A GPS-Based Methodology to Analyze Environment-Health Associations at the Trip Level: Case-Crossover Analyses of Built Environments and Walking

Measuring environmental exposures in people's activity space: The need to account for travel modes and exposure decay

BACKGROUND

Accurately quantifying people's out-of-home environmental exposure is important for identifying disease risk factors. Several activity space-based exposure assessments exist, possibly leading to different exposure estimates, and have neither considered individual travel modes nor exposure-related distance decay effects.

OBJECTIVE

We aimed (1) to develop an activity space-based exposure assessment approach that included travel modes and exposure-related distance decay effects and (2) to compare the size of such spaces and the exposure estimates derived from them across typically used activity space operationalizations.

METHODS

We used 7-day-long global positioning system (GPS)-enabled smartphone-based tracking data of 269 Dutch adults. People's GPS trajectory points were classified into passive and active travel modes. Exposure-related distance decay effects were modeled through linear, exponential, and Gaussian decay functions. We performed cross-comparisons on these three functional decay models and an unweighted model in conjunction with four activity space models (i.e., home-based buffers, minimum convex polygons, two standard deviational ellipses, and time-weighted GPS-based buffers). We applied non-parametric Kruskal-Wallis tests, pair-wise Wilcoxon signed-rank tests, and Spearman correlations to assess mean differences in the extent of the activity spaces and correlations across exposures to particulate matter (PM2.5), noise, green space, and blue space.

RESULTS

Participants spent, on average, 42% of their daily life out-of-home. We observed that including travel modes into activity space delineation resulted in significantly more compact activity spaces. Exposure estimates for PM2.5 and blue space were significantly (p < 0.05) different between exposure estimates that did or did not account for travel modes, unlike noise and green space, for which differences did not reach significance. While the inclusion of distance decay effects significantly affected noise and green space exposure assessments, the decay functions applied appear not to have had any impact on the results. We found that residential exposure estimates appear appropriate for use as proxy values for the overall amount of PM2.5 exposure in people's daily lives, while GPS-based assessments are suitable for noise, green space, and blue space.

SIGNIFICANCE

For some exposures, the tested activity space definitions, although significantly correlated, exhibited differing exposure estimate results based on inclusion or exclusion of travel modes or distance decay effect. Results only supported using home-based buffer values as proxies for individuals' daily short-term PM2.5 exposure.

Examining the association between the built environment and active travel using GPS data: A study of a large residential area (Daju) in Shanghai

Automobile dependence and physical inactivity have become common health challenges for residents in large suburban residential areas. Limited literature has examined the associations between the built environment and active travel in such residential areas and the differences in these associations among residents from different neighborhoods. To avoid inaccurate results potentially derived from residence-based measures, we adopt a mobility-based approach for environmental exposure assessment. Using GPS data from 530 trips made by 98 participants in a large residential area in Shanghai, we investigate the relationships between neighborhood types, pollution perceptions, built environment features and active travel. The results indicate that residents in affordable and relocation housing make fewer active trips than those in market-rate housing, while the built environment seems to mitigate this difference. Sports facilities promote active travel while commercial facilities and road intersections discourage it. We identify significant interactions between the percentage of green space and neighborhood type, as well as floor area ratio and air pollution perception. Interventions promoting active travel include active-travel-friendly design for commercial facilities and road intersections, the provision of more sports facilities, a careful increase in floor area ratio, and the provision of more green space that is attractive to residents from different neighborhoods.

What triggers selective daily mobility among older adults? A study comparing trip and environmental characteristics between observed path and shortest path

Interest is growing in neighborhood effects on health beyond individual's home locations. However, few studies accounted for selective daily mobility bias. Selective mobility of 470 older adults (aged 67-94) living in urban and suburban areas of Luxembourg, was measured through detour percentage between their observed GPS-based paths and their shortest paths. Multilevel negative binomial regression tested associations between detour percentage, trips characteristics and environmental exposures. Detour percentage was higher for walking trips (28%) than car trips (16%). Low-speed areas and connectivity differences between observed and shortest paths vary by transport mode, indicating a potential selective daily mobility bias. The positive effects of amenities, street connectivity, low-speed areas and greenness on walking detour reinforce the existing evidence on older adults' active transportation. Urban planning interventions favoring active transportation will also promote walking trips with longer detours, helping older adults to increase their physical activity levels and ultimately promote healthy aging.

Objectively measuring the association between the built environment and physical activity: a systematic review and reporting framework

Background

Objective measures of built environment and physical activity provide the opportunity to directly compare their relationship across different populations and spatial contexts. This systematic review synthesises the current body of knowledge and knowledge gaps around the impact of objectively measured built environment metrics on physical activity levels in adults (≥ 18 years). Additionally, this review aims to address the need for improved quality of methodological reporting to evaluate studies and improve inter-study comparability though the creation of a reporting framework.

