Journal of activity, sedentary and sleep behaviors最新文献

{"title":"Prevalence and correlates of meeting the Canadian 24-hour movement guidelines among a sample of Canadian parents during the COVID-19 pandemic.","authors":"Scott Rollo, Abigail Sckrapnick, Julie E Campbell, Sarah A Moore, Guy Faulkner, Mark S Tremblay","doi":"10.1186/s44167-023-00027-3","DOIUrl":"10.1186/s44167-023-00027-3","url":null,"abstract":"<p><strong>Background: </strong>Parents' own movement behaviours can influence those of their children, thus contributing to the health and well-being of the whole family. Parents experienced a shift in work and childcare responsibilities during the COVID-19 pandemic. This may have led to a reduction in their healthy movements. This study examined the prevalence and correlates of meeting vs. not meeting the individual and combined recommendations within the Canadian 24-hour movement guidelines for adults among a sample of Canadian parents during the second wave (October 2020) of the COVID-19 pandemic.</p><p><strong>Methods: </strong>Parents of children aged 5-17 years (n = 1,477) responded to a cross-sectional survey conducted in October 2020. A total of 21 self-reported correlates, including parental and child demographics, and change in family movement behaviours/characteristics were assessed. Parental movement behaviours were reported and classified as meeting or not meeting each of the guidelines. Associations between correlates and meeting each of the guidelines were examined using multiple logistic regression.</p><p><strong>Results: </strong>The proportion of parents who met the moderate-vigorous physical activity (MVPA), recreational screen time, sleep duration and combined guidelines were 21.2, 51.0, 66.1, and 9.1%, respectively. Being a parent ≥ 45 years old, having a university education, and higher levels of outdoor play were associated with meeting the combined guidelines. Age, dwelling type, family hobbies, and outdoor play were associated with meeting the MVPA recommendation. Employment status, education level, dog ownership, children's age, family physical activity, and levels of distress were associated with meeting the recreational screen time recommendation. Geographical region, dwelling type, and levels of distress were associated with meeting the sleep duration recommendation.</p><p><strong>Conclusions: </strong>Few Canadian parents were meeting the combined 24-hour movement guidelines recommendations for MVPA, recreational screen time, and sleep six months into the COVID-19 pandemic. Several socio-demographic, behavioural, and COVID-19-related factors emerged as significant correlates of meeting vs. not meeting the individual and/or combined recommendations within the guidelines. The findings provide various avenues for which to target future movement behaviour interventions and guideline adoption for parents.</p>","PeriodicalId":73581,"journal":{"name":"Journal of activity, sedentary and sleep behaviors","volume":" ","pages":"17"},"PeriodicalIF":0.0,"publicationDate":"2023-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11960277/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44718616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The associations between physical activity, sedentary behaviour, and sleep with mortality and incident cardiovascular disease, cancer, diabetes and mental health in adults: a systematic review and meta-analysis of prospective cohort studies.","authors":"Mitch J Duncan, Leah Murphy, Stina Oftedal, Matthew J Fenwick, Grace E Vincent, Sasha Fenton","doi":"10.1186/s44167-023-00026-4","DOIUrl":"10.1186/s44167-023-00026-4","url":null,"abstract":"<p><strong>Background: </strong>Physical activity, sedentary behaviour and sleep are interrelated and may have a synergistic impact on health. This systematic review and meta-analysis of prospective cohort studies aimed to evaluate the combined influence of different combinations of these behaviours on mortality risk and incidence of cardiovascular disease (CVD), cancer, diabetes, and mental health.</p><p><strong>Methods: </strong>Four online databases were used to identify studies from database inception to May 2023. Prospective cohort studies that examined how different combinations of physical activity, sedentary and sleep behaviours were associated with mortality and incident cardiovascular disease, cancer, diabetes and mental health in adults were included. Random effects meta-analyses using the Der Simonian and Laird method were conducted.