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

Qualitative exploration of determinants of active mobility and social participation in Urban neighborhoods: individual perceptions over objective factors?

BACKGROUND

Urban neighborhood environments play an important role in facilitating or hindering residents to engage in active mobility and social participation. However, while there is much quantitative research, in-depth knowledge that contextualizes residents' subjective perceptions of barriers and facilitators of active mobility and social participation is still insufficient. Therefore, a qualitative approach was used to collect subjectively perceived barriers and facilitators of active mobility and social participation of residents from different neighborhoods with objectively determined high vs. low walkability. Furthermore, to better understand (non) concordance of objective environmental characterizations and actual levels of behavior, low and high walkability neighborhood-specific barriers, proposed improvements, and particularities that determine (non) engagement in active mobility and social participation were explored.

METHODS

Three focus groups (N = 6, N = 6, and N = 5) with 17 participants (7 women, 10 men) aged 21-64 (mean age 43.4 ± 14,6 years) were conducted utilizing a pre-structured interview guideline. Participants lived in 11 different neighborhoods with either high or low objectively determined walkability. The focus groups were transcribed verbatim, followed by a thematic analysis of the content with deductive and inductive code categories, utilizing the MAXQDA software.

RESULTS

Notable was the consensus of many perceived barriers and facilitators of active mobility and social participation along with their assignability to the same context (points-of-interest, infrastructure; safety, communication, community; topography, physical compositions, weather, aesthetics; personal / individual attitudes, influences, evaluations). Another main finding was that high and low walkability neighborhood-specific particularities were revealed that are in contrast to some objective characterizations of walkability: For example, too high density can inhibit active mobility, and too many options can inhibit social participation.

CONCLUSIONS

The consensus of many barriers and facilitators of active mobility and social participation suggests that valuable synergies could be created by coordinating interventions aiming to promote both active mobility and social participation in urban neighborhoods. Also, considering subjective perceptions of residents helps to identify neighborhood-specific factors that determine (non) engagement in active mobility and social participation. The findings can help city planners and public health officials improve the promotion of active mobility and social participation in the creation of health-enhancing urban neighborhoods.

Measuring Environmental and Behavioral Drivers of Chronic Diseases Using Smartphone-Based Digital Phenotyping: Intensive Longitudinal Observational mHealth Substudy Embedded in 2 Prospective Cohorts of Adults

BACKGROUND

Previous studies investigating environmental and behavioral drivers of chronic disease have often had limited temporal and spatial data coverage. Smartphone-based digital phenotyping mitigates the limitations of these studies by using intensive data collection schemes that take advantage of the widespread use of smartphones while allowing for less burdensome data collection and longer follow-up periods. In addition, smartphone apps can be programmed to conduct daily or intraday surveys on health behaviors and psychological well-being.

OBJECTIVE

The aim of this study was to investigate the feasibility and scalability of embedding smartphone-based digital phenotyping in large epidemiological cohorts by examining participant adherence to a smartphone-based data collection protocol in 2 ongoing nationwide prospective cohort studies.

METHODS

Participants (N=2394) of the Beiwe Substudy of the Nurses' Health Study 3 and Growing Up Today Study were followed over 1 year. During this time, they completed questionnaires every 10 days delivered via the Beiwe smartphone app covering topics such as emotions, stress and enjoyment, physical activity, access to green spaces, pets, diet (vegetables, meats, beverages, nuts and dairy, and fruits), sleep, and sitting. These questionnaires aimed to measure participants' key health behaviors to combine them with objectively assessed high-resolution GPS and accelerometer data provided by participants during the same period.

RESULTS

Between July 2021 and June 2023, we received 11.1 TB of GPS and accelerometer data from 2394 participants and 23,682 survey responses. The average follow-up time for each participant was 214 (SD 148) days. During this period, participants provided an average of 14.8 (SD 5.9) valid hours of GPS data and 13.2 (SD 4.8) valid hours of accelerometer data. Using a 10-hour cutoff, we found that 51.46% (1232/2394) and 53.23% (1274/2394) of participants had >50% of valid data collection days for GPS and accelerometer data, respectively. In addition, each participant submitted an average of 10 (SD 11) surveys during the same period, with a mean response rate of 36% across all surveys (SD 17%; median 41%). After initial processing of GPS and accelerometer data, we also found that participants spent an average of 14.6 (SD 7.5) hours per day at home and 1.6 (SD 1.6) hours per day on trips. We also recorded an average of 1046 (SD 1029) steps per day.

CONCLUSIONS

In this study, smartphone-based digital phenotyping was used to collect intensive longitudinal data on lifestyle and behavioral factors in 2 well-established prospective cohorts. Our assessment of adherence to smartphone-based data collection protocols over 1 year suggests that adherence in our study was either higher or similar to most previous studies with shorter follow-up periods and smaller sample sizes. Our efforts resulted in a large dataset on health behaviors that can be linked to spatial datasets to examine environmental and behavioral drivers of chronic disease.

A review of geospatial exposure models and approaches for health data integration

BACKGROUND

Geospatial methods are common in environmental exposure assessments and increasingly integrated with health data to generate comprehensive models of environmental impacts on public health.

OBJECTIVE

Our objective is to review geospatial exposure models and approaches for health data integration in environmental health applications.

