Objectively Measured Sedentary Time Before and After Transition to Retirement: The Finnish Retirement and Aging Study

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.

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 (β = -0.60, p = 0.04) and waist circumference (β = -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 (β = 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.

Stability and longitudinal association between Body Mass Index and maladaptive eating behaviors in older adults: Results from the NutriAct Family Study (NFS)

PURPOSE

Due to the increasing prevalence of overweight and obesity with age and associated health risks, older adults are an important target group to promote healthy weight. Evidence indicates that maladaptive eating behaviors are associated with higher BMI. However, older adults are often neglected in this research field. This prospective study aims to clarify the temporal relationship between BMI and maladaptive eating behaviors among older adults.

METHODS

In total, 964 participants of the NutriAct Family Study (Mage = 63.34 years) completed web-based questionnaires two times (M = 3.33 years apart). BMI was assessed via self-reported height and weight, and maladaptive eating behaviors with the Dutch Eating Behavior Questionnaire (DEBQ). The stability and longitudinal associations were analyzed using cross-lagged models.

RESULTS

Cross-sectional analysis showed positive correlations between BMI and emotional (r = 0.218), external (r = 0.101), as well as restrictive eating (r = 0.160). All maladaptive eating behaviors (β > 0.684) and BMI (β > 0.922) were longitudinally stable. No significant bidirectional relationships were found between BMI and maladaptive eating behaviors over time, except for BMI predicting restrictive eating (β = 0.133).

CONCLUSION

The observed cross-sectional, but not longitudinal associations between BMI and maladaptive eating behaviors underline the need for prospective study designs to deepen the understanding of the role of maladaptive eating behaviors in weight management among the general population. Maladaptive eating behaviors among older adults may have already consolidated and play a smaller role in explaining weight course, compared to early life like childhood.

mHealth to Support Outdoor Gym Resistance Training: The ecofit Effectiveness RCT

INTRODUCTION

In Australia, 45% of adults meet the aerobic recommendations, and only 9%-30% meet the resistance training guidelines. Given the lack of at-scale community-based interventions promoting resistance training, the aim of this study was to assess the impact of an innovative mHealth intervention on upper- and lower-body muscular fitness, cardiorespiratory fitness, physical activity, and social-cognitive mediators among a sample of community-dwelling adults.

STUDY DESIGN

Researchers evaluated the community-based ecofit intervention using a cluster RCT from September 2019 to March 2022 in 2 regional municipalities of New South Wales, Australia.

SETTING/PARTICIPANTS

Researchers recruited a sample of 245 participants (72% female, aged 53.4±13.9 years) who were randomized to the ecofit intervention group (n=122) or waitlist control (n=123) group.

INTERVENTION

The intervention group received access to a smartphone application with standardized workouts tailored to 12 outdoor gym locations and an introductory session. Participants were encouraged to perform at least 2 ecofit workouts per week.

MAIN OUTCOME MEASURES

Primary and secondary outcomes were assessed at baseline, 3 months, and 9 months. The coprimary muscular fitness outcomes were evaluated using the 90-degree push-up and the 60-second sit-to-stand test. Intervention effects were estimated using linear mixed models accounting for group-level clustering (participants could enroll in groups of up to 4). Statistical analysis was conducted in April 2022.

RESULTS

Statistically significant improvements were observed in upper (1.4 repetitions, 95% CI=0.3, 2.6, p=0.018) and lower (2.6 repetitions, 95% CI=0.4, 4.8, p=0.020) body muscular fitness at 9 months but not at 3 months. Increases in self-reported resistance training, resistance training self-efficacy, and implementation intention for resistance training were statistically significant at 3 and 9 months.

CONCLUSION

This study has shown that a mHealth intervention promoting resistance training using the built environment can improve muscular fitness, physical activity behavior, and related cognitions in a community sample of adults.

TRIAL REGISTRATION

This trial was preregistered with the Australian and New Zealand Clinical Trial Registry (ACTRN12619000868189).

