Search

Background: Greater public transport use has been linked to higher physical activity levels. However, neither the amount of physical activity associated with each daily public transport trip performed, nor the potential total physical activity gain associated with an increase in trips/day, has been determined. Using objective measures, we aimed to quantify the association between public transport use, physical activity and sedentary time. Methods: A longitudinal study of Australian adults living in Hobart, Tasmania, who were infrequent bus users (≥ 18 years; used bus ≤ 2 times/week). The number of bus trips performed each day was determined from objective smartcard data provided by the public transportation (bus) provider across a 36-week study timeframe. Accelerometer measured steps/day (primary outcome), moderate-to-vigorous physical activity (min/day), and sedentary time (min/day) were assessed across four separate one-week periods. Results: Among 73 participants across 1483 day-level observations, on days that public transport was used, participants achieved significantly more steps (β = 2147.48; 95%CI = 1465.94, 2829.03), moderate to vigorous physical activity (β = 22.79; 95% CI = 14.33, 31.26), and sedentary time (β = 37.00; 95% CI = 19.80, 54.21) compared to days where no public transport trips were made. The largest increase in steps per day associated with a one-trip increase was observed when the number of trips performed each day increased from zero to one (β = 1761.63; 95%CI = 821.38, 2701.87). The increase in the number of steps per day was smaller and non-significant when the number of trips performed increased from one to two (β = 596.93; 95%CI=-585.16, 1779.01), and two to three or more (β = 632.39; 95%CI=-1331.45, 2596.24) trips per day. Significant increases in sedentary time were observed when the number of trips performed increased from zero to one (β = 39.38; 95%CI = 14.38, 64.39) and one to two (β = 48.76; 95%CI = 25.39, 72.12); but not when bus trips increased from two to three or more (β=-27.81; 95%CI=-76.00, 20.37). Conclusions: Greater public transport use was associated with higher physical activity and sedentary behaviour. Bus use may yield cumulative increases in steps that amount to 15–30% of the daily recommended physical activity target. A policy and public health focus on intersectoral action to promote public transport may yield meaningful increases in physical activity and subsequent health benefits. [ABSTRACT FROM AUTHOR]

Background: Among elementary-aged children (5-12yrs), summer vacation is associated with accelerated gains in Body Mass Index (BMI). A key behavioral driver of BMI gain is a lack of physical activity (PA). Previous studies indicate PA decreases during summer, compared to the school year but whether this difference is consistent among boys and girls, across age, and by income status remains unclear. This study examined differences in school and summer movement behaviors in a diverse cohort of children across three years. Methods: Children (N = 1,203, age range 5–14 years, 48% girls) wore wrist-placed accelerometers for a 14-day wear-period during school (April/May) and summer (July) in 2021 to 2023, for a total of 6 timepoints. Mixed-effects models examined changes in school vs. summer movement behaviors (moderate-to-vigorous physical activity [MVPA], sedentary) for boys and girls, separately, and by age and household income groups (low, middle, and upper based on income-to-poverty ratio). Results: Children provided a total of 35,435 valid days of accelerometry. Overall, boys (+ 9.1 min/day, 95CI 8.1 to 10.2) and girls (+ 6.2 min/day, 95CI 5.4 to 7.0) accumulated more MVPA during school compared to summer. Boys accumulated less time sedentary (-9.9 min/day, 95CI -13.0 to -6.9) during school, while there was no difference in sedentary time (-2.7 min/day, 95CI -5.7 to 0.4) for girls. Different patterns emerged across ages and income groups. Accumulation of MVPA was consistently greater during school compared to summer across ages and income groups. Generally, the difference between school and summer widened with increasing age, except for girls from middle-income households. Accumulation of sedentary time was higher during school for younger children (5-9yrs), whereas for older children (10-14yrs), sedentary time was greater during summer for the middle- and upper-income groups. For boys from low-income households and girls from middle-income households, sedentary time was consistently greater during summer compared to school across ages. Conclusions: Children are less active and more sedentary during summer compared to school, which may contribute to accelerated BMI gain. However, this differs by biological sex, age, and income. These findings highlight the complex factors influencing movement behaviors between school and summer. [ABSTRACT FROM AUTHOR]

Background: There is a growing population of survivors of colorectal cancer (CRC). Fatigue and insomnia are common symptoms after CRC, negatively influencing health-related quality of life (HRQoL). Besides increasing physical activity and decreasing sedentary behavior, the timing and patterns of physical activity and rest over the 24-h day (i.e. diurnal rest-activity rhythms) could also play a role in alleviating these symptoms and improving HRQoL. We investigated longitudinal associations of the diurnal rest-activity rhythm (RAR) with fatigue, insomnia, and HRQoL in survivors of CRC. Methods: In a prospective cohort study among survivors of stage I-III CRC, 5 repeated measurements were performed from 6 weeks up to 5 years post-treatment. Parameters of RAR, including mesor, amplitude, acrophase, circadian quotient, dichotomy index, and 24-h autocorrelation coefficient, were assessed by a custom MATLAB program using data from tri-axial accelerometers worn on the upper thigh for 7 consecutive days. Fatigue, insomnia, and HRQoL were measured by validated questionnaires. Confounder-adjusted linear mixed models were applied to analyze longitudinal associations of RAR with fatigue, insomnia, and HRQoL from 6 weeks until 5 years post-treatment. Additionally, intra-individual and inter-individual associations over time were separated. Results: Data were available from 289 survivors of CRC. All RAR parameters except for 24-h autocorrelation increased from 6 weeks to 6 months post-treatment, after which they remained relatively stable. A higher mesor, amplitude, circadian quotient, dichotomy index, and 24-h autocorrelation were statistically significantly associated with less fatigue and better HRQoL over time. A higher amplitude and circadian quotient were associated with lower insomnia. Most of these associations appeared driven by both within-person changes over time and between-person differences in RAR parameters. No significant associations were observed for acrophase. Conclusions: In the first five years after CRC treatment, adhering to a generally more active (mesor) and consistent (24-h autocorrelation) RAR, with a pronounced peak activity (amplitude) and a marked difference between daytime and nighttime activity (dichotomy index) was found to be associated with lower fatigue, lower insomnia, and a better HRQoL. Future intervention studies are needed to investigate if restoring RAR among survivors of CRC could help to alleviate symptoms of fatigue and insomnia while enhancing their HRQoL. Trial registration: EnCoRe study NL6904 (https://www.onderzoekmetmensen.nl/). [ABSTRACT FROM AUTHOR]

Background: Sedentary behavior (SB) is a recognized risk factor for many chronic diseases. ActiGraph and activPAL are two commonly used wearable accelerometers in SB research. The former measures body movement and the latter measures body posture. The goal of the current study is to quantify the pattern and variation of movement (by ActiGraph activity counts) during activPAL-identified sitting events, and examine associations between patterns and health-related outcomes, such as systolic and diastolic blood pressure (SBP and DBP). Methods: The current study included 314 overweight postmenopausal women, who were instructed to wear an activPAL (at thigh) and ActiGraph (at waist) simultaneously for 24 hours a day for a week under free-living conditions. ActiGraph and activPAL data were processed to obtain minute-level time-series outputs. Multilevel functional principal component analysis (MFPCA) was applied to minute-level ActiGraph activity counts within activPAL-identified sitting bouts to investigate variation in movement while sitting across subjects and days. The multilevel approach accounted for the nesting of days within subjects. Results: At least 90% of the overall variation of activity counts was explained by two subject-level principal components (PC) and six day-level PCs, hence dramatically reducing the dimensions from the original minute-level scale. The first subject-level PC captured patterns of fluctuation in movement during sitting, whereas the second subject-level PC delineated variation in movement during different lengths of sitting bouts: shorter (< 30 minutes), medium (30 -39 minutes) or longer (> 39 minute). The first subject-level PC scores showed positive association with DBP (standardized β ^ : 2.041, standard error: 0.607, adjusted p = 0.007), which implied that lower activity counts (during sitting) were associated with higher DBP. Conclusion: In this work we implemented MFPCA to identify variation in movement patterns during sitting bouts, and showed that these patterns were associated with cardiovascular health. Unlike existing methods, MFPCA does not require pre-specified cut-points to define activity intensity, and thus offers a novel powerful statistical tool to elucidate variation in SB patterns and health. Trial registration: ClinicalTrials.gov NCT03473145; Registered 22 March 2018; https://clinicaltrials.gov/ct2/show/NCT03473145; International Registered Report Identifier (IRRID): DERR1-10.2196/28684 [ABSTRACT FROM AUTHOR]

Background: Actigraphy is often used to measure sleep in pediatric populations, despite little confirmatory evidence of the accuracy of existing sleep/wake algorithms. The aim of this study was to determine the performance of 11 sleep algorithms in relation to overnight polysomnography in children and adolescents. Methods: One hundred thirty-seven participants aged 8–16 years wore two Actigraph wGT3X-BT (wrist, waist) and three Axivity AX3 (wrist, back, thigh) accelerometers over 24-h. Gold standard measures of sleep were obtained using polysomnography (PSG; Embletta MPRPG, ST + Proxy and TX Proxy) in the home environment, overnight. Epoch by epoch comparisons of the Sadeh (two algorithms), Cole-Kripke (three algorithms), Tudor-Locke (four algorithms), Count-Scaled (CS), and HDCZA algorithms were undertaken. Mean differences from PSG values were calculated for various sleep outcomes. Results: Overall, sensitivities were high (mean ± SD: 91.8%, ± 5.6%) and specificities moderate (63.8% ± 13.8%), with the HDCZA algorithm performing the best overall in terms of specificity (87.5% ± 1.3%) and accuracy (86.4% ± 0.9%). Sleep outcome measures were more accurately measured by devices worn at the wrist than the hip, thigh or lower back, with the exception of sleep efficiency where the reverse was true. The CS algorithm provided consistently accurate measures of sleep onset: the mean (95%CI) difference at the wrist with Axivity was 2 min (-6; -14,) and the offset was 10 min (5, -19). Several algorithms provided accurate measures of sleep quantity at the wrist, showing differences with PSG of just 1–18 min a night for sleep period time and 5–22 min for total sleep time. Accuracy was generally higher for sleep efficiency than for frequency of night wakings or wake after sleep onset. The CS algorithm was more accurate at assessing sleep period time, with narrower 95% limits of agreement compared to the HDCZA (CS:-165 to 172 min; HDCZA: -212 to 250 min). Conclusion: Although the performance of existing count-based sleep algorithms varies markedly, wrist-worn devices provide more accurate measures of most sleep measures compared to other sites. Overall, the HDZCA algorithm showed the greatest accuracy, although the most appropriate algorithm depends on the sleep measure of focus. [ABSTRACT FROM AUTHOR]

