How far from home? The locations of physical activity in an urban U.S. setting

Crime-related perceptions and walking for recreation inside and outside one's home neighborhood

It is widely assumed crime and related concerns, including neighborhood incivilities and fear of crime, are barriers to physical activity (PA). Past studies reveal mixed evidence. Studies of impacts for crime-protective factors are less common but have similarly mixed results. This paper evaluates a comprehensive transdisciplinary conceptual framework of cross-sectional associations between crime-related perceptions and reported minutes/week of recreational walking inside and outside one's home neighborhood. Safe and Fit Environments Study (SAFE) recruited and surveyed 2302 participants from adolescents to older adults from four U.S. metropolitan areas. A zero-inflated model estimated two components of each outcome: whether the respondent walked, and minutes/week walked. Correlates of recreational walking were location-specific, differing based on walking location. Fear of crime, risk evaluation, victimization, and incivilities were not consistently associated with walking for recreation inside one's neighborhood. People with crime concerns about their own neighborhoods, however, more commonly walked for recreation outside their neighborhoods. Protective crime-related perceptions that seldom have been studied in relation to PA, such as street efficacy (i.e., the perceived ability to avoid and manage danger), were strongly associated with recreational walking in both locations, indicating the additional heuristic value of the SAFE conceptual framework. Crime-related perceptions and walking for recreation: Evaluating a conceptual model.

Systematic review of best practices for GPS data usage, processing, and linkage in health, exposure science and environmental context research

Global Positioning System (GPS) technology is increasingly used in health research to capture individual mobility and contextual and environmental exposures. However, the tools, techniques and decisions for using GPS data vary from study to study, making comparisons and reproducibility challenging.

OBJECTIVES

The objectives of this systematic review were to (1) identify best practices for GPS data collection and processing; (2) quantify reporting of best practices in published studies; and (3) discuss examples found in reviewed manuscripts that future researchers may employ for reporting GPS data usage, processing and linkage of GPS data in health studies.

DESIGN

A systematic review.

DATA SOURCES

Electronic databases searched (24 October 2023) were PubMed, Scopus and Web of Science (PROSPERO ID: CRD42022322166).

ELIGIBILITY CRITERIA

Included peer-reviewed studies published in English met at least one of the criteria: (1) protocols involving GPS for exposure/context and human health research purposes and containing empirical data; (2) linkage of GPS data to other data intended for research on contextual influences on health; (3) associations between GPS-measured mobility or exposures and health; (4) derived variable methods using GPS data in health research; or (5) comparison of GPS tracking with other methods (eg, travel diary).

DATA EXTRACTION AND SYNTHESIS

We examined 157 manuscripts for reporting of best practices including wear time, sampling frequency, data validity, noise/signal loss and data linkage to assess risk of bias.

RESULTS

We found that 6% of the studies did not disclose the GPS device model used, only 12.1% reported the per cent of GPS data lost by signal loss, only 15.7% reported the per cent of GPS data considered to be noise and only 68.2% reported the inclusion criteria for their data.

CONCLUSIONS

Our recommendations for reporting on GPS usage, processing and linkage may be transferrable to other geospatial devices, with the hope of promoting transparency and reproducibility in this research.

PROSPERO REGISTRATION NUMBER

CRD42022322166.

Global Positioning System Indicators of Community Mobility and Future Health Outcomes Among Older Adults

BACKGROUND

We examined the relationship between global positioning system (GPS) indicators of community mobility and incident hospitalizations, emergency department (ED) visits, and falls over 1-year in community-dwelling older adults.

METHODS

We performed a secondary analysis of a randomized trial investigating a physical therapy intervention to improve mobility in older adults. One hundred and forty-eight participants (mean age: 76.9 ± 6.2 years; 65% female) carried a GPS device following the postintervention visit. Over 1-year, new hospitalizations, falls, and ED visits were reported. GPS indicators of community mobility included the median area and compactness of the standard deviation ellipse (SDE), the median percentage of time spent outside of home (TOH), and median maximum distance from home. Generalized linear models assessed the association between 1-year risk of outcomes and GPS measures adjusted for age, race, gender, body mass index, comorbidity burden, and fall history.

RESULTS

The mean ± standard deviation of the median SDE area was 4.4 ± 8.5 km2, median SDE compactness 0.7 ± 0.2, median percentage TOH 14.4 ± 12.0%, and median maximum distance from home was 38 ± 253 km. Each 5% increase in median percentage TOH was associated with a 24% lower risk of hospitalization (incident rate ratio = IRR = 0.76, 95%CI: 0.61-0.95; p = .01). The association persisted after covariate adjustment (IRR = 0.78, 95%CI: 0.63-0.98; p = .03). No significant associations appeared for any GPS indicators with incident falls or ED visits.

CONCLUSIONS

Increased TOH was associated with a lower risk of incident hospitalization over 1 year among community-dwelling older adults. Restricted community mobility may be an indicator of activity limitations related to future health outcomes, but further study is warranted.

Walking Behaviour of Individuals with Intermittent Claudication Compared to Matched Controls in Different Locations: An Exploratory Study

Individuals with intermittent claudication (IC) are less physically active than their peers, but how this varies with location is unclear. Individuals with IC and matched controls [sex, age ±5 years, home < 5 miles] wore an activity monitor (activPAL) and carried a GPS device (AMOD-AGL3080) for 7 days. GPS data categorised walking events as occurring at home (<=50 m from home co-ordinates) or away from home, and indoors (signal to noise ratio <= 212 dB) or outdoors. Number of walking events, walking duration, steps and cadence were compared between groups and each location pair using mixed model ANOVAs. In addition, the locus of activity (distance from home) at which walking was conducted was compared between groups. Participants (n = 56) were mostly male (64%) and aged 54-89 years. Individuals with IC spent significantly less time walking and took fewer steps than their matched controls at all locations, including at home. Participants spent more time and took more steps away from home than at home, but were similar when walking indoors and outdoors. The locus of activity was significantly smaller for individuals with IC, suggesting that it is not just physical capacity that influences walking behaviour, and other factors (e.g., social isolation) may play a role.

