Seasonal differences in mobility and activity space in later life: a case study of older adults in the Northern Netherlands.

Mobility is crucial for maintaining well-being in later life. Previous research has shown that older adults' mobility fluctuates throughout the day, with a particular focus on afternoon outdoor movement. This paper takes a broader approach and explores the seasonal differences and similarities in mobility and activity space in later life, using older adults in the Northern Netherlands as a case study. Seventeen older adults participated in the study, for which we used a mixed-methods approach combining GPS-, activity diaries, and in-depth interview data analysed through grounded visualisation. We have collected data from each participant for a week, once during fall/winter and once during summer. The findings of this paper defy common expectations around older adult mobility; for instance, the participants walked less in summer and had a larger activity space in winter. Equally, we demonstrate that it is crucial to distinguish between daily and incidental activity spaces, particularly when factoring in seasonal variations. Yet our mixed-methods approach revealed discrepancies between perceived and measured mobility and activity space. We argue that the intricate interplay of seasonal influences, weather conditions, and personal factors significantly shapes mobility practices in later life, underscoring the need for holistic planning of age-inclusive environments.

Objective Neighborhood-Level Disorder Versus Subjective Safety as Predictors of HIV Transmission Risk and Momentary Well-Being.

Mental health and HIV risk behavior have been studied with ecological momentary assessment (EMA), but this approach has not been combined with tracking of activity space (where people go and what they encounter there) in people with HIV and their social relations, who may be HIV+ or HIV-. Activity space represents a modifiable risk or protective factor for behavior related to health status and quality of life, in both clinical and nonclinical populations. We conducted an observational study with 286 participants (243 HIV+ and 43 HIV-), roughly matched for socioeconomic status and neighborhood of residence via three waves of snowball sampling. Each participant carried a smartphone for up to 4 weeks, making 5 randomly prompted entries and 1 end-of-day entry each day, plus self-initiated event-contingent entries for sexual activity and drug use. Responses to randomly prompted items provided subjective evaluations of the safety of the participant's current social and physical environment (the place they were and the people they were with). GPS-based location tracking-coupled with publicly available statistic indicating neighborhood-level physical disorder and socioeconomic disadvantage-provided an indicator of each participant's exposure to objective psychosocial hazard. We examined possible relationships of these objective and subjective environmental exposures with risky sexual and intravenous drug-use behavior, knowledge and utilization of antiretroviral treatment and prophylaxis, and momentary mental health (mood and stress, which relate to risky behavior and overall well-being). We found that both risky behavior and mental health were more related to participants' subjective evaluations of their activity space than to objective measures of neighborhood-level disorder, suggesting that, even within an objectively hazardous neighborhood, people who find a niche they perceive as socially and physically safe may engage in less risky behavior and have better well-being.Trial registration Clinicaltrials.gov Identifier NCT01571752.

Child maltreatment and youth exposure to risky environments: Latent class analysis of youth activity spaces.

BACKGROUND: Child maltreatment may alter the way that adolescents engage in and interact within the places they visit in their daily routines, namely youth activity spaces. Thus, it is important to understand how maltreatment experiences are linked to adolescents' exposure to environmental and contextual risks within their activity spaces. OBJECTIVE: The aim of the study was to explore the associations between child maltreatment and patterns of risk exposures within youth activity spaces among adolescents. PARTICIPANTS AND SETTING: Study participants were 1364 adolescents between the ages of 11 and 17, living in a Midwest state in the United States. METHODS: We linked data from the Adolescent Health and Development in Context (AHDC) study and the Statewide Automated Child Welfare Information System (SACWIS). A three-step latent class analysis (LCA) was employed. RESULTS: Three contextual risk exposure classes were identified: 1) The aggression/violence class (7.7 %); 2) The smoking and drinking class (12.3 %); and 3) The non-risk class (80.0 %). Adolescents with more maltreatment reports were more likely to be in the aggression/violence class compared to the non-risk class. CONCLUSIONS: Capitalizing on the novel linkage between administrative child welfare records and ecological momentary assessment (EMA)-based youth spatial/environmental exposure data, we found a positive link between the number of maltreatment reports made to child protective services and membership in the aggression/violence class. Intervention efforts should be directed toward youths with a history of child maltreatment, ensuring that they have access to safe, structured, and non-violent environments during their daily routines.