METHODS

We conduct a literature review and synthesis.

RESULTS

First, we discuss key concepts and terminology for geospatial exposure data and models. Second, we provide an overview of workflows in geospatial exposure model development and health data integration. Third, we review modeling approaches, including proximity-based, statistical, and mechanistic approaches, across diverse exposure types, such as air quality, water quality, climate, and socioeconomic factors. For each model type, we provide descriptions, general equations, and example applications for environmental exposure assessment. Fourth, we discuss the approaches used to integrate geospatial exposure data and health data, such as methods to link data sources with disparate spatial and temporal scales. Fifth, we describe the landscape of open-source tools supporting these workflows.

Visiting natural open spaces in urban areas during pregnancy and its association with daily physical activity

We examined the association between visiting natural open spaces (NOS) and physical activity (PA) at different trimesters of pregnancy. We used GPS and accelerometer data from women residing in Donostia-San Sebastian and Barcelona. Daily visits to NOS were associated with an increase of circa 8 min of moderate to vigorous physical activity (MVPA) in the first and second trimesters of pregnancy. Women who visited NOS were more likely to meet the WHO daily PA guidelines during the first trimester. Visiting NOS can promote PA consistently during pregnancy, improving maternal health and well-being in urban settings.

Smartphone GPS-Based Exposure to Greenspace and Walkability and Accelerometer-Assessed Physical Activity During Pregnancy and Early Postpartum-Evidence from the MADRES Cohort

A growing number of studies have associated walkability and greenspace exposure with greater physical activity (PA) in women during pregnancy. However, most studies have focused on examining women's residential environments and neglected exposure in locations outside the home neighborhood. Using 350 person-days (N = 55 participants) of smartphone global positioning system (GPS) location and accelerometer data collected during the first and third trimesters and 4-6 months postpartum from 55 Hispanic pregnant women from the Maternal and Developmental Risks from Environmental and Social Stressors (MADRES) study, we examined the day-level effect of women's exposure to walkability and greenspace on their PA outcomes during pregnancy and in the early postpartum period. Moderate-to-vigorous physical activity [MVPA] minutes per day was assessed using accelerometers. Walkability and greenspace were measured using geographic information systems (GIS) within women's daily activity spaces (i.e., places visited and routes taken) recorded using a smartphone GPS and weighted by time spent. We used a generalized linear mixed-effects model to estimate the effects of daily GPS-derived environmental exposures on day-level MVPA minutes. Results showed that women engaged in 23% more MVPA minutes on days when they had some versus no exposure to parks and open spaces in activity spaces (b = 1.23; 95%CI: 1.02-1.48). In addition, protective effects of daily greenspace and walkability exposure on MVPA were stronger in the first and third trimesters, among first-time mothers, and among women who had high pre-pregnancy body mass index (BMI) and lived in least-safe neighborhoods. Our results suggest that daily greenspace and walkability exposure are important for women's PA and associated health outcomes during pregnancy and early postpartum.

New insights into grocery store visits among east Los Angeles residents using mobility data

In this study, we employed spatially aggregated population mobility data, generated from mobile phone locations in 2021, to investigate patterns of grocery store visits among residents east and northeast of Downtown Los Angeles, in which 60% of the census tracts had previously been designated as "food deserts". Further, we examined whether the store visits varied with neighborhood sociodemographics and grocery store accessibility. We found that residents averaged 0.4 trips to grocery stores per week, with only 13% of these visits within home census tracts, and 40% within home and neighboring census tracts. The mean distance from home to grocery stores was 2.2 miles. We found that people visited grocery stores more frequently when they lived in neighborhoods with higher percentages of Hispanics/Latinos, renters and foreign-born residents, and a greater number of grocery stores. This research highlights the utility of mobility data in elucidating grocery store use, and factors that may facilitate or be a barrier to store access. The results point to limitations of using geographically constrained metrics of food access like food deserts.

GPS-derived environmental exposures during pregnancy and early postpartum - Evidence from the madres cohort

The built and natural environment factors (e.g., greenspace, walkability) are associated with maternal and infant health during and after pregnancy. Most pregnancy studies assess exposures to environmental factors via static methods (i.e., residential location at a single point in time, usually 3rd trimester). These do not capture dynamic exposures encountered in activity spaces (e.g., locations one visits and paths one travels) and their changes over time. In this study, we aimed to compare daily environmental exposure estimates using residential and global positioning systems (GPS)-measured activity space approaches and evaluated potential for exposure measurement error in the former. To do this, we collected four days of continuous geolocation monitoring during the 1st and 3rd trimesters of pregnancy and at 4-6 months postpartum in sixty-two pregnant Hispanic women enrolled in the MADRES cohort. We applied residential and GPS-based methods to assess daily exposures to greenspace, access to parks and transit, and walkability, respectively. We assessed potential for exposure measurement error in residential vs GPS-based estimates using Pearson correlations for each measure overall and by study period. We found residential and GPS-based estimates of daily exposure to total areas of parks and open spaces were weakly positively correlated (r = 0.31, P < .001) across pregnancy and postpartum periods. Residential estimates of %greenspace (r = 0.52, P < .001) and tree cover (r = 0.55, P < .001) along walkable roads were moderately correlated with GPS-based estimates. Residential and GPS-based estimates of public transit proximity, pedestrian-oriented intersection density, and walkability index score were all highly positively correlated (r > 0.70, P < .001). We also found associations between residential and GPS-based estimates decreased among participants with greater daily mobility. Our findings suggest the popular approach that assessing the built and natural environment exposures using residential methods at one time point may introduce exposure measurement error in pregnancy studies. GPS-based methods, to the extent feasible, are recommended for future studies.

