Utility of Global Positioning System to Measure Active Transport in Urban Areas

Review of Validity and Reliability of Garmin Activity Trackers

Purpose

A systematic review to summarize the validity and reliability of steps, distance, energy expenditure, speed, elevation, heart rate, and sleep assessed by Garmin activity trackers.

Methods

Searches included studies published through December 31, 2018. Correlation coefficients (CC) were assessed as low (<0.60), moderate (0.60-<0.75), good (0.75-<0.90), or excellent (>=0.90). Mean absolute percentage errors (MAPE) were assessed as acceptable at <5% in controlled conditions and <10% for free-living.

Results

Overall, 32 studies of adults documented validity. Four of these studies also documented reliability. The sample size ranged from 1 to 95 for validity and 4 to 31 for reliability testing. Step inter- and intra-reliability was good-to-excellent and speed intra-reliability was excellent. No other features were explored for reliability. Step validity, across 16 studies, generally indicated good-to-excellent CC and acceptable MAPE. Distance validity, tested in three studies, generally indicated poor CC and MAPE that exceeded acceptable limits, with both over and underestimation. Energy expenditure validity, across 12 studies, generally indicated wide variability in CC and MAPE that exceeded acceptable limits. Heart rate validity in five studies had low-to-excellent CC and all MAPE exceeded acceptable limits. Speed, elevation, and sleep validity were assessed in only one or two studies each; for sleep, the criterion relied on self-report rather than polysomnography.

Conclusion

This systematic review of Garmin activity trackers among adults indicated higher validity of steps; few studies on speed, elevation, and sleep; and lower validity for distance, energy expenditure, and heart rate. Intra- and inter-device feature reliability needs further testing.

United States' neighborhood park use and physical activity over two years: The National Study of Neighborhood Parks

The United States lacks surveillance to monitor park use and conditions. The purpose of this study was to use the System for Observing Play and Recreation in Communities (SOPARC) as a surveillance tool to describe the conditions, user characteristics, and physical activity of a national sample of neighborhood parks at two time points. Using a stratified multistage sampling strategy, a representative sample of 174 neighborhood parks in 25 major United States' cities were selected. During 2014 and 2016, park-related use, conditions, and physical activity were assessed using SOPARC in 169 parks. Overall, 74,106 park users were observed at baseline and 69,150 park users were observed two years later (p = 0.37). There were persistent disparities in park use by gender and age, with disproportionately more male than female users in each age group (child, teenager, adult, older adult). Older adults used the park less than other age groups. Almost two-thirds of park users were observed being sedentary (61.9% in 2014, 60.7% in 2016), followed by moderate (30.8%, 32.0%) and vigorous (7.3%, 7.3%) activity. Empty target areas increased over two years (75.3%, 77.6%; p = 0.01) and those that were equipped (2.6%, 1.2%; p = 0.0003), accessible (95.4%, 94.3%; p = 0.01), and organized (2.6%, 1.7%; p = 0.01) decreased. Areas that were usable (97.5%, 97.4%) or provided supervised activities (2.0%, 2.4%) did not change significantly. The findings demonstrate the value of SOPARC as a surveillance tool, identify user groups under represented at parks, and suggest an opportunity to encourage more park-based physical activity among park visitors.

Park use and physical activity among adolescent girls at two time points

This longitudinal study described park usage and assessed the contribution of parks to moderate to vigorous physical activity (MVPA) among adolescent girls. High school girls from California (n = 131) and Minnesota (n = 134) wore a global positioning system (GPS) monitor and accelerometer for 6 consecutive days at two time points, one year apart. Park visits were classified by linking the GPS, accelerometer, and park and built environment data around home and school locations into a geographic information system. At baseline, 20% of girls visited a park at least once (mean 0.1 times/day), which was similar one year later (19%, mean 0.1 times/day). Girls lived a mean Euclidean distance of 0.2 miles to the nearest park at both times. Among all park visits, the mean Euclidean distance of the park visited was 4.1 (baseline) and 3.9 miles (follow-up). The average duration of park visits was higher at baseline (63.9 minutes) compared to follow-up (38.4 minutes). On days when a park was visited, MVPA was higher than on days when a park was not visited. On average, 1.9% (baseline) and 2.8% (follow-up) of MVPA occurred in parks. In this study, parks were an under-used resource for adolescent girls, particularly for MVPA.

A Pilot Study Using Mixed GPS/Narrative Interview Methods to Understand Geospatial Behavior in Homeless Populations

Tracking the movements of homeless populations presents methodological difficulties, but understanding their movements in space and time is needed to inform optimal placement of services. This pilot study developed, tested, and refined methods to apply global positioning systems (GPS) technology paired with individual narratives to chronicle the movements of homeless populations. Detail of methods development and difficulties encountered and addressed, and geospatial findings are provided. A pilot sample of 29 adults was recruited from a low-demand homeless shelter in the downtown area of Fort Worth, Texas. Pre- and post-deployment interviews provided participant characteristics and planned and retrospectively-reported travels. Only one of the first eight deployments returned with sufficient usable data. Ultimately 19 participants returned the GPS device with >20 h of usable data. Protocol adjustments addressing methodological difficulties achieved 81 % of subsequent participants returning with sufficient usable data. This study established methods and demonstrated feasibility for tracking homeless population travels.