Methods

A systematic search of the literature was conducted following the PRISMA guidelines. After abstract and full-text screening, 94 studies were included in the final review. Results were synthesised using an association matrix to show overall association between built environment and physical activity variables. Finally, the new PERFORM (’Physical and Environmental Reporting Framework for Objectively Recorded Measures’) checklist was created and applied to the included studies rating them on their reporting quality across four key areas: study design and characteristics, built environment exposures, physical activity metrics, and the association between built environment and physical activity.

Results

Studies came from 21 countries and ranged from two days to six years in duration. Accelerometers and using geographic information system (GIS) to define the spatial extent of exposure around a pre-defined geocoded location were the most popular tools to capture physical activity and built environment respectively. Ethnicity and socio-economic status of participants were generally poorly reported. Moderate-to-vigorous physical activity (MVPA) was the most common metric of physical activity used followed by walking. Commonly investigated elements of the built environment included walkability, access to parks and green space. Areas where there was a strong body of evidence for a positive or negative association between the built environment and physical activity were identified. The new PERFORM checklist was devised and poorly reported areas identified, included poor reporting of built environment data sources and poor justification of method choice.

Conclusions

This systematic review highlights key gaps in studies objectively measuring the built environment and physical activity both in terms of the breadth and quality of reporting. Broadening the variety measures of the built environment and physical activity across different demographic groups and spatial areas will grow the body and quality of evidence around built environment effect on activity behaviour. Whilst following the PERFORM reporting guidance will ensure the high quality, reproducibility, and comparability of future research.

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.

GPS-based built environment measures associated with adult physical activity

Studies often rely on home locations to access built environment (BE) influences on physical activity (PA). We use GPS and accelerometer data collected for 288 individuals over a two-week period to examine eight GPS-derived BE characteristics and moderate-to-vigorous PA (MVPA) and light-to-moderate-vigorous PA (LMVPA). NDVI, parks, blue space, pedestrian-orientated intersections, and population density were associated with increased odds of LMVPA and MVPA, while traffic air pollution and noise were associated with decreased odds of LMVPA and MVPA. Associations varied by population density and when accounting for multiple BE measures. These findings provide further information on where individuals choose to be physically active.

Neighbourhood and path-based greenspace in three European countries: associations with objective physical activity

Background

Greenspace has been associated with health benefits in many contexts. An important pathway may be through outdoor physical activity. We use a novel approach to examine the link between greenspace microenvironments and outdoor physical activity levels in the HEALS study conducted in Edinburgh (UK), the Netherlands, and Athens and Thessaloniki (Greece).

Methods

Using physical activity tracker recordings, 118 HEALS participants with young children were classified with regard to daily minutes of moderate to vigorous physical activity (MVPA); 60 were classified with regard to the metabolic equivalent task (MET)-minutes for each of the 1014 active trips they made. Greenspace indicators were generated for Normalised Difference Vegetation Index (NDVI), tree cover density (TCD), and green land use (GLU). We employed linear mixed-effects models to analyse (1) daily MVPA in relation to greenspace within 300 m and 1000 m of residential addresses and (2) trip MET-minutes in relation to average greenspace within a 50 m buffer of walking/cycling routes. Models were adjusted for activity, walkability, bluespace, age, sex, car ownership, dog ownership, season, weekday/weekend day, and local meteorology.

Results

There was no clear association between MVPA-minutes and any residential greenspace measure. For example, in fully adjusted models, a 10 percentage point increase in NDVI within 300 m of home was associated with a daily increase of 1.14 (95% CI − 0.41 to 2.70) minutes of MVPA. However, we did find evidence to indicate greenspace markers were positively linked to intensity and duration of activity: in fully adjusted models, 10 percentage point increases in trip NDVI, TCD, and GLU were associated with increases of 10.4 (95% CI: 4.43 to 16.4), 10.6 (95% CI: 4.96 to 16.3), and 3.36 (95% CI: 0.00 to 6.72) MET-minutes, respectively. The magnitude of associations with greenspace tended to be greater for cycling.

Conclusions

More strenuous or longer walking and cycling trips occurred in environments with more greenspace, but levels of residential greenspace did not have a clear link with outdoor MVPA. To build on our research, we suggest future work examine larger, more diverse populations and investigate the influence of greenspace for trip purpose and route preference.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-10259-0.

Physical activity and sedentary behaviour related to transport activity assessed with multiple body-worn accelerometers: the RECORD MultiSensor Study

OBJECTIVES

The study explored the physical activity and sedentary behaviours related to transport activity. The aim was to provide evidence to support public health and transport policies encouraging people to reach daily recommendations of physical activity.

STUDY DESIGN

The study design of this study is a cross-sectional study design.

METHODS

Between 2013 and 2015, the RECORD MultiSensor Study collected data from 155 participants using two accelerometers worn on the thigh and trunk. In addition, data were collected from Global Positioning System (GPS) receivers and a GPS-based mobility survey. Relationships between transport modes and the durations and partition patterns of physical behaviours were established at the trip stage (n = 7692) and trip levels (n = 4683) using multilevel linear models with a random effect at the individual level and taking into account temporal autocorrelation.

