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Background: Previous research has reported associations between features of the residential built environment and physical activity but these studies have mainly been cross-sectional, limiting inference. This paper examines whether changes in a range of residential built environment features are associated with changes in measures of physical activity in adults. It also explores whether observed effects are moderated by socio-economic status., Methods: Data from the Examining Neighbourhood Activity in Built Living Environments in London (ENABLE London) study were used. A cohort of 1278 adults seeking to move into social, intermediate, and market-rent East Village accommodation was recruited in 2013-2015, and followed up after 2 years. Accelerometer-derived steps (primary outcome), and GIS-derived measures of residential walkability, park proximity and public transport accessibility were obtained both at baseline and follow-up. Daily steps at follow-up were regressed on daily steps at baseline, change in built environment exposures and confounding variables using multilevel linear regression to assess if changes in neighbourhood walkability, park proximity and public transport accessibility were associated with changes in daily steps. We also explored whether observed effects were moderated by housing tenure as a marker of socio-economic status., Results: Between baseline and follow-up, participants experienced a 1.4 unit (95%CI 1.2,1.6) increase in neighbourhood walkability; a 270 m (95%CI 232,307) decrease in distance to their nearest park; and a 0.7 point (95% CI 0.6,0.9) increase in accessibility to public transport. A 1 s.d. increase in neighbourhood walkability was associated with an increase of 302 (95%CI 110,494) daily steps. A 1 s.d. increase in accessibility to public transport was not associated with any change in steps overall, but was associated with a decrease in daily steps amongst social housing seekers (- 295 steps (95%CI - 595, 3), and an increase in daily steps for market-rent housing seekers (410 95%CI -191, 1010) (P-value for effect modification = 0.03)., Conclusion: Targeted changes in the residential built environment may result in increases in physical activity levels. However, the effect of improved accessibility to public transport may not be equitable, showing greater benefit to the more advantaged.

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.

Background: Physical inactivity increases the risk of many chronic diseases including coronary heart disease, type 2 diabetes and some cancers. It is recommended that adults should undertake at least 150 minutes of moderate intensity physical activity throughout the week but many adults do not achieve this. An opportunity for working adults to accumulate the recommended activity levels is through the daily commute., Methods: Employees will be recruited from workplaces in south-west England and south Wales. In the intervention arm, workplace Walk-to-Work promoters will be recruited and trained. Participating employees will receive Walk-to-Work materials and support will be provided through four contacts from the promoters over 10 weeks. Workplaces in the control arm will continue with their usual practice. The intervention will be evaluated by a cluster randomized controlled trial including economic and process evaluations. The primary outcome is daily minutes of moderate to vigorous physical activity (MVPA). Secondary outcomes are: overall physical activity; sedentary time; modal shift away from private car use during the commute; and physical activity/MVPA during the commute. Accelerometers, GPS receivers and travel diaries will be used at baseline and one year follow-up. Questionnaires will be used at baseline, immediately post intervention, and one year follow-up. The process evaluation will examine the context, delivery and response to the intervention from the perspectives of employers, Walk-to-Work promoters and employees using questionnaires, descriptive statistics, fieldnotes and interviews. A cost-consequence study will include employer, employee and health service costs and outcomes. Time and consumables used in implementing the intervention will be measured. Journey time, household commuting costs and expenses will be recorded using travel diaries to estimate costs to employees. Presenteeism, absenteeism, employee wellbeing and health service use will be recorded., Discussion: Compared with other forms of physical activity, walking is a popular, familiar and convenient, and the main option for increasing physical activity in sedentary populations. To our knowledge, this is the first full-scale randomised controlled trial to objectively measure (using accelerometers and GPS receivers) the effectiveness of a workplace intervention to promote walking during the commute to and from work., Trial Registration: ISRCTN15009100 (10 December 2014).