Refining Time-Activity Classification of Human Subjects Using the Global Positioning System

BACKGROUND

Detailed spatial location information is important in accurately estimating personal exposure to air pollution. Global Position System (GPS) has been widely used in tracking personal paths and activities. Previous researchers have developed time-activity classification models based on GPS data, most of them were developed for specific regions. An adaptive model for time-location classification can be widely applied to air pollution studies that use GPS to track individual level time-activity patterns.

METHODS

Time-activity data were collected for seven days using GPS loggers and accelerometers from thirteen adult participants from Southern California under free living conditions. We developed an automated model based on random forests to classify major time-activity patterns (i.e. indoor, outdoor-static, outdoor-walking, and in-vehicle travel). Sensitivity analysis was conducted to examine the contribution of the accelerometer data and the supplemental spatial data (i.e. roadway and tax parcel data) to the accuracy of time-activity classification. Our model was evaluated using both leave-one-fold-out and leave-one-subject-out methods.

RESULTS

Maximum speeds in averaging time intervals of 7 and 5 minutes, and distance to primary highways with limited access were found to be the three most important variables in the classification model. Leave-one-fold-out cross-validation showed an overall accuracy of 99.71%. Sensitivities varied from 84.62% (outdoor walking) to 99.90% (indoor). Specificities varied from 96.33% (indoor) to 99.98% (outdoor static). The exclusion of accelerometer and ambient light sensor variables caused a slight loss in sensitivity for outdoor walking, but little loss in overall accuracy. However, leave-one-subject-out cross-validation showed considerable loss in sensitivity for outdoor static and outdoor walking conditions.

CONCLUSIONS

The random forests classification model can achieve high accuracy for the four major time-activity categories. The model also performed well with just GPS, road and tax parcel data. However, caution is warranted when generalizing the model developed from a small number of subjects to other populations.

Comparing GPS, Log, Survey, and Accelerometry to Measure Physical Activity

OBJECTIVES

We explored how objectively measured global positioning system (GPS) and accelerometer data match with travel logs and questionnaires in predicting trip duration and physical activity (PA).

METHODS

99 participants wore GPS devices and accelerometers, and recorded all trips in a log for 5 consecutive days. Participants also completed a self-administered questionnaire on PA and travel behaviors.

RESULTS

There was good agreement between GPS and log for assessment of trip duration, although log measures overestimated trip duration (concordance correlation coefficient 0.53 [0.47, 0.59]; Bland-Altman estimate 0.76 [0.16, 3.71] comparing GPS to log). Log measures underestimated light PA and overestimated moderate PA compared to accelerometry when greater than zero moderate PA was reported.

CONCLUSIONS

It is often not feasible to deploy accelerometry or GPS devices in population research because these devices are expensive and require technical expertise and data processing. Questionnaires and logs provide inexpensive tools to assess PA and travel with reasonable concordance with objective measures. However, they have shortcomings in evaluating the presence and amount of light and moderate PA. Future questionnaires and logs should be developed to evaluate sensitivity to light and moderate PA.

Technologies That Assess the Location of Physical Activity and Sedentary Behavior: A Systematic Review

Background

The location in which physical activity and sedentary behavior are performed can provide valuable behavioral information, both in isolation and synergistically with other areas of physical activity and sedentary behavior research. Global positioning systems (GPS) have been used in physical activity research to identify outdoor location; however, while GPS can receive signals in certain indoor environments, it is not able to provide room- or subroom-level location. On average, adults spend a high proportion of their time indoors. A measure of indoor location would, therefore, provide valuable behavioral information.

Objective

This systematic review sought to identify and critique technology which has been or could be used to assess the location of physical activity and sedentary behavior.

Methods

To identify published research papers, four electronic databases were searched using key terms built around behavior, technology, and location. To be eligible for inclusion, papers were required to be published in English and describe a wearable or portable technology or device capable of measuring location. Searches were performed up to February 4, 2015. This was supplemented by backward and forward reference searching. In an attempt to include novel devices which may not yet have made their way into the published research, searches were also performed using three Internet search engines. Specialized software was used to download search results and thus mitigate the potential pitfalls of changing search algorithms.

Results

A total of 188 research papers met the inclusion criteria. Global positioning systems were the most widely used location technology in the published research, followed by wearable cameras, and radio-frequency identification. Internet search engines identified 81 global positioning systems, 35 real-time locating systems, and 21 wearable cameras. Real-time locating systems determine the indoor location of a wearable tag via the known location of reference nodes. Although the type of reference node and location determination method varies between manufacturers, Wi-Fi appears to be the most popular method.

Conclusions

The addition of location information to existing measures of physical activity and sedentary behavior will provide important behavioral information.

The relationship between utilitarian walking, utilitarian cycling, and body mass index in a population based cohort study of adults: comparing random intercepts and fixed effects models

OBJECTIVE

To examine associations between utilitarian walking, utilitarian cycling, leisure time physical activity and body mass index (BMI).

METHODS

Participants from the National Population Health Survey (NPHS) of Statistics Canada were interviewed by telephone every two years from 1994 to 2010. Analysis includes data from 6894 living participants aged 18-64years. Fixed effects and random intercepts models examined the association between BMI, utilitarian walking, and utilitarian cycling, controlling for behavioral and sociodemographic factors.

