Linking GPS and travel diary data using sequence alignment in a study of children's independent mobility

A brief review of methods for determining time-activity patterns in California

Air pollution exposure has been found to be linked with numerous adverse human health effects. Because both air pollution concentrations and the location of human individuals change spatiotemporally, understanding the time-activity patterns (TAPs) is of utmost importance for the mitigation of adverse exposures and to improve the accuracy of air pollution and health analyses. "Time-activity patterns" outlined here broadly refer to the spatiotemporal positions of individuals. In this review paper, we briefly review past efforts on collecting individual TAP information for air pollution and health studies, with a specific focus on California efforts. We also critically summarize emerging technologies and approaches for collecting TAP data. Specifically, we critically reviewed five types of emerging TAP data sources, including call detail record, social media location data, Google Location History, iPhone Significant Location, and crowd-sourced location data. This review provides a comprehensive summary and critique of different methods to collect TAP information and offers recommendations for use in retrospective air pollution and health studies.Implications: In this review paper, we provide a comprehensive overview of approaches for collecting time-activity pattern (TAP) data from individuals, a crucial component in understanding human behavior and its implications across various fields such as urban planning, environmental science, and, particularly, public health in relation to air pollution exposures.Furthermore, our paper introduces and critically evaluates several emerging methods for TAP data collection. These novel approaches, including but not limited to Google Location History, iPhone Significant Locations, and crowdsourced smartphone location data, offer unprecedented granularity in tracking human activities. By showcasing these methodologies and their often not well-recognized weaknesses, we highlight both the potential and limitations of these tools to advance our understanding of human behavior patterns, especially in terms of how individuals interact with their environments. This discussion not only showcases the originality of our work but also sets the stage for future research directions that can benefit from these innovative data collection strategies.

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.

Place-Based Developmental Research: Conceptual and Methodological Advances in Studying Youth Development in Context

Scientists have, for some time, recognized that development unfolds in numerous settings, including families, schools, neighborhoods, and organized and unorganized activity settings. Since the turn of the 20th century, the body of mainstream neighborhood effects scholarship draws heavily from the early 20th century Chicago School of Sociology frameworks and have been situating development in neighborhood contexts and working to identify the structures and processes via which neighborhoods matter for a range of developmental outcomes, especially achievement, behavioral and emotional problems, and sexual activity. From this body of work, two new areas of developmental scholarship are emerging. Both areas are promising for advancing an understanding of child development in context. First, cultural-developmental neighborhood researchers are advancing neighborhood effects research that explicitly recognizes the ways that racial, ethnic, cultural, and immigrant social positions matter for neighborhood environments and for youths' developmental demands, affordances, experiences, and competencies. This body of work substantially expands the range of developmental outcomes examined in neighborhood effects scholarship to recognize normative physical, emotional, cognitive, behavioral, social, and cultural competencies that have largely been overlooked in neighborhood effects scholarship that espoused a more color-blind developmental approach. Second, activity space neighborhood researchers are recognizing that residential neighborhoods have important implications for broader activity spaces-or the set of locations and settings to which youth are regularly exposed, including, for example, schools, work, organized activities, and hang-outs. They are using newer technologies and geographic frameworks to assess exposure to residential neighborhood and extra-neighborhood environments. These perspectives recognize that time (i.e., from microtime to mesotime) and place are critically bound and that exposures can be operationalized at numerous levels of the ecological system (i.e., from microsystems to macrosystems). These frameworks address important limitations of prior development in context scholarship by addressing selection and exposure. Addressing selection involves recognizing that families have some degree of choice when selecting into settings and variables that predict families' choices (e.g., income) also predict development. Considering exposure involves recognizing that different participants or residents experience different amounts of shared and nonshared exposures, resulting in both under-and over-estimation of contextual effects. Activity space scholars incorporate exposure to the residential neighborhood environments, but also to other locations and settings to which youth are regularly exposed, like schools, after-school settings, work, and hang-outs. Unfortunately, the cultural-development and activity space streams, which have both emerged from early 20th century work on neighborhood effects on development, have been advancing largely independently. Thus, the overarching aim of this monograph is to integrate scholarship on residential neighborhoods, cultural development, and activity spaces to advance a framework that can support a better understanding of development in context for diverse groups. In Chapters I and II we present the historical context of the three streams of theoretical, conceptual, and methodological research. We also advance a comprehensive cultural-developmental activity space framework for studying development in context among children, youth, and families that are ethnically, racially, and culturally heterogeneous. This framework actively recognized diversity in ethnic, racial, immigrant, and socioeconomic social positions. In Chapters III-V we advance specific features of the framework, focusing on: (1) the different levels of nested and nonnested ecological systems that can be captured and operationalized with activity space methods, (2) the different dimensions of time and exposures or experiences that can be captured and operationalized by activity space methods, and (3) the importance of settings structures and social processes for identifying underlying mechanisms of contextual effects on development. Structures are setting features related to the composition and spatial arrangement of people and institutions (e.g., socioeconomic disadvantage, ethnic/racial compositions). Social processes represent the collective social dynamics that take place in settings, like social interactions, group activities, experiences with local institutions, mechanisms of social control, or shared beliefs. In Chapter VI, we highlight a range of methodological and empirical exemplars from the United States that are informed by our comprehensive cultural-developmental activity space framework. These exemplars feature both quantitative and qualitative methods, including method mixing. These exemplars feature both quantitative and qualitative methods, including method mixing. The exemplars also highlight the application of the framework across four different samples from populations that vary in terms of race, ethnicity, gender, age, socioeconomic status (SES), geographic region, and urbanicity. They capture activity space characteristics and features in a variety of ways, in addition to incorporating family shared and nonshared activity space exposures. Finally, in Chapter VII we summarize the contributions of the framework for advancing a more comprehensive science of development in context, one that better realizes major developmental theories emphasizing persons, processes, contexts, and time. Additionally, we offer a place-based, culturally informed developmental research agenda to meet the needs of an increasingly diverse population.

