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

Pasanen, Sanna; Halonen, Jaana I.; Pulakka, Anna; Kestens, Yan; Thierry, Benoît; Brondeel, Ruben; Pentti, Jaana; Vahtera, Jussi; Leskinen, Tuija; Stenholm, Sari

doi:10.1136/bmjopen-2020-042600

Cited by 7 publications

(6 citation statements)

References 34 publications

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“…One explanation may be removal of active commuting that is a relatively common activity in our study population, as approximately 20% of women and 14% of men reported commuting by walking or cycling [7]. Our previous work has shown that actively conducted trips, such as commuting on workdays contribute markedly to daily MVPA in this age group [36]. In general, aging seems to be related to decreasing intensity of physical activity [37], but it is unlikely the explanation for our findings, given that the follow-up time was only one year and the study population was relatively active and healthy.…”

Section: Discussionmentioning

confidence: 82%

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

Suorsa

Leskinen

Pasanen

et al. 2022

Int J Behav Nutr Phys Act

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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.

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Section: Discussionmentioning

confidence: 82%

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

Suorsa

Leskinen

Pasanen

et al. 2022

Int J Behav Nutr Phys Act

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“…This may also be a more feasible goal than aiming to increase MVPA levels, because the pre-retirement MVPA levels may be relatively high (in this study ≈ 80 min/day). Moreover, a large proportion of pre-retirement daily physical activity comes from worktime physical activity and active commuting 26,51 which may be di cult to compensate after retirement. We observed some bene ts of replacing SED with LPA, but compared to that of MVPA a threefold increase in LPA was needed to gain approximately same amount of reduction in obesity indicators.…”

Section: Discussionmentioning

confidence: 99%

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

Suorsa

Gupta²,

Leskinen

et al. 2023

Preprint

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Background Retirement is associated with 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 obesity indicators 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 with a 1-year lag, 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 was measured twice. Compositional linear regression analysis and isotemporal substitution analysis were used to study associations between changes in 24-h movement behaviors and changes in obesity indicators. 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 minutes 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 In the transition from work to retirement, increase in MVPA and sleep in relation the remaining behaviors were associated with improvement and worsening, respectively, in obesity indicators. Common life-transitions, like retirement, should be taken into account, when giving recommendations and guidance for physically active life style and sleep.

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“…The length of monitoring (ie, 1 week or several weeks) and days included in the monitoring (ie, weekday, workday, day off, and weekend) should be harmonized as they influence physical activity performance [ 20 , 80 , 81 ]. If reliable results can often be found with 1 week of monitoring, longer monitoring can help health professionals capture days of the week in which the participant is always inactive to further adapt the intervention program [ 80 ].…”

Section: Discussionmentioning

confidence: 99%

Wearables for Measuring the Physical Activity and Sedentary Behavior of Patients With Axial Spondyloarthritis: Systematic Review

Soulard¹,

Carlin²,

Knitza³

et al. 2022

JMIR Mhealth Uhealth

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Background Axial spondyloarthritis (axSpA) is an inflammatory rheumatic disease associated with chronic back pain and restricted mobility and physical function. Increasing physical activity is a viable strategy for improving the health and quality of life of patients with axSpA. Thus, quantifying physical activity and sedentary behavior in this population is relevant to clinical outcomes and disease management. However, to the best of our knowledge, no systematic review to date has identified and synthesized the available evidence on the use of wearable devices to objectively measure the physical activity or sedentary behavior of patients with axSpA. Objective This study aimed to review the literature on the use of wearable activity trackers as outcome measures for physical activity and sedentary behavior in patients with axSpA. Methods PubMed, PEDro, and Cochrane electronic databases were searched in July 2021 for relevant original articles, with no limits on publication dates. Studies were included if they were original articles, targeted adults with a diagnosis of axSpA, and reported wearable device–measured physical activity or sedentary behavior among patients with axSpA. Data regarding the study’s characteristics, the sample description, the methods used for measuring physical activity and sedentary behavior (eg, wearable devices, assessment methods, and outcomes), and the main results of the physical activity and sedentary behavior assessments were extracted. Results A total of 31 studies were initially identified; 13 (13/31, 42%) met the inclusion criteria, including 819 patients with axSpA. All the studies used accelerometer-based wearable devices to assess physical activity. Of the 13 studies, 4 (4/31, 31%) studies also reported outcomes related to sedentary behavior. Wearable devices were secured on the wrists (3/13 studies, 23%), lower back (3/13, 23%), right hip (3/13, 23%), waist (2/13, 15%), anterior thigh (1/13, 8%), or right arm (1/13, 8%). The methods for reporting physical activity and sedentary behavior were heterogeneous. Approximately 77% (10/13) of studies had a monitoring period of 1 week, including weekend days. Conclusions To date, few studies have used wearable devices to quantify the physical activity and sedentary behavior of patients with axSpA. The methodologies and results were heterogeneous, and none of these studies assessed the psychometric properties of these wearables in this specific population. Further investigation in this direction is needed before using wearable device–measured physical activity and sedentary behavior as outcome measures in intervention studies in patients with axSpA. Trial Registration PROSPERO CRD42020182398; https://tinyurl.com/ec22jzkt International Registered Report Identifier (IRRID) RR2-10.2196/23359

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

Cited by 7 publications

References 34 publications

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

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

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

Wearables for Measuring the Physical Activity and Sedentary Behavior of Patients With Axial Spondyloarthritis: Systematic Review

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