Cross-Sectional Study of Location-Based Built Environments, Physical Activity, Dietary Intake, and Body Mass Index in Adult Twins

We examined relationships between walkability and health behaviors between and within identical twin pairs, considering both home (neighborhood) walkability and each twin's measured activity space. Continuous activity and location data (via accelerometry and GPS) were obtained in 79 pairs over 2 weeks. Walkability was estimated using Walk Score^® (WS); home WS refers to neighborhood walkability, and GPS WS refers to the mean of individual WSs matched to every GPS point collected by each participant. GPS WS was assessed within (WHN) and out of the neighborhood (OHN), using 1-mile Euclidean (air1mi) and network (net1mi) buffers. Outcomes included walking and moderate-to-vigorous physical activity (MVPA) bouts, dietary energy density (DED), and BMI. Home WS was associated with WHN GPS WS (b = 0.71, SE = 0.03, p < 0.001 for air1mi; b = 0.79, SE = 0.03, p < 0.001 for net1mi), and OHN GPS WS (b = 0.18, SE = 0.04, p < 0.001 for air1mi; b = 0.22, SE = 0.04, p < 0.001 for net1mi). Quasi-causal relationships (within-twin) were observed for home and GPS WS with walking (ps < 0.01), but not MVPA, DED, or BMI. Results support previous literature that neighborhood walkability has a positive influence on walking.

Cross-sectional associations between neighbourhood walkability and objective physical activity levels in identical twins

OBJECTIVES

Physical activity is a cornerstone of chronic disease prevention and treatment, yet most US adults do not perform levels recommended for health. The neighborhood-built environment (BE) may support or hinder physical activity levels. This study investigated whether identical twins who reside in more walkable BEs have greater activity levels than twins who reside in less walkable BEs (between-twin analysis), and whether associations remain significant when controlling for genetic and shared environmental factors (within-twin analysis).

DESIGN

A cross-sectional study.

SETTING

The Puget Sound region around Seattle, Washington, USA.

PARTICIPANTS

The sample consisted of 112 identical twin pairs who completed an in-person assessment and 2-week at-home measurement protocol using a global positioning system (GPS)monitor and accelerometer.

EXPOSURE

The walkability of each participants' place of residence was calculated using three BE dimensions (intersection density, population density and destination accessibility). For each variable, z scores were calculated and summed to produce the final walkability score.

OUTCOMES

Objectively measured bouts of walking and moderate-to-vigorous physical activity (MVPA), expressed as minutes per week.

RESULTS

Walkability was associated with walking bouts (but not MVPA) within the neighbourhood, both between (b=0.58, SE=0.13, p<0.001) and within pairs (b=0.61, SE=0.18, p=0.001). For a pair with a 2-unit difference in walkability, the twin in a more walkable neighbourhood is likely to walk approximately 16 min per week more than the co-twin who lives in a less walkable neighbourhood.

CONCLUSIONS

This study provides robust evidence of an association between walkability and objective walking bouts. Improvements to the neighbourhood BE could potentially lead to increased activity levels in communities throughout the USA.

Using combined Global Position System and accelerometer data points to examine how built environments and gentrification are associated with physical activity in four Canadian cities

BACKGROUND

Built and social environments are associated with physical activity. Global Positioning Systems (GPS) and accelerometer data can capture how people move through their environments and provide promising tools to better understand associations between environmental characteristics and physical activity. The purpose of this study is to examine the associations between GPS-derived exposure to built environment and gentrification characteristics and accelerometer-measured physical activity in a sample of adults across four cities.

METHODS

We used wave 1 data from the Interventions, Research, and Action in Cities Team, a cohort of adults living in the Canadian cities of Victoria, Vancouver, Saskatoon, and Montreal. A subsample of participants wore a SenseDoc device for 10 days during May 2017-January 2019 to record GPS and accelerometry data. Two physical activity outcomes were derived from SenseDoc data: time spent in light, moderate, and vigorous physical activity; and time spent in moderate or vigorous physical activity. Using corresponding GPS coordinates, we summarized physical activity outcomes by dissemination area-a Canadian census geography that represents areas where 400 to 700 people live- and joined to built (active living space, proximity to amenities, and urban compactness) and gentrification measures. We examined the associations between environmental measures and physical activity outcomes using multi-level negative binomial regression models that were stratified by city and adjusted for covariates (weekday/weekend), home dissemination area, precipitation, temperature) and participant-level characteristics obtained from a survey (age, gender, income, race).

RESULTS

We found that adults spent more time being physically active near their homes, and in environments that were more walkable and near parks and less time in urban compact areas, regardless of where participants lived. Our analysis also highlighted how proximity to different amenities was linked to physical activity across different cities.

CONCLUSIONS

Our study provides insights into how built environment and gentrification characteristics are associated with the amount of time adults spend being physically active in four Canadian cities. These findings enhance our understanding of the influence that environments have on physical activity over time and space, and can support policies to increase physical activity.

GPS-based activity space exposure to greenness and walkability is associated with increased accelerometer-based physical activity

INTRODUCTION

Built and natural environments may provide opportunities for physical activity. However, studies are limited by primarily using residential addresses to define exposure and self-report to measure physical activity. We quantified associations between global positioning systems (GPS)-based activity space measures of environmental exposure and accelerometer-based physical activity.

METHODS

Using a nationwide sample of working female adults (N = 354), we obtained seven days of GPS and accelerometry data. We created Daily Path Area activity spaces using GPS data and linked these activity spaces to spatial datasets on walkability (EPA Smart Location Database at the Census block group level) and greenness (satellite vegetation at 250 m resolution). We utilized generalized additive models to examine nonlinear associations between activity space exposures and accelerometer-derived physical activity outcomes adjusted for demographic characteristics, socioeconomic factors, and self-rated health.

RESULTS

Higher activity space walkability was associated with higher levels of moderate-vigorous physical activity, and higher activity space greenness was associated with greater numbers of steps per week. No strong relationships were observed for sedentary behavior or light physical activity. Highest levels of moderate-vigorous physical activity were observed for participants with both high walkability and high greenness in their activity spaces.

CONCLUSION

This study contributes evidence that higher levels of physical activity occur in environments with more dense, diverse, and well-connected built environments, and with higher amounts of vegetation. These data suggest that urban planners, landscape architects, and policy makers should implement and evaluate environmental interventions to encourage higher levels of physical activity.

A comprehensive evaluation of physical activity on sidewalks and streets in three U.S. Cities

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Video-enhanced observation provides objective data on sidewalks/streets activity.

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Neighborhood-level walkability was strongly associated with sidewalks/streets use.

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Most people (67%) were walking; others were sitting, standing, cycling, jogging.

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Sidewalk/street activity varied by time of day, weather, & environmental condition.