Physical Activity and Sedentary Behaviour with Retirement in Maltese Civil Servants: A Dialectical Mixed-Method Study

(1) Background: Retirement is a life event that can influence physical activity (PA) and sedentary behaviour (SB) and can be used as an opportunity to promote positive lifestyle choices. The aims of this study were to (a) to identify changes in PA and SB resulting from retirement and (b) to explore predictors of any changes in PA and SB following retirement in Maltese civil servants. (2) Methods: a hybrid mixed-method (MM) study, using first quantitative followed by qualitative methods, of civil servants aged ≥60 years, who were followed during their retirement transition for two years. A proportion of the research participants in the MM study retired while the others remained employed. Questionnaires and semi-structured interviews were used to collect data. (3) Results: there were no changes in total PA and sitting behaviour with retirement in Maltese civil servants. People who retired carried out more domestic PA compared to when they were in employment, which resulted in more moderate-intensity PA behaviour. People perceived that their sitting time increased with retirement in the qualitative interviews, but this was not observed in the quantitative data. Past PA behaviour was an important predictor of future PA behaviour, but not for SB. (4) Conclusions: A change in PA occurs with the retirement transition. However, the uptake of exercise is a personal choice that is dependent on previous experience. Increasing SB is perceived as part of the retirement plan but is not necessarily seen in the measured quantitative data.

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12966-022-01364-3.

Socioeconomic Differences in Physical Activity and Sedentary Behavior During the Retirement Transition: A Systematic Review of Longitudinal Studies

BACKGROUND

The retirement transition constitutes both a risk and an opportunity for changes in physical activity (PA) and sedentary behavior (SB). The present systematic review aims to summarize the current evidence regarding the differences between socioeconomic status (SES) groups in changes in PA and SB across the retirement transition.

METHODS

The authors searched 5 databases. Inclusion criteria were: investigating statutory retirement, measuring PA and/or SB at least once before and once after retirement, and reporting information on SES differences. Results are reported by means of a narrative synthesis, combined with harvest plots based on direction of effect.

RESULTS

We included 24 papers from 19 studies. Sixteen papers focused on PA, 3 on SB, and 5 investigated both. For total PA, occupational PA, and total sedentary time, nearly all publications reported more favorable changes for high SES groups. For recreational PA, active transport, and screen time, there seemed to be a tendency toward more favorable changes for high SES groups. Changes in household/caregiving PA did not appear to differ between SES groups.

CONCLUSIONS

Changes in movement behavior during the retirement transition are potentially more favorable for high SES adults. Nonetheless, the differences between SES groups seem to depend on the domain of movement behavior.

Understanding the effect of retirement on health behaviors in China: Causality, heterogeneity and time-varying effect

Retirement is an important turning point during the course of life, but few studies have examined the effects of retirement on a broad range of health behaviors in China. We use the longitudinal data of the China Health and Nutrition Survey (CHNS) from 2004 to 2015 to conduct empirical analysis. Fuzzy discontinuity regression was used to assess the association between retirement and health behaviors in the entire sample and subgroups based on gender and education. A time-varying effect model was used to measure the anticipatory effect, immediate effect and lag effect of retirement. We observed that the transition to retirement was associated with healthier lifestyle habits, such as reduced smoking and alcohol consumption and increased exercise motivation. However, the transition was associated with worse sedentary behavior. No significant statistical association was found between retirement and sleep duration. Men and those with higher education levels are more likely to experience the impact of retirement. The anticipatory effect suggests that as the statutory pension age is predictable, workers adjust their behaviors 4 and 5 years before retirement. The lagged effect indicates that it takes time to develop new habits; thus, retirees change their behaviors 2-3 years after retirement. The paper discusses possible reasons for our findings and proposes several policy implications from the perspectives of the government and society to facilitate the realization of healthy aging.

Association with Temperature Variability and Physical Activity, Sedentary Behavior, and Sleep in a Free-Living Population

The present study examines the temperature variability in physical activity (PA), sedentary behavior (SB), and sleep in a free-living population. A representative sample of 1235 adults (ages 21–70) from Iowa, U.S.A., wore a SenseWear Mini Armband (SWA) for a randomly assigned day. Koppen’s weather climate classification was used to precisely classify the temperature: cold (−13 to 32 °F), cool (32 to 50 °F), mild (50 to 64 °F), warm (64 to 73 °F), and hot (73 to 95 °F). The main effect of three-way ANOVA (age × gender × temperature) had differences for SB and sleep, with older adults having higher levels than younger adults (p < 0.05). However, moderate to vigorous PA (MVPA) did not vary systematically by age or gender, and contrary to expectations, the main effect of the weather was not significant for MVPA (p > 0.05). Participants spent more time participating in PA at cold than at hot temperatures. The results clarify the impact of temperature on shaping PA and SB patterns in adults. The variable impacts and differential patterns by age suggest that weather should be considered when interpreting differences in PA patterns in research or surveillance applications.