Background: There is a lack of longitudinal studies examining changes in device-measured physical activity and sedentary time from childhood to young adulthood. We aimed to assess changes in device-measured physical activity and sedentary time from childhood, through adolescence, into young adulthood in a Norwegian sample of ostensibly healthy men and women. Methods: A longitudinal cohort of 731 Norwegian boys and girls (49% girls) participated at age 9 years (2005–2006) and 15 years (2011–2012), and 258 of these participated again at age 24 years (2019–2021; including the COVID-19 pandemic period). Physical activity and sedentary time were measured using ActiGraph accelerometers. Linear mixed models were used to analyse changes in physical activity and sedentary time and whether low levels of childhood physical activity track, i.e., persist into young adulthood (nchange=721; ntracking=640). Results: The most prominent change occurred between the ages of 9 to 15 years, with an increase in sedentary time (150 min/day) and less time spent in light (125 min/day), moderate (16 min/day), and vigorous physical activity (8 min/day). Only smaller changes were observed between the ages of 15 and 24 years. Changes in moderate-to-vigorous physical activity from childhood to young adulthood differed between subgroups of sex, tertiles of body mass index at baseline and tertiles of peak oxygen uptake at baseline. While the tracking models indicated low absolute stability of physical activity from childhood to young adulthood, children in the lowest quartiles of moderate-to-vigorous (OR:1.88; 95%CI: 1.23, 2.86) and total physical activity (OR: 1.87; 95%CI: 1.21, 2.87) at age 9 years were almost 90% more likely to be in these quartiles at age 24 years compared to those belonging to the upper three quartiles at baseline. Conclusions: We found a substantial reduction in physical activity and increase in time spent sedentary between age 9 and 15 years. Contrary to previous studies, using mainly self-reported physical activity, little change was observed between adolescence and young adulthood. The least active children were more likely to remain the least active adults and could be targeted for early intervention. [ABSTRACT FROM AUTHOR]

Background: Parental practices and neighbourhood environmental factors may influence children's movement behaviours. We aimed to investigate the cross-sectional and prospective associations of parental practices and neighbourhood environmental factors with accelerometer-measured 24-hour movement behaviours (24 h-MBs) among school-aged children in Singapore. Methods: The Growing Up in Singapore Towards healthy Outcomes (GUSTO) study collected information on dimensions of parental practices and neighbourhood environment at age 5.5 years. Confirmatory factor analyses were performed to generate latent variables and used to compute overall parental practices [involvement in PA + support for PA + control of screen viewing context] and environmental scores [facilities for active play + active mobility facilitators + barriers*-1]. Children wore an accelerometer on their non-dominant wrist for seven consecutive days at ages 5.5 and 8 years. The R-package GGIR 2.6 was used to derive moderate-to-vigorous-intensity physical activity (MVPA), light-intensity physical activity (LPA), inactivity, and total-sleep (napping+night sleep) minutes per day. Associations were determined using compositional data analysis with multivariate linear regression models, taking into account potential confounders. Results: Among 425 children (48% girls, 59% Chinese), higher parental involvement in PA, parental support for PA and overall parental practices were associated with 24 h-MBs at ages 5.5 and 8 years, specifically with greater time spent in MVPA and less time being inactive relative to the remaining movement behaviours. The corresponding mean changes in the overall 24 h-MB for increasing parental practices from lowest to highest scores (− 2 to + 2 z-scores) indicated potential increases of up to 15-minutes in MVPA, 20-minutes in LPA, 5-minutes in sleep duration, and a reduction of 40-minutes in inactivity at age 5.5 years. At age 8 years, this could translate to approximately 15-minutes more of MVPA, 20-minutes more of LPA, a 20-minute reduction in sleep duration, and a 20-minute reduction in inactivity. Parental control of screen viewing contexts and neighbourhood environmental factors were not associated with 24 h-MBs. Conclusions: Parental practices but not environmental factors were associated with higher MVPA and lower inactivity among Singaporean children, even at a later age. Further research may provide insights that support development of targeted public health strategies to promote healthier movement behaviours among children. Study registration: This study was registered on 4th August 2010 and is available online at ClinicalTrials.gov: NCT01174875. [ABSTRACT FROM AUTHOR]

Background: Few studies have examined the relationship between motor skill competence and device-measured physical activity in large samples and none have used non-linear modelling. This study assessed the linear and non-linear associations between motor skill competence and physical activity in children using pooled data from eight studies. Methods: Cross-sectional ActiGraph accelerometer and motor skills competence data from 988 children (50.8% boys) aged 3–11 years were included. Total, object control and locomotor skill competence were assessed using the Test of Gross Motor Skill Development. Linear mixed models were fitted to examine linear associations between motor skill competence and physical activity. Then, restricted cubic splines models were used to assess potential non-linear relationships. Interactions by sex and age were assessed. Results: There was evidence of positive linear associations between total skill, and object control and locomotor skills, with moderate- and vigorous-intensity physical activity; however, the associations with total skill competence and object control better fitted a non-linear model. Non-linear models indicated associations were positive but relatively weak in the low to mid ranges of TGMD/object control scores but at high ranges (~ > 70 out of 100/ and ~ 35 out of 50) the association strength increased for both moderate- and vigorous-intensity physical activity. There were sex interactions for locomotor skills only, specifically for vigorous activity with boys having a stronger positive association than girls. Conclusions: There appears to be a threshold for object control skill proficiency that children need to reach to enhance their physical activity levels which provides support for a motor skill "proficiency barrier". This provides a tangible benchmark for children to achieve in motor competence programs. [ABSTRACT FROM AUTHOR]

Background: Previous studies on physical activity (PA) and pelvic organ prolapse (POP) were largely limited to self-reported PA in athletes, soldiers, and women in postpartum. We aimed to investigate the association of accelerometer-measured PA and sedentary behavior with the risk of POP in middle-aged and elderly women. Methods: In this prospective cohort derived from the UK Biobank, the intensity and duration of PA and sedentary behavior were measured with wrist-worn accelerometers over a 7-day period in 2013–2015 for 47,674 participants (aged 42.8–77.9 years) without pre-existing POP. Participants were followed up until the end of 2022, during which incident POP was ascertained mainly by the electronic health records. Multivariable-adjusted Cox proportional hazards models and restricted cubic splines were used to assess the associations of interest. Isotemporal substitution models were applied to test the effects of substituting a type of activity with equivalent duration of others. Results: During a median follow-up of 8.0 years, 779 cases of POP were recorded. The duration of light-intensity PA (LPA) was positively whereas sedentary time was negatively associated with the risk of POP. Every additional 1 h/day of LPA elevated the risk of POP by 18% (95% confidence interval [CI], 10%–26%). In contrast, the risk decreased by 5% (95% CI, 0–8%) per 1 h/day increment in sedentary behavior. No associations were found between moderate-intensity PA (MPA) or vigorous-intensity PA (VPA) and POP, except that women who had a history of hysterectomy were more likely to develop POP when performing more VPA (53% higher risk for every additional 15 min/day). Substituting 1 h/day of LPA with equivalent sedentary time was associated with a 18% (95% CI, 11%–24%) lower risk of POP. The risk can also be reduced by 17% (95% CI, 7%–25%) through substituting 30 min/day of LPA with MPA. Conclusions: More time spent in LPA or less sedentary time was linked to an elevated risk of POP in middle-aged and elderly women, while MPA or VPA was not. Substituting LPA with equivalent duration of sedentary behavior or MPA may lower the risk of POP. [ABSTRACT FROM AUTHOR]

Background: The longitudinal associations between physical behaviours and lean muscle mass indices need to be better understood to aid healthy ageing intervention development. Methods: We assessed physical behaviours (total physical activity, moderate-to-vigorous physical activity (MVPA), light physical activity, total sedentary time and prolonged sedentary bout time) for 7 days using hip-worn accelerometers. We also assessed domain-specific physical behaviours (walking, cycling, gardening and housework time) with self-report questionnaires at baseline (2006–2011) and follow-up (2012–2016) in the European Prospective Investigation into Cancer (EPIC)-Norfolk study. We assessed body composition using dual-energy X-ray absorptiometry (DEXA) at follow-up in 1535 participants (≥ 60 years at baseline). From this, we derived appendicular lean muscle mass (ALM) indices (% relative ALM = (ALM/total body weight)*100), body mass index (BMI)-scaled ALM (ALM/BMI, kg/kg/m2) and height-scaled ALM (ALM/height2, kg/m2)). We evaluated the prospective associations of both baseline and change in physical behaviours with follow-up muscle mass indices using multivariable linear regression. Results: Over 5.5 years (SD 14.8) follow-up, higher baseline accelerometer-measured physical activity and lower sedentary time were associated with higher subsequent relative ALM and BMI-scaled ALM, but not height-scaled ALM (e.g. 0.02% higher subsequent relative ALM per minute/day of baseline MVPA for men). Greater increases in physical activity and greater declines in sedentary time variables were associated with higher subsequent relative ALM and BMI-scaled ALM, but not height-scaled ALM (e.g. 0.001 kg/kg/m2 subsequent BMI-scaled ALM and 0.04% subsequent relative ALM per min/day/year increases in LPA over follow-up; 0.001 kg/kg/m2 subsequent BMI-scaled ALM and -0.03% subsequent relative ALM per min/day/year less of total sedentary time over follow-up). Greater increases in women's cycling and gardening over follow-up were associated with greater subsequent relative ALM (cycling 0.9% per hour/week/year; gardening 0.2% per hour/week/year) and BMI-scaled ALM (cycling 0.03 kg/kg/m2 per hour/week/year; gardening 0.004 kg/kg/m2 per hour/week/year). Conclusion: Physical behaviours across all intensities, and in women more specifically cycling and gardening, may help prevent age-related declines in muscle mass. [ABSTRACT FROM AUTHOR]

Background: There is limited understanding of the extent to which differences in physical activity across the day and week may be associated with mental wellbeing. Such an understanding is needed for better targeting of interventions. In this study, we describe total and temporal patterning of physical activity across the week in adolescents (age 13-14y) and assess their prospective associations with mental wellbeing. Methods: 1,983 13-14-year-old adolescent participants based in Cambridgeshire and Essex, recruited between 2016 and 2017 into the Get Others Active Trial provided data at baseline and 4 months. Physical activity was measured at baseline using wrist-worn accelerometers across different time segments (whole week, weekday schooltime, weekday out of school, and weekend), and operationalized as average movement-related acceleration for each time segment. Mental Wellbeing at baseline and 4 months was measured using the Warwick Edinburgh MentalWellbeing Scale. Associations between physical activity across different time segments (whole week, weekday schooltime, weekday out of school, and weekend) and mental wellbeing at 4 months were investigated using sex-stratified multi-level regression models, adjusted for covariates, and both adjusted and unadjusted for baseline mental wellbeing. Results: Our analyses found positive associations between physical activity and mental wellbeing at 4 months, unadjusted for baseline wellbeing. Among girls, positive associations were shown when considering physical activity across the whole week 0.07 (95% CI, 0.03–0.12), and across all separate time periods studied: weekday schooltime 0.07 (95% CI, 0.02–0.11), weekday out-of-school time 0.07 (95% CI, 0.03–0.12), and weekend 0.07 (95% CI, 0.02–0.11). For boys, similar associations were observed for activity across the week 0.07 (95% CI, 0.03–0.11), during weekday schooltime 0.08 (95% CI, 0.04–0.12), and weekday out-of-school time 0.07 (95% CI, 0.03–0.11), but not the weekend 0.01 (95% CI, -0.03-0.05). For both girls and boys, associations were attenuated below significance after adjusting for baseline wellbeing. Conclusions: This longitudinal analysis showed positive associations between physical activity and later mental wellbeing in both male and female adolescents across most time segments. Higher physical activity throughout the week may be associated with better mental wellbeing in the adolescent population. Further research is required to understand determinants of change in wellbeing over time. Trial Registration: Registration Number: ISRCTN31583496. Registered: 18/02/2014. [ABSTRACT FROM AUTHOR]

A correction to the article "Validation of actigraphy sleep metrics in children aged 8 to 16 years: Considerations for device type, placement and algorithms" that was published in a 2024 issue of the journal is presented.