RESULTS

The final adjusted fixed effects models showed no significant relationship between utilitarian walking and BMI. In the unbalanced sample utilitarian cycling for 1 to 5h per week (b=-0.15, 95% CI: -0.28 to -0.02), and more than 5h per week (b=-0.22, 95% CI: -0.44 to 0.00) was significantly associated with BMI over time. In the fully balanced sample utilitarian cycling for 1 to 5h per week (b=-0.12, 95% CI: -0.27 to 0.03), more than 5h per week (b=-0.16, 95% CI: -0.45 to 0.13) was not significantly associated with BMI over time.

CONCLUSION

The results suggest that utilitarian walking is not related to BMI. The relationship between utilitarian cycling and BMI is less clear.

Global position sensing and step activity as outcome measures of community mobility and social interaction for an individual with a transfemoral amputation due to dysvascular disease

BACKGROUND AND PURPOSE

Community mobility of individuals following lower limb amputation is highly variable and has a great impact on their quality of life. Currently, clinical assessments of ambulatory ability and motivation influence prosthetic prescription. However, these outcome measures do not effectively quantify community mobility (ie, mobility outside of the clinic) of individuals with an amputation. Advances in global positioning systems (GPSs) and other wearable step-monitoring devices allow for objective, quantifiable measurement of community mobility. This case report will examine the combined use of a GPS unit and a step activity monitor to quantify community mobility and social interaction of an individual with transfemoral amputation due to dysvascular disease.

CASE DESCRIPTION

A 76-year-old woman with a unilateral transfemoral amputation due to vascular disease carried a commercial GPS unit and step activity monitor to quantify her community mobility and social interaction every day over a period of 1 month. The step activity monitor was affixed to her prosthesis. The patient used a wheelchair as well as her prosthesis for everyday mobility.

OUTCOME

Information from the GPS unit and step activity monitor provided quantitative details on the patient's steps taken in and out of the home, wheelchair use, prosthesis use, driving trips, and time spent on social and community trips.

DISCUSSION

This case report describes a potential clinical measurement procedure for quantifying community mobility and social interaction of an individual with lower limb amputation. Future efforts are needed to validate this measurement tool on large sample sizes and in individuals with different mobility levels. Additionally, automatization of data analysis and technological approaches to reduce compromised GPS signals may eventually lead to a practical, clinically useful tool.

Innovation through Wearable Sensors to Collect Real-Life Data among Pediatric Patients with Cardiometabolic Risk Factors

Background. While increasing evidence links environments to health behavior, clinicians lack information about patients' physical activity levels and lifestyle environments. We present mobile health tools to collect and use spatio-behavioural lifestyle data for personalized physical activity plans in clinical settings. Methods. The Dyn@mo lifestyle intervention was developed at the Sainte-Justine University Hospital Center to promote physical activity and reduce sedentary time among children with cardiometabolic risk factors. Mobility, physical activity, and heart rate were measured in free-living environments during seven days. Algorithms processed data to generate spatio-behavioural indicators that fed a web-based interactive mapping application for personalised counseling. Proof of concept and tools are presented using data collected among the first 37 participants recruited in 2011. Results. Valid accelerometer data was available for 5.6 (SD = 1.62) days in average, heart rate data for 6.5 days, and GPS data was available for 6.1 (2.1) days. Spatio-behavioural indicators were shared between patients, parents, and practitioners to support counseling. Conclusion. Use of wearable sensors along with data treatment algorithms and visualisation tools allow to better measure and describe real-life environments, mobility, physical activity, and physiological responses. Increased specificity in lifestyle interventions opens new avenues for remote patient monitoring and intervention.

Field assessments for obesity prevention in children and adults: physical activity, fitness, and body composition

Nutrition and health educators work in community settings implementing lifestyle programs focused on obesity prevention and chronic disease risk reduction. These programs typically focus on improving diet and physical activity (PA) behaviors. Many nutrition educators may not be confident in their ability to select, administer, and interpret PA assessments to effectively evaluate their PA or lifestyle programs. This report will assist educators in identifying and selecting appropriate field-based assessments for measurement of PA, physical fitness, and body composition for children and adults. Specific guidelines, references, and resources are given for selecting assessment methods and test within these 3 areas.

Comparing self-identified and census-defined neighborhoods among adolescents using GPS and accelerometer

BACKGROUND

Numerous definitions of neighborhood exist, yet few studies have considered youth's perceptions of neighborhood boundaries. This study compared youth-identified neighborhood (YIN) boundaries to census-defined neighborhood (CDN) boundaries, and determined how the amount of time spent and moderate-to-vigorous physical activity (MVPA) levels compared within both boundary types.

METHODS

Adolescents aged 11-14 years were asked to identify their neighborhood boundaries using a map. Objective location and physical activity data collected using Global Positioning System (GPS) devices and accelerometers were used to calculate the amount of time spent and MVPA within youth-identified and census-defined neighborhood boundaries. Paired bivariate analyses compared mean area (meters squared), percent of total time, daily MVPA (minutes), time density (minutes/m2) and MVPA density (minutes/m2) for both boundary types.

RESULTS

Youth-identified neighborhoods (1,821,705 m²) and census-defined neighborhoods (1,277,181 m²) were not significantly different in area, p = 0.30. However, subjects spent more time in youth-identified neighborhoods (80.3%) than census-defined neighborhoods (58.4%), p < 0.0001, and engaged in more daily MVPA within youth-identified neighborhoods (14.7 minutes) than census-defined neighborhoods (9.5 minutes), p < 0.0001. After adjusting for boundary area, MVPA density (minutes of MVPA per squared meter of area) remained significantly greater for youth-identified neighborhoods (2.4 × 10-4 minutes/m²) than census-defined neighborhoods (1.4 × 10-4 minutes/m²), p = 0.02.