Geomatics and epidemiology: Associating oxidative stress and greenness in urban areas

Green spaces may benefit human health mainly by mitigating noise and air pollution, promoting physical or social activities and improving mental health. Based on the influence that green space exposure seems to exert on Public Health and using a multidisciplinary approach, we investigated, the association between oxidative stress (OS) and green exposure in children. Overall, 207 subjects (10-13 yrs) living in Torino (NW- Italy) were involved in this study. Each participant provided a urinary sample, used to quantify a reliable OS biomarker (15-F2t-IsoP), and their residence addresses, used for geocoding. Green exposure was characterised by calculating i) the Soil Adjusted Vegetation Index (SAVI) within fixed buffers around each participant's home, using remotely-sensed data; ii) Tree Map accounting for evergreen/broadleaf species; iii) The percentage of green cover (PGC). Significant negative correlation (Pearson's r = -0.758, p < 0.001) between PGC and 15-F2t-IsoP was found. Greater SAVI was associated with lower OS (Pearson's r = -0.717, p < 0.001). Noticeably, evergreens seemed to determine a significant OS reduction compared to broadleaves (slope = -0.12 and -0.02, respectively; Warton-test F = 12.48, p = 0.0011). Finally, a spatial distribution of 15-F2t-IsoP estimates map, overlying with 2011 Census Data on same-aged dwellers of Torino, was generated. Predictive models accounting for green spaces influence on OS can be useful tool derived from geomatic employ in the Public Health field. Future developments of such a multidisciplinary approach should be considered in urban planning and policy-makers decisions to better define priority zones to requalify in urban settings.

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

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

Variable Selection in the Regularized Simultaneous Component Analysis Method for Multi-Source Data Integration

Interdisciplinary research often involves analyzing data obtained from different data sources with respect to the same subjects, objects, or experimental units. For example, global positioning systems (GPS) data have been coupled with travel diary data, resulting in a better understanding of traveling behavior. The GPS data and the travel diary data are very different in nature, and, to analyze the two types of data jointly, one often uses data integration techniques, such as the regularized simultaneous component analysis (regularized SCA) method. Regularized SCA is an extension of the (sparse) principle component analysis model to the cases where at least two data blocks are jointly analyzed, which - in order to reveal the joint and unique sources of variation - heavily relies on proper selection of the set of variables (i.e., component loadings) in the components. Regularized SCA requires a proper variable selection method to either identify the optimal values for tuning parameters or stably select variables. By means of two simulation studies with various noise and sparseness levels in simulated data, we compare six variable selection methods, which are cross-validation (CV) with the "one-standard-error" rule, repeated double CV (rdCV), BIC, Bolasso with CV, stability selection, and index of sparseness (IS) - a lesser known (compared to the first five methods) but computationally efficient method. Results show that IS is the best-performing variable selection method.