A considerable proportion of outdoor physical activity (PA) is done on sidewalks/streets. The purpose of the current study was to create a comprehensive picture of PA and non-PA (sitting and standing) occurring on sidewalks/streets. A wearable video device was used to capture videos during 2019 in three different size (small, medium, large), U.S. cities along 24 observation routes (sidewalks/streets) located in 24 study areas that varied in walkability, income level, and minority composition. Videos were collected over the course of one year during different times of week and weekend days. Expert reviewers examined each video to extract data on counts of people engaged in different types of activities (e.g., walking) per minute of video. A total of 1154 individuals were described in 1237 min of video as either walking (66.9%), sitting/standing (25.7%), jogging (4.2%), cycling (1.8%) or skating/playing (1.4%). A greater number of active people/min were seen in the evening and in the small city (P < 0.05) while more non-PA people/min were observed in the medium city and during the weekend (P < 0.05). Active and non-PA people/min were associated with walkability, income, and minority composition. For instance, in high walkability, low income areas, 3.2 active people/min were observed in areas with a high percentage of non-minority residents compared to 0.9 active people /min in areas with a high percentage of minority residents. Sidewalks/street activities are related to dynamic interactions between social and physical environmental factors. The results of this study may serve as a reference to which future, similar evaluations can compare.

The Places–People Exercise: Understanding Spatial Patterns and the Formation Mechanism for Urban Commercial Fitness Space in Changchun City, China

The fitness industry is rapidly developing due to the demand for fitness activities, and a large number of commercial fitness spaces have emerged in Changchun city. The distribution of commercial fitness spaces in the city is not chaotic; different types of fitness spaces should have different spaces to choose from. The purpose of this article is to summarize the spatial distribution characteristics and laws of urban commercial fitness spaces, to help better develop commercial fitness spaces. Using Changchun (a central city in northeastern China) as an example, the article divides commercial fitness spaces into five categories. Then, GIS tools are used to analyze the distribution patterns, level distributions, and agglomeration characteristics of commercial fitness spaces. The city’s commercial fitness space distribution patterns are subjected to further study, along with the influencing factors and forming mechanisms of the pattern. Moreover, based on the research results, this study provides targeted suggestions for the development of fitness spaces. The study found that the commercial fitness space in Changchun city has formed a multi-core spatial pattern. Various types of fitness spaces show significant spatial differentiation in many aspects, such as “center-periphery” characteristics, the spatial distribution form, and the specialized characteristics of each block unit. Fitness needs, national policies, transportation accessibility, spatial agglomeration, land rent, urban population distribution, etc., are the main factors affecting the spatial distributions of fitness spaces.

Walkability measures to predict the likelihood of walking in a place: A classification and regression tree analysis

Walkability is a popular and ubiquitous term at the intersection of urban planning and public health. As the number of potential walkability measures grows in the literature, there is a need to compare their relative importance for specific research objectives. This study demonstrates a classification and regression tree (CART) model to compare five familiar measures of walkability from the literature for their relative ability to predict whether or not walking occurs in a dataset of objectively measured locations. When analyzed together, the measures had moderate-to-high accuracy (87.8% agreement: 65.6% of true walking GPS-measured points classified as walking and 93.4% of non-walking points as non-walking). On its own, the most well-known composite measure, Walk Score, performed only slightly better than measures of the built environment composed of a single variable (transit ridership, employment density, and residential density).Thus there may be contexts where transparent and longitudinally available measures of urban form are worth a marginal tradeoff in prediction accuracy. This comparison of walkability measures using CART highlights the importance for public health and urban design researchers to think carefully about how and why particular walkability measures are used.

Location-Based Sedentary Time and Physical Activity in People Living With Coronary Artery Disease

PURPOSE

Sedentary time (ST) and lack of physical activity increase the risk of adverse outcomes for those living with coronary artery disease (CAD). Little is known about how much ST, light physical activity (LPA), and moderate to vigorous physical activity (MVPA) that CAD participants not attending cardiac rehabilitation engage in, the locations where they engage in these behaviors, and how far from home the locations are.

METHODS

Participants completed a survey and wore an accelerometer and global positioning system receiver for 7 d at baseline and 6 mo later.

RESULTS

Accelerometer analyses (n = 318) showed that participants averaged 468.4 ± 102.7 of ST, 316.1 ± 86.5 of LPA, and 32.9 ± 28.9 of MVPA min/d at baseline. ST and LPA remained stable at 6 mo, whereas MVPA significantly declined. The global positioning system (GPS) analyses (n = 315) showed that most of participant ST, LPA, and MVPA time was spent at home followed by other residential, retail/hospitality, and work locations at baseline and 6 mo. When not at home, the average distance to a given location ranged from approximately 9 to 18 km.

CONCLUSIONS

Participants with CAD spent the majority of their time being sedentary. Home was the location used the most to engage in ST, LPA, and MVPA. When not home, ST, LPA, and MVPA were distributed across a variety of locations. The average distance from home to a given location suggests that proximity to home may not be a barrier from an intervention perspective.

Measurement of neighborhood-based physical activity bouts

This study examined how buffer type (shape), size, and the allocation of activity bouts inside buffers that delineate the neighborhood spatially produce different estimates of neighborhood-based physical activity. A sample of 375 adults wore a global positioning system (GPS) data logger and accelerometer over 2 weeks under free-living conditions. Analytically, the amount of neighborhood physical activity measured objectively varies substantially, not only due to buffer shape and size, but by how GPS-based activity bouts are identified with respect to containment within neighborhood buffers. To move the "neighborhood-effects" literature forward, it is critical to delineate the spatial extent of the neighborhood, given how different ways of measuring GPS-based activity containment will result in different levels of physical activity across different buffer types and sizes.

Physical Activity Measurement in Children Who Use Mobility Assistive Devices: Accelerometry and Global Positioning System

PURPOSE

To explore the usefulness of combining accelerometry, global positioning systems, and geographic information systems, to describe the time spent in different locations and physical activity (PA) duration/count levels by location for 4 children with cerebral palsy (CP) who use assistive devices (AD).

METHODS

A descriptive multiple-case study.

RESULTS

Combining the 3 instruments was useful in describing and differentiating duration by location, and amount and location of PA across differing functional levels and AD. For example, the child classified with a Gross Motor Function Classification System (GMFCS) level II exhibited large amounts of PA in community settings. In contrast, the child classified with a GMFCS level V had small amounts of PA and spent most measured time at home.

CONCLUSIONS

Combined accelerometry, global positioning system, and geographic information system have potential to capture time spent and amount/intensity of PA relative to locations within daily environments for children with CP who use AD.

Locations of Physical Activity: Where Are Children, Adolescents, and Adults Physically Active? A Systematic Review

The aim of this systematic review was to examine where physical activity (PA) takes place and how much time children, adolescents and adults spend being physically active within the identified locations. A systematic literature search was carried out in five electronic databases (PubMed, CINAHL, SPORTDiscus, PsycInfo, Scopus). For inclusion, primary studies had to identify locations of PA using device-based or self-report tools, whereas minutes of PA had to be examined using device-based tools only. Thirty-two studies were included, methodological quality and sex/gender sensitivity of the studies were assessed. The narrative data synthesis revealed that the highest average amount of daily moderate-to-vigorous PA was found in home and recreational locations, followed by school and neighborhood locations. In adults, highest average amount of daily moderate-to-vigorous PA was found in neighborhood and home locations followed by workplace and recreational locations. The majority of studies had a low risk of bias in four out of six domains; eight studies reported significant sex/gender differences in location-based PA. The results indicate that different locations are used for PA to a varying degree across the lifespan. Future research on the promotion of PA should focus on location-specific design features that encourage children, adolescents and adults to be physically active.