CONCLUSIONS

Adolescents perceive their neighborhoods to be similar in size to census-defined neighborhoods. However, youth-identified neighborhoods better capture the locations in which adolescents spend time and engage in physical activity. Asking adolescents to identify their neighborhood boundaries is a feasible and valuable method for identifying the spaces that adolescents are exposed to and use to be physically active.

A pilot study using global positioning systems (GPS) devices and surveys to ascertain older adults' travel patterns

Some studies indicate that older adults lead active lives and travel to many destinations including those not in their immediate residential neighborhoods. We used global positioning system (GPS) devices to track the travel patterns of 40 older adults (mean age: 69) in San Francisco and Los Angeles. Study participants wore the GPS devices for 7 days in fall 2010 and winter 2011. We collected survey responses concurrently about travel patterns. GPS data showed a mean of four trips/day, and a mean trip distance of 7.6 km. Survey data indicated that older adults commonly made trips for four activities (e.g., volunteering, work, visiting friends) at least once each week. Older adults regularly travel outside their residential neighborhoods. GPS can document the mode of travel, the path of travel, and the destinations. Surveys can document the purpose of the travel and the impressions or experiences in the specific locations.

Improving Quality of Life by Increasing Outings after Stroke: Study Protocol for the Out-and-About Trial

Rationale

Almost one-third of Australians need help to travel outdoors after a stroke. Ambulation training and escorted outings are recommended as best practice in Australian clinical guidelines for stroke. Yet fewer than 20% of people with stroke receive enough of these sessions in their local community to change outcomes.

Aims

The Out-and-About trial aims to determine the efficacy and cost effectiveness of an implementation program to change team behavior and increase outings by people with stroke.

Design

A two-group cluster-randomized trial will be conducted using concealed allocation, blinded assessors, and intention-to-treat analysis. Twenty community teams and their stroke clients ( n = 300) will be recruited. Teams will be randomized to receive either the Out-and-About program or written guidelines only.

Study Outcomes

The primary outcome is the proportion of people with stroke receiving multiple escorted outings during therapy sessions, measured at baseline and 13 months postintervention. Secondary outcomes include number of outings and distance traveled, measured using a self-report diary at baseline and six months postbaseline, and a global positioning system after six months. Cost effectiveness will measure quality-adjusted life years and health service use, measured at baseline and six months postbaseline.

Discussion

A potential outcome of this study will be evidence for a costed, transferable implementation program. If successful, the program will have international relevance and transferability. Another potential outcome will be validation of a novel and objective method of measuring outdoor travel (global positioning system) to supplement self-report methods.

Contribution of the school journey to daily physical activity in children aged 11-12 years

BACKGROUND

Active travel is a possible method to increase physical activity in children, but the precise contribution of walking to school to daily physical activity is unclear.

PURPOSE

To combine accelerometer and GPS data to quantify moderate-to-vigorous physical activity (MVPA) on the walk to and from school in relation to overall daily levels.

METHODS

Participants were 141 children aged 11-12 years from the PEACH Project (Personal and Environmental Associated with Children's Health) in Bristol, England, measured between 2008 and 2009. Eighty-four children met the inclusion criteria and were included in the final analysis. Accelerometers measured physical activity, GPS receivers recorded location, and mode of travel was self-reported. Data were analyzed between April and October 2011. Combined accelerometer and GPS data were mapped in a GIS. Minutes of MVPA were compared for school journeys taking place between 8:00 AM and 9:00 AM and between 3:00 PM and 5:00 PM and in relation to whole-day levels.

RESULTS

Physical activity levels during journeys to and from school were highly similar, and contributed 22.2 minutes (33.7%) of total daily MVPA. In addition, MVPA on the journey did not differ between boys and girls, but because girls have lower levels of daily physical activity than boys, the journey contributed a greater proportion of their daily MVPA (35.6% vs 31.3%).

CONCLUSIONS

The journey to and from school is a significant contributor to MVPA in children aged 11-12 years. Combining GPS and accelerometer data within a GIS is a useful approach to quantifying specific journeys.

The inter- and intra-unit variability of a low-cost GPS data logger/receiver to study human outdoor walking in view of health and clinical studies

Purpose

The present study evaluates the intra- and inter-unit variability of the GlobalSat® DG100 GPS data logger/receiver (DG100) when estimating outdoor walking distances and speeds.

Methods

Two experiments were performed using healthy subjects walking on a 400 m outdoor synthetic track. The two experiments consisted of two different outdoor prescribed walking protocols with distances ranging from 50 to 400 m. Experiment 1 examined the intra-unit variability of the DG100 (test-retest reproducibility) when estimating walking distances. Experiment 2 examined the inter-unit variability of four DG100 devices (unit to unit variability) when estimating walking distances and speeds.

Results

The coefficient of variation [95% confidence interval], for the reliability of estimating walking distances, was 2.8 [2.5–3.2] %. The inter-unit variability among the four DG100 units tested ranged from 2.8 [2.5–3.2] % to 3.9 [3.5–4.4] % when estimating distances and from 2.7 [2.4–3.0] % to 3.8 [3.4–4.2] % when estimating speeds.

