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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: Sleep disturbance is an increasingly recognized non‐motor trait in dystonia, with varying findings reported to date. Here, we examine sleep in a UK Biobank derived dystonia cohort using subjective self‐reported sleep symptoms and objective accelerometer‐derived sleep measures, with comparison to a control population. Methods: A total of 241 dystonia cases were compared to 964 matched controls in analysis of self‐reported sleep symptoms and changes in sleep architecture using wrist‐worn triaxial accelerometers. Results: Dystonia participants had poorer self‐reported sleep patterns compared to controls. Accelerometery measurements demonstrated later sleep times, reduced time in bed, and shifts in circadian rhythm. No association was observed with pain, and only limited relationships with psychiatric symptoms. Discussion: This study demonstrates the utility of accelerometers in longer term evaluation of sleep in dystonia, for measurement of disturbance and response to treatment. Compared to controls, altered sleep and circadian rhythm were more common in dystonia patients which may contribute to the clinical phenotype. [ABSTRACT FROM AUTHOR]

Aim: This study was aimed to: (1) compare raw triaxial acceleration data from GENEActiv (GA) and ActiGraph GT3X+ (AG) placed on the non‐dominant wrist; (2) compare AG placed on the non‐dominant and dominant wrist, and waist; (3) derive brand‐ and placement‐specific absolute intensity thresholds for inactive and sedentary time, and physical activity intensity in adults. Methods: Eighty‐six adults (44 men; 34.6 ± 10.8 years) performed nine activities while simultaneously wearing GA and AG on wrist and waist. Acceleration (in gravitational equivalent units; mg) was compared with oxygen uptake (measured with indirect calorimetry). Results: Increases in acceleration mirrored increases in intensity of activities, regardless of device brand and placement. Differences in acceleration between GA and AG worn at the non‐dominant wrist were small but tended to be high at lower intensity activities. Thresholds for differentiating inactivity (<1.5 MET) from activity (≥1.5 MET) ranged from 25 mg (AG non‐dominant wrist; sensitivity 93%, specificity 95%) to 40 mg (AG waist; sensitivity 78%, specificity 100%). For moderate intensity (≥3 METs), thresholds ranged from 65 mg (AG waist; sensitivity 96%, specificity 94%) to 92 mg (GA non‐dominant; sensitivity 93%, specificity 98%); vigorous intensity (≥6 METs) thresholds ranged from 190 mg (AG waist; sensitivity 82%, specificity 92%) to 283 mg (GA non‐dominant; sensitivity 93%, specificity 98%). Conclusion: Raw triaxial acceleration outputs from two widely used accelerometer brands may have limited comparability in low intensity activities. Thresholds derived in this study can be utilized in adults to reasonably classify movement behaviors into categories of intensity. [ABSTRACT FROM AUTHOR]

Background: Most studies investigating the association between physical activity (PA) and the risk of type 2 diabetes are derived from self-reported questionnaires, with limited evidence using device-based measurements. Therefore, this study aimed to investigate the dose–response relationship between device-measured PA and incident type 2 diabetes. Methods: This prospective cohort study included 40,431 participants of the UK Biobank. Wrist-worn accelerometers were used to estimate total, light, moderate, vigorous and moderate-to-vigorous PA. The associations between PA and incident type 2 diabetes were analysed using Cox-proportional hazard models. The mediating role of body mass index (BMI) was tested under a causal counterfactual framework. Results: The median follow-up period was 6.3 years (IQR: 5.7–6.8), with 591 participants developing type 2 diabetes. Compared to those achieving < 150 min/week of moderate PA, people achieving 150–300, 300–600 and > 600 min/week were at 49% (95% CI 62–32%), 62% (95% CI 71–50%) and 71% (95% CI 80–59%) lower risk of type 2 diabetes, respectively. For vigorous PA, compared to those achieving < 25 min/week, individuals achieving 25–50, 50–75 and > 75 min/week were at 38% (95% CI 48–33%), 48% (95% CI 64–23%) and 64% (95% CI 78–42%) lower type 2 diabetes risk, respectively. Twelve per cent and 20% of the associations between vigorous and moderate PA and type 2 diabetes were mediated by lower BMI, respectively. Conclusions: PA has clear dose-response relationship with a lower risk of type 2 diabetes. Our findings support the current aerobic PA recommendations but suggest that additional PA beyond the recommendations is associated with even greater risk reduction. Trial registration: The UK Biobank study was approved by the North West Multi-Centre Research Ethics Committee (Ref 11/NW/0382 on June 17, 2011). [ABSTRACT FROM AUTHOR]

This study examined sleep and its cognitive and affective correlates in adults with and without autism spectrum disorder (ASD), utilizing UK Biobank data. There were no group differences in subjective sleep duration [n = 220 ASD; n = 2200 general population (GP)]. Accelerometer measures of sleep duration or nighttime activity did not differ by group, but sleep efficiency was marginally lower in ASD (n = 83 ASD; n = 824 GP). Sleep efficiency was associated with wellbeing and mental health, and pathways between accelerometer sleep measures and wellbeing and mental health were significantly stronger for adults with ASD (who also reported substantially poorer wellbeing and > 5 × likelihood of experiencing mental distress). These findings highlight the need to monitor sleep to maintain good mental health in adult ASD. [ABSTRACT FROM AUTHOR]

Introduction: Physical activity (PA) is recognized as one of the key lifestyle behaviors that reduces risk of developing dementia late in life. However, PA also leads to increased respiration, and in areas with high levels of air pollution, PA may increase exposure to pollutants linked with higher risk of developing dementia. Here, we investigate whether air pollution attenuates the association between PA and dementia risk. Methods: This prospective cohort study included 35,562 adults 60 yrs and older from the UK Biobank. Average acceleration magnitude (ACCave) from wrist-worn accelerometers was used to assess PA levels. Air pollution levels (NO, NO2, PM10, PM2.5, PM2.5–10, and PM2.5 absorbance) were estimated with land use regression methods. Incident all-cause dementia was derived from inpatient hospital records and death registry data. Results: In adjusted models, ACCave was associated with reduced risk of developing dementia (HR = 0.71, 95% confidence interval [CI] = 0.60–0.83), whereas air pollution variables were not associated with dementia risk. There were significant interactions between ACCave and PM2.5 (HRinteraction = 1.33, 95% CI = 1.13–1.57) and PM2.5 absorbance (HRinteraction = 1.24, 95% CI = 1.07–1.45) on incident dementia. At the lowest tertiles of pollution, ACCave was associated with reduced risk of incident dementia (HRPM 2.5 = 0.66, 95% CI = 0.49–0.91; HRPM 2.5 absorbance = 0.60, 95% CI = 0.44–0.81). At the highest tertiles of these pollutants, there was no significant association of ACCave with incident dementia (HRPM 2.5 = 0.88, 95% CI = 0.68–1.14; HRPM 2.5 absorbance = 0.79, 95% CI = 0.60–1.04). Conclusions: PA is associated with reduced risk of developing all-cause dementia. However, exposure to even moderate levels of air pollution attenuates the benefits of PA on risk of dementia. [ABSTRACT FROM AUTHOR]

