyle guidance indicators for health maintenance. [Participants and Methods] We compared the daily steps of older individuals (age of ≥65 years) by month, sex, and disease status from August to January by using three-way analysis of covariance. We evaluated a total of 115 participants (83 females and 32 males). [Results] Females with diseases had significantly fewer monthly daily steps than females without diseases in November (mean difference=1,138 ± 220) and December (mean difference=1,578 ± 239). Throughout, males with diseases completed significantly fewer monthly daily steps than did males without diseases. Furthermore, monthly daily steps never differed significantly between females with diseases and their male counterparts. [Conclusion] Compared with healthy older individuals, in older persons with diseases, physical activity was lower year-round among males and in November and December among females. Separate daily step count goals may be required for health maintenance in both sexes. It is important to determine the daily steps necessary to prevent various diseases and mitigate their severity while maintaining physical activity among older persons with diseases.

The potential of a multimodal digital care program in addressing healthcare inequities in musculoskeletal pain management

Digital interventions have emerged as a solution for time and geographical barriers, however, their potential to target other social determinants of health is largely unexplored. In this post-hoc analysis, we report the impact of social deprivation on engagement and clinical outcomes after a completely remote multimodal musculoskeletal (MSK) digital care program managed by a culturally-sensitive clinical team. Patients were stratified in five categories according to their social deprivation index, and cross-referenced with their race/ethnicity, rurality and distance to healthcare facilities. From a total of 12,062 patients from all U.S. states, 8569 completed the program. Higher social deprivation was associated with greater baseline disease burden. We observed that all categories reported pain improvements (ranging from -2.0 95%CI -2.1, -1.9 to -2.1 95%CI -2.3, -1.9, p < 0.001) without intergroup differences in mean changes or responder rates (from 59.9% (420/701) to 66.6% (780/1172), p = 0.067), alongside reduction in analgesic consumption. We observed significant improvements in mental health and productivity across all categories, with productivity and non-work-related functional recovery being greater within the most deprived group. Engagement was high but varied slightly across categories. Together these findings highlight the importance of a patient-centered digital care program as a tool to address health inequities in musculoskeletal pain management. The idea of investigating social deprivation within a digital program provides a foundation for future work in this field to identify areas of improvement.

Physical Activity Patterns among Individuals with Prediabetes or Type 2 Diabetes across Two Years-A Longitudinal Latent Class Analysis

BACKGROUND

This study aimed to identify distinct profiles of physical activity (PA) patterns among individuals with prediabetes or type 2 diabetes participating in a two-year PA trial and to investigate predictors of the profiles.

METHODS

Data (n = 168, collected 2013-2020) from the cohort of a randomized trial aimed at increasing PA in individuals with prediabetes and type 2 diabetes were used. PA and sedentary behaviours were assessed by waist-worn ActiGraph GT1M accelerometers at baseline and at 6, 12, 18 and 24 months. Fifteen PA and sedentary variables were entered into a latent class mixed model for multivariate longitudinal outcomes. Multinominal regression analysis modelled profile membership based on baseline activity level, age, gender, BMI, disease status and group randomisation.

RESULTS

Two profiles of PA patterns were identified: "Increased activity" (n = 37, 22%) included participants increasing time in PA and decreasing sedentary time. "No change in activity" (n = 131, 78%) included participants with no or minor changes. "Increased activity" were younger (p = 0.003) and more active at baseline (p = 0.011), compared to "No change in activity". No other predictor was associated with profile membership.

CONCLUSIONS

A majority of participants maintained PA and sedentary patterns over two years despite being part of a PA intervention. Individuals improving PA patterns were younger and more active at baseline.

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

BACKGROUND

This study aimed to identify latent moderate-to-vigorous intensity physical activity (MVPA) and sedentary behavior (SB) trajectories in older adults participating in a randomized intervention trial and to explore associations with baseline social-cognitive predictors.

METHODS

Data were assessed at baseline (T0, participants were inactive or had recently become active), after a ten-week physical activity intervention (T1), and a second 24-week intervention phase (T2). Latent class growth analysis was used on accelerometer-assessed weekly MVPA and daily SB, respectively (n = 215 eligible participants). Activity changes within trajectory classes and baseline social-cognitive predictor differences between trajectory classes were analyzed.

RESULTS

A "stable insufficient MVPA" (n = 197, p for difference in MVPA level at T0 and T2 (pT0-T2) = .789, effect size (Cohen's d) = .03) and a "stable high MVPA" trajectory (n = 18, pT0-T2 = .137, d = .39), as well as a "slightly decreasing high SB" (n = 63, p for difference in SB (pT0-T2) = .022, d = .36) and a "slightly increasing moderate SB" trajectory (n = 152, pT0-T2 = .019, d = .27) emerged. Belonging to the "stable high MVPA" trajectory was associated with higher action planning levels compared to the "stable insufficient MVPA" trajectory (M = 5.46 versus 4.40, d = .50). Belonging to the "decreasing high SB" trajectory was associated with higher action self-efficacy levels compared to the "increasing moderate SB" trajectory (M = 5.27 versus 4.72, d = .33).