Conclusion

The present study indicates that the DG100, an economical and convenient GPS data logger/receiver, can be reliably used to study human outdoor walking activities in unobstructed conditions. This device let facilitate the use of GPS in studies of health and disease.

Automated time activity classification based on global positioning system (GPS) tracking data

BACKGROUND

Air pollution epidemiological studies are increasingly using global positioning system (GPS) to collect time-location data because they offer continuous tracking, high temporal resolution, and minimum reporting burden for participants. However, substantial uncertainties in the processing and classifying of raw GPS data create challenges for reliably characterizing time activity patterns. We developed and evaluated models to classify people's major time activity patterns from continuous GPS tracking data.

METHODS

We developed and evaluated two automated models to classify major time activity patterns (i.e., indoor, outdoor static, outdoor walking, and in-vehicle travel) based on GPS time activity data collected under free living conditions for 47 participants (N = 131 person-days) from the Harbor Communities Time Location Study (HCTLS) in 2008 and supplemental GPS data collected from three UC-Irvine research staff (N = 21 person-days) in 2010. Time activity patterns used for model development were manually classified by research staff using information from participant GPS recordings, activity logs, and follow-up interviews. We evaluated two models: (a) a rule-based model that developed user-defined rules based on time, speed, and spatial location, and (b) a random forest decision tree model.

RESULTS

Indoor, outdoor static, outdoor walking and in-vehicle travel activities accounted for 82.7%, 6.1%, 3.2% and 7.2% of manually-classified time activities in the HCTLS dataset, respectively. The rule-based model classified indoor and in-vehicle travel periods reasonably well (Indoor: sensitivity > 91%, specificity > 80%, and precision > 96%; in-vehicle travel: sensitivity > 71%, specificity > 99%, and precision > 88%), but the performance was moderate for outdoor static and outdoor walking predictions. No striking differences in performance were observed between the rule-based and the random forest models. The random forest model was fast and easy to execute, but was likely less robust than the rule-based model under the condition of biased or poor quality training data.

CONCLUSIONS

Our models can successfully identify indoor and in-vehicle travel points from the raw GPS data, but challenges remain in developing models to distinguish outdoor static points and walking. Accurate training data are essential in developing reliable models in classifying time-activity patterns.

How far do children travel from their homes? Exploring children's activity spaces in their neighborhood

This study explored children's activity spaces. In 2007, children aged 10-12 years (n=1480) completed a survey and mapping activity, and wore a pedometer for seven days. Their parents completed a survey (n=1314). Over half traveled <25% of their 'neighborhood', defined as 800 m and 1600 m network buffers. More local destinations (boys β=-0.022; girls β=-0.013) and parent report of living on a busy road (girls β=-0.43) were associated with smaller activity spaces whereas being independently mobile resulted in larger (girls β=0.28) ones. Traditionally defined neighborhoods may not reflect children's movements. Freedom, fewer local destinations and traffic safety may be important for increasing spatial ranges.

The accuracy of a simple, low-cost GPS data logger/receiver to study outdoor human walking in view of health and clinical studies

INTRODUCTION

Accurate and objective measurements of physical activity and lower-extremity function are important in health and disease monitoring, particularly given the current epidemic of chronic diseases and their related functional impairment.

PURPOSE

The aim of the present study was to determine the accuracy of a handy (lightweight, small, only one stop/start button) and low-cost (∼$75 with its external antenna) Global Positioning System (GPS) data logger/receiver (the DG100) as a tool to study outdoor human walking in perspective of health and clinical research studies. Methods. Healthy subjects performed two experiments that consisted of different prescribed outdoor walking protocols. Experiment 1. We studied the accuracy of the DG100 for detecting bouts of walking and resting. Experiment 2. We studied the accuracy of the DG100 for estimating distances and speeds of walking.

RESULTS

Experiment 1. The performance in the detection of bouts, expressed as the percentage of walking and resting bouts that were correctly detected, was 92.4% [95% Confidence Interval: 90.6-94.3]. Experiment 2. The coefficients of variation [95% Confidence Interval] for the accuracy of estimating the distances and speeds of walking were low: 3.1% [2.9-3.3] and 2.8% [2.6-3.1], respectively.

CONCLUSION

The DG100 produces acceptable accuracy both in detecting bouts of walking and resting and in estimating distances and speeds of walking during the detected walking bouts. However, before we can confirm that the DG100 can be used to study walking with respect to health and clinical studies, the inter- and intra-DG100 variability should be studied.

TRIAL REGISTRATION

ClinicalTrials.gov NCT00485147.

The reliability and validity of subjective notational analysis in comparison to global positioning system tracking to assess athlete movement patterns

Subjective notational analysis can be used to track players and analyse movement patterns during match-play of team sports such as futsal. The purpose of this study was to establish the validity and reliability of the Event Recorder for subjective notational analysis. A course was designed, replicating ten minutes of futsal match-play movement patterns, where ten participants undertook the course. The course allowed a comparison of data derived from subjective notational analysis, to the known distances of the course, and to GPS data. The study analysed six locomotor activity categories, focusing on total distance covered, total duration of activities and total frequency of activities. The values between the known measurements and the Event Recorder were similar, whereas the majority of significant differences were found between the Event Recorder and GPS values. The reliability of subjective notational analysis was established with all ten participants being analysed on two occasions, as well as analysing five random futsal players twice during match-play. Subjective notational analysis is a valid and reliable method of tracking player movements, and may be a preferred and more effective method than GPS, particularly for indoor sports such as futsal, and field sports where short distances and changes in direction are observed.

