Changes in physical activity during transition to retirement: a cohort study

Stenholm, Sari; Pulakka, Anna; Kawachi, Ichiro; Oksanen, Tuula; Halonen, Jaana I.; Aalto, Ville; Kivimäki, Mika; Vahtera, Jussi

doi:10.1186/s12966-016-0375-9

Cited by 83 publications

(111 citation statements)

References 25 publications

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“…This study showed that in early old age, an important time of transition between work and retirement when behavior change may be possible,57 higher PAEE and greater time spent in LPA and MVPA and less sedentary time were related to more favorable CVD biomarker profiles. The associations found were stronger in women than men and remained after adjustment for covariates.…”

Section: Discussionmentioning

confidence: 62%

Physical Activity, Sedentary Time, and Cardiovascular Disease Biomarkers at Age 60 to 64 Years

Elhakeem

Cooper

Whincup

et al. 2018

JAHA

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BackgroundWe examined associations of objectively measured physical activity (PA) and sedentary time with cardiovascular disease biomarkers at age 60 to 64 years. This included investigation of sex differences and the extent to which associations may be mediated by adiposity.Methods and ResultsParticipants were 795 men and 827 women aged 60 to 64 years from the Medical Research Council National Survey of Health and Development. Combined heart rate and movement sensors worn for 5 consecutive days were used to derive overall PA energy expenditure, kJ/kg per day) and time spent sedentary (<1.5 metabolic equivalent of tasks), in light PA (1.5–3 metabolic equivalent of tasks) and moderate‐to‐vigorous intensity PA (>3 metabolic equivalent of tasks). Linear regression models were used to relate each PA parameter to inflammatory (C‐reactive protein, interleukin‐6), endothelial (tissue‐plasminogen activator, E‐selectin) and adipokine (leptin, adiponectin) markers extracted from fasting blood samples. Greater time in light PA and moderate‐to‐vigorous intensity PA and less sedentary time were associated with more favorable biomarker levels. For C‐reactive protein, interleukin‐6, and leptin, these differences were greater among women than men. For example, % differences (95% confidence intervals) in leptin for men and women per SD increases in sedentary time: 7.9 (2.7, 13.0) and 20.6 (15.3, 25.8); moderate‐to‐vigorous intensity PA: −3.8 (−8.9, 12.7) and −17.7 (−23.1, −12.4), moderate‐to‐vigorous intensity PA: −12.9 (−17.9, −8.0) and −18.3 (−23.4, −13.1). Fat mass mediated a greater proportion of these associations in women than men.ConclusionsGreater light PA and moderate‐to‐vigorous intensity PA and less sedentary time in early old age were associated with more favorable cardiovascular biomarker profiles. Fat mass partially mediated these associations but more strongly in women than men, which explained sex differences.

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Section: Discussionmentioning

confidence: 62%

Physical Activity, Sedentary Time, and Cardiovascular Disease Biomarkers at Age 60 to 64 Years

Elhakeem

Cooper

Whincup

et al. 2018

JAHA

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“…These were therefore treated as covariates. We obtained information from the employers' registers regarding participants' sex, age at retirement and occupational status categorized according to the Classification of Occupations by Statistics Finland 22, as in previous studies 23, 24, into three groups: ‘high’, including physicians and teachers; ‘intermediate’, including registered nurses and technicians; and ‘low’, including maintenance workers and cleaners. Level of education (high = university degree; intermediate = high school or vocational school; low = basic education) was obtained from Statistics Finland 25, while marital status (married/cohabiting; single; divorced/widowed), smoking (current smoker versus not), depression (‘Have you ever been diagnosed with depression?’ yes versus no) and self‐reported health (poor versus good) were elicited by the questionnaires.…”

Section: Methodsmentioning

confidence: 99%

Trajectories of risky drinking around the time of statutory retirement: a longitudinal latent class analysis

et al. 2017

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Background and AimsLife transitions such as retirement may influence alcohol consumption, but only a few studies have described this using longitudinal data. We identified patterns and predictors of risky drinking around the time of retirement.DesignA cohort study assessing trajectories and predictors of risky drinking among employees entering statutory retirement between 2000 and 2011.Setting and ParticipantsA total of 5805 men and women from the Finnish Public Sector study who responded to questions on alcohol consumption one to three times prior to (w−3, w−2, w−1), and one to three times after (w+1, w+2, w+3) retirement.MeasurementsWe assessed trajectories of risky drinking (> 24 units per week among men, > 16 units among women, or an extreme drinking occasion during past year) from pre‐ to post‐retirement, as well as predictors of each alcohol consumption trajectory.FindingsThree trajectories were identified: sustained healthy drinking (81% of participants), temporary increase in risky drinking around retirement (12%) and slowly declining risky drinking after retirement (7%). The strongest pre‐retirement predictors for belonging to the group of temporary increase in risky drinking were current smoking [odds ratio (OR) = 3.90, 95% confidence interval (CI) = 2.70–5.64], male sex (OR = 2.77, 95% CI = 2.16–3.55), depression (OR = 1.44, 95% CI = 1.05–1.99) and work‐place in the metropolitan area (OR = 1.29, 95% CI = 1.00–1.66). Compared with the slowly declining risky drinking group, the temporary increase in risky drinking group was characterized by lower occupational status and education, and work‐place outside the metropolitan area.ConclusionsIn Finland, approximately 12% of people who reach retirement age experience a temporary increase in alcohol consumption to risky levels, while approximately 7% experience a slow decline in risky levels of alcohol consumption. Male gender, smoking, being depressed and working in a metropolitan area are associated with increased likelihood of increased alcohol consumption.

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“…11,12 The time spent on activity at each intensity level in hours per week was multiplied by the average energy expenditure of each activity, expressed in metabolic equivalent (MET). Physical activity was categorized into four groups:…”

Section: Assessment Of Covariatesmentioning

confidence: 99%

Changes in Sleep Duration During Transition to Statutory Retirement: A Longitudinal Cohort Study

Myllyntausta

Salo

Kronholm

et al. 2017

Sleep

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Study Objectives: This study examined whether sleep duration changes during the transition from full-time work to statutory retirement and, if this were the case, which pre-retirement factors, including sociodemographic, work, lifestyle and health factors, predict these changes. [CI] 6 h 54 min to 7 h 6 min) to 7 hours and 22 minutes (95% CI 7 h 16 min to 7 h 27 min); thus, mean increase being 22 minutes. Increase in sleep duration was greatest in those who were short sleepers, heavy drinkers or had sleep difficulties. After the retirement transition, sleep duration remained at approximately the same level, as no significant changes were observed. Methods Conclusions:This longitudinal study suggests that transition from full-time work to statutory retirement is associated with an increase in sleep duration.

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Changes in physical activity during transition to retirement: a cohort study

Cited by 83 publications

References 25 publications

Physical Activity, Sedentary Time, and Cardiovascular Disease Biomarkers at Age 60 to 64 Years

Physical Activity, Sedentary Time, and Cardiovascular Disease Biomarkers at Age 60 to 64 Years

Trajectories of risky drinking around the time of statutory retirement: a longitudinal latent class analysis

Changes in Sleep Duration During Transition to Statutory Retirement: A Longitudinal Cohort Study

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