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 (SD) age, 63.5 (1.1) yr) 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 (1 yr in-between). Cardiometabolic biomarkers, including LDL-cholesterol, HDL-cholesterol, total/HDL-cholesterol ratio, triglycerides, C-reactive protein, 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 -1 . 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 -1 decrease in triglycerides. Findings related to LDL-cholesterol, C-reactive protein, 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.

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.

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.

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.