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

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.

Monitoring mobility in older adults using a Global Positioning System (GPS) smartwatch and accelerometer: A validation study

There is growing interest in identifying valid and reliable methods for detecting early mobility limitations in aging populations. A multi-sensor approach that combines accelerometry with Global Positioning System (GPS) devices could provide valuable insights into late-life mobility decline; however, this innovative approach requires more investigation. We conducted a series of two experiments with 25 older participants (66.2±8.5 years) to determine the validity of a GPS enabled smartwatch (TicWatch S2 and Pro 3 Ultra GPS) and separate accelerometer (ActiGraph wGT3X-BT) to collect movement, navigation and body posture data relevant to mobility. In experiment 1, participants wore the TicWatchS2 and ActiGraph simultaneously on the wrist for 3 days. In experiment 2, participants wore the TicWatch Pro 2 Ultra GPS on the wrist and ActiGraph on the thigh for 3 days. In both experiments participants also carried a Qstarz data logger for trips outside the home. The TicWatch Pro 3 Ultra GPS performed better than the S2 model and was similar to the Qstarz in all tested trip-related measures, and it was able to estimate both passive and active trip modes. Both models showed similar results to the gold standard Qstarz in life-space-related measures. The TicWatch S2 demonstrated good to excellent overall agreement with the ActiGraph algorithms for the time spent in sedentary and non-sedentary activities, with 84% and 87% agreement rates, respectively. Under controlled conditions, the TicWatch Pro 3 Ultra GPS consistently measured step count in line with the participants' self-reported data, with a bias of 0.4 steps. The thigh-worn ActiGraph algorithm accurately classified sitting and lying postures (97%) and standing postures (90%). Our multi-sensor approach to monitoring mobility has the potential to capture both accelerometer-derived movement data and trip/life-space data only available through GPS. In this study, we found that the TicWatch models were valid devices for capturing GPS and raw accelerometer data, making them useful tools for assessing real-life mobility in older adults.

Urban environment and health behaviours in children from six European countries

BACKGROUND

Urban environmental design is increasingly considered influential for health and wellbeing, but evidence is mostly based on adults and single exposure studies. We evaluated the association between a wide range of urban environment characteristics and health behaviours in childhood.

METHODS

We estimated exposure to 32 urban environment characteristics (related to the built environment, traffic, and natural spaces) for home and school addresses of 1,581 children aged 6-11 years from six European cohorts. We collected information on health behaviours including total amount of overall moderate-to-vigorous physical activity, physical activity outside school hours, active transport, sedentary behaviours and sleep duration, and developed patterns of behaviours with principal component analysis. We used an exposure-wide association study to screen all exposure-outcome associations, and the deletion-substitution-addition algorithm to build a final multi-exposure model.

RESULTS

In multi-exposure models, green spaces (Normalized Difference Vegetation Index, NDVI) were positively associated with active transport, and inversely associated with sedentary time (22.71 min/day less (95 %CI -39.90, -5.51) per interquartile range increase in NDVI). Residence in densely built areas was associated with more physical activity and less sedentary time, and densely populated areas with less physical activity outside school hours and more sedentary time. Presence of a major road was associated with lower sleep duration (-4.80 min/day (95 %CI -9.11, -0.48); compared with no major road). Results for the behavioural patterns were similar.

CONCLUSIONS

This multicohort study suggests that areas with more vegetation, more building density, less population density and without major roads are associated with improved health behaviours in childhood.