</p><p><strong>Results: </strong>Assessment of 4583 records resulted in twelve studies being included. Studies were qualitatively summarised and a sub-group of studies (n = 5) were meta-analysed. The most frequent combination of behaviours was duration of leisure time physical activity and sleep (n = 9), with all-cause mortality (n = 16), CVD mortality (n = 9) and cancer mortality (n = 7) the most frequently examined outcomes. Meta-analysis revealed that relative to High physical activity & Mid sleep, High physical activity and Short sleep was not associated with risk of all-cause mortality (RR = 1.05, 95% CI = 0.97, 1.14), however Low physical activity and Short Sleep (RR = 1.42, 95% CI = 1.24, 1.63), Low physical activity and Mid Sleep (RR = 1.30, 95% CI = 1.12, 1.52), High physical activity and Long Sleep (RR = 1.16, 95% CI = 1.01, 1.32), and Low physical activity and Long Sleep were associated with risk of all-cause mortality (RR = 1.63, 95% CI = 1.21, 2.20).</p><p><strong>Conclusions: </strong>High levels of physical activity may offset all-cause mortality risks associated with short sleep duration. Low levels of physical activity combined with short sleep duration and any level of physical activity in combination with long sleep duration appear to increase mortality risk. Currently there is limited evidence regarding how dimensions of physical activity, sedentary and sleep behaviours other than duration (e.g., quality, timing, type) are associated with future health status.</p>","PeriodicalId":73581,"journal":{"name":"Journal of activity, sedentary and sleep behaviors","volume":" ","pages":"19"},"PeriodicalIF":0.0,"publicationDate":"2023-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11960281/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47770365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The association between 24-hour activity, sedentary and sleep compositions and mental health in Australian adults: a cross-sectional study.","authors":"Rachel G Curtis, Dot Dumuid, Hamish McCabe, Ben Singh, Ty Ferguson, Carol Maher","doi":"10.1186/s44167-023-00024-6","DOIUrl":"10.1186/s44167-023-00024-6","url":null,"abstract":"<p><strong>Background: </strong>Physical activity, sedentary behaviour, and sleep are key components to health and well-being. Compositional data analysis of activity data overcomes the limitations of traditional statistical approaches and comprehensively assesses the association of all activities throughout a 24-hour day. Few studies have used compositional analysis to explore associations between movement behaviours and mental health. This study examined the association between 24-hour activity compositions and mental health in middle-aged Australian adults.</p><p><strong>Methods: </strong>This study used cross-sectional data from participants (n = 322; mean age 40.4 years; 58.1% female; 47.8% university degree; 84.8% partnered) in the longitudinal Annual Rhythms in Adults' lifestyle and health study (Adelaide, Australia). Activity composition (sleep, sedentary behaviour, light physical activity, and moderate-to-vigorous physical activity) was derived using 24-hour Fitbit accelerometry from the first month of participation (December). Mental health outcomes (depression, anxiety, and stress) were obtained from the Depression Anxiety Stress Scale 21-item short-form (DASS-21). The associations between activity composition (conveyed as isometric log ratios) and DASS-21 scores were examined using compositional multi-level linear regression models with a random intercept for clustering of individuals within families. Using the compositional time reallocation model, expected differences in mental health were examined for hypothetical time reallocations between individual activities.</p><p><strong>Results: </strong>Favourable associations were observed when time (15 min) was reallocated to light physical activity from sleep (depression: -0.31 [95% CI=-0.57: -0.06]; anxiety: -0.20 [95% CI=-0.37: -0.03] and from sedentary behaviour (depression: -0.29 [95% CI=-0.46: -0.13]; anxiety: -0.14 [95% CI=-0.25: -0.03]; stress: -0.16 [95% CI=-0.31: -0.01]). Detrimental associations were observed when time was reallocated away from light physical activity to sleep (depression: 0.32 [95% CI = 0.07: 0.58]; anxiety: 0.20 [95% CI = 0.03: 0.37]) and to sedentary behaviour (depression: 0.30 [95% CI = 0.13: 0.48); anxiety: 0.15 [95% CI = 0.03: 0.26]; stress: 0.17 [95% CI = 0.01: 0.32]). There were no associations when time was allocated to or from moderate-to-vigorous physical activity.