Using Geographic Information Systems (GIS) to assess the role of the built environment in influencing obesity: a glossary

Features of the built environment are increasingly being recognised as potentially important determinants of obesity. This has come about, in part, because of advances in methodological tools such as Geographic Information Systems (GIS). GIS has made the procurement of data related to the built environment easier and given researchers the flexibility to create a new generation of environmental exposure measures such as the travel time to the nearest supermarket or calculations of the amount of neighbourhood greenspace. Given the rapid advances in the availability of GIS data and the relative ease of use of GIS software, a glossary on the use of GIS to assess the built environment is timely. As a case study, we draw on aspects the food and physical activity environments as they might apply to obesity, to define key GIS terms related to data collection, concepts, and the measurement of environmental features.

Identifying walking trips from GPS and accelerometer data in adolescent females

BACKGROUND

Studies that have combined accelerometers and global positioning systems (GPS) to identify walking have done so in carefully controlled conditions. This study tested algorithms for identifying walking trips from accelerometer and GPS data in free-living conditions. The study also assessed the accuracy of the locations where walking occurred compared with what participants reported in a diary.

METHODS

A convenience sample of high school females was recruited (N = 42) in 2007. Participants wore a GPS unit and an accelerometer, and recorded their out-of-school travel for 6 days. Split-sample validation was used to examine agreement in the daily and total number of walking trips with Kappa statistics and count regression models, while agreement in locations visited by walking was examined with geographic information systems.

RESULTS

Agreement varied based on the parameters of the algorithm, with algorithms exhibiting moderate to substantial agreement with self-reported daily (Kappa = 0.33-0.48) and weekly (Kappa = 0.41-0.64) walking trips. Comparison of reported locations reached by walking and GPS data suggest that reported locations are accurate.

CONCLUSIONS

The use of GPS and accelerometers is promising for assessing the number of walking trips and the walking locations of adolescent females.

Performances of different global positioning system devices for time-location tracking in air pollution epidemiological studies

BACKGROUND

People's time-location patterns are important in air pollution exposure assessment because pollution levels may vary considerably by location. A growing number of studies are using global positioning systems (GPS) to track people's time-location patterns. Many portable GPS units that archive location are commercially available at a cost that makes their use feasible for epidemiological studies.

METHODS

We evaluated the performance of five portable GPS data loggers and two GPS cell phones by examining positional accuracy in typical locations (indoor, outdoor, in-vehicle) and factors that influence satellite reception (building material, building type), acquisition time (cold and warm start), battery life, and adequacy of memory for data storage. We examined stationary locations (eg, indoor, outdoor) and mobile environments (eg, walking, traveling by vehicle or bus) and compared GPS locations to highly-resolved US Geological Survey (USGS) and Digital Orthophoto Quarter Quadrangle (DOQQ) maps.

RESULTS

The battery life of our tested instruments ranged from <9 hours to 48 hours. The acquisition of location time after startup ranged from a few seconds to >20 minutes and varied significantly by building structure type and by cold or warm start. No GPS device was found to have consistently superior performance with regard to spatial accuracy and signal loss. At fixed outdoor locations, 65%-95% of GPS points fell within 20-m of the corresponding DOQQ locations for all the devices. At fixed indoor locations, 50%-80% of GPS points fell within 20-m of the corresponding DOQQ locations for all the devices except one. Most of the GPS devices performed well during commuting on a freeway, with >80% of points within 10-m of the DOQQ route, but the performance was significantly impacted by surrounding structures on surface streets in highly urbanized areas.

CONCLUSIONS

All the tested GPS devices had limitations, but we identified several devices which showed promising performance for tracking subjects' time location patterns in epidemiological studies.

Patterns of GPS measured time outdoors after school and objective physical activity in English children: the PEACH project

Background

Observational studies have shown a positive association between time outdoors and physical activity in children. Time outdoors may be a feasible intervention target to increase the physical activity of youth, but methods are required to accurately measure time spent outdoors in a range of locations and over a sustained period. The Global Positioning System (GPS) provides precise location data and can be used to identify when an individual is outdoors. The aim of this study was to investigate whether GPS data recorded outdoors were associated with objectively measured physical activity.

Methods

Participants were 1010 children (11.0 ± 0.4 years) recruited from 23 urban primary schools in South West England, measured between September 2006 and July 2008. Physical activity was measured by accelerometry (Actigraph GT1M) and children wore a GPS receiver (Garmin Foretrex 201) after school on four weekdays to record time outdoors. Accelerometer and GPS data were recorded at 10 second epochs and were combined to describe patterns of physical activity when both a GPS and accelerometer record were present (outdoors) and when there was accelerometer data only (indoors). ANOVA was used to investigate gender and seasonal differences in the patterns of outdoor and indoor physical activity, and linear regression was used to examine the cross-sectional associations between GPS-measured time outdoors and physical activity.

Results

GPS-measured time outdoors was a significant independent predictor of children's physical activity after adjustment for potential confounding factors. Physical activity was more than 2.5 fold higher outdoors than indoors (1345.8 ± 907.3 vs 508.9 ± 282.9 counts per minute; F = 783.2, p < .001). Overall, children recorded 41.7 ± 46.1 minutes outdoors between 3.30 pm and 8.30 pm, with more time spent outdoors in the summer months (p < .001). There was no gender difference in time spent outdoors. Physical activity outdoors was higher in the summer than the winter (p < .001), whilst there was no seasonal variation in physical activity indoors.