Aims: Restrictions during the COVID‐19 crisis will have impacted on opportunities to be active. We aimed to (a) quantify the impact of COVID‐19 restrictions on accelerometer‐assessed physical activity and sleep in people with type 2 diabetes and (b) identify predictors of physical activity during COVID‐19 restrictions. Methods: Participants were from the UK Chronotype of Patients with type 2 diabetes and Effect on Glycaemic Control (CODEC) observational study. Participants wore an accelerometer on their wrist for 8 days before and during COVID‐19 restrictions. Accelerometer outcomes included the following: overall physical activity, moderate‐to‐vigorous physical activity (MVPA), time spent inactive, days/week with ≥30‐minute continuous MVPA and sleep. Predictors of change in physical activity taken pre‐COVID included the following: age, sex, ethnicity, body mass index (BMI), socio‐economic status and medical history. Results: In all, 165 participants (age (mean±S.D = 64.2 ± 8.3 years, BMI=31.4 ± 5.4 kg/m2, 45% women) were included. During restrictions, overall physical activity was lower by 1.7 mg (~800 steps/day) and inactive time 21.9 minutes/day higher, but time in MVPA and sleep did not statistically significantly change. In contrast, the percentage of people with ≥1 day/week with ≥30‐minute continuous MVPA was higher (34% cf. 24%). Consistent predictors of lower physical activity and/or higher inactive time were higher BMI and/or being a woman. Being older and/or from ethnic minorities groups was associated with higher inactive time. Conclusions: Overall physical activity, but not MVPA, was lower in adults with type 2 diabetes during COVID‐19 restrictions. Women and individuals who were heavier, older, inactive and/or from ethnic minority groups were most at risk of lower physical activity during restrictions. [ABSTRACT FROM AUTHOR]

Hyperactivity is one of the three core symptoms in children with attention deficit hyperactivity disorder (ADHD). Diagnosing ADHD typically involves self-report, third party report and observations. Objective activity data can make a valuable contribution to the diagnostic process. Small actigraphy studies in clinical samples have shown that children with ADHD move more than children without ADHD. However, differences in physical activity between children with and without ADHD have not been assessed in large community samples or longitudinally. This study used data from the Millennium Cohort Study to test whether symptoms of ADHD (parent-rating Strengths and Difficulties Questionnaire) and ADHD diagnosis at age 14 (reported by parents) could be predicted from objective activity data (measured with actigraphs) at age 7 in N = 6675 children (final N = 5251). Regressions showed that less sedentary behavior at age 7 predicted more ADHD symptoms at age 14 (β = − 0.002, CI − 0.004 to − 0.001). The result remained significant when controlled for ADHD symptoms at age 7, sex, BMI, month of birth, SES and ethnicity (β = − 0.001, CI − 0.003 to − 0.0003). ADHD diagnosis at age 14 was also significantly predicted by less sedentary behavior at age 7 (β = − 0.008). Our findings show that symptoms of ADHD can be predicted by objective activity data 5 years in advance and suggest that actigraphy could be a useful instrument aiding an ADHD diagnosis. Interestingly, the results indicate that the key difference between children with and without ADHD lies in reduced sedentary activity, i.e., times of rest. [ABSTRACT FROM AUTHOR]

This study provides a new test of time-use diary methodology, comparing diaries with a pair of objective criterion measures: wearable cameras and accelerometers. A volunteer sample of respondents (n = 148) completed conventional self-report paper time-use diaries using the standard UK Harmonised European Time Use Study (HETUS) instrument. On the diary day, respondents wore a camera that continuously recorded images of their activities during waking hours (approximately 1,500–2,000 images/day) and also an accelerometer that tracked their physical activity continuously throughout the 24-hour period covered by the diary. Of the initial 148 participants recruited, 131 returned usable diary and camera records, of whom 124 also provided a usable whole-day accelerometer record. The comparison of the diary data with the camera and accelerometer records strongly supports the use of diary methodology at both the aggregate (sample) and individual levels. It provides evidence that time-use data could be used to complement physical activity questionnaires for providing population-level estimates of physical activity. It also implies new opportunities for investigating techniques for calibrating metabolic equivalent of task (MET) attributions to daily activities using large-scale, population-representative time-use diary studies. [ABSTRACT FROM AUTHOR]

Supplemental digital content is available in the text. Purpose: This study aimed to investigate whether prospectively reallocating time away from sedentary behavior (SB) into different physical activity intensities is associated with 12-month change to cardiometabolic health in a cohort at high risk of type 2 diabetes (T2DM). Methods: Participants with known risk factors for T2DM were recruited from primary care (Leicestershire, United Kingdom) as part of the Walking Away from Type 2 Diabetes trial (n = 808). Participants were followed up at 12, 24, and 36 months. SB, light-intensity physical activity (LPA) and moderate-to-vigorous intensity physical activity (MVPA) were measured objectively by accelerometer. Postchallenge glucose, triglycerides, HDL cholesterol, systolic blood pressure, and waist circumference were analyzed individually and combined into a clustered cardiometabolic risk score (CMRS). Associations of changing SB over each consecutive 12-month period were analyzed taking account of repeated measures. Results: Reallocating 30 min from SB to LPA was associated with 0.21-cm (95% confidence interval, 0.03–0.38 cm) reduction in waist circumference, 0.09-mmol·L−1 (0.04–0.13 mmol·L−1) reduction in 2-h glucose, 0.02-mmol·L−1 (0.00–0.04 mmol·L−1) reduction in triglycerides, and 0.02 (0.01–0.03) reduction in CMRS. Every 30-min reallocation from SB to MVPA was associated with 1.23-cm (0.68–1.79 cm) reduction in waist circumference, 0.23-mmol·L−1 (0.10–0.36 mmol·L−1) reduction in 2-h glucose, 0.04-mmol·L−1 (0.00–0.09 mmol·L−1) reduction in triglycerides, and 0.07 (0.04–0.11) reduction in CMRS. Reallocating 30 min from LPA into MVPA was also associated with 1.02-cm (0.43–1.60 cm) reduction in waist circumference, 0.16-mmol·L−1 (0.02–0.30 mmol·L−1) reduction in 2-h glucose, and 0.05 (0.01–0.09) reduction in CMRS. Conclusion: Over 12 months, reallocating time away from SB into LPA or MVPA was associated with improved cardiometabolic health in a population at risk of T2DM, with the greatest benefits observed for MVPA. [ABSTRACT FROM AUTHOR]