Using a sample of English schoolchildren, we evaluate whether a change in school local area environmental supportiveness between primary and secondary school is associated with changes in active travel behaviours and physical activity levels. Participant׳s activity levels and travel behaviours were recorded for a week during their primary school final year and secondary school first year. Environmental supportiveness was evaluated using a Geographical Information System. Children attending both a primary and secondary school with a more supportive local environment were more likely to maintain active travel behaviours than those with less supportive environments. However, no trends were apparent with change in school supportiveness and change in physical activity. Policies that focus on the maintenance and uptake of active travel behaviours may help maintain children׳s physical activity levels into adolescence., (Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: School travel mode and parenting practices have been associated with children's physical activity (PA). The current study sought to examine whether PA parenting practices differ by school travel mode and whether school travel mode and PA parenting practices are associated with PA., Methods: 469 children (aged 9-11) wore accelerometers from which mean weekday and after-school (3.30 to 8.30 pm) minutes of moderate-to-vigorous intensity PA (MVPA) and counts per minute (CPM) were derived. Mode of travel to and from school (passive vs. active) and PA parenting practices (maternal and paternal logistic support and modelling behaviour) were child-reported., Results: Children engaged in an average of 59.7 minutes of MVPA per weekday. Active travel to school by girls was associated with 5.9 more minutes of MVPA per day compared with those who travelled to school passively (p = 0.004). After-school CPM and MVPA did not differ by school travel mode. There was no evidence that physical activity parenting practices were associated with school travel mode., Conclusions: For girls, encouraging active travel to school is likely to be important for overall PA. Further formative research may be warranted to understand how both parental logistic support and active travel decisions are operationalized in families as a means of understanding how to promote increased PA among pre-adolescent children.

Objective: To objectively examine the contribution to adult physical activity levels of walking to work., Methods: Employees (n = 103; 36.3 ± 11.7 years) at 17 workplaces in south-west England, who lived within 2 miles (3.2 km) of their workplace, wore Actigraph accelerometers for seven days during waking hours and carried GPS receivers during the commute to and from work. Physical activity volume (accelerometer counts per minute (cpm)) and intensity (minutes of moderate to vigorous physical activity (MVPA)) were computed overall and during the walk to work., Results: Total weekday physical activity was 45% higher in participants who walked to work compared to those travelling by car (524.6. ± 170.4 vs 364.6 ± 138.4 cpm) and MVPA almost 60% higher (78.1 ± 24.9 vs 49.8 ± 25.2 minutes per day). No differences were seen in weekend physical activity, and sedentary time did not differ between the groups. Combined accelerometer and GPS data showed that walking to work contributed 47.3% of total weekday MVPA., Conclusions: Walking to work was associated with overall higher levels of physical activity in young and middle-aged adults. These data provide preliminary evidence to underpin the need for interventions to increase active commuting, specifically walking, in adults.

Background: To better understand the health benefits of promoting active travel, it is important to understand the relationship between a change in active travel and changes in recreational and total physical activity., Methods: These analyses, carried out in April 2012, use longitudinal data from 1628 adult respondents (mean age 54 years; 47% male) in the UK-based iConnect study. Travel and recreational physical activity were measured using detailed seven-day recall instruments. Adjusted linear regression models were fitted with change in active travel defined as 'decreased' (<-15 min/week), 'maintained' (± 15 min/week) or 'increased' (>15 min/week) as the primary exposure variable and changes in (a) recreational and (b) total physical activity (min/week) as the primary outcome variables., Results: Active travel increased in 32% (n=529), was maintained in 33% (n=534) and decreased in 35% (n=565) of respondents. Recreational physical activity decreased in all groups but this decrease was not greater in those whose active travel increased. Conversely, changes in active travel were associated with commensurate changes in total physical activity. Compared with those whose active travel remained unchanged, total physical activity decreased by 176.9 min/week in those whose active travel had decreased (adjusted regression coefficient -154.9, 95% CI -195.3 to -114.5) and was 112.2 min/week greater among those whose active travel had increased (adjusted regression coefficient 135.1, 95% CI 94.3 to 175.9)., Conclusion: An increase in active travel was associated with a commensurate increase in total physical activity and not a decrease in recreational physical activity.

Background: Active travel is a possible method to increase physical activity in children, but the precise contribution of walking to school to daily physical activity is unclear., Purpose: To combine accelerometer and GPS data to quantify moderate-to-vigorous physical activity (MVPA) on the walk to and from school in relation to overall daily levels., Methods: Participants were 141 children aged 11-12 years from the PEACH Project (Personal and Environmental Associated with Children's Health) in Bristol, England, measured between 2008 and 2009. Eighty-four children met the inclusion criteria and were included in the final analysis. Accelerometers measured physical activity, GPS receivers recorded location, and mode of travel was self-reported. Data were analyzed between April and October 2011. Combined accelerometer and GPS data were mapped in a GIS. Minutes of MVPA were compared for school journeys taking place between 8:00 AM and 9:00 AM and between 3:00 PM and 5:00 PM and in relation to whole-day levels., Results: Physical activity levels during journeys to and from school were highly similar, and contributed 22.2 minutes (33.7%) of total daily MVPA. In addition, MVPA on the journey did not differ between boys and girls, but because girls have lower levels of daily physical activity than boys, the journey contributed a greater proportion of their daily MVPA (35.6% vs 31.3%)., Conclusions: The journey to and from school is a significant contributor to MVPA in children aged 11-12 years. Combining GPS and accelerometer data within a GIS is a useful approach to quantifying specific journeys., (Copyright © 2012 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.)