Background: Despite apparent shortcomings such as measurement error and low precision, self-reported sedentary time is still widely used in surveillance and research. The aim of this study was threefold; (i) to examine the agreement between self-reported and device-measured sitting time in a general adult population; (ii), to examine to what extent demographics, lifestyle factors, long-term health conditions, physical work demands, and educational level is associated with measurement bias; and (iii), to explore whether correcting for factors associated with bias improves the prediction of device-measured sitting time based on self-reported sitting time. Methods: A statistical validation model study based on data from 23 993 adults in the Trøndelag Health Study (HUNT4), Norway. Participants reported usual sitting time on weekdays using a single-item questionnaire and wore two AX3 tri-axial accelerometers on the thigh and low back for an average of 3.8 (standard deviation [SD] 0.7, range 1–5) weekdays to determine their sitting time. Statistical validation was performed by iteratively adding all possible combinations of factors associated with bias between self-reported and device-measured sitting time in a multivariate linear regression. We randomly selected 2/3 of the data (n = 15 995) for model development and used the remaining 1/3 (n = 7 998) to evaluate the model. Results: Mean (SD) self-reported and device-measured sitting time were 6.8 (2.9) h/day and 8.6 (2.2) h/day, respectively, corresponding to a mean difference of 1.8 (3.1) h/day. Limits of agreement ranged from − 8.0 h/day to 4.4 h/day. The discrepancy between the measurements was characterized by a proportional bias with participants device-measured to sit less overestimating their sitting time and participants device-measured to sit more underestimating their sitting time. The crude explained variance of device-measured sitting time based on self-reported sitting time was 10%. This improved to 24% when adding age, body mass index and physical work demands to the model. Adding sex, lifestyle factors, educational level, and long-term health conditions to the model did not improve the explained variance. Conclusions: Self-reported sitting time had low validity and including a range of factors associated with bias in self-reported sitting time only marginally improved the prediction of device-measured sitting time. [ABSTRACT FROM AUTHOR]

Background: Movement behaviours, including physical activity, sedentary behaviour, and sleep have been shown to be associated with several chronic diseases. However, they have not been objectively measured in large-scale prospective cohort studies in low-and middle-income countries. We aim to describe the patterns of device-measured movement behaviours collected in the China Kadoorie Biobank (CKB) study. Methods: During 2020 and 2021, a random subset of 25,087 surviving CKB individuals participated in the 3rd resurvey of the CKB. Among them, 22,511 (89.7%) agreed to wear an Axivity AX3 wrist-worn triaxial accelerometer for seven consecutive days to assess their habitual movement behaviours. We developed a machine-learning model to infer time spent in four movement behaviours [i.e. sleep, sedentary behaviour, light intensity physical activity (LIPA), and moderate-to-vigorous physical activity (MVPA)]. Descriptive analyses were performed for wear-time compliance and patterns of movement behaviours by different participant characteristics. Results: Data from 21,897 participants (aged 65.4 ± 9.1 years; 35.4% men) were received for demographic and wear-time analysis, with a median wear-time of 6.9 days (IQR: 6.1–7.0). Among them, 20,370 eligible participants were included in movement behavior analyses. On average, they had 31.1 mg/day (total acceleration) overall activity level, accumulated 7.7 h/day (32.3%) of sleep time, 8.8 h/day (36.6%) sedentary, 5.7 h/day (23.9%) in light physical activity, and 104.4 min/day (7.2%) in moderate-to-vigorous physical activity. There was an inverse relationship between age and overall acceleration with an observed decline of 5.4 mg/day (17.4%) per additional decade. Women showed a higher activity level than men (32.3 vs 28.8 mg/day) and there was a marked geographical disparity in the overall activity level and time allocation. Conclusions: This is the first large-scale accelerometer data collected among Chinese adults, which provides rich and comprehensive information about device-measured movement behaviour patterns. This resource will enhance our knowledge about the potential relevance of different movement behaviours for chronic disease in Chinese adults. [ABSTRACT FROM AUTHOR]

Background: The beneficial effect of acute physical exercise on cognitive performance has been studied in laboratory settings and in long-term longitudinal studies. Less is known about these associations in everyday environment and on a momentary timeframe. This study investigated momentary and daily associations between physical activity and cognitive functioning in the context of everyday life. Methods: Middle-aged adults (n = 291, aged 40–70) were asked to wear accelerometers and complete ecological momentary assessments for eight consecutive days. Processing speed and visual memory were assessed three times per day and self-rated evaluations of daily cognition (memory, thinking, and sharpness of mind) were collected each night. The number of minutes spent above the active threshold (active time) and the maximum vector magnitude counts (the highest intensity obtained) before each cognitive test and at a daily level were used as predictors of momentary cognitive performance and nightly subjective cognition. Analyses were done with multilevel linear models. The models were adjusted for temporal and contextual factors, age, sex, education, and race/ethnicity. Results: When participants had a more active time or higher intensity than their average level within the 20 or 60 minutes prior to the cognitive test, they performed better on the processing speed task. On days when participants had more active time than their average day, they rated their memory in the evening better. Physical activity was not associated with visual memory or self-rated thinking and sharpness of mind. Conclusions: This study provides novel evidence that outside of laboratory settings, even small increases in physical activity boost daily processing speed abilities and self-rated memory. The finding of temporary beneficial effects is consistent with long-term longitudinal research on the cognitive benefits of physical activity. [ABSTRACT FROM AUTHOR]

Background: Suboptimal rest-activity patterns in adolescence are associated with worse health outcomes in adulthood. Understanding sociodemographic factors associated with rest-activity rhythms may help identify subgroups who may benefit from interventions. This study aimed to investigate the association of rest-activity rhythm with demographic and socioeconomic characteristics in adolescents. Methods: Using cross-sectional data from the nationally representative National Health and Nutrition Examination Survey (NHANES) 2011–2014 adolescents (N = 1814), this study derived rest-activity profiles from 7-day 24-hour accelerometer data using functional principal component analysis. Multiple linear regression was used to assess the association between participant characteristics and rest-activity profiles. Weekday and weekend specific analyses were performed in addition to the overall analysis. Results: Four rest-activity rhythm profiles were identified, which explained a total of 82.7% of variance in the study sample, including (1) High amplitude profile; (2) Early activity window profile; (3) Early activity peak profile; and (4) Prolonged activity/reduced rest window profile. The rest-activity profiles were associated with subgroups of age, sex, race/ethnicity, and household income. On average, older age was associated with a lower value for the high amplitude and early activity window profiles, but a higher value for the early activity peak and prolonged activity/reduced rest window profiles. Compared to boys, girls had a higher value for the prolonged activity/reduced rest window profiles. When compared to Non-Hispanic White adolescents, Asian showed a lower value for the high amplitude profile, Mexican American group showed a higher value for the early activity window profile, and the Non-Hispanic Black group showed a higher value for the prolonged activity/reduced rest window profiles. Adolescents reported the lowest household income had the lowest average value for the early activity window profile. Conclusions: This study characterized main rest-activity profiles among the US adolescents, and demonstrated that demographic and socioeconomic status factors may shape rest-activity behaviors in this population. [ABSTRACT FROM AUTHOR]

Background: Physical behavior (PB) is a key lifestyle factor in regulating and preventing diseases across the lifespan. Researchers identified affective, cognitive, and contextual factors like weather conditions, as significant contributors in determining if individuals are physically active. However, there is scarce empirical evidence about potential associations between PB and affective states influenced by weather conditions in daily life. Therefore, we explored if weather conditions moderated the within-subject association between momentary affective states and subsequent PB. Methods: Utilizing ambulatory assessment, 79 participants completed electronic diaries about their affective states (i.e., valence, energetic arousal, and calmness) up to six times a day over five days, and their PB (i.e., physical activity and sedentariness) was simultaneously recorded via accelerometers. Weather conditions (i.e., temperature and precipitation) recorded near participants' locations served as moderators in the multilevel analyses. Results: We confirmed earlier findings associating affective states with PB. Increased valence and energetic arousal were positively associated with physical activity (β = 0.007; p <.001), whereas calmness predicted lower levels of physical activity (β = -0.006; p <.001). Higher levels of calmness showed a positive association with sedentary behavior (β = 0.054; p =.003). In addition, we revealed a significant positive association between temperature, as a momentary weather condition, and physical activity (β = 0.025; p =.015). Furthermore, we showed that the association of affective states and physical activity was moderated by temperature. Higher temperatures enhanced the positive effects of valence on physical activity (β =.001, p =.023) and attenuated the negative effects of calmness on physical activity (β =.001, p =.021). Moreover, higher temperatures enhanced the positive effects of valence on reduced sedentary behavior (β = -0.011, p =.043). Conclusions: Temperature alterations appeared to have an impact on subsequent physical activity. Furthermore, temperature alterations moderated the influence of affective states on conducted physical activity. This might offer the opportunity for just-in-time adaptive interventions to intervene in individually appropriate environmental conditions for promoting physical activity. [ABSTRACT FROM AUTHOR]

Background: Mental health problems in young people have become a global health burden. The positive effects of physical activity on mental health in adults are well known but still not clear in children. The aim of this study was to investigate to what extent physical activity in early childhood would affect mental health in middle childhood. Methods: From the Dutch GECKO Drenthe birth cohort, 850 children (51.5% boys) were enrolled in this analysis. Physical activity and sedentary time were measured at age 5–6 using ActiGraph GT3X. Mental health was assessed using the Strengths and Difficulties Questionnaire (SDQ) at age 5–6 and age 10–11. Multiple linear regression models were used to estimate the associations between physical activity, sedentary time and SDQ subscales, stratified by gender, adjusting for age, BMI, maternal education level, family size, accelerometer wear time and season, and additionally adjusting for SDQ scores at age 5–6 to take tracking of mental health over time into account. Results: Greater physical activity volume at age 5–6 was associated with lower peer problems scores at age 10–11 in boys and girls. An increase in MVPA was associated with lower peer problems scores in boys (b = -0.445, -0.713 to -0.176) and girls (b = -0.354, -0.601 to -0.107), however, increased sedentary time was linked to higher peer problems scores in boys (b = 1.18, 0.455 to 1.906) and girls (b = 0.870, 0.191 to 1.550). For hyperactivity, higher levels of physical activity volume and MVPA were associated with higher hyperactivity scores in boys. Increased sedentary time was related to lower hyperactivity scores in boys. Further adjustment for SDQ scores at age 5–6 attenuated associations between physical activity and hyperactivity in boys but hardly changed the relationships with peer problems. No significant associations between physical activity and other SDQ subscales or total difficulties scores were observed, neither in boys nor in girls. Conclusions: Children who are more physically active at age 5–6 have fewer peer problems at age 10–11, and for boys, greater activity levels at age 5–6 could be an indicator of hyperactivity at age 10–11. [ABSTRACT FROM AUTHOR]