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.

Activity space during treatment with medication for opioid use disorder: Relationships with personality, mood, and drug use.

INTRODUCTION: Activity space in people with substance use disorders (SUDs) has been assessed for theoretical reasons and for detection/prevention of relapse. In this observational study, we relate passively obtained activity space measures to mental states and behaviors relevant to the success of treatment for opioid use disorder. Our long-term goal is to use such data to assess risk in real time and to recognize when SUD patients might benefit from a just-in-time intervention. METHODS: We used GPS data from 238 urban residents in the first 16 weeks of stabilization on medication for opioid use disorder to test preregistered hypotheses about activity space (distance traveled, number of locations, time spent moving, and psychosocial-hazard levels of neighborhoods where participants spent time) in relation to certain static variables (personality, mood propensities) and time-varying treatment-relevant behaviors such as craving and use of opioids and cocaine. RESULTS: The most consistent findings were that 1) mobility decreased over the course of the study; 2) neuroticism was associated with overall lower mobility; 3) trait-like positive mood (averaged from momentary ratings) was associated with higher mobility; 4) participants who used cocaine more frequently had lower mobility; 5) early in treatment, participants spent less time moving (i.e., were more sedentary) on days when they were craving. Some of these findings were in the expected direction (i.e., the ones involving neuroticism and positive mood), and some were opposite to the expected direction (i.e., we expected cocaine use to be associated with higher mobility); others (e.g., changes in mobility over time or in relation to craving) involved nondirectional hypotheses. CONCLUSIONS: Real-time information that patients actively provide is valuable for assessing their current state, but providing this information can be burdensome. The current results indicate that certain static or passively obtained data (personality variables and GPS-derived mobility information) are relevant to time-varying, treatment-relevant mental states and drug-related behavior, and therefore might be useful when incorporated into algorithms for detecting need for intervention in real time. Further research should assess how population-specific these relationships are, and how these passive measures can best be combined with low temporal-density, actively-provided data to obtain valid, reliable assessments with minimal burden.

Exploring the impact of environmental exposure changes on metabolic biomarkers: A 6-month GPS-GIS study among women with overweight or obesity.

BACKGROUND: Little is known about the impact of environmental exposure change on metabolic biomarkers associated with cancer risk. Furthermore, this limited epidemiological evidence on metabolic biomarkers focused on residential exposure, without considering the activity space which can be done by modelling dynamic exposures. In this longitudinal study, we aimed to investigate the impact of environmental exposures change on metabolic biomarkers using GPS-GIS based measurements. METHODS: Among two weight loss interventions, the Reach for Health and the MENU studies, which included ∼460 women at risk of breast cancer or breast cancer survivors residing in Southern California, three metabolic biomarkers (insulin resistance, fasting glucose, and C-reactive protein) were assessed. Dynamic GPS-GIS based exposure to green spaces, recreation, walkability, NO2, and PM2.5 were calculated at baseline and 6 months follow-up using time-weighted spatial averaging. Generalized estimating equations models were used to examine the relationship between changes in environmental exposures and biomarker levels over time. RESULTS: Overall, six-month environmental exposure change was not associated with metabolic biomarkers change. Stratified analyses by level of environmental exposures at baseline revealed that reduced NO2 and PM2.5 exposure was associated with reduced fasting glucose concentration among women living in a healthier environment at baseline (ß -0.010, 95%CI -0.025, 0.005; ß -0.019, 95%CI -0.034, -0.003, respectively). Women living in poor environmental conditions at baseline and exposed to greener environments had decreased C-reactive protein concentrations (ß -1.001, 95%CI -1.888, -0.131). CONCLUSIONS: The impact of environmental exposure changes on metabolic biomarkers over time may be modified by baseline exposure conditions.