Residential neighborhood features associated with objectively measured walking near home: Revisiting walkability using the Automatic Context Measurement Tool (ACMT)

Many distinct characteristics of the social, natural, and built neighborhood environment have been included in walkability measures, and it is unclear which measures best describe the features of a place that support walking. We developed the Automatic Context Measurement Tool, which measures neighborhood environment characteristics from public data for any point location in the United States. We explored these characteristics in home neighborhood environments in relation to walking identified from integrated GPS, accelerometer, and travel log data from 681 residents of King Country, WA. Of 146 neighborhood characteristics, 92 (63%) were associated with walking bout counts after adjustment for individual characteristics and correction for false discovery. The strongest built environment predictor of walking bout count was housing unit count. Models using data-driven and a priori defined walkability measures exhibited similar fit statistics. Walkability measures consisting of different neighborhood characteristic measurements may capture the same underlying variation in neighborhood conditions.

Current State of Geospatial Methodologic Approaches in Canadian Population Oncology Research

Geospatial analyses are increasingly used in population oncology. We provide a first review of geospatial analysis in Canadian population oncology research, compare to international peers, and identify future directions. Geospatial-focused peer-reviewed publications from 1992-2020 were compiled using PubMed, MEDLINE, Web of Science, and Google Scholar. Abstracts were screened for data derived from a Canadian cancer registry and use of geographic information systems. Studies were classified by geospatial methodology, geospatial unit, location, cancer site, and study year. Common limitations were documented from article discussion sections. Our search identified 71 publications using data from all provincial and national cancer registries. Thirty-nine percent (N = 28) were published in the most recent 5-year period (2016-2020). Geospatial methodologies included exposure assessment (32.4%), identifying spatial associations (21.1%), proximity analysis (16.9%), cluster detection (15.5%), and descriptive mapping (14.1%). Common limitations included confounding, ecologic fallacy, not accounting for residential mobility, and small case/population sizes. Geospatial analyses are increasingly used in Canadian population oncology; however, efforts are concentrated among a few provinces and common cancer sites, and data are over a decade old. Limitations were similar to those documented internationally, and more work is needed to address them. Organized efforts are needed to identify common challenges, develop leading practices, and identify shared priorities.

The neighborhood social environment and physical activity: a systematic scoping review

BACKGROUND

Investigating the association of the neighborhood social environment on physical activity is complex. A systematic scoping review was performed to (1) provide an inventory of studies assessing the influence of the neighborhood social environment on physical activity since 2006; (2) describe methodologies employed; and (3) formulate recommendations for the field.

METHODS

Two databases were searched using terms related to 'physical activity,' 'neighborhood,' and 'social environment' in January 2017. Eligibility criteria included: 1) physical activity as an outcome; 2) neighborhood social environment as a predictor; 3) healthy population (without diagnosed clinical condition or special population); 4) observational or experimental design. Of 1352 studies identified, 181 were included. Textual data relevant to the social environment measurement and analysis were extracted from each article into qualitative software (MAXQDA) and coded to identify social environmental constructs, measurement methods, level of measurement (individual vs. aggregated to neighborhood), and whether authors explicitly recognized the construct as the social environment. The following measures were generated for each construct: number of unique measurements; % of times measured at an aggregate level; % of times authors referred to the construct as the social environment. Social environmental constructs were then grouped into larger descriptive dimensions.

RESULTS/FINDINGS

Fifty-nine social environmental constructs were identified and grouped into 9 dimensions: Crime & Safety (n = 133 studies; included in 73% of studies); Economic & Social Disadvantage (n = 55, 33%); Social Cohesion & Capital (n = 47, 26%); Social Relationships (n = 22, 12%); Social Environment (n = 16, 9%); Disorder & Incivilities (n = 15, 8%); Sense of Place/Belonging (n = 8, 4%); Discrimination/Segregation (n = 3, 2%); Civic Participation & Engagement (n = 2, 1%). Across all articles, the social environment was measured using 176 different methods, was measured at an aggregate-level 38% of the time, and referred to as the social environment 23% of the time.

CONCLUSIONS

Inconsistent terminology, definitions, and measurement of the social environment and the lack of explicit language identifying constructs as the social environment make it challenging to compare results across studies and draw conclusions. Improvements are needed to increase our understanding of social environmental correlates and/or determinants of physical activity and facilitate cross-disciplinary conversations necessary to effectively intervene to promote physical activity.

TRIAL REGISTRATION

PROSPERO CRD42017059580.

Methodologies for assessing contextual exposure to the built environment in physical activity studies: A systematic review

Growing research has integrated Global Positioning Systems (GPS), Geographic Information Systems (GIS), and accelerometry in studying effects of built environment on physical activity outcomes. This systematic review aimed to summarize current geospatial methods of assessing contextual exposure to the built environment in these studies. Based on reviewing 79 eligible articles, methods were identified and grouped into three main categories based on similarities in their approaches as follows: domain-based (67% of studies), buffer-based (22%), and activity space-based (11%). Additionally, technical barriers and potential sources of uncertainties in each category were discussed and recommendations on methodological improvements were made.

Daily Walking among Commuters: A Cross-Sectional Study of Associations with Residential, Work, and Regional Accessibility in Melbourne, Australia (2012-2014)

BACKGROUND

Most research on walking for transport has focused on the walkability of residential neighborhoods, overlooking the contribution of places of work/study and the ease with which destinations outside the immediate neighborhood can be accessed, referred to as regional accessibility.

OBJECTIVES

We aimed to examine if local accessibility/walkability around place of work/study and regional accessibility are independently and interactively associated with walking.

METHODS

A sample of 4,913 adult commuters was derived from a household travel survey in Melbourne, Australia (2012-2014). Local accessibility was measured as the availability of destinations within an 800-m pedestrian network from homes and places of work/education using a local living index [LLI; 0-3 (low), 4-6, 7-9, and 10-12 (high) destinations]. Regional accessibility was estimated using employment opportunity, commute travel time by mode, and public transport accessibility. Every individual's potential minutes of walking for each level of exposure (observed and counter to fact) were predicted using multivariable regression models including confounders and interaction terms. For each contrast of exposure levels of interest, the corresponding within-individual differences in predicted walking were averaged across individuals to estimate marginal effects.

