Changes in Accelerometer-Measured Physical Activity and Sedentary Time Across Retirement Transition as a Predictor of Self-Rated Health.

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.

Longitudinal Associations between 24-H Movement Behaviors and Cardiometabolic Biomarkers: A Natural Experiment over Retirement.

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 age 63.5 years, SD 1.1) 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 (one year in-between). Cardiometabolic biomarkers, including LDL-cholesterol, HDL-cholesterol, total:HDL-cholesterol ratio, triglycerides, C-reactive protein (CRP), 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. 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 decrease in triglycerides. Findings related to LDL-cholesterol, CRP, 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.

Finnish Retirement and Aging Study: a prospective cohort study.

PURPOSE: The Finnish Retirement and Aging (FIREA) Study was set up to study changes in health behavioural and cardiometabolic risk factors across retirement transition, and to examine the long-term consequences of work and retirement on health and functioning with advancing age. PARTICIPANTS: Public sector workers whose estimated statutory retirement date was in 2014-2019 were invited to participate by sending them a questionnaire 18 months prior to their estimated retirement date. In the first phase of the FIREA Study, participants were followed up with annual surveys, accelerometer and clinical measurements during retirement transition into post-retirement years. The FIREA survey cohort includes 6783 participants, of which 908 belong also to the activity substudy and 290 to the clinical substudy. FINDINGS TO DATE: Collected data include survey measures about health, lifestyle factors, psychosocial distress, work-related factors as well as retirement intentions. Accelerometer and GPS devices are used to measure 24-hour movement behaviours. Clinical examination includes blood and hair sample, measurements of anthropometry, cardiovascular function, physical fitness, physical and cognitive function. Our results suggest that in general retirement transition seems to have beneficial influence on health behaviours as well as on physical and mental health, but there are large individual differences, and certain behaviours such as sedentariness tend to increase especially among those retiring from manual occupations. FUTURE PLANS: The second phase of the FIREA Study will be conducted during 2023-2025, when participants are 70 years old. The FIREA Study welcomes research collaboration proposals that fall within the general aims of the project.

Weekday and weekend physical activity patterns and their correlates among young adults.

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.

Modifications of 24-h movement behaviors to prevent obesity in retirement: a natural experiment using compositional data analysis.

BACKGROUND: Retirement often leads to a more passive lifestyle and may therefore lead to weight gain. This study aims to investigate longitudinal associations between changes in 24-h movement behaviors and BMI and waist circumference in relation to the transition from work to retirement. METHODS: The study population included 213 retiring public sector workers (mean age 63.5 years, standard deviation 1.1) from the Finnish Retirement and Aging study. Before and after retirement participants wore an Axivity accelerometer on their thigh and filled in a daily log for at least four days to measure daily time spent sleeping, in sedentary behavior (SED), light physical activity (LPA) and moderate-to-vigorous physical activity (MVPA). Also, their body mass index (BMI) and waist circumference were measured repeatedly. Compositional linear regression analysis and isotemporal substitution analysis were used to study associations between one-year changes in 24-h movement behaviors and concurrent changes in BMI and waist circumference. RESULTS: An increase in MVPA in relation to sleep, SED and LPA was associated with a decreasing BMI (ß = -0.60, p = 0.04) and waist circumference (ß = -2.14, p = 0.05) over one year from before retirement to after retirement. In contrast, increasing sleep in relation to SED, LPA and MVPA was associated with an increasing BMI (ß = 1.34, p = 0.02). Reallocating 60 min from MVPA to SED or sleep was estimated to increase BMI by on average 0.8-0.9 kg/m2 and waist circumference by 3.0 cm during one year. CONCLUSIONS: During the transition from work to retirement, increasing MVPA was associated with a slight decrease in BMI and waist circumference, whereas increasing sleep was associated with an increasing BMI. Common life transitions, like retirement, should be considered when giving recommendations and guidance for physical activity and sleep.

Association of Sit-to-Stand Capacity and Free-Living Performance Using Thigh-Worn Accelerometers among 60- to 90-Yr-Old Adults.