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 &gt;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.

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.

Association between socioeconomic status and physical inactivity in a general Japanese population: NIPPON DATA2010

BACKGROUND

Lower socioeconomic status (SES) may be related to inactivity lifestyle; however, the association between SES and physical inactivity has not been sufficiently investigated in Japan.

METHODS

The study population is the participants of NIPPON DATA2010, which is a prospective cohort study of the National Health and Nutrition Survey 2010 in Japan. They were residents in 300 randomly selected areas across Japan. This study included 2,609 adults. Physical activity was assessed by physical activity index (PAI) calculated from activity intensity and time. The lowest tertile of PAI for each 10-year age class and sex was defined as physical inactivity. Multivariable logistic regression analyses were conducted to examine the association of SES (employment status, educational attainment, living status, and equivalent household expenditure (EHE)) with physical inactivity.

RESULTS

In the distribution of PAI by age classes and sex, the highest median PAI was aged 30-39 years among men (median 38.6), aged 40-49 years among women (38.0), and median PAI was decreased with increasing age. Multivariable-adjusted model shows that not working was significantly associated with physical inactivity after adjustment for age in all age groups and sexes. Not living with spouse for adult women and elderly men was significantly associated with physical inactivity compared to those who living with spouse. However, neither educational attainment nor EHE had any significant associations with physical inactivity.

CONCLUSIONS

The result indicated that physical inactivity was associated with SES in a general Japanese population. SES of individuals need to be considered in order to prevent inactivity lifestyle.

Assessment of Physical Activity in Adults using Wrist Accelerometers

The health benefits of physical activity have been widely recognized, yet traditional measures of physical activity including questionnaires and category-based assessments of volume and intensity provide only broad estimates of daily activities. Accelerometers have advanced epidemiologic research on physical activity by providing objective and continuous measurement of physical activity in free-living conditions. Wrist-worn accelerometers have become especially popular due to low participant burden. However, the validity and reliability of wrist-worn devices for adults have yet to be summarized. Moreover, accelerometer data provide rich information on how physical activity is accumulated throughout the day, but only a small portion of these rich data have been utilized by researchers. Lastly, new methodological developments that aim to overcome some of the limitations of accelerometers are emerging. The purpose of this review is to provide an overview of accelerometry research, with a special focus on wrist-worn accelerometers. We describe briefly how accelerometers work, summarize the validity and reliability of wrist-worn accelerometers, discuss the benefits of accelerometers including measuring light-intensity physical activity, and discuss pattern metrics of daily physical activity recently introduced in the literature. A summary of large-scale cohort studies and randomized trials that implemented wrist-worn accelerometry is provided. We conclude the review by discussing new developments and future directions of research using accelerometers, with a focus on wrist-worn accelerometers.

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 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

Changes in prolonged sedentary behaviour across the transition to retirement

BACKGROUND

Prolonged sedentary behaviour is associated with a higher risk of cardiometabolic diseases. This longitudinal study examined changes in daily total, prolonged (≥30 min) and highly prolonged (≥60 min) sedentary time across the transition to retirement by gender and occupational status.

METHODS

We included 689 aging workers (mean (SD) age before retirement 63.2 (1.6) years, 85% women) from the Finnish Retirement and Aging Study (FIREA). Sedentary time was measured annually using a wrist-worn triaxial ActiGraph accelerometer before and after retirement with on average 3.4 (range 2-4) measurement points.

RESULTS

Women increased daily total sedentary time by 22 min (95% CI 13 to 31), prolonged sedentary time by 34 min (95% CI 27 to 42) and highly prolonged sedentary time by 15 min (95% CI 11 to 20) in the transition to retirement, and remained at the higher level of sedentary time years after retirement. The highest increase in total and prolonged sedentary time was observed among women retiring from manual occupations. Men had more total and prolonged sedentary time compared with women before and after retirement. Although no changes in men's sedentary time were observed during the retirement transition, there was a gradual increase of 33 min (95% CI 6 to 60) in prolonged sedentary time from pre-retirement years to post-retirement years.

CONCLUSION

The transition to retirement was accompanied by an abrupt increase in prolonged sedentary time in women but a more gradual increase in men. The retirement transition may be a suitable time period for interventions aiming to decrease sedentary behaviour.