Statistical inference for complete and incomplete mobility trajectories under the flight-pause model

We formulate a statistical flight-pause model (FPM) for human mobility, represented by a collection of random objects, called motions, appropriate for mobile phone tracking (MPT) data. We develop the statistical machinery for parameter inference and trajectory imputation under various forms of missing data. We show that common assumptions about the missing data mechanism for MPT are not valid for the mechanism governing the random motions underlying the FPM, representing an understudied missing data phenomenon. We demonstrate the consequences of missing data and our proposed adjustments in both simulations and real data, outlining implications for MPT data collection and design.

Parenthood, spatial temporal environmental exposure, and leisure-time physical activity participation: Evidence from a micro-timescale retrospective longitudinal study

Parents with dependent children are at a high risk of physical inactivity. While previous studies have mostly focused on how parents' time constraints and changing social network may inhibit leisure time physical activity (LTPA) over the long-term, less is known about the integrated effects of parenting and spatial-temporal environmental exposure on the execution of LTPA during certain episodes of a day. By adopting an integrated social-spatiotemporal-environmental model (ST-ISEM) based on micro-timescale retrospective longitudinal analysis, we examine the association between LTPA participation and spatial-temporal environmental exposure at a micro-timescale, i.e., at the episode-level in working adults' workday, and specifically how parenting integrated with spatial-temporal environmental exposure can jointly influence episode-level LTPA participation. Using data from the day reconstruction method from 701 individuals in Shenzhen, China, we find that parenting may affect the participation of LTPA on workdays not only by shaping temporal environmental factors (time constraint path and social network path), but also by interacting with built environmental exposures (spatial path), both at the episode-level. This study contributes to the theorizing of an integrated social-environmental model for health and wellbeing by extending the ISEM from the life span to the micro-timescale and also by highlighting the importance of temporality in environmental exposure and health studies. It also contributes to the spatial temporal behavioral perspective of time geography literature by clarifying multiple pathways through which social and spatiotemporal environmental factors could interact and jointly affect health behaviors at a micro-timescale. This study contributes to the literature on parenting and LTPA decline by enriching and deepening the understanding of the time constraint and social network pathways through which parenting leads to LTPA change at the micro-timescale. While time constraints may decrease parents' LTPA at long-term, increasing physical activities related to childcare after work may strongly obstruct moderate-to-vigorous LTPA at a micro-timescale. This study also identifies a spatial pathway by which parenting hinders LTPA due to changing understanding and usage of urban spaces. This pathway warrants attention from social epidemiologists, health geographers, and urban planners since existing interventions promoting physical activity in urban spaces may be ineffective for parents.

Residential green and blue spaces with nonalcoholic fatty liver disease incidence: Mediating effect of air pollutants

BACKGROUND

This study aimed to investigate the relationship of residential green and blue spaces with incident nonalcoholic fatty liver disease (NAFLD), and explore the potential mediation effects of air pollutants and modification effect of genetic susceptibility.

METHODS

411,200 UK Biobank participants without prior liver diseases were included. Land use data were used to estimate residential green and blue spaces (land coverage percentage) at 300 m and 1000 m buffer. The study outcome was incident NAFLD, ascertained through linkage to hospital admissions and death registry records.

RESULTS

5198 NAFLD cases were documented after a median follow-up of 12.5 years. Green and blue spaces were inversely associated with the hazard of NAFLD: per standard deviation (SD) increment of green space coverage at 300 m (SD: 14.5 %; HR, 0.88, 95 %CI, 0.86-0.91) and 1000 m (SD: 14.1 %; HR, 0.88, 95 %CI, 0.86-0.91) buffer, and blue space coverage at 300 m (SD: 1.0 %; HR,0.95, 95 %CI, 0.93-0.98) and 1000 m (SD: 1.2 %; HR,0.96, 95 %CI, 0.93-0.99) buffer were related with a 4-12 % reduction of NAFLD incidence. The beneficial effects of approximately 25-52 % of green space exposure and about 5-35 % of blue space exposure on NAFLD incidence were mediated by the reduction of PM2.5, NO2 and NOx (All Pindirect effect <0.05). Moreover, genetic susceptibility of NAFLD did not modify the relationship of green and blue spaces with NAFLD incidence.

CONCLUSION

Residential green and blue spaces were inversely related to NAFLD incidence. These results suggest that green and blue spaces are modifiable factors that may help prevent NAFLD, and therefore, can be considered as a novel environmental strategy to promote liver health at the community level, rather than only at the individual level.