</p><p><strong>Conclusion: </strong>The way adults spend their time across a 24-hour day is associated with their mental health. Spending more time in light physical activity appears favourable if this time is taken from sleep and sedentary behaviour. These findings provide support for \"move more, sit less\" public health messages.</p><p><strong>Trial registration: </strong>This study was prospectively registered on the Australian New Zealand Clinical Trial Registry (Trial ID: ACTRN12619001430123) on the 16/10/2019.</p>","PeriodicalId":73581,"journal":{"name":"Journal of activity, sedentary and sleep behaviors","volume":" ","pages":"15"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11960370/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46214869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How are different clusters of physical activity, sedentary, sleep, smoking, alcohol, and dietary behaviors associated with cardiometabolic health in older adults? A cross-sectional latent class analysis.","authors":"Simone J J M Verswijveren, Sara Dingle, Alan E Donnelly, Kieran P Dowd, Nicola D Ridgers, Brian P Carson, Patricia M Kearney, Janas M Harrington, Stephanie E Chappel, Cormac Powell","doi":"10.1186/s44167-023-00025-5","DOIUrl":"10.1186/s44167-023-00025-5","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Studies to date that investigate combined impacts of health behaviors, have rarely examined device-based movement behaviors alongside other health behaviors, such as smoking, alcohol, and sleep, on cardiometabolic health markers. The aim of this study was to identify distinct classes based on device-assessed movement behaviors (prolonged sitting, standing, stepping, and sleeping) and self-reported health behaviors (diet quality, alcohol consumption, and smoking status), and assess associations with cardiometabolic health markers in older adults.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;The present study is a cross-sectional secondary analysis of data from the Mitchelstown Cohort Rescreen (MCR) Study (2015-2017). In total, 1,378 older adults (aged 55-74 years) participated in the study, of whom 355 with valid activPAL3 Micro data were included in the analytical sample. Seven health behaviors (prolonged sitting, standing, stepping, sleep, diet quality, alcohol consumption, and smoking status) were included in a latent class analysis to identify groups of participants based on their distinct health behaviors. One-class through to six-class solutions were obtained and the best fit solution (i.e., optimal number of classes) was identified using a combination of best fit statistics (e.g., log likelihood, Akaike's information criteria) and interpretability of classes. Linear regression models were used to test associations of the derived classes with cardiometabolic health markers, including body mass index, body fat, fat mass, fat-free mass, glycated hemoglobin, fasting glucose, total cholesterol, triglycerides, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, very-low-density lipoprotein cholesterol, systolic and diastolic blood pressure.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;In total, 355 participants (89% of participants who were given the activPAL3 Micro) were included in the latent class analysis. Mean participant ages was 64.7 years and 45% were female. Two distinct classes were identified: \"Healthy time-users\" and \"Unhealthy time-users\". These groups differed in their movement behaviors, including physical activity, prolonged sitting, and sleep. However, smoking, nutrition, and alcohol intake habits among both groups were similar. Overall, no clear associations were observed between the derived classes and cardiometabolic risk markers.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Discussion: &lt;/strong&gt;Despite having similar cardiometabolic health, two distinct clusters were identified, with differences in key behaviors such as prolonged sitting, stepping, and sleeping. This is suggestive of a complex interplay between many lifestyle behaviors, whereby one specific behavior alone cannot determine an individual's health status. Improving the identification of the relation of multiple risk factors with health is imperative, so that effective and targeted interventions for improving health in older adults can be designed and implemented.