PURPOSE: Five times sit-to-stand (STS) test is commonly used as a clinical assessment of lower-extremity functional ability, but its association with free-living performance has not been studied. Therefore, we investigated the association between laboratory-based STS capacity and free-living STS performance using accelerometry. The results were stratified according to age and functional ability groups. METHODS: This cross-sectional study included 497 participants (63% women) 60-90 yr old from three independent studies. A thigh-worn triaxial accelerometer was used to estimate angular velocity in maximal laboratory-based STS capacity and in free-living STS transitions over 3-7 d of continuous monitoring. Functional ability was assessed with short physical performance battery. RESULTS: Laboratory-based STS capacity was moderately associated with the free-living mean and maximal STS performance ( r = 0.52-0.65, P < 0.01). Angular velocity was lower in older compared with younger and in low- versus high-functioning groups, in both capacity and free-living STS variables (all P < 0.05). Overall, angular velocity was higher in capacity compared with free-living STS performance. The STS reserve (test capacity - free-living maximal performance) was larger in younger and in high-functioning groups compared with older and low-functioning groups (all P < 0.05). CONCLUSIONS: Laboratory-based STS capacity and free-living performance were found to be associated. However, capacity and performance are not interchangeable but rather provide complementary information. Older and low-functioning individuals seemed to perform free-living STS movements at a higher percentage of their maximal capacity compared with younger and high-functioning individuals. Therefore, we postulate that low capacity may limit free-living performance.

Daily Physical Activity Patterns and Their Associations with Cardiometabolic Biomarkers: The Maastricht Study.

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.

Meanings Attributed to Physical Activity and Changes in Self-Reported and Accelerometer-Measured Physical Activity among Recent Retirees.

Retirement poses opportunities and challenges for maintaining and adopting physically active habits, which may have major implications for health and functional ability in later life. Qualitative studies suggest that a broad range of meanings of physical activity should be considered when promoting physical activity among retirees. The current study utilized the Physical Activity Relationship (PAR) approach to examine the importance of meanings attributed to physical activity and their associations with physical activity over time. A total of 230 recently retired participants (65.2 years old, 83% women) responded to a 54-item inventory assessing the importance of meanings attributed to physical activity at baseline. Eight meaning dimensions were identified through exploratory factor analysis. Differences in their importance across gender and occupational background were examined using t-tests and ANOVA. Associations between meaning dimensions and self-reported and accelerometer-measured physical activity over 12 months were examined with general linear models. Dimensions defined as Physical Fitness, Positive Mood, and Belonging were positively associated with changes in self-reported and accelerometer-measured physical activity. Additionally, the importance of several meaning dimensions varied across occupational background. In conclusion, physical activity promotion among retirees should focus on physical fitness, positive mood, and social belonging. Furthermore, meanings attributed to physical activity may vary across occupational backgrounds.

Work ability and physical fitness among aging workers: the Finnish Retirement and Aging Study.

Background: With advancing age, physical capacity gradually decreases which may lead to decreased work ability, if the physical work requirements remain the same. Examination of the importance of physical fitness for work ability among aging workers will help to find potential strategies to promote work ability in old age. The aim of this study was to investigate the association between physical fitness and work ability among aging workers. Methods: Aging workers (n = 288, mean age 62.5, 83% women) from the Finnish Retirement and Aging study underwent cardiorespiratory, muscular fitness and functional testing. Work ability was inquired on a scale 0-10 from poor to excellent. Association between physical fitness indicators and work ability was examined using ordinary least squares regression, taking into account age, gender, occupational status, heavy physical work, body mass index and accelerometer-measured daily total physical activity. Results: VO2peak, modified push-up test and maximal walking speed were positively associated with work ability (ß = 0.51, 95% confidence interval (CI) 0.29-0.74, ß = 0.46, 95% CI 0.26-0.66 and ß = 0.23, 95% CI 0.07-0.39, respectively), while chair rise test time was inversely associated with work ability (ß = -0.23, 95% CI -0.39--0.06). No associations were found between hand grip strength or sit-up test and work ability. Conclusions: Cardiorespiratory fitness, upper body strength, and lower extremity function were positively associated with work ability. Good physical fitness may help to maintain work ability among aging workers. Supplementary Information: The online version contains supplementary material available at 10.1007/s10433-022-00714-1.

Changes in the 24-h movement behaviors during the transition to retirement: compositional data analysis.