A Mobile Health Application Using Geolocation for Behavioral Activity Tracking

The increasing popularity of mHealth presents an opportunity for collecting rich datasets using mobile phone applications (apps). Our health-monitoring mobile application uses motion detection to track an individual's physical activity and location. The data collected are used to improve health outcomes, such as reducing the risk of chronic diseases and promoting healthier lifestyles through analyzing physical activity patterns. Using smartphone motion detection sensors and GPS receivers, we implemented an energy-efficient tracking algorithm that captures user locations whenever they are in motion. To ensure security and efficiency in data collection and storage, encryption algorithms are used with serverless and scalable cloud storage design. The database schema is designed around Mobile Advertising ID (MAID) as a unique identifier for each device, allowing for accurate tracking and high data quality. Our application uses Google's Activity Recognition Application Programming Interface (API) on Android OS or geofencing and motion sensors on iOS to track most smartphones available. In addition, our app leverages blockchain and traditional payments to streamline the compensations and has an intuitive user interface to encourage participation in research. The mobile tracking app was tested for 20 days on an iPhone 14 Pro Max, finding that it accurately captured location during movement and promptly resumed tracking after inactivity periods, while consuming a low percentage of battery life while running in the background.

The park physical activity questionnaire (Park-PAQ): A reliable measurement tool for park-based and total physical activity

BACKGROUND

Few studies have explicitly quantified the proportion of park-based physical activity to park users' overall physical activity levels. Population studies need new context-specific physical activity measurement tools to achieve this. The objective of this study was to develop a reliable measure of self-reported park use and physical activity undertaken within and outside of parks to determine the contribution that park-based physical activity makes to overall physical activity levels.

METHODS

A test-retest reliability study (n = 104) was conducted using the Park Physical Activity Questionnaire (Park-PAQ), an instrument based on the Active Australia Survey. Park-PAQ items captured the frequency and duration of walking for recreation or exercise, walking for transport, moderate and vigorous physical activity and strength, conditioning and balance activities done in parks and elsewhere.

RESULTS

Recall of doing any walking for recreation (kappa = 0.649, p < 0.001) and any vigorous physical activity (kappa = 0.772, p < 0.001) was 'substantial', recall of doing any moderate physical activity (kappa = 0.553, p < 0.001) was 'moderate/acceptable', and recall of any walking for transport (kappa = 0.840, p < 0.001) 'near perfect'. Recall of the time spent walking for recreation in parks (ICC = 0.928, p < 0.001) was 'near perfect', whilst recall of time spent doing moderate activity in parks (ICC = 0.925, p < 0.001) and vigorous activity in parks (ICC = 0.962, p < 0.001) was 'near perfect'. Time spent walking for transport in a park (ICC = 0.200, p = 0.056) showed 'poor' agreement. Repeatability of the usual level of park use was 'substantial' (kappa = 0.744).

CONCLUSIONS

The Park-PAQ reliably measures six domains of physical activity and quantifies the proportion of physical activity done in parks as a proportion of total physical activity. The Park-PAQ, used alone or embedded into park or physical activity surveys, will reliably capture context-specific activities that will optimise population level physical activity interventions, park programming and park management and design.

Association between the built environment and moderate to vigorous leisure-time physical activity among suzhou adolescents: a cross-sectional study

INTRODUCTION

Cardiovascular disease and obesity are both significantly influenced by physical inactivity. A rapidly expanding corpus of research contends that features of the built environment might encourage adolescents to lead active lives. There are still issues with the present evidence for determining which aspects of the built environment give adolescents the opportunity to engage in leisure-time physical activity (LTPA). This study looked at the relationship between the characteristics of the built environment and moderate-to-vigorous leisure-time physical activity (Leisure-time MVPA) of adolescents.

METHODS

2628 adolescents between the ages of 11 and 18 were chosen as study participants from 19 Suzhou urban communities. They must have resided in the neighborhood for longer than six months and be permanent residents there. The International Physical Activities Questionnaire (n = 2628) and the Neighborhood Environment Walkability Scale for Chinese Children (NEWS-CC) were used to collect the data. LTPA are connected to different modes: Walking, leisure-time MPA, and leisure-time VPA. Univariate analysis and multinomial logistic regression were used to screen for potential associations between the built environment and the leisure-time MVPA in adolescents.

RESULTS

Univariate analysis of the general demographic and built environment showed statistically significant differences in gender, residential density, accessibility, pedestrian safety, aesthetic and security (P < 0.05). Step by walking reference category, security (P < 0.05, OR = 1.131) were associated with adolescents' leisure-time MPA, aesthetics (P < 0.05, OR = 1.187) were associated with adolescents' leisure-time VPA, they both have a significant positive correlation.

CONCLUSION

Security was positively associated with adolescents' leisure-time MPA, aesthetics was positively associated with adolescents' leisure-time VPA. This suggests that built environment may associated with leisure-time MVPA of Suzhou adolescents.

Smartphone Global Positioning System-Based System to Assess Mobility in Health Research: Development, Accuracy, and Usability Study

BACKGROUND

As global positioning system (GPS) measurement is getting more precise and affordable, health researchers can now objectively measure mobility using GPS sensors. Available systems, however, often lack data security and means of adaptation and often rely on a permanent internet connection.

OBJECTIVE

To overcome these issues, we aimed to develop and test an easy-to-use, easy-to-adapt, and offline working app using smartphone sensors (GPS and accelerometry) for the quantification of mobility parameters.