&lt;","PeriodicalId":73581,"journal":{"name":"Journal of activity, sedentary and sleep behaviors","volume":" ","pages":"16"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11960331/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44319344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characteristics associated with differences in 24-hour device-measured and self-reported sleep, sedentary behaviour and physical activity in a sample of Australian primary school children.","authors":"Joshua Gauci, Timothy Olds, Carol Maher, Amanda Watson, François Fraysse, Mason Munzberg, Isaac Hoepfl, Dorothea Dumuid","doi":"10.1186/s44167-023-00023-7","DOIUrl":"10.1186/s44167-023-00023-7","url":null,"abstract":"<p><strong>Background: </strong>How much time children spend sleeping, being sedentary and participating in physical activity affects their health and well-being. To provide accurate guidelines for children's time use, it is important to understand the differences between device-measured and self-reported use-of-time measures, and what may influence these differences. Among Australian primary school-aged children, this study aimed to describe the differences between device-measured and self-reported sleep, sedentary behaviour, light-intensity physical activity (LPA), and moderate-vigorous-intensity physical activity (MVPA), and to explore how sociodemographic and personal characteristics were associated with these differences.</p><p><strong>Methods: </strong>Participants (n = 120, 67% female, age 9-11 years) were drawn from the Life on Holidays cohort study. Device measured use of time was from 7-day accelerometry worn over five timepoints in a 2-year period, and self-reported use of time was from 2-day Multimedia Activity Recall for Children and Adults (MARCA), conducted at the same timepoints. For each participant and measurement method, average daily time spent in sleep, sedentary time, LPA and MVPA was derived for any overlapping days (that had both types of measurement) across the study period. Participant characteristics were either obtained from baseline parental survey (age, sex, parental education, puberty) or derived from the average of direct measurements across the study timepoints (aerobic fitness from shuttle run, body mass index from anthropometric measurements, academic performance from national standardised tests). Differences between device-measured and self-reported use of time were described using Bland-Altmann plots. Compositional outcome linear-regression models were used to determine which participant characteristics were associated with differences by use-of-time measurement type.</p><p><strong>Results: </strong>Relative to device-measured, self-reported daily LPA was underestimated by 83 min (35% difference), whilst sleep (+ 37 min; 6% difference), MVPA (+ 34 min; 33% difference) and sedentary time (+ 12 min; 3% difference) were overestimated. Characteristics underpinning the differences between measurement types were sex (χ² = 11.9, p = 0.008), parental education (χ² = 23.0, p = 0.001), aerobic fitness (χ² = 10.7, p = 0.01) and academic performance (χ² = 15.9, p = 0.001).</p><p><strong>Conclusions: </strong>Among primary school-aged children, device-measured and self-reported use-of-time measurements should not be used interchangeably as there are systematic biases and differences relative to socio-demographic characteristics.</p>","PeriodicalId":73581,"journal":{"name":"Journal of activity, sedentary and sleep behaviors","volume":" ","pages":"14"},"PeriodicalIF":0.0,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11960218/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46053660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Vigorously cited: a bibliometric analysis of the 100 most cited sedentary behaviour articles.","authors":"Aamir R Memon, Sitong Chen, Quyen G To, Corneel Vandelanotte","doi":"10.1186/s44167-023-00022-8","DOIUrl":"10.1186/s44167-023-00022-8","url":null,"abstract":"<p><strong>Objectives: </strong>No citation analysis has examined peer-reviewed sedentary behaviour research articles, which is needed to assess the impact of this research and identify knowledge gaps. Therefore, this study aimed to identify the 100 most cited sedentary behaviour articles and examine their bibliometric characteristics.</p><p><strong>Methods: </strong>All databases indexed in the Web of Science database were searched in October 2022, and bibliometric characteristics of the studies, irrespective of the publication year, were imported and calculated. Descriptive statistics and visualisations by the VOSviewer were used for the presentation of bibliometric characteristics.