BACKGROUND: Transition to retirement is shown to affect sleep, sedentary time and physical activity, but no previous studies have examined how retirement changes the distribution of time spent daily in these movement behaviors. The aim of this study was to examine longitudinally how the composition of 24-h movement behaviors changes during the transition to retirement using compositional data analysis (CoDA). METHODS: We included 551 retiring public sector workers (mean age 63.2 years, standard deviation 1.1) from the Finnish Retirement and Aging study. The study participants wore a wrist-worn ActiGraph accelerometer for one week 24 h per day before and after retirement, with one year between the measurements. The daily proportions to time spent sleeping, in sedentary behavior (SED), light physical activity (LPA) and moderate-to-vigorous physical activity (MVPA) were estimated using the GGIR package. Changes in the daily proportions of movement behaviors were examined using Compositional Data Analysis version of linear mixed models. RESULTS: In general, the proportion of time spent in active behaviors decreased relative to time spent in passive behaviors after retirement (p < .001). This change depended on occupation (occupation*time interaction p < .001). After retirement manual workers increased the proportions of both sleep and SED in relation to active behaviors, whereas non-manual workers increased the proportion of sleep in relation to active behaviors and SED. The proportion of MVPA decreased relatively more than the proportion of LPA (p = 0.01), independently of gender and occupation. CONCLUSIONS: Retirement induced a decrease in the proportion of time spent in active behaviors, especially time spent in MVPA. Future studies are needed to find ways to maintain or increase daily physical activity levels at the cost of sedentary behaviors among retirees.

Physical activity and health: Findings from Finnish monozygotic twin pairs discordant for physical activity.

Genetic and early environmental differences including early health habits associate with future health. To provide insight on the causal nature of these associations, monozygotic (MZ) twin pairs discordant for health habits provide an interesting natural experiment. Twin pairs discordant for leisure-time physical activity (LTPA) in early adult life is thus a powerful study design to investigate the associations between long-term LTPA and indicators of health and wellbeing. We have identified 17 LTPA discordant twin pairs from two Finnish twin cohorts and summarize key findings of these studies in this paper. The carefully characterized rare long-term LTPA discordant MZ twin pairs have participated in multi-dimensional clinical examinations. Key findings highlight that compared with less active twins in such MZ twin pairs, the twins with higher long-term LTPA have higher physical fitness, reduced body fat, reduced visceral fat, reduced liver fat, increased lumen diameters of conduit arteries to the lower limbs, increased bone mineral density in loaded bone areas, and an increased number of large high-density lipoprotein particles. The findings increase our understanding on the possible site-specific and system-level effects of long-term LTPA.

Effects of physical activity intervention on 24-h movement behaviors: a compositional data analysis.

We utilized compositional data analysis (CoDA) to study changes in the composition of the 24-h movement behaviors during an activity tracker based physical activity intervention. A total of 231 recently retired Finnish retirees were randomized into intervention and control groups. The intervention participants were requested to use a commercial activity tracker bracelet with daily activity goal and inactivity alerts for 12 months. The controls received no intervention. The 24-h movement behaviors, i.e., sleep, sedentary time (SED), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) were estimated from wrist-worn ActiGraph data using the GGIR R-package. Three balance coordinates describing the composition of movement behaviors were applied: ratio of active vs. passive behaviors, LPA vs. MVPA, and sleep vs. SED. A linear mixed model was used to study changes between the baseline and 6-month time point. Overall, the changes in the 24-h movement behaviors were small and did not differ between the groups. Only the ratio of LPA to MVPA tended to change differently between the groups (group*time interaction p = 0.08) as the intervention group increased LPA similarly to controls but decreased their MVPA. In conclusion, the use of a commercial activity tracker may not be enough to induce changes in the 24-h movement behaviors among retirees.

The Effect of a Consumer-Based Activity Tracker Intervention on Accelerometer-Measured Sedentary Time Among Retirees: A Randomized Controlled REACT Trial.

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 Impact of a 12-Month Activity Tracker Intervention on Activity Behavior Across Body Mass Index Subgroups Among Recent Retirees: Post Hoc Analysis of a Randomized Controlled Trial.

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.

The Effect of Consumer-based Activity Tracker Intervention on Physical Activity among Recent Retirees-An RCT Study.

PURPOSE: The randomized controlled trial REACT (NCT03320746) examined the effect of a 12-month consumer-based activity tracker intervention on accelerometer-measured physical activity among recent retirees. METHODS: Altogether 231 recently retired Finnish adults (age, 65.2 ± 1.1 yr, mean ± SD; 83% women) were randomized to intervention and control groups. Intervention participants were requested to wear a commercial wrist-worn activity tracker (Polar Loop 2; Polar, Kempele, Finland) for 12 months, to try to reach the daily activity goals shown on the tracker display, and to upload their activity data to a Web-based program every week. The control group received no intervention. Accelerometer-based outcome measurements of daily total, light physical activity (LPA), and moderate to vigorous (MVPA) physical activity were conducted at baseline and at 3-, 6-, and 12-month time points. Hierarchical linear mixed models were used to examine the differences between the groups over time. All analyses were performed by intention-to-treat principle and adjusted for wake wear time. RESULTS: The use of a commercial activity tracker did not increase daily total activity, LPA, or MVPA over the 12-months period when compared with nonuser controls (group-time interaction, P = 0.39, 0.23, and 0.77, respectively). There was an increase in LPA over the first 6 months in both the intervention (26 min·d-1, 95% confidence interval [CI] = 13 to 39) and the control (14 min·d-1, 95% CI = 1 to 27) groups, but the difference between the groups was not significant (12 min·d-1, 95% CI = -6 to 30). In both groups, LPA decreased from 6 to 12 months. CONCLUSION: The 12-month use of a commercial activity tracker does not appear to elicit significant changes in the daily total activity among a general population sample of recent retirees, thus highlighting the need to explore other alternatives to increase physical activity in this target group.