Parents' Perceptions of the Neighbourhood Built Environment Are Associated with the Social and Emotional Development of Young Children

The influence of the neighbourhood built environment on young children’s physical development has been well-documented; however, there is limited empirical evidence of an association with social and emotional development. Parental perceptions of the neighbourhood built environment may act as facilitators or barriers to young children’s play and interactions in their local environment. The aim of this study was to examine the associations between parents’ perceptions of the neighbourhood built environment and the social-emotional development of children aged two-to-five years. Parents’ positive perceptions of traffic safety (OR 0.74; 95% CI 0.55, 0.98), crime safety (OR 0.79; 95% CI 0.64, 0.99) and land use mix–access (OR 0.74; 95% CI 0.56, 0.98) were associated with lower odds of social-emotional difficulties, while positive perceptions of walking and cycling facilities were associated with higher odds of difficulties (OR 1.26; 95% CI 1.02, 1.55). Positive perceptions of land use mix–access (OR 1.32; 95% CI 1.03, 1.69), street connectivity (OR 1.35; 95% CI 1.10, 1.66) and neighbourhood aesthetics (OR 1.27; 95% CI 1.01, 1.60) were associated with higher odds of prosocial behaviours. Interventions to improve parents’ perceptions of built environment features may facilitate opportunities for play and interactions which contribute to healthy social-emotional development.

Identifying risk profiles for excess sedentary behaviour in youth using individual, family and neighbourhood characteristics

There are few known determinants of sedentary behaviour (SB) in children. We generated and compared profiles associated with risk of excess SB among children (n = 294) both at 8-10 and 10-12 years of age (Visits 1 and 2, respectively), using data from the QUebec Adipose and Lifestyle InvesTigation in Youth. Excess SB was measured by accelerometry and defined as >50% of total wear time at <100 counts/minutes. Recursive partitioning analyses were performed with candidate individual-, family-, and neighbourhood-level factors assessed at Visit 1, and distinct groups at varying risk of excess SB were identified for both timepoints. From the ages of 8-10 to 10-12 years, the prevalence of excess SB more than doubled (24.5% to 57.1%). At Visit 1, excess SB was greatest (73%) among children simultaneously not meeting physical activity guidelines, reporting >2 h/day of weekday non-academic screen time, living in low-dwelling density neighbourhoods, having poor park access, and living in neighbourhoods with greater disadvantage. At Visit 2, the high-risk group (70%) was described by children simultaneously not meeting physical activity guidelines, reporting >2 h/day of non-academic screen time on weekends, and living in neighbourhoods with low disadvantage. Risk factors related to individual lifestyle behaviours are generally consistent, and neighbourhood factors generally inconsistent, as children age from late childhood to pre-adolescence. Multiple factors from developmental, behavioural and contextual domains increase risk for excess sedentary behaviour; these warrant consideration to devise effective prevention or management strategies.

Land use mix in the neighbourhood and childhood obesity

Land use mix (LUM) in the neighbourhood is an important aspect for promoting healthier lifestyles and consequently reducing the risk for childhood obesity. However, findings of the association between LUM and childhood obesity remain controversial. A literature search was conducted on Cochrane Library, PubMed and Web of Science for articles published before 1 January 2019. In total, 25 cross-sectional and two longitudinal studies were identified. Among them, Geographic Information Systems were used to measure LUM in 15 studies, and perceived LUM was measured in 12 studies. Generally, most studies revealed an association between a higher LUM and higher PA levels and lower obesity rates, although some studies also reported null or negative associations. The various exposure and outcome assessment have limited the synthesis to obtain pooled estimates. The evidence remains scare on the association between LUM and children's weight status, and more longitudinal studies are needed to examine the independent pathways and causality between LUM and weight-related behaviours/outcomes.

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.

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

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

Are neighborhood characteristics associated with sedentary behavior in adolescents? A systematic review

Sedentary behavior (SB) has emerged as a potential risk factor for chronic diseases. SB includes activities requiring low energy expenditure (≤1.5 metabolic equivalents) performed in a sitting or reclining posture. Our study aimed to gather evidence on the association between SB outcomes in adolescents (10-19 years) and neighborhood characteristics. This systematic review (PROSPERO registration number: CRD42018076877) examined studies indexed in PubMed Central®, LILACS, ScienceDirect, and SPORTDiscus databases. Sixteen articles were included. Insecurity during daytime hours, crime incidence, physical and social disorders, a higher neighborhood socioeconomic level, and time spent with peers were associated with higher levels of SB. Traffic, availability of a favorable environment for physical activity, and higher residential density were associated with lower levels of SB. Despite great variability in the SB cutoff points and methodology used for evaluating SB and neighborhood characteristics among studies, the evidence suggests that adolescent SB might be influenced by neighborhood characteristics.