Background: Public transport users tend to accumulate more physical activity than non-users; however, whether physical activity is increased by financially incentivising public transport use is unknown. The trips4health study aimed to determine the impact of an incentive-based public transport intervention on physical activity. Methods: A single-blinded randomised control trial of a 16-week incentive-based intervention involved Australian adults who were infrequent bus users (≥ 18 years; used bus ≤ 2 times/week) split equally into intervention and control groups. The intervention group were sent weekly motivational text messages and awarded smartcard bus credit when targets were met. The intervention group and control group received physical activity guidelines. Accelerometer-measured steps/day (primary outcome), self-reported transport-related physical activity (walking and cycling for transport) and total physical activity (min/week and MET-min/week) outcomes were assessed at baseline and follow-up. Results: Due to the COVID pandemic, the trial was abandoned prior to target sample size achievement and completion of all assessments (N = 110). Steps/day declined in both groups, but by less in the intervention group [-557.9 steps (-7.9%) vs.-1018.3 steps/week (-13.8%)]. In the intervention group, transport-related physical activity increased [80.0 min/week (133.3%); 264.0 MET-min/week (133.3%)] while total physical activity levels saw little change [35.0 min/week (5.5%); 25.5 MET-min/week (1.0%)]. Control group transport-related physical activity decreased [-20.0 min/week (-27.6%); -41.3 MET-min/week (-17.3%)], but total physical activity increased [260.0 min/week (54.5%); 734.3 MET-min/week (37.4%)]. Conclusion: This study found evidence that financial incentive-based intervention to increase public transport use is effective in increasing transport-related physical activity These results warrant future examination of physical activity incentives programs in a fully powered study with longer-term follow-up. Trial registration: This trial was registered with the Australian and New Zealand Clinical Trials Registry August 14th, 2019: ACTRN12619001136190; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=377914&isReview=true [ABSTRACT FROM AUTHOR]

Background: The associations of sedentary time and patterns with functional disability among older adults remain unclear, and few studies have accounted for the co-dependency of sedentary behavior and physical activities when modeling sedentary behavior with risk of functional disability. We aimed to examine the associations between sedentary time and patterns and risk of incident functional disability, and assess whether replacing sedentary time with light physical activity (LPA) or moderate-to-vigorous intensity physical activity (MVPA) is associated with reduced risk of functional disability in community-dwelling older adults. Methods: A total of 1,687 Japanese adults aged ≥ 65 years without functional disability at baseline were prospectively followed-up for 9 years (2011–2020). Functional disability was ascertained using the national database of Japan's Long-term Care Insurance System. Sedentary time and patterns, LPA, and MVPA were measured using a tri-axial accelerometer secured to participants' waists. Results: During follow-up, 466 participants developed functional disability. Compared with the lowest quartile of total sedentary time, the multivariable-adjusted hazard ratios (95% confidence intervals) of functional disability for the second, third, and top quartiles were 1.21 (0.91‒1.62), 1.45 (1.10‒1.92), and 1.40 (1.05‒1.88) (p for trend = 0.01). After further adjusting for MVPA, total sedentary time was no longer significantly associated with the risk of functional disability (p for trend = 0.41). Replacing 10 min/day of sedentary time with the same amount of MVPA (but not LPA) was significantly associated with a 12% reduced risk of functional disability (hazard ratio [95% confidence interval]: 0.88 [0.84‒0.92]). No significant association was observed between sedentary bout length and functional disability. Conclusion: Higher levels of total sedentary time were associated with an increased risk of incident functional disability. However, this association was not independent of MVPA. Replacing sedentary time with MVPA, but not LPA, was associated with reduced risk of functional disability in older adults. [ABSTRACT FROM AUTHOR]

Background: Walking is known to be good for health. However, it is unknown whether it matters if steps are taken during work or leisure. Therefore, we aimed to examine the prospective association between accelerometer-measured steps taken during work or leisure and register-based long-term sickness absence (LTSA). Methods: We included 937 blue- and white-collar workers from the PODESA cohort who wore a thigh-based accelerometer over four days to measure number of steps during work and leisure. Steps were divided into domain based on diary data. First event of LTSA was retrieved from a national register with four years' follow-up. We used Cox proportional hazard models to analyze the association between domain-specific and total daily steps and LTSA, adjusted for age, sex, job type, smoking, and steps in the other domain (e.g., work/leisure). Results: We found more steps at work to be associated with a higher LTSA risk [Hazard Ratio (HR):1.04; 95% CI: 1.00–1.08 per 1000 steps]. No significant association was found between steps during leisure and LTSA (HR: 0.97; 95% CI: 0.91–1.02), nor between total daily steps and LTSA (HR: 1.01; CI 95% 0.99–1.04). Conclusions: More steps at work were associated with higher risk of LTSA, while steps during leisure was not clearly associated with LTSA risk. These findings partly support 'the physical activity paradox' stating that the association between physical activity and health depends on the domain. [ABSTRACT FROM AUTHOR]

Background: Research on the association of physical activity and sedentary time with dementia is accumulating, though elusive, and the interaction effects of the two remain unclear. We analysed the joint associations of accelerometer-measured physical activity and sedentary time with risk of incident dementia (all-cause dementia, Alzheimer's disease and vascular dementia). Methods: A total of 90,320 individuals from the UK Biobank were included. Accelerometer-measured total volume of physical activity (TPA) and sedentary time were measured at baseline and dichotomised by median (low TPA [< 27 milli-gravity (milli-g)], high TPA [≥ 27 milli-g]; low sedentary time [< 10.7 h/day], high sedentary time [≥ 10.7 h/day]). Cox proportional hazards models were used to evaluate the joint associations with incident dementia on both additive and multiplicative scales. Results: During a median follow-up of 6.9 years, 501 cases of all-cause dementia were identified. Higher TPA was associated with a lower risk of all-cause dementia, Alzheimer's disease and vascular dementia; the multivariate adjusted hazard ratios (HRs) (95% CI) per 10 milli-g increase were 0.63 (0.55–0.71), 0.74 (0.60–0.90) and 0.69 (0.51–0.93), respectively. Sedentary time was only found to be linked to all-cause dementia, and the HR for high sedentary time was 1.03 (1.01–1.06) compared with that for low sedentary time. No additive and multiplicative relationship of TPA and sedentary time to incident dementia was found (all P values > 0.05). Conclusion: Higher TPA level was related to a lower risk of incident dementia irrespective of sedentary time, which highlighted the implication of promoting physical activity participation to counteract the potential detrimental effect of sedentary time on dementia. [ABSTRACT FROM AUTHOR]

Background: Over the last decade use of raw acceleration metrics to assess physical activity has increased. Metrics such as Euclidean Norm Minus One (ENMO), and Mean Amplitude Deviation (MAD) can be used to generate metrics which describe physical activity volume (average acceleration), intensity distribution (intensity gradient), and intensity of the most active periods (MX metrics) of the day. Presently, relatively little comparative data for these metrics exists in youth. To address this need, this study presents age- and sex-specific reference percentile values in England youth and compares physical activity volume and intensity profiles by age and sex. Methods: Wrist-worn accelerometer data from 10 studies involving youth aged 5 to 15 y were pooled. Weekday and weekend waking hours were first calculated for youth in school Years (Y) 1&2, Y4&5, Y6&7, and Y8&9 to determine waking hours durations by age-groups and day types. A valid waking hours day was defined as accelerometer wear for ≥ 600 min·d−1 and participants with ≥ 3 valid weekdays and ≥ 1 valid weekend day were included. Mean ENMO- and MAD-generated average acceleration, intensity gradient, and MX metrics were calculated and summarised as weighted week averages. Sex-specific smoothed percentile curves were generated for each metric using Generalized Additive Models for Location Scale and Shape. Linear mixed models examined age and sex differences. Results: The analytical sample included 1250 participants. Physical activity peaked between ages 6.5–10.5 y, depending on metric. For all metrics the highest activity levels occurred in less active participants (3rd-50th percentile) and girls, 0.5 to 1.5 y earlier than more active peers, and boys, respectively. Irrespective of metric, boys were more active than girls (p <.001) and physical activity was lowest in the Y8&9 group, particularly when compared to the Y1&2 group (p <.001). Conclusions: Percentile reference values for average acceleration, intensity gradient, and MX metrics have utility in describing age- and sex-specific values for physical activity volume and intensity in youth. There is a need to generate nationally-representative wrist-acceleration population-referenced norms for these metrics to further facilitate health-related physical activity research and promotion. [ABSTRACT FROM AUTHOR]

Background: Accelerometer measures of physical behaviours (physical activity, sedentary behaviour and sleep) in observational studies offer detailed insight into associations with health and disease. Maximising recruitment and accelerometer wear, and minimising data loss remain key challenges. How varying methods used to collect accelerometer data influence data collection outcomes is poorly understood. We examined the influence of accelerometer placement and other methodological factors on participant recruitment, adherence and data loss in observational studies of adult physical behaviours. Methods: The review was in accordance with the Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA). Observational studies of adults including accelerometer measurement of physical behaviours were identified using database (MEDLINE (Ovid), Embase, PsychINFO, Health Management Information Consortium, Web of Science, SPORTDiscus and Cumulative Index to Nursing & Allied Health Literature) and supplementary searches to May 2022. Information regarding study design, accelerometer data collection methods and outcomes were extracted for each accelerometer measurement (study wave). Random effects meta-analyses and narrative syntheses were used to examine associations of methodological factors with participant recruitment, adherence and data loss. Results: 123 accelerometer data collection waves were identified from 95 studies (92.5% from high-income countries). In-person distribution of accelerometers was associated with a greater proportion of invited participants consenting to wear an accelerometer (+ 30% [95% CI 18%, 42%] compared to postal distribution), and adhering to minimum wear criteria (+ 15% [4%, 25%]). The proportion of participants meeting minimum wear criteria was higher when accelerometers were worn at the wrist (+ 14% [ 5%, 23%]) compared to waist. Daily wear-time tended to be higher in studies using wrist-worn accelerometers compared to other wear locations. Reporting of information regarding data collection was inconsistent. Conclusion: Methodological decisions including accelerometer wear-location and method of distribution may influence important data collection outcomes including recruitment and accelerometer wear-time. Consistent and comprehensive reporting of accelerometer data collection methods and outcomes is needed to support development of future studies and international consortia. Review supported by the British Heart Foundation (SP/F/20/150002) and registered (Prospero CRD42020213465). [ABSTRACT FROM AUTHOR]

Introduction: Physical activity is important for children's health and well-being. Supportiveness for physical activity of home and neighborhood environments may affect children's PA, but most studies are cross-sectional. We examined environmental predictors of change in children's physical activity over two years. Methods: Data were from the longitudinal, observational cohort study, 'Neighborhood Impact on Kids'. Participants were children (initially aged 6–12 years) and their parent/caregiver (n = 727 dyads) living in neighborhoods throughout San Diego County, California and King County (Seattle area), Washington, USA. Children's moderate-to-vigorous physical activity (MVPA) was measured using accelerometers at T1 (Time 1 or baseline, 2007–2009) and T2, the two-year follow-up. At T1, parents survey-reported on physical activity (PA) equipment at home and demographics. Neighborhood environment was measured using spatial data in Geographic Information Systems (intersection density; park availability) and in-person audits (informal play space near home; park-based PA facilities; land use; support for walking/cycling). Generalized additive mixed models estimated total effects, then direct effects, of environmental attributes on MVPA at T1. Two-way moderating effects of child's sex and age were examined at T1. To examine associations of environmental exposures with changes in MVPA, we estimated interaction effects of environmental attributes on the association between time and MVPA. Results: On average, children accumulated 146 min/day (standard deviation or SD = 53) of MVPA at T1, and 113 (SD = 58) min/day at T2. There were no significant total or direct effects of environmental attributes on MVPA at T1, and no significant two-way interaction effects of child's age and sex for T1 MVPA. Having informal play spaces proximal to home with more amenities was associated with less MVPA decline from T1 to T2. Higher residential density, higher land use mix, and higher number of PA facilities in nearby parks were unexpectedly associated with greater MVPA decline. Conclusion: Higher quality informal play spaces close to home may help offset declines in MVPA during middle childhood, as they may promote unstructured active play with opportunities for parental or neighbor surveillance. Unexpectedly, environmental factors consistent with higher walkability were associated with greater declines in children's MVPA. As physical activity differs across the lifespan, so may environmental factors that facilitate it. [ABSTRACT FROM AUTHOR]

A correction is presented to the article "Device-measured Movement Behaviours in Over 20,000 China Kadoorie Biobank Participants," which appeared in the 2023 issue of the magazine.