Behavioral mapping of children's physical activities and social behaviors in an indoor preschool facility: methodological challenges in revealing the influence of space in play

BACKGROUND

GIS (Geographic Information Systems) based behavior maps are useful for visualizing and analyzing how children utilize their play spaces. However, a GIS needs accurate locational information to ensure that observations are correctly represented on the layout maps of play spaces. The most commonly used tools for observing and coding free play among children in indoor play spaces require that locational data be collected alongside other play variables. There is a need for a practical, cost-effective approach for extending most tools for analyzing free play by adding geospatial locational information to children's behavior data collected in indoor play environments.

RESULTS

We provide a non-intrusive approach to adding locational information to behavior data acquired from video recordings of preschool children in their indoor play spaces. The gridding technique showed to be a cost-effective method of gathering locational information about children from video recordings of their indoor physical activities and social behaviors. Visualizing the proportions of categories and observed intervals was done using bubble pie charts which allowed for the merging of multiple categorical information on one map. The addition of locational information to other play activity and social behavior data presented the opportunity to assess what types of equipment or play areas may encourage different physical activities and social behaviors among preschool children.

CONCLUSIONS

Gridding is an effective method for providing locational data when analyzing physical activities and social behaviors of preschool children in indoor spaces. It is also reproducible for most GIS behavior mapping focusing on indoor environments. This bypasses the need to have positioning devices attached to children during observations, which can raise ethical considerations regarding children's privacy and methodological implications with children playing less naturally. It also supports visualizations on behavior maps making them easier to interpret.

RegularizedSCA: Regularized simultaneous component analysis of multiblock data in R

This article introduces a package developed for R (R Core Team, 2017) for performing an integrated analysis of multiple data blocks (i.e., linked data) coming from different sources. The methods in this package combine simultaneous component analysis (SCA) with structured selection of variables. The key feature of this package is that it allows to (1) identify joint variation that is shared across all the data sources and specific variation that is associated with one or a few of the data sources and (2) flexibly estimate component matrices with predefined structures. Linked data occur in many disciplines (e.g., biomedical research, bioinformatics, chemometrics, finance, genomics, psychology, and sociology) and especially in multidisciplinary research. Hence, we expect our package to be useful in various fields.

Investigating Dominant Trip Distance for Intercity Passenger Transport Mode Using Large-Scale Location-Based Service Data

Intercity transport systems have been plagued by low efficiency and overutilization for a long time, due to unhealthy competition among multi-transport modes. Hence, this study aims to estimate the dominant trip distance of intercity passenger transport modes to optimize the allocation of intercity passenger transport resources and improve the efficiency of intercity transport systems. Dominant trip distance was classified into two types: Absolute dominant trip distance and relative dominant trip distance; and their respective models were developed using passenger transport mode share functions and fitting curves. Particularly, the big data of intercity passenger transport mode share rate of more than 360 cities in China was obtained using a network crawler and each passenger transport mode share function and their curves were proposed. Furthermore, the dominant trip distances estimation models of intercity passenger transport were developed and solved. The results show that there are significant differences in dominant trip distance between the transport modes. For example, the absolute and relative dominant trip distances of highway are 8–119 km and 8–463 km, respectively, while those of airway are 1594–3000 km and 2477–3000 km, respectively.

Roaming the Neighbourhood: Influences of Independent Mobility Parenting Practices and Parental Perceived Environment on Children's Territorial Range

Children’s independent mobility (IM), their freedom to move about their neighbourhood without supervision by adults, has been in steady decline in recent decades. Previous research has linked perceptions of the environment with various measures of IM, but recently concerns have been raised regarding inconsistency in measuring IM. This study used various measures of IM and aimed to address how parental perceptions of the neighbourhood environment are associated with children’s territorial range (actual IM), as well as how this relationship is mediated by IM parenting practices (allowed IM). A sample of 105 child/parent dyads from Vancouver, Canada participated in this study. Children (age 10–13) wore a global positioning system (GPS) watch and an accelerometer and completed an activity diary for seven days to assess their territorial range. Parents completed a questionnaire that assessed perceptions of their neighbourhood environment and IM parenting practices—license for IM and roaming allowance. Path analyses were used to address the research aims. License for IM and roaming allowance mediated the relationship between perceived walking facilities, crime safety, and neighbourhood relations and children’s territorial range. Findings suggest that future interventions to increase children’s territorial range should focus primarily on attitude and behaviour change among parents to grant children more freedom.