RESULTS

Participants travelled for a median of 1 h 45 min per day. Trip stages and trips involving walking, other active modes or public transport were associated with a lower sitting duration and a higher moderate-to-vigorous physical activity (MVPA) duration than trips with a personal motorised vehicle. Using public transport was associated with a lower number of transitions between sedentary behaviours and non-sedentary behaviours, and with a higher number of transitions between non-sedentary behaviours and MVPA than relying on a private motorised vehicle.

CONCLUSIONS

This study is the first to assess the association of transport mode with physical activity and sedentary behaviours captured with thigh- and trunk-worn accelerometers at both the trip stage and trip levels. The results demonstrate that, in addition to active transport modes, encouraging people to use public transport increases physical activity and reduces sedentary time.

Linking physical and social environments with mental health in old age: a multisensor approach for continuous real-life ecological and emotional assessment

Background

Urban stress is mentioned as a plausible mechanism leading to chronic stress, which is a risk factor of depression. Yet, an accurate assessment of urban stressors in environmental epidemiology requires new methods. This article discusses methods for the sensor-based continuous assesment of geographic environments, stress and depressive symptoms in older age. We report protocols of the promoting mental well-being and healthy ageing in cities (MINDMAP) and Healthy Aging and Networks in Cities (HANC) studies nested in the RECORD Cohort as a background for a broad discussion about the theoretical foundation and monitoring tools of mobile sensing research in older age. Specifically, these studies allow one to compare how older people with and without depression perceive, navigate and use their environment; and how the built environments, networks of social contacts, and spatial mobility patterns influence the mental health of older people.

Methods

Our research protocol combines (1) Global Positioning System (GPS) and accelerometer tracking and a GPS-based mobility survey to assess participants’ mobility patterns, activity patterns and environmental exposures; (2) proximity detection to assess whether household members are close to each other; (3) ecological momentary assessment to track momentary mood and stress and environmental perceptions; and (4) electrodermal activity for the tentative prediction of stress. Data will be compared within individuals (at different times) and between persons with and without depressive symptoms.

Conclusion

The development of mobile sensing and survey technologies opens an avenue to improve understanding of the role of momentary stressors and resourcing features of residential and non-residential environments for older populations’ mental health. However, validation, privacy and ethical aspects are important issues to consider.

A systematic review of the evolution of GPS use in active living research: A state of the evidence for research, policy, and practice

This is the first systematic review to comprehensively capture Global Positioning Systems' (GPS) utilization in active living research by investigating the influence of physical contexts and social environment on all intensities of physical activity and sedentary behavior among all age groups. An extensive search of peer-reviewed literature was conducted using six databases. Out of 2026 articles identified, 129 studies met the inclusion criteria. After describing the evolution of GPS use across four themes (study designs and methods, physical contexts and social environment, active transportation, and behaviors), evidence-based recommendations for active living research, policy, and practice were generated.

Measuring objective and subjective well-being: dimensions and data sources

Well-being is an important value for people’s lives, and it could be considered as an index of societal progress. Researchers have suggested two main approaches for the overall measurement of well-being, the objective and the subjective well-being. Both approaches, as well as their relevant dimensions, have been traditionally captured with surveys. During the last decades, new data sources have been suggested as an alternative or complement to traditional data. This paper aims to present the theoretical background of well-being, by distinguishing between objective and subjective approaches, their relevant dimensions, the new data sources used for their measurement and relevant studies. We also intend to shed light on still barely unexplored dimensions and data sources that could potentially contribute as a key for public policing and social development.

The short-term association between exposure to noise and heart rate variability in daily locations and mobility contexts

BACKGROUND

Personal exposure to noise has been shown to be associated with concomitant increases and lagged decreases of short-term heart rate variability (HRV). It is however unknown whether this association differs between contexts defined by visited places or mobility as both exposure sources and expectations may be different between these contexts.

METHOD

Between July 2014 and June 2015, the RECORD MultiSensor Study collected sound level and heart rate data for 75 participants, aged 34-74 years, in their living environments for 7 days using a personal dosimeter and electrocardiography sensor on the chest. Their whereabouts were collected using a GPS receiver and a mobility survey. Short-term concomitant and lagged associations between sound level and HRV parameters were assessed within types of visited places and transport modes using mixed effects models with a random intercept for participants.

RESULTS

Increases in sound level were associated with a concomitant increase in all HR/HRV parameters, and delayed decreases in the overall HRV. Interactions between the sound level and the visited place/mobility context were documented. Compared with home, the concomitant association of sound level with HR and rMSSD was doubled within active and private-motorized transport modes, respectively.

CONCLUSIONS

The association of sound level with HR/HRV varies between visited places/mobility contexts. Future studies investigating these context-dependent associations in ambulatory settings will need to assess additional acoustical factors relating to the visited environments as well as non-acoustical factors impacting the perception of noise.

