Device-measured Physical Activity Research Articles

Associations Between Intersecting Sociodemographic Characteristics and Device-Measured Physical Activity Among Children and Adolescents Living in the United States.

Despite robust evidence demonstrating sociodemographic characteristics may underly some of the disparities in physical activity observed among children and adolescents, the often-overlooked nexus of potential interactions between these characteristics warrants further exploration. This study explored the intersectionality of gender, race/ethnicity, parental education, and household income in relation to device-measured physical activity volume and intensity in a nationally representative sample of US children and adolescents. Cross-sectional data from 3 cycles of the US National Health and Nutrition Survey (2011-2012; 2012 National Youth Fitness Survey; and 2013-2014) were used. A total of 6116 participants (49% female) between 3 and 17years of age wore an accelerometer on their nondominant wrist for 7days. Monitor-independent movement summary units were used to represent physical activity volume and intensity. A Social Jeopardy Index was created to represent increasing levels of intersecting social disadvantages based on combinations of gender, race/ethnicity, parental education, and household income-to-poverty ratio tertiles. Generalized linear regression models were computed. The results showed social disadvantages become increasingly evident among children and adolescents during the most intense 60minutes of daily physical activity (B = -48.69 [9.94] SE, P < .001), but disparities in total volume were not observed (B = 34.01 [44.96] SE, P = .45). Findings suggest that patterns of physical activity behavior may differ based on intersecting sociodemographic characteristics-more socially disadvantaged children and adolescents appear to accumulate activity at lighter intensities. Collecting contextual information about device-measured physical activity represents an important next step for gaining insight into these sociodemographic differences.

Changes in physical activity and sleep following the COVID-19 pandemic on a university campus: Perception versus reality

It has been hypothesized that key lifestyle behaviors of physical activity and sleep worsened in response to the Coronavirus disease (COVID-19) pandemic. However, there have been inconsistencies in findings of changes in these key lifestyle behaviors across populations likely due to the wide variety of assessment methods. The purpose of the study was to compare physical activity and sleep before and after the COVID-19 pandemic using accelerometers and self-reported behaviors. A longitudinal follow-up was conducted on students, faculty, and staff at a university campus in the United States. In the periods before March 2020 (covering the academic years of 2018–2019 or 2019–2020) and again in April–June 2021, participants completed surveys to evaluate their physical activity and sleep behaviors and wore an accelerometer. A total of 44 participants completed the survey at both timepoints and 32 completed accelerometer assessment at both timepoints. Fifty-seven percent of participants reported a perceived decline in physical activity, while 30% reported a worsening in sleep. From self-reported data, overall physical activity did not change, but there was a decrease in active transport (p ​< ​0.001) and increase in domestic physical activity (p ​= ​0.012). Sleep quality decreased as evidenced by an increase in Pittsburgh Sleep Quality Index scores (p ​= ​0.045). There were no changes in accelerometer measured physical activity or sleep. There were no changes in physical or mental health. While perceptions of physical activity declined from prior to the COVID-19 pandemic, there were no changes in device-measured physical activity, and changes in self-reported physical activity differed by domain.

Effect of a coaching intervention to enhance physical activity and prevent falls in community-dwelling people aged 60+ years: a cluster randomised controlled trial

ObjectivesTo evaluate the effect of a coaching intervention compared with control on physical activity and falls rate at 12 months in community-dwelling people aged 60+ years.DesignCluster randomised controlled trial.SettingCommunity-dwelling older...

Joint Associations of Diet and Device-Measured Physical Activity with Mortality and Incident CVD and Cancer: A Prospective Analysis of the UK Biobank Study.