RESULTS

High LLI at home and work/education was associated with more minutes walking than low LLI by 3.9 [95% confidence interval (CI): 2.3, 5.5] and 8.3 (95% CI: 7.3, 9.3) min, respectively, in mutually adjusted models. Across regional accessibility measures, an independent association with walking and an interactive association with LLI at work/education was observed. To take one example, the regional accessibility measure of "Jobs within 30 min by public transport" was associated with 4.3 (95% CI: 2.9, 5.7) more mins walking for high (≥30,000 jobs) compared with low (<4,000 jobs) accessibility in adjusted models. The estimated difference for high vs. low LLI (work/education) (among those with low regional accessibility) was 3.6 min (95% CI: 2.3, 4.8), while the difference for high vs. low regional accessibility (among those with low LLI) was negligible (-0.01; 95% CI: -1.2, 1.2). However, the combined effect estimate for high LLI and high regional accessibility, compared with low on both, was 12.8 min (95% CI: 11.1, 14.5), or 9.3 (95% CI: 6.7, 11.8) min/d walking more than expected based on the separate effect estimates.

CONCLUSIONS

High local living (work/education) and regional accessibility, regardless of the regional accessibility measure used, are positively associated with physical activity. High exposure to both is associated with greater benefit than exposure to one or the other alone. https://doi.org/10.1289/EHP3395.

Beyond the bus stop: where transit users walk

OBJECTIVES

Extending the health benefits of public transit requires understanding how transit use affects pedestrian activity, including pedestrian activity not directly temporally or spatially related to transit use. In this study, we identified where transit users walked on transit days compared with non-transit days within and beyond 400m and 800m buffers surrounding their home and work addresses.

METHODS

We used data collected from 2008-2013 in King County, Washington, from 221 non-physically-disabled adult transit users, who were equipped with an accelerometer, global positioning system (GPS), and travel diary. We assigned walking activity to the following buffer locations: less than and at least 400m or 800m from home, work, or home/work (the home and work buffers comprised the latter buffer). We used Poisson generalized estimating equations to estimate differences in minutes per day of total walking and minutes per day of non-transit-related walking on transit days compared with non-transit days in each location.

RESULTS

We found that durations of total walking and non-transit-related walking were greater on transit days than on non-transit days in all locations studied. When considering the home neighborhood in isolation, most of the greater duration of walking occurred beyond the home neighborhood at both 400m and 800m; results were similar when considering the work neighborhood in isolation. When considering the neighborhoods jointly (i.e., by using the home/work buffer), at 400m, most of the greater duration of walking occurred beyond the home/work neighborhood. However, at 800m, most of the greater duration of walking occurred within the home/work neighborhood.

CONCLUSIONS

Transit days were associated with greater durations of total walking and non-transit related walking within and beyond the home and work neighborhoods. Accordingly, research, design, and policy strategies focused on transit use and pedestrian activity should consider locations outside the home and work neighborhoods, in addition to locations within them.

A Location-Based Objective Assessment of Physical Activity and Sedentary Behavior in Ambulatory Hemodialysis Patients

Background:

Dialysis patients have reduced moderate to vigorous physical activity, and light physical activity. This has been shown in self-reported surveys and objective accelerometer studies. Less attention has been directed toward sedentary behavior, which is characterized by low energy expenditure (≤1.5 metabolic equivalents). Furthermore, locations where physical activity and sedentary behavior occur are largely unknown for dialysis patients.

Objectives:

The objectives of this study were (1) to determine the minutes per day of moderate to vigorous physical activity, light physical activity, and sedentary behavior for hemodialysis patients; (2) to describe differences in moderate to vigorous physical activity, light physical activity, and sedentary behavior comparing dialysis versus nondialysis days; and (3) to describe the locations where moderate to vigorous physical activity, light physical activity, and sedentary behavior occur using global positioning system (GPS) data.

Design:

Cross-sectional study.

Setting:

The study was performed at a tertiary care hospital in Nova Scotia, Canada.

Patients:

A total of 50 adult in-center hemodialysis patients consented to the study.

Measurements:

Physical activity and sedentary behavior were measured with an Actigraph-GT3X accelerometer. Location was determined using a Qstarz BT-Q1000X GPS receiver.

Methods:

Minutes of daily activity were described as was percentage of wear time for each activity level across different locations during waking hours. Physical activity intensity, quantity, and location were also analyzed according to dialysis vs nondialysis days.

Results:

Forty-three patients met requirements for accelerometer analysis, of whom 42 had GPS data. Median wear time was 836.5 min/day (interquartile range [IQR]: 788.3-918.3). Median minutes of daily wear time spent in sedentary behavior, light physical activity, and moderate to vigorous physical activity was 636 minutes (IQR: 594.1-730.1), 178 minutes (IQR: 144-222.1), and 1.6 minutes (IQR: 0.6-7.7), respectively. Proportion of daily wear time spent in sedentary behavior, light physical activity, and moderate to vigorous physical activity was 78.4% (IQR: 70.7-84.0), 21.5% (IQR: 16.0-26.9), and 0.2% (IQR: 0.1-1.1), respectively. Home was the dominant location for total linked accelerometer-GPS time (59.4%, IQR: 46.9-69.5) as well as for each prespecified level of activity. Significantly more sedentary behavior and less light physical activity occurred on dialysis days compared with nondialysis days (P ≤ .01, respectively). Moderate to vigorous physical activity did not differ significantly between dialysis and nondialysis days.

Limitations:

Small sample size from a single academic center may limit generalizability. Difficult to engage population as less than half of eligible dialysis patients provided consent. Physical activity may have been underestimated as devices were not worn for all waking hours or aquatic activities, and hip-based accelerometers may not capture stationary exercise.

Conclusions:

Ambulatory, in-center hemodialysis patients exhibit substantial sedentary behavior and minimal physical activity across a limited range of locations. Given the sedentary tendencies of this population, focus should be directed on increasing physical activity at any location frequented. Home-based exercise programs may serve as a potential adjunct to established intradialytic-based therapies given the amount of time spent in the home environment.

Assessing Physical Activities Occurring on Sidewalks and Streets: Protocol for a Cross-Sectional Study

Background

A considerable proportion of outdoor physical activity (PA) is done on sidewalks and streets, necessitating the development of a reliable measure of PA performed in these settings. The Block Walk Method (BWM) is one of the more common approaches for this purpose. Although it utilizes reliable observation techniques and displays criterion validity, it remains relatively unchanged since its introduction in 2006. It is a nontechnical, labor-intensive, first generation method. Advancing the BWM would contribute significantly to our understanding of PA behavior.

Objective

This study will develop and test a new BWM that utilizes a wearable video device (WVD) and computer video analysis to assess PAs performed on sidewalks and streets. The specific aims are to improve the BWM by incorporating a WVD (eyeglasses with a high-definition video camera in the frame) into the methodology and advance this WVD-enhanced BWM by applying machine learning and recognition software to automatically extract information on PAs occurring on the sidewalks and streets from the videos.