Conclusions

Duration of GPS recording is positively associated with objectively measured physical activity and is sensitive to seasonal differences. Minute by minute patterning of GPS and physical activity data is feasible and may be a useful tool to investigate environmental influences on children's physical activity and to identify opportunities for intervention.

Mapping the walk to school using accelerometry combined with a global positioning system

BACKGROUND

Walking to school is associated with higher levels of physical activity, but the contribution of the journey itself to physical activity before school is unknown.

PURPOSE

This study combined accelerometer and GPS data to investigate the level and location of physical activity in children walking to school.

METHODS

Participants were 137 children (aged 11.3 + or - 0.3 years) from London, England, measured in June-July 2006. Physical activity was measured by accelerometry, and location was determined with a GPS receiver. Travel mode was self-reported. Accelerometer and GPS data were time-matched to provide activity level and location for each 10-second epoch where both were available. Journeys were mapped in a GIS.

RESULTS

Mean accelerometer counts per minute before school (8:00 am to 9:00 am) were 43% higher in those who walked to school than those traveling by car (878.8 + or - 387.6 vs 608.7 + or - 264.1 counts per minute [cpm], p<0.001). Eleven percent (4.5 minutes) of daily moderate to vigorous physical activity (MVPA) occurred in this hour, with walkers recording 2.1 minutes more than car travelers (p = 0.004). Children followed direct routes between home and the school playground. Total activity during the walk to school was twice that in the playground (2131.3 + or - 1170.7 vs 1089.7 + or - 938.6 cpm, p<0.001), with the journey contributing three times as much MVPA as time in the playground.

CONCLUSIONS

Our results provide evidence that the journey to school is purposeful and contributes to higher total physical activity and MVPA in children. Combining accelerometer and GPS data may aid our understanding of the environmental context of physical activity.

Analyses of school commuting data for exposure modeling purposes

Human exposure models often make the simplifying assumption that school children attend school in the same census tract where they live. This paper analyzes that assumption and provides information on the temporal and spatial distributions associated with school commuting. The data were obtained using Oak Ridge National Laboratory's LandScan USA population distribution model applied to Philadelphia, PA. It is a high-resolution model used to allocate individual school-aged children to both a home and school location, and to devise a minimum-time home-to-school commuting path (called a trace) between the two locations. LandScan relies heavily on Geographic Information System (GIS) data. With respect to school children attending school in their home census tract, the vast majority does not in Philadelphia. Our analyses found that: (1) about 32% of the students walk across two or more census tracts going to school and 40% of them walk across four or more census blocks; and (2) 60% drive across four or more census tracts going to school and 50% drive across 10 or more census blocks. We also find that: (3) using a 5-min commuting time interval - as opposed to the modeled "trace" - results in misclassifying the "actual" path taken in 90% of the census blocks, 70% of the block groups, and 50% of the tracts; (4) a 1-min time interval is needed to reasonably resolve time spent in the various census unit designations; and (5) approximately 50% of both the homes and schools of Philadelphia school children are located within 160 m of highly traveled roads, and 64% of the schools are located within 200 m. These findings are very important when modeling school children's exposures, especially, when ascertaining the impacts of near-roadway concentrations on their total daily body burden. As many school children also travel along these streets and roadways to get to school, a majority of children in Philadelphia are in mobile source-dominated locations most of the day. We hypothesize that exposures of school children in Philadelphia to benzene and particulate matter will be much higher than if home and school locations and commuting paths at a 1-min time resolution are not explicitly modeled in an exposure assessment. Undertaking such an assessment will be the topic of a future paper.

Global positioning system: a new opportunity in physical activity measurement

Accurate measurement of physical activity is a pre-requisite to monitor population physical activity levels and design effective interventions. Global Positioning System (GPS) technology offers potential to improve the measurement of physical activity. This paper 1) reviews the extant literature on the application of GPS to monitor human movement, with a particular emphasis on free-living physical activity, 2) discusses issues associated with GPS use, and 3) provides recommendations for future research. Overall findings show that GPS is a useful tool to augment our understanding of physical activity by providing the context (location) of the activity and used together with Geographical Information Systems can provide some insight into how people interact with the environment. However, no studies have shown that GPS alone is a reliable and valid measure of physical activity.

Environmental supportiveness for physical activity in English schoolchildren: a study using Global Positioning Systems

Background

There is increasing evidence that the environment plays a role in influencing physical activity in children and adults. As children have less autonomy in their behavioural choices, neighbourhood environment supportiveness may be an important determinant of their ability to be active. Yet we know rather little about the types of environment that children use for bouts of physical activity. This study uses accelerometery and global positioning system technologies to identify the charactieristics of environments being used for bouts of continuous moderate to vigorous physical activity (MVPA) in a sample of English schoolchildren.

Methods

The study used a convenience sample of 100 children from SPEEDY (Sport, Physical activity and Eating behaviour: Environmental Determinants in Young people), a cohort of 2064 9–10 year-olds from Norfolk, England, recruited in 2007. Children wore an ActiGraph GT1M accelerometer and a Garmin Forerunner 205 GPS unit over four consecutive days. Accelerometery data points were matched to GPS locations and bouts (5 minutes or more) of MVPA were identified. Bout locations were overlaid with a detailed landcover dataset developed in a GIS to identify the types of environment supporting MVPA. Findings are presented using descriptive statistics.

