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Background: Evidence on the prevalence, determinants, and health outcomes of physical activity in disabled people is limited. It is possible that the limited availability of high-quality scientific evidence is due to the extent and nature of disability assessment in physical activity research. This scoping review explores how disability has been measured in epidemiological studies that included accelerometer-based measurement of physical activity. Methods: Data sources: MEDLINE (Ovid), Embase, PsychINFO, Health Management Information Consortium, Web of Science, SPORTDiscus, and CINAHL. Eligibility criteria: Prospective and cross-sectional studies that included an accelerometer measurement of physical activity. Survey instruments used in these studies were obtained, and questions relating to the International Classification of Functioning, Disability and Health domains of (1) health conditions, (2) body functions and structures, and (3) activities and participation, were extracted for analysis. Results: Eighty-four studies met the inclusion criteria, from which complete information on the 3 domains was obtained for 68. Seventy-five percent of studies (n = 51) captured whether a person had at least one health condition, 63% (n = 43) had questions related to body functions and structures, and 75% (n = 51) included questions related to activities and participation. Conclusion: While most studies asked something about one of the 3 domains, there was substantial diversity in the focus and style of questions. This diversity indicates a lack of consensus on how these concepts should be assessed, with implications for the comparability of evidence across studies and subsequent understanding of the relationships between disability, physical activity, and health.

Background: Temporal changes in sedentary behavior patterns reflect the evolving nature of our built and social environments, particularly the expanding availability of electronic media. It is important to understand what types of sedentary behavior are assessed in national surveillance to determine whether, and to what extent, they reflect contemporary patterns. The aims of this review were to describe the characteristics of questionnaires used for national surveillance of sedentary behavior and to identify the types of sedentary behaviors being measured. Method: We reviewed questionnaires from national surveillance systems listed on the Global Observatory for Physical Activity (GoPA!) country cards to locate items on sedentary behavior. Questionnaire characteristics were categorized using the Taxonomy of Self-reported Sedentary Behavior Tools (TASST). The purpose and type of sedentary behaviors captured were classified using the Sedentary Behavior International Taxonomy (SIT). Results: Overall, 346 surveillance systems were screened for eligibility, of which 93 were included in this review. Most questionnaires used a single-item direct measure of sitting time (n = 78, 84%). Work and domestic were the most frequently captured purposes of sedentary behavior, while television viewing and computer use were the most frequently captured types of behaviors. Conclusion: National surveillance systems should be periodically reviewed in response to evidence on contemporary behavior patterns in the population and the release of updated public health guidelines.

Background Screen behaviours are highly prevalent in adolescents and may be adversely associated with physical and mental health. Understanding how screen behaviours inter-relate with physical activity and sleep may help to clarify pathways through which they impact health and potential routes to behaviour change. This cross-sectional study examines the association of contemporary screen behaviours with physical activity, sedentary behaviour and sleep in adolescents. Method Data are from sweep 6 (2015/2016) of the Millennium Cohort Study, conducted when participants were aged 14 years. Outcome variables were accelerometer-assessed overall physical activity and moderate-to-vigorous physical activity (MVPA), self-reported sedentary behaviour and sleep duration. Screen behaviours were assessed using a 24-h time-use diary. Multivariable regression was used to examine the association between screen behaviours and each outcome variable separately for weekdays and weekend days. Results The use of social network sites was associated with (beta coefficient, 95% confidence interval (CI); minutes/day) less time in MVPA (weekdays: − 5.2 (− 10.3, − 0.04); weekend: − 10.0 (− 15.5, − 4.5)), and sedentary behaviours (weekdays: − 19.8 (− 31.0, − 8.6); weekend: − 17.5 (− 30.9, − 4.1)). All screen behaviours were associated with shorter sleep duration on weekdays, whereas only the use of email/texts and social network sites was associated with shorter sleep duration on weekend days. The association of using social network sites with overall physical activity was stronger in girls than in boys; the association of internet browsing with sedentary behaviour was stronger in boys than in girls. Conclusion Intervention strategies to enhance MVPA and sleep duration by limiting screen-based activities may be warranted.

Screen behaviours are highly prevalent in adolescents and may be adversely associated with physical and mental health. Understanding how screen behaviours inter-relate with physical activity and sleep may help to clarify pathways through which they impact health and potential routes to behaviour change. This cross-sectional study examines the association of contemporary screen behaviours with physical activity, sedentary behaviour and sleep in adolescents.Data are from sweep 6 (2015/2016) of the Millennium Cohort Study, conducted when participants were aged 14 years. Outcome variables were accelerometer-assessed overall physical activity and moderate-to-vigorous physical activity (MVPA), self-reported sedentary behaviour and sleep duration. Screen behaviours were assessed using a 24-h time-use diary. Multivariable regression was used to examine the association between screen behaviours and each outcome variable separately for weekdays and weekend days.The use of social network sites was associated with (beta coefficient, 95% confidence interval (CI); minutes/day) less time in MVPA (weekdays: - 5.2 (- 10.3, - 0.04); weekend: - 10.0 (- 15.5, - 4.5)), and sedentary behaviours (weekdays: - 19.8 (- 31.0, - 8.6); weekend: - 17.5 (- 30.9, - 4.1)). All screen behaviours were associated with shorter sleep duration on weekdays, whereas only the use of email/texts and social network sites was associated with shorter sleep duration on weekend days. The association of using social network sites with overall physical activity was stronger in girls than in boys; the association of internet browsing with sedentary behaviour was stronger in boys than in girls.Intervention strategies to enhance MVPA and sleep duration by limiting screen-based activities may be warranted.

