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Background: Retirement transition has been shown to associate with changes in physical activity (PA) and self-rated health (SRH), but their interrelationship is less studied. The aim was to investigate changes in accelerometer-measured total PA, moderate to vigorous PA (MVPA), and sedentary time across retirement transition as a predictor of SRH. Methods: Data from the Swedish Retirement Study and the Finnish Retirement and Aging study were harmonized and pooled. Data from 3 waves (about 12 mo apart) were included: 1 preretirement (wave 1) and 2 postretirement follow-ups (wave 2–3). A totally of 245 participants (27% men) were included. Thigh-worn accelerometers were used to collect data for PA variables (wave 1–2), and SRH was obtained from the questionnaire (wave 1–3). Results: Between wave 1 and 2, total PA decreased with 11 (CI, −22 to −1) minutes per day, MVPA was stable (0 [CI, −3 to 3] min), and sedentary time decreased nonsignificantly with 9 (CI, −20 to 1) minutes. SRH changed between all 3 waves (all P <.001). At preretirement, 10 more minutes of MVPA was associated with greater odds of better SRH when adjusting for accelerometer wear-time, cohort, sex, age, and occupational status (odds ratio: 1.11 [95% CI, 1.02–1.22]). This association was no longer statistically significant when additionally adjusting for marital status, body mass index, and smoking. No significant associations were observed between changes in the PA variables during retirement transition and SRH at postretirement follow-ups. Conclusions: This study showed a cross-sectional association between MVPA and greater odds of reporting better SRH before retirement. No longitudinal associations were observed between changes in the PA variables from before to after retirement and later changes in SRH. [ABSTRACT FROM AUTHOR]

Introduction: Physical activity, sedentary behavior, and sleep, that is, 24-h movement behaviors, often change in the transition from work to retirement, which may affect cardiometabolic health. This study investigates the longitudinal associations between changes in 24-h movement behaviors and cardiometabolic biomarkers during the retirement transition. Methods: Retiring public sector workers (n = 212; mean (SD) age, 63.5 (1.1) yr) from the Finnish Retirement and Aging study used a thigh-worn Axivity accelerometer and filled out a diary to obtain data on daily time spent in sedentary behavior (SED), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA), and sleep before and after retirement (1 yr in-between). Cardiometabolic biomarkers, including LDL-cholesterol, HDL-cholesterol, total/HDL-cholesterol ratio, triglycerides, C-reactive protein, fasting glucose, and insulin, were measured. Associations between changes in 24-h movement behaviors and cardiometabolic biomarkers were analyzed using compositional robust regression and isotemporal substitution analysis. Results: Increasing LPA in relation to remaining behaviors was associated with an increase in HDL-cholesterol and decrease in total/HDL-cholesterol ratio ( P < 0.05 for both). For instance, reallocation of 30 min from sleep/SED to LPA was associated with an increase in HDL-cholesterol by 0.02 mmol⋅L-1. Moreover, increasing MVPA in relation to remaining behaviors was associated with a decrease in triglycerides ( P = 0.02). Reallocation of 30 min from SED/sleep to MVPA was associated with 0.07-0.08 mmol⋅L-1 decrease in triglycerides. Findings related to LDL-cholesterol, C-reactive protein, fasting glucose, and insulin were less conclusive. Conclusions: During the transition from work to retirement, increasing physical activity at the expense of passive behaviors was associated with a better lipid profile. Our findings suggest that life transitions like retirement could be utilized more as an optimal time window for promoting physical activity and health. [ABSTRACT FROM AUTHOR]

Background: This study examined the effectiveness of a 12-month activity tracker-based intervention on activity behavior among recent retirees (Enhancing physical ACTivity and healthy aging among recent REtirees [REACT]) in subgroups based on body mass index. Methods: REACT trial randomized 231 participants (mean age 65.2) into intervention and control groups. Main outcomes were accelerometer-measured moderate-to-vigorous (MVPA) and light physical activity (LPA) and sedentary time (SED) measured at baseline and 3-, 6-, and 12-month follow-ups. As a post hoc analysis, the intervention effect was examined among participants with normal weight (n = 77), overweight (n = 89), and obesity (n = 61). Results: An intervention effect was observed among participants with obesity in LPA (time × group P =.045) mirrored by a similar, albeit nonsignificant, effect in SED (P =.067), but not in MVPA (P =.92). A transient increase of 41 minutes per day (95% confidence interval, 14 to 68) in LPA was observed at 6 months among the intervention group, with a concomitant decrease of 42 minutes per day (−72 to −12) in SED. However, these changes were not maintained at 12 months. No between-group differences in changes over time were observed among participants with normal or overweight. Conclusions: Activity trackers may be particularly suitable for promoting changes in LPA and SED among older adults with obesity. However, their long-term effectiveness might be limited. [ABSTRACT FROM AUTHOR]

