An assessment of the relevance of the home neighbourhood for understanding environmental influences on physical activity: how far from home do people roam?

BACKGROUND: The choice of geographical unit of analysis in studies of the built environment and physical activity has typically been restricted to the home neighbourhood where only a small proportion of physical activity may actually be undertaken. This study aimed to examine the distance from home at which physical activity takes place and how this varies by personal and neighbourhood characteristics. METHODS: A cross-sectional, population based study of 195 people in the North West region of England, aged 18 to 91 years, clustered in 60 localities (small geographical areas of ~125 households). Individual socio-demographic data were collected by computer-aided personal interviews and physical activity was characterised by accelerometer and Global Positioning System (GPS) data. The locations of periods of light, moderate and vigorous intensity physical activity (LMVPA) undertaken outdoors were linked to measures of the neighbourhood around the home and distance from home. RESULTS: Sixty per cent of outdoors LMVPA took place outside of the proximal home neighbourhood (800 m buffer). Distances from home where median levels of LMVPA were undertaken varied by gender (p < 0.05), home location, area deprivation, and car ownership (all p < 0.001). CONCLUSIONS: Objectively measured physical activity appears to vary appreciably by participant characteristics and home location, although for many settings a large proportion is undertaken outside of the home neighbourhood, suggesting the characterisation of neighbourhoods close to home will fail to properly capture the environmental influences on physical activity.

Socioeconomic position and childhood sedentary time: evidence from the PEACH project.

BACKGROUND: Associations between socioeconomic position (SEP) and sedentary behaviour in children are unclear. Existing studies have used aggregate measures of weekly sedentary time that could mask important differences in the relationship between SEP and sedentary time at different times of the day or between weekdays and weekend days. These studies have also employed a variety of measures of SEP which may be differentially associated with sedentary time. This paper examines associations of multiple indicators of SEP and accelerometer-measured, temporally specific, sedentary time in school children. METHODS: Between 2006 and 2007 sedentary time data (minutes spent below 100 accelerometer counts per minute) for weekdays before-school (7.00-8.59AM), during school-time (9.00AM-2.59PM) and after-school (3.00PM-11.00PM), and weekend days were recorded for 629 10-11 year old children using accelerometers. Ordinary least squares regression was used to examine associations with 5 indicators of SEP (area deprivation, annual household income, car ownership, parental education and access to a private garden). Covariates were; gender, BMI, minutes of daylight, accelerometer wear time and school travel method. Analyses were conducted in 2012. RESULTS: Following adjustments for covariates, having a parent educated to university degree level was associated with more minutes of school (5.87 [95% CI 1.72, 10.04]) and after-school (6.04 [95% CI 0.08, 12.16]) sedentary time. Quartiles of area deprivation (most to least deprived) were positively associated with after-school (Q2: 4.30 [95% CI -6.09, 14.70]; Q3: 10.77 [95% CI 0.47, 21.06]; Q4: 12.74 [95% CI 2.65, 22.84]; P(trend) = 0.04) and weekend (Q2: 26.34 [95% CI 10.16, 42.53]; Q3: 33.28 [95% CI 16.92, 49.65]; Q4: 29.90 [95% CI 14.20, 45.60]; P(trend) = 0.002) sedentary time. Having a garden was associated with less sedentary time after-school (-14.39 [95% CI -25.14, -3.64]) and at weekends (-27.44 [95% CI -43.11, -11.78]). CONCLUSIONS: Associations between SEP and children's sedentary-time varied by SEP indicator and time of day. This highlights the importance of measuring multiple indicators of SEP and examining context specific sedentary time in children in order to fully understand how SEP influences this behaviour. Further research should combine self-report and objective data to examine associations with specific sedentary behaviours in the contexts within which they occur, as well as total sedentary time.

Developing and testing a street audit tool using Google Street View to measure environmental supportiveness for physical activity.

BACKGROUND: Walking for physical activity is associated with substantial health benefits for adults. Increasingly research has focused on associations between walking behaviours and neighbourhood environments including street characteristics such as pavement availability and aesthetics. Nevertheless, objective assessment of street-level data is challenging. This research investigates the reliability of a new street characteristic audit tool designed for use with Google Street View, and assesses levels of agreement between computer-based and on-site auditing. METHODS: The Forty Area STudy street VIEW (FASTVIEW) tool, a Google Street View based audit tool, was developed incorporating nine categories of street characteristics. Using the tool, desk-based audits were conducted by trained researchers across one large UK town during 2011. Both inter and intra-rater reliability were assessed. On-site street audits were also completed to test the criterion validity of the method. All reliability scores were assessed by percentage agreement and the kappa statistic. RESULTS: Within-rater agreement was high for each category of street characteristic (range: 66.7%-90.0%) and good to high between raters (range: 51.3%-89.1%). A high level of agreement was found between the Google Street View audits and those conducted in-person across the nine categories examined (range: 75.0%-96.7%). CONCLUSION: The audit tool was found to provide a reliable and valid measure of street characteristics. The use of Google Street View to capture street characteristic data is recommended as an efficient method that could substantially increase potential for large-scale objective data collection.