The Social Context of HIV Prevention and Care among Black Men Who Have Sex with Men in Three U.S. Cities: The Neighborhoods and Networks (N2) Cohort Study

Background: In many parts of the world, stark racial disparities in human immunodeficiency virus (HIV) prevalence, incidence, prevention, and care outcomes persist among gay, bisexual, and other men who have sex with men (MSM), with Black MSM significantly impacted in the United States (U.S.). Individual-level characteristics, including sexual behaviors and socioeconomic status, do not fully account for racial/ethnic disparities in HIV among MSM. We hypothesize that neighborhood contexts and network characteristics influence risk for HIV infection as well as HIV-related prevention and care behaviors. As such, the study design includes the use of real-time geospatial methods and in-depth assessments of multiple network typologies to investigate the impact of neighborhood and network-level factors on HIV prevention and treatment among Black MSM residing in longstanding priority HIV elimination areas in the U.S., namely Chicago, Illinois and in the Deep South (Jackson, Mississippi and New Orleans, Louisiana) (n = 450, n = 50, and n = 100, respectively). We describe the design, sampling methods, data collection, data management methods, and preliminary findings of the ongoing 'Neighborhoods and Networks (N2) Cohort Study'. Methods/Design: N2 employs a prospective longitudinal design. The sample includes Black MSM participants in Chicago recruited via respondent-driven sampling and assessed every six months over two years of follow-up. Participants enrolled in Jackson and New Orleans are being recruited through existing health and community services and assessed every six months over one year of follow-up. Mobility within and between neighborhoods is being assessed using global positioning system (GPS) technology. Social and sexual networks among Black MSM are being studied through egocentric network inventories as well as newer methods of creating meso-level networks that involve social media (Facebook) and mobile phone contacts. Key HIV prevention outcomes such as pre-exposure prophylaxis (PrEP) care engagement, and HIV/STI (sexually transmitted infections) biomarkers will be examined at baseline and follow-up. Results: As of 31 December 2018, a total of 361 men were enrolled across all study sites: 259 in Chicago and 102 in the Deep South (75 in New Orleans and 27 in Jackson). At baseline, participants ranged in age from 17 to 65 years old (mean = 34.3, standard deviation = 5.1) with 123 men (34.1%) self-reported as HIV positive. While HIV treatment levels were similar between sites, men in the Deep South reported higher rates of adherence than men in Chicago (63.3% versus 49.4%, p = 0.03). Sexual risk profiles were mainly the same between men from different study sites, with 22.9% of men in Chicago and 28.9% in the Deep South reporting consistent condom use during vaginal and anal sex (p = 0.26). Regarding their home neighborhoods, men in the Deep South were more likely than those in Chicago to characterize theirs as having a good reputation (43.1% versus 24.7%, p < 0.001) and as being safe (37.3% versus 21.2%, p = 0.002). Conclusions: The focus on Black MSM in the N2 Study will allow for a nuanced exploration of the attitudes, beliefs, behaviors, and practices of a diverse group of Black MSM. The study is also positioned to provide novel insight about neighborhood and network characteristics that influence HIV-related behaviors. A health equity framework ensures that Black MSM are not explicitly or implicitly deemed as deviant, disordered, or the non-reference group. Findings from N2 will provide guidance for the implementation of more impactful HIV prevention interventions that engage a diverse population of Black MSM as we work toward HIV elimination in the U.S.

Children's Independent Mobility: Current Knowledge, Future Directions, and Public Health Implications

Environmental changes significantly impact health behavior. Active travel behavior is mostly affected by increasing motorization, urban sprawl, and traffic safety. Especially for children, active and independent travel can contribute to physical activity, social and motor development, and other health-related outcomes. A reduced number of children engaging in independent mobility over the last 20 years demanded researchers to further examine the construct of children’s independent mobility. By examining relevant literature, this narrative review aims to provide the current state of knowledge on children’s independent mobility, and identify future directions in research, as well as practical implications. From a public health perspective, considering children’s independent mobility in intervention programs is recommended, since it is associated with numerous health and environmental benefits. To develop interventions, multilevel socio-ecological influences on children’s independent mobility are widely examined; however, evidence is limited due to heterogeneous measurements and a lack of high-quality prospective studies. To oppose the decline in children’s independent mobility, further analysis using comparable measures is needed to understand the determinants of children’s independent mobility and to enable international comparison.

Are disadvantaged children more likely to be excluded from analysis when applying global positioning systems inclusion criteria?