Using Google Earth™ and Geographical Information System data as method to delineate sample domains for an urban household surveys: the case of Maroua (Far North Region-Cameroon)

Background

Getting a random household sample during a survey can be expensive and very difficult especially in urban area and non-specialist. This study aimed to test an alternative method using freely available aerial imagery.

Methods

A gridded map and random selection method was used to select households for interviews. A hundred numbered of points were put along the edges of an updated map of Maroua. Then two numbers were randomly draw at a time and a line was drawn between those two numbers. A lot of different kinds of shapes of different sizes obtained were numbered. Ten shapes were randomly draw and the one selected were considered as ‘neighbourhoods’. A grid of 30 m × 30 m was drawn over each and then numbered. 202 grids considered here as households were randomly selected from the ten neighbourhoods for interviews.

Results

Out of 202 households visited, only 4 were found to be something other than a house. In addition, 30 sampled households (14.85%) were abandoned or the occupants had relocated elsewhere. This method resulted in an accuracy level of 72%, its advantage is the ability to generate efficient random sample at relatively low cost as well the time required.

Conclusions

The method proposed in this study was efficient and cost-effective when compared to the infield generation of a household inventory or Global Positioning System (GPS) tracking of households. It can then be used by researchers in low-incomes countries where funding for research is a challenge. However, this method needs to train the investigators on how to use the GPS.

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.

Combining sensor tracking with a GPS-based mobility survey to better measure physical activity in trips: public transport generates walking

Background

Policymakers need accurate data to develop efficient interventions to promote transport physical activity. Given the imprecise assessment of physical activity in trips, our aim was to illustrate novel advances in the measurement of walking in trips, including in trips incorporating non-walking modes.

Methods

We used data of 285 participants (RECORD MultiSensor Study, 2013–2015, Paris region) who carried GPS receivers and accelerometers over 7 days and underwent a phone-administered web mobility survey on the basis of algorithm-processed GPS data. With this mobility survey, we decomposed trips into unimodal trip stages with their start/end times, validated information on travel modes, and manually complemented and cleaned GPS tracks. This strategy enabled to quantify walking in trips with different modes with two alternative metrics: distance walked and accelerometry-derived number of steps taken.

Results

Compared with GPS-based mobility survey data, algorithm-only processed GPS data indicated that the median distance covered by participants per day was 25.3 km (rather than 23.4 km); correctly identified transport time vs. time at visited places in 72.7% of time; and correctly identified the transport mode in 67% of time (and only in 55% of time for public transport). The 285 participants provided data for 8983 trips (21,163 segments of observation). Participants spent a median of 7.0% of their total time in trips. The median distance walked per trip was 0.40 km for entirely walked trips and 0.85 km for public transport trips (the median number of accelerometer steps were 425 and 1352 in the corresponding trips). Overall, 33.8% of the total distance walked in trips and 37.3% of the accelerometer steps in trips were accumulated during public transport trips. Residents of the far suburbs cumulated a 1.7 times lower distance walked per day and a 1.6 times lower number of steps during trips per 8 h of wear time than residents of the Paris core city.

Conclusions

Our approach complementing GPS and accelerometer tracking with a GPS-based mobility survey substantially improved transport mode detection. Our findings suggest that promoting public transport use should be one of the cornerstones of policies to promote physical activity.

Electronic supplementary material

The online version of this article (10.1186/s12966-019-0841-2) contains supplementary material, which is available to authorized users.

Accelerometer and GPS Data to Analyze Built Environments and Physical Activity

Purpose: Most built environment studies have quantified characteristics of the areas around participants' homes. However, the environmental exposures for physical activity (PA) are spatially dynamic rather than static. Thus, merged accelerometer and global positioning system (GPS) data were utilized to estimate associations between the built environment and PA among adults. Methods: Participants (N = 142) were recruited on trails in Massachusetts and wore an accelerometer and GPS unit for 1-4 days. Two binary outcomes were created: moderate-to-vigorous PA (MVPA vs. light PA-to-sedentary); and light-to-vigorous PA (LVPA vs. sedentary). Five built environment variables were created within 50-meter buffers around GPS points: population density, street density, land use mix (LUM), greenness, and walkability index. Generalized linear mixed models were fit to examine associations between environmental variables and both outcomes, adjusting for demographic covariates. Results: Overall, in the fully adjusted models, greenness was positively associated with MVPA and LVPA (odds ratios [ORs] = 1.15, 95% confidence interval [CI] = 1.03, 1.30 and 1.25, 95% CI = 1.12, 1.41, respectively). In contrast, street density and LUM were negatively associated with MVPA (ORs = 0.69, 95% CI = 0.67, 0.71 and 0.87, 95% CI = 0.78, 0.97, respectively) and LVPA (ORs = 0.79, 95% CI = 0.77, 0.81 and 0.81, 95% CI = 0.74, 0.90, respectively). Negative associations of population density and walkability with both outcomes reached statistical significance, yet the effect sizes were small. Conclusions: Concurrent monitoring of activity with accelerometers and GPS units allowed us to investigate relationships between objectively measured built environment around GPS points and minute-by-minute PA. Negative relationships between street density and LUM and PA contrast evidence from most built environment studies in adults. However, direct comparisons should be made with caution since most previous studies have focused on spatially fixed buffers around home locations, rather than the precise locations where PA occurs.

