How does cessation of work affect sleep? Prospective analyses of sleep duration, timing and efficiency from the Swedish Retirement 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.

Are changes in sleep problems associated with changes in life satisfaction during the retirement transition?

Retirement reduces sleep problems, but changes in life satisfaction during the retirement transition are multifactorial and partly unknown. The aim of this prospective cohort study was to examine whether changes in sleep problems are associated with changes in total and domain-specific life satisfaction during the retirement transition (on average 0.5 years before and 0.5 years after retirement). The study population consisted of Finnish public sector employees (n = 3518) from the Finnish Retirement and Aging (FIREA) study who responded to annual surveys before and after transition to statutory retirement. Sleep problems were measured with Jenkins Sleep Problem Scale questionnaire and participants were grouped into four sleep problem groups depending on the state of their sleep problems during the retirement transition: 'Never,' 'Decreasing,' 'Increasing,' and 'Constant' sleep problems. Life satisfaction was measured with the Life Satisfaction Scale questionnaire including four domains (interestingness, happiness, easiness, togetherness). We found that the improvement in total life satisfaction was greatest for participants in the 'Decreasing' (0.17, 95% CI 0.11-0.23, SMD 0.27) and 'Constant' (0.12, 95% CI 0.07-0.18, SMD 0.19) sleep problem groups. Of the specific life satisfaction domains, similar findings were observed only for the easiness domain. It seems that decreasing or constant sleep problems are associated with improved life satisfaction during the retirement transition, especially in the feeling of easiness of life. This may be due to the fact that as the demands of working life are removed, sleep problems are alleviated or it becomes easier to live with them, which improves life satisfaction.

Accelerometry Measured Movement Behaviors in Middle-Aged and Older Adults: Cross-Sectional Analysis of the ELSA-Brasil Study

BACKGROUND

Little investigation of accelerometry assessed movement behaviors and physical inactivity was carried out in middle-aged and older adults in low-middle-income countries.

OBJECTIVE

Describe accelerometry-measured movement behaviors and prevalence of physical inactivity in middle-aged and older adults.

METHODS

We collected raw accelerometry data during the third visit (2017-2019) of ELSA-Brasil, a large-scale multicenter Brazilian cohort. Participants wore an ActiGraph wGT3X-BT on the waist for 24 hours for 7 days and documented sleep in a diary.

RESULTS

Nine thousand two hundred and seventy-nine participants had valid data (73.4% of the eligible cohort). Overall activity was higher for men (11.82mg; 95% confidence interval [CI], 11.7 to 11.93) than women (10.69mg; 95% CI, 10.6 to 10.77) and lower in older groups-women (-0.12mg/y; 95% CI, -0.13 to -0.11), men (-0.16mg/y; 95% CI, -0.17 to -0.14). Participants were more active from noon to midnight. Distribution of movement behaviors varied with sex and age, and sleep duration was longer in older individuals. Overall, 14.4% (95% CI, 13.7 to 15.1) were inactive, with inactivity being more frequent in women (16.4%; 95% CI, 15.4 to 17.4) than men (12.2%; 95% CI, 11 to 13). Higher rates were observed in the oldest. Retirement was associated with a higher prevalence of physical inactivity in both sexes.

CONCLUSION

Women were less active than men. Older individuals showed a high prevalence of physical inactivity, probably related to transition into retirement. These findings strengthen evidence for public policies promoting physical activity by emphasizing the need to target women, older individuals, and those transitioning to retirement to improve and/or maintain physical activity levels throughout the course of their lives.

Disturbed sleep and its attribution to stress and other causes: A population-based survey

This study explores the prevalence of attributed causes of disturbed sleep and the association between stress-disturbed sleep and age, sex, and sleep duration on weekdays as well as weekends in a representative sample. A nationally representative sample (n = 1,128, response rate 72.8%), stratified for sex and age, completed a computer-assisted phone survey that included questions about sleep disturbances and attributed causes. Stress was the main attributed cause of sleep disturbance (35.1%), most frequently attributed by younger women (χ²  = 26.5, p < 0.001). Prevalence of stress-disturbed sleep was higher with lower age (B = -0.05, odds ratio (OR) = 0.94, CI = 0.91, 0.98). There was a trend, however, toward a significant interaction between age and sex, with women in the older age-groups more frequently reporting stress-disturbed sleep than older men (B = -0.02, OR = 1.022, CI = 1.003, 1.042). Weekday sleep duration decreased with increased stress-disturbed sleep, with an inverse relationship on weekends except for those reporting stress-disturbed sleep more than 5 days per week (F = 10.5, p < 0.001), who also had the shortest weekend sleep duration. Sleep disturbances were commonly attributed to stress, and more strongly so in women younger than 46 years. Stress-disturbed sleep during weekdays seems to be potentially compensated for with extended sleep on weekends, except for those with continuous stress-disturbed sleep.