</p><p><strong>Results: </strong>The 100 most cited articles received 49,062 citations in total, with a median citation density of 32.5 citations per article per year. The majority of included articles were reviews (n = 48; 22,856 citations), focused on adults (58%; 26,809 citations) and reported on the relationship of sedentary behaviour with health (n = 64; 34,598 citations); more specifically they focused on anthropometric indices (28%), metabolic health (24%), and mortality (23%). The United States was ranked first in terms of the overall for most cited articles. However, Australia was ranked first for institutions and authors contributing to the most cited sedentary behaviour articles.</p><p><strong>Conclusions: </strong>Papers published after 2007 were predominant in the list of 100 most cited sedentary behaviour papers, as were those focusing on associations with physical health outcomes and those focusing on adults. While original articles were cited more, discussion papers had more impact on the field as they received more citations in less time. Research examining associations between sedentary behaviour and health was cited more. The field is dominated by contributions from high-income countries.</p>","PeriodicalId":73581,"journal":{"name":"Journal of activity, sedentary and sleep behaviors","volume":" ","pages":"13"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11960230/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43480187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Relative time in physical activity and sedentary behaviour across a 2-year pedometer-based intervention in people with prediabetes or type 2 diabetes: a secondary analysis of a randomised controlled trial.","authors":"Kristina Larsson, Philip Von Rosen, Jenny Rossen, Unn-Britt Johansson, Maria Hagströmer","doi":"10.1186/s44167-023-00020-w","DOIUrl":"10.1186/s44167-023-00020-w","url":null,"abstract":"<p><strong>Background: </strong>People with prediabetes or type 2 diabetes (T2D) need to be physically active, including moderate-to-vigorous intensity physical activity (MVPA) and light-intensity physical activity (LIPA) and reduce time in sedentary behaviour (SB). Few studies have evaluated the effect of randomised controlled trials taking all movement behaviours into account. This study aimed to investigate the effects of a 2-year pedometer-based intervention in people with prediabetes or T2D on relative time in movement behaviours.</p><p><strong>Methods: </strong>Secondary analysis of longitudinal data on individuals with prediabetes or T2D from a three-armed randomised controlled trial, the Sophia Step Study, was conducted. The three groups were (1) a multi‑component group (self‑monitoring of steps with a pedometer plus counselling), (2) a single‑component group (self‑monitoring of steps with a pedometer, without counselling), and (3) a standard care group (control). The three behaviours MVPA, LIPA and SB during waking hours were measured with an ActiGraph GT1M accelerometer at baseline, 6, 12, 18 and 24 months. Relative time in MVPA, LIPA and SB for each participant at each time point was calculated and used as outcome measures. Linear mixed models assessed the effect of the intervention over time.</p><p><strong>Results: </strong>In total 184 participants with mean (SD) age 64.3 (7.6) years and 41% female was included. In the multi-component group, compared to the control group, a significant group-by-time interaction effect for relative time in all three behaviours was found at 6 and 18 months and for MVPA and SB at 24 months. In the single-component group, compared to the control group, an effect occurred in the MVPA and SB behaviours at 6 months and MVPA and LIPA at 24 months. The estimated marginal means ranged from 0.9 to 1.5% of more MVPA, 1.9-3.9% of less LIPA and from 0.5% of less SB to 1.7 more SB in the intervention groups compared to the control group.</p><p><strong>Conclusions: </strong>The findings show a beneficial effect on all behaviours over time in the two intervention groups compared to the control group. A more pronounced effect occurred in the multi-component intervention compared to the single-component intervention, implicating the importance of counselling in pedometer-based interventions. Trial registration ClinicalTrials.gov, NCT02374788.