Critical Hours and Important Environments: Relationships between Afterschool Physical Activity and the Physical Environment Using GPS, GIS and Accelerometers in 10-12-Year-Old Children

Introduction: The objective of this study was to assess relationships between children’s physical environment and afterschool leisure time physical activity (PA) and active transport. Methods: Children aged 10–12 years participated in a 7-day accelerometer and Global Positioning Systems (GPS) protocol. Afterschool leisure time PA and active transport were identified based on location- and speed-algorithms based on accelerometer, GPS and Geospatial Information Systems (GIS) data. We operationalized children’s exposure to the environment by combining home, school and the daily transport environment in individualized daily activity-spaces. Results: In total, 255 children from 20 Dutch primary schools from suburban areas provided valid data. This study showed that greenspaces and smaller distances from the children’s home to school were associated with afterschool leisure time PA and walking. Greater distances between home and school, as well as pedestrian infrastructure were associated with increased cycling. Conclusion: We demonstrated associations between environments and afterschool PA within several behavioral contexts. Future studies are encouraged to target specific behavioral domains and to develop natural experiments based on interactions between several types of the environment, child characteristics and potential socio-cognitive processes.

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.

Activity spaces in studies of the environment and physical activity: A review and synthesis of implications for causality

Activity spaces are increasingly used to understand how people interact with their environment and engage in activity but their use may raise challenges regarding causal inference. We conducted a systematic review of findings and the methodological, analytical and conceptual issues relevant to causal inference. Studies were included if they comprised a spatial summary of locations visited, assessed any part of the causal pathway between the environment, physical activity and health, and used quantitative or qualitative methods. We searched seven electronic databases in January 2018 and screened 11910 articles for eligibility. Forty-seven studies were included for review. Studies answered research questions about features of or environmental features within activity spaces using a range of spatial and temporal summary techniques. The conceptual challenge of using activity spaces to strengthen causal inference was rarely considered, although some studies discussed circularity, temporality, and plausibility. Future studies should use longitudinal and experimental designs and consider the potential and actual use of spaces for physical activity, and their relationship with total levels of activity.

Mobile Sensing in Environmental Health and Neighborhood Research

Public health research has witnessed a rapid development in the use of location, environmental, behavioral, and biophysical sensors that provide high-resolution objective time-stamped data. This burgeoning field is stimulated by the development of novel multisensor devices that collect data for an increasing number of channels and algorithms that predict relevant dimensions from one or several data channels. Global positioning system (GPS) tracking, which enables geographic momentary assessment, permits researchers to assess multiplace personal exposure areas and the algorithm-based identification of trips and places visited, eventually validated and complemented using a GPS-based mobility survey. These methods open a new space-time perspective that considers the full dynamic of residential and nonresidential momentary exposures; spatially and temporally disaggregates the behavioral and health outcomes, thus replacing them in their immediate environmental context; investigates complex time sequences; explores the interplay among individual, environmental, and situational predictors; performs life-segment analyses considering infraindividual statistical units using case-crossover models; and derives recommendations for just-in-time interventions.

Neighborhood Social Environment and Cardiovascular Disease Risk

Purpose of review

Limited physical activity (PA) and obesity are two primary risk factors for cardiovascular disease (CVD). Within a socio-ecological framework, neighborhood social environment may play a key role in influencing PA and obesity. However, the mechanisms underlying this relationship remain ambiguous. Our goals in this review are: (1) to summarize findings from the recent studies on neighborhood social environment in relation to PA and obesity as CVD risk factors, and (2) to briefly describe several innovative approaches to assessing neighborhood social environment.

Recent findings

Almost all recent studies assessed neighborhood social environment around residential areas. There were consistent associations between neighborhood social environment and PA and obesity, with some exceptions (indicating null associations or paradoxical associations). However, a focus on residential social environment may limit results because these studies did not account for any exposures occurring away from individuals' homes. Additionally, the majority of studies utilized a cross-sectional design, which limits our ability to make inferences regarding the causality of the association between social environment and PA or obesity as CV risk factors.

Summary

The majority of the studies on neighborhood social environment characterized factors around residential areas and assessed participant activity via self-reported surveys. Future research should leverage tools to account for the spatial mismatch between environmental exposures and outcomes by using global positioning systems, ecological momentary assessments, virtual neighborhood audits, and simulation modeling. These approaches can overcome major limitations by tracking individuals' daily activity and real-time perceptions of neighborhood social environments linked to CVD events.