We examined the joint associations of diet and device-measured intensity-specific physical activity (PA) with all-cause mortality (ACM), cardiovascular disease (CVD), and cancer incidence. We used data from 79,988 participants from the UK Biobank, a population-based prospective cohort study. Light PA (LPA), moderate-to-vigorous PA (MVPA), vigorous PA (VPA), and total PA (TPA) were measured using a wrist-worn accelerometer. Diet quality score (DQS) was based on 10 foods and ranged from 0 (unhealthiest) to 100 (healthiest) points. We derived joint PA and diet variables. Outcomes were ACM, CVD, and cancer incidence including PA, diet and adiposity-related (PDAR) cancer. During a median follow-up of 8 years, 2,863 deaths occurred, 11,053 participants developed CVD, 7,005 developed cancer, and 3,400 developed PDAR cancer. Compared with the least favorable referent group (bottom PA tertile/low DQS), participants with middle and high (total and intensity specific) PA, except for LPA, had lower ACM risk and incident CVD risk, regardless of DQS. For example, among middle and high VPA and high DQS groups, CVD HR were 0.79 (95% CI, 0.74-0.86) and 0.75 (95% CI, 0.69-0.82), respectively. The pattern of cancer results was less pronounced but in agreement with the ACM and CVD incidence findings (e.g., HR, 0.90, 95% CI, 0.81-0.99; 0.88, 0.79-0.98; and 0.82, 0.74-0.92 among high VPA for low, moderate, and high DQS groups, respectively). Device-measured PA reveals novel joint associations with diet on health outcomes. Our results emphasize the crucial role of PA in addition to a healthy diet for reducing chronic diseases and mortality risk.

Relationship of device measured physical activity type and posture with cardiometabolic health markers: pooled dose–response associations from the Prospective Physical Activity, Sitting and Sleep Consortium

Aims/hypothesisThe aim of this study was to examine the dose–response associations of device-measured physical activity types and postures (sitting and standing time) with cardiometabolic health.MethodsWe conducted an individual participant harmonised meta-analysis of 12,095 adults (mean ± SD age 54.5±9.6 years; female participants 54.8%) from six cohorts with thigh-worn accelerometry data from the Prospective Physical Activity, Sitting and Sleep (ProPASS) Consortium. Associations of daily walking, stair climbing, running, standing and sitting time with a composite cardiometabolic health score (based on standardised z scores) and individual cardiometabolic markers (BMI, waist circumference, triglycerides, HDL-cholesterol, HbA1c and total cholesterol) were examined cross-sectionally using generalised linear modelling and cubic splines.ResultsWe observed more favourable composite cardiometabolic health (i.e. z score <0) with approximately 64 min/day walking (z score [95% CI] −0.14 [−0.25, −0.02]) and 5 min/day stair climbing (−0.14 [−0.24, −0.03]). We observed an equivalent magnitude of association at 2.6 h/day standing. Any amount of running was associated with better composite cardiometabolic health. We did not observe an upper limit to the magnitude of the dose–response associations for any activity type or standing. There was an inverse dose–response association between sitting time and composite cardiometabolic health that became markedly less favourable when daily durations exceeded 12.1 h/day. Associations for sitting time were no longer significant after excluding participants with prevalent CVD or medication use. The dose–response pattern was generally consistent between activity and posture types and individual cardiometabolic health markers.Conclusions/interpretationIn this first activity type-specific analysis of device-based physical activity, ~64 min/day of walking and ~5.0 min/day of stair climbing were associated with a favourable cardiometabolic risk profile. The deleterious associations of sitting time were fully attenuated after exclusion of participants with prevalent CVD and medication use. Our findings on cardiometabolic health and durations of different activities of daily living and posture may guide future interventions involving lifestyle modification.Graphical

Longitudinal changes in device-measured physical activity from childhood to young adulthood: the PANCS follow-up study

BackgroundThere 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.MethodsA 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).ResultsThe 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.ConclusionsWe 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.

Motor skill competence and moderate- and vigorous-intensity physical activity: a linear and non-linear cross-sectional analysis of eight pooled trials

BackgroundFew 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.MethodsCross-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.ResultsThere 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.ConclusionsThere 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.