METHODS

An Android app, a server backend, and a specialized analysis pipeline have been developed (development substudy). Parameters of mobility by the study team members were extracted from the recorded GPS data using existing and newly developed algorithms. Test measurements were performed with participants to complete accuracy and reliability tests (accuracy substudy). Usability was examined by interviewing community-dwelling older adults after 1 week of device use, followed by an iterative app design process (usability substudy).

RESULTS

The study protocol and the software toolchain worked reliably and accurately, even under suboptimal conditions, such as narrow streets and rural areas. The developed algorithms had high accuracy (97.4% correctness, F₁-score=0.975) in distinguishing dwelling periods from moving intervals. The accuracy of the stop/trip classification is fundamental to second-order analyses such as the time out of home, as they rely on a precise discrimination between the 2 classes. The usability of the app and the study protocol was piloted with older adults, which showed low barriers and easy implementation into daily routines.

CONCLUSIONS

Based on accuracy analyses and users' experience with the proposed system for GPS assessments, the developed algorithm showed great potential for app-based estimation of mobility in diverse health research contexts, including mobility patterns of community-dwelling older adults living in rural areas.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1186/s12877-021-02739-0.

Accounting for space, time, and behavior using GPS derived dynamic measures of environmental exposure

Time-weighted spatial averaging approaches (TWSA) are an increasingly utilized method for calculating exposure using global positioning system (GPS) mobility data for health-related research. They can provide a time-weighted measure of exposure, or dose, to various environments or health hazards. However, little work has been done to compare existing methodologies, nor to assess how sensitive these methods are to mobility data inputs (e.g., walking vs driving), the type of environmental data being assessed as the exposure (e.g., continuous surfaces vs points of interest), and underlying point-pattern clustering of participants (e.g., if a person is highly mobile vs predominantly stationary). Here we contrast three TWSA approaches that have been previously used or recently introduced in the literature: Kernel Density Estimation (KDE), Density Ranking (DR), and Point Overlay (PO). We feed GPS and accelerometer data from 602 participants through each method to derive time-weighted activity spaces, comparing four mobility behaviors: all movement, stationary time, walking time, and in-vehicle time. We then calculate exposure values derived from the various TWSA activity spaces with four environmental layer data types (point, line, area, surface). Similarities and differences across TWSA derived exposures for the sample and between individuals are explored, and we discuss interpretation of TWSA outputs providing recommendations for researchers seeking to apply these methods to health-related studies.

Wave 1 results of the INTerventions, Research, and Action in Cities Team (INTERACT) cohort study: Examining spatio-temporal measures for urban environments and health

Built environment interventions have the potential to improve population health and reduce health inequities. The objective of this paper is to present the first wave of the INTErventions, Research, and Action in Cities Team (INTERACT) cohort studies in Victoria, Vancouver, Saskatoon, and Montreal, Canada. We examine how our cohorts compared to Canadian census data and present summary data for our outcomes of interest (physical activity, well-being, and social connectedness). We also compare location data and activity spaces from survey data, research-grade GPS and accelerometer devices, and a smartphone app, and compile measures of proximity to select built environment interventions.

Analyzing Person-Place Interactions During Walking Episodes: Innovative Ambulatory Assessment Approach of Walking-Triggered e-Diaries

BACKGROUND

Walking behavior is positively associated with physiological and mental health as much evidence has already shown. Walking is also becoming a critical issue for health promotion in urban environments as it is the most often used form of active mobility and helps to replace carbon dioxide emissions from motorized forms of transport. It therefore contributes to mitigate the negative effects of climate change and heat islands within cities. However, to promote walking among urban dwellers and to utilize its health-enhancing potential, we need to know more about the way in which physical and social environments shape individual experiences during walking episodes. Such person-place interactions could not adequately be analyzed in former studies owing to methodological constraints.

OBJECTIVE

This study introduces walking-triggered e-diaries as an innovative ambulatory assessment approach for time-varying associations, and investigates its accuracy with 2 different validation strategies.

METHODS

The walking trigger consists of a combination of movement acceleration via an accelerometer and mobile positioning of the cellphone via GPS and transmission towers to track walking activities. The trigger starts an e-diary whenever a movement acceleration exceeds a predetermined threshold and participants' locations are identified as nonstationary outside a predefined place of residence. Every 420 (±300) seconds, repeated e-diaries were prompted as long as the trigger conditions were met. Data were assessed on 10 consecutive days. First, to investigate accuracy, we reconstructed walking routes and calculated a percentage score for all triggered prompts in relation to all walking routes where a prompt could have been triggered. Then, to provide data about its specificity, we used momentary self-reports and objectively assessed movement behavior to describe activity levels before the trigger prompted an e-diary.

RESULTS

Data of 67 participants could be analyzed and the walking trigger led to 3283 e-diary prompts, from which 2258 (68.8%) were answered. Regarding accuracy, the walking trigger prompted an e-diary on 732 of 842 (86.9%) reconstructed walking routes. Further, in 838 of 1206 (69.5%) triggered e-diaries, participants self-reported that they were currently walking outdoors. Steps and acceleration movement was higher during these self-reported walking episodes than when participants denied walking outdoors (steps: 106 vs 32; acceleration>0.2 g in 58.4% vs 19% of these situations).