Contexts of sedentary time and physical activity among ageing workers and recent retirees: cross-sectional GPS and accelerometer study.

OBJECTIVES: We examined sedentary time and physical activity in different contexts among ageing workers, between their workdays and days off, and recent retirees, between their weekdays and weekend days. DESIGN: Cross-sectional study. SETTING: Finnish Retirement and Aging study and Enhancing physical activity and healthy ageing among recent retirees-Randomised controlled in-home physical activity trial. PARTICIPANTS: 137 workers (544 measurement days) and 53 retirees (323 days), who provided data for at least 1 workday/weekday and 1 day off/weekend day. PRIMARY AND SECONDARY OUTCOME MEASURES: Physical activity behaviour was measured with a combined Global Positioning System and accelerometer device (SenseDoc V.2.0), providing information on sedentary time, light physical activity and moderate-to-vigorous physical activity (MVPA) by locations (home or non-home) and trips (active travel, ie, speed <20 km/hour and passive travel, ie, speed ≥20 km/hour). RESULTS: Workers accumulated more sedentary time and physical activity at non-home locations than at home on workdays, while the opposite was confirmed for days off (p<0.01). Workers accrued more MVPA on days off than on workdays (34 vs 28 min, p<0.05), of which 9 min on workdays and 14 min on days off was accrued during active travel. Retirees' physical activity behaviour did not differ between weekdays and weekend days (p>0.05). Regardless of the day, retirees accumulated 33 min of daily MVPA, of which 14 min was accrued during active travel. CONCLUSIONS: Workers accumulated more MVPA on days off than on workdays, and their activity behaviour varied between workdays and days off at different locations. Our results showed that a large proportion of the MVPA was accumulated during travel at slower speeds, which suggests that active travel could be a feasible way to increase MVPA among older adults. TRIAL REGISTRATION NUMBER: NCT03320746.

The Effect of Commercial Activity Tracker Based Physical Activity Intervention on Body Composition and Cardiometabolic Health Among Recent Retirees.

The REACT is a commercial activity tracker based intervention, which primarily aimed to increase physical activity. This study examines the secondary outcomes of the physical activity intervention on body composition and cardiometabolic health indicators. Overall 231 recently retired Finnish men and women [65.2 (SD 1.1) years, 83% women] took part to the study. The participants were randomized into intervention (n = 117) and control (n = 114) groups. The intervention group members used a commercial activity tracker (Polar Loop 2, Polar, Kempele, Finland) with a daily activity goal and inactivity alerts every day for 12 months. Controls received no intervention. Secondary health outcomes included body weight, fat mass, fat free mass, waist circumference, blood pressure, indicators of glucose and lipid metabolisms, and high-sensitivity C-reactive protein, and they were measured at baseline and at 12-months end point. Hierarchical linear mixed models were used to examine the differences between the groups over time, and no differences in the mean changes of the body composition and cardiometabolic health indicators between the groups were found (group*time interaction >0.20 for all measures). Fat free mass, waist circumference, blood pressure, and low density lipoprotein levels decreased in both groups over the 12 months. These findings state that 1-year daily use of commercial activity tracker does not induce different cardiometabolic health effects when compared to the non-user controls among general population of recent retirees.

Changes in body composition by age and obesity status in preschool-aged children: the STEPS study.

