Integrating activity spaces in health research: Comparing the VERITAS activity space questionnaire with 7-day GPS tracking and prompted recall

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

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

OBJECTIVES

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

DESIGN

A systematic review.

DATA SOURCES

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

ELIGIBILITY CRITERIA

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

DATA EXTRACTION AND SYNTHESIS

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

RESULTS

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

CONCLUSIONS

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

PROSPERO REGISTRATION NUMBER

CRD42022322166.

Associations of the neighbourhood built and natural environment with cardiometabolic health indicators: A cross-sectional analysis of environmental moderators and behavioural mediators

BACKGROUND

Most studies examining the effects of neighbourhood urban design on cardiometabolic health focused solely on the built or natural environment. Also, they did not consider the roles of neighbourhood socio-economic status (SES) and ambient air pollution in the observed associations, and the extent to which these associations were mediated by physical activity and sedentary behaviours.

METHODS

We used data from the AusDiab3 study (N = 4141), a national cohort study of Australian adults to address the above-mentioned knowledge gaps. Spatial data were used to compute indices of neighbourhood walkability (population density, intersection density, non-commercial land use mix, commercial land use), natural environment (parkland and blue spaces) and air pollution (annual average concentrations of nitrogen dioxide (NO2) and fine particulate matter <2.5 μm in diameter (PM2.5)). Census indices were used to define neighbourhood SES. Clinical assessments collected data on adiposity, blood pressure, blood glucose and blood lipids. Generalised additive mixed models were used to estimate associations.

RESULTS

Neighbourhood walkability showed indirect beneficial associations with most indicators of cardiometabolic health via resistance training, walking and sitting for different purposes; indirect detrimental associations with the same indicators via vigorous gardening; and direct detrimental associations with blood pressure. The neighbourhood natural environment had beneficial indirect associations with most cardiometabolic health indicators via resistance training and leisure-time sitting, and beneficial direct associations with adiposity and blood lipids. Neighbourhood SES and air pollution moderated only a few associations of the neighbourhood environment with physical activity, blood lipids and blood pressure.

CONCLUSIONS

Within a low-density and low-pollution context, denser, walkable neighbourhoods with good access to nature may benefit residents' cardiometabolic health by facilitating the adoption of an active lifestyle. Possible disadvantages of living in denser neighbourhoods for older populations are having limited opportunities for gardening, higher levels of noise and less healthy dietary patterns associated with eating out.

A detour for snacks and beverages? A cross-sectional assessment of selective daily mobility bias in food outlet exposure along the commuting route and dietary intakes

The evidence of selective daily mobility bias distorting exposure-health associations is limited. Using 7-day smartphone-based global positioning system (GPS) tracking data for 67 Dutch adults aged 25-45, we conducted paired Wilcoxon tests to compare the absolute and relative exposure to food outlets along actual and modelled commuting routes. We fitted Tobit regressions to examine their associations with three daily snack and soft drink intake outcomes. We found significant differences in absolute food outlet exposure between two types of routes. Adjusted regression analyses yielded unexpected associations between dietary intakes and food outlet exposures. Our results suggested no evidence of a selective daily mobility bias in the association between the food environment along commuting routes and adults' snacks and soft drink consumption in this sample.

Novel Location-Based Survey Using Cognitive Interviews to Assess Geographic Networks and Hotspots of Sex and Drug Use: Implementation and Validation Study

BACKGROUND

The Ending the HIV Epidemic initiative in the United States relies on HIV hotspots to identify where to geographically target new resources, expertise, and technology. However, interventions targeted at places with high HIV transmission and infection risk, not just places with high HIV incidence, may be more effective at reducing HIV incidence and achieving health equity.

OBJECTIVE

We described the implementation and validation of a web-based activity space survey on HIV risk behaviors. The survey was intended to collect geographic information that will be used to map risk behavior hotspots as well as the geography of sexual networks in Los Angeles County.

METHODS

The survey design team developed a series of geospatial questions that follow a 3-level structure that becomes more geographically precise as participants move through the levels. The survey was validated through 9 cognitive interviews and iteratively updated based on participant feedback until the saturation of topics and technical issues was reached.

RESULTS

In total, 4 themes were identified through the cognitive interviews: functionality of geospatial questions, representation and accessibility, privacy, and length and understanding of the survey. The ease of use for the geospatial questions was critical as many participants were not familiar with mapping software. The inclusion of well-known places, landmarks, and road networks was critical for ease of use. The addition of a Google Maps interface, which was familiar to many participants, aided in collecting accurate and precise location information. The geospatial questions increased the length of the survey and warranted the inclusion of features to simplify it and speed it up. Using nicknames to refer to previously entered geographic locations limited the number of geospatial questions that appeared in the survey and reduced the time taken to complete it. The long-standing relationship between participants and the research team improved comfort to disclose sensitive geographic information related to drug use and sex. Participants in the cognitive interviews highlighted how trust and inclusive and validating language in the survey alleviated concerns related to privacy and representation.

CONCLUSIONS

This study provides promising results regarding the feasibility of using a web-based mapping survey to collect sensitive location information relevant to ending the HIV epidemic. Data collection at several geographic levels will allow for insights into spatial recall of behaviors as well as future sensitivity analysis of the spatial scale of hotspots and network characteristics. This design also promotes the privacy and comfort of participants who provide location information for sensitive topics. Key considerations for implementing this type of survey include trust from participants, community partners, or research teams to overcome concerns related to privacy and comfort. The implementation of similar surveys should consider local characteristics and knowledge when crafting the geospatial components.

Does work-related and commuting physical activity predict changes in physical activity and sedentary behavior during the transition to retirement? GPS and accelerometer study

We examined how GPS and accelerometer measured work-related and commuting physical activity contribute to changes in physical activity and sedentary behavior during the retirement transition in the Finnish Retirement and Aging study (n = 118). Lower work-related activity was associated with a decrease in sedentary time and an increase in light physical activity during retirement. Conversely, higher work-related activity was associated with an increase in sedentary time and a decrease in light physical activity, except among those active workers who also were active commuters. Thus, both work-related and commuting physical activity predict changes in physical activity and sedentary behavior when retiring.