Objective

When using global positioning systems (GPS) to assess an individual’s exposure to their environment, a first step in data cleaning is to establish minimum GPS ‘inclusion criteria’ (a set of rules used to determine which GPS data are able to be included in analyses). Care is needed at this stage to avoid any data exclusion (data loss) systematically biasing results in terms of characteristics of the environment and participants. The extent of potential systematic bias in sample retention due to GPS data loss and application of GPS inclusion criteria is unknown. The aim of this study was to describe differences in sample size and socio-demographic characteristics of the retained sample when applying three different GPS inclusion criteria. The study assessed 7-day GPS data collected from children (aged 9–13 years) recruited from nine schools in Auckland, New Zealand as part of the Kids in the City study.

Results

Participants from ethnic minorities and those attending schools in lower socioeconomic areas were disproportionately excluded from the retained samples. This highlights potential equity implications in basing the assessment of exposure—which ultimately influences research results on the relationship between environment and health—on non-representative GPS data.

The usefulness of GPS bicycle tracking data for evaluating the impact of infrastructure change on cycling behaviour

Issue addressed A key strategy to increase active travel is the construction of bicycle infrastructure. Tools to evaluate this strategy are limited. This study assessed the usefulness of a smartphone GPS tracking system for evaluating the impact of this strategy on cycling behaviour. Methods Cycling usage data were collected from Queenslanders who used a GPS tracking app on their smartphone from 2013-2014. 'Heat' and volume maps of the data were reviewed, and GPS bicycle counts were compared with surveillance data and bicycle counts from automatic traffic-monitoring devices. Results Heat maps broadly indicated that changes in cycling occurred near infrastructure improvements. Volume maps provided changes in counts of cyclists due to these improvements although errors were noted in geographic information system (GIS) geo-coding of some GPS data. Large variations were evident in the number of cyclists using the app in different locations. These variations limited the usefulness of GPS data for assessing differences in cycling across locations. Conclusion Smartphone GPS data are useful in evaluating the impact of improved bicycle infrastructure in one location. Using GPS data to evaluate differential changes in cycling across multiple locations is problematic when there is insufficient traffic-monitoring devices available to triangulate GPS data with bicycle traffic count data. So what? The use of smartphone GPS data with other data sources is recommended for assessing how infrastructure improvements influence cycling behaviour.

Integrating data from multiple time-location measurement methods for use in exposure assessment: the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air)

Tools to assess time-location patterns related to environmental exposures have expanded from reliance on time-location diaries (TLDs) and questionnaires to use of geospatial location devices such as data-logging Global Positioning System (GPS) equipment. The Multi-Ethnic Study of Atherosclerosis and Air Pollution obtained typical time-location patterns via questionnaire for 6424 adults in six US cities. At a later time (mean 4.6 years after questionnaire), a subset (n=128) participated in high-resolution data collection for specific 2-week periods resulting in concurrent GPS and detailed TLD data, which were aggregated to estimate time spent in various microenvironments. During these 2-week periods, participants were observed to spend the most time at home indoors (mean of 78%) and a small proportion of time in-vehicle (mean of 4%). Similar overall patterns were reported by these participants on the prior questionnaire (mean home indoors: 75%; mean in-vehicle: 4%). However, individual micro-environmental time estimates measured over specific 2-week periods were not highly correlated with an individual's questionnaire report of typical behavior (Spearman's ρ of 0.43 for home indoors and 0.39 for in-vehicle). Although questionnaire data about typical time-location patterns can inform interpretation of long-term epidemiological analyses and risk assessment, they may not reliably represent an individual's short-term experience.

Benefits of Mobile Phone Technology for Personal Environmental Monitoring

Background

Tracking individuals in environmental epidemiological studies using novel mobile phone technologies can provide valuable information on geolocation and physical activity, which will improve our understanding of environmental exposures.

Objective

The objective of this study was to assess the performance of one of the least expensive mobile phones on the market to track people's travel-activity pattern.

Methods

Adults living and working in Barcelona (72/162 bicycle commuters) carried simultaneously a mobile phone and a Global Positioning System (GPS) tracker and filled in a travel-activity diary (TAD) for 1 week (N=162). The CalFit app for mobile phones was used to log participants’ geographical location and physical activity. The geographical location data were assigned to different microenvironments (home, work or school, in transit, others) with a newly developed spatiotemporal map-matching algorithm. The tracking performance of the mobile phones was compared with that of the GPS trackers using chi-square test and Kruskal-Wallis rank sum test. The minute agreement across all microenvironments between the TAD and the algorithm was compared using the Gwet agreement coefficient (AC1).