Background: This study aimed to examine associations of early childhood physical fitness and physical activity (PA) with PA during later childhood/early adolescence while accounting for gender differences. Methods: We selected data of N = 4329 children from the IDEFICS/I. Family cohort (age 2.4–11.7 years) with data on baseline fitness and accelerometer measurements. At baseline, physical fitness tests were conducted including Flamingo balance, Backsaver sit and reach, Handgrip strength, Standing Long Jump, 40-m sprint and 20-m Shuttle run (to estimate cardio-respiratory fitness levels). PA was measured with Actigraph accelerometers over 3 days at baseline (ActiTrainer or GT1M) and 7 days at follow-up (GT3X). Evenson cutpoints were used to determine moderate-to-vigorous PA (MVPA) time, and children with ≥60mins/day of average MVPA were deemed as having met WHO guidelines at baseline and follow-up. Linear and logistic regressions were performed to examine longitudinal associations between meeting WHO guidelines, MVPA, and physical fitness tests at baseline with meeting WHO guidelines and MVPA at follow-up. Models were conducted on the entire sample, the sex-stratified sample, and stratified by sex and pubertal status at follow-up. Results: Results showed that meeting WHO guidelines for MVPA at baseline was positively associated with MVPA (Standardized Beta (B) = 0.13, 95%CI:(5.6;11.1)) and meeting WHO guidelines at follow-up for the entire sample (OR = 2.1, 95%CI:(1.5; 3.14), and stratified by males (OR = 2.5, 95%CI:(1.5; 4.1)) and females (OR = 1.8, 95%CI:(1.0; 3.2)). This was also found for both male pre/early pubertal and pubertal groups but only in the female pre/early pubertal group, and not the female pubertal group (MVPA: B =.00, 95%CI:(− 6.1; 5.6), WHO: OR = 0.61, 95%CI:(0.23;1.6)). Models indicated that Standing Long jump, 40-m sprint, Shuttle run and Flamingo balance at baseline were associated with MVPA and meeting the guidelines at follow-up. Conclusions: Meeting WHO guidelines and certain fitness tests at baseline were strongly associated with MVPA and meeting WHO guidelines at follow-up, but this association varied with sex and pubertal status. Consequently, these findings underline the importance of ensuring sufficient physical activity in terms of quality and quantity for children at the earliest stages of life. Trial registration: ISRCTN62310987. [ABSTRACT FROM AUTHOR]

Background: Our understanding of the mechanisms through which physical activity might benefit lipoprotein metabolism is inadequate. Here we characterise the continuous associations between physical activity of different intensities, sedentary time, and a comprehensive lipoprotein particle profile. Methods: Our cohort included 762 fifth grade (mean [SD] age = 10.0 [0.3] y) Norwegian schoolchildren (49.6% girls) measured on two separate occasions across one school year. We used targeted proton nuclear magnetic resonance (1H NMR) spectroscopy to produce 57 lipoprotein measures from fasted blood serum samples. The children wore accelerometers for seven consecutive days to record time spent in light-, moderate-, and vigorous-intensity physical activity, and sedentary time. We used separate multivariable linear regression models to analyse associations between the device-measured activity variables—modelled both prospectively (baseline value) and as change scores (follow-up minus baseline value)—and each lipoprotein measure at follow-up. Results: Higher baseline levels of moderate-intensity and vigorous-intensity physical activity were associated with a favourable lipoprotein particle profile at follow-up. The strongest associations were with the larger subclasses of triglyceride-rich lipoproteins. Sedentary time was associated with an unfavourable lipoprotein particle profile, the pattern of associations being the inverse of those in the moderate-intensity and vigorous-intensity physical activity analyses. The associations with light-intensity physical activity were more modest; those of the change models were weak. Conclusion: We provide evidence of a prospective association between time spent active or sedentary and lipoprotein metabolism in schoolchildren. Change in activity levels across the school year is of limited influence in our young, healthy cohort. Trial registration: ClinicalTrials.gov, #NCT02132494. Registered 7th April 2014 [ABSTRACT FROM AUTHOR]

Background: During the 2020 UK COVID-19 lockdown restrictions, children spent almost all of their time at home, which had a significant influence on their physical activity (PA) and sedentary behaviour. This study aimed to: 1) determine changes to the social and physical environment at home and children's home-based sitting, PA, standing and sitting breaks as a result of the COVID-19 restrictions; and 2) examine associations between changes at home and children's movement behaviours. Methods: One hundred and two children had their PA and sitting, standing and sitting breaks at home objectively measured pre-COVID-19 and during the first COVID-19 lockdown (June-July 2020). Children's parents (n = 101) completed an audit of their home physical environment and a survey on the home social environment at both time points. Changes in the home physical and social environment and behavioural outcomes were assessed using Wilcoxon signed ranked tests, paired t-tests, or chi-square. Repeated linear regression analyses examined associations between changes in homes and changes in the home-based behavioural outcomes. Results: During COVID-19, households increased the amount of seated furniture and electronic media equipment at home. The number of books and PA equipment decreased and fewer parents enforced a screen-time rule. Children's preference for physical activities and socialising at home decreased. Time at home and sitting at home increased during COVID-19, whilst PA, standing and sitting breaks decreased. Both MVPA and TPA were positively associated with child preference for PA, and negatively associated with attending school. Sitting was negatively associated with child preference for PA and child preference for socialising at home. Media equipment was negatively associated with sitting breaks, whilst PA equipment was positively associated with standing. Conclusion: The COVID-19 restrictions forced children to spend almost all their time at home. Children's PA, standing, and sitting breaks at home declined during the restrictions, while sitting increased. Mostly negative changes occurred in homes, some of which impacted children's behaviours at home. To avoid the changes persisting post-lockdown, interventions are needed to reset and promote children's PA and discourage prolonged sitting time. [ABSTRACT FROM AUTHOR]

Background: The time that children spend in physical activity, sedentary behaviour, and sleep each day (i.e., 24-h time-use behaviours), is related to physical and mental health outcomes. Currently, there is no comprehensive evidence on New Zealand school-aged children's 24-h time-use behaviours, adherence to the New Zealand 24-h Movement Guidelines, and how these vary among different sociodemographic groups. Methods: This study utilises data from the 8-year wave of the Growing Up in New Zealand longitudinal study. Using two Axivity AX3 accelerometers, children's 24-h time-use behaviours were described from two perspectives: activity intensity and activity type. Compositional data analysis techniques were used to explore the differences in 24-h time-use compositions across various sociodemographic groups. Results: Children spent on average, 31.1%, 22.3%, 6.8%, and 39.8% of their time in sedentary, light physical activity, moderate-to-vigorous physical activity, and sleep, respectively. However, the daily distribution of time in different activity types was 33.2% sitting, 10.8% standing, 7.3% walking, 0.4% running, and 48.2% lying. Both the activity intensity and activity type compositions varied across groups of child ethnicity, gender, and household income or deprivation. The proportion of children meeting each of the guidelines was 90% for physical activity, 62.5% for sleep, 16% for screen time, and 10.6% for the combined guidelines. Both gender and residence location (i.e., urban vs. rural) were associated with meeting the physical activity guideline, whereas child ethnicity, mother's education and residence location were associated with meeting the screen time guideline. Child ethnicity and mother's education were also significantly associated with the adherence to the combined 24-h Movement Guidelines. Conclusions: This study provided comprehensive evidence on how New Zealand children engage in 24-h time-use behaviours, adherence to the New Zealand 24-h Movement Guidelines, and how these behaviours differ across key sociodemographic groups. These findings should be considered in designing future interventions for promoting healthy time-use patterns in New Zealand children. [ABSTRACT FROM AUTHOR]

Background: The e-coachER trial aimed to determine whether adding web-based behavioural support to exercise referral schemes (ERS) increased long-term device-measured physical activity (PA) for patients with chronic conditions, compared to ERS alone, within a randomised controlled trial. This study explores the mechanisms of action of the e-coachER intervention using measures of the behaviour change processes integral to the intervention's logic model. Methods: Four hundred fifty adults with obesity, diabetes, hypertension, osteoarthritis or history of depression referred to an ERS were recruited in Plymouth, Birmingham and Glasgow. The e-coachER intervention comprising 7-Steps to Health was aligned with Self-Determination Theory and mapped against evidence-based behaviour change techniques (BCTs). Participants completed questionnaires at 0, 4, and 12 months to assess PA and self-reported offline engagement with core BCTs in day-to-day life (including action planning and self-monitoring) and beliefs relating to PA (including perceived importance, confidence, competence, autonomy and support). We compared groups at 4 and 12 months, controlling for baseline measures and other covariates. Mediation analysis using the product of coefficients method was used to determine if changes in process variables mediated intervention effects on moderate to vigorous physical activity (MVPA) recorded by accelerometer and self-report at 4- and 12-months. Results: The internal reliability (Cronbach's alpha) for all multi-item scales was > 0.77. At 4-months, those randomised to e-coachER reported higher levels of PA beliefs relating to importance (1.01, 95% confidence interval (CI): 0.42 to 1.61, p = 0.001), confidence (1.28, 95% CI: 0.57 to 1.98, p < 0.001), competence (1.61, 95% CI:.68 to 2.54, p = 0.001), availability of support (0.77, 95% CI: 0.07 to 1.48, p = 0.031), use of action planning (1.54, 95% CI: 0.23 to 2.85, p = 0.021) and use of self-monitoring (0.76, 95% CI: 0.19 to 1.32, p = 0.009) compared to ERS alone. There were no intervention effects on autonomous beliefs or perceived frequency of support, compared to ERS alone. At the 12-month follow-up, participants belief in the importance of PA was the only process measure to remain significantly higher in the e-coachER group when compared to ERS alone (0.75, 95% CI: 0.05 to 1.45). Intervention effects on perceived importance (2.52, 95% CI: 0.45 to 5.39), action planning (1.56, 95% CI: 0.10 to 3.54) and self-monitoring (1.92, 95% CI: 0.21 to 4.33) at 4-months significantly mediated change in accelerometer measured MVPA at 12-months (recorded in ≥ 10-min bouts). Conclusions: e-coachER led to some short-term changes in most process outcomes. Some of these processes also appeared to mediate e-coachER effects on changes in accelerometer measured MVPA. Further work should be carried out to understand how best to design and implement theoretically underpinned web-based physical activity promotion interventions within ERS. Trial registration: ISRCTN, ISRCTN15644451. Registered 12 February 2015. [ABSTRACT FROM AUTHOR]