</p>","PeriodicalId":73581,"journal":{"name":"Journal of activity, sedentary and sleep behaviors","volume":" ","pages":"10"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11960371/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42430099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"TRACK & ACT: a pragmatic randomised controlled trial exploring the comparative effectiveness of pedometers and activity trackers for changing physical activity and sedentary behaviour in inactive individuals.","authors":"Daniel J Ryan, Megan H Ross, Joshua Simmich, Norman Ng, Nicola W Burton, Nick Gilson, Toby Pavey, Wendy J Brown, Sjaan R Gomersall","doi":"10.1186/s44167-023-00018-4","DOIUrl":"10.1186/s44167-023-00018-4","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Pedometers have been shown to be effective for increasing physical activity, however the potential additional effects of activity trackers, and their added capacity to simultaneously modify sedentary behaviour, has not been thoroughly explored. This study aimed to explore the comparative effectiveness of two activity trackers and a pedometer for improving daily step count and moderate-vigorous physical activity (MVPA), and reducing sedentary behaviour in inactive adults.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;48 inactive participants were allocated to one of three groups based on their workplace. Each group randomly received either a Fitbit ONE, Jawbone UP or Digi-Walker SW200 pedometer (PED) for 8-weeks and an orientation session to their respective device. Participants were informed about the study aims and were provided with their respective devices and where applicable, the associated Apps. Participants intentionally received no other active intervention components to simulate as closely as possible the experience of purchasing a device 'off the shelf'. Step count, MVPA and time in sedentary behaviour were measured using accelerometry (Actigraph GT3X+) at baseline and four-, eight- and 16-weeks. Analyses were conducted using linear mixed-effect regression models to compare changes from baseline. Post-hoc tests of model estimates compared each activity tracker group to the pedometer group. Model estimates are reported for baseline-16 week follow-up.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;At baseline, average (standard deviation) step count, MVPA and time spent sedentary was 6557 (2111) steps/day, 23 (13) minutes/day and 10.3 (1.0) hours/day in the PED group, 7156 (1496) steps/day, 26 (12) minutes/day and 9.3 (1.2) hours/day in the ONE group and 6853 (1281) steps/day, 29 (10) minutes/day and 10.1 (1.0) hours/day in the UP group. At 16-weeks, based on estimates from the linear mixed-effect regression model, the ONE and UP groups increased step count by 129 steps/day (95% CI - 1497, 1754) and 504 steps/day more (95% CI - 1120, 2130), respectively, than the PED group. For MVPA, the ONE and UP groups increased by 2.3 min/day (95% CI - 10.9, 15.4) and 2.7 min/day more (95% CI - 10.5, 15.8), respectively, than the PED group. For sedentary behaviour, the ONE group had 34 min/day more in time spent sedentary than the PED group (95% CI - 35, 104), while the UP group had 53 min/day more in time spent sedentary than the PED group (95% CI - 18, 123).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;All three groups demonstrated an increase in steps and MVPA, and a decrease in time spent in sedentary behaviour, however there was substantial individual variation in these outcomes indicating considerable uncertainty about the relative effectiveness of activity trackers and pedometers in improving PA and sedentary behaviour. Randomised controlled trials with adequate sample sizes are indicated.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Trial registration: &lt;/strong&gt;ACTRN1262300002761","PeriodicalId":73581,"journal":{"name":"Journal of activity, sedentary and sleep behaviors","volume":" ","pages":"12"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11960358/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48309128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"To be well or not to be well: compositional associations of physical activity, sedentary behaviour and sleep with mental well-being in Flemish adults aged 55+ years.","authors":"Julie Vanderlinden, Gregory J H Biddle, Filip Boen, Jannique G Z van Uffelen","doi":"10.1186/s44167-023-00019-3","DOIUrl":"10.1186/s44167-023-00019-3","url":null,"abstract":"<p><strong>Background: </strong>Well-being is a key aspect for healthy ageing and there is an established association between physical activity and well-being in ageing adults. Despite the recent interest in physical activity as part of a 24-h continuum also including sedentary behaviour and sleep, there is a lack of studies examining the link between these 24-h behaviours and well-being in older adults. Therefore, the aim of this study was twofold: (1) to describe 24-h behaviours and their associations with mental well-being in community dwelling adults aged 55+ years; and (2) to examine the theoretical changes in mental well-being if time were reallocated from one behaviour to another.