Influence of parental perceived environment on physical activity, TV viewing, active play and Body Mass Index among Portuguese children: A mediation analysis

OBJECTIVES

The environment is believed to be key in obesity prevention, yet it is unclear how factors in the neighborhood influence weight-related behaviors. The present study aimed to investigate the influence of parental perceived environment on physical activity (PA), television (TV) time, active play and Body Mass Index (BMI) z score, and the mediating role of these weight-related behaviors on the relationship between neighborhood characteristics and children's BMI.

METHODS

Data of 8472 Portuguese preschool (aged 3-6, n = 3819) and school-aged children (aged 7-11 years, n = 4653) were collected during 2016/2017. Structural equation modeling was used to estimate the associations between parents perceived neighborhood characteristics (latent variables: unsafety and built/physical environment) and child's BMI z score, PA and TV time.

RESULTS

Among preschoolers, the latent variables of the perceived environment were not associated with the BMI, TV time, extracurricular PA, and active play. Among schoolchildren, the unsafety environment was positively associated with both the BMI (SC = 0.050, P = .008) and the time spent watching TV (SC = 0.052, P = .031) and negatively associated with extracurricular PA (SC = -0.125, P < .001). The latent variable Favorable Built Environment for PA (ie, environmental facilitating elements) was positively associated with active play (SC = 0.041, P = .031). Moreover, the TV time was a marginally significant mediator of the relationship between the perceived unsafe environment and the BMI of school-aged children (B = 0.002, P = .096).

CONCLUSIONS

In conclusion, changes in the environment to targeting parental perception of neighborhood safety could have positive effects on the promotion of healthy weight and the adoption of a healthy lifestyle in school-aged children.

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.

On the accuracy and potential of Google Maps location history data to characterize individual mobility for air pollution health studies

Appropriately characterizing spatiotemporal individual mobility is important in many research areas, including epidemiological studies focusing on air pollution. However, in many retrospective air pollution health studies, exposure to air pollution is typically estimated at the subjects' residential addresses. Individual mobility is often neglected due to lack of data, and exposure misclassification errors are expected. In this study, we demonstrate the potential of using location history data collected from smartphones by the Google Maps application for characterizing historical individual mobility and exposure. Here, one subject carried a smartphone installed with Google Maps, and a reference GPS data logger which was configured to record location every 10 s, for a period of one week. The retrieved Google Maps Location History (GMLH) data were then compared with the GPS data to evaluate their effectiveness and accuracy of the GMLH data to capture individual mobility. We also conducted an online survey (n = 284) to assess the availability of GMLH data among smartphone users in the US. We found the GMLH data reasonably captured the spatial movement of the subject during the one-week time period at up to 200 m resolution. We were able to accurately estimate the time the subject spent in different microenvironments, as well as the time the subject spent driving during the week. The estimated time-weighted daily exposures to ambient particulate matter using GMLH and the GPS data logger were also similar (error less than 1.2%). Survey results showed that GMLH data may be available for 61% of the survey sample. Considering the popularity of smartphones and the Google Maps application, detailed historical location data are expected to be available for large portion of the population, and results from this study highlight the potential of these location history data to improve exposure estimation for retrospective epidemiological studies.

Towards a comprehensive set of GPS-based indicators reflecting the multidimensional nature of daily mobility for applications in health and aging research

BACKGROUND

GPS tracking is increasingly used in health and aging research to objectively and unobtrusively assess individuals' daily-life mobility. However, mobility is a complex concept and its thorough description based on GPS-derived mobility indicators remains challenging.

METHODS

With the aim of reflecting the breadth of aspects incorporated in daily mobility, we propose a conceptual framework to classify GPS-derived mobility indicators based on their characteristic and analytical properties for application in health and aging research. In order to demonstrate how the classification framework can be applied, existing mobility indicators as used in existing studies are classified according to the proposed framework. Then, we propose and compute a set of selected mobility indicators based on real-life GPS data of 95 older adults that reflects diverse aspects of individuals' daily mobility. To explore latent dimensions that underlie the mobility indicators, we conduct a factor analysis.