Background: TransformUs was a four-arm school-based intervention to increase physical activity and reduce sedentary behaviour among primary school children. Pedagogical and environmental strategies targeted the classroom, school grounds and family setting. The aims of this study were to evaluate program fidelity, dose, appropriateness, satisfaction and sustainability, and associations between implementation level and outcomes among the three intervention arms. Methods: At baseline, 18-months (mid-intervention) and 30-months (post-intervention), teachers, parents and children completed surveys, and children wore GT3X ActiGraph accelerometers for 8 days at each time point to determine physical activity and sedentary time. Implementation data were pooled across the three intervention groups and teachers were categorised by level of implementation: (i) 'Low' (< 33% delivered); (ii) 'Moderate' (33–67% delivered); and (iii) 'High' (> 67% delivered). Linear and logistic mixed models examined between group differences in implementation, and the association with children's physical activity and sedentary time outcomes. Qualitative survey data were analysed thematically. Results: Among intervention recipients, 52% (n = 85) of teachers, 29% (n = 331) of parents and 92% (n = 407) of children completed baseline evaluation surveys. At 18-months, teachers delivered on average 70% of the key messages, 65% set active/standing homework, 30% reported delivering > 1 standing lesson/day, and 56% delivered active breaks per day. The majority of teachers (96%) made activity/sports equipment available during recess and lunch, and also used this equipment in class (81%). Fidelity and dose of key messages and active homework reduced over time, whilst fidelity of standing lessons, active breaks and equipment use increased. TransformUs was deemed appropriate for the school setting and positively received. Implementation level and child behavioural outcomes were not associated. Integration of TransformUs into existing practices, children's enjoyment, and teachers' awareness of program benefits all facilitated delivery and sustainability. Conclusions: This study demonstrated that intervention dose and fidelity increased over time, and that children's enjoyment, senior school leadership and effective integration of interventions into school practices facilitated improved intervention delivery and sustainability. Teacher implementation level and child behavioural outcomes were unrelated, suggesting intervention efficacy was achieved irrespective of implementation variability. The potential translatability of TransformUs into practice contexts may therefore be increased. Findings have informed scale-up of TransformUs across Victoria, Australia. Trial registration: International Standard Randomized Controlled Trial Number ISRCTN83725066; Australian New Zealand Clinical Trials Registry Number ACTRN12609000715279. Registered 19 August 2009. Available at: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=308387&isReview=true [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Accurate accelerometer-based methods are required for assessment of 24-h physical behavior in young children. We aimed to summarize evidence on measurement properties of accelerometer-based methods for assessing 24-h physical behavior in young children. Methods: We searched PubMed (MEDLINE) up to June 2021 for studies evaluating reliability or validity of accelerometer-based methods for assessing physical activity (PA), sedentary behavior (SB), or sleep in 0–5-year-olds. Studies using a subjective comparison measure or an accelerometer-based device that did not directly output time series data were excluded. We developed a Checklist for Assessing the Methodological Quality of studies using Accelerometer-based Methods (CAMQAM) inspired by COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN). Results: Sixty-two studies were included, examining conventional cut-point-based methods or multi-parameter methods. For infants (0—12 months), several multi-parameter methods proved valid for classifying SB and PA. From three months of age, methods were valid for identifying sleep. In toddlers (1—3 years), cut-points appeared valid for distinguishing SB and light PA (LPA) from moderate-to-vigorous PA (MVPA). One multi-parameter method distinguished toddler specific SB. For sleep, no studies were found in toddlers. In preschoolers (3—5 years), valid hip and wrist cut-points for assessing SB, LPA, MVPA, and wrist cut-points for sleep were identified. Several multi-parameter methods proved valid for identifying SB, LPA, and MVPA, and sleep. Despite promising results of multi-parameter methods, few models were open-source. While most studies used a single device or axis to measure physical behavior, more promising results were found when combining data derived from different sensor placements or multiple axes. Conclusions: Up to age three, valid cut-points to assess 24-h physical behavior were lacking, while multi-parameter methods proved valid for distinguishing some waking behaviors. For preschoolers, valid cut-points and algorithms were identified for all physical behaviors. Overall, we recommend more high-quality studies evaluating 24-h accelerometer data from multiple sensor placements and axes for physical behavior assessment. Standardized protocols focusing on including well-defined physical behaviors in different settings representative for children's developmental stage are required. Using our CAMQAM checklist may further improve methodological study quality. PROSPERO Registration number: CRD42020184751. [ABSTRACT FROM AUTHOR]

Background: Many children do not engage in sufficient physical activity, and schools provide a unique venue for children to reach their recommended 60 daily minutes of moderate-to-vigorous physical activity (MVPA). Prior research examining effects of MVPA on academic achievement is inconclusive, and few studies have investigated potential moderators of this relationship. This study examined whether student-level characteristics (gender, race/ethnicity, free/reduced-price lunch status) and school-level characteristics (proportion of students qualifying for free/reduced-price lunch, physical activity environment and opportunities) moderate the relationship between MVPA and academic achievement. Methods: In a large, diverse metropolitan public school district in Georgia, 4,936 students in Grade 4 were recruited from 40 elementary schools. Students wore accelerometers to measure school-day MVPA for a total of 15 days across three semesters (fall 2018, spring 2019, fall 2019). Academic achievement data, including course marks (grades) for math, reading, spelling, and standardized test scores in writing, math, reading, and Lexile (reading assessment), were collected at baseline (Grade 3, ages 8–9) and at follow-up in Grade 4 (ages 9–10). Standardized test scores were not measured in Grade 5 (ages 10–11) due to COVID-19-related disruptions. Multilevel modeling assessed whether student-level and/or school-level characteristics were moderators in the cross-sectional and longitudinal MVPA-academic achievement relationship. Results: Cross sectional analyses indicated that the MVPA and AA relationship was moderated only by student Hispanic ethnicity for Grade 4 fall spelling marks (β = -0.159 p < 0.001). The relationship for Grade 4 fall spelling marks was also moderated by school physical activity opportunities (β = -0.128 (p < 0.001). Longitudinally, there was no significant moderation of the MVPA-academic achievement. A relationship by student gender, free/reduced-price lunch status, race/ethnicity; nor for school-level factors including proportion of students qualifying for free/reduced-price lunch, physical activity environment, and physical activity opportunities. Conclusions: Overall, our results did not suggest that student- or school-level characteristics moderate the MVPA-academic achievement relationship. While statistically significant results were observed for certain outcomes, practical differences were negligible. In this population, school-based MVPA does not appear to differently affect academic performance based on student gender, race/ethnicity, free/reduced-price lunch, nor school characteristics. Trial registration: This study was registered with the National Institutes of Health (NIH) ClinicalTrials.gov system, with ID NCT03765047. Registered 05 December 2018—Retrospectively registered. [ABSTRACT FROM AUTHOR]

Background: Hip-worn accelerometer cut-points have poor validity for assessing children's sedentary time, which may partly explain the equivocal health associations shown in prior research. Improved processing/classification methods for these monitors would enrich the evidence base and inform the development of more effective public health guidelines. The present study aimed to develop and evaluate a novel computational method (CHAP-child) for classifying sedentary time from hip-worn accelerometer data. Methods: Participants were 278, 8–11-year-olds recruited from nine primary schools in Melbourne, Australia with differing socioeconomic status. Participants concurrently wore a thigh-worn activPAL (ground truth) and hip-worn ActiGraph (test measure) during up to 4 seasonal assessment periods, each lasting up to 8 days. activPAL data were used to train and evaluate the CHAP-child deep learning model to classify each 10-s epoch of raw ActiGraph acceleration data as sitting or non-sitting, creating comparable information from the two monitors. CHAP-child was evaluated alongside the current practice 100 counts per minute (cpm) method for hip-worn ActiGraph monitors. Performance was tested for each 10-s epoch and for participant-season level sedentary time and bout variables (e.g., mean bout duration). Results: Across participant-seasons, CHAP-child correctly classified each epoch as sitting or non-sitting relative to activPAL, with mean balanced accuracy of 87.6% (SD = 5.3%). Sit-to-stand transitions were correctly classified with mean sensitivity of 76.3% (SD = 8.3). For most participant-season level variables, CHAP-child estimates were within ± 11% (mean absolute percent error [MAPE]) of activPAL, and correlations between CHAP-child and activPAL were generally very large (> 0.80). For the current practice 100 cpm method, most MAPEs were greater than ± 30% and most correlations were small or moderate (≤ 0.60) relative to activPAL. Conclusions: There was strong support for the concurrent validity of the CHAP-child classification method, which allows researchers to derive activPAL-equivalent measures of sedentary time, sit-to-stand transitions, and sedentary bout patterns from hip-worn triaxial ActiGraph data. Applying CHAP-child to existing datasets may provide greater insights into the potential impacts and influences of sedentary time in children. [ABSTRACT FROM AUTHOR]

Background: Latina women are less likely to report engaging in leisure-time physical activity (PA) than non-Latina white women. This study evaluated the 24-month impact of a faith-based PA intervention targeting Latinas. Methods: The study is a cluster randomized controlled trial of a PA intervention or cancer screening comparison condition, with churches as the randomization unit. A total of 436 Latinas (aged 18-65 years) from 16 churches who engaged in low levels of self-report and accelerometer-based PA were enrolled. The experimental condition was a 24-month PA intervention, with in-person classes, social support, and environmental changes, led by community health workers (i.e., promotoras). At baseline, 12-, and 24 months, we assessed changes in accelerometer-based and self-reported moderate to vigorous physical activity (MVPA; primary outcomes). Secondary outcomes were light intensity activity, sedentary time, body mass index (BMI), and waist circumference. Results: After adjusting for sociodemographic factors, a mixed effects analysis found significant increases in self-reported leisure time MVPA (p < 0.005) and marginal increases in accelerometer-assessed MVPA (p < 0.08) 24 months post-baseline in the intervention compared to the attention-control condition. Data showed significant associations between PA class attendance and engaging in MVPA as assessed by self-report and accelerometry. No significant changes were found for light activity, sedentary time, BMI, or waist circumference. Conclusions: Participants who attended the PA classes at least once a month engaged in significantly higher MVPA compared to those who did not. Maximizing engagement and maintenance strategies to enhance PA maintenance could contribute to important long-term health benefits. Trial registration: NCT01776632, Registered March 18, 2011. [ABSTRACT FROM AUTHOR]

Background: The number of individuals recovering from severe COVID-19 is increasing rapidly. However, little is known about physical behaviours that make up the 24-h cycle within these individuals. This study aimed to describe physical behaviours following hospital admission for COVID-19 at eight months post-discharge including associations with acute illness severity and ongoing symptoms. Methods: One thousand seventy-seven patients with COVID-19 discharged from hospital between March and November 2020 were recruited. Using a 14-day wear protocol, wrist-worn accelerometers were sent to participants after a five-month follow-up assessment. Acute illness severity was assessed by the WHO clinical progression scale, and the severity of ongoing symptoms was assessed using four previously reported data-driven clinical recovery clusters. Two existing control populations of office workers and individuals with type 2 diabetes were comparators. Results: Valid accelerometer data from 253 women and 462 men were included. Women engaged in a mean ± SD of 14.9 ± 14.7 min/day of moderate-to-vigorous physical activity (MVPA), with 12.1 ± 1.7 h/day spent inactive and 7.2 ± 1.1 h/day asleep. The values for men were 21.0 ± 22.3 and 12.6 ± 1.7 h /day and 6.9 ± 1.1 h/day, respectively. Over 60% of women and men did not have any days containing a 30-min bout of MVPA. Variability in sleep timing was approximately 2 h in men and women. More severe acute illness was associated with lower total activity and MVPA in recovery. The very severe recovery cluster was associated with fewer days/week containing continuous bouts of MVPA, longer total sleep time, and higher variability in sleep timing. Patients post-hospitalisation with COVID-19 had lower levels of physical activity, greater sleep variability, and lower sleep efficiency than a similarly aged cohort of office workers or those with type 2 diabetes. Conclusions: Those recovering from a hospital admission for COVID-19 have low levels of physical activity and disrupted patterns of sleep several months after discharge. Our comparative cohorts indicate that the long-term impact of COVID-19 on physical behaviours is significant. [ABSTRACT FROM AUTHOR]