The association between park facilities and the occurrence of physical activity during park visits

Prior research has found a positive relationship between the variety of park facilities and park-based physical activity (PA), but has not provided an estimate of the effect that additional different PA facilities have on whether an individual is active during a park visit. Using objective measures of park visits and PA from an urban sample of 225 adults in King County, Washington, we compared the variety of PA facilities in parks visited where an individual was active to PA facilities in parks where the same individual was sedentary. Each additional different PA facility at a park was associated with a 6% increased probability of being active during a visit. Adding additional different PA facilities to a park appears to have a moderate effect on whether an individual is active during a park visit, which could translate into large community health impacts when scaled up to multiple park visitors.

Wearable sensors for multifactorial personal exposure measurements - A ranking study

Individuals are simultaneously exposed to multiple environmental stressors during their daily life. Studies of adverse health effects and their etiology as well as recommendations for a healthier life style demand for an assessment of multifactorial personal exposure, according to the exposome concept. A challenge is to record exposure while people are moving in heterogeneous urban environments. Therefore wearable sensor technologies are becoming a promising way to measure personal exposure continuously: indoors, outdoors and even on the move. So far, studies which test the accuracy and usability of wearable sensors for multiple stressors are lacking. Performance evaluations are important and should take place beforehand, especially to ensure the success of citizens-oriented studies. For the first time we rigorously examined the accuracy and application suitability of wearable sensors for acoustic noise, heat (temp), particle number counts (PNC) and geo-location (GPS) in different environments. We present an extensive device inter-comparison and a ranking of the sensors based on performance measures, Taylor diagrams, Bland-Altman plots, and ease-of-use aspects. The sensors showed moderate to high correlations with precision reference devices (r = 0.4-0.99). Differences between errors outdoors and indoors suggest that environmental conditions have impact upon the accuracy of the sensors. Reaction time, recording interval, and sensor ventilation are features that play a crucial role for both ease-of-use and accuracy. We conclude with a final performance () ranking: (GPS) >  (noise) >  (temp) >  (PNC). The results are relevant for future epidemiological studies of multifactorial exposure of individuals and their health and should guide the selection of wearables when persons are involved that are technically untaught. Inferences from multifactorial data are based on the performance of all sensors and the weakest chain links are PNC and temp sensors for which our article recommends urgent improvements.

Association between residential self-selection and non-residential built environment exposures

Studies employing 'activity space' measures of the built environment do not always account for how individuals self-select into different residential and non-residential environments when testing associations with physical activity. To date, no study has examined whether preferences for walkable residential neighborhoods predict exposure to other walkable neighborhoods in non-residential activity spaces. Using a sample of 9783 university students from Toronto, Canada, we assessed how self-reported preferences for a walkable neighborhood predicted their exposure to other walkable, non-residential environments, and further whether these preferences confounded observed walkability-physical activity associations. We found that residential walkability preferences and non-residential walkability were significant associated (β = 0.42, 95% CI: (0.37, 0.47)), and further that these preferences confounded associations between non-residential walkability exposure and time spent walking (reduction in association = 10.5%). These results suggest that self-selection factors affect studies of non-residential built environment exposures.

User acceptance of location-tracking technologies in health research: Implications for study design and data quality

Research regarding place and health has undergone a revolution due to the availability of consumer-focused location-tracking devices that reveal fine-grained details of human mobility. Such research requires that participants accept such devices enough to use them in their daily lives. There is a need for a theoretically grounded understanding of acceptance of different location-tracking technology options, and its research implications. Guided by an extended Unified Theory of Acceptance and Use of Technology (UTAUT), we conducted a 28-day field study comparing 21 chronically ill people's acceptance of two leading, consumer-focused location-tracking technologies deployed for research purposes: (1) a location-enabled smartphone, and (2) a GPS watch/activity tracker. Participants used both, and completed two surveys and qualitative interviews. Findings revealed that all participants exerted effort to facilitate data capture, such as by incorporating devices into daily routines and developing workarounds to keep devices functioning. Nevertheless, the smartphone was perceived to be significantly easier and posed fewer usability challenges for participants than the watch. Older participants found the watch significantly more difficult to use. For both devices, effort expectancy was significantly associated with future willingness to participate in research although prosocial motivations overcame some concerns. Social influence, performance expectancy and use behavior were significantly associated with intentions to use the devices in participants' personal lives. Data gathered via the smartphone was significantly more complete than data gathered via the watch, primarily due to usability challenges. To make longer-term participation in location tracking research a reality, and to achieve complete data capture, researchers must minimize the effort involved in participation; this requires usable devices. For long-term location-tracking studies using similar devices, findings indicate that only smartphone-based tracking is up to the challenge.

Categorizing a continuous predictor subject to measurement error

Epidemiologists often categorize a continuous risk predictor, even when the true risk model is not a categorical one. Nonetheless, such categorization is thought to be more robust and interpretable, and thus their goal is to fit the categorical model and interpret the categorical parameters. We address the question: with measurement error and categorization, how can we do what epidemiologists want, namely to estimate the parameters of the categorical model that would have been estimated if the true predictor was observed? We develop a general methodology for such an analysis, and illustrate it in linear and logistic regression. Simulation studies are presented and the methodology is applied to a nutrition data set. Discussion of alternative approaches is also included.