Use of accelerometry to classify activity beneficial to bone in premenopausal women.

PURPOSE: The aims of this study were to quantify the relation between ground reaction force (GRF) and peak acceleration from hip- and wrist-worn accelerometers and determine peak acceleration cut-points associated with a loading rate previously demonstrated as beneficial to bone (43 body weights (BW)·s⁻¹) in premenopausal women. METHODS: Forty-seven premenopausal women (age, 39.2 ± 5.6 yr; mass, 65.9 ± 11.0 kg; height, 1.67 ± 0.06 m) performed walking (slow, fast, and with bag), floor sweeping, running (slow and fast), jumping (low, <5 cm; high, >5 cm), and box drop (20 cm) trials. Peak accelerations were sampled at 100 Hz by GENEActiv and ActiGraph GT3X+ accelerometers (ActiGraph LLC, Pensacola, FL) worn at the hip (vertical and resultant) and the wrist (resultant). A force plate (960 Hz, AMTI) was used to assess peak vertical GRF and peak loading rate for eight steps per activity. Receiver operating characteristic curves were used to determine the optimal peak acceleration cut-points associated with a loading rate of 43 BW·s⁻¹ in 37 participants, and these cut-points were cross-validated in the remaining 10 participants. RESULTS: For all activities combined, peak accelerations were positively and significantly (P < 0.001) correlated with peak vertical GRF (hip r > 0.8, wrist r > 0.7) and peak loading rate (hip r > 0.7, wrist r > 0.57). Irrespective of monitor type and wear site, peak acceleration discriminated between loading rates above and below 43 BW·s⁻¹ with high levels of accuracy (area under the curve >0.92, P < 0.001). Overall classification agreement was >85% for both monitors worn at either the wrist or hip in the cross-validation sample. CONCLUSION: GENEActiv and ActiGraph GT3X+ accelerometers worn at the wrist or hip can be used as an unobtrusive tool to identify the occurrence of loading rates likely beneficial to bone in premenopausal women during their daily activity.

Moderate to vigorous physical activity and sedentary time and cardiometabolic risk factors in children and adolescents.

CONTEXT: Sparse data exist on the combined associations between physical activity and sedentary time with cardiometabolic risk factors in healthy children. OBJECTIVE: To examine the independent and combined associations between objectively measured time in moderate- to vigorous-intensity physical activity (MVPA) and sedentary time with cardiometabolic risk factors. DESIGN, SETTING, AND PARTICIPANTS: Pooled data from 14 studies between 1998 and 2009 comprising 20 871 children (aged 4-18 years) from the International Children's Accelerometry Database. Time spent in MVPA and sedentary time were measured using accelerometry after reanalyzing raw data. The independent associations between time in MVPA and sedentary time, with outcomes, were examined using meta-analysis. Participants were stratified by tertiles of MVPA and sedentary time. MAIN OUTCOME MEASURES: Waist circumference, systolic blood pressure, fasting triglycerides, high-density lipoprotein cholesterol, and insulin. RESULTS: Times (mean [SD] min/d) accumulated by children in MVPA and being sedentary were 30 (21) and 354 (96), respectively. Time in MVPA was significantly associated with all cardiometabolic outcomes independent of sex, age, monitor wear time, time spent sedentary, and waist circumference (when not the outcome). Sedentary time was not associated with any outcome independent of time in MVPA. In the combined analyses, higher levels of MVPA were associated with better cardiometabolic risk factors across tertiles of sedentary time. The differences in outcomes between higher and lower MVPA were greater with lower sedentary time. Mean differences in waist circumference between the bottom and top tertiles of MVPA were 5.6 cm (95% CI, 4.8-6.4 cm) for high sedentary time and 3.6 cm (95% CI, 2.8-4.3 cm) for low sedentary time. Mean differences in systolic blood pressure for high and low sedentary time were 0.7 mm Hg (95% CI, -0.07 to 1.6) and 2.5 mm Hg (95% CI, 1.7-3.3), and for high-density lipoprotein cholesterol, differences were -2.6 mg/dL (95% CI, -1.4 to -3.9) and -4.5 mg/dL (95% CI, -3.3 to -5.6), respectively. Geometric mean differences for insulin and triglycerides showed similar variation. Those in the top tertile of MVPA accumulated more than 35 minutes per day in this intensity level compared with fewer than 18 minutes per day for those in the bottom tertile. In prospective analyses (N = 6413 at 2.1 years' follow-up), MVPA and sedentary time were not associated with waist circumference at follow-up, but a higher waist circumference at baseline was associated with higher amounts of sedentary time at follow-up. CONCLUSION: Higher MVPA time by children and adolescents was associated with better cardiometabolic risk factors regardless of the amount of sedentary time.