Comparison of static and dynamic exposures to air pollution, noise, and greenness among seniors living in compact-city environments

GPS technology and tracking study designs have gained popularity as a tool to go beyond the limitations of static exposure assessments based on the subject's residence. These dynamic exposure assessment methods offer high potential upside in terms of accuracy but also disadvantages in terms of cost, sample sizes, and types of data generated. Because of that, with our study we aim to understand in which cases researchers need to use GPS-based methods to guarantee the necessary accuracy in exposure assessment. With a sample of 113 seniors living in Barcelona (Spain) we compare their estimated daily exposures to air pollution (PM2.5, PM10, NO2), noise (dB), and greenness (NDVI) using static and dynamic exposure assessment techniques. Results indicate that significant differences between static and dynamic exposure assessments are only present in selected exposures, and would thus suggest that static assessments using the place of residence would provide accurate-enough values across a number of exposures in the case of seniors. Our models for Barcelona's seniors suggest that dynamic exposure would only be required in the case of exposure to smaller particulate matter (PM2.5) and exposure to noise levels. The study signals to the need to consider both the mobility patterns and the built environment context when deciding between static or dynamic measures of exposure assessment.

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.

Survey-derived activity space-based exposures to fast food outlets and their cross-sectional associations with use of fast food outlets, diet quality and BMI

There is a need for conceptual and methodological innovation in food environment-health research. We compared different operationalizations of survey-derived activity space exposures to fast food outlets (FFOs) in associations with use of FFO, diet quality and body mass index (BMI). FFO exposure was determined for home, work and a maximum of sixteen other locations reported by 1728 Dutch adults. Considerable differences in count of FFO between locations were found. Adjusted linear regression analyses resulted in small, unexpected associations with use of FFO, diet quality and BMI, whereby the strength of associations differed between exposure measures. Using home and work areas may be a cost-efficient compromise to capture large parts of the exposure to FFOs.

Investigating where adolescents engage in moderate to vigorous physical activity and sedentary behaviour: An exploratory study

BACKGROUND

There is a persistent lack of understanding on the influence of the environment on behaviour and health. While the environment is considered an important modifiable determinant of health behaviour, past research assessing environments often relies on static, researcher-defined buffers of arbitrary distance. This likely leads to misrepresentation of true environmental exposures. This exploratory study aims to compare researcher-defined and self-drawn buffers in reflecting the spaces and time adolescents engage in physical activity (PA) and sedentary behaviour. It also investigates if adolescent's access the PA facility and greenspace nearest their home or school for PA, as well as examine how much time adolescents spent in PA at any PA facilities and greenspaces.

METHODS

Adolescents (aged 14-18 years; n = 34) were recruited from schools in West Yorkshire, England. Seven consecutive days of global positioning system (GPS) and accelerometer data were collected at 15 second intervals. Using ArcGIS, we compared 30 different researcher-defined buffers including: radial, network and ellipse buffers at 400m, 800m, 1000m, 1600m and 3000m and participant-defined self-drawn neighbourhoods to objectively measured PA and sedentary space and PA time. Location of PA was also compared to Points of Interest data to determine if adolescents use the nearest PA facility or greenspace to their home or school and to examine how much PA was undertaken within these locations.

RESULTS

Our exploratory findings show the inadequacy of researcher-defined buffer size in assessing MVPA space or sedentary space. Furthermore, less than 35% of adolescents used the greenspaces or PA facilities nearest to their home or school. Approximately 50% of time spent in PA did not occur within the home, school, PA facility, or greenspace environments.

CONCLUSION

Our exploratory findings help to begin to quantify the inadequacy of researcher-defined, and self-drawn buffers in capturing adolescent MVPA and sedentary space, as well as time spent in PA. Adolescents often do not use PA facilities and greenspaces nearest their home and school and a large proportion of PA is achieved outside PA facilities and greenspaces. Further research with larger samples are needed to confirm the findings of this exploratory study.

Investigating how researcher-defined buffers and self-drawn neighbourhoods capture adolescent availability to physical activity facilities and greenspaces: An exploratory study

BACKGROUND

Modifying the environment is considered an effective population-level approach for increasing healthy behaviours, but associations remain ambiguous. This exploratory study aims to compare researcher-defined buffers and self-drawn neighbourhoods (SDN) to objectively measured availability of physical activity (PA) facilities and greenspaces in adolescents.

METHODS

Seven consecutive days of GPS data were collected in an adolescent sample of 14-18 year olds (n = 69). Using Points of Interest and greenspace data, availability of PA opportunities within activity spaces were determined. We compared 30 different definitions of researcher-defined neighbourhoods and SDNs to objectively measured availability.

RESULTS

Findings showed low agreement for all researcher-defined buffers in measuring the availability of PA facilities in activity spaces. However, results were less clear for greenspace. SDNs also demonstrate low agreement for capturing availability to the PA environment.

CONCLUSION

This exploratory study highlights the inadequacy of researcher-defined buffers and SDNs to define availability to environmental features.

Daily space-time activities, multiple environmental exposures, and anxiety symptoms: A cross-sectional mobile phone-based sensing study

BACKGROUND

Few mobility-based studies have investigated the associations between multiple environmental exposures, including social exposures, and mental health.

OBJECTIVE

To assess how exposure to green space, blue space, noise, air pollution, and crowdedness along people's daily mobility paths are associated with anxiety symptoms.

METHODS

358 participants were cross-sectionally tracked with Global Positioning System (GPS)-enabled mobile phones. Anxiety symptoms were measured at baseline using the Generalized Anxiety Disorder-7 (GAD-7) questionnaire. Green space, blue space, noise, and air pollution were assessed based on concentric buffers of 50 m and 100 m around each GPS point. Crowdedness was measured by the number of nearby Bluetooth-enabled devices detected along the mobility paths. Multiple linear regressions with full covariate adjustment were fitted to examine anxiety-environmental exposures associations. Random forest models were applied to explore possible nonlinear associations and exposure interactions.