An evaluation of transport mode shift policies on transport-related physical activity through simulations based on random forests

BACKGROUND

Physical inactivity is widely recognized as one of the leading causes of mortality, and transport accounts for a large part of people's daily physical activity. This study develops a simulation approach to evaluate the impact of the Ile-de-France Urban Mobility Plan (2010-2020) on physical activity, under the hypothesis that the intended transport mode shifts are realized.

METHODS

Based on the Global Transport Survey (2010, n = 21,332) and on the RECORD GPS Study (2012-2013, n = 229) from the French capital region of Paris (Ile-de-France), a simulation method was designed and tested. The simulation method used accelerometer data and random forest models to predict the impact of the transport mode shifts anticipated in the Mobility Plan on transport-related moderate-to-vigorous physical activity (T-MVPA). The transport mode shifts include less private motorized trips in favor of more public transport, walking, and biking trips.

RESULTS

The simulation model indicated a mean predicted increase of 2 min per day of T-MVPA, in case the intended transport mode shifts in the Ile-de-France Urban Mobility Plan were realized. The positive effect of the transport mode shifts on T-MVPA would, however, be larger for people with a higher level of education. This heterogeneity in the positive effect would further increase the existing inequality in transport-related physical activity by educational level.

CONCLUSIONS

The method presented in this paper showed a significant increase in transport-related physical activity in case the intended mode shifts in the Ile-de-France Urban Mobility Plan were realized. This simulation method could be applied on other important health outcomes, such as exposure to noise or air pollution, making it a useful tool to anticipate the health impact of transport interventions or policies.

Increased Walking's Additive and No Substitution Effect on Total Physical Activity

PURPOSE

We assessed the associations between a change in time spent walking and a change in total physical activity (PA) time within an urban living adult sample to test for additive or substitution effects.

METHODS

Participants living in the greater Seattle area were assessed in 2008-2009 and again 1-2 yr later (2010-2011). At each time point, they wore accelerometers and GPS units and recorded trips and locations in a travel diary for seven consecutive days. These data streams were combined to derive a more objective estimate of walking and total PA. Participants also completed the International Physical Activity Questionnaire to provide self-reported estimates of walking and total PA. Regression analyses assessed the associations between within-participant changes in objective and self-reported walking and total PA.

RESULTS

Data came from 437 participants. On average, a 1-min increase in total walking was associated with an increase in total PA of 1 min, measured by objective data, and 1.2-min, measured by self-reported data. A similar additive effect was consistently found with utilitarian, transportation, or job-related walking, measured by both objective and self-reported data. For recreational walking, the effect of change was mixed between objective and self-reported results.

CONCLUSION

Both objective and self-reported data confirmed an additive effect of utilitarian and total walking on PA.

The daycourse of place

The present paper aims to contribute to the debate about the temporal relationships between place and health. It explores the notion of 'daycourse of place' echoing the discussion which recently occurred in this journal about the 'lifecourse of place' (Andrews, 2017; Lekkas et al., 2017a, b). When highlighting the importance of time in shaping health within places, most of studies focus either on the trajectories of places over a matter of years or the daily trajectories of people in link with their activity space. However, daily trajectories of places remain a poor cousin in place and health literature. This paper is intended to overcome 'jetlag', which places suffer when they are labelled with frozen attributes over a 24-h period. It explores the values and feasibility of exploring daily trajectories of places to investigate place effects on health or to design area-based interventions for public health action. More than just a metaphor, the 'daycourse of place' appears to be an inspiring framework to elaborate the importance of daily temporal relationalities for research and action in place-based health inequalities.

Visualizing omics and clinical data: Which challenges for dealing with their variety?

Life sciences are currently going through a great number of transformations raised by the in-going revolution in high-throughput technologies for the acquisition of data. The integration of their high dimensionality, ranging from omics to clinical data, is becoming one of the most challenging stages. It involves inter-disciplinary developments with the aim to move towards an enhanced understanding of human physiology for caring purposes. Biologists, bioinformaticians, physicians and other experts related to the healthcare domain have to accompany each step of the analysis process in order to investigate and expertise these various data. In this perspective, methods related to information visualization are gaining increasing attention within life sciences. The softwares based on these methods are now well recognized to facilitate expert users' success in carrying out their data analysis tasks. This article aims at reviewing the current methods and techniques dedicated to information visualisation and their current use in software development related to omics or/and clinical data.

Mobility assessment of a rural population in the Netherlands using GPS measurements

Background

The home address is a common spatial proxy for exposure assessment in epidemiological studies but mobility may introduce exposure misclassification. Mobility can be assessed using self-reports or objectively measured using GPS logging but self-reports may not assess the same information as measured mobility. We aimed to assess mobility patterns of a rural population in the Netherlands using GPS measurements and self-reports and to compare GPS measured to self-reported data, and to evaluate correlates of differences in mobility patterns.