Exposure to natural environments, known as greenspace, appears to positively influence health, yet the mechanisms are unclear. Given that gut microbiota are associated with inflammatory disorders more prevalent in urban areas and individuals with lower greenspace exposure, microbiota may act as a mediator between greenspace and health. Using 2443 participants of the TwinsUK cohort, microbiota differences were compared in relation to rural/urban living and with quantiles of area-level greenspace at three different neighbourhood distances: 800 m, 3000 m and 5000 m. Using microbiota data captured from faecal samples using 16S rRNA marker gene sequencing, small compositional differences in association with 3000 m greenspace (p = 0.003) in models adjusted for confounders of microbiota variance (sequencing depth, antibiotics use, body mass index, frailty, age, diet, region and socioeconomic variables) were observed. Differences in abundances of genus were observed for all measures of greenspace in adjusted models; a key pathogenic genus was increased in abundance in association with urbanicity (Escherichia/Shigella, logFC = 0.73742, padj

Many adults accumulate considerable time in screen-based behaviours, some of which have been associated with negative physical and psychological health outcomes. The aims of this study were to characterise contemporary patterns of screen-based behaviours and describe their temporal trends by global region, age, sex and education. Data covering the period 2012-2019 were obtained in aggregated form from GWI (previously known as Global Web Index), a global market research company. Temporal trends in the duration of adults' (16-64 years) self-reported personal computer, laptop and tablet use, mobile phone use, broadcast television viewing, online television viewing and games console use were described using data from over 2 million participants from 46 countries. For each activity, participants selected from response options ranging from less than 30 min to more than 10 h. Internationally, daily screen time increased from approximately 9 h in 2012 to 11 h in 2019, with notable increases in mobile phone use (approx. 2 h), online television viewing (approx. 37 min) and games console use (approx. 26 min). Differences were seen in the duration of time spent engaging in screen-based behaviours across regions and between socio-demographic groups, with Latin America, the Middle East and Africa and younger age groups seeing greater increases in overall screen time. The findings have important implications for health behaviour surveillance and for research exploring the links between screen-based behaviours and health.

$\textbf{Background}$ A wide range of environmental factors have been related to active ageing, but few studies have explored the impact of weather and day length on physical activity in older adults. We investigate the cross-sectional association between weather conditions, day length and activity in older adults using a population-based cohort in England, the European Prospective Investigation into Cancer and Nutrition (EPIC) Norfolk study. $\textbf{Methods}$ Physical activity was measured objectively over 7 days using an accelerometer and this was used to calculate daily total physical activity (counts per minute), daily minutes of sedentary behaviour and light, moderate and vigorous physical activity (LMVPA). Day length and two types of weather conditions, precipitation and temperature, were obtained from a local weather station. The association between these variables and physical activity was examined by multilevel first-order autoregressive modelling. $\textbf{Results}$ After adjusting for individual factors, short day length and poor weather conditions, including high precipitation and low temperatures, were associated with up to 10% lower average physical activity (p

Introduction: Increasing physical activity is associated with health benefits. Reduced physical activity has been noted in sarcoidosis, particularly where fatigue co-exists. Monitoring physical activity is possible with wrist-worn devices. This study compared two available devices to determine patient preference and compare wear-time, with a secondary outcome of comparing device outputs with fatigue scores. Methods: Patients with sarcoidosis wore two wrist-worn activity monitors (GENEActiv actiwatch and Actigraph GT3X-bt) separately for seven days each. Participants were randomly allocated to receive either device first. Participants completed the Fatigue Assessment Scale (FAS) questionnaire immediately before wearing the first device. All participants completed a questionnaire of their perception regarding each device after the wear period. Data from the devices was analysed for total wear time, time spent in moderate or vigorous activity (MVPA) and for time spent in sedentary behaviours. Results: Twelve patients with sarcoidosis were included. The GENEActiv device was preferred by ten (83.3%) participants. Wear time was greater with the GENEActiv device (1354 minutes/day vs 1079 minutes/day). Time spent in MVPA was slightly higher when recorded by the GENEActiv compared with the Actigraph. Moderately strong correlation was seen between FAS scores and sedentary time (r=-0.554), light activity (r=-0.585) and moderate activity (r=0.506). Discussion: A clear preference was demonstrated for the GENEActiv. This was reflected in higher wear time and suggests the device can be comfortably worn 24 hours per day. Data from this small cohort also suggests there is correlation between fatigue and activity scores in patients with sarcoidosis. (Sarcoidosis Vasc Diffuse Lung Dis 2018; 35: 62-68)