RESULTS

Regression results showed null linear associations between GAD-7 scores and environmental exposures. Random forest models indicated that GAD-7-environment associations varied nonlinearly with exposure levels. We found a negative association between green space and GAD-7 scores only for participants with moderate green space exposure. We observed a positive association between GAD-7 scores and noise levels above 60 dB and air pollution concentrations above 17.2 μg m^-3. Crowdedness was positively associated with GAD-7 scores, but exposure-response functions flattened out with pronounced crowdedness of >7.5. Blue space tended to be positively associated with GAD-7 scores. Random forest models ranked environmental exposures as more important to explain GAD-7 scores than linear models.

CONCLUSIONS

Our findings indicate possible nonlinear associations between mobility-based environmental exposures and anxiety symptoms. More studies are needed to obtain an in-depth understanding of underlying anxiety-environment mechanisms during daily life.

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.

From urban neighbourhood environments to cognitive health: a cross-sectional analysis of the role of physical activity and sedentary behaviours

BACKGROUND

There is a dearth of studies on the effects of the neighbourhood environment on adults' cognitive function. We examined how interrelated aspects of the built and natural neighbourhood environment, including air pollution, correlate with adults' cognitive function, and the roles of physical activity and sedentary behaviours in these associations.

METHODS

We used data from 4,141 adult urban dwellers who participated in the Australian Diabetes, Obesity and Lifestyle 3 study on socio-demographic characteristics, neighbourhood self-selection, physical activity and sedentary behaviours, and cognitive function. Neighbourhood environmental characteristics included population density, intersection density, non-commercial land use mix, and percentages of commercial land, parkland and blue space, all within 1 km residential buffers. We also calculated annual mean concentrations of NO2 and PM2.5. Generalised additive mixed models informed by directed acyclic graphs were used to estimate the total, direct and indirect effects of environmental attributes on cognitive functions and the joint-significance test was used to examine indirect effects via behaviours.

RESULTS

In the total effects models, population density and percentage of parkland were positively associated with cognitive function. A positive association of PM2.5 with memory was also observed. All neighbourhood environmental attributes were directly and/or indirectly related to cognitive functions via other environmental attributes and/or physical activity but not sedentary behaviours. Engagement in transportation walking and gardening frequency partially mediated the positive effects of the neighbourhood environment on cognitive function, while frequency of transportation walking mediated the negative effects.

CONCLUSIONS

In the context of a low-density country like Australia, denser urban environments with access to parkland may benefit residents' cognitive health by providing opportunities for participation in a diversity of activities. A more fine-grained characterisation of the neighbourhood environment may be necessary to tease out the negative and positive impacts of inter-related characteristics of urban neighbourhood environments on cognitive function.

Delineating the geographic context of physical activities: A systematic search and scoping review of the methodological approaches used in social ecological research over two decades

BACKGROUND

The social ecological approach suggests that the spatial context among other factors influence physical activity behavior. Ample research documents physical environmental effects on physical activity. Yet, to date inconsistent associations remain, which might be explained by conceptual and methodological challenges in measuring the spatial dimensions of health behavior. We review methods applied to measure the spatial contexts in the social ecological physical activity literature.

METHODS

Online databases and selected reviews were used to identify papers published between 1990 and 2020. A total of 2167 records were retrieved, from which 412 studies that used physical activity as a primary outcome variable, included measures of the physical environment and applied the main principles of the social ecological approach, were included.

RESULTS

Subjective approaches were the dominant method to capture the spatial context of physical activities. These approaches were applied in 67% (n=279) of the studies. From the objective approaches an administrative unit was most prevalent and was applied in 29% (n=118) of the studies. The most comprehensive objective spatial methods that capture the true environmental exposure, were used only in 2% (n=10) of the studies.

CONCLUSIONS

Current social ecological physical activity research applies simple conceptualizations and methods of the spatial context. While conceptual and methodological concerns have been repeatedly expressed, no substantive progress has been made in the use of spatial approaches. To further our understanding on place effects on health, future studies should carefully consider the choice of spatial approaches, and their effect on study results.

Changes in physical activity by context and residential greenness among recent retirees: Longitudinal GPS and accelerometer study

This study examined the changes in accelerometer-measured physical activity by GPS-measured contexts among Finnish retirees (n = 45 (537 measurement days)) participating in a physical activity intervention. We also assessed whether residential greenness, measured with Normalized Difference Vegetation Index, moderated the changes. Moderate-to-vigorous physical activity (MVPA) increased at home by 7 min/day, (P < 0.001) and during active travel by 5 min/day (P = 0.03). The participants with the highest vs. lowest greenness had 25 min/day greater increase in MVPA over the follow-up (P for Time*Greenness interaction = 0.04). In conclusion, retirees participating in the intervention increased their MVPA both at home and in active travel, and more so if they lived in a greener area.

GPS2space: An Open-source Python Library for Spatial Measure Extraction from GPS Data

Global Positioning System (GPS) data have become one of the routine data streams collected by wearable devices, cell phones, and social media platforms in this digital age. Such data provide research opportunities in that they may provide contextual information to elucidate where, when, and why individuals engage in and sustain particular behavioral patterns. However, raw GPS data consisting of densely sampled time series of latitude and longitude coordinate pairs do not readily convey meaningful information concerning intra-individual dynamics and inter-individual differences; substantial data processing is required. Raw GPS data need to be integrated into a Geographic Information System (GIS) and analyzed, from which the mobility and activity patterns of individuals can be derived, a process that is unfamiliar to many behavioral scientists. In this tutorial article, we introduced GPS2space, a free and open-source Python library that we developed to facilitate the processing of GPS data, integration with GIS to derive distances from landmarks of interest, as well as extraction of two spatial features: activity space of individuals and shared space between individuals, such as members of the same family. We demonstrated functions available in the library using data from the Colorado Online Twin Study to explore seasonal and age-related changes in individuals' activity space and twin siblings' shared space, as well as gender, zygosity and baseline age-related differences in their initial levels and/or changes over time. We concluded with discussions of other potential usages, caveats, and future developments of GPS2space.