Background: Accelerometers enable assessment of within and between day variation in physical activity. The main aim was to examine weekday and weekend physical activity patterns among young adults. Additionally, correlates of the physical activity patterns were examined. Methods: Overall 325 adults (mean age 26.0 years, standard deviation 0.03) from the Special Turku Coronary Risk Factor Intervention Project used a wrist‐worn ActiGraph accelerometer continuously for 1 week. Physical activity patterns over weekdays and weekends were identified by using the group‐based trajectory modeling. Adolescent leisure time physical activity (LTPA) and sociodemographic characteristics (sex, marital and family status, education, work status, occupation, and health consciousness) were examined as possible correlates of physical activity patterns using multinomial regression analysis. Results: Five patterns were identified: consistently low activity (45%), active on weekday evenings and weekends (32%), consistently moderate activity (11%), active on weekdays (7%), and consistently high activity (5%). Low adolescent LTPA was associated with consistently low activity pattern in young adulthood. Women were more likely than men to belong in the more physically active groups (all other groups except active on weekdays, odds ratios between 2.26 and 6.17). Those in the active on weekdays group had lower education, were more often in the working life and in manual occupations than those in the consistently low activity group. Conclusions: Marked heterogeneity in physical activity patterns across the week was observed among young adults. Especially history of physical activity, sex, education, work status, and occupation were associated with different physical activity patterns. [ABSTRACT FROM AUTHOR]

There is scarcity of studies using device-based measures to examine how relationship and parenthood transitions modify 24-h movement behaviors. This study examined how the composition of 24-h movement behaviors changes during these life transitions. Young adults (n = 170, mean age 25.6 years, SD 0.6) from the Special Turku Coronary Risk Factor Intervention Project (STRIP) wore wrist-worn accelerometers for 1 week and completed questionnaire at ages 26 and 31 years. Participants were categorized by relationship status into single (16%), those transitioning from single to partnered (31%), partnered (47%), and separated (7%), and by parenthood status into non-parents (73%), new parents (19%), and parents (8%). Changes in daily movement behaviors, including sleep, sedentary behavior (SED), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA), were examined using compositional linear mixed models. In general, LPA and MVPA decreased relative to sleep and SED (p = 0.007). Differences emerged between LPA and MVPA in relationship and parenthood groups (p for group × time interaction 0.008 and 0.001). Those transitioning to partnership decreased MVPA by 17 min/day, while partnered and separated individuals showed no notable MVPA change but decreased LPA by 14 and 43 min/day. Single individuals and non-parents decreased LPA and MVPA in similar proportions. New parents decreased MVPA by 20 min/day, while parents increased it by 19 min/day. Becoming first-time parent and starting relationship was associated with decline of MVPA. Our results suggest the importance of considering these life transitions and providing guidance for maintaining physical activity despite changes in life situations., (© 2024 The Author(s). Scandinavian Journal of Medicine & Science In Sports published by John Wiley & Sons Ltd.)

Purpose: This study aimed to identify physical activity patterns and examine their association with cardiometabolic biomarkers in a cross-sectional design., Methods: Overall 6072 participants (mean age, 60.2 yr; SD 8.6 yr, 50% women) from The Maastricht Study provided daily physical activity data collected with thigh-worn activPAL3 accelerometers. The patterns of daily physical activity over weekdays and weekend days were identified by using Group Based Trajectory Modeling. Cardiometabolic biomarkers included body mass index, waist circumference, office blood pressure, glucose, HbA1c, and cholesterol levels. Associations between the physical activity patterns and cardiometabolic outcomes were examined using the analyses of covariance adjusted for sex, age, education, smoking, and diet. Because of statistically significant interaction, the analyses were stratified by type 2 diabetes status., Results: Overall, seven physical activity patterns were identified: consistently inactive (21% of participants), consistently low active (41%), active on weekdays (15%), early birds (2%), consistently moderately active (7%), weekend warriors (8%), and consistently highly active (6%). The consistently inactive and low active patterns had higher body mass index, waist, and glucose levels compared with the consistently moderately and highly active patterns, and these associations were more pronounced for participants with type 2 diabetes. The more irregular patterns accumulated moderate daily total activity levels but had rather similar cardiometabolic profiles compared with the consistently active groups., Conclusions: The cardiometabolic profile was most favorable in the consistently highly active group. All patterns accumulating moderate to high levels of daily total physical activity had similar health profile suggesting that the amount of daily physical activity rather than the pattern is more important for cardiometabolic health., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American College of Sports Medicine.)

Background: Effective strategies to reverse the increasing trend of sedentary behavior after retirement are needed. The aim of this study was to examine the effect of 12-month activity tracker-based intervention on daily total and prolonged sedentary time (≥60 minutes) among recent retirees., Methods: Randomization to intervention and control groups was performed to 231 retirees (mean age 65.2 [SD 1.1] years, 83% women). Intervention participants wore a consumer-based wrist-worn activity tracker (Polar Loop 2, Polar, Kempele, Finland), including daily activity goal, every day and night for 12 months. The activity tracker also gave vibrating reminders to break up uninterrupted inactivity periods after 55 minutes. A wrist-worn triaxial ActiGraph wGT3X-BT accelerometer was used to measure sedentary time at baseline and at 3-, 6-, and 12-month time points., Results: The use of an activity tracker did not reduce daily total or prolonged sedentary time over 12 months (p values for time * group interaction 0.39 and 0.27, respectively). In the post hoc analysis focusing on short- and medium-term effects on prolonged sedentary time, no differences between the intervention and control groups over 3 months were found, but a tendency for a greater decrease in prolonged sedentary time in the intervention group over 6 months was seen (mean difference in changes between the groups 29 minutes, 95% CI -2 to 61)., Conclusions: The activity tracker with inactivity alerts did not elicit changes in sedentary time over 12 months among recent retirees. Alternative approaches may be needed to achieve long-term changes in sedentary time among retirees. Clinical Trials registration Number: NCT03320746., (© The Author(s) 2021. Published by Oxford University Press on behalf of The Gerontological Society of America.)