Joint associations of device-measured physical activity and abdominal obesity with incident cardiovascular disease: a prospective cohort study

ObjectiveTo examine the joint associations between physical activity and abdominal obesity with the risk of cardiovascular disease (CVD) events.MethodsWe included 70 830 UK Biobank participants (mean age±SD=61.6 ± 7.9 years;...

Association Between Accelerometer-Measured Physical Activity and Mobility Limitations in Twins.

The associations between mobility limitations and device-measured physical activity are sparsely studied. In this study, these associations are studied among community-dwelling older twins. This cross-sectional study utilized data gathered in 2014-2016 for the MOBILETWIN study. Participants were twins born in Finland between 1940 and 1944 (774 participants, mean age 73years). Physical activity was measured with a hip-worn accelerometer. Mobility limitations were assessed with a questionnaire. Individual-level analyses revealed that physical activity was associated with mobility limitations. Participants with severe mobility limitations took 2,637 (SD = 1,747) steps per day, those with some mobility limitations 4,437 (SD = 2,637) steps, and those without mobility limitations 7,074 (SD = 2,931) steps (p < .05). The within-twin pair analyses revealed the same pattern for the 144 dizygotic twin pairs, but no associations were seen for the 117 monozygotic twin pairs. Accelerometer-measured physical activity and mobility limitations were associated in community-dwelling older adults. Genetic factors may explain some of the variations in physical activity. A personalized exercise program to promote increased physical activity should be provided for older adults who report mobility difficulties. Future research is needed to examine causality between physical activity and mobility limitations.

FMUPorto - Summaries and comments

a Device-measured physical activity, sedentary time, and risk of all-cause mortality: an individual participant data analysis of four prospective cohort studies* b Association between estimated cardiorespiratory fitness and breast cancer: a prospective cohort study

Agcounts: An R Package to Calculate ActiGraph Activity Counts From Portable Accelerometers

Portable accelerometers are used to capture physical activity in free-living individuals with the ActiGraph being one of the most widely used device brands in physical activity and health research. Recently, in February 2022, ActiGraph published their activity count algorithm and released a Python package for generating activity counts from raw acceleration data for five generations of ActiGraph devices. The nonproprietary derivation of the ActiGraph count improved the transparency and interpretation of accelerometer device-measured physical activity, but the Python release of the count algorithm does not integrate with packages developed by the physical activity research community using the R Statistical Programming Language. In this technical note, we describe our efforts to create an R-based translation of ActiGraph’s Python package with additional extensions to make data processing easier and faster for end users. We call the resulting R package agcounts and provide an inside look at its key functionalities and extensions while discussing its prospective impacts on collaborative open-source software development in physical behavior research. We recommend that device manufacturers follow ActiGraph’s lead by providing open-source access to their data processing algorithms and encourage physical activity researchers to contribute to the further development and refinement of agcounts and other open-source software.

Ground Truthing: Perceived Versus Objectively Measured Built Environment Attributes in South African Communities

Introduction :No ground truthing study of ‘neighbourhood walkability’ has been conducted in Africa that contrasts the lived experience of the neighbourhood-built environment against objectively measured attributes using GIS and subscales of the NEWS-Africa instrument. Methods: This is a cross-sectional survey and observation study. A convenient sample of residents (n=52) aged 18-65 years from four urban suburbs in low- and high-income settings, self-reported transport, leisure-time physical activity (PA) and device-measured moderate-to-vigorous PA (MVPA) were assessed. Built environment constructs was derived from individual-level street network measures (1000m buffer, using ArcGIS 10.51). We also assessed PA between the four groups based on income and GIS walkability. Results: There was no significant relationship between self-reported MVPA and GIS-measured walkability in the study sample. Only intersection density had a significant inversely association with moderate and MVPA (rho=-0.31, P&lt;0.05) in the overall study sample. Self-report transport PA differed between groups (P&lt;0.013). Device-measured vigorous activity differed between groups and was lower in both Low-SES groups compared to the High-SES/Low Walkable group (P&lt;0.04). Total PA was not associated with GIS measured walkability, but inversely associated with positive perceived neighbourhood attributes. Conclusions: There is a modest inverse association between device-measured PA and GIS-measured intersection density. These results suggest that constructs of walkability, whether measured or perceived, may predict volitional and utilitarian PA differently in our study population.