Background: UK Biobank is a large prospective cohort study containing accelerometer-based physical activity data with strong validity collected from 100,000 participants approximately 5 years after baseline. In contrast, the main cohort has multiple self-reported physical behaviours from > 500,000 participants with longer follow-up time, offering several epidemiological advantages. However, questionnaire methods typically suffer from greater measurement error, and at present there is no tested method for combining these diverse self-reported data to more comprehensively assess the overall dose of physical activity. This study aimed to use the accelerometry sub-cohort to calibrate the self-reported behavioural variables to produce a harmonised estimate of physical activity energy expenditure, and subsequently examine its reliability, validity, and associations with disease outcomes. Methods: We calibrated 14 self-reported behavioural variables from the UK Biobank main cohort using the wrist accelerometry sub-cohort (n = 93,425), and used published equations to estimate physical activity energy expenditure (PAEESR). For comparison, we estimated physical activity based on the scoring criteria of the International Physical Activity Questionnaire, and by summing variables for occupational and leisure-time physical activity with no calibration. Test-retest reliability was assessed using data from the UK Biobank repeat assessment (n = 18,905) collected a mean of 4.3 years after baseline. Validity was assessed in an independent validation study (n = 98) with estimates based on doubly labelled water (PAEEDLW). In the main UK Biobank cohort (n = 374,352), Cox regression was used to estimate associations between PAEESR and fatal and non-fatal outcomes including all-cause, cardiovascular diseases, respiratory diseases, and cancers. Results: PAEESR explained 27% variance in gold-standard PAEEDLW estimates, with no mean bias. However, error was strongly correlated with PAEEDLW (r = −.98; p < 0.001), and PAEESR had narrower range than the criterion. Test-retest reliability (Λ =.67) and relative validity (Spearman =.52) of PAEESR outperformed two common approaches for processing self-report data with no calibration. Predictive validity was demonstrated by associations with morbidity and mortality, e.g. 14% (95%CI: 11–17%) lower mortality for individuals meeting lower physical activity guidelines. Conclusions: The PAEESR variable has good reliability and validity for ranking individuals, with no mean bias but correlated error at individual-level. PAEESR outperformed uncalibrated estimates and showed stronger inverse associations with disease outcomes. [ABSTRACT FROM AUTHOR]

Supplemental digital content is available in the text. Purpose: To establish whether associations between sedentary behavior and cardiometabolic health differ when assessed by thigh-worn and waist-worn accelerometry. Methods: Participants were recruited from several areas in the United Kingdom. Sedentary behavior was assessed using the activPAL worn on the thigh and ActiGraph worn on the waist. Average total (TST), prolonged (bouts ≥30 min; PST) and breaks (BST) in sedentary time were calculated. Cardiometabolic health markers included: adiposity (body fat) and surrogate markers of adiposity ((waist circumference, body mass index [BMI]), lipids (total, low density lipoprotein, and high-density lipoprotein [HDL] cholesterol, triglycerides), blood pressure, and glucose (fasting, 2 h and glycated hemoglobin A1c). A clustered cardiometabolic risk score was calculated. Linear regression analysis examined the associations with cardiometabolic health. Results: There were 1457 participants (mean age [± standard deviation], 59.38 ± 11.85 yr; 51.7% male; mean BMI, 30.19 ± 5.59 kg·m−2) included in the analyses. ActivPAL and ActiGraph sedentary variables were moderately correlated (0.416–0.511, P < 0.01); however, all variables were significantly different from each other (P < 0.05). Consistency was observed across devices in the direction and magnitude of associations of TST and PST with adiposity, surrogate markers of adiposity, HDL, triglycerides, and cardiometabolic risk score and for BST with adiposity, surrogate markers of adiposity, and cardiometabolic risk. Differences across devices were observed in associations of TST and PST with diastolic blood pressure, for TST with 2-h glucose and for BST with HDL. No other associations were observed for any other health marker for either device. Conclusions: Results suggest that associations with cardiometabolic health are largely comparable across the two common assessments of sedentary behavior but some small differences may exist for certain health markers. [ABSTRACT FROM AUTHOR]

Abstract Aims With increasing age, physical inactivity and sedentary behaviour levels increase, as does cardiovascular disease (CVD) incidence. We investigate how device-measured sedentary behaviour and physical activity (PA) are related to CVD onset in men aged 70+; whether the total volume of activity is more important than pattern. Methods and results Prospective population-based cohort study of men recruited from 24 UK General Practices in 1978–80. In 2010–12, 3137 survivors were invited to complete questionnaires and wear an Actigraph GT3x accelerometer for 7 days. PA intensity was categorised as sedentary, light and moderate to vigorous (MVPA). Men were followed up for Myocardial Infarction, stroke and heart failure (ICD9 410–414, 430–438 and 428) morbidity and mortality from 2010 to 12 to June 2016. Hazard Ratios (HRs) for incident Cardiovascular Disease (CVD) were estimated. 1528/3137 (49%) men had sufficient accelerometer data. 254 men with pre-existing CVD were excluded. Participants' mean age was 78.4 (range 71–92) years. After median 4.9 years follow-up, 122 first CVD events occurred in 1181 men (22.7/1000 person-years) with complete data. For each additional 30 min in sedentary behaviour, light PA,10 min in MVPA, or 1000 steps/day, HRs for CVD were 1.09(95%CI 1.00, 1.19), 0.94(0.85, 1.04), 0.88(0.81, 0.96) and 0.86(0.78 to 0.95) respectively, adjusted for measurement-related factors, socio-demographics, health behaviours and disability. HRs for accumulating 150 min/week MVPA in bouts ≥1 min and bouts ≥10 min were 0.47(0.32 to 0.69), and 0.49(0.25, 0.98). Conclusions In older men, high volume of steps or MVPA rather than MVPA bouts was associated with reduced CVD risk. Highlights • Prospective studies report that self-reported physical activity protects against cardiovascular disease (CVD). • Yet, self-reported behaviours cannot easily be used to assess the value of the 10 min activity bouts specified in guidelines. • This is the first study of risk of fatal and non-fatal CVD based on device measured physical activity and sedentary behaviour. • Among 1181 men aged over 70 years, more time in moderate to vigorous physical activity and more steps reduced 5-year CVD risk. • The pattern of accumulating moderate to vigorous physical activity in 10 min bouts was not important for CVD risk. [ABSTRACT FROM AUTHOR]

Objective: To investigate the validity and reliability of accelerometers to detect lying, sitting and standing postures or purposeful activity in hospitalized adults recovering from acute or critical illness. Data sources: CINAHL, MEDLINE, EMBASE, AMED, Cochrane Library, PEDro, PsycINFO and SPORTDiscuss were searched from inception to June 2017. Professional networks and reference lists of relevant articles were also searched. The main selection criteria were hospitalized adults with acute or critical illness and studies investigating the validity or reliability of accelerometers to identify body position or purposeful activity. Review methods: Two authors individually assessed study eligibility and independently undertook methodological quality assessment and data extraction from selected articles. A narrative synthesis of the data was undertaken. Results: Fifteen studies, collectively enrolling 385 hospitalized participants, were identified. Populations included stroke, the elderly, acute exacerbation of chronic respiratory disease, abdominal surgery and those recovering from critical illness. Correlations of r = 0.36 to 0.98 and levels of agreement of κ = 0.28 to 0.98 were reported for identification of lying, sitting or standing postures. Correlations of r = 0.4 to 0.8 with general activity were found, with r = 0.94 and 0.96 reported for step count. The reliability of accelerometry measurement was investigated in one study evaluating step count quantification (intraclass correlation coefficient (ICC) = 0.99, 95% confidence interval (CI) = 0.99–1.00). Conclusion: The validity of accelerometers to determine lying, sitting and standing postures or quantify purposeful activity within hospitalized acute or critically ill populations is variable. The reliability of accelerometry measurement within this setting remains largely unexplored. [ABSTRACT FROM AUTHOR]