GPS2space: An Open-source Python Library for Spatial Measure Extraction from GPS Data

Global Positioning System (GPS) data have become one of the routine data streams collected by wearable devices, cell phones, and social media platforms in this digital age. Such data provide research opportunities in that they may provide contextual information to elucidate where, when, and why individuals engage in and sustain particular behavioral patterns. However, raw GPS data consisting of densely sampled time series of latitude and longitude coordinate pairs do not readily convey meaningful information concerning intra-individual dynamics and inter-individual differences; substantial data processing is required. Raw GPS data need to be integrated into a Geographic Information System (GIS) and analyzed, from which the mobility and activity patterns of individuals can be derived, a process that is unfamiliar to many behavioral scientists. In this tutorial article, we introduced GPS2space, a free and open-source Python library that we developed to facilitate the processing of GPS data, integration with GIS to derive distances from landmarks of interest, as well as extraction of two spatial features: activity space of individuals and shared space between individuals, such as members of the same family. We demonstrated functions available in the library using data from the Colorado Online Twin Study to explore seasonal and age-related changes in individuals' activity space and twin siblings' shared space, as well as gender, zygosity and baseline age-related differences in their initial levels and/or changes over time. We concluded with discussions of other potential usages, caveats, and future developments of GPS2space.

Does the built environment have independent obesogenic power? Urban form and trajectories of weight gain

OBJECTIVE

To determine whether selected features of the built environment can predict weight gain in a large longitudinal cohort of adults.

METHODS

Weight trajectories over a 5-year period were obtained from electronic health records for 115,260 insured patients aged 18-64 years in the Kaiser Permanente Washington health care system. Home addresses were geocoded using ArcGIS. Built environment variables were population, residential unit, and road intersection densities captured using Euclidean-based SmartMaps at 800-m buffers. Counts of area supermarkets and fast food restaurants were obtained using network-based SmartMaps at 1600, and 5000-m buffers. Property values were a measure of socioeconomic status. Linear mixed effects models tested whether built environment variables at baseline were associated with long-term weight gain, adjusting for sex, age, race/ethnicity, Medicaid insurance, body weight, and residential property values.

RESULTS

Built environment variables at baseline were associated with differences in baseline obesity prevalence and body mass index but had limited impact on weight trajectories. Mean weight gain for the full cohort was 0.06 kg at 1 year (95% CI: 0.03, 0.10); 0.64 kg at 3 years (95% CI: 0.59, 0.68), and 0.95 kg at 5 years (95% CI: 0.90, 1.00). In adjusted regression models, the top tertile of density metrics and frequency counts were associated with lower weight gain at 5-years follow-up compared to the bottom tertiles, though the mean differences in weight change for each follow-up year (1, 3, and 5) did not exceed 0.5 kg.

CONCLUSIONS

Built environment variables that were associated with higher obesity prevalence at baseline had limited independent obesogenic power with respect to weight gain over time. Residential unit density had the strongest negative association with weight gain. Future work on the influence of built environment variables on health should also examine social context, including residential segregation and residential mobility.

Identifying the Daily Activity Spaces of Older Adults Living in a High-Density Urban Area: A Study Using the Smartphone-Based Global Positioning System Trajectory in Shanghai

The characteristics of the built environment and the configuration of public facilities can affect the health and well-being of older adults. Recognizing the range of daily activities and understanding the utilization of public facilities among older adults has become essential in planning age-friendly communities. However, traditional methods are unable to provide large-scale objective measures of older adults’ travel behaviors. To address this issue, we used the smartphone-based global positioning system (GPS) trajectory to explore the activity spaces of 76 older adults in a high-density urban community in Shanghai for 102 consecutive days. We found that activity spaces are centered around older adults’ living communities, with 46.3% within a 1.5 km distance. The older adults’ daily activities are within a 15 min walking distance, and accessibility is the most important factor when making a travel choice to parks and public facilities. We also found that the travel range and spatial distribution of points of interest are different between age and gender groups. In addition, we found that using a concave hull with Alpha shape algorithm is more applicable and robust than the traditional convex hull algorithm. This is a unique case study in a high-density urban area with objective measures for assessing the activity spaces of older adults, thus providing empirical evidence for promoting healthy aging in cities.

Accuracy of buffers and self-drawn neighbourhoods in representing adolescent GPS measured activity spaces: An exploratory study

BACKGROUND

There continues to be a lack of understanding as to the geographical area at which the environment exerts influence on behaviour and health. This exploratory study compares different potential methods of both researcher- and participant-defined definitions of neighbourhood reflect an adolescent's activity space.

METHODS

Seven consecutive days of global positioning system (GPS) tracking data were collected at 15 s intervals using a small exploratory adolescent sample of 14-18 year olds (n = 69) in West Yorkshire, England. A total of 304,581 GPS tracking points were collected and compared 30 different definitions of researcher-defined neighbourhoods including radial, network and ellipse buffers at 400 m, 800 m, 1000 m, 1600 m and 3000 m, as well as participant-defined self-drawn neighbourhoods.

RESULTS

This exploratory study supports emerging evidence cautioning against the use of static neighbourhood definitions for defining exposure. Traditional buffers (network and radial) capture at most 67% of activity space (home radial), and at worst they captured only 3.5% (school network) and range from capturing between 3 and 88% of total time. Similarly, self-drawn neighbourhoods captured only 10% of actual daily movement. Interestingly, 40% of an adolescent's self-drawn neighbourhood was not used. We also demonstrate that buffers capture a range of space (22-95%) where adolescents do not go, thus misclassifying the exposure.

CONCLUSION

Our exploratory findings demonstrate that neither researcher- nor participant-defined definition of neighbourhood adequately captures adolescent activity space. Further research with larger samples are needed to confirm the findings of this exploratory study.