Background: This study examined the strength, shape and direction of associations of accelerometer-assessed overall, school- and non-school-based moderate-to-vigorous physical activity (MVPA) and sedentary time (ST) with BMI among adolescents across the world. Second, we examined whether these associations differed by study site and sex. Methods: Cross-sectional data from the IPEN Adolescent study, an observational multi-country study, were used. Participants wore an accelerometer for seven days, reported height and weight, and completed a socio-demographic survey. In total, 4852 adolescents (46.6% boys), aged 11–19 years (mean age = 14.6, SD = 1.7 years) were included in the analyses, using generalized additive mixed models. Results: Adolescents accumulated on average 41.3 (SD = 22.6) min/day of MVPA and 531.8 (SD = 81.1) min/day of ST, and the prevalence of overweight and obesity was 17.2% (IOTF), but these mean values differed by country. Linear negative associations of accelerometer-based MVPA and ST with standardized BMI scores and the likelihood of being overweight/obese were found. School-based ST and non-school-based MVPA were more strongly negatively associated to the outcomes than non-school based ST and school-based MVPA. Study site moderated the associations; adolescent sex did not. No curvilinear associations were found. Conclusions: This multi-country study confirmed the importance of MVPA as a potential protective factor against overweight/obesity in adolescents. Non-school-based MVPA seemed to be the main driver of these associations. Unexpected results were found for ST, calling for further examination in methodologically sound international studies but using inclinometers or pressure sensors to provide more precise ST measures. [ABSTRACT FROM AUTHOR]

Background: In the current Physical Activity Guidelines (PAG) for moderate- and vigorous-intensity physical activity (MVPA), abrupt transition from ≥ 60 min/day [youth PAG] to ≥ 150 min/week (≥ 22 min/day on average) [adult PAG] during emerging adulthood is poorly justified. The aim of this study was to examine body fat mass changes according to whether meeting the youth and adult PAGs in late adolescence (age 18 years) to early adulthood (age 22 years). Methods: The study sample included 2,099 participants (1,113 females) from the 1993 Pelotas (Brazil) Study. At ages 18 and 22 years, MVPA was measured using wrist-worn accelerometry and fat mass was measured using dual-energy X-ray absorptiometry. MVPA at age 18 was categorized into two groups: 0–59 or ≥ 60 min/day (no [N] or yes [Y] for meeting the youth recommendation, respectively). MVPA at age 22 was categorized into three groups: 0–21, 22–59, or ≥ 60 min/day (N, Y22, or Y60 for not meeting the adult recommendation, meeting the adult recommendation, or meeting the youth recommendation, respectively). The combination of these groups created six MVPA groups (N&N, N&Y22, N&Y60, Y&N, Y&Y22, and Y&Y60). Sex-specific multivariable linear regression analyses were conducted to estimate change in fat mass index (FMI) from age 18 to 22 years in the six MVPA groups. Results: Among males, compared to Y&Y60 (FMI increase = 1.2 kg/m2 [95% CI = 1.0, 1.4]), Y&Y22 and Y&N had larger FMI increases (1.9 [1.6, 2.1] and 1.9 [1.2, 2.5], respectively). Among females, Y&Y60 and Y&Y22 had an equal FMI increase (1.6 [1.4, 1.9] for both groups), while Y&N had a larger FMI increase (2.4 [1.8, 3.0]). Conclusions: These findings suggest that among those who were active in late adolescence, engaging in ≥ 22 min/day of MVPA in adulthood is associated with lower body fat gain for females, but not for males. [ABSTRACT FROM AUTHOR]

Background: It is unknown if and how children's movement behaviour accumulation patterns change as a result of physical activity and/or sedentary behaviour interventions. It is important to establish the effectiveness of interventions targeting changes in such accumulation patterns. This study aimed to investigate the effect of the Transform-Us! school- and home-based intervention program on children's movement behaviour accumulation patterns, focusing on sporadic accumulation versus time in bouts. Methods: Baseline and post-intervention (18 months) accelerometer data from the Transform-Us! 2 × 2 factorial design cluster randomised controlled trial was used (Melbourne, 2010–2012; analytical sample n = 267; aged 8–9 years). Linear mixed models were fitted to examine effects of three different interventions (targeting increases in physical activity [PA-I], reductions in sedentary time [SB-I], or both [PA + SB-I]) compared to a usual practice (control) group on post-intervention movement behaviour accumulation compositions with eight components, including sporadic time and bouts of sedentary time, and light-, moderate- and vigorous-intensity physical activity. Results: Intervention effects on distribution of time in the post-intervention waking movement behaviour accumulation composition (adjusted for baseline composition) were small and not significant. However, visual inspection of the change in compositions over time revealed that only groups with a sedentary behaviour intervention component (SB-I and PA + SB-I) reduced time in sedentary bouts, compared to the overall sample compositional mean. In addition, the SB-I group was the only group with an increase in vigorous-intensity physical activity. The combined intervention group (PA + SB-I) was characterized by the largest proportional increase in MPA bouts. The usual practice group was characterized by the largest proportional increases in both sporadic and bouts of sedentary time. Conclusions: This study showed some early evidence to suggest that the "break up your sitting" message may result in greater impact than the "move more" message. Future research, including larger sample sizes, should investigate if this type of messaging is indeed more effective in changing movement behaviours and ultimately child health. Trial registration: International Standard Randomized Controlled Trial Number ISRCTN83725066; Australian New Zealand Clinical Trials Registry Number ACTRN12609000715279. [ABSTRACT FROM AUTHOR]

Background: Built and social environments are associated with physical activity. Global Positioning Systems (GPS) and accelerometer data can capture how people move through their environments and provide promising tools to better understand associations between environmental characteristics and physical activity. The purpose of this study is to examine the associations between GPS-derived exposure to built environment and gentrification characteristics and accelerometer-measured physical activity in a sample of adults across four cities. Methods: We used wave 1 data from the Interventions, Research, and Action in Cities Team, a cohort of adults living in the Canadian cities of Victoria, Vancouver, Saskatoon, and Montreal. A subsample of participants wore a SenseDoc device for 10 days during May 2017–January 2019 to record GPS and accelerometry data. Two physical activity outcomes were derived from SenseDoc data: time spent in light, moderate, and vigorous physical activity; and time spent in moderate or vigorous physical activity. Using corresponding GPS coordinates, we summarized physical activity outcomes by dissemination area—a Canadian census geography that represents areas where 400 to 700 people live- and joined to built (active living space, proximity to amenities, and urban compactness) and gentrification measures. We examined the associations between environmental measures and physical activity outcomes using multi-level negative binomial regression models that were stratified by city and adjusted for covariates (weekday/weekend), home dissemination area, precipitation, temperature) and participant-level characteristics obtained from a survey (age, gender, income, race). Results: We found that adults spent more time being physically active near their homes, and in environments that were more walkable and near parks and less time in urban compact areas, regardless of where participants lived. Our analysis also highlighted how proximity to different amenities was linked to physical activity across different cities. Conclusions: Our study provides insights into how built environment and gentrification characteristics are associated with the amount of time adults spend being physically active in four Canadian cities. These findings enhance our understanding of the influence that environments have on physical activity over time and space, and can support policies to increase physical activity. [ABSTRACT FROM AUTHOR]

Background: Most available evidence on the effects of the COVID-19 pandemic on child movement behaviors is from cross-sectional studies using self-report measures. This study aimed to identify change trajectories and their associated factors for objectively-assessed physical activity and sedentary time among an ethnically and socioeconomically diverse sample of school-age children from Central Texas, U.S.A., during COVID-19. Methods: Pre- (Sept. 2019 – Feb. 2020) and during- (Oct. 2020 – March 2021) COVID-19 physical activity and sedentary behavior data were collected for school-age children (8–11 years) enrolled in the Safe Travel Environment Evaluation in Texas Schools (STREETS) cohort study. Daily time spent in moderate- to vigorous-intensity physical activity (MVPA) and sedentary time were assessed using GT3X-wBT Actigraph accelerometers. Parent surveys were used to assess socio-ecological factors. Latent class linear mixed models were used to identify change trajectories of MVPA and sedentary time. Logistic regression models were used to assess the association between socio-ecological characteristics with physical activity and sedentary time change trajectory groups. Results: There was a significant decrease in mean daily MVPA (− 9.4 mins, SD = 18.54) and an increase in sedentary behavior (0.83 hrs, SD = 1.18). Two trajectory groups were identified for MVPA ('decrease MPVA' and 'maintain high MVPA'), with the majority (82.1%) being in the 'decrease MVPA' group. Three trajectory groups were identified for sedentary behavior ('moderate increase sedentary, 'steep increase sedentary,' and 'decrease sedentary'), with most children (78.5%) being in the 'moderate increase' group. Girls had significantly lower odds of being in the 'maintain high MVPA' group than boys (OR = 0.27, 95% CI = 0.11, 0.61). Children living in neighborhoods with higher perceived social cohesion had significantly higher odds of being in the 'maintain high MVPA' group (OR = 1.22, 95% CI = 1.06, 1.41), while those in neighborhoods with higher social cohesion had lower odds of being in the 'decrease sedentary' group (OR = 0.86, 95% CI = 0.74, 0.99). Conclusions: Declines in physical activity and increases in sedentary time among most school-age children during COVID-19 in a socioeconomically and ethnically diverse U.S. sample, were observed in our study, especially among girls. These findings highlight the need to counteract the short-term negative changes in movement behaviors in response to COVID-19 among children. [ABSTRACT FROM AUTHOR]

Background: Restrictions due to the coronavirus disease 2019 (COVID-19) pandemic reduced physical activity provision for both children and their parents. Recent studies have reported decreases in physical activity levels during lockdown restrictions, but these were largely reliant on self-report methods, with data collected via unrepresentative self-report surveys. The post-pandemic impacts on children's activity levels remain unknown. A key question is how active children become once lockdown restrictions are lifted. Methods: Active-6 is a repeated cross-sectional natural experiment. Accelerometer data from 1296 children aged 10–11 and their parents were collected in 50 schools in the Greater Bristol area, UK in March 2017-May 2018 (pre-COVID-19 comparator group), and compared to 393 children aged 10–11 and parents in 23 of the same schools, collected in May-December 2021. Mean minutes of accelerometer-measured moderate-to-vigorous physical activity (MVPA) were derived for weekdays and weekend and compared pre- and post-lockdown via linear multilevel models. Results: After adjusting for seasonality, accelerometer wear time and child/parent demographics, children's mean weekday and weekend MVPA were 7.7 min (95% CI: 3.5 to 11.9) and 6.9 min (95% CI: 0.9 to 12.9) lower in 2021 than in 2018, respectively, while sedentary time was higher by 25.4 min (95% CI: 15.8 to 35.0) and 14.0 min (95% CI: 1.5 to 26.5). There was no evidence that differences varied by child gender or household education. There was no significant difference in parents' MVPA or sedentary time, either on weekdays or weekends. Conclusions: Children's MVPA was lower by 7–8 min/day in 2021 once restrictions were lifted than before the pandemic for all groups, on both weekdays and weekends. Previous research has shown that there is an undesirable age-related decline in children's physical activity. The 8-min difference reported here would be broadly comparable to the decline that would have previously been expected to occur over a three-year period. Parents' physical activity was similar to pre-pandemic levels. Our results suggest that despite easing of restrictions, children's activity levels have not returned to pre-pandemic levels. There is an urgent need to understand why these changes have occurred and how long they are maintained. [ABSTRACT FROM AUTHOR]