Background: Physical inactivity is a highly modifiable risk factor for the development of osteoporosis but, due to a lack of research that has precisely and objectively meaured physical activity (PA) relevant to bone, the specific contribution that PA can make to bone health is poorly understood. This study examined whether a more precise measure of PA relelvant to bone was associated with meaures of bone health in pre- and post-menopausal women in UK Biobank.Methods: Time spent at intensities specific to bone health [≥750 milli-gravitational units (mg) and ≥1000 mg] were analysed from raw tri-axial acceleration data averaged over 1-second epochs from 7-day monitoring of habitual PA using accelerometry-based activity monitors (100 Hz; AX3, Axivity, UK) of 1218 pre- and 1316 post-menopausal healthy women. In a cross-sectional analysis, associations between categories of time (<1, 1-2 and ≥2 minutes) spent above the intensity thresholds and calcaneal quantitative ultrasound measures of bone health (bone mineral density T-score, BMDT-score; speed of sound, SOS; and broadband ultrasound attenuation, BUA) were examined.Results: Compared with <1 minute, spending 1-2 or ≥2 minutes/day at intensities ≥1000 mg in pre-menopausal and ≥750 mg in post-menopausal women was positively associated with BMDT-score, SOS and BUA.Conclusion: Brief bursts of high-intensity PA relevant to bone health can be captured by applying bone-specific thresholds of intensity to raw tri-axial accelerations averaged over 1-second epochs. Accumulating 1-2 minutes/day of high-intensity PA, equivalent to running in pre-menopausal women and slow jogging in post-menopausal women, is associated with better bone health. [ABSTRACT FROM AUTHOR]

Background: Objectively measured physical activity (PA) intensity has traditionally been categorized as light, moderate, and vigorous using laboratory calibrated cut points. The relative contribution of time spent across a spectrum of accelerometer-determined intensities on health outcomes is less clear. Purpose: This study aimed to assess the relationship between objectively measured PA intensity on a continuous scale and markers of insulin sensitivity (IS). Methods: Participants at high risk of type 2 diabetes mellitus were recruited from primary care (Leicestershire, UK). PA was measured using an ActiGraph accelerometer. Fasting and postchallenge glucose and insulin levels were assessed using an oral glucose tolerance test. IS was calculated using the Matsuda-IS and the HOMA-IS indices. Log-linear regression modeling was used to assess the relationship between PA intensity, in increments of 500 counts per minute, with markers of IS. Models were controlled for known confounders. Results: Complete data were available for 569 participants. PA intensity was favorably associated with fasting and 2 h of insulin and IS, with the association increasing in magnitude with each increment of 500 counts per minute. Differences in HOMA-IS per 10 min of PA ranged from 12.4% (95% confidence interval = 3.7%-21.8%) to 26.8% (11.0%-44.7%) within the moderate-intensity PA category (from 2000-2499 to 3500-3999 counts per minute). For Matsuda-IS, these differences were 22.0% (10.3%-34.9%) and 34.7% (13.9%-59.3%), respectively. Significant associations for fasting insulin were no longer observed after controlling for body mass index, whereas differences associated with 2-h insulin and IS were attenuated but still significant. Conclusion: PA of any intensity may positively influence glucose regulation and insulin sensitivity in individuals at high risk of type 2 diabetes mellitus in a dose-response manner. Further research is required to identify the intensity thresholds at which clinically relevant benefits occur in this population. [ABSTRACT FROM AUTHOR]

Lameness is an important health, welfare and economic problem in sheep flocks and early treatment is key to controlling lameness. Biologging technology provides high-resolution, continuous data that offers a novel opportunity to detect lameness either directly or by identifying behavioural changes; either option would facilitate more rapid treatment of lame sheep than visual observation. Here, the role of biologging data to identify lame sheep through behavioural changes within and between sheep is investigated. Accelerometers and proximity sensors were fitted to a flock of 50 Poll Dorset ewes rearing 32 single and 36 twin lambs, in Devon, UK in October 2019. Accelerometers were used to identify standing time and classify behaviour into four states for ewes (inactive, ruminating, grazing, walking) and three for lambs (inactive, sucking, moving). Principal components analysis reduced these behaviours to two components, 'feeding' and 'inactive' for ewes, and 'inactive' and 'feeding' for lambs. A visual locomotion score of each sheep was used each day to assess lameness. Complete records from sensors and locomotion observations were obtained for 513 days of ewe-activity and 720 days of lamb-activity (40 ewes, 26 single-raised and 28 twin-raised lambs). Linear mixed effects models were used to assess the effect of lameness adjusted for covariates age, litter size, social behaviour, environment and climate on standing time and the principal components. Lame ewes stood less, spent less time grazing and were more inactive than non-lame ewes. Lame lambs also stood less and were more inactive than non-lame lambs. Lambs with severely lame dams were also more inactive than those with non-lame dams. In conclusion, it is possible to identify behavioural differences between lame and non-lame ewes and lambs which could help enable automated early warning of lameness and consequently early treatment of lameness, and improved sheep welfare. • Biologging technology identified behavioural differences between lame and non-lame sheep. • Lame ewes and lambs stand less and are more inactive compared with non-lame animals. • Lame ewes graze less than non-lame ewes. [ABSTRACT FROM AUTHOR]