Community transmission of multidrug-resistant tuberculosis is associated with activity space overlap in Lima, Peru

Background

Transmission of multidrug-resistant tuberculosis (MDRTB) requires spatial proximity between infectious cases and susceptible persons. We assess activity space overlap among MDRTB cases and community controls to identify potential areas of transmission.

Methods

We enrolled 35 MDRTB cases and 64 TB-free community controls in Lima, Peru. Cases were whole genome sequenced and strain clustering was used as a proxy for transmission. GPS data were gathered from participants over seven days. Kernel density estimation methods were used to construct activity spaces from GPS locations and the utilization distribution overlap index (UDOI) was used to quantify activity space overlap.

Results

Activity spaces of controls (median = 35.6 km², IQR = 25.1–54) were larger than cases (median = 21.3 km², IQR = 17.9–48.6) (P = 0.02). Activity space overlap was greatest among genetically clustered cases (mean UDOI = 0.63, sd = 0.67) and lowest between cases and controls (mean UDOI = 0.13, sd = 0.28). UDOI was positively associated with genetic similarity of MDRTB strains between case pairs (P < 0.001). The odds of two cases being genetically clustered increased by 22% per 0.10 increase in UDOI (OR = 1.22, CI = 1.09–1.36, P < 0.001).

Conclusions

Activity space overlap is associated with MDRTB clustering. MDRTB transmission may be occurring in small, overlapping activity spaces in community settings. GPS studies may be useful in identifying new areas of MDRTB transmission.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-05953-8.

Older adults' activity destinations before and during COVID-19 restrictions: From a variety of activities to mostly physical exercise close to home

The aim was to study various types of older adult's activity destinations (counts, frequency of visitation, and distance from home) in the pre-COVID-19 era, and to study prospectively how COVID-19-related regulations limiting mobility affected these. Using a map-based questionnaire, 75-85-year-old participants reported activity destinations, that is, any destinations for physical exercise, destinations facilitating one's outdoor mobility, and destinations for other activities, which they had visited several times during the past month. At baseline, a variety of activity destinations was reported, but during COVID-19, destinations reported markedly declined in number, they were reported predominantly for physical exercise, and they were located closer to home.

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.

Map-based assessment of older adults' life space: validity and reliability

Background

Map-based tools have recently found their way into health-related research. They can potentially be used to quantify older adults’ life-space. This study aimed to evaluate the validity (vs. GPS) and the test-retest reliability of a map-based life-space assessment (MBA).

Methods

Life-space of one full week was assessed by GPS and by MBA. MBA was repeated after approximately 3 weeks. Distance-related (mean and maximum distance from home) and area-related (convex hull, standard deviational ellipse) life-space indicators were calculated. Intraclass correlations (MBA vs. GPS and test-retest) were calculated in addition to Bland-Altman analyses (MBA vs. GPS).

Results

Fifty-eight older adults (mean age 74, standard deviation 5.5 years; 39.7% women) participated in the study. Bland-Altman analyses showed the highest agreement between methods for the maximum distance from home. Intraclass correlation coefficients ranged between 0.19 (95% confidence interval 0 to 0.47) for convex hull and 0.72 (95% confidence interval 0.52 to 0.84) for maximum distance from home. Intraclass correlation coefficients for test-retest reliability ranged between 0.04 (95% confidence interval 0 to 0.30) for convex hull and 0.43 (95% confidence interval 0.19 to 0.62) for mean distance from home.

Conclusions

While acceptable validity and reliability were found for the distance-related life-space parameters, MBA cannot be recommended for the assessment of area-related life-space parameters.

Perceived neighbourhood characteristics and depressive symptoms: Potential mediators and the moderating role of employment status

Multiple neighbourhood characteristics have been linked to depressive symptoms. However, few studies have simultaneously considered multiple mechanisms that explain this relationship, and how they might interact. Further, most studies regard exposure to the residential environment as constant, and therefore disregard variation in exposure by individual factors. This study investigates whether and to what extent stress and physical activity mediate the association between neighbourhood characteristics and depression, and also to what extent employment status moderates this relationship. A population-representative survey of n = 11,505 people in the Netherlands was conducted. Depressive symptoms were measured using the Patient Health Questionnaire (PHQ-9). Neighbourhood characteristics were perceived green and blue space, pleasantness, environmental disturbance, social cohesion and safety. Employment status was combined with place of work to establish two groups: those who were non-working or who worked from home ('at home'), and those who worked somewhere outside of the home ('working'). Multi-group structural equation modelling was employed to understand the theorised relationships for both groups. Perceived environmental disturbance, social cohesion and safety were significantly indirectly related to depressive symptoms via stress, with larger effect sizes in the 'at home' group. Pleasantness was also significantly indirectly related to depressive symptoms via stress, in the 'at home' group only. There was no evidence for physical activity as a mediator. Our findings suggest that neighbourhood social characteristics may have a greater influence on depressive symptoms than physical characteristics. Stress appears to be a key mediator of this relationship. In addition, the neighbourhood appears to exert a greater influence on those who spend more time in their neighbourhood. Interventions to promote mental health should focus on the social environment, and in particular pay attention to those who are spatially confined in poorer quality neighbourhoods.

Prediction of human active mobility in rural areas: development and validity tests of three different approaches

BACKGROUND/AIM

Active mobility may play a relevant role in the assessment of environmental exposures (e.g. traffic-related air pollution, livestock emissions), but data about actual mobility patterns are work intensive to collect, especially in large study populations, therefore estimation methods for active mobility may be relevant for exposure assessment in different types of studies. We previously collected mobility patterns in a group of 941 participants in a rural setting in the Netherlands, using week-long GPS tracking. We had information regarding personal characteristics, self-reported data regarding weekly mobility patterns and spatial characteristics. The goal of this study was to develop versatile estimates of active mobility, test their accuracy using GPS measurements and explore the implications for exposure assessment studies.

METHODS

We estimated hours/week spent on active mobility based on personal characteristics (e.g. age, sex, pre-existing conditions), self-reported data (e.g. hours spent commuting per bike) or spatial predictors such as home and work address. Estimated hours/week spent on active mobility were compared with GPS measured hours/week, using linear regression and kappa statistics.

