Development of methods to objectively identify time spent using active and motorised modes of travel to work: how do self-reported measures compare?

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.

Device-Measured and Self-Reported Active Travel Associations with Cardiovascular Disease Risk Factors in an Ethnically Diverse Sample of Adults

Active travel (AT) provides an opportunity to alleviate the physical inactivity and climate crises contributing to the global chronic disease burden, including cardiovascular diseases (CVD). Though AT shows promising links to reduced CVD risk, prior studies relied on self-reported AT assessment. In the present study, device-measured and self-reported AT were compared across population subgroups and relationships with CVD risk biomarkers were evaluated for both measures. The study recruited an ethnically diverse sample (N = 602, mean age 59 years, 42% Hispanic/Latino ethnicity) from neighborhoods that varied by walkability and food access. AT was assessed using concurrently collected accelerometer and GPS data and self-report data from a validated survey. Relationships with body mass index (BMI), triglycerides, high-density lipoprotein (HDL) cholesterol, blood pressure (BP), and moderate-to-vigorous physical activity (MVPA) were modeled using multivariable linear regression. Devices captured more AT than did self-report. We found differences in AT measures by population subgroups, including race, ethnicity, education, income, vehicle access, and walkability. Men had more accelerometer-measured MVPA, though women self-reported more daily minutes. Both device and survey AT measures were positively associated with total accelerometer-measured MVPA, though the relationship was stronger with device-measured AT. Device-measured AT was associated with lower BMI. No other CVD risk biomarker was associated with either AT measure. No effect modification by Hispanic/Latino ethnicity was detected. Further studies with device-based measures are warranted to better understand the relationship between AT and cardiovascular health.

Cycling but not walking to work or study is associated with physical fitness, body composition and clustered cardiometabolic risk in young men

Introduction

Active commuting is an inexpensive and accessible form of physical activity and may be beneficial to health. The aim of this study was to investigate the association of active commuting and its subcomponents, cycling and walking, with cardiometabolic risk factors, physical fitness and body composition in young men.

Methods

Participants were 776 Finnish young (26±7 years), healthy adult men. Active commuting was measured with self-report. Waist circumference was measured and body mass index (BMI) calculated. Aerobic fitness was measured with bicycle ergometer and muscular fitness with maximal leg and bench press, sit-ups, push-ups and standing long jump. Cardiometabolic risk factors were analysed from blood samples and selected variables (glucose, insulin, triglycerides, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, as well as systolic and diastolic blood pressure) were further converted to z-score to form clustered cardiometabolic risk.

Results

A total of 24% used active commuting consisting of 10% of walkers and 14% of cyclists. After adjustments for age, smoking, time of year, leisure-time and occupational physical activities, cycling was inversely associated with the clustered cardiometabolic risk (β=−0.11, 95% CI −0.22 to −0.01), while walking was not (β=−0.04, 95% CI −0.16 to 0.08). However, further adjustment for waist circumference attenuated the associations to non-significant. Moreover, cycling but not walking was inversely associated with BMI, waist circumference and maximal strength, while a positive association was observed with aerobic fitness (p<0.05).

Conclusion

This study shows that cycling to work or study has beneficial associations to clustered cardiometabolic risk, body composition and aerobic fitness in young, healthy adult men.

Merging self-reported with technically sensed data for tracking mobility behavior in a naturalistic intervention study. Insights from the GISMO study

Sound exposure data are central for any intervention study. In the case of utilitarian mobility, where studies cannot be conducted in controlled environments, exposure data are commonly self‐reported. For short‐term intervention studies, wearable devices with location sensors are increasingly employed. We aimed to combine self‐reported and technically sensed mobility data, in order to provide more accurate and reliable exposure data for GISMO, a long‐term intervention study. Through spatio‐temporal data matching procedures, we are able to determine the amount of mobility for all modes at the best possible accuracy level. Self‐reported data deviate ±10% from the corrected reference. Derived modal split statistics prove high compliance to the respective recommendations for the control group (CG) and the two intervention groups (IG‐PT, IG‐C). About 73.7% of total mileage was travelled by car in CG. This share was 10.3% (IG‐PT) and 9.7% (IG‐C), respectively, in the intervention groups. Commuting distances were comparable in CG and IG, but annual mean travel times differ between x¯  = 8,458 min (σ = 6,427 min) for IG‐PT, x¯  = 8,444 min (σ = 5,961 min) for IG‐C, and x¯  = 5,223 min (σ = 5,463 min) for CG. Seasonal variabilities of modal split statistics were observable. However, in IG‐PT and IG‐C no shift toward the car occurred during winter months. Although no perfect single‐method solution for acquiring exposure data in mobility‐related, naturalistic intervention studies exists, we achieved substantially improved results by combining two data sources, based on spatio‐temporal matching procedures.

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.

Active or Passive Commuter? Discrepancies in Cut-off Criteria among Adolescents

Active commuting to school has health implications for young people. Previous research has shown the need to consistently define the concept of “active commuter”, given that assessment as well as comparison between studies may be hindered by current discrepancies in frequency criteria. Using a sample of 158 Spanish students (12th–13th grade, 60.8% girls), the current study aimed to compare several cut-off criteria to rigorously identify the frequency of weekly active trips to school in order to categorize adolescents as active or passive commuters, and to analyze whether the threshold living distance to school is associated with the different trip cut-off criteria. Percentages of active commuters ranged from 75% to 88.6%, varying significantly depending on the cut-off criteria (5–10 active trips/week) used. The results also support the need to be stricter in the selection of a cut-off criterion when the distance to the school becomes shorter. Our findings highlight the importance of following a standard criterion to classify individuals as active or passive commuters, considering the characteristics of the context in which each study is conducted.

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.

Students’ Temporal Distributing of Learning Activities in Psychology Courses: Factors of Influence and Effects on the Metacognitive Learning Outcome

Studies demonstrate that students’ study behavior is frequently dysfunctional, because they tend to cram shortly before examinations. This behavior is antithetical to spaced learning and can impair academic achievement. We investigated the extent that the temporal distribution of learning activities (a) varies as a function of the organization of the course, (b) is subject to individual differences and (c) affects the metacognitive learning outcome. Participants of four lecture-like educational psychology courses ( N = 259) were presented with learning materials stored on the university’s online learning platform. New materials were published weekly and access to these materials was automatically registered. The students completed either a test at the end of the semester (in two end-term-test courses) or fulfilled written assignments throughout the semester (in two multiple-assignment courses) . Students in the multiple-assignment courses accessed the materials more continuously than students in the end-term-test courses. Cluster analyses in the end-term-test courses revealed students primarily accessing the materials late in the semester and students accessing the materials continuously throughout the semester. Continuous access was associated with more accurate metacognitive monitoring. The results are discussed in the context of the relation between metacognitive monitoring and the regulation of study behavior.

Development of the Impacts of Cycling Tool (ICT): A modelling study and web tool for evaluating health and environmental impacts of cycling uptake

BACKGROUND

A modal shift to cycling has the potential to reduce greenhouse gas emissions and provide health co-benefits. Methods, models, and tools are needed to estimate the potential for cycling uptake and communicate to policy makers the range of impacts this would have.

METHODS AND FINDINGS

The Impacts of