Background: Older adults have low physical activity(PA) and high sedentary behaviour(SB) levels. We investigate how total volume and specific patterns of moderate to vigorous PA(MVPA), light PA(LPA) and SB are related to adiposity and metabolic syndrome (MS). Then, with reference to physical activity guidelines which encourage MVPA in bouts > =10 min and avoiding “long” sedentary bouts, we investigate whether accumulating PA and SB in bouts of different defined durations are differently associated with these outcomes. Methods: Cross-sectional study of men (71-91 years) recruited in UK primary care centres. Nurses made physical measures (weight, height, bio-impedance, blood pressure) and took fasting blood samples. 1528/3137 (49 %) surviving men had ≥3 valid days (≥600 min) accelerometer data. 450 men with pre-existing chronic disease were excluded. 1009/1078 (93.6 %) had complete covariate data. Results: Men (n = 1009, mean age 78.5(SD 4.7) years) spent 612(SD 83), 202(SD 64) and 42(SD 33) minutes in SB, LIPA and MVPA respectively. Each additional 30 min/day of SB and MVPA were associated with 0.32 (95 % CI 0.23, 0.40)Kg/m2 higher Body Mass Index (BMI) and −0.72(−0.93, −0.51) lower BMI Kg/m2 respectively. Patterns for waist circumference (WC), fat mass index (FMI), fasting insulin and MS were similar. MVPA in bouts lasting <10 min or ≥10 min duration were not associated differently with outcomes. In models adjusted for total MVPA, each minute accumulated in SB bouts lasting 1-15 min was associated with lower BMI −0.012 kg/m2, WC −0.029 cm, and OR 0.989 for MS (all p < 0.05), and coefficients for LPA bouts 1-9 min were very similar in separate models adjusted for total MVPA. Minutes accumulated in SB bouts 1-15 min and LPA bouts 1-9 min were correlated, r = 0.62. Conclusions: Objectively measured MVPA, LPA and SB were all associated with lower adiposity and metabolic risk. The beneficial associations of LPA are encouraging for older adults for whom initiating MVPA and maintaining bouts lasting ≥10 min may be particularly challenging. Findings that short bouts of LPA (1-9 min) and SB (1-15 min), but that all MVPA, not just MVPA accumulated in bouts ≥10 min were associated with lower adiposity and better metabolic health could help refine older adult PA guidelines. [ABSTRACT FROM AUTHOR]

Background: Older adults are the most inactive age group and self-reporting of activities may be complicated by age-related reductions in structured activities and misclassification or recall biases. We investigate the validity of simple questionnaires about sedentary behaviour (SB), (including the widely used proxy television (TV) viewing), and physical activity (PA) in comparison with objective measures. Methods: Community dwelling men aged 71-93 years, from a UK population-based cohort wore a GT3X accelerometer over the right hip for 7 days and self-completed a questionnaire including information about SB (TV, reading, computer use and car use) and PA (leisure and sporting domains). Results: 1566/3137 surviving men (mean age 79 years) attended. 1377 ambulatory men provided questionnaire and accelerometer data. Questionnaires under-estimated mean daily sedentary time; 317 minutes total SB (TV, computer use, reading or driving), 176 minutes (TV) vs 619 minutes (objectively measured). Correlations between objective measures and self-reports were 0.18 (total SB) and 0.17 (TV), both P < 0.001. Objective SB levels were similar across the lowest three quartiles of self-reported SB but raised in the highest quartile. Correlations between steps/day or moderate to vigorous PA with self-reported total PA were both 0.49, P < 0.001 and measured PA levels were progressively higher at higher levels of self-reported PA. Conclusions: Among older men, simple SB questions performed poorly for identifying total SB time, although simple PA questions were associated with a graded increase with objectively measured PA. Future studies of health effects of SB in older men would benefit from objective measures of SB. [ABSTRACT FROM AUTHOR]

Background: The reported lower physical activity (PA) levels of British South Asians (SA) are suggested as a key influence in their increased risk of non-communicable diseases compared to their White British peers. Differences in objectively measured PA and sedentary behaviour (SB) between these ethnic groups have been observed during childhood (ages: 8-10 years). However, no information exists on objectively measured PA/SB in younger children, or how early in life differences in these behaviours emerge. Assessing PA/SB in the Born in Bradford (BIB) cohort study provides an opportunity to address such gaps in the literature, but previous studies have found recruiting and retaining SA participants challenging, and the feasibility of using accelerometers with SA children and parents is unknown. This study investigated the feasibility of recruiting and objectively measuring the habitual PA/SB of 2-3 year old SA and White British children and parents from the BIB study.Methods: Families were informed about the study during routine BIB assessments. Consenting families were visited at home for anthropometry measurements, interviews, material delivery and collection. Participants (child and parents) were instructed to wear the ActiGraph GT3X+ for 8 days. Descriptive statistics were computed, and ethnic differences tested (Chi-square) for recruitment uptake and compliance.Results: 160 families (30 % SA) provided contact details, and 97 (22 % SA) agreed to enter the study. White British families showed lower refusal and higher intake into the study than SA (p = 0.006). Of 89 children issued with an accelerometer, 34 % complied with the 8-day protocol (significantly less SA; p = 0.015) and 75 % provided enough days (≥ 3) to assess habitual PA/SB (no ethnic differences). Parental rates of compliance with the protocol did not differ between ethnicities. Issues experienced with the protocol and accelerometer use, and successful implementation strategies/procedures are presented.Conclusions: Although greater efforts may be required to recruit SA, those consenting to participate were as likely as White British to provide enough data to assess habitual PA/SB. The issues and successful strategies reported in this feasibility study represent valuable information for planning future studies, and enhance recruitment and compliance with accelerometer protocols in SA and White British toddlers and parents. [ABSTRACT FROM AUTHOR]

Background: Physical activity (PA) has many health benefits but may increase falls risk among older adults. We study how objectively measured habitual daily PA is related to falls by exploring the modifying effect of mobility limitations and the mediating roles of fitness and lower-limb strength. Methods: One thousand six hundred fifty-five (53%) of 3137 surviving participants (men age 71-91 yr) in an ongoing UK-population-based cohort study wore an ActiGraph GT3x accelerometer over the hip for 1 wk in 2010-2012 to measure PA (exposure) and reported demographic and health status, including mobility limitations. One year later, 825 men reported falls history (outcome). Results: Seven hundred of 825 men had ≥600 min·d-1 of accelerometer wear for ≥3 d. Nineteen percent (n = 128) reported falls 1 yr later. Associations between PA and falls differed by presence of mobility limitations. Among 66% (n = 471) of men without mobility limitations, number of falls increased incrementally (for every 30 min of moderate to vigorous PA [MVPA]: incidence rate ratio [IRR], 1.50; 95% confidence interval [CI], 1.10-2.03, adjusted for falls risk factors). Step count was not related to number of falls below 9000 steps per day but was related to number of falls ≥9000 steps per day (for every additional 1000 steps per day: IRR, 1.59; 95% CI, 1.16-2.18). Among 33% (n = 229) of men with mobility limitations, falls risk declined with increasing activity (for every 1000 steps per day: IRR, 0.80; 95% CI, 0.70-0.91; for every 30 min of MVPA: IRR, 0.61; 95% CI, 0.42-0.89; for every additional 30 min of sedentary behavior ≥600 min·d-1: IRR, 1.22; 95% CI, 1.07-1.40). Conclusions: Interventions to promote MVPA in older men should incorporate falls prevention strategies. Among adults with mobility limitations, trials should investigate whether increasing MVPA levels can reduce falls risk. [ABSTRACT FROM AUTHOR]