</p><p><strong>Methods: </strong>This was a cross-sectional study (n = 410). Daily time spent in sedentary behaviour, light and moderate-vigorous physical activity, and sleep was assessed using wrist-worn accelerometers during 6 days. Mental well-being was assessed using the 14-item Warwick-Edinburgh Mental Well-being Scale (WEMWBS). The association of 24-h behaviours and well-being was examined using crude and adjusted linear regression models with compositional data analysis procedures (aim 1). Associations between reallocations of five-minute intervals from five to 60 min between these behaviours and well-being were modelled using compositional isotemporal substitutions (aim 2).</p><p><strong>Results: </strong>Mean age (SD) was 71.3 (6.3) years and 71% were female. In 24-h, participants spent 5.66 h asleep, 13.88 h sedentary, 2.58 h in light intensity and 1,89 h in moderate-vigorous intensity physical activity. There were no statistically significant associations between 24-h behaviours and mental well-being in fully adjusted models (aim 1). Reallocations up to 30 min were not significantly associated with changes in well-being (aim 2). There were some statistically significant theoretical changes of up to 2 points on the WEMWBS with substitutions larger than 30 min.</p><p><strong>Discussion: </strong>24-h behaviours and time reallocations between behaviours were not associated with better or worse well-being in community dwelling adults aged 55+ years. Considering well-being as a key aspect for healthy ageing, future public health research should continue to examine physical activity (both light and moderate-to-vigorous), sedentary behaviour, as well as sleep as a part of the 24-h continuum and its associations with mental health outcomes in older adults. Trial registration This trial was registered at ClinicalTrials.gov on 3th July, 2018 (Trial registration NCT03576209).</p>","PeriodicalId":73581,"journal":{"name":"Journal of activity, sedentary and sleep behaviors","volume":" ","pages":"9"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11960346/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49301767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The potential harms of sedentary behaviour on cardiometabolic health are mitigated in highly active adults: a compositional data analysis.","authors":"Wouter M A Franssen, Jarne Jermei, Hans H C M Savelberg, Bert O Eijnde","doi":"10.1186/s44167-023-00015-7","DOIUrl":"10.1186/s44167-023-00015-7","url":null,"abstract":"<p><strong>Background: </strong>Insufficient physical activity and sedentary behaviour (SB) are important factors that determine cardiometabolic health and the development of non-communicable diseases. The aim of this study was to investigate the modifying effects of moderate-to-vigorous physical activity (MVPA) on the association between SB and cardiometabolic health within highly active adults.</p><p><strong>Methods: </strong>In a cross-sectional design, 61 (male/female: 41/20) highly trained adults (age: 33.6 ± 10.7 years; BMI: 22.4 ± 2.3 kg/m²) performed a maximal cardiopulmonary exercise test from which indicators for peak performance were determined. Physical activity and SB were assessed using the activPAL3™ accelerometer. In addition, anthropometrics, blood pressure, plasma lipids and insulin sensitivity were assessed. These cross-sectional associations between a daily movement behaviour composition and cardiometabolic health parameters were investigated using a compositional data analysis approach.</p><p><strong>Results: </strong>Participants spent 600 ± 86 min/day in SB and engaged in almost 1.5 h per day of MVPA. No association was found between SB and cardiometabolic health related variables, whereas MVPA (β = 8.07 ± 2.18; r² = 0.544; p < 0.001) was only significantly associated with oxygen uptake, relative to all other remaining behaviours.</p><p><strong>Conclusion: </strong>No associations were found between the time spent in SB and cardiometabolic health related outcomes, possibly due to the high amount of time spent in MVPA within highly active adults.</p><p><strong>Trial registration: </strong>The present study was registered on the 14th of January 2022 at clinicaltrials.gov (NCT04711928).</p>","PeriodicalId":73581,"journal":{"name":"Journal of activity, sedentary and sleep behaviors","volume":" ","pages":"6"},"PeriodicalIF":0.0,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11960216/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44062735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}