Using EMA to explore the role of Black adolescents' experiences in activity spaces in momentary negative emotion and marijuana use.

Research examining the role of place in Black adolescents' health behaviors typically examines neighborhoods, with little attention paid to micro geographies such as activity spaces. Understanding experiences in activity spaces may be especially important for Black adolescents living in neighborhoods traditionally characterized as disadvantaged. The SPIN project recruited 75 Black adolescents living in a single neighborhood to complete ecological momentary assessments (EMA) about the activity spaces they encountered over a month. Perceptions of violence and social support in activity spaces in a day are related to marijuana use during the day, relationships partially explained by negative momentary emotions.

Store-specific grocery shopping patterns and their association with objective and perceived retail food environments.

OBJECTIVE: To explore store-specific grocery shopping patterns and assess associations with the objective and perceived retail food environment (RFE). DESIGN: This cross-sectional study used principal component analysis and hierarchical cluster analysis to identify grocery shopping patterns and logistic regression models to assess their associations with the RFE, while adjusting for household characteristics. SETTING: The Montpellier Metropolitan Area, France. PARTICIPANTS: To be eligible for inclusion, participants had to be 18 years of age or older and reside in the Montpellier Metropolitan Area. Analyses were carried out on 415 households. RESULTS: Households of cluster 'Supermarket' (49 % of households) primarily shopped at supermarkets and were less likely to live near a convenience store. Households of cluster 'Diversified' (18 %) shopped mostly at organic stores, at markets, at specialised stores, and from producers and were more likely to have a market in their activity space. Households of cluster 'Discount' (12 %) primarily shopped at discounters and were less likely to perceive a producer in their activity space. Households of cluster 'Convenience' (12 %) mostly shopped online or in convenience stores. Finally, households of cluster 'Specialized' (9 %) had high expenditures in greengrocers and in other specialised food stores and were more likely to live near a specialised food store. CONCLUSIONS: This study highlighted the importance of considering both perceived and objective RFE indicators, as well as assessments around the home and in activity space. Understanding how people buy food and interact with their RFE is crucial for policymakers seeking to improve urban food policies.

The Impact of Urbanization on Taxonomic Diversity and Functional Similarity among Butterfly Communities in Waterfront Green Spaces.

Urbanization has been shown to cause biodiversity loss. However, its effects on butterfly taxonomic and functional diversity still need to be studied, especially in urban waterfront green spaces where mechanisms of impact still need to be explored. We used butterflies as indicators to study how urbanization affects their taxonomic and functional diversity and identify indicator species in different urban ecological gradient areas. From July to September 2022, we surveyed 10 urban waterfront green spaces in Fuzhou City, China. We recorded 1163 butterflies of 28 species from 6 families. First, we explored the effects of urbanization on butterfly communities and made pairwise comparisons of different urban ecological gradients (α-diversity); secondly, we looked for differences between butterfly communities across urban ecological gradients (ß-diversity); finally, we investigated differences in the response of butterfly functional groups to different urban ecological gradient areas and identified ecological indicative species. This study found the following: (1) Urbanization has led to the simplification of butterfly community structure, but there are also favorable factors that support the survival of individual butterflies; (2) Urbanization has led to significant differences in butterfly communities and plant-feeding polyphagous butterfly groups; (3) Urbanization has led to differences in the functional diversity of butterfly diet and activity space groups; (4) We identified five eco-indicator species in different urban ecological gradients.

Does the built environment influence location- and trip-based sedentary behaviors? Evidence from a GPS-based activity space approach of neighborhood effects on older adults.