Methods

Trained observers (1 wearing and 1 not wearing the WVD) will walk together at a set pace along predetermined 1000 ft sidewalk and street observation routes representing low, medium, and high walkable areas. During the walks, the non-WVD observer will use the traditional BWM to record the numbers of individuals standing, sitting, walking, biking, and running in observation fields along the routes. The WVD observer will continuously video the observation fields. Later, 2 investigators will view the videos to determine the number of individuals performing PAs in the observation fields. The video data will then be analyzed automatically using multiple deep convolutional neural networks (CNNs) to determine the number of humans in the observation fields and the type of PAs performed. Bland Altman methods and intraclass correlation coefficients (ICCs) will be used to assess agreement. Potential sources of error such as occlusions (eg, trees) will be assessed using moderator analyses.

Results

Outcomes from this study are pending; however, preliminary studies supporting the research protocol indicate that the BWM is reliable for determining the PA mode (Cramer V=.89; P<.001), the address where the PA occurred (Cohen kappa=.85; P<.001), and the number engaged in an observed PA (ICC=.85; P<.001). The number of individuals seen walking along routes was correlated with several environmental characteristics such as sidewalk quality (r=.39; P=.02) and neighborhood aesthetics (r=.49; P<.001). Furthermore, we have used CNNs to detect cars, bikes, and pedestrians as well as individuals using park facilities.

Conclusions

We expect the new approach will enhance measurement accuracy while reducing the burden of data collection. In the future, the capabilities of the WVD-CNN system will be expanded to allow for the determination of other characteristics captured in videos such as caloric expenditure and environmental conditions.

International Registered Report Identifier (IRRID)

PRR1-10.2196/12976

Validation of the Block Walk Method for Assessing Physical Activity occurring on Sidewalks/Streets

The block walk method (BWM) is one of the more common approaches for assessing physical activity (PA) performed on sidewalks/streets; however, it is non-technical, labor-intensive, and lacks validation. This study aimed to validate the BWM and examine the potential for using a wearable video device (WVD) to assess PA occurring on sidewalks/streets. Trained observers (one wearing and one not wearing the WVD) walked together and performed the BWM according to a previously developed protocol along routes in low, medium, and high walkable areas. Two experts then reviewed the videos. A total of 1150 (traditional) and 1087 (video review) individuals were observed during 900 min of observation. When larger numbers of individuals were observed, the traditional method overestimated the overall number of people as well as those walking and sitting/standing, while underestimating the number of runners. Valid estimates of PA occurring on sidewalks/streets can be obtained by the traditional BWM in low and medium walkability areas and/or with non-common activities (cycling); however, its validity is questionable when sidewalks/streets use volume is high. The use of WVDs in PA assessment has the potential to establish new levels of accuracy, reduce resource requirements, and open up the possibility for retrospective analysis.

A Time-Based Objective Measure of Exposure to the Food Environment

Exposure to food environments has mainly been limited to counting food outlets near participants’ homes. This study considers food environment exposures in time and space using global positioning systems (GPS) records and fast food restaurants (FFRs) as the environment of interest. Data came from 412 participants (median participant age of 45) in the Seattle Obesity Study II who completed a survey, wore GPS receivers, and filled out travel logs for seven days. FFR locations were obtained from Public Health Seattle King County and geocoded. Exposure was conceptualized as contact between stressors (FFRs) and receptors (participants’ mobility records from GPS data) using four proximities: 21 m, 100 m, 500 m, and ½ mile. Measures included count of proximal FFRs, time duration in proximity to ≥1 FFR, and time duration in proximity to FFRs weighted by FFR counts. Self-reported exposures (FFR visits) were excluded from these measures. Logistic regressions tested associations between one or more reported FFR visits and the three exposure measures at the four proximities. Time spent in proximity to an FFR was associated with significantly higher odds of FFR visits at all proximities. Weighted duration also showed positive associations with FFR visits at 21-m and 100-m proximities. FFR counts were not associated with FFR visits. Duration of exposure helps measure the relationship between the food environment, mobility patterns, and health behaviors. The stronger associations between exposure and outcome found at closer proximities (<100 m) need further research.

Reconciling opposing perceptions of access to physical activity in a gentrifying urban neighborhood

OBJECTIVE

We sought to understand perspectives on access to physical activity in a gentrifying neighborhood.

DESIGN

This qualitative descriptive study used street intercept interviews and photo documentation.

SAMPLE

Participants included members (n = 19) of a gentrifying neighborhood in a northeastern city.

RESULTS

Participants held markedly different perceptions of opportunities for physical activity. Some participants, particularly area university students or those who are identified as White, perceived the neighborhood as favorable to physical activity, with high walkability and abundant resources. Other participants, particularly those who identified as Black or African-American, felt it was difficult to be physically active because neighborhood recreation facilities are scarce or unaffordable and parks are poorly maintained or unsafe. Multiple participants noted strategies to overcome neighborhood barriers to physical activity. Regardless of neighborhood perceptions, family and friends played an important role in influencing physical activity.

CONCLUSIONS

Nurses must consider how disparities in actual and perceived access to neighborhood resources influence participation in physical activity, particularly in gentrifying neighborhood. Public health nurses are embedded in the neighborhoods that they serve, providing a unique opportunity to understand and address the impact of neighborhood on health.

Evidence synthesis - Where are children and adults physically active and sedentary? - a rapid review of location-based studies

INTRODUCTION

Geographical positioning systems (GPS) have the capacity to provide further context around where physical activity (PA) and sedentary time (ST) are accrued especially when overlaid onto objectively measured movement. The objective of this rapid review was to summarize evidence from location-based studies which employed the simultaneous use of GPS and objective measures of PA and/or ST.

METHODS

Six databases were searched to identify studies that employed the simultaneous use of GPS and objective measures of PA or ST to quantify location of movement. Risk of bias was assessed, and a qualitative synthesis completed.

RESULTS

Searching identified 3446 articles; 59 were included in the review. A total of 22 studies in children, 17 in youth and 20 in adults were captured. The active transportation environment emerged as an important location for moderate-to-vigorous intensity physical activity (MVPA) in children, youth and adults. In children and youth, the school is an important location for MVPA, especially the schoolyard for children. Indoor locations (e.g., schools, homes) appear to be greater sources of lighter intensities of PA and ST. The review was limited by a lack of standardization in the nomenclature used to describe the locations and methods, as well as measures of variance.

CONCLUSION

Evidence suggests that the active transportation environment is a potentially important contributor of MVPA across an individual's lifespan. There is a need for future location-based studies to report on locations of all intensity of movement (including minutes and proportion) using a whole-day approach in larger representative samples.