Device-measured physical activity and type 2 diabetes mellitus risk.

We investigated how device-measured physical activity (PA) volume (PA energy expenditure [PAEE]) and intensity (fraction of PAEE from moderate-to-vigorous PA [FMVPAEE]) were associated with the incidence of type 2 diabetes mellites (T2DM). This population-based prospective cohort study included 90,044 participants. The primary exposures were PAEE and FMVPAEE. The secondary exposures were energy expenditure exerted during light, moderate, and vigorous PA and their fraction of PAEE. Each 1-SD increase in PAEE was associated with a 17% lower risk of T2DM (hazard ratio [HR]: 0.83, 95% confidence interval [CI]: 0.78-0.98). Each 1-SD increase in FMVPAEE was associated with a 21% lower incidence of T2DM (HR: 0.79, 95% CI: 0.74-0.83). Achieving the same PA volume (KJ/kg/day) through vigorous PA (HR: 0.88, 95% CI: 0.85-0.91) was more effective in preventing T2DM than moderate PA (HR: 0.97, 95% CI: 0.96-0.98) and light PA (HR: 0.99, 95% CI: 0.98-1.00). A higher PA volume is associated with a lower incidence of T2DM. Achieving the same PA volumes through higher-intensity PA is more effective than low-intensity PA in reducing T2DM incidence.

Device-Measured Physical Activity in 3506 Individuals with Knee or Hip Arthroplasty.

Hip and knee arthroplasty aims to reduce joint pain and increase functional mobility in patients with osteoarthritis; however, the degree to which arthroplasty is associated with higher physical activity is unclear. The current study sought to assess the association of hip and knee arthroplasty with objectively measured physical activity. This cross-sectional study analyzed wrist-worn accelerometer data collected in 2013-2016 from UK Biobank participants (aged 43-78 yr). Multivariable linear regression was performed to assess step count, cadence, overall acceleration, and activity behaviors between nonarthritic controls, end-stage arthritic, and postoperative cohorts, controlling for demographic and behavioral confounders. From a cohort of 94,707 participants with valid accelerometer wear time and complete self-reported data, electronic health records were used to identify 3506 participants having undergone primary or revision hip or knee arthroplasty and 68,389 nonarthritic controls. End-stage hip or knee arthritis was associated with taking 1129 fewer steps per day (95% confidence interval (CI), 811-1447; P < 0.001) and having 5.8 fewer minutes per day (95% CI, 3.0-8.7; P < 0.001) of moderate-to-vigorous activity compared with nonarthritic controls. Unilateral primary hip and knee arthroplasties were associated with 877 (95% CI, 284-1471; P = 0.004) and 893 (95% CI, 232-1554; P = 0.008) more steps than end-stage osteoarthritic participants, respectively. Postoperative unilateral hip arthroplasty participants demonstrated levels of moderate-to-vigorous physical activity and daily step count equivalent to nonarthritic controls. No difference in physical activity was observed between any cohorts in terms of overall acceleration, or time spent in daily light activity, sedentary behavior, or sleep. Hip and knee arthroplasties are associated with higher levels of physical activity compared with participants with end-stage arthritis. Unilateral hip arthroplasty patients, in particular, demonstrate equivalence to nonarthritic peers at more than 1 yr after surgery.