OBJECTIVE: Evidence on the influence of built environments on sedentary behaviors remains unclear and is often contradictory. The main limitations encompass the use of self-reported proxies of sedentary time (ST), the scarce consideration of the plurality of sedentary behaviors, and environmental exposures limited to the residential neighborhood. We investigated the relationships between GPS-based activity space measures of environmental exposures and accelerometer-based ST measured in total, at the place of residence, at all locations, and during trips. METHODS: This study is part of the CURHA project, based on 471 older adults residing in Luxembourg, who wore a GPS receiver and a tri-axial accelerometer during 7 days. Daily ST was computed in total, at the residence, at all locations and during trips. Environmental exposures included exposure to green spaces, walking, biking, and motorized transportation infrastructures. Associations between environments and ST were examined using linear and negative binomial mixed models, adjusted for demographics, self-rated health, residential self-selection, weather conditions and wear time. RESULTS: Participants accumulated, on average, 8 h and 14 min of ST per day excluding sleep time. ST spent at locations accounted for 83 % of the total ST. ST spent at the residence accounted for 87 % of the location-based ST and 71 % of the total ST. Trip-based ST represents 13 % of total ST, and 4 % remained unclassified. Higher street connectivity was negatively associated with total ST, while the density of parking areas correlated positively with total and location-based ST. Stronger associations were observed for sedentary bouts (uninterrupted ST over 20 and 30 min). CONCLUSION: Improving street connectivity and controlling the construction of new parking, while avoiding the spatial segregation of populations with limited access to public transport, may contribute to limit ST. Such urban planning interventions may be especially efficient in limiting the harmful uninterrupted bouts of ST among older adults.

Social-spatial network structures among young urban and suburban persons who inject drugs in a large metropolitan area.

BACKGROUND: Recent studies underscore the significance of adopting a syndemics approach to study opioid misuse, overdose, hepatitis C (HCV) and HIV infections, within the broader context of social and environmental contexts in already marginalized communities. Social interactions and spatial contexts are crucial structural factors that remain relatively underexplored. This study examines the intersections of social interactions and spatial contexts around injection drug use. More specifically, we investigate the experiences of different residential groups among young (aged 18-30) people who inject drugs (PWID) regarding their social interactions, travel behaviors, and locations connected to their risk behaviors. By doing so, we aim to achieve a more comprehensive understanding of the multidimensional risk environment, thereby facilitating the development of informed policies. METHODS: We collected and examined data regarding young PWID's egocentric injection network and geographic activity spaces (i.e., where they reside, inject drugs, purchase drugs, and meet sex partners). Participants were stratified based on the location of all place(s) of residence in the past year i.e., urban, suburban, and transient (both urban and suburban) to i) elucidate geospatial concentration of risk activities within multidimensional risk environments based on kernel density estimates; and ii) examine spatialized social networks for each residential group. RESULTS: Participants were mostly non-Hispanic white (59%); 42% were urban residents, 28% suburban, and 30% transient. We identified a spatial area with concentrated risky activities for each residential group on the West side of Chicago in Illinois where a large outdoor drug market area is located. The urban group (80%) reported a smaller concentrated area (14 census tracts) compared to the transient (93%) and suburban (91%) with 30 and 51 tracts, respectively. Compared to other areas in Chicago, the identified area had significantly higher neighborhood disadvantages. Significant differences were observed in social network structures and travel behaviors: suburban participants had the most homogenous network in terms of age and residence, transient participants had the largest network (degree) and more non-redundant connections, while the urban group had the shortest travel distance for all types of risk activities. CONCLUSION: Distinct residential groups exhibit varying patterns of network interaction, travel behaviors, and geographical contexts related to their risk behaviors. Nonetheless, these groups share common concentrated risk activity spaces in a large outdoor urban drug market area, underscoring the significance of accounting for risk spaces and social networks in addressing syndemics within PWID populations.

Integrating health geography and behavioral economic principles to strengthen context-specific behavior change interventions.

