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Effects of physical activity intervention on 24-h movement behaviors: a compositional data analysis.

ABSTRACT: 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.

SUBMITTER: Pasanen J

PROVIDER: S-EPMC9130120 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature

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Effects of physical activity intervention on 24-h movement behaviors: a compositional data analysis.

Pasanen Jesse J Leskinen Tuija T Suorsa Kristin K Pulakka Anna A Virta Joni J Auranen Kari K Stenholm Sari S

Scientific reports 20220524 1

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 behavior ...[more]

PMID: 35610297

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Project description:ObjectiveThis study investigates the relationship between movement behaviors and physical fitness (PF) in university students, and based on the top 5% of model-predicted outcomes for PF to determine the optimal movement behaviors balance.MethodsA total of 463 university students aged 15-24 years from Jinhua City wore accelerometers to measure moderate-to-vigorous physical activity (MVPA), light-intensity physical activity (LPA), and sedentary behavior (SB). Sleep (SLP) was self-reported. The body mass index (BMI), forced vital capacity (FVC), 50-meter dash, standing long jump, sit-and-reach, sit-ups (female), pull-ups (male), 800-meter run (female), and 1000-meter run (male) were used as indicators to assess the physical fitness of university students. Regression analysis was used to examine the relationship between movement behaviors and PF. All possible movement component combinations were investigated to determine the best correlation (top 5%) with each outcome.ResultsFor males, SB (β = 5.05, p < 0.05) was significantly correlated with an increase in BMI. MVPA was significantly correlated with improvements in BMI (β = -1.75, p < 0.05), FVC (β = 494.21, p < 0.05), and endurance qualities (β = -25.77, p < 0.05). For females, MVPA was significantly correlated with improvements in BMI (β = -1.03, p < 0.05), FVC (β = 176.05, p < 0.05), speed capability (β = -0.26, p < 0.05), and endurance qualities (β = -16.38, p < 0.05). LPA was associated with improvements in endurance qualities (β = -24.10, p < 0.05). SB was significantly correlated with a decline in endurance qualities (β = 24.25, p < 0.05). The average (range) optimal combination of time use was as follows: For males, MVPA = 142 min/day, SB = 534 min/day, LPA = 295 min/day, and SLP = 469 min/day. For females, MVPA = 115 min/day, SB = 536 min/day, LPA = 306 min/day, and SLP = 482 min/day.ConclusionFor both males and females, increased MVPA and reduced sedentary time were associated with improved endurance and strength, while optimal sleep duration contributed to overall fitness. These findings highlight the importance of a balanced daily movement schedule for university students.

Project description:BackgroundFavorable movement behavior patterns, comprising more physical activity, less sedentary behavior, and sufficient sleep, may promote the maintenance of good quality of life (QoL) with advancing age. The aim of the present study was to investigate whether movement behaviors predict future changes in QoL among community-dwelling older adults over a four-year follow-up.MethodsParticipants were 75-, 80- and 85-year-old community-dwelling older adults (n = 203) followed up for 4 years. Participants wore thigh- and trunk-mounted accelerometers for 3-7 days at baseline. Proportion of time-use in physical activity, standing and sedentary behavior were assessed based on body posture and movement intensity. Time in bed was determined using an automated algorithm. QoL was assessed during a home interview using the short Older People's Quality of Life Questionnaire at baseline and follow-up (range 13-65, higher scores indicate higher QoL). Compositional linear regression analysis was used to study whether baseline time-use composition predicts changes in QoL.ResultsOver the 4-year follow-up, QoL scores decreased by 5% on average. Higher physical activity in relation to the other movement behaviors was associated with increase in QoL over time (βilr 0.94, p = 0.013), but this association attenuated after adding baseline physical function into the model. Sedentary behavior, standing, and time in bed were not associated with changes in QoL. Theoretical reallocation of 30 min of physical activity into sedentary behavior, standing or time in bed was estimated to decrease QoL by 0.5 (CI 95% -0.6 to -0.4), 0.6 (-0.7 to -0.5) and 0.4 (-0.5 to -0.3) points, respectively.ConclusionsTheoretical reallocation of physical activity into sedentary behavior, standing, and time in bed was found to be associated with prospective decline in QoL among older adults. Engaging more in physical activity and less in more passive activities may promote better QoL with advancing age.