RESULTS

The proposed framework enables a conceptual classification of mobility indicators based on the characteristic and analytical aspects they reflect. Characteristic aspects inform about the content of the mobility indicator and comprise categories related to space, time, movement scope, and attribute. Analytical aspects inform how a mobility indicator is aggregated with respect to temporal scale and statistical property. The proposed categories complement existing studies that often underrepresent mobility indicators involving timing, temporal distributions, and stop-move segmentations of movements. The factor analysis uncovers the following six dimensions required to obtain a comprehensive view of an older adult's daily mobility: extent of life space, quantity of out-of-home activities, time spent in active transport modes, stability of life space, elongation of life space, and timing of mobility.

CONCLUSION

This research advocates incorporating GPS-based mobility indicators that reflect the multi-dimensional nature of individuals' daily mobility in future health- and aging-related research. This will foster a better understanding of what aspects of mobility are key to healthy aging.

Mobile Sensing in Environmental Health and Neighborhood Research

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

Objectively measured active transportation to school and other destinations among 10-13 year olds

BACKGROUND

Descriptive data on active transportation in children focuses on the trip to school and has relied on subjective reports. The purpose of this study was to use objective measures to describe total active transportation and active transportation to common destinations within children.

METHODS

This was a descriptive study of 388 children aged 10-13 years from Kingston, Ontario, Canada. Participants wore a Garmin GPS watch during waking hours for seven days. Personal Activity Measurement Location System software used the GPS data to identify trips, time spent in each trip and the trip modality (walking, bicycle or vehicle). Google Maps software was used to identify trip destinations.

RESULTS

A total of 8875 trips were identified. Most (69%) trips were made by vehicle; 25% were made by walking and 6% by bicycle. Mean time spent in active transportation was 10.3 min/day (95% CI: 7.4, 14.5). Time spent in active transportation was higher for boys (12.1 min/day [95% CI: 8.8, 17.0) than for girls (8.5 min/day [95% CI: 6.1, 12.0]) and increased from 7.7 min/day (95% CI: 5.5, 11.1) at age 10 to 14.3 min/day (95% CI: 10.3, 19.9) at age 13. Time spent in active transportation was lower in the winter by comparison to the other seasons. The four most common active transportation destinations were the participant's home, school, other people's homes, and parks or greenspace with 69%, 39%, 37% and 32% of participants walking or bicycling to these destinations at least once over the 7-day measurement period.

CONCLUSION

Over 65% of trips made and time spent travelling occurred in a vehicle. When active transportation was used, the most common destinations were home, school, other people's homes, and parks.

Predictors of Daily Mobility of Adults in Peri-Urban South India

Daily mobility, an important aspect of environmental exposures and health behavior, has mainly been investigated in high-income countries. We aimed to identify the main dimensions of mobility and investigate their individual, contextual, and external predictors among men and women living in a peri-urban area of South India. We used 192 global positioning system (GPS)-recorded mobility tracks from 47 participants (24 women, 23 men) from the Cardiovascular Health effects of Air pollution in Telangana, India (CHAI) project (mean: 4.1 days/person). The mean age was 44 (standard deviation: 14) years. Half of the population was illiterate and 55% was in unskilled manual employment, mostly agriculture-related. Sex was the largest determinant of mobility. During daytime, time spent at home averaged 13.4 (3.7) h for women and 9.4 (4.2) h for men. Women's activity spaces were smaller and more circular than men's. A principal component analysis identified three main mobility dimensions related to the size of the activity space, the mobility in/around the residence, and mobility inside the village, explaining 86% (women) and 61% (men) of the total variability in mobility. Age, socioeconomic status, and urbanicity were associated with all three dimensions. Our results have multiple potential applications for improved assessment of environmental exposures and their effects on health.