Capturing fine-scale travel behaviors: a comparative analysis between personal activity location measurement system (PALMS) and travel diary

Background

Device-collected data from GPS and accelerometers for identifying active travel behaviors have dramatically changed research methods in transportation planning and public health. Automated algorithms have helped researchers to process large datasets with likely fewer errors than found in other collection methods (e.g., self-report travel diary). In this study, we compared travel modes identified by a commonly used automated algorithm (PALMS) that integrates GPS and accelerometer data with those obtained from travel diary estimates.

Methods

Sixty participants, who made 2100 trips during seven consecutive days of data collection, were selected from among the baseline sample of a project examining the travel behavior impact of a new light rail system in the greater Seattle, WA (USA) area. GPS point level analyses were first conducted to compare trip/place and travel mode detection results using contingency tables. Trip level analyses were then performed to investigate the effect of proportions of time overlap between travel logs and device-collected data on agreement rates. Global performance (with all subjects’ data combined) and subject-level performance of the algorithm were compared at the trip level.

Results

At the GPS point level, the overall agreement rate of travel mode detection was 77.4% between PALMS and the travel diary. The agreement rate for vehicular trip detection (84.5%) was higher than for bicycling (53.5%) and walking (58.2%). At the trip level, the global performance and subject-level performance of the PALMS algorithm were 46.4% and 42.4%, respectively. Vehicular trip detection showed highest agreement rates in all analyses. Study participants’ primary travel mode and car ownership were significantly related to the subject-level mode agreement rates.

Conclusions

The PALMS algorithm showed moderate identification power at the GPS point level. However, trip level analyses found lower agreement rates between PALMS and travel diary data, especially for active transportation. Testing different PALMS parameter settings may serve to improve the detection of active travel and help expand PALMS’s applicability in geographically different urbanized areas with a variety of travel modes.

Differences in Behavior, Time, Location, and Built Environment between Objectively Measured Utilitarian and Recreational Walking

OBJECTIVES

Utilitarian and recreational walking both contribute to physical activity. Yet walking for these two purposes may be different behaviors. We sought to provide operational definitions of utilitarian and recreational walking and to objectively measure their behavioral, spatial, and temporal differences in order to inform transportation and public health policies and interventions.

METHODS

Data were collected 2008-2009 from 651 Seattle-King County residents, wearing an accelerometer and a GPS unit, and filling-in a travel diary for 7 days. Walking activity bouts were classified as utilitarian or recreational based on whether walking had a destination or not. Differences between the two walking purposes were analyzed, adjusting for the nested structure of walking activity within participants.

RESULTS

Of the 4,905 observed walking bouts, 87.4% were utilitarian and 12.6% recreational walking. Utilitarian walking bouts were 45% shorter in duration (-12.1 min) and 9% faster in speed (+0.3km/h) than recreational walking bouts. Recreational walking occurred more frequently in the home neighborhood and was not associated with recreational land uses. Utilitarian walking occurred in areas having higher residential, employment, and street density, lower residential property value, higher area percentage of mixed-use neighborhood destinations, lower percentage of parks/trails, and lower average topographic slope than recreational walking.

CONCLUSION

Utilitarian and recreational walking are substantially different in terms of frequency, speed, duration, location, and related built environment. Policies that promote walking should adopt type-specific strategies. The high occurrence of recreational walking near home highlights the importance of the home neighborhood for this activity.

Kids in space: Measuring children's residential neighborhoods and other destinations using activity space GPS and wearable camera data

INTRODUCTION

Defining the boundary of children's 'neighborhoods' has important implications for understanding the contextual influences on child health. Additionally, insight into activities that occur outside people's neighborhoods may indicate exposures that place-based studies cannot detect. This study aimed to 1) extend current neighborhood research, using data from wearable cameras and GPS devices that were worn over several days in an urban setting; 2) define the boundary of children's neighborhoods by using leisure time activity space data; and 3) determine the destinations visited by children in their leisure time, outside their neighborhoods.

METHOD

One hundred and fourteen children (mean age 12y) from Wellington, New Zealand wore wearable cameras and GPS recorders. Residential Euclidean buffers at incremental distances were paired with GPS data (thereby identifying time spent in different places) to explore alternative definitions of neighborhood boundaries. Children's neighborhood boundary was at 500 m. A newly developed software application was used to identify 'destinations' visited outside the neighborhood by specifying space-time parameters. Image data from wearable cameras were used to determine the type of destination.

RESULTS

Children spent over half of their leisure time within 500 m of their homes. Children left their neighborhood predominantly to visit school (for leisure purposes), other residential locations (e.g. to visit friends) and food retail outlets (e.g. convenience stores, fast food outlets). Children spent more time at food retail outlets than at structured sport and in outdoor recreation locations combined.

CONCLUSION

Person-centered neighborhood definitions may serve to better represent children's everyday experiences and neighborhood exposures than previous methods based on place-based measures. As schools and other residential locations (friends and family) are important destinations outside the neighborhood, such destinations should be taken into account. The combination of image data and activity space GPS data provides a more robust approach to understanding children's neighborhoods and activity spaces.

Active Transportation on a Complete Street: Perceived and Audited Walkability Correlates

Few studies of walkability include both perceived and audited walkability measures. We examined perceived walkability (Neighborhood Environment Walkability Scale—Abbreviated, NEWS-A) and audited walkability (Irvine–Minnesota Inventory, IMI) measures for residents living within 2 km of a “complete street”—one renovated with light rail, bike lanes, and sidewalks. For perceived walkability, we found some differences but substantial similarity between our final scales and those in a prior published confirmatory factor analysis. Perceived walkability, in interaction with distance, was related to complete street active transportation. Residents were likely to have active transportation on the street when they lived nearby and perceived good aesthetics, crime safety, and traffic safety. Audited walkability, analyzed with decision trees, showed three general clusters of walkability areas, with 12 specific subtypes. A subset of walkability items (n = 11), including sidewalks, zebra-striped crosswalks, decorative sidewalks, pedestrian signals, and blank walls combined to cluster street segments. The 12 subtypes yielded 81% correct classification of residents’ active transportation. Both perceived and audited walkability were important predictors of active transportation. For audited walkability, we recommend more exploration of decision tree approaches, given their predictive utility and ease of translation into walkability interventions.

Correlates of sedentary behaviour in adults: a systematic review

OBJECTIVE

The objective of this study was to systematically review evidence to identify intrapersonal, social environmental, physical environmental and policy correlates of sedentary behaviour (SB) among adults.