Project description:BackgroundBlood pressure (BP)-lowering effects of structured exercise are well-established. Effects of 24-hour movement behaviors captured in free-living settings have received less attention. This cross-sectional study investigated associations between a 24-hour behavior composition comprising 6 parts (sleeping, sedentary behavior, standing, slow walking, fast walking, and combined exercise-like activity [eg, running and cycling]) and systolic BP (SBP) and diastolic BP (DBP).MethodsData from thigh-worn accelerometers and BP measurements were collected from 6 cohorts in the Prospective Physical Activity, Sitting and Sleep consortium (ProPASS) (n=14 761; mean±SD, 54.2±9.6 years). Individual participant analysis using compositional data analysis was conducted with adjustments for relevant harmonized covariates. Based on the average sample composition, reallocation plots examined estimated BP reductions through behavioral replacement; the theoretical benefits of optimal (ie, clinically meaningful improvement in SBP [2 mm Hg] or DBP [1 mm Hg]) and minimal (ie, 5-minute reallocation) behavioral replacements were identified.ResultsThe average 24-hour composition consisted of sleeping (7.13±1.19 hours), sedentary behavior (10.7±1.9 hours), standing (3.2±1.1 hours), slow walking (1.6±0.6 hours), fast walking (1.1±0.5 hours), and exercise-like activity (16.0±16.3 minutes). More time spent exercising or sleeping, relative to other behaviors, was associated with lower BP. An additional 5 minutes of exercise-like activity was associated with estimated reductions of -0.68 mm Hg (95% CI, -0.15, -1.21) SBP and -0.54 mm Hg (95% CI, -0.19, 0.89) DBP. Clinically meaningful improvements in SBP and DBP were estimated after 20 to 27 minutes and 10 to 15 minutes of reallocation of time in other behaviors into additional exercise. Although more time spent being sedentary was adversely associated with SBP and DBP, there was minimal impact of standing or walking.ConclusionsStudy findings reiterate the importance of exercise for BP control, suggesting that small additional amounts of exercise are associated with lower BP in a free-living setting.

Project description:IntroductionThe relationship between 24-h movement behaviours (i.e. sleep, sedentary behaviour and physical activity) and adiposity in preschoolers remains unclear. Therefore, this study aims to investigate the associations between 24-h movement behaviours and adiposity in preschoolers making use of compositional data analysis (CoDA).MethodsAustralian preschoolers (3-5 years) from the Early Start Baseline Study wore an ActiGraph accelerometer to assess sedentary behaviour (SB), light physical activity (LPA) and moderate-to-vigorous physical activity (MVPA). Their weight and height were measured using standardized protocols and converted to Body Mass Index (BMI) z-scores using the World Health Organisation growth references. Their parents completed a questionnaire to assess their level of education and the child's sleep duration, age and sex. CoDA was employed to investigate the association between 24-h movement behaviours and adiposity in R.ResultsThis study included 169 preschoolers and their overall 24-h movement behaviour composition was associated with BMI z-scores (F = 5.02, p = 0.002). When examining the association between each movement behaviour relative to the others and BMI z-scores, we observed a statistically significant favourable association for sleep (p = 0.025) and unfavourable association for MVPA (p = 0.010), but not for the other behaviours. As such, reallocating 10 min from sleep or from MVPA, proportionally to all other behaviours was associated with a difference of + 0.031 (95%CI = 0.004,0.06) and -0.085 (95%CI = -0.15,-0.02) in BMI z-score, respectively.ConclusionDespite the association between more time spent in MVPA and higher BMI z-scores, promoting a balanced amount of time in each 24-h movement behaviour-more MVPA, less sedentary time, and sufficient sleep-remains important for overall health. Future studies should address methodological challenges (e.g. recruitment bias that may exist in the parents/children willing to participate versus the general population, recall bias in parent reported sleep duration, or other confounding variables such as diet), use larger and more diverse samples, and consider longitudinal designs. Additionally, focusing on other adiposity indicators, such as waist-to-height ratio or fat percentage, could enhance understanding of these relationships.

Project description:BackgroundCompositional data analysis (CoDA) techniques are well suited for examining associations between 24-h movement behaviors (i.e., sleep, sedentary behavior, physical activity) and indicators of health given they recognize these behaviors are co-dependent, representing relative parts that make up a whole day. Accordingly, CoDA techniques have seen increased adoption in the past decade, however, heterogeneity in research reporting practices may hinder efforts to synthesize and quantify these relationships via meta-analysis. This systematic review described reporting practices in studies that used CoDA techniques to investigate associations between 24-h movement behaviors and indicators of health.MethodsA systematic search of eight databases was conducted, in addition to supplementary searches (e.g., forward/backward citations, expert consultation). Observational studies that used CoDA techniques involving log-ratio transformation of behavioral data to examine associations between time-based estimates of 24-h movement behaviors and indicators of health were included. Reporting practices were extracted and classified into seven areas: (1) methodological justification, (2) behavioral measurement and data handling strategies, (3) composition construction, (4) analytic plan, (5) composition-specific descriptive statistics, (6) model results, and (7) auxiliary information. Study quality and risk of bias were assessed by the National Institutes of Health Quality Assessment Tool for Observational Cohort and Cross-sectional Studies.Results102 studies met our inclusion criteria. Reporting practices varied considerably across areas, with most achieving high standards in methodological justification, but inconsistent reporting across all other domains. Some items were reported in all studies (e.g., how many parts the daily composition was partitioned into), whereas others seldom reported (e.g., definition of a day: midnight-to-midnight versus wake-to-wake). Study quality and risk of bias was fair in most studies (85%).ConclusionsCurrent studies generally demonstrate inconsistent reporting practices. Consistent, clear and detailed reporting practices are evidently needed moving forward as the field of time-use epidemiology aims to accurately capture and analyze movement behavior data in relation to health outcomes, facilitate comparisons across studies, and inform public health interventions and policy decisions. Achieving consensus regarding reporting recommendations is a key next step.Supplementary informationThe online version contains supplementary material available at 10.1186/s44167-024-00062-8.

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Effects of physical activity intervention on 24-h movement behaviors: a compositional data analysis.

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Effects of physical activity intervention on 24-h movement behaviors: a compositional data analysis.

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