RESULTS

Estimated and measured hours/week spent on active mobility had low correspondence, even the best predicting estimation method based on self-reported data, resulted in a R² of 0.09 and Cohen's kappa of 0.07. A visual check indicated that, although predicted routes to work appeared to match GPS measured tracks, only a small proportion of active mobility was captured in this way, thus resulting in a low validity of overall predicted active mobility.

CONCLUSIONS

We were unable to develop a method that could accurately estimate active mobility, the best performing method was based on detailed self-reported information but still resulted in low correspondence. For future studies aiming to evaluate the contribution of home-work traffic to exposure, applying spatial predictors may be appropriate. Measurements still represent the best possible tool to evaluate mobility patterns.

An activity space approach to understanding how food access is associated with dietary intake and BMI among urban, low-income African American women

Inconclusive evidence for how food environments affect health may result from an emphasis on residential neighborhood-based measures of exposure. We used an activity space approach to examine whether 1) measures of food access and 2) associations with diet and BMI differ between residential and activity space food environments among low-income African American women in Atlanta, Georgia (n = 199). Although residential and activity space environments differed across all dimensions of food access, being located farther away from 'unhealthy' outlets was associated with lower BMI in both environments. Future research should move beyond asking whether residential and activity space environments differ, toward examining if, how, and under what conditions these differences impact the estimation of health effects.

Combining social network and activity space data for health research: tools and methods

Contextual factors influencing population health have received substantial attention, especially with regard to people's social networks and the roles of built environments in their activity spaces. Yet little health research has considered spatial and social contexts simultaneously, often because of a lack of existing data. This paper presents a tool for collecting relational data on social network and activity space that extends an existing map-based questionnaire with the addition of a name generator. We then illustrate how network analysis provides a useful framework for studying connections between social and spatial contexts using data collected in the Contrasted Urban settings for Healthy Aging research project.

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.

How urban densification shapes walking behaviours in older community dwellers: a cross-sectional analysis of potential pathways of influence

BACKGROUND

Population growth, population ageing, and urbanisation are major global demographic trends that call for an examination of the impact of urban densification on older adults' health-enhancing behaviours, such as walking. No studies have examined the pathways through which urban densification may affect older adults' walking. This information is key to evidence-based, health-oriented urban and transport planning. This study aimed to identify neighbourhood environment characteristics potentially responsible for the effects of neighbourhood densification on older adults' frequency and amount of transportation and recreation walking within and outside the neighbourhood.

METHODS

The Active Lifestyle and the Environment in Chinese Seniors (ALECS) project collected self-reported data from 909 older adults (≥ 65 years) living in 128 physically and socially diverse neighbourhoods in Hong Kong (71% response rate). Walking was measured using the Neighbourhood Walking Questionnaire for Chinese Seniors. Objective residential density and other neighbourhood environmental attributes were assessed using Geographic Information Systems. Generalised additive mixed models examined the total effects of neighbourhood residential density on walking and the mediating role of other environmental attributes and car ownership.

RESULTS

A complex network of potential pathways of positive and negative influences of neighbourhood residential density on different aspects of walking was revealed. While residential density was positively related to within-neighbourhood transportation and outside-neighbourhood recreation walking only, it exhibited positive and/or negative nonlinear indirect effects on all examined aspects of walking via recreation, public transport, food/retail and street intersection densities, and/or car ownership.

CONCLUSIONS

High-density environments appear to support within-neighbourhood walking by providing access to food and retail outlets via well-connected street networks and discouraging car ownership. However, extreme density may lead to reductions in walking. Public transport density accompanying high-density areas may facilitate outside-neighbourhood walking but deter within-neighbourhood walking. The development of activity-friendly communities for ageing populations need to consider these opposing influences.

Obesity and the Built Environment: A Reappraisal

The built environment (BE) has been viewed as an important determinant of health. Numerous studies have linked BE exposure, captured using a variety of methods, to diet quality and to area prevalence of obesity, diabetes, and cardiovascular disease. First-generation studies defined the neighborhood BE as the area around the home. Second-generation studies turned from home-centric to person-centric BE measures, capturing an individual's movements in space and time. Those studies made effective uses of global positioning system tracking devices and mobile phones, sometimes coupled with accelerometers and remote sensors. Activity space metrics explored travel paths, modes, and destinations to assess BE exposure that was both person and context specific. However, as measures of the contextual exposome have become ever more fine-grained and increasingly complex, connections to long-term chronic diseases with complex etiologies, such as obesity, are in danger of being lost. Furthermore, few studies on obesity and the BE have included intermediate energy balance behaviors, such as diet and physical activity, or explored the potential roles of social interactions or psychosocial pathways. Emerging survey-based applications that identify habitual destinations and associated travel patterns may become the third generation of tools to capture health-relevant BE exposures in the long term.

Effect of changes in green spaces on mental health in older adults: a fixed effects analysis

Background

Urban green spaces have been linked to different health benefits, but longitudinal studies on the effect of green spaces on mental health are sparse and evidence often inconclusive. Our objective was to study the effect of changes in green spaces in the residential environment on changes in mental health using data with 10 years of follow-up (2004–2014).

Methods

Data from 3175 Dutch adults were linked to accessibility and availability measures of green spaces at three time points (2004/2011/2014). Mental health was measured with the Mental Health Inventory-5. Fixed effects analyses were performed to assess the effect of changes in green spaces on mental health.

Results

Cross-sectional analysis of baseline data showed significant associations between Euclidean distances to the nearest green space and mental health, with an increase of 100 m correlating with a lower mental health score of approximately 0.5 (95% CI −0.87 to −0.12) on a 0–100 scale. Fixed effects models showed no evidence for associations between changes in green spaces and changes in mental health both for the entire sample as well as for those that did not relocate during follow-up.