BACKGROUND/OBJECTIVES: Obesity in early childhood is associated with increased risk of chronic diseases, but studies of body composition at preschool ages are sparse. Therefore, we examined differences in body composition by sex and obesity status in Finnish preschool-aged children and within-individual changes in body composition in normal and overweight children. SUBJECT/METHODS: Body composition was measured using segmental multifrequency bioimpedance analysis (BIA) in 476 children and in 781 children at age 3 and 5 years, respectively. Of those, 308 had repeated BIA measurements at both ages. BMI-SDS was used for classification of normal weight and overweight children. RESULTS: Sex difference in the amount of lean mass (LM) was already seen at 3 years of age (boys 11.7 kg, girls 11.3 kg; p < 0.001). At 5 years of age, boys had lower fat mass (FM; 3.6 kg vs. 3.9 kg, p < 0.001), lower percent fat mass (%FM; 17.2% vs. 19.1%; p < 0.001), and higher LM (16.0 kg vs. 15.2 kg; p < 0.001) than girls. Overweight children had higher values in FM, %FM, and LM compared with normal weight peers at both ages. Among normal weight children, the increase of LM by age was associated with only minor changes in FM, whereas children who were or became overweight both LM and FM was substantially increased between 3 and 5 years of age. CONCLUSIONS: BIA-assessed body composition differs by sex and obesity status already at age of 3 years. For children who are or become overweight at very young age, the patterns for the changes in LM and FM by age are different than for normal weight children.

Daily Physical Activity Patterns and Their Association With Health-Related Physical Fitness Among Aging Workers-The Finnish Retirement and Aging Study.

BACKGROUND: This study aimed to identify accelerometer-measured daily physical activity patterns, and to examine how they associate with health-related physical fitness among aging workers. METHODS: The study population consisted of 263 participants (mean age 62.4 years, SD 1.0) from the Finnish Retirement and Aging study, who used wrist-worn ActiGraph accelerometer for at least 1 week including both workdays and days off. Health-related physical fitness measures included body composition (waist circumference, bioimpedance), cardiorespiratory fitness (bicycle ergometer test), and muscular fitness (push-up and chair rise tests). RESULTS: Based on the latent class trajectory analysis, 6 trajectories were identified for workdays showing variation in activity level on working hours and on evening hours. Moderate activity during working hours and increase of activity level in the evening was associated with the most favorable health-related fitness in comparison to low activity throughout the workday: waist circumference 90.0 cm (95% confidence interval [CI] 85.5-94.5) versus 99.5 cm (95% CI 96.8-102.3), fat mass 13.9 kg (9.3-18.5) versus 23.8 kg (20.2-27.4), cardiorespiratory fitness 33.4 mL/kg/min (95% CI 31.4-35.3) versus 29.1 mL/kg/min (95% CI 27.8-30.3) (adjusted for age, sex, days off activity, smoking, and alcohol). For the days off, 2 different trajectories were identified, but they differed only in terms of level and not by timing of physical activity. CONCLUSIONS: A large variation in the workday physical activity patterns was observed among aging workers. Independent of worktime activity, people who were more active in the evenings had more favorable health-related physical fitness than those who were less active throughout the day.

Leisure-Time and Occupational Physical Activity Associates Differently with Epigenetic Aging.

PURPOSE: Greater leisure-time physical activity (LTPA) associates with healthier lives, but knowledge regarding occupational physical activity (OPA) is more inconsistent. DNA methylation (DNAm) patterns capture age-related changes in different tissues. We aimed to assess how LTPA and OPA are associated with three DNAm-based epigenetic age estimates, namely, DNAm age, PhenoAge, and GrimAge. METHODS: The participants were young adult (21-25 yr, n = 285) and older (55-74 yr, n = 235) twin pairs, including 16 pairs with documented long-term LTPA discordance. Genome-wide DNAm from blood samples was used to compute DNAm age, PhenoAge, and GrimAge Age acceleration (Acc), which describes the difference between chronological and epigenetic ages. Physical activity was assessed with sport, leisure-time, and work indices based on the Baecke Questionnaire. Genetic and environmental variance components of epigenetic age Acc were estimated by quantitative genetic modeling. RESULTS: Epigenetic age Acc was highly heritable in young adult and older twin pairs (~60%). Sport index was associated with slower and OPA with faster DNAm GrimAge Acc after adjusting the model for sex. Genetic factors and nonshared environmental factors in common with sport index explained 1.5%-2.7% and 1.9%-3.5%, respectively, of the variation in GrimAge Acc. The corresponding proportions considering OPA were 0.4%-1.8% and 0.7%-1.8%, respectively. However, these proportions were minor (<0.5%) after adjusting the model for smoking status. CONCLUSIONS: LTPA associates with slower and OPA with faster epigenetic aging. However, adjusting the models for smoking status, which may reflect the accumulation of unhealthy lifestyle habits, attenuated the associations.