Background: Physical activity (PA) levels among older adults are generally low and sedentary behaviour (SB) very common; increasing PA and reducing SB levels could have appreciable health benefits. Quantifying PA and SB patterns through the day could help in defining strategies for change. We examined within day variations in PA and SB and whether these varied by demographic factors and health status. Methods: Men aged 71-91 years participating in an established UK population-based cohort study were invited to wear a GT3x Actigraph accelerometer over the hip for one week in 2010-12. Percentages of time spent in sedentary (SB, <100 counts per minute [CPM]); in light (LIPA, 100-1040 CPM) and in moderate to vigorous PA (MVPA, >1040 CPM) were derived. Multilevel models were used to estimate the associations between demographic factors and health status and SB, LIPA and MVPA. Results: 1455 of 3137 men invited (46.4 %) participated and provided adequate data. Men spent 73 % of the day in SB, 23 % in LIPA and 4.5 % in MVPA (619, 197 and 39 min per day respectively). The percentage of time spent in MVPA was highest in the morning, peaking at 10-11 am (8.4 %), and then declining until the evening, with the exception of a small increase at 2-3 pm. LIPA followed a similar pattern. Conversely, SB levels were lowest in the morning and increased throughout the day, peaking at 9 pm (88 %). Men who were older, did not use active transport, had mobility limitations, were obese, depressed, had more chronic health conditions, and were smokers had lower levels of MVPA. The impacts of older age, obesity, mobility limitations and chronic diseases on LIPA,MVPA and SB were more marked in the morning than in the afternoon and evening. Conclusions: Levels of MVPA and LIPA are highest in the morning (peak at 10-11 am) and decrease during the day. SB increases through the course of the day to peak in the evening. Interventions to encourage older men to be physically active may need to take account of current PA patterns, aiming to prolong active morning bouts of PA and/or reducing SB in the afternoon and evening hours. [ABSTRACT FROM AUTHOR]

Background: Despite the health benefits of physical activity, data from the UK suggest that a large proportion of adolescents do not meet the recommended levels of moderate-to-vigorous physical activity (MVPA). This is particularly evident in girls, who are less active than boys across all ages and may display a faster rate of decline in physical activity throughout adolescence. The 'Girls Active' intervention has been designed by the Youth Sport Trust to target the lower participation rates observed in adolescent girls. 'Girls Active' uses peer leadership and marketing to empower girls to influence decision making in their school, develop as role models and promote physical activity to other girls. Schools are provided with training and resources to review their physical activity, sport and PE provision, culture and practices to ensure they are relevant and attractive to adolescent girls. Methods/Design: This study is a two-arm cluster randomised controlled trial (RCT) aiming to recruit 20 secondary schools. Clusters will be randomised at the school level (stratified by school size and proportion of Black and Minority Ethnic (BME) pupils) to receive either the 'Girls Active' intervention or carry on with usual practice (1:1). The 20 secondary schools will be recruited from state secondary schools within the Midlands area. We aim to recruit 80 girls aged 11-14 years in each school. Data will be collected at three time points; baseline and seven and 14 months after baseline. Our primary aim is to investigate whether 'Girls Active' leads to higher objectively measured (GENEActiv) moderate-tovigorous physical activity in adolescent girls at 14 months after baseline assessment compared to the control group. Secondary outcomes include other objectively measured physical activity variables, adiposity, physical activity-related psychological factors and the cost-effectiveness of the 'Girls Active' intervention. A thorough process evaluation will be conducted during the course of the intervention delivery. Discussion: The findings of this study will provide valuable information on whether this type of school-based approach to increasing physical activity in adolescent girls is both effective and cost-effective in the UK. [ABSTRACT FROM AUTHOR]

Background: The steep decline in physical activity (PA) among the oldest old is not well understood; there is little information about the patterns of change in PA and sedentary behaviour (SB) in older people. Longitudinal data on objectively measured PA data can give insights about how PA and SB change with age. Methods: Men age 70-90 yr, from a United Kingdom population-based cohort wore a GT3X accelerometer over the hip annually on up to three occasions (56%, 50%, and 51% response rates) spanning 2 yr. Multilevel models were used to estimate change in activity. Men were grouped according to achieving ≥150 min·wk-1 o f MVPA in bouts o f ≥10 min (current guidelines) at two or three time points. Results: A total of 1419 ambulatory men had ≥600 min wear time on ≥3 d at ≥2 time points. At baseline, men took 4806 steps per day and spent 72.5% o f their day in SB, 23.1% in light PA, and 4.1% in moderate-to-vigorous PA (MVP A). Mean change per year was -341 steps,+1.1% SB, -0.7% light PA, and -0.4% MVPA each day (all P<0.001). A total of 76.3%(n = 1083) never met guidelines (“stable low”), 7.9% (n = 112) consistently met guidelines (“stable high”), 8.2% (n = 116) stopped meeting guidelines by the last occasion (“decreasers”), and 4.9% (n = 69) started meeting guidelines by the last occasion (“increasers”). “Decreasers” spent 69.3% o f each day in SB at baseline, which increased by 2% per year (P < 0.005), light activity remained at 23.3% (change, -0.2% per year; P = 0.4), and total MVPA decreased from 7.1% by -1.7% per year, (P < 0.001). The number o f sedentary bouts >30 min increased from 5.1 by 0.1 per year (P = 0.02). Conclusions: Among older adults, the steep decline in total PA occurred because of reductions in MVPA, while light PA is relatively spared and sedentary time and long sedentary bouts increase. [ABSTRACT FROM AUTHOR]

Accelerometers provide detailed data about physical activity (PA) across the full intensity spectrum. However, when examining associations with health, results are often aggregated to only a few summary measures [e.g. time spent "sedentary" or "moderate-to-vigorous" intensity PA]. Using multivariate pattern analysis, which can handle collinear exposure variables, we examined associations between the full PA intensity spectrum and cardiometabolic risk (CMR) in a population-based sample of middle-aged to older adults. Participants (n = 3660; mean ± SD age = 69 ± 8y and BMI = 26.7 ± 4.2 kg/m2; 55% female) from the EPIC-Norfolk study (UK) with valid accelerometry (ActiGraph-GT1M) data were included. We used multivariate pattern analysis with partial least squares regression to examine cross-sectional multivariate associations (r) across the full PA intensity spectrum [minutes/day at 0-5000 counts-per-minute (cpm); 5 s epoch] with a continuous CMR score (reflecting waist, blood pressure, lipid, and glucose metabolism). Models were sex-stratified and adjusted for potential confounders. There was a positive (detrimental) association between PA and CMR at 0-12 cpm (maximally-adjusted r = 0.08 (95%CI 0.06-0.10). PA was negatively (favourably) associated with CMR at all intensities above 13 cpm ranging between r = -0.09 (0.07-0.12) at 800-999 cpm and r = -0.14 (0.11-0.16) at 75-99 and 4000-4999 cpm. The strongest favourable associations were from 50 to 800 cpm (r = 0.10-0.12) in men, but from ≥2500 cpm (r = 0.18-0.20) in women; with higher proportions of model explained variance for women (R2 = 7.4% vs. 2.3%). Most of the PA intensity spectrum was beneficially associated with CMR in middle-aged to older adults, even at intensities lower than what has traditionally been considered "sedentary" or "light-intensity" activity. This supports encouragement of PA at almost any intensity in this age-group. [ABSTRACT FROM AUTHOR]