Physiological State Evaluation in Working Environment Using Expert System and Random Forest Machine Learning Algorithm

Healthy lifestyle is one of the most important factors in the prevention of premature deaths, chronic diseases, productivity loss, obesity, and other economic and social aspects. The workplace plays an important role in promoting the physical activity and wellbeing of employees. Previous studies are mostly focused on individual interviews, various questionnaires that are a conceptual information about individual health state and might change according to question formulation, specialist competence, and other aspects. In this paper the work ability was mostly related to the employee's physiological state, which consists of three separate systems: cardiovascular, muscular, and neural. Each state consists of several exercises or tests that need to be performed one after another. The proposed data transformation uses fuzzy logic and different membership functions with three or five thresholds, according to the analyzed physiological feature. The transformed datasets are then classified into three stages that correspond to good, moderate, and poor health condition using machine learning techniques. A three-part Random Forest method was applied, where each part corresponds to a separate system. The obtained testing accuracies were 93%, 87%, and 73% for cardiovascular, muscular, and neural human body systems, respectively. The results indicate that the proposed work ability evaluation process may become a good tool for the prevention of possible accidents at work, chronic fatigue, or other health problems.

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.

A systematic review of evidence on employment transitions and weight change by gender in ageing populations

Background

Becoming unemployed is associated with poorer health, including weight gain. Middle- and older-age adults are a growing segment of workforces globally, but they are also more vulnerable to changes to employment status, especially during economic shocks. Expected workforce exits over the next decade may exacerbate both the obesity epidemic and the economic burden of obesity. This review extends current knowledge on economic correlates of health to assess whether employment transitions impact body weight by sex/gender among middle-aged and older adults.

Methods

Eight bibliometric databases were searched between June and July 2021, supplemented by hand-searches, with no restriction on publication date or country. Longitudinal studies, or reviews, were eligible when examining body weight as a function of employment status change in adults ≥50 years. Data extraction and quality appraisal used predefined criteria; reported findings were analysed by narrative synthesis.

Results

We screened 6,001 unique abstracts and identified 12 articles that met inclusion criteria. All studies examined retirement; of which two also examined job-loss. Overall, studies showed that retirement led to weight gain or no difference in weight change compared to non-retirees; however, reported effects were not consistent for either women or men across studies or for both women and men within a study. Reported effects also differed by occupation: weight gain was more commonly observed among retirees from physical occupations but not among retirees from sedentary occupations. Few studies assessed the role of health behaviours; sleep was the least studied. Most studies were medium quality.

Conclusions

Existing studies do not provide a clear enough picture of how employment transitions affect body weight. Firm conclusions on the impact of employment transitions on weight cannot be made without further high-quality evidence that considers the role of gender, job-type, other health behaviours, and other transitions, like job-loss.

Weekend sleep after early and later school start times confirmed a model-predicted failure to catch up sleep missed on weekdays

Background

Many people believe they sleep for longer time on weekend nights to make up for sleep lost on weekdays. However, results of simulations of risetimes and bedtimes on weekdays and weekends with a sleep–wake regulating model revealed their inability to prolong weekend sleep. In particular, they predicted identical durations of weekend sleep after weeks with relatively earlier and relatively later risetime on weekdays. In the present study, this paradoxical prediction was empirically confirmed.

Methods

Times in bed were calculated from weekday and weekend risetimes and bedtimes in pairs of samples of students with early and later school start time and in subsets of samples from 7 age groups with weekday risetime earlier and later than 7:00 a.m.

Results

Among 35 pairs of students, mean age ± standard deviation was 14.5 ± 2.9 years and among the age group samples, 21.6 ± 14.6 years. As predicted by the simulations, times in bed on weekends were practically identical in the samples with early and later school start time and in two subsets with earlier and later weekday risetime.