CONCLUSIONS

Accuracy analysis revealed that walking-triggered e-diaries are suitable to collect different data of individuals' current experiences in situations in which a person walks outdoors. Combined with environmental data, such an approach increases knowledge about person-place interactions and provides the possibility to gain knowledge about user preferences for health-enhancing urban environments. From a methodological viewpoint, however, specificity analysis showed how changes in trigger conditions (eg, increasing the threshold for movement acceleration) lead to changes in accuracy.

Mental health in urban environments: Uncovering the black box of person-place interactions requires interdisciplinary approaches (Preprint)

Living in urban environments affects individuals' mental health through different pathways. For instance, physical activity and social participation are seen as mediators. However, aiming to understand underlying mechanisms, it is necessary to consider that the individual is interacting with its environment. In this regard, this viewpoint discusses how urban health research benefits from integration of socioecological and interdisciplinary perspectives, combined with innovative ambulatory data assessments that enable researchers to integrate different data sources. It is stated that neither focusing on the objective and accurate assessment of the environment (from the perspective of spatial sciences) nor focusing on subjectively measured individual variables (from the public health as well as a psychosocial perspective) alone is suitable to further develop the field. Addressing person-place interactions requires an interdisciplinary view on the level of theory (eg, which variables should be focused on?), assessment methods (eg, combination of time-varying objective and subjective measures), as well as data analysis and interpretation. Firstly, this viewpoint gives an overview on previous findings addressing the relationship of environmental characteristics to physical activity and mental health outcomes. We emphasize the need for approaches that allow us to appropriately assess the real-time interaction between a person and a specific environment and examine within-subject associations. This requires the assessment of environmental features, the spatial-temporal behavior of the individual, and the subjective experiences of the situation together with other individual factors, such as momentary affective states. Therefore, we finally focused on triggered study designs as an innovative ambulatory data assessment approach that allows us to capture real-time data in predefined situations (eg, while walking through a specific urban area).

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.

Time-activity and daily mobility patterns during pregnancy and early postpartum - evidence from the MADRES cohort

INTRODUCTION

Pregnant women's daily time-activity and mobility patterns determine their environmental exposures and subsequently related health effects. Most studies ignore these and assess pregnancy exposures using static residential measures.

METHODS

We conducted 4-day continuous geo-location monitoring in 62 pregnant Hispanic women, during pregnancy and early post-partum then derived trips by mode and stays, classified by context (indoor/outdoor, type). Generalized mixed-effect models were used to examine whether these patterns changed over time.

RESULTS

Women spent on average 17.3 h/day at home. Commercial and service locations were the most popular non-home destinations, while parks and open spaces were seldom visited. Women made 3.5 daily trips (63.7 min/day and approximately 25% were pedestrian-based). Women were less likely to visit commercial and services locations and make vehicle-based trips postpartum compared to the 3^rd trimester.

CONCLUSION

Our findings suggest time-activity patterns vary across pregnancy and postpartum, thus assessing exposures at stationary locations might introduce measurement error.

Stop motion: using high resolution spatiotemporal data to estimate and locate stationary and movement behaviour in an office workplace

Prolonged periods of stationary behaviour, a common occurrence in many office workplaces, are linked with a range of physical disorders. Investigating the physical context of this behaviour may be a key to developing effective interventions. This study aimed to estimate and locate the stationary and movement behaviours of office workers (n = 10) by segmenting spatiotemporal data collected over 5 days in an office work-based setting. The segmentation method achieved a balanced accuracy ≥85.5% for observation classification and ≥90% for bout classification when compared to reference data. The results show the workers spent the majority of their time stationary (Mean = 86.4%) and had on average, 28.4 stationary and 25.9 moving bouts per hour. While these findings accord with other studies, the segmented data was also visualised, revealing that the workers were stationary for periods ≥5 min at multiple locations and these locations changed across time. Practitioner Summary: This study applied a data segmentation method to classify stationary and moving behaviours from spatiotemporal data collected in an office workplace. The segmented data revealed not only what behaviours occurred but also their location, duration, and time. Segmenting spatiotemporal data may add valuable physical context to aid workplace research.

The association between Geographic Information System-based neighborhood built environmental factors and accelerometer-derived light-intensity physical activity across the lifespan: a cross-sectional study

Background

Evidence on associations between environmental factors and accelerometer-derived light-intensity physical activity (LPA) is scarce. The aim of this study was to examine associations between Geographic Information System (GIS)-based neighborhood built environmental factors and accelerometer-derived LPA, and to investigate the moderating effect of age group (adolescents, adults, older adults) on these associations.

Methods

Objective data were used from three similar observational studies conducted in Ghent (Belgium) between 2007 and 2015. Accelerometer data were collected from 1,652 participants during seven consecutive days, and GIS-based neighborhood built environmental factors (residential density, intersection density, park density, public transport density, entropy index) were calculated using sausage buffers of 500 m and 1,000 m around the home addresses of all participants. Linear mixed models were performed to estimate the associations.