Method

In total 870 participants filled in a questionnaire regarding their transport modes and carried a GPS-logger for 7 consecutive days. Transport modes were assigned to GPS-tracks based on speed patterns. Correlates of measured mobility data were evaluated using multiple linear regression. We calculated walking, biking and motorised transport durations based on GPS and self-reported data and compared outcomes. We used Cohen’s kappa analyses to compare categorised self-reported and GPS measured data for time spent outdoors.

Results

Self-reported time spent walking and biking was strongly overestimated when compared to GPS measurements. Participants estimated their time spent in motorised transport accurately. Several variables were associated with differences in mobility patterns, we found for instance that obese people (BMI > 30 kg/m²) spent less time in non-motorised transport (GMR 0.69–0.74) and people with COPD tended to travel longer distances from home in motorised transport (GMR 1.42–1.51).

Conclusions

If time spent walking outdoors and biking is relevant for the exposure to environmental factors, then relying on the home address as a proxy for exposure location may introduce misclassification. In addition, this misclassification is potentially differential, and specific groups of people will show stronger misclassification of exposure than others. Performing GPS measurements and identifying explanatory factors of mobility patterns may assist in regression calibration of self-reports in other studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12942-017-0103-y) contains supplementary material, which is available to authorized users.

GPS-Based Exposure to Greenness and Walkability and Accelerometry-Based Physical Activity

Background: Physical inactivity is a risk factor for cancer that may be influenced by environmental factors. Indeed, dense and well-connected built environments and environments with natural vegetation may create opportunities for higher routine physical activity. However, studies have focused primarily on residential environments to define exposure and self-reported methods to estimate physical activity. This study explores the momentary association between minute-level global positioning systems (GPS)-based greenness exposure and time-matched objectively measured physical activity.Methods: Adult women were recruited from sites across the United States. Participants wore a GPS device and accelerometer on the hip for 7 days to assess location and physical activity at minute-level epochs. GPS records were linked to 250 m resolution satellite-based vegetation data and Census Block Group-level U.S. Environmental Protection Agency (EPA) Smart Location Database walkability data. Minute-level generalized additive mixed models were conducted to test for associations between GPS measures and accelerometer count data, accounting for repeated measures within participant and allowing for deviations from linearity using splines.Results: Among 360 adult women (mean age of 55.3 ± 10.2 years), we observed positive nonlinear relationships between physical activity and both greenness and walkability. In exploratory analyses, the relationships between environmental factors and physical activity were strongest among those who were white, had higher incomes, and who were middle-aged.Conclusions: Our results indicate that higher levels of physical activity occurred in areas with higher greenness and higher walkability.Impact: Findings suggest that planning and design policies should focus on these environments to optimize opportunities for physical activity. Cancer Epidemiol Biomarkers Prev; 26(4); 525-32. ©2017 AACRSee all the articles in this CEBP Focus section, "Geospatial Approaches to Cancer Control and Population Sciences."

Walk Score, Transportation Mode Choice, and Walking Among French Adults: A GPS, Accelerometer, and Mobility Survey Study

Background: Few studies have used GPS data to analyze the relationship between Walk Score, transportation choice and walking. Additionally, the influence of Walk Score is understudied using trips rather than individuals as statistical units. The purpose of this study is to examine associations at the trip level between Walk Score, transportation mode choice, and walking among Paris adults who were tracked with GPS receivers and accelerometers in the RECORD GPS Study. Methods: In the RECORD GPS Study, 227 participants were tracked during seven days with GPS receivers and accelerometers. Participants were also surveyed with a GPS-based web mapping application on their activities and transportation modes for all trips (6969 trips). Walk Score, which calculates neighborhood walkability, was assessed for each origin and destination of every trip. Multilevel logistic and linear regression analyses were conducted to estimate associations between Walk Score and walking in the trip or accelerometry-assessed number of steps for each trip, after adjustment for individual/neighborhood characteristics. Results: The mean overall Walk Scores for trip origins were 87.1 (SD = 14.4) and for trip destinations 87.1 (SD = 14.5). In adjusted trip-level associations between Walk Score and walking only in the trip, we found that a walkable neighborhood in the trip origin and trip destination was associated with increased odds of walking in the trip assessed in the survey. The odds of only walking in the trip were 3.48 (95% CI: 2.73 to 4.44) times higher when the Walk Score for the trip origin was “Walker’s Paradise” compared to less walkable neighborhoods (Very/Car-Dependent or Somewhat Walkable), with an identical independent effect of trip destination Walk Score on walking. The number of steps per 10 min (as assessed with accelerometry) was cumulatively higher for trips both originating and ending in walkable neighborhoods (i.e., “Very Walkable”). Conclusions: Walkable neighborhoods were associated with increases in walking among adults in Paris, as documented at the trip level. Creating walkable neighborhoods (through neighborhood design increased commercial activity) may increase walking trips and, therefore, could be a relevant health promotion strategy to increase physical activity.