Results

The mobile phone acquired locations for 905 (29.2%) more trips reported in travel diaries than the GPS tracker (P<.001) and had a median accuracy of 25 m. Subjects spent on average 57.9%, 19.9%, 9.0%, and 13.2% of time at home, work, in transit, and other places, respectively, according to the TAD and 57.5%, 18.8%, 11.6%, and 12.1%, respectively, according to the map-matching algorithm. The overall minute agreement between both methods was high (AC1 .811, 95% CI .810-.812).

Conclusions

The use of mobile phones running the CalFit app provides better information on which microenvironments people spend their time in than previous approaches based only on GPS trackers. The improvements of mobile phone technology in microenvironment determination are because the mobile phones are faster at identifying first locations and capable of getting location in challenging environments thanks to the combination of assisted-GPS technology and network positioning systems. Moreover, collecting location information from mobile phones, which are already carried by individuals, allows monitoring more people with a cheaper and less burdensome method than deploying GPS trackers.

Children's GPS-determined versus self-reported transport in leisure time and associations with parental perceptions of the neighborhood environment

Background

This study aimed to examine both GPS-determined and self-reported walking, cycling and passive transport in leisure time during week- and weekend-days among 10 to 12-year old children. Comparisons between GPS-determined and self-reported transport in leisure time were investigated. Second, associations between parental perceptions of the neighborhood environment and GPS-determined walking, cycling and passive transport in leisure time were studied.

Methods

Children (10 to 12-years old; n = 126) wore a GPS device and an accelerometer for 7 consecutive days to assess objectively measured transport in leisure time and filled out a diary to assess self-reported transport in leisure time. Parents completed a questionnaire to assess parental perceptions of the neighborhood environment. Pearson correlations and t-tests were used to test for concurrent validity and differences between GPS-determined and self-reported transport in leisure time. Generalized linear models were used to determine the associations between the parental perceptions of the neighborhood environment and GPS-determined transport in leisure time.

Results

Overall, children under-reported their walking and cycling in leisure time, compared to GPS-determined measures (all p values <0.001). However, children reported their passive transport in leisure time during weekend days quite accurate. GPS-determined measures revealed that children walked most during weekdays (M = 3.96 trips/day; 26.10 min/day) and used passive transport more frequently during weekend days (M = 2.12 trips/day; 31.39 min/day). Only a few parental perceived environmental attributes of the neighborhood (i.e. residential density, land use mix access, quality and availability of walking and cycling facilities, and aesthetics) were significantly associated with children’s GPS-determined walking, cycling or passive transport in leisure time.

Conclusions

To accurately assess children’s active transport in leisure time, GPS measures are recommended over self-reports. More research using GPS with a focus on children’s transport in leisure time and investigating the associations with parental perceptions of the neighborhood environment is needed to confirm the results of the present study.

Electronic supplementary material

The online version of this article (doi:10.1186/s12942-016-0045-9) contains supplementary material, which is available to authorized users.

Assessing neighbourhood destination access for children: development of the NDAI-C audit tool

Considerable societal changes across many countries have altered how children interact with their local environment, yet child-specific destination data have not been translated into a child-related destination accessibility index to further understand how neighbourhood locations support or hinder child mobility. Using data sourced from 238 9–11 year-old children living in Auckland, New Zealand, we aimed to: identify common destinations children travelled to; and develop a spatially derived objective index to quantify access to destinations that may support child mobility in the neighbourhood. Our findings show that children accessed a wide range of destinations during their daily activities, and the neighbourhoods that supported children's mobility tended to be located in more established areas, rather than newer greenfield developments.

Measures of outdoor play and independent mobility in children and youth: A methodological review

OBJECTIVES

Declines in children's outdoor play have been documented globally, which are partly due to heightened restrictions around children's independent mobility. Literature on outdoor play and children's independent mobility is increasing, yet no paper has summarized the various methodological approaches used. A methodological review could highlight most commonly used measures and comprehensive research designs that could result in more standardized methodological approaches.

DESIGN

Methodological review.

METHODS

A standardized protocol guided a methodological review of published research on measures of outdoor play and children's independent mobility in children and youth (0-18 years). Online searches of 8 electronic databases were conducted and studies included if they contained a subjective/objective measure of outdoor play or children's independent mobility. References of included articles were scanned to identify additional articles.

RESULTS

Twenty-four studies were included on outdoor play, and twenty-three on children's independent mobility. Study designs were diverse. Common objective measures included accelerometry, global positioning systems and direct observation; questionnaires, surveys and interviews were common subjective measures. Focus groups, activity logs, monitoring sheets, travel/activity diaries, behavioral maps and guided tours were also utilized. Questionnaires were used most frequently, yet few studies used the same questionnaire. Five studies employed comprehensive, mixed-methods designs.