International children's accelerometry database (ICAD): design and methods.

BACKGROUND: Over the past decade, accelerometers have increased in popularity as an objective measure of physical activity in free-living individuals. Evidence suggests that objective measures, rather than subjective tools such as questionnaires, are more likely to detect associations between physical activity and health in children. To date, a number of studies of children and adolescents across diverse cultures around the globe have collected accelerometer measures of physical activity accompanied by a broad range of predictor variables and associated health outcomes. The International Children's Accelerometry Database (ICAD) project pooled and reduced raw accelerometer data using standardized methods to create comparable outcome variables across studies. Such data pooling has the potential to improve our knowledge regarding the strength of relationships between physical activity and health. This manuscript describes the contributing studies, outlines the standardized methods used to process the accelerometer data and provides the initial questions which will be addressed using this novel data repository. METHODS: Between September 2008 and May 2010 46,131 raw Actigraph data files and accompanying anthropometric, demographic and health data collected on children (aged 3-18 years) were obtained from 20 studies worldwide and data was reduced using standardized analytical methods. RESULTS: When using ≥ 8, ≥ 10 and ≥ 12 hrs of wear per day as a criterion, 96%, 93.5% and 86.2% of the males, respectively, and 96.3%, 93.7% and 86% of the females, respectively, had at least one valid day of data. CONCLUSIONS: Pooling raw accelerometer data and accompanying phenotypic data from a number of studies has the potential to: a) increase statistical power due to a large sample size, b) create a more heterogeneous and potentially more representative sample, c) standardize and optimize the analytical methods used in the generation of outcome variables, and d) provide a means to study the causes of inter-study variability in physical activity. Methodological challenges include inflated variability in accelerometry measurements and the wide variation in tools and methods used to collect non-accelerometer data.

Children's screen viewing is related to psychological difficulties irrespective of physical activity.

OBJECTIVE: We hypothesized that greater screen use would be associated with greater psychological difficulties and that children with high levels of screen entertainment use and low levels of physical activity would have the most-negative psychological profiles. METHODS: Participants were 1013 children (age, mean ± SD: 10.95 ± 0.41 years), who self-reported average daily television hours and computer use and completed the Strengths and Difficulties Questionnaire. Sedentary time (minutes per day with <100 cpm) and moderate/vigorous physical activity (MVPA) (minutes with ≥ 2000 cpm) were measured by using accelerometers. Multivariate regression models examined the association between television viewing, computer use, sedentary time, and Strengths and Difficulties Questionnaire scores, with adjustment for MVPA, age, gender, level of deprivation, and pubertal status. RESULTS: Greater television and computer use were related to higher psychological difficulty scores after adjustment for MVPA, sedentary time, and confounders. However, sedentary time was inversely related to psychological difficulties after adjustment. Children who spent >2 hours per day watching television or using a computer were at increased risk of high levels of psychological difficulties (television, odds ratio [OR]: 1.61 [95% confidence interval [CI]: 1.20-2.15]; computer, OR: 1.59 [95% CI: 1.32-1.91]), and this risk increased if the children also failed to meet physical activity guidelines (television, OR: 1.70 [95% CI: 1.09-2.61]; computer, OR: 1.81 [95% CI: 1.02-3.20]). CONCLUSION: Both television viewing and computer use are important independent targets for intervention for optimal well-being for children, irrespective of levels of MVPA or overall sedentary time.

The school effect on children's school time physical activity: the PEACH Project.

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.

Patterns of GPS measured time outdoors after school and objective physical activity in English children: the PEACH project.