The socioecological approach emphasises that health promotion should focus on a variety of factors that surround individuals simultaneously, yet there is little evidence on how these factors relatively affect physical activity (PA). The main objective was to identify relevant determinants of PA by examining the associations between factors within multilayered socioecological categories and PA. A prospective analysis was conducted with 84,052 participants participating in the accelerometer measurement from the UK Biobank. Time spent in moderate-to-vigorous PA (MVPA) was calculated from participants who wore a wrist-worn accelerometer for seven days; a questionnaire-based self-reported leisure-time physical activity was also assessed. A categorical principal component analysis was conducted to reduce the dimensions of 184 variables. The associations between principal components (PCs) and PA were evaluated using general linear models. A network of PCs was constructed to assess the comprehensive association with PA. PCs related to body composition and chronic diseases were suggested as key determinants of objectively measured MVPA and found to be clustered in the network. PCs related to body composition and socio-economic status were proposed as the key regulatory hubs in the network because they exhibited the highest level of indirect linkages with other components. In the environmental category, PCs related to greenness and air pollution were revealed to be key factors in the self-reported walking for pleasure. Using a socioecological approach, it was discovered that obesity and disease-related factors were the most important determinants, and they had an integrative influence with other factors in different categories. [ABSTRACT FROM AUTHOR]

Background: Physical activity is important for childre's health, but successful physical activity promotion is challenging. Whether performing many different types of activities (Variety) is associated with higher physical activity independent of the number of activity sessions (Frequency) is unknown, but this information could inform physical activity promotion and public health strategies in children. Methods: In the SPEEDY study we measured moderate-to-vigorous intensity physical activity (MVPA; =2000 counts/minute) over 7 days using GT1M Actigraph accelerometers in 1700 children from Norfolk, UK (56% girls, Mean ± SD 10.3 ± 0.3 years-old). Children reported participation in 28 leisure-time activities over the previous 7 days. Sex differences in activity participation were assessed using multilevel logistic regression, clustered by school. Associations of log-transformed MVPA with z-score-Variety (number of different activities/week) and z-score-Frequency (sum of all activity sessio/;week) were examined using multilevel linear regression, adjusted for age, sex, parental education and age-standardised BMI. Results: Children';s activity participation often reflected gender stereotypes. Mean ± SD Variety was 10.8 ± 5.0 activities/ek, and Frequency was 24.2±15.0 sessions/week. In separate models lnMVPA had similar strength, positive associations with z-score-Variety and z-score-Frequency (Exp ß(95% CI); Variety 1.04(1.02-1.06), Frequency 1.04(1.02-1.06)). lnMVPA was not associated with z-score-Variety independent of z-score-Frequency (Variety 1.01 (0.98-1.04), Frequency 1.03(1.00-1.06)). Conclusions: Future physical activity interventions and public health strategies could allow for gender specific activity preferences and could target both Variety and Frequency of activities participated in by children. [ABSTRACT FROM AUTHOR]

Many researchers are beginning to adopt the use of wrist-worn accelerometers to objectively measure personal activity levels. Data from these devices are often used to summarise such activity in terms of averages, variances, exceedances, and patterns within a profile. In this study, we report the development of a clustering utilising the whole activity profile. This was achieved using the robust clustering technique of k-medoids applied to an extensive data set of over 90,000 activity profiles, collected as part of the UK Biobank study. We identified nine distinct activity profiles in these data, which captured both the pattern of activity throughout a week and the intensity of the activity: "Active 9 to 5", "Active", "Morning Movers", "Get up and Active", "Live for the Weekend", "Moderates", "Leisurely 9 to 5", "Sedate" and "Inactive". These patterns are differentiated by sociodemographic, socioeconomic, and health and circadian rhythm data collected by UK Biobank. The utility of these findings are that they sit alongside existing summary measures of physical activity to provide a way to typify distinct activity patterns that may help to explain other health and morbidity outcomes, e.g., BMI or COVID-19. This research will be returned to the UK Biobank for other researchers to use. [ABSTRACT FROM AUTHOR]

Summary: In a free-living cohort of 4-year old children, mean daily time in moderate-vigorous physical activity and daily calcium intake at 3 years, were positively related to hip bone size and density. Relationships between physical activity and bone indices were stronger when calcium intake was above compared with below median (966 mg/day). Introduction: We examined the cross-sectional relationships between childhood physical activity, dietary calcium intake and bone size and density. Methods: Children aged 4 years were recruited from the Southampton Women's Survey. They underwent measurement of bone mass by DXA (Hologic Discovery). Physical activity was assessed by accelerometry (Actiheart, Cambridge Neurotechnology Ltd, Cambridge, UK) for seven continuous days. Results: Four hundred twenty-two children (212 boys) participated. In a cross-sectional analysis, after adjusting for gender, daily mean time(minutes per day) spent in moderate to very vigorous activity (MVPA) was positively related to hip BA ( R = 3%, p < 0.001), BMC ( R = 4%, p < 0.001), aBMD ( R = 3%, p = 0.001) and estimated vBMD ( R = 2%, p = 0.01), but not height ( r = 0.04, p = 0.42) or weight ( r = 0.01, p = 0.76). Mean daily calcium intake (assessed at 3 years old) positively predicted bone indices in those with a calcium intake below the median (966 mg/day), but there was a much attenuated relationship in those above this. These associations persisted after inclusion of total energy, protein and phosphorus in multivariate models. The relationships between MVPA and bone indices were stronger in children with calcium intakes above the median. Thus, for aBMD, the variance explained by MVPA when daily calcium intake was below the median was 2% ( p = 0.1) and above median was 6% ( p = 0.001). Conclusions: These results support the notion that adequate calcium intake may be required for optimal action of physical activity on bone development and that improving levels of physical activity and calcium intake in childhood may help to optimise accrual of bone mass. [ABSTRACT FROM AUTHOR]

The article presents a study on the use a miniature lightweight ear-worn sensor for evaluating energy expenditure (EE) estimation in healthy adults during normal and sporting activities. It describes the methodology of the study that was conducted on 25 healthy subjects who were asked to perform a protocol of 11 activities, including walking, running, and cycling, wearing the ear sensor. The study reveals the findings of the ear sensor regarding EE of various activities and concludes that the device is useful for predicting EE for a wide range of activities without any behavior interference.