Results

A small but significant negative association was observed between residential density (500 m buffer) and LPA in the total sample (B = -0.002; SE = 0.0001; p = 0.04), demonstrating that every increase of 1,000 dwellings per surface buffer was associated with a two minute decrease in LPA. Intersection density, park density, public transport density and entropy index were not related to LPA, and moderating effects of age group were absent.

Conclusions

The small association, in combination with other non-significant associations suggests that the neighborhood built environment, as classically measured in moderate-to-vigorous intensity physical activity research, is of limited importance for LPA. More research is needed to unravel how accelerometer-derived LPA is accumulated, and to gain insight into its determinants.

Cross-sectional and longitudinal associations of park coverage, greenness exposure and neighbourhood median household income with children's depressive and anxiety symptoms

AIM

Internalising symptoms and disorders often emerge in childhood and are associated with negative health outcomes into adulthood. Studies have shown neighbourhood characteristics (e.g. socio-economic composition, greenspace exposure) to be associated with depression and anxiety symptoms in adults; however, research that explores these relationships longitudinally in children is lacking. This study examined cross-sectional and longitudinal associations of neighbourhood characteristics with developmental trajectories of internalising symptoms in 202 children (ages 8-12) from the Mothers' and Their Children's Health (MATCH) Study.

METHODS

The MATCH Study is a Los Angeles-based longitudinal observational investigation of children's health outcomes with six semi-annual assessment waves across 3 years. Latent growth curve modelling was used to examine cross-sectional and longitudinal associations between child's self-reported anxiety or depressive symptoms and their neighbourhood's park coverage, greenness exposure and median household income. All models included the following as covariates: child's age, sex, ethnicity, family household income and mother's mental health measures.

RESULTS

Cross-sectionally, results indicated that neighbourhood median household income was negatively associated with children's depressive symptoms at baseline. Longitudinally, neighbourhood median household income was associated with steeper increases in children's depressive symptoms. Neither greenness exposure nor park coverage was associated with children's depressive or anxiety symptoms cross-sectionally or longitudinally.

CONCLUSIONS

Childhood plays a key factor in setting the foundations for healthy mental, social, physical and cognitive growth. Our study suggests future mental health prevention programmes in youth should cater to a multilevel approach that integrates individual, familial and neighbourhood interventions and pay special attention to their neighbourhood SES levels.

Activity space, office space: Measuring the spatial movement of office workers

A key to the development of more effective interventions to promote movement and reduce physical inactivity in office workplaces may be to measure and locate individual's spatial movement. Using an activity space estimation method, high resolution location data collected from 15 office workers over 12 days were used to estimate and analyse the location and extent of their daily spatial movement whilst in an office work-based setting. The results indicated that the method, kernel density estimation, combined with location data offers significant opportunities to not only measure and compare spatial movement behaviours but also simultaneously identify the locations where the behaviours occur. Combined with other data streams, this method will allow researchers to further investigate the influence of different environmental characteristics on these behaviours, potentially leading the development of more effective, longer lasting interventions to promote movement and reduce stationary behaviour, ultimately improving the health of office workers.

Smart Watch Versus Classic Receivers: Static Validity of Three GPS Devices in Different Types of Built Environments

In order to study the relationship between human physical activity and the design of the built environment, it is important to measure the location of human movement accurately. In this study, we compared an inexpensive GPS receiver (Holux RCV-3000) and a frequently used Garmin Forerunner 35 smart watch, with a device that has been validated and recommended for physical activity research (Qstarz BT-Q1000XT). These instruments were placed on six geodetic points, which represented a range of different environments (e.g., residential, open space, park). The coordinates recorded by each device were compared with the known coordinates of the geodetic points. There were no differences in accuracy among the three devices when averaged across the six sites. However, the Garmin was more accurate in the city center and the Holux was more accurate in the park and housing estate areas compared to the other devices. We consider the location accuracy of the Holux and the Garmin to be comparable to that of the Qstarz. Therefore, we consider these devices to be suitable instruments for locating physical activity. Researchers must also consider other differences among these devices (such as battery life) when determining if they are suitable for their research studies.

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.

Momentary associations between stress and physical activity among children using ecological momentary assessment

Chronic and acute stress may have a detrimental effect on children's physical activity. Research on stress as a predictor of children's physical activity has mostly focused on stress between children, rather than how children's within-day variation in stress may predict physical activity. The current study assessed the within- and between-effects of stress on subsequent physical activity in three different time windows using ecological momentary assessment (EMA) and accelerometry. Children (N = 190; M_{Baseline Age} =10.1±0.9, 53% female, 56% self-identified Hispanic/Latino) completed six semi-annual assessment bursts across three years. During each burst, participants responded to up to seven (weekend) or three (weekday) randomly prompted EMA surveys on smartphones for seven days and wore a waist-worn accelerometer. Multi-level structural equation modeling examined within- and between-subjects effects of stress as a predictor of children's subsequent moderate-to-vigorous physical activity (MVPA) in the 15, 30, and 60 minutes following the EMA prompt. Latent variables were created for within- and between-subjects stress were comprised of three EMA stress items. Higher than average levels of stress (within-subjects) significantly predicted lower MVPA in the subsequent 15, 30 and 60 minutes (ps < .05). Between-subjects stress was not significantly associated with subsequent MVPA (ps > .05). Results indicate that elevated momentary stress predicts less subsequent MVPA. These findings suggest that within-day fluctuations in stress may be a barrier for children engaging in physical activity. Childhood physical activity promotion and interventions should consider the role of children's stress, aim to reduce the stress children experience throughout the day, and incorporate stress coping strategies.