BACKGROUND: Observational studies have shown a positive association between time outdoors and physical activity in children. Time outdoors may be a feasible intervention target to increase the physical activity of youth, but methods are required to accurately measure time spent outdoors in a range of locations and over a sustained period. The Global Positioning System (GPS) provides precise location data and can be used to identify when an individual is outdoors. The aim of this study was to investigate whether GPS data recorded outdoors were associated with objectively measured physical activity. METHODS: Participants were 1010 children (11.0 +/- 0.4 years) recruited from 23 urban primary schools in South West England, measured between September 2006 and July 2008. Physical activity was measured by accelerometry (Actigraph GT1M) and children wore a GPS receiver (Garmin Foretrex 201) after school on four weekdays to record time outdoors. Accelerometer and GPS data were recorded at 10 second epochs and were combined to describe patterns of physical activity when both a GPS and accelerometer record were present (outdoors) and when there was accelerometer data only (indoors). ANOVA was used to investigate gender and seasonal differences in the patterns of outdoor and indoor physical activity, and linear regression was used to examine the cross-sectional associations between GPS-measured time outdoors and physical activity. RESULTS: GPS-measured time outdoors was a significant independent predictor of children's physical activity after adjustment for potential confounding factors. Physical activity was more than 2.5 fold higher outdoors than indoors (1345.8 +/- 907.3 vs 508.9 +/- 282.9 counts per minute; F = 783.2, p < .001). Overall, children recorded 41.7 +/- 46.1 minutes outdoors between 3.30 pm and 8.30 pm, with more time spent outdoors in the summer months (p < .001). There was no gender difference in time spent outdoors. Physical activity outdoors was higher in the summer than the winter (p < .001), whilst there was no seasonal variation in physical activity indoors. CONCLUSIONS: Duration of GPS recording is positively associated with objectively measured physical activity and is sensitive to seasonal differences. Minute by minute patterning of GPS and physical activity data is feasible and may be a useful tool to investigate environmental influences on children's physical activity and to identify opportunities for intervention.

Mapping the walk to school using accelerometry combined with a global positioning system.

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.

Independent mobility, perceptions of the built environment and children's participation in play, active travel and structured exercise and sport: the PEACH Project.

BACKGROUND: Independent mobility (IM) and perceptions of the built environment may relate differentially to children's participation in various physical activity contexts. This cross-sectional study investigated whether independent mobility and perceptions of the built environment in boys and girls were related to physical activity in three different contexts (outdoor play, structured exercise/sport, active commuting). METHODS: Thirteen hundred and seven 10-11 year old boys and girls from 23 schools in a large UK city completed a computerised questionnaire. Independent variables in logistic regression analyses were weekly self-reported frequency of participation in outdoor play, structured exercise/sport and mode of travel home from school. Dependent variables were perceptions of the environment (aesthetics, nuisance, safety, social norm, constraint, play space, accessibility), local and area independent mobility and linear distance from home to school. Analyses were adjusted for body mass index, minutes of daylight after school, level of neighbourhood deprivation and pubertal status. RESULTS: For boys, local independent mobility (Local-IM) was related to an increased likelihood of everyday participation in play (OR 1.58: 95% CI 1.19-2.10), structured exercise/sport (OR 1.42: 1.06-1.89) and active commuting (OR 1.40: 1.07-1.87) but was only related to active commuting for girls (OR1.49: 1.07-2.07). Boys and girls were more likely to report playing out every day if they had higher scores for Social Norm (Boys: OR 1.63 (1.12-2.37); Girls: OR 1.53 (1.01-2.31)) and, for girls only, more positive perceptions of traffic safety (OR 1.63: 1.14-2.34). Easy access to a range of destinations was the dominant predictor for taking part in structured exercise/sport everyday (Boys: OR 1.62 (1.01-2.66); Girls: OR 1.65 (1.07-2.53)). Shorter distance from home to school (OR 0.99: 0.98-0.99) and, for boys only, greater perceived accessibility (OR 1.87: 1.04-3.36) were significantly related to active commuting to school. CONCLUSIONS: Perceptions of the physical environment relate differently to different physical activity contexts and by gender. The only consistent correlate for outdoor play, structured ex/sport and active commuting was higher independent mobility to visit local destinations (Local-IM) for boys. Considering both the physical activity context and its independent correlates should improve the specificity of physical activity interventions in children.

Independent mobility in relation to weekday and weekend physical activity in children aged 10-11 years: The PEACH Project.

BACKGROUND: Children's independent mobility has fallen in recent years and may in part explain reported declines in physical activity in young people. This cross-sectional study investigated whether independent mobility in boys and girls was related to objectively measured physical activity. METHODS: Thirteen hundred and seven 10-11 year old boys and girls from 23 schools in a large UK city took part. Measures included objectively recorded physical activity (accelerometer (Actigraph GT1M)), height (m) and weight (kg), a newly developed scale for local (Local-IM) and area independent mobility (Area-IM), minutes of daylight after school, level of neighbourhood deprivation and pubertal status. RESULTS: Boys had greater Local-IM, Area-IM and physical activity (average weekday and weekend counts per minute) compared to girls. In linear regression analyses (adjusting for minutes of daylight after school, neighbourhood deprivation, pubertal status and body mass index) higher scores for Local-IM and Area-IM were significantly (p < 0.01) related to higher levels of physical activity on weekdays for boys and girls. For weekend physical activity, only Local-IM in girls remained significant (p < 0.05) in the model. CONCLUSION: Independent mobility appears to be an important independent correlate of weekday physical activity for both boys and girls.