Abstract: Despite the known health benefits, the majority of children do not meet physical activity guidelines, with past interventions to increase physical activity yielding little success. Social and friendship networks have been shown to influence obesity, smoking and academic achievement, and peer-led interventions have successfully reduced the uptake of adolescent smoking. However, the role of social networks on physical activity is not clear. This paper investigates the extent to which friendship networks influence children’s physical activity, and attempts to quantify the association using spatial analytical techniques to account for the social influence. Physical activity data were collected for 986 children, aged 10–11 years old, from 40 schools in Bristol, UK. Data from 559 children were used for analysis. Mean accelerometer counts per minute (CPM) and mean minutes of moderate to vigorous physical activity per day (MVPA) were calculated as objective measures of physical activity. Children nominated up to 4 school-friends, and school-based friendship networks were constructed from these nominations. Networks were tested to assess whether physical activity showed spatial dependence (in terms of social proximity in social space) using Moran’s I statistic. Spatial autoregressive modelling was then used to assess the extent of spatial dependence, whilst controlling for other known predictors of physical activity. This model was compared with linear regression models for improvement in goodness-of-fit. Results indicated spatial autocorrelation of both mean MVPA (I = .346) and mean CPM (I = .284) in the data, indicating that children clustered in friendship groups with similar activity levels. Spatial autoregressive modelling of mean MVPA concurred that spatial dependence was present (ρ = .26, p < .001), and improved model fit by 31% on the linear regression model. These results demonstrate an association between physical activity levels of children and their school-friends, and indicate that spatial modelling is an informative method for incorporating the influence of school social structure into physical activity analysis. [Copyright &y& Elsevier]

Objective: The school-setting is a potentially important environment for influencing children's physical activity. However limited research has focused on whether children's school-time physical activity is associated with the school they attend. This paper investigates the school effect on children's physical activity. Method: Participants were 1307 pupils aged 10–11 years recruited from 23 primary schools in Bristol, UK during 2006–2008. Multilevel modelling (MLM) (MLwin 2.02) was used to asses between school differences in children's physical activity, measured using accelerometry (ActiGraph GT1M), adjusting for both individual and school variables. Results: A significant school effect (p =0.001) was found accounting for 14.5% of the total variance in physical activity. Boys were significantly more active than girls (p <0.001), and the school attended accounted for a greater proportion of variance in boys'' physical activity than girls'' (23.4% vs. 12.2%). Seasonal variation and economic deprivation of the school neighbourhood were both significantly associated with children's school-time activity. Conclusion: This paper highlights a significant school effect on children's physical activity providing evidence that the school attended should be accounted for in future analysis and supporting the use of MLM in this field. Further investigation is required to explain the differences in physical activity found between schools. [Copyright &y& Elsevier]

To: a) identify motivational profiles for exercise, using Self-Determination Theory as a theoretical framework, among a sample of parents of UK primary school children; b) explore the movement between motivational profiles over a five year period; and c) examine differences across these profiles in terms of gender, physical activity and BMI. Data were from the B-Proact1v cohort. 2555 parents of British primary school children participated across three phases when the child was aged 5–6, 8–9, and 10–11. Parents completed a multidimensional measure of motivation for exercise and wore an ActiGraph GT3X + accelerometer for five days in each phase. Latent profile and transition analyses were conducted using a three-step approach in MPlus. Six profiles were identified, comprising different combinations of motivation types. Between each timepoint, moving between profiles was more likely than remaining in the same one. People with a more autonomous profile at a previous timepoint were unlikely to move to more controlled or amotivated profiles. At all three timepoints, more autonomous profiles were associated with higher levels of MVPA and lower BMI. The results show that people's motivation for exercise can be described in coherent and consistent profiles which are made up of multiple and simultaneous types of motivation. More autonomous motivation profiles were more enduring over time, indicating that promoting more autonomous motivational profiles may be central to facilitating longer-term physical activity engagement. • Six qualitatively different profiles of motivation for exercise were identified. • More autonomous profiles were associated with higher accelerometer estimated MVPA. • Movement between profiles was dynamic and more autonomous profiles were more stable. • Personal value and enjoyment of exercise appear to persist over time. [ABSTRACT FROM AUTHOR]

The lack of healthcare staff and increasing proportions of elderly population is alarming. The traditional means to look after elderly has resulted in 255,000 reported falls (only within UK). This not only resulted in extensive aftercare needs and surgeries (summing up to £4.4 billion) but also in added suffering and increased mortality. In such circumstances, the technology can greatly assist by offering automated solutions for the problem at hand. The proposed work offers an Internet of things (IoT) based patient bed-exit monitoring system in clinical settings, capable of generating a timely response to alert the healthcare workers and elderly by analyzing the wireless data streams, acquired through wearable sensors. This work analyzes two different datasets obtained from divergent families of sensing technologies, i.e., smartphone-based accelerometer and radio frequency identification (RFID) based accelerometer. The findings of the proposed system show good efficacy in monitoring the bed-exit and discriminate other ambulating activities. Furthermore, the proposed work manages to keep the average end-to-end system delay (i.e., communications of sensed data to Data Sink (DS)/Control Center (CC) + machine-based feature extraction and class identification + feedback communications to a relevant healthcare worker/elderly) below 1 10 th of a second. [ABSTRACT FROM AUTHOR]

Background: Increases in physical activity through active travel have the potential to have large beneficial effects on populations, through both better health outcomes and reduced motorized traffic. However accurately identifying travel mode in large datasets is problematic. Here we provide an open source tool to quantify time spent stationary and in four travel modes(walking, cycling, train, motorised vehicle) from accelerometer measured physical activity data, combined with GPS and GIS data. Methods: The Examining Neighbourhood Activities in Built Living Environments in London study evaluates the effect of the built environment on health behaviours, including physical activity. Participants wore accelerometers and GPS receivers on the hip for 7 days. We time-matched accelerometer and GPS, and then extracted data from the commutes of 326 adult participants, using stated commute times and modes, which were manually checked to confirm stated travel mode. This yielded examples of five travel modes: walking, cycling, motorised vehicle, train and stationary. We used this example data to train a gradient boosted tree, a form of supervised machine learning algorithm, on each data point (131,537 points), rather than on journeys. Accuracy during training was assessed using five-fold cross-validation. We also manually identified the travel behaviour of both 21 participants from ENABLE London (402,749 points), and 10 participants from a separate study (STAMP-2, 210,936 points), who were not included in the training data. We compared our predictions against this manual identification to further test accuracy and test generalisability. Results: Applying the algorithm, we correctly identified travel mode 97.3% of the time in cross-validation (mean sensitivity 96.3%, mean active travel sensitivity 94.6%). We showed 96.0% agreement between manual identification and prediction of 21 individuals' travel modes (mean sensitivity 92.3%, mean active travel sensitivity 84.9%) and 96.5% agreement between the STAMP-2 study and predictions (mean sensitivity 85.5%, mean active travel sensitivity 78.9%). Conclusion: We present a generalizable tool that identifies time spent stationary and time spent walking with very high precision, time spent in trains or vehicles with good precision, and time spent cycling with moderate precisionIn studies where both accelerometer and GPS data are available this tool complements analyses of physical activity, showing whether differences in PA may be explained by differences in travel mode. All code necessary to replicate, fit and predict to other datasets is provided to facilitate use by other researchers. [ABSTRACT FROM AUTHOR]