Background: We compared the relation between neighborhood features and moderate to vigorous physical activity (MVPA) using linear regression analysis and the more novel compositional data analysis (CoDA). Compositional data analysis allows us to take the time children allocate to different movement behaviours during a 24-hour time period into account. Methodology: Data from youth participants (n = 409) in the QUALITY (QUebec Adipose and Lifestyle InvesTigation in Youth) cohort were included. Time spent in MVPA, light physical activity, sedentary behavior, and sleep ("24-hour movement behaviours") was measured using accelerometers. Neighborhood data were collected using a geographic information system and through direct observation. In CoDA models, we used orthogonal logratio coordinates, which allows for the association of neighbourhood walkability with MVPA to be estimated with respect to the average composition of all other behaviours within a 24-hour time frame. In baseline linear regression models, MVPA was regressed cross-sectionally on neighborhood walkability. All models were stratified by sex, and controlled for BMI z-scores, pubertal development, seasonal variation, parental education, and neighbourhood safety. Results: Based on CoDA, girls who lived in more walkable neighborhoods had 10% higher daily MVPA (95% CI: 2%, 19%), taking into account all other movement behaviours. Based on linear regression, girls who resided in more walkable neighborhoods engaged in 4.2 (95% confidence interval [CI]: 1.2, 6.6) more minutes of MVPA per day on average than girls residing in less walkable neighborhoods. Conclusions: Unlike with traditional linear models, all movement behaviours were included in a single model using CoDA, allowing for a more complete picture of the strength and direction of the association between neighbourhood Walkability and MVPA. Application of CoDA to investigate determinants of physical activity provides additional insight into potential mechanisms and the ways in which people allocate their time. [ABSTRACT FROM AUTHOR]

Background: Childcare settings are important environments for influencing child eating and physical activity (PA). Family childcare homes (FCCH) care for many children of low-income and diverse racial/ethnic backgrounds who are at greater risk for poor diet quality, low PA, and obesity, but few interventions have targeted this setting. The aim of this study was to assess the efficacy of a multicomponent intervention conducted in FCCH on the diet quality and PA of 2–5 year old children in their care. Trial design: Cluster randomized trial. Methods: The cluster-randomized trial, Healthy Start/Comienzos Sanos (2015–2019) evaluated an 8-month nutrition and PA intervention that included four components: (1) monthly telephone calls from a support coach using brief motivational interviewing, (2) tailored reports, newsletters and videos, (3) group support meetings, and (4) active play toys. After completing baseline measurement, FCCH were randomized into intervention or comparison groups in matched pairs. Both groups received the same intervention components but on different topics (intervention: nutrition/PA vs. comparison: reading readiness/literacy). Evaluation staff were blinded to group assignment. Child primary outcome measures collected at baseline and 8-months included: 1) Healthy Eating Index (HEI-2015) scores calculated from diet observation, and 2) accelerometer measurement of PA. Process measures were collected from field data and provider surveys. Generalized Estimating Equation Models assessed changes in HEI-2015 scores and PA over time by experimental condition. Results: Ethnically diverse FCCH providers (n = 119) and 2-to-5-year-old children in their care (n = 377) were included in the final analysis. Process evaluation showed high participation in all intervention components except for group meetings. Compared to children in comparison group FCCH, children in intervention FCCH increased total HEI-2015 scores by 7.2 points (p <.001) including improvement in component scores for vegetables (0.84 points, p =.025) and added sugar (0.94 points, p =.025). For PA, compared to children in the comparison group, children in intervention FCCH decreased sedentary time by 5.7% (p =.021). Conclusions: The multicomponent Healthy Start intervention was effective in improving diet quality and sedentary behavior of children in FCCH, which demonstrates the promise of obesity prevention interventions in this setting. Future research could include enhancing the Healthy Start intervention to strengthen the PA component, considering virtual peer support, and determining how to best translate and disseminate the intervention into FCCH nationally. Trial registration: National Institutes of Health, NCT02452645. Registered 5 May 2015. [ABSTRACT FROM AUTHOR]

Background: Physical activity (PA) declines during childhood. Important sources of PA are active travel, organised sport and physical education (PE), but it is unclear how these domain-specific PA sources contribute to (changes in) daily moderate-to-vigorous PA (MVPA) in young people. This study aimed to examine (1) the cross-sectional association between domain-specific physical activity (i.e., active travel, organised sport and PE) and daily minutes in accelerometer-assessed MVPA; and (2) the longitudinal association between domain-specific physical activity at baseline and change in daily minutes in MVPA. Methods: Participants (baseline age 11.3 ±.1.2 years) were drawn from three studies in the International Children's Accelerometry Database. The contribution of self-reported standardised active travel, organised sport and PE to accelerometer-measured daily minutes in MVPA was examined using linear regression. In cross-sectional analyses, MVPA was regressed on each PA domain in separate models, adjusted for study, age, sex, maternal education, season, and monitor wear time. In longitudinal analyses, change in MVPA was regressed on each of the baseline PA domains, additionally adjusting for changes in season and wear time, follow-up duration, and baseline MVPA. R-squared was used to compare variance explained by each PA domain. Results: In the cross-sectional analyses (n = 3871), organised sport (standardised β = 3.81, 95% confidence interval [95%CI] = 3.06, 4.56) and active travel (β = 3.46, 95%CI = 2.73, 4.19) contributed more to daily MVPA than PE (β = 0.82, 95%CI = -0.02, 1.66). Compared to the base model which included only covariates (R2 = 21.5%), organised sport (absolute change: + 1.9%) and active travel (+ 1.7%) models explained more of the variance than the PE model (± < 0.1%). Associations followed a similar pattern in the longitudinal analyses (n = 2302), but none of the PA domains predicted change in MVPA (organised sport: standardised β = 0.85, 95%CI = -0.03, 1.72; active travel: β = 0.68, 95%CI = -0.14, 1.50; PE: β = 0.02, 95%CI = -0.87, 0.91). Conclusions: A multi-sectoral approach covering a wide range of PA domains should be promoted to minimise the age-related decline in MVPA during childhood. [ABSTRACT FROM AUTHOR]

Accelerometers measure the acceleration of the body part they are attached and allow to estimate time spent in activity levels (sedentary behaviour, light, and moderate-to-vigorous physical activity) and sleep over a 24-h period for several consecutive days. These advantages come with the challenges to analyse the large amount of data while integrating dimensions of both physical activity/sedentary behaviour and sleep domains. This commentary raises the questions of 1) how to classify sleep breaks (i.e. wake after sleep onset) during the night within the 24-h movement behaviour framework and 2) how to assess their impact on health while also accounting for night time sleep duration and time in sedentary behaviour and physical activity during the day. The authors advocate for future collaborations between researchers from the physical activity/sedentary behaviour and sleep research fields to ensure appropriate analysis and interpretation of the tremendous amount of data recorded by the newer generation accelerometers. This is the only way forward to provide meaningfully accurate evidence to inform future 24-h movement behaviour guidelines. [ABSTRACT FROM AUTHOR]

Background: Moderate-to-vigorous intensity physical activity (MVPA) is associated with favorable self-rated mental and physical health. Conversely, poor self-rated health in these domains could precede unfavorable shifts in activity. We evaluated bidirectional associations of accelerometer-estimated time spent in stationary behavior (SB), light intensity physical activity (LPA), and MVPA with self-rated health over 10 years in in the CARDIA longitudinal cohort study. Methods: Participants (n = 894, age: 45.1 ± 3.5; 63% female; 38% black) with valid accelerometry wear and self-rated health at baseline (2005–6) and 10-year follow-up (2015–6) were included. Accelerometry data were harmonized between exams and measured mean total activity and duration (min/day) in SB, LPA, and MVPA; duration (min/day) in long-bout and short-bout SB (≥30 min vs. < 30 min) and MVPA (≥10 min vs. < 10 min) were also quantified. The Short-Form 12 Questionnaire measured both a mental component score (MCS) and physical component score (PCS) of self-rated health (points). Multivariable linear regression associated baseline accelerometry variables with 10-year changes in MCS and PCS. Similar models associated baseline MCS and PCS with 10-year changes in accelerometry measures. Results: Over 10-years, average (SD) MCS increased 1.05 (9.07) points, PCS decreased by 1.54 (7.30) points, and activity shifted toward greater SB and less mean total activity, LPA, and MVPA (all p < 0.001). Only baseline short-bout MVPA was associated with greater 10-year increases in MCS (+ 0.92 points, p = 0.021), while baseline mean total activity, MVPA, and long-bout MVPA were associated with greater 10-year changes in PCS (+ 0.53 to + 1.47 points, all p < 0.005). In the reverse direction, higher baseline MCS and PCS were associated with favorable 10-year changes in mean total activity (+ 9.75 cpm, p = 0.040, and + 15.66 cpm, p < 0.001, respectively) and other accelerometry measures; for example, higher baseline MCS was associated with − 13.57 min/day of long-bout SB (p < 0.001) and higher baseline PCS was associated with + 2.83 min/day of MVPA (p < 0.001) in fully adjusted models. Conclusions: The presence of bidirectional associations between SB and activity with self-rated health suggests that individuals with low overall activity levels and poor self-rated health are at high risk for further declines and supports intervention programming that aims to dually increase activity levels and improve self-rated health. [ABSTRACT FROM AUTHOR]

Background: Reliable estimates of habitual sleep, physical activity, and sedentary time are essential to investigate the associations between these behaviours and health outcomes. While the number of days needed and hours/day for estimates of physical activity and sedentary time are generally known, the criteria for sleep estimates are more uncertain. The objective of this study was to identify the number of nights needed to obtain reliable estimates of habitual sleep behaviour using the GENEActiv wrist worn accelerometer. The number of days to obtain reliable estimate of physical activity was also examined. Methods: Data was used from a two-year longitudinal study. Children wore an accelerometer for up to 8 days 24 h/day across three timepoints. The sample included 2,745 children (51 % girls) between the ages of 7-12-years-old (mean = 9.8 years, SD = 1.1 year) with valid accelerometer data from any timepoint. Reliability estimates were calculated for sleep duration, sleep efficiency, sleep onset, wake time, time in bed, light physical activity, moderate physical activity, moderate-to-vigorous physical activity, vigorous physical activity, and sedentary time. Results: Intraclass correlations and the Spearman Brown prophecy formula were used to determine the nights and days needed for reliable estimates. We found that between 3 and 5 nights were needed to achieve acceptable reliability (ICC = 0.7) in sleep outcomes, while physical activity and sedentary time outcomes required between 3 and 4 days. Conclusions: To obtain reliable estimates, researchers should consider these minimum criteria when designing their studies and prepare strategies to ensure sufficient wear time compliance. [ABSTRACT FROM AUTHOR]