CONCLUSIONS

Outdoor play and children's independent mobility have been measured using a wide variety of techniques, with only a few studies using similar methodologies. A standardized methodological approach does not exist. Future researchers should consider including both objective measures (accelerometry and global positioning systems) and subjective measures (questionnaires, activity logs, interviews), as more comprehensive designs will enhance understanding of each multidimensional construct. Creating a standardized methodological approach would improve study comparisons.

Environmental and socio-demographic associates of children's active transport to school: a cross-sectional investigation from the URBAN Study

Background

Active transport (e.g., walking, cycling) to school (ATS) can contribute to children’s physical activity and health. The built environment is acknowledged as an important factor in understanding children’s ATS, alongside parental factors and seasonality. Inconsistencies in methodological approaches exist, and a clear understanding of factors related to ATS remains equivocal. The purpose of this study was to gain a better understanding of associates of children’s ATS, by considering the effects of daily weather patterns and neighbourhood walk ability and neighbourhood preferences (i.e., for living in a high or low walkable neighbourhood) on this behaviour.

Methods

Data were drawn from the Understanding Relationships between Activity and Neighbourhoods study, a cross-sectional study of physical activity and the built environment in adults and children in four New Zealand cities. Parents of participating children completed an interview and daily trip diary that assessed their child’s mode of travel to school, household and individual demographic information, and parental neighbourhood preference. Daily weather data were downloaded from New Zealand’s national climate database. Geographic information systems-derived variables were calculated for distance to school and neighbourhood walkability. Bivariate analyses were conducted with ATS and potential associates; factors related to ATS at p < 0.20 were considered simultaneously in generalized estimation equation models, and backwards elimination of non-significant factors was conducted; city was treated as a fixed effect in all models.

Results

A total of 217 children aged 6.5-15 years participated in this study. Female sex, age, city, household income, limited/no car access, residing in zone of school, shorter distance to school, neighbourhood self selection, rainfall, and sunlight hours were simultaneously considered in multivariate generalised estimation equation modelling (all p < 0.20 in bivariate analyses). After elimination of non-significant factors, age (p = 0.005), shorter distance to school (p < 0.001), city (p = 0.03), and neighbourhood self selection (p = 0.04) remained significantly associated with ATS in the multivariate analysis.

Conclusion

Distance to school is the prevailing environmental influencing factor on children’s ATS. This study, in conjunction with previous research, suggests that school siting is likely an important associate of children’s ATS.

Using Global Positioning Systems (GPS) and temperature data to generate time-activity classifications for estimating personal exposure in air monitoring studies: an automated method

BACKGROUND

Personal exposure studies of air pollution generally use self-reported diaries to capture individuals' time-activity data. Enhancements in the accuracy, size, memory and battery life of personal Global Positioning Systems (GPS) units have allowed for higher resolution tracking of study participants' locations. Improved time-activity classifications combined with personal continuous air pollution sampling can improve assessments of location-related air pollution exposures for health studies.

METHODS

Data was collected using a GPS and personal temperature from 54 children with asthma living in Montreal, Canada, who participated in a 10-day personal air pollution exposure study. A method was developed that incorporated personal temperature data and then matched a participant's position against available spatial data (i.e., road networks) to generate time-activity categories. The diary-based and GPS-generated time-activity categories were compared and combined with continuous personal PM2.5 data to assess the impact of exposure misclassification when using diary-based methods.

RESULTS

There was good agreement between the automated method and the diary method; however, the automated method (means: outdoors = 5.1%, indoors other =9.8%) estimated less time spent in some locations compared to the diary method (outdoors = 6.7%, indoors other = 14.4%). Agreement statistics (AC1 = 0.778) suggest 'good' agreement between methods over all location categories. However, location categories (Outdoors and Transit) where less time is spent show greater disagreement: e.g., mean time "Indoors Other" using the time-activity diary was 14.4% compared to 9.8% using the automated method. While mean daily time "In Transit" was relatively consistent between the methods, the mean daily exposure to PM2.5 while "In Transit" was 15.9 μg/m3 using the automated method compared to 6.8 μg/m3 using the daily diary.

CONCLUSIONS

Mean times spent in different locations as categorized by a GPS-based method were comparable to those from a time-activity diary, but there were differences in estimates of exposure to PM2.5 from the two methods. An automated GPS-based time-activity method will reduce participant burden, potentially providing more accurate and unbiased assessments of location. Combined with continuous air measurements, the higher resolution GPS data could present a different and more accurate picture of personal exposures to air pollution.