Improving infrastructure for walking and cycling is increasingly recommended as a means to promote physical activity, prevent obesity, and reduce traffic congestion and carbon emissions. However, limited evidence from intervention studies exists to support this approach. Drawing on classic epidemiological methods, psychological and ecological models of behavior change, and the principles of realistic evaluation, we have developed an applied ecological framework by which current theories about the behavioral effects of environmental change may be tested in heterogeneous and complex intervention settings. Our framework guides study design and analysis by specifying the most important data to be collected and relations to be tested to confirm or refute specific hypotheses and thereby refine the underlying theories.

Background: Walking to school is associated with higher levels of physical activity, but the contribution of the journey itself to physical activity before school is unknown., Purpose: This study combined accelerometer and GPS data to investigate the level and location of physical activity in children walking to school., Methods: Participants were 137 children (aged 11.3 + or - 0.3 years) from London, England, measured in June-July 2006. Physical activity was measured by accelerometry, and location was determined with a GPS receiver. Travel mode was self-reported. Accelerometer and GPS data were time-matched to provide activity level and location for each 10-second epoch where both were available. Journeys were mapped in a GIS., Results: Mean accelerometer counts per minute before school (8:00 am to 9:00 am) were 43% higher in those who walked to school than those traveling by car (878.8 + or - 387.6 vs 608.7 + or - 264.1 counts per minute [cpm], p<0.001). Eleven percent (4.5 minutes) of daily moderate to vigorous physical activity (MVPA) occurred in this hour, with walkers recording 2.1 minutes more than car travelers (p = 0.004). Children followed direct routes between home and the school playground. Total activity during the walk to school was twice that in the playground (2131.3 + or - 1170.7 vs 1089.7 + or - 938.6 cpm, p<0.001), with the journey contributing three times as much MVPA as time in the playground., Conclusions: Our results provide evidence that the journey to school is purposeful and contributes to higher total physical activity and MVPA in children. Combining accelerometer and GPS data may aid our understanding of the environmental context of physical activity., (Copyright 2010 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.)

Objective: To investigate motivators, de-motivators and adherence to regular physical activity during and at six months after participation in a 12-week randomized controlled trial (RCT) of walking., Design: Purposive sampling in a group of men who participated in a RCT of supported, home-based walking in Bristol, England, between December 2002 and June 2005., Method: 38 sedentary, hypercholesterolemic men (54.8 (5.0) years) who participated in a 12-week RCT of walking with regular professional support, were interviewed by telephone six months after the RCT., Results: Health or fitness were the main motivational themes for adherence to walking during the RCT. Six-months after the RCT, 27 participants were still doing some walking and 18 were more physically active than before the RCT. In those who were still physically active, health benefits were motivators for adherence. In those who were less active, lack of time was a de-motivator with external support identified as a motivator for becoming more active., Conclusion: Health was the main motivating factor for adherence to physical activity during and after the supported RCT. Lack of external support was a de-motivator for sustaining physical activity.

Background: Hypercholesterolaemia and physical inactivity significantly contribute towards risk of coronary heart disease. Increased physical activity may be an effective way to improve lipid profiles in hypercholesterolaemic individuals. The aim of this study was to investigate whether a home-based physical activity program meeting current guidelines improved the lipid profile of hypercholesterolaemic men., Methods: Sixty-seven hypercholesterolaemic men (55.1 (4.9) years), from Bristol England, recruited between 2002-2004, were randomized to either 12 weeks of brisk walking sufficient to expend at least 300 kcal each walk or control condition. Fasting lipids including total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), triglycerides (TG), glucose, insulin, blood pressure and anthropometric characteristics were measured at baseline and follow-up. Compliance was monitored using accelerometers and activity logs., Results: After controlling for baseline differences, TC/HDL-C was significantly lower in the intervention group at follow-up (-0.28, 95% CI: -0.52, -0.03, p=0.03). An increase in HDL-C (0.07 mmol/l: -0.01, 0.12, p=0.07) and reduction in TG (-0.30 mmol/l: -0.64, 0.03, p=0.07) in intervention participants were of borderline statistical significance. Weight significantly decreased in intervention participants (-1.40 kg: -2.43, -0.38, p<0.01). No other significant between group effects were found. Compliance to the walking program was 97.6%., Conclusions: Twelve weeks of moderate intensity walking was sufficient to improve TC/HDL-C in hypercholesterolaemic men, primarily through improvement in HDL-C.