Conclusions

Despite observed cross-sectional correlations between the accessibility of green space in the residential environment and mental health, no evidence was found for an association between changes in green spaces and changes in mental health. If mental health and green spaces are indeed causally linked, then changes in green spaces in the Eindhoven area between 2004 and 2014 are not enough to produce a significant effect.

Assessing Older Adults' Daily Mobility: A Comparison of GPS-Derived and Self-Reported Mobility Indicators

Interest in global positioning system (GPS)-based mobility assessment for health and aging research is growing, and with it the demand for validated GPS-based mobility indicators. Time out of home (TOH) and number of activity locations (#ALs) are two indicators that are often derived from GPS data, despite lacking consensus regarding thresholds to be used to extract those as well as limited knowledge about their validity. Using 7 days of GPS and diary data of 35 older adults, we make the following three main contributions. First, we perform a sensitivity analysis to investigate how using spatial and temporal thresholds to compute TOH and #ALs affects the agreement between self-reported and GPS-based indicators. Second, we show how daily self-reported and GPS-derived mobility indicators are compared. Third, we explore whether the type and duration of self-reported activity events are related to the degree of correspondence between reported and GPS event. Highest indicator agreement was found for temporal interpolation (Tmax) of up to 5 h for both indicators, a radius (Dmax) to delineate home between 100 and 200 m for TOH, and for #ALs a spatial extent (Dmax) between 125 and 200 m, and temporal extent (Tmin) between 5 and 6 min to define an activity location. High agreement between self-reported and GPS-based indicators is obtained for TOH and moderate agreement for #ALs. While reported event type and duration impact on whether a reported event has a matching GPS event, indoor and outdoor events are detected at equal proportions. This work will help future studies to choose optimal threshold settings and will provide knowledge about the validity of mobility indicators.

Feasibility and Validity of Geographically Explicit Ecological Momentary Assessment With Recall-Aided Space-Time Budgets

We employ data from the Adolescent Health and Development in Context Study-a representative sample of urban youth ages 11-17 in and around the Columbus, OH area-to investigate the feasibility and validity of smartphone-based geographically explicit ecological momentary assessment (GEMA). Age, race, household income, familiarity with smartphones, and self-control were associated with missing global positioning systems (GPS) coverage, whereas school day was associated with discordance between percent of time at home based on GPS-only versus recall-aided space-time budget data. Fatigue from protocol compliance increases missing GPS across the week, which results in more discordance. Although some systematic differences were observed, these findings offer evidence that smartphone-based GEMA is a viable method for the collection of activity space data on urban youth.

Dynamic Urban Environmental Exposures on Depression and Suicide (NEEDS) in the Netherlands: a protocol for a cross-sectional smartphone tracking study and a longitudinal population register study

INTRODUCTION

Environmental exposures are intertwined with mental health outcomes. People are exposed to the environments in which they currently live, and to a multitude of environments along their daily movements and through their residential relocations. However, most research assumes that people are immobile, disregarding that such dynamic exposures also serve as stressors or buffers potentially associated with depression and suicide risk. The aim of the Dynamic Urban Environmental Exposures on Depression and Suicide (NEEDS) study is to examine how dynamic environmental exposures along people's daily movements and over their residential histories affect depression and suicide mortality in the Netherlands.

METHODS AND ANALYSIS

The research design comprises two studies emphasising the temporality of exposures. First, a cross-sectional study is assessing how daily exposures correlate with depression. A nationally representative survey was administered to participants recruited through stratified random sampling of the population aged 18-65 years. Survey data were enriched with smartphone-based data (eg, Global Positioning System tracking, Bluetooth sensing, social media usage, communication patterns) and environmental exposures (eg, green and blue spaces, noise, air pollution). Second, a longitudinal population register study is addressing the extent to which past environmental exposures over people's residential history affect suicide risk later in life. Statistical and machine learning-based models are being developed to quantify environment-health relations.

ETHICS AND DISSEMINATION

Ethical approval (FETC17-060) was granted by the Ethics Review Board of Utrecht University, The Netherlands. Project-related findings will be disseminated at conferences and in peer-reviewed journal papers. Other project outcomes will be made available through the project's web page, http://www.needs.sites.uu.nl.

Activity space metrics not associated with sociodemographic variables, diet or health outcomes in the Seattle Obesity Study II

BACKGROUND

Activity spaces (AS), captured using GPS tracking devices, are measures of dynamic exposure to the built environment (BE).

METHODS

Seven days of Global Positioning Systems (GPS) tracking data were obtained for 433 adult participants in the Seattle Obesity Study (SOS II). Heights and weights were measured. Dietary intakes from a food frequency questionnaire were used to calculate Healthy Eating Index (HEI 2010) scores. Linear regression analyses examined associations between AS measures: daily route length, convex hull, and radius of gyration, and diet quality and health outcomes, adjusting for covariates.

RESULTS

AS measures did not vary by age, gender, race/ethnicity, or socioeconomic status. AS measures were not associated with diet quality or with self-reported obesity or diabetes. One AS measure, route length (in miles), was associated with being employed, living in the suburbs, and with distance and time commuting to work.

CONCLUSION

Spatial mobility studies based on GPS tracking of environmental exposure need to demonstrate a link to relevant health outcomes.

The Moving to Health (M2H) approach to natural experiment research: A paradigm shift for studies on built environment and health

Improving the built environment (BE) is viewed as one strategy to improve community diets and health. The present goal is to review the literature on the effects of BE on health, highlight its limitations, and explore the growing use of natural experiments in BE research, such as the advent of new supermarkets, revitalized parks, or new transportation systems. Based on recent studies on movers, a paradigm shift in built-environment health research may be imminent. Following the classic Moving to Opportunity study in the US, the present Moving to Health (M2H) strategy takes advantage of the fact that changing residential location can entail overnight changes in multiple BE variables. The necessary conditions for applying the M2H strategy to Geographic Information Systems (GIS) databases and to large longitudinal cohorts are outlined below. Also outlined are significant limitations of this approach, including the use of electronic medical records in lieu of survey data. The key research question is whether documented changes in BE exposure can be linked to changes in health outcomes in a causal manner. The use of geo-localized clinical information from regional health care systems should permit new insights into the social and environmental determinants of health.