Dynamic Accuracy of GPS Receivers for Use in Health Research: A Novel Method to Assess GPS Accuracy in Real-World Settings

The emergence of portable global positioning system (GPS) receivers over the last 10 years has provided researchers with a means to objectively assess spatial position in free-living conditions. However, the use of GPS in free-living conditions is not without challenges and the aim of this study was to test the dynamic accuracy of a portable GPS device under real-world environmental conditions, for four modes of transport, and using three data collection intervals. We selected four routes on different bearings, passing through a variation of environmental conditions in the City of Copenhagen, Denmark, to test the dynamic accuracy of the Qstarz BT-Q1000XT GPS device. Each route consisted of a walk, bicycle, and vehicle lane in each direction. The actual width of each walking, cycling, and vehicle lane was digitized as accurately as possible using ultra-high-resolution aerial photographs as background. For each trip, we calculated the percentage that actually fell within the lane polygon, and within the 2.5, 5, and 10 m buffers respectively, as well as the mean and median error in meters. Our results showed that 49.6% of all ≈68,000 GPS points fell within 2.5 m of the expected location, 78.7% fell within 10 m and the median error was 2.9 m. The median error during walking trips was 3.9, 2.0 m for bicycle trips, 1.5 m for bus, and 0.5 m for car. The different area types showed considerable variation in the median error: 0.7 m in open areas, 2.6 m in half-open areas, and 5.2 m in urban canyons. The dynamic spatial accuracy of the tested device is not perfect, but we feel that it is within acceptable limits for larger population studies. Longer recording periods, for a larger population are likely to reduce the potentially negative effects of measurement inaccuracy. Furthermore, special care should be taken when the environment in which the study takes place could compromise the GPS signal.

Tracking and visualization of space-time activities for a micro-scale flu transmission study

Background

Infectious diseases pose increasing threats to public health with increasing population density and more and more sophisticated social networks. While efforts continue in studying the large scale dissemination of contagious diseases, individual-based activity and behaviour study benefits not only disease transmission modelling but also the control, containment, and prevention decision making at the local scale. The potential for using tracking technologies to capture detailed space-time trajectories and model individual behaviour is increasing rapidly, as technological advances enable the manufacture of small, lightweight, highly sensitive, and affordable receivers and the routine use of location-aware devices has become widespread (e.g., smart cellular phones). The use of low-cost tracking devices in medical research has also been proved effective by more and more studies. This study describes the use of tracking devices to collect data of space-time trajectories and the spatiotemporal processing of such data to facilitate micro-scale flu transmission study. We also reports preliminary findings on activity patterns related to chances of influenza infection in a pilot study.

Methods

Specifically, this study employed A-GPS tracking devices to collect data on a university campus. Spatiotemporal processing was conducted for data cleaning and segmentation. Processed data was validated with traditional activity diaries. The A-GPS data set was then used for visual explorations including density surface visualization and connection analysis to examine space-time activity patterns in relation to chances of influenza infection.

Results

When compared to diary data, the segmented tracking data demonstrated to be an effective alternative and showed greater accuracies in time as well as the details of routes taken by participants. A comparison of space-time activity patterns between participants who caught seasonal influenza and those who did not revealed interesting patterns.

Conclusions

This study proved that tracking technology an effective technique for obtaining data for micro-scale influenza transmission research. The findings revealed micro-scale transmission hotspots on a university campus and provided insights for local control and prevention strategies.

Quantifying human exposure to air pollution--moving from static monitoring to spatio-temporally resolved personal exposure assessment

Quantifying human exposure to air pollutants is a challenging task. Ambient concentrations of air pollutants at potentially harmful levels are ubiquitous in urban areas and subject to high spatial and temporal variability. At the same time, every individual has unique activity-patterns. Exposure results from multifaceted relationships and interactions between environmental and human systems, adding complexity to the assessment process. Traditionally, approaches to quantify human exposure have relied on pollutant concentrations from fixed air quality network sites and static population distributions. New developments in sensor technology now enable us to monitor personal exposure to air pollutants directly while people are moving through their activity spaces and varying concentration fields. The literature review on which this paper is based on reflects recent developments in the assessment of human exposure to air pollution. This includes the discussion of methodologies and concepts, and the elaboration of approaches and study designs applied in the field. We identify shortcomings of current approaches and discuss future research needs. We close by proposing a novel conceptual model for the integrated assessment of human exposure to air pollutants taking into account latest technological capabilities and contextual information.