Association between Physical Activity and Reduced Mortality in Inoperable Lung Cancer

We examined device-measured physical activity (PA) and sedentary behaviour at the time of diagnosis in people with inoperable lung cancer and investigated their associations with 12-month mortality. The people with inoperable lung cancer wore an accelerometer for seven days prior to the treatment commencement. The analysed PA/sedentary behaviour variables included light-intensity PA, moderate-to-vigorous-intensity PA (MVPA), step count, the total time spent sedentary, and the usual sedentary bout duration. The data on the disease stage, clinical covariates and 12-month mortality were extracted from medical records. Cox regression models were used to estimate the association between the PA measures and 12-month mortality, and the sedentary behaviour measures and 12-month mortality. The models were adjusted for the stage and neutrophil-to-lymphocyte ratio. All the PA and sedentary behaviour variables were dichotomised at their medians for analysis. Eighty-nine participants (70 ± 10 years; 55 [62%] males) contributed valid data. The twelve-month mortality was 30% (n = 27). Compared to the participants who spent ≤4.6 min/day in MVPA (n = 45), those who spent &gt;4.6 min/day (n = 44) had a relative risk of 12-month mortality reduced by 60% (hazard ratio, 0.40; 95% CI, 0.16 to 0.96; 18 versus nine deaths, respectively). The other variables of PA/sedentary behaviour were not associated with 12-month mortality. Higher device-measured MVPA was associated with reduced 12-month mortality in people who were newly diagnosed with inoperable lung cancer.

Device-measured physical activity and cardiometabolic health: the Prospective Physical Activity, Sitting, and Sleep (ProPASS) consortium.

Physical inactivity, sedentary behaviour (SB), and inadequate sleep are key behavioural risk factors of cardiometabolic diseases. Each behaviour is mainly considered in isolation, despite clear behavioural and biological interdependencies. The aim of this study was to investigate associations of five-part movement compositions with adiposity and cardiometabolic biomarkers. Cross-sectional data from six studies (n = 15 253 participants; five countries) from the Prospective Physical Activity, Sitting and Sleep consortium were analysed. Device-measured time spent in sleep, SB, standing, light-intensity physical activity (LIPA), and moderate-vigorous physical activity (MVPA) made up the composition. Outcomes included body mass index (BMI), waist circumference, HDL cholesterol, total:HDL cholesterol ratio, triglycerides, and glycated haemoglobin (HbA1c). Compositional linear regression examined associations between compositions and outcomes, including modelling time reallocation between behaviours. The average daily composition of the sample (age: 53.7 ± 9.7 years; 54.7% female) was 7.7 h sleeping, 10.4 h sedentary, 3.1 h standing, 1.5 h LIPA, and 1.3 h MVPA. A greater MVPA proportion and smaller SB proportion were associated with better outcomes. Reallocating time from SB, standing, LIPA, or sleep into MVPA resulted in better scores across all outcomes. For example, replacing 30 min of SB, sleep, standing, or LIPA with MVPA was associated with -0.63 (95% confidence interval -0.48, -0.79), -0.43 (-0.25, -0.59), -0.40 (-0.25, -0.56), and -0.15 (0.05, -0.34) kg/m2 lower BMI, respectively. Greater relative standing time was beneficial, whereas sleep had a detrimental association when replacing LIPA/MVPA and positive association when replacing SB. The minimal displacement of any behaviour into MVPA for improved cardiometabolic health ranged from 3.8 (HbA1c) to 12.7 (triglycerides) min/day. Compositional data analyses revealed a distinct hierarchy of behaviours. Moderate-vigorous physical activity demonstrated the strongest, most time-efficient protective associations with cardiometabolic outcomes. Theoretical benefits from reallocating SB into sleep, standing, or LIPA required substantial changes in daily activity.

How does relative time in moderate-to-vigorous physical activity correspond to the 2020 guidelines on physical activity and sedentary behaviour?