Purpose: Active travel to school provides an opportunity for daily physical activity. Previous studies have shown that walking and cycling to school are associated with higher physical activity levels. The purpose of this study was to investigate whether the way that children and adolescents travel to school is associated with level of cardiovascular fitness., Methods: Participants were recruited via a proportional, two-stage cluster sample of schools (N = 25) in the region of Odense, Denmark as part of the European Youth Heart Study (EYHS). Nine hundred nineteen participants (529 children, age 9.7 +/- 0.5 yr; 390 adolescents, age 15.5 +/- 0.4 yr) completed a maximal cycle ergometer test to assess cardiorespiratory fitness (Wmax x kg(-1)). Mode of travel to school was investigated by questionnaire. Physical activity was measured in 531 participants using an accelerometer. Regression analyses with robust standard errors and adjustment for confounders (gender, age, body composition (skinfolds), pubertal status, and physical activity) and the cluster sampling procedure were used to compare fitness levels for different travel modes. Multinomial logistic regression was applied to assess the odds for belonging to quartiles of fitness., Results: Children and adolescents who cycled to school were significantly more fit than those who walked or traveled by motorized transport and were nearly five times as likely (OR 4.8; 95% CI 2.8-8.4) to be in the top quartile of fitness., Conclusion: Cycling to school may contribute to higher cardiovascular fitness in young people.

Background: Active commuting to school by walking or bicycle is widely promoted to increase children's physical activity. However, there is little data to describe the impact that travel mode, and in particular cycling, may have on activity levels., Methods: Primary school children wore an accelerometer recording minute-by-minute physical activity, and completed questions describing travel habits. Total volume of physical activity and hourly physical activity patterns were estimated and groups of children compared by mode of travel to school. Data were collected as part of the European Youth Heart Study., Results: A total of 332 children (average age 9.7 years, standard deviation [SD] = 0.4 years) completed all measurements. Children who walked to school were significantly more physically active than those who traveled by car (accelerometer counts per minute [cpm]: 667.7, SD = 233.7 vs 557.3, SD = 191.4; p = 0.01). Those who cycled to school recorded higher accelerometer counts than those who traveled by car, but differences were not significant. Boys who walked or cycled to school were significantly more physically active than those traveling by car (walk: 732.2 cpm, SD = 253.1 vs 592.8 cpm, SD = 193.9; p=0.007; cycle: 712.6 cpm, SD = 249.1 vs 592.8 cpm, SD = 193.9; p = 0.013). In girls, walking but not cycling to school was significantly associated with higher daily physical activity levels (606.3 cpm, SD = 197.7, vs 523.4 cpm, SD = 185.0 cpm; p = 0.05)., Conclusions: In primary school-aged children, walking to school is associated with higher levels of overall physical activity compared with those who travel to school by motorized transport. Cycling is associated with higher overall physical activity only in boys.

Background: The journey to school is an opportunity for increasing children's daily physical activity. However, the contribution that active commuting to school makes to overall physical activity is unknown. This study used objective measurement to investigate the physical activity patterns of children by mode of travel to school., Methods: Primary-school children wore an accelerometer programmed to record minute-by-minute physical activity for 7 days and completed a brief questionnaire describing their usual travel to school. The total volume of physical activity and the time spent in activity of at least moderate intensity, as recorded by the accelerometer, was estimated for weekdays and the weekend, and groups of children were compared by mode of transport to school. Data were collected in May/June 2002., Results: Of the 114 children (59 boys, 55 girls; aged 10.4+/-0.8 years) who took part in the study, those who walked to school (65%) were significantly more active than those who traveled by car (712.0+/-206.7 vs 629.9+/-207.2 accelerometer counts per minute, p=0.05). Analysis by gender indicated that the major differences in physical activity between travel groups were seen only in boys. Hourly activity patterns demonstrated that boys who walked to school were more active after school and throughout the evening than were car users., Conclusions: In boys, walking to school was associated with higher physical activity after school and during the evening. Active transport may contribute to a more physically active profile, at least for boys, supporting walk-to-school initiatives to increase children's physical activity.