The long-term economic viability of modern health care systems is uncertain, in part due to costs of health care at the end of life and increasing health care utilization associated with an increasing population prevalence of multiple chronic diseases. Control of health care spending and sustaining delivery of health care services will require strategic investments in prevention to reduce the risk of disease and its complications over an individual's life course. Behavior change interventions aimed at reducing a range of harmful and risky health-related behaviors including smoking, physical inactivity, excess alcohol consumption, and excess weight, are one approach that has proven effective at reducing risk and preventing chronic disease. However, large-scale efforts to reduce population-level chronic diseases are challenging and have not been very successful at reducing the burden of chronic diseases. A new approach is required to identify when, where, and how to intervene to disrupt patterns of behavior associated with high-risk factors using context-specific interventions that can be scaled. This paper introduces the need to integrate theoretical and methodological principles of health geography and behavioral economics as opportunities to strengthen behavior change interventions for the prevention of chronic diseases. We discuss how health geography and behavioral economics can be applied to expand existing behavior change frameworks and how behavior change interventions can be strengthened by characterizing contexts of time and activity space.

Behavior change interventions are challenged by lack of information about the contexts influencing decisions patients make as part of their daily routine such as when, where, and how health behaviors occur. A new approach is required to strengthen behavior change interventions by integrating contexts of time and activity space so that strategies can be scaled across populations to influence how individuals make decisions about improving their health behaviors. Incorporating ideas from health geography and behavioral economics into the design of behavior change interventions provides an opportunity to collect and investigate individual-level health information characterizing contexts of individuals' activities across space, connections to place, time management, and patterns in behavior over time. By visualizing and characterizing key spatiotemporal contexts about an individual's day-to-day routine, insight can be gained about where and for how long activities occur and what opportunities exist for adapting day-to-day routines. This paper will discuss how theory from health geography could be applied to understand contexts influencing behaviors and how spatiotemporal information could be applied for the purpose of tailoring behavioral economic strategies to strengthen the design of behavior change interventions.

Aircraft and road traffic noise, insulin resistance, and diabetes: The role of neighborhood socioeconomic status in San Diego County.

Evidence linking traffic noise to insulin resistance and diabetes is limited and unanswered questions remain regarding the potential effect modification by neighborhood socioeconomic status (nSES). We aimed to assess socioeconomic inequalities in noise exposure, whether road and aircraft noise exposures were associated with insulin resistance or diabetes, and whether nSES modified these relationships. Among the Community of Mine Study in San Diego County, road and aircraft noise exposure at enrollment was calculated based on the static (participant's administrative boundary, and circular buffer around participant homes), and dynamic (mobility data by global positioning system, GPS) spatio-temporal aggregation methods. Associations of noise with insulin resistance (HOMA-IR) or type 2 diabetes (T2DM) were quantified using generalized estimating equation models adjusted for sex, age, ethnicity, individual income, and air pollution (nitrogen dioxide) exposure. Additive interaction between noise and nSES was assessed. Among 573 participants (mean age 58.7 y), participants living in low nSES were exposed to higher levels of aircraft and road noise using noise level at the census tract, circular buffer, or Kernel Density Estimation (KDE) of GPS data. Participants exposed to road noise greater or equal to the median (53 dB(A)) at the census tract and living in low nSES had an increased level of insulin resistance (ß = 0.15, 95%CI: -0.04, 0.34) and higher odds of T2DM (Odds Ratio = 2.34, 95%CI: 1.12, 4.90). A positive additive interaction was found as participants living in low nSES had higher odds of T2DM. The impact of noise exposure on insulin resistance and T2DM differs substantially by nSES. Public health benefits of reducing exposure to road or aircraft noise would be larger in individuals living in low nSES.

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.

Integrating coordination of food purchasing into activity space-based food environment research: Toward a household perspective.

Despite the advances in person-based approaches to studying food environments, most studies using these approaches have relied on individual-centered activity space measures and largely ignored cohabiting household members who play crucial roles in shaping an individual's food access, food behaviors, and diet. This can be problematic for completely capturing food environments relevant to an individual and add uncertainties to explorations of how individuals' food environments relate to their food behaviors. This viewpoint discusses the need for, and implications of, considering household members when measuring food access and disentangling the behavioral pathways connecting the food environment to diet. Ultimately, a conceptual framework and potential questions are proposed to integrate household members into food environment research.

Egalitarian Attitudes and Activity Spaces in Chitwan, Nepal.