BackgroundMore and more researchers have started to analyse device-measured physical activity data using compositional data analysis (CoDA), which has led to that the effect of relative time in different behaviours can be explored. However, there are challenges related to the interpretation of the results based on CoDA. This is partly related to that CoDA provides estimates based on the relative time that is difficult to interpret relative to the 2020 guidelines of physical activity and sedentary behaviour. Since many data cohorts do not have data on sleep, the proportion of time in physical activity may vary depending on accelerometer wear time. Therefore, there is a need to explore cut-points for relative time to distinguish between individuals that do and do not reach 150–300 min of moderate-to-vigorous intensity physical activity (MVPA) per week. The aim was to establish a ratio of MVPA to awaken time that corresponds to meeting the 2020 guidelines of physical activity and sedentary behaviour in adults.MethodTo estimate the cut-off points of relative time in MVPA, the publicly available data from NHANES 2003–2004 was used and cut-off points were explored in different subsets of the total population. Values for sensitivity, specificity and cut-off values were explored; i) in total sample, ii) by tertiles of wear time, iii) in individuals with ± 5 min from 150 to 300 min of MVPA, iiii) in individuals with ± 5 min from 150 to 300 min of MVPA in the middle tertile of wear time.ResultsOverall, the analyses show high values for sensitivity (88–100%) and specificity (66–99%) for different cut-off values associated with 150–300 min of MVPA. Spending 2.4–4.7% of the time awake in MVPA was found to correspond to the 2020 guidelines of physical activity and sedentary behaviour.ConclusionBased on publicly available data from NHANES 2003–2004, spending 2.4–4.7% of time awake in MVPA corresponds to meeting the 2020 guidelines of physical activity and sedentary behaviour.

Brief bouts of device-measured intermittent lifestyle physical activity and its association with major adverse cardiovascular events and mortality in people who do not exercise: a prospective cohort study

Guidelines emphasise the health benefits of bouts of physical activity of any duration. However, the associations of intermittent lifestyle physical activity accumulated through non-exercise with mortality and major adverse cardiovascular events (MACE) remain unclear. We aimed to examine the associations of bouts of moderate-to-vigorous intermittent lifestyle physical activity (MV-ILPA) and the proportion of vigorous activity contributing within these bouts with mortality and MACE. In this prospective cohort study, we used data from the UK Biobank on adults who do not exercise (ie, those who did not report leisure-time exercise) who had wrist-worn accelerometry data available. Participants were followed up until Nov 30, 2022, with the outcome of interest of all-cause mortality obtained through linkage with NHS Digital of England and Wales, and the NHS Central Register and National Records of Scotland, and MACE obtained from inpatient hospitalisation data provided by the Hospital Episode Statistics for England, the Patient Episode Database for Wales, and the Scottish Morbidity Record for Scotland. MV-ILPA bouts were derived using a two-level Random Forest classifier and grouped as short (<1 min), medium (1 to <3 min; 3 to <5 min), and long (5 to <10 min). We further examined the dose-response relationship of the proportion of vigorous physical activity contributing to the MV-ILPA bout. Between June 1, 2013, and Dec 23, 2015, 103 684 Biobank participants wore an accelerometer on their wrist. 25 241 adults (mean age 61·8 years [SD 7·6]), of whom 14 178 (56·2%) were women, were included in our analysis of all-cause mortality. During a mean follow-up duration of 7·9 years (SD 0·9), 824 MACE and 1111 deaths occurred. Compared with bouts of less than 1 min, mortality risk was lower for bouts of 1 min to less than 3 min (hazard ratio [HR] 0·66 [0·53-0·81]), 3 min to less than 5 min (HR 0·56 [0·46-0·69]), and 5 to less than 10 min (HR 0·48 [0·39-0·59]). Similarly, compared with bouts of less than 1 min, risk of MACE was lower for bouts of 1 min to less than 3 min (HR 0·71 [0·54-0·93]), 3 min to less than 5 min (0·62 [0·48-0·81]), and 5 min to less than 10 min (0·59 [0·46-0·76]). Short bouts (<1 min) were associated with lower MACE risk only when bouts were comprised of at least 15% vigorous activity. Intermittent non-exercise physical activity was associated with lower mortality and MACE. Our results support the promotion of short intermittent bouts of non-exercise physical activity of moderate-to-vigorous intensity to improve longevity and cardiovascular health among adults who do not habitually exercise in their leisure time. Australian National Health, Medical Research Council, and Wellcome Trust.