Conclusions

The model-based simulations of sleep times can inform an individual about an amount of irrecoverable loss of sleep caused by an advance shift of wakeups on weekdays.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11325-022-02648-5.

Sleep during "lockdown" highlighted the need to rethink the concept of weekend catch-up sleep

Purpose

Many people believe in their ability to sleep for longer time on weekends to make up for sleep lost due to early wakeups on weekdays. This widely held belief was not supported by the simulations of rise- and bedtimes on weekdays and weekends with a sleep–wake regulating model. The simulations suggested the inability to extend sleep on any of two weekend nights and they predicted identical weekend sleep durations for weeks with relatively earlier and relatively later weekday risetimes. By April 2020, about half of the world’s population was under some form of “lockdown” due to the COVID-19 pandemic. This “lockdown” provided a new opportunity to demonstrate the predictive power of the sleep–wake regulating models. Therefore, the purpose of this report was to support the prediction of identity of weekend sleep durations after weeks with earlier and later weekday wakeups.

Methods

Weekend and weekday rise- and bedtimes before and during “lockdown” for 31 samples were taken from recent journal publications. Time in bed on weekends and 12 other measures of sleep duration and timing were calculated and simulated.

Results

For only one of 13 measures, weekend time in bed, statistical analysis did not yield a statistically significant difference between the estimates obtained before and during “lockdown”. The model-based simulations pointed to the 0.3-h delay of the sleep–wake cycle in response to the 1-h delay of weekday risetime during “lockdown”.

Conclusion

The model-based prediction was confirmed, thus, highlighting again the necessity to rethink the concept of weekend catch-up sleep.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11325-021-02492-z.

Association of job strain with accelerometer-based sleep duration and timing of sleep among older employees

Job strain has been associated with poor sleep quality and could lead to changes in duration and timing of sleep as well. This study examined the association of job strain with sleep duration, bedtimes and awakening times among public sector employees close to their retirement age. Differences in these sleep parameters between workdays and free days across job strain groups were examined. Duration and timing of sleep were measured repeatedly with accelerometers among 466 public sector employees in Finland (mean age 63 years, 86% women), who contributed to 759 measurements in total. Job demands (low/high) and control (low/high) measured by self-reports and job exposure matrix were used to identify low strain (low demand, high control), passive (low, low), active (high, high) and high strain (high, low) jobs. No differences in sleep duration were observed on workdays, whereas on free days those in the high strain group had longer sleep duration than those in the low strain and passive job groups. The high strain group also extended their sleep from workdays to free days more, the extension being on average 59 min (95% CI 42 min-75 min) when adjusted for several sociodemographic, work and health factors. This extension of sleep duration resulted mostly from a greater delay of awakening times from workdays to free days. Psychosocial work factors, such as job strain, need to be considered when promoting sufficient sleep duration among older employees, as those with job strain may have a greater need for recovery and sleep.

How consistently does sleep quality improve at retirement? Prospective analyses with group-based trajectory models

Growing evidence indicates that retiring from paid work is associated, at least in the short-term, with dramatic reductions in sleep difficulties and more restorative sleep. However, much is still not known, in particular how universal these improvements are, how long they last, and whether they relate to the work environment. A methodological challenge concerns how to model time when studying abrupt changes such as retirement. Using data from Swedish Longitudinal Occupational Survey of Health (n = 2,148), we studied difficulties falling asleep, difficulties maintaining sleep, premature awakening, restless sleep, a composite scale of these items, and non-restorative sleep. We compared polynomial and B-spline functions to model time in group-based trajectory modelling. We estimated variations in the individual development of sleep difficulties around retirement, relating these to the pre-retirement work environment. Reductions in sleep difficulties at retirement were sudden for all outcomes and were sustained for up to 11 years for non-restorative sleep, premature awakening, and restless sleep. Average patterns masked distinct patterns of change: groups of retirees experiencing greatest pre-retirement sleep difficulties benefitted most from retiring. Higher job demands, lower work time control, lower job control, and working full-time were work factors that accounted membership in these groups. Compared to polynomials, B-spline models more appropriately estimated time around retirement, providing trajectories that were closer to the observed shapes. The study highlights the need to exercise care in modelling time over a sudden transition because using polynomials can generate artefactual uplifts or omit abrupt changes entirely, findings that would have fallacious implications.