Connections between individuals' sociodemographic characteristics and their social attitudes have been widely studied, but there has been less research on how individuals' spatial patterns are related to attitudes. Studies that do incorporate space have focused on residential locations, neglecting spatial experience outside residential neighborhoods. To fill this gap, we test hypotheses relating multiple measures of activity space (AS) to social attitudes, using innovative spatial data from Nepal. First, we hypothesize that the gender and caste attitudes of a focal individual will be positively associated with the gender and caste attitudes of others in the focal individual's AS, including spaces beyond the residential neighborhood. Second, we hypothesize that privileged individuals (i.e., males and those of the Chhetri/Brahmin caste) with greater potential exposure to females and those of lower castes in their AS will have more egalitarian attitudes about gender and caste than those with less exposure in their AS. Linear regression models provide support for both hypotheses.

Feasibility and acceptability of mobile methods to assess home and neighborhood environments related to adolescent sleep.

OBJECTIVE: A growing evidence base suggests home and neighborhood environmental exposures may influence adolescent sleep, but few studies have assessed these relationships using methods that account for time-varying, location-specific exposures, or multiple neighborhood contexts. This study aimed to assess the feasibility and acceptability of using smartphone global positioning system (GPS) tracking and ecological momentary assessment (EMA) to assess time-varying home and neighborhood environmental exposures hypothesized to be associated with adolescent sleep. METHODS: Adolescents aged 15-17 years in Philadelphia completed 7 days of continuous smartphone GPS tracking, which was used to identify daily levels of exposure to geocoded neighborhood factors (eg, crime, green space). Four daily EMA surveys assessed home sleep environment (eg, noise, light), stress, health behaviors, and neighborhood perceptions. Feasibility and acceptability of GPS tracking and EMA were assessed, and distributions of daily environmental exposures were examined. RESULTS: Among 25 teens (mean age 16, 56% male), there was a high level of GPS location data captured (median daily follow-up: 24 hours). Seventy-eight percent of EMA surveys were completed overall. Most participants (96%) reported no privacy concerns related to GPS tracking and minimal burden from EMA surveys. Exposures differed between participants' home neighborhoods and locations visited outside the home neighborhood (eg, higher crime away from home). Sleep environment disruptions were present on 29% of nights (most common: uncomfortable temperature) and were reported by 52% of adolescents. CONCLUSIONS: Results demonstrate the feasibility and acceptability of mobile methods for assessing time-varying home and neighborhood exposures relevant to adolescent sleep for up to 1 week.

Geographic intelligence to investigate community participation: a scoping review.

PURPOSE: To understand the applicability and unique contributions of global positioning system (GPS) and geographic information system (GIS) technologies to investigate individuals' participation in the community. METHODS: A scoping review was conducted to summarize studies that employed GPS and/or GIS to assess community participation. Systematic literature searches were performed using nine electronic databases, up to April 2022. Two independent reviewers screened studies for eligibility and extracted data from the selected studies. RESULTS: The searches retrieved 628 articles, of which 36 met the inclusion criteria. In 31 studies, a GPS unit or GPS-enabled device monitored the community mobility of individuals with different health conditions. Tracking periods varied from five hours to 30 consecutive days. The spatiotemporal parameters obtained from satellite-based data provided information about individuals' presence in the community. Most studies combined GPS with other measuring tools (self-report diaries/questionnaires, qualitative interviews) to capture a broader description of community participation. CONCLUSIONS: GPS and GIS are viable approaches for advancing research as they provide unique information about community participation not easily captured by other methods. The combination of available methods comprehensively address the physical and social dimensions of this construct.IMPLICATIONS FOR REHABILITATIONGlobal positioning system (GPS) and geographic information system (GIS) technology allows direct and real-time quantification of patterns of individuals' community mobility.The geographic area where individuals participate in daily living activities complements information from self-report diaries/questionnaires.Combining GPS technology with self-report diaries/questionnaires allows a broader description of individuals' community participation, addressing respectively both its physical and social dimensions.Knowledge of individuals' access to and involvement in community locations/situations may help therapists design interventions to improve community participation.

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.