Changes in Self-Reported and Device-Measured Physical Activity Before Abdominal Resection Surgery: A Meta-Analysis

Objective To determine the effect of interventions on physical activity levels of patients awaiting abdominal resection surgery using self-reported as well as device-measured outcome measures. Data source PubMed and EMBASE databases were searched on the 18th of April 2023 up to April 2023 for studies on interventions to promote physical activity during the preoperative phase. Review methods Studies were included if pre- and post-intervention physical activity was measured between diagnosis and abdominal surgery. Risk of bias was assessed by the Physiotherapy Evidence Database (PEDro) assessment tool for trials. Meta-analyses were performed to assess the effect of the pre-surgery activity promoting interventions on self-reported and device-measured physical activity. Results Seventeen studies were included in the analysis with 452 subjects in the intervention groups. The random-effect meta-analysis showed a moderate improvement in intervention groups measures in pre-surgery physical activity levels compared to the baseline (SMD = 0.67, [CI = 0.30;1.03], I2 = 79%). The self-reported subgroup meta-analysis showed the largest increase in performed physical activity, (SMD = 0.78, [CI = 0.4;1.15], I2 = 79%) whilst non-significant increase was shown in the device-measured subgroup (SMD = 0.16, [CI = −0.64;0.97], I2 = 58%). Conclusion Increasing physical activity in the preoperative phase is feasible. Self-reported physical activity outcome measures show larger effects compared to device-measured outcome measures. More high-quality research should be performed utilizing objective measures.

O.4.5-1 Device-measured physical activity and sedentary time in a national sample of Luxembourg residents: moving beyond the traditional metrics in the ORISCAV-LUX 2 study

Abstract Purpose This is the first study aiming at describing the volume and pattern of device-measured movement behaviours performed by adults living in Luxembourg, spanning the full intensity spectrum, and including markers of sedentary time accumulation. We also demonstrated the added value of a multidimensional approach for the comparison of sub-populations. Methods This observational study included Luxembourg residents aged 18-79y who each provided ≥4 valid days of triaxial accelerometry in 2016-18 (n = 1122). Compliance with the current international physical activity (PA) guideline was quantified. Linear regression models were used to quantify variability in average 24h acceleration (indicative of PA volume), awake-time PA levels, sedentary time and accumulation pattern with sociodemographic characteristics and other covariates. Data were weighted to be nationally representative. Results Overall, participants spent 51% of daily sedentary time (12.1 h/day), 11% in light PA (2.7 h/day), 6% in moderate to vigorous PA (MVPA; 1.5 h/day), and remaining time asleep (7.7 h/day). Adherence to the current PA guideline was high (98.1%), but drop to 22% when including only bouts &amp;gt;10min. Although time spent in MVPA did not differ between women and men, average 24h acceleration and light PA were higher in women than men, while men achieved higher average accelerations across the most active periods of the day. Women performed less sedentary time and shorter sedentary bouts. Older participants (≥55y) registered a lower average 24h acceleration and engaged in less MVPA, more sedentary time and longer sedentary bouts. Average 24h acceleration was higher in participants of lower educational attainment, who also performed less sedentary time, shorter bouts, and fewer bouts of prolonged sedentariness. Average 24h acceleration and levels of PA were higher in participants with standing and manual occupations than a sedentary work type, but manual workers registered lower average accelerations across the most active periods of the day. Standing and manual workers accumulated less sedentary time and fewer bouts of prolonged sedentariness than sedentary workers. Conclusions Traditional metrics may incompletely reflect differences in the physical behaviour between sub-populations. Breaking up continuous sedentary periods and replacing sedentary time with active alternatives should be the focus of public health initiatives in Luxembourg. Funding Luxembourg Institute of Health.