CONCLUSIONS

Change occurred heterogeneously in latent (not directly observed) subgroups, with significant positive trajectories only observed in the highly sedentary.

TRIAL REGISTRATION

German Registry of Clinical Trials, DRKS00016073 , Registered 10 January 2019.

Impact of Seasonality on Physical Activity: A Systematic Review

BACKGROUND

The purpose of this study was to collect and analyze the available scientific evidence of the impact of seasonality on physical activity (PA). PA refers to walking, biking, sports and/or active recreation.

METHODS

The search was performed in the following databases: PubMed, PEDro, Cochrane and Embase. All publications from January 2015 to September 2020 assessing seasonal variations on physical activity development in adults were selected.

RESULTS

A total of 1159 articles were identified, of which 26 fulfilled the selection criteria involving 9300 participants from 18 different countries. The results obtained suggest that seasonality affects PA independently of the countries, pathologies of the participants and the tool to collect PA information.

CONCLUSIONS

PA level varies across the seasons, with higher PA level in summer compared with other seasons, especially in winter. Sedentary behavior follows the opposite trend. Impact of seasonality variations should be considered in clinical research involving PA as a primary outcome as well as in interventions on PA promotion.

A trajectory analysis of daily step counts during a physician-delivered intervention

OBJECTIVES

Higher steps are associated with lower mortality and cardiovascular event rates. We previously demonstrated that tailored physician-delivered step count prescriptions successfully increased steps/day in adults with type 2 diabetes mellitus (T2DM) and/or hypertension. In the present analysis, we examined patterns of step count change and the factors that influence different responses.

DESIGN

Longitudinal observational study METHODS: Active arm participants (n=118) recorded steps/day. They received a step count prescription from their physician every 3-4 months. We computed mean steps/day and changes from baseline for sequential 30-day periods. Group-based trajectory modeling was applied.

RESULTS

Four distinct trajectories of mean steps/day emerged, distinguishable by differences in baseline steps/day: sedentary (19%), low active (40%), somewhat active (30%) and active (11%). All four demonstrated similar upward slopes. Three patterns emerged for the change in steps from baseline: gradual decrease (30%), gradual increase with late decline (56%), and rapid increase with midpoint decline (14%); thus 70% had an increase from baseline. T2DM (odd ratios [OR]: 3.7, 95% CI 1.7, 7.7) and age (OR per 10-year increment: 2, 95% CI 1.3, 2.8) were both associated with starting at a lower baseline but participants from these groups were no less likely than others to increase steps/day.

CONCLUSIONS

T2DM and older age were associated with lower baseline values but were not indicators of likelihood of step count increases. A physician-delivered step count prescription and monitoring strategy has strong potential to be effective in increasing steps irrespective of baseline counts and other clinical and demographic characteristics.

Distinct trajectories of physical activity and related factors during the life course in the general population: a systematic review

BACKGROUND

In recent years, researchers have begun applying a trajectory approach to identify homogeneous subgroups of physical activity (PA) in heterogeneous populations. This study systematically reviewed the articles identifying longitudinal PA trajectory classes and the related factors (e.g., determinants, predictors, and outcomes) in the general population during different life phases.

METHODS

The included studies used finite mixture models for identifying trajectories of PA, exercise, or sport participation. Three electronic databases, PubMed (Medline), Web of Science, and CINAHL, were searched from the year 2000 to 13 February 2018. The study was conducted according to the PRISMA recommendations.

RESULTS

Twenty-seven articles were included and organized into three age group: youngest (eleven articles), middle (eight articles), and oldest (eight articles). The youngest group consisted mainly of youth, the middle group of adults and the oldest group of late middle-aged and older adults. Most commonly, three or four trajectory classes were reported. Several trajectories describing a decline in PA were reported, especially in the youngest group, whereas trajectories of consistently increasing PA were observed in the middle and oldest group. While the proportion of persistently physically inactive individuals increased with age, the proportion was relatively high at all ages. Generally, male gender, being Caucasian, non-smoking, having low television viewing time, higher socioeconomic status, no chronic illnesses, and family support for PA were associated either with persistent or increasing PA.

CONCLUSIONS

The reviewed articles identified various PA subgroups, indicating that finite mixture modeling can yield new information on the complexity of PA behavior compared to studying population mean PA level only. The studies also provided novel information how different factors relate to changes in PA during life course. The recognition of the PA subgroups and their determinants is important for the more precise targeting of PA promotion and PA interventions.

TRIAL REGISTRATION

PROSPERO registration number: CRD42018088120 .