Results

Boys were also more active than girls, spending an average of 20 (SD 23) versus 11 (SD 15) minutes per day in MVPA bouts. Children who spent more time outside the home were more active (p = 0.002), especially girls and children living in rural locations (both p < 0.05). Children tended to be active close to home, with 63% of all bout time occurring inside neighbourhoods, although boys (p = 0.05) and rural children (p = 0.01) were more likely to roam outside their neighbourhood. Amongst urban children, gardens (28% of bout time) and the street environment (20%) were the most commonly used environments for MVPA bouts. Amongst rural children farmland (22%) and grassland (18%) were most frequently used.

Conclusion

The study has developed a new methodology for the identification of environments in which bouts of continuous physical activity are undertaken. The results highlight the importance of the provision of urban gardens and greenspaces, and the maintenance of safe street environments as places for children to be active.

Air pollution and activity during transportation by car, subway, and walking

BACKGROUND

Little evidence exists about the health risks and benefits associated with using public buses and subways rather than cars. The objective of the current study was to assess the magnitude and variance of personal exposure to particulate matter 2.5 microns or smaller (PM(2.5)) and concomitant physical activity energy expenditure (PAEE) for transportation by car, subway, or walking.

METHODS

Twenty nonsmoking volunteers from New York City traveled on predetermined routes by car, subway, and walking, for up to 8 hours on 3 different days, between October 2007 and February 2008. Outfitted with a personal monitor with PM(2.5) aerosol inlet, and a GPS receiver, they completed a detailed physical activity diary for each route. Both metabolic equivalent (MET) and PAEE rates (Kcal/min) were computed from GPS-derived activity durations and speeds, activity-specific METs, and measured body weight.

RESULTS

Total PM(2.5) exposures did not differ among car, subway, and walking arms (respectively, 21.4, 30.6, and 26.5 microg/m(3) x min, p=0.19); but average MET values (respectively, 1.51, 2.03, and 2.60 Kcal/kg x hr, p<0.0001) and PAEE rates (1.74, 2.35, and 3.04 Kcal/min, p<0.0001) did. After correction for the humidity factor, exposure to PM(2.5) appeared to be lower for the car arm (13.1 microg/m(3) x min) than for the subway (19.6 microg/m(3) x min) or walking (23.9 microg/m(3) x min, p=0.004) arms.

CONCLUSIONS

Driving cars was associated with less physical activity but not necessarily less exposure to PM(2.5) than riding subways or walking in an urban environment. These effect sizes and variances can be used to design larger experiments assessing the health effects of urban transportation.

A criterion method for measuring route distance in physically active commuting

PURPOSE

There is a need for accurate, reliable, and feasible methods for determining route distances in physically active transportation. The aim of this study, therefore, was to scrutinize if distances of commuting routes drawn by physically active commuters and measured with a digital curvimetric distance measurement device could serve such a purpose.

METHODS

Participants were recruited when walking or bicycling in the inner urban area of Stockholm, Sweden. Questionnaires and individually adjusted maps were sent twice to the participants (n = 133). Commuting routes from home to work were drawn on the maps. These were measured using a digital curvimetric distance measurer that was carefully controlled for validity and reproducibility. Marked points of origin and destination were checked for validity and reproducibility using stated addresses and address geocoding systems. Nineteen participants were followed with a global positioning system (GPS) to control for validity of drawn routes. An analysis of the effect on distance measurements of any deviations between GPS route tracings and drawn routes was undertaken.

RESULTS

No order effects were noted on distance measurements, and the test-retest intraclass correlation coefficient was 0.999 (P <or= 0.001). The map markings of route origins and destinations were accurate and reproducible. GPS tracings of actual commuting routes taken (n = 19) as displayed in six cases had slight deviations from the routes drawn by the commuters on maps. However, these deviations played an insubstantial role (0.4%) for the distances measured.

CONCLUSION

When physically active commuters draw their commuting routes on maps, they create a valid and reproducible basis for route distance measurements. In combination with an accurate digital curvimetric distance-measuring device, a potential criterion method for measuring the commuting route distance is established.

Applying GPS to enhance understanding of transport-related physical activity

The purpose of the paper is to review the utility of the global positioning system (GPS) in the study of health-related physical activity. The paper draws from existing literature to outline the current work performed using GPS to examine transport-related physical activity, with a focus on the relative utility of the approach when combined with geographic information system (GIS) and other data sources including accelerometers. The paper argues that GPS, especially when used in combination with GIS and accelerometery, offers great promise in objectively measuring and studying the relationship of numerous environmental attributes to human behaviour in terms of physical activity and transport-related activity. Limitations to the use of GPS for the purpose of monitoring health-related physical activity are presented, and recommendations for future avenues of research are discussed.

Explaining Changes in Walking and Bicycling Behavior: Challenges for Transportation Research

As issues of traffic congestion, obesity, and environmental conservation receive increased attention globally and in the US, focus turns to the role that walking and cycling can play in mitigating such problems. This enthusiasm has created a need for evidence on the degree to which policies to increase walking and cycling travel have worked. This paper outlines the important challenges researchers face in their attempts to produce credible evidence on walking and cycling interventions. It closes by discussing matters to consider in such research endeavors, including the importance of clear conceptualization, sound research design, measurement innovations, and strategic sampling.