Children's outdoor active mobility behaviour and neighbourhood safety: a systematic review in measurement methods and future research directions

BACKGROUND

Numerous studies have examined the association between safety and primary school-aged children's forms of active mobility. However, variations in studies' measurement methods and the elements addressed have contributed to inconsistencies in research outcomes, which may be forming a barrier to advancing researchers' knowledge about this field. To assess where current research stands, we have synthesised the methodological measures in studies that examined the effects of neighbourhood safety exposure (perceived and measured) on children's outdoor active mobility behaviour and used this analysis to propose future research directions.

METHOD

A systematic search of the literature in six electronic databases was conducted using pre-defined eligibility criteria and was concluded in July 2020. Two reviewers screened the literature abstracts to determine the studies' inclusion, and two reviewers independently conducted a methodological quality assessment to rate the included studies.

RESULTS

Twenty-five peer-reviewed studies met the inclusion criteria. Active mobility behaviour and health characteristics were measured objectively in 12 out of the 25 studies and were reported in another 13 studies. Twenty-one studies overlooked spatiotemporal dimensions in their analyses and outputs. Delineations of children's neighbourhoods varied within 10 studies' objective measures, and the 15 studies that opted for subjective measures. Safety perceptions obtained in 22 studies were mostly static and primarily collected via parents, and dissimilarities in actual safety measurement methods were present in 6 studies. The identified schematic constraints in studies' measurement methods assisted in outlining a three-dimensional relationship between 'what' (determinants), 'where' (spatial) and 'when' (time) within a methodological conceptual framework.

CONCLUSIONS

The absence of standardised measurement methods among relevant studies may have led to the current diversity in findings regarding active mobility, spatial (locality) and temporal (time) characteristics, the neighbourhood, and the representation of safety. Ignorance of the existing gaps and heterogeneity in measures may impact the reliability of evidence and poses a limitation when synthesising findings, which could result in serious biases for policymakers. Given the increasing interest in children's health studies, we suggested alternatives in the design and method of measures that may guide future evidence-based research for policymakers who aim to improve children's active mobility and safety.

Objective measurement of children's physical activity geographies: A systematic search and scoping review

This study aimed to systematically identify, map out, and describe geographical information systems (GIS)-based approaches that have been employed to measure children's neighborhood geographies for physical activity behaviors. Forty studies were included, most were conducted in the USA. Heterogeneity in GIS methods and measures was found. The majority of studies estimated children's environments using Euclidean or network buffers ranging from 100 m to 5 km. No singular approach to measuring children's physical activity geographies was identified as optimal. Geographic diversity in studies as well as increased use of measures of actual neighborhood exposure are needed. Improved consistency and transparency in reporting research methods is urgently required.

•

Varied GIS measures of children's physical activity geographies were identified.

•

Evidence was heterogeneous and predominantly from the USA.

•

Most research used Euclidean or network buffers ranging from 100 m to 5 km.

•

Larger buffer sizes (i.e., ≥800 m) performed better than smaller buffer sizes.

•

No optimal approach to measuring children's activity geographies was determined.

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.

Adults' leisure-time physical activity and the neighborhood built environment: a contextual perspective

BACKGROUND

Context-free outcome measures, such as overall leisure-time physical activity (LTPA), are habitually applied to study the neighborhood built environment correlates of physical activity. This cross sectional study identifies and empirically tests potential methodological limitations related to the use of context-free measures and discusses how these may help in the interpretation of inconsistent associations between participation in moderate-to-vigorous LTPA and objectively measured neighborhood-level built environment attributes.

METHODS

We employ a public participation geographic information system (PPGIS), an advanced participatory mapping method, to study the spatial distribution of moderate-to-vigorous LTPA among adult urban Finnish residents (n 1322). Secondary sources of GIS land-use and sport facility data were used to disaggregate respondent-mapped LTPA by the behavioral context, such as indoor and outdoor sport facilities, green spaces, and other public open spaces. Associations between the use of the identified LTPA settings and a range of objectively measured neighborhood built environment attributes were studied with multilevel logistic regression models.

RESULTS

Disaggregated by behavioral context, we observed varied and partly opposite built environment correlates for LTPA. The use of indoor and outdoor sport facilities showed no significant associations with their neighborhood availability, but were significantly associated with personal-level attributes. By contrast, participation in LTPA in green and built public open space shared significant associations with access to and availability of neighborhood green space that persisted after controlling for personal-level covariates. Moreover, neighborhood distances up to 1600 m poorly captured participation in moderate-to-vigorous LTPA, as, on average, 40% of visits were located further from home. However, we found the immediate home environment to be an important LTPA setting for the least active participants.

CONCLUSIONS

This study demonstrates that LTPA can be a highly heterogeneous measure regarding both the spatial distribution and the environmental correlates of behavioral contexts. The results show that context-free LTPA outcome measures yield inconsistent associations with built environment exposure variables, challenging the applicability of such measures in designing neighborhood-level built environment interventions.