METHODS

Six databases were searched to identify studies that reported on intrapersonal, social, physical environmental and/or policy correlates of SB across domains (i.e. occupational, leisure and transportation) in adults (mean ≥ 18 years old). Subgroup differences (sex, age, disease status, publication status and date, weekdays vs. weekend) were examined. Risk of bias was assessed, and a qualitative synthesis completed.

PROSPERO

CRD42014009814 RESULTS: Searching identified 22,779 articles; 257 were used in the analysis. Most studies used self-reported SB and were cross-sectional. The most studied domain of SB and correlate was leisure and intrapersonal, respectively. Consistent evidence found positive relationships between full-time employment and higher transportation and lower leisure SB; higher income/socioeconomic status and greater transportation and occupation SB; living in more urban areas and greater sitting time and total SB; ownership of televisions and greater leisure SB; and, active workstations and lower occupational SB.

CONCLUSIONS

The review identifies the need for longitudinal studies, as well as further research on factors in the physical, social and policy environments. The review also recognizes the need to standardize methodology for collecting, defining and reporting SB and correlates.

The Relationship Between Objectively Measured Walking and Risk of Pedestrian-Motor Vehicle Collision

Safe urban walking environments may improve health by encouraging physical activity, but the relationship between an individual's location and walking pattern and the risk of pedestrian-motor vehicle collision is unknown. We examined associations between individuals' walking bouts and walking risk, measured as mean exposure to the risk of pedestrian-vehicle collision. Walking bouts were ascertained through integrated accelerometry and global positioning system data and from individual travel-diary data obtained from adults in the Travel Assessment and Community Study (King County, Washington) in 2008-2009. Walking patterns were superimposed onto maps of the historical probabilities of pedestrian-vehicle collisions for intersections and midblock segments within Seattle, Washington. Mean risk of pedestrian-vehicle collision in specific walking locations was assessed according to walking exposure (duration, distance, and intensity) and participant demographic characteristics in linear mixed models. Participants typically walked in areas with low pedestrian collision risk when walking for recreation, walking at a faster pace, or taking longer-duration walks. Mean daily walking duration and distance were not associated with collision risk. Males walked in areas with higher collision risk compared with females, while vehicle owners, residents of single-family homes, and parents of young children walked in areas with lower collision risk. These findings may suggest that pedestrians moderate collision risk by using lower-risk routes.

Geospatial Approaches to Cancer Control and Population Sciences

Cancer incidence and mortality display strong geographic patterns worldwide and in the United States (1, 2). The environment where individuals live, work, and play is increasingly being recognized as important across the cancer control continuum, including the risk of cancer development, detection, diagnosis, treatment, mortality, and survivorship (3-5). At the same time, emergent technological capacity in geographic information systems (GIS) and mapping, along with increasing sophistication in applied spatial methods, has resulted in a growing research community developing and applying geospatial approaches in health research (5). Through collaborative, transdisciplinary efforts, and continued data collection efforts, there is great potential to apply these emerging geospatial approaches to various aspects of cancer prevention and control to inform etiology and target interventions and implementation of efficacious risk-reducing strategies. Cancer Epidemiol Biomarkers Prev; 26(4); 472-5. ©2017 AACRSee all the articles in this CEBP Focus section, "Geospatial Approaches to Cancer Control and Population Sciences."

Sports Facilities, Shopping Centers or Homes: What Locations are Important for Adults' Physical Activity? A Cross-Sectional Study

Physical activity (PA) is influenced by the built environment. However, little is known about the types of built environment where adults spend their time, and at what levels of PA they engage in those environments. Understanding the effect of the built environment on PA requires insight into PA behavior at different types of locations (e.g., home, work, shopping centers, and sports facilities). Therefore, this study describes where adults aged 45–65 years were active with moderate-to-vigorous intensity (MVPA), and examines associations of socio-demographic factors and neighborhood with MVPA at these locations. Participants’ (N = 308) PA was measured for seven days using accelerometers and GPS-devices. Adults spent most minutes of MVPA at home and work. Highest MVPA-ratios of total time spent at a location were achieved in sports facilities and during transport. Neighborhood characteristics and socio-demographic factors such as work status, health status and household structure, had significant effects on MVPA at various locations and on total MVPA. Understanding PA behavior at various locations may provide insights that allow professionals in different domains (e.g., health, landscaping, urban planning) to develop strategies to stimulate PA.

The association between park visitation and physical activity measured with accelerometer, GPS, and travel diary

Public parks are promoted as places that support physical activity (PA), but evidence of how park visitation contributes to overall PA is limited. This study observed adults living in the Seattle metropolitan area (n=671) for one week using accelerometer, GPS, and travel diary. Park visits, measured both objectively (GPS) and subjectively (travel diary), were temporally linked to accelerometer-measured PA. Park visits occurred at 1.4 per person-week. Participants who visited parks at least once (n=308) had an adjusted average of 14.3 (95% CI: 8.9, 19.6)min more daily PA than participants who did not visit a park. Even when park-related activity was excluded, park visitors still obtained more minutes of daily PA than non-visitors. Park visitation contributes to a more active lifestyle, but is not solely responsible for it. Parks may best serve to complement broader public health efforts to encourage PA.

Technologies That Assess the Location of Physical Activity and Sedentary Behavior: A Systematic Review

Background

The location in which physical activity and sedentary behavior are performed can provide valuable behavioral information, both in isolation and synergistically with other areas of physical activity and sedentary behavior research. Global positioning systems (GPS) have been used in physical activity research to identify outdoor location; however, while GPS can receive signals in certain indoor environments, it is not able to provide room- or subroom-level location. On average, adults spend a high proportion of their time indoors. A measure of indoor location would, therefore, provide valuable behavioral information.

Objective

This systematic review sought to identify and critique technology which has been or could be used to assess the location of physical activity and sedentary behavior.

Methods

To identify published research papers, four electronic databases were searched using key terms built around behavior, technology, and location. To be eligible for inclusion, papers were required to be published in English and describe a wearable or portable technology or device capable of measuring location. Searches were performed up to February 4, 2015. This was supplemented by backward and forward reference searching. In an attempt to include novel devices which may not yet have made their way into the published research, searches were also performed using three Internet search engines. Specialized software was used to download search results and thus mitigate the potential pitfalls of changing search algorithms.

Results

A total of 188 research papers met the inclusion criteria. Global positioning systems were the most widely used location technology in the published research, followed by wearable cameras, and radio-frequency identification. Internet search engines identified 81 global positioning systems, 35 real-time locating systems, and 21 wearable cameras. Real-time locating systems determine the indoor location of a wearable tag via the known location of reference nodes. Although the type of reference node and location determination method varies between manufacturers, Wi-Fi appears to be the most popular method.

Conclusions

The addition of location information to existing measures of physical activity and sedentary behavior will provide important behavioral information.