Convergent validity of an activity-space survey for use in health research

We explored the validity of a survey measuring activity spaces for use in health research in a racially/ethnically diverse adult sample (n = 86) living in four Chicago neighborhoods. Participants reported on the location and visit frequency of 64 activities and wore a GPS data logger. We assessed the spatial congruence of survey- and GPS-derived convex hull measures and the number of GPS points within 100 m and 1000 m of survey locations. The survey-derived convex hull measures captured a small percentage (median = 35.9%) of the GPS-derived convex hull area. However, most GPS points were located within 100 m or 1000 m of home or reported survey locations (median = 73.4% and 92.6%, respectively).

Environmental, Individual and Personal Goal Influences on Older Adults' Walking in the Helsinki Metropolitan Area

Physical activity is a fundamental factor in healthy ageing, and the built environment has been linked to individual health outcomes. Understanding the linkages between older adult’s walking and the built environment are key to designing supportive environments for active ageing. However, the variety of different spatial scales of human mobility has been largely overlooked in the environmental health research. This study used an online participatory mapping method and a novel modelling of individual activity spaces to study the associations between both the environmental and the individual features and older adults’ walking in the environments where older adult’s actually move around. Study participants (n = 844) aged 55+ who live in Helsinki Metropolitan Area, Finland reported their everyday errand points on a map and indicated which transport mode they used and how frequently they accessed the places. Respondents walking trips were drawn from the data and the direct and indirect effects of the personal, psychological as well as environmental features on older adults walking were examined. Respondents marked on average, six everyday errand points and walked for transport an average of 20 km per month. Residential density and the density of walkways, public transit stops, intersections and recreational sports places were significantly and positively associated with older adult’s walking for transport. Transit stop density was found having the largest direct effect to older adults walking. Built environment had an independent effect on older adults walking regardless of individual demographic or psychological features. Education and personal goals related to physical activities had a direct positive, and income a direct negative, effect on walking. Gender and perceived health had an indirect effect on walking, which was realized through individuals’ physical activity goals.

Advanced Smartphone-Based Sensing with Open-Source Task Automation

Smartphone-based sensing is becoming a convenient way to collect data in science, especially in environmental research. Recent studies that use smartphone sensing methods focus predominantly on single sensors that provide quantitative measurements. However, interdisciplinary projects call for study designs that connect both, quantitative and qualitative data gathered by smartphone sensors. Therefore, we present a novel open-source task automation solution and its evaluation in a personal exposure study with cyclists. We designed an automation script that advances the sensing process with regard to data collection, management and storage of acoustic noise, geolocation, light level, timestamp, and qualitative user perception. The benefits of this approach are highlighted based on data visualization and user handling evaluation. Even though the automation script is limited by the technical features of the smartphone and the quality of the sensor data, we conclude that task automation is a reliable and smart solution to integrate passive and active smartphone sensing methods that involve data processing and transfer. Such an application is a smart tool gathering data in population studies.

Capturing exposure in environmental health research: challenges and opportunities of different activity space models

Background

The built environment health promotion has attracted notable attention across a wide spectrum of health-related research over the past decade. However, the results about the contextual effects on health and PA are highly heterogeneous. The discrepancies between the results can potentially be partly explained by the diverse use of different spatial units of analysis in assessing individuals’ exposure to various environment characteristics. This study investigated whether different residential and activity space units of analysis yield distinct results regarding the association between the built environment and health. In addition, this study examines the challenges and opportunities of the different spatial units of analysis for environmental health-related research.

Methods

Two common residential units of analysis and two novel activity space models were used to examine older adults’ wellbeing in relation to the built environment features in the Helsinki Metropolitan Area, Finland. An administrative unit, 500 m residential buffer, home range model and individualized residential exposure model were used to assess the associations between the built environment and wellbeing of respondent’s (n = 844).

Results

All four different spatial units of analysis yield distinct results regarding the associations between the built environment characteristics and wellbeing. A positive association between green space and health was found only when exposure was assessed with individualized residential exposure model. Walkability index and the length of pedestrian and bicycle roads were found to positively correlate with perceived wellbeing measures only with a home range model. Additionally, all units of analysis differed from each other in terms of size, shape, and how they capture different contextual measures.

Conclusions

The results show that different spatial units of analysis result in considerably different measurements of built environment. In turn, the differences derived from the use of different spatial units seem to considerably affect the associations between environment characteristics and wellbeing measures. Although it is not easy to argue about the correctness of these measurements, what is evident is that they can reveal different wellbeing outcomes. While some methods are especially usable to determine the availability of environmental opportunities that promote active travel and the related health outcomes, others can provide us with insight into the mechanisms how the actual exposure to green structure can enhance wellbeing.

An Innovative Context-Based Crystal-Growth Activity Space Method for Environmental Exposure Assessment: A Study Using GIS and GPS Trajectory Data Collected in Chicago

Scholars in the fields of health geography, urban planning, and transportation studies have long attempted to understand the relationships among human movement, environmental context, and accessibility. One fundamental question for this research area is how to measure individual activity space, which is an indicator of where and how people have contact with their social and physical environments. Conventionally, standard deviational ellipses, road network buffers, minimum convex polygons, and kernel density surfaces have been used to represent people’s activity space, but they all have shortcomings. Inconsistent findings of the effects of environmental exposures on health behaviors/outcomes suggest that the reliability of existing studies may be affected by the uncertain geographic context problem (UGCoP). This paper proposes the context-based crystal-growth activity space as an innovative method for generating individual activity space based on both GPS trajectories and the environmental context. This method not only considers people’s actual daily activity patterns based on GPS tracks but also takes into account the environmental context which either constrains or encourages people’s daily activity. Using GPS trajectory data collected in Chicago, the results indicate that the proposed new method generates more reasonable activity space when compared to other existing methods. This can help mitigate the UGCoP in environmental health studies.