Accelerometer-based studies of children's physical activity have reported seasonal patterns in activity levels. However, the inability of many accelerometers to detect activity while the wearer is swimming or cycling may introduce a bias to the estimation of seasonality if participation in these activities are themselves seasonally patterned. We explore seasonal patterns in children's swimming and cycling among a sample of 7–8 year olds (N = 591) participating in the Millennium Cohort Study, UK. Participating children wore an accelerometer for one week on up to five occasions over the year and their parents completed a diary recording daily minutes spent swimming and cycling. Both swimming and cycling participation showed seasonal patterns, with 2.7 (SE 0.8) more minutes swimming and 5.7 (0.7) more minutes cycling performed in summer compared to winter. Adding swimming and cycling time to accelerometer-determined MVPA increased the summer-winter difference in MVPA from 16.6 (1.6) to 24.9 min. The seasonal trend in swimming and cycling appears to follow the same pattern as accelerometer-measured MVPA. Studies relying solely on accelerometers may therefore underestimate seasonal differences in children's activity., Highlights • Children's physical activity is higher in spring/summer relative to autumn/winter. • Accelerometers cannot detect activity while the wearer is swimming or cycling. • Parent-reported time spent swimming and cycling also varies seasonally. • Accelerometer-based studies may underestimate seasonal differences in activity.

Use of unplanned health care has long been increasing, and not enough is known about which interventions may reduce use. We aimed to review the effectiveness of interventions to reduce the use of unplanned health care by rural populations.The method used was systematic review. Scientific databases (Medline, Embase and Central), grey literature and selected references were searched. Study quality and bias was assessed using Cochrane Risk of Bias and modified Newcastle Ottawa Scales. Results were summarized narratively.A total of 2708 scientific articles, reports and other documents were found. After screening, 33 studies met the eligibility criteria, of which eight were randomized controlled trials, 13 were observational studies of unplanned care use before and after new practices were implemented and 12 compared intervention patients with non-randomized control patients. Eight of the 33 studies reported modest statistically significant reductions in unplanned emergency care use while two reported statistically significant increases in unplanned care. Reductions were associated with preventative medicine, telemedicine and targeting chronic illnesses. Cost savings were also reported for some interventions.Relatively few studies report on unscheduled medical care by specifically rural populations, and interventions were associated with modest reductions in unplanned care use. Future research should evaluate interventions more robustly and more clearly report the results.

Background This study examined whether objective measures of food, physical activity and built environment exposures, in home and non-home settings, contribute to children’s body weight. Further, comparing GPS and GIS measures of environmental exposures along routes to and from school, we tested for evidence of selective daily mobility bias when using GPS data. Methods This study is a cross-sectional analysis, using objective assessments of body weight in relation to multiple environmental exposures. Data presented are from a sample of 94 school-aged children, aged 5–11 years. Children’s heights and weights were measured by trained researchers, and used to calculate BMI z-scores. Participants wore a GPS device for one full week. Environmental exposures were estimated within home and school neighbourhoods, and along GIS (modelled) and GPS (actual) routes from home to school. We directly compared associations between BMI and GIS-modelled versus GPS-derived environmental exposures. The study was conducted in Mebane and Mount Airy, North Carolina, USA, in 2011. Results In adjusted regression models, greater school walkability was associated with significantly lower mean BMI. Greater home walkability was associated with increased BMI, as was greater school access to green space. Adjusted associations between BMI and route exposure characteristics were null. The use of GPS-actual route exposures did not appear to confound associations between environmental exposures and BMI in this sample. Conclusions This study found few associations between environmental exposures in home, school and commuting domains and body weight in children. However, walkability of the school neighbourhood may be important. Of the other significant associations observed, some were in unexpected directions. Importantly, we found no evidence of selective daily mobility bias in this sample, although our study design is in need of replication in a free-living adult sample. Electronic supplementary material The online version of this article (doi:10.1186/1476-072X-14-8) contains supplementary material, which is available to authorized users.

Objective To examine if individual risk of unplanned medical admissions (UMAs) was associated with municipality general practitioner (GP) or long-term care (LTC) volume among the entire Norwegian elderly population. Design Cross-sectional population-based study. Setting 428 of 430 Norwegian municipalities in 2009. Participants All Norwegians aged ≥65 years (n=721 915; 56% women—15% of the total population). Main outcome measure Individual risk of UMA. Results Using a multilevel analytical framework, consisting of individuals (N=722 464) nested within municipalities (N=428), nested within local hospital areas (N=52) we found no association between municipality GP or LTC volume and UMAs. However, we found that higher LTC levels of provision were associated with fewer hospitalisations among the older age groups. A modest geographical variability was observed for UMA in adjusted analysis. Conclusions A higher primary healthcare volume was only associated with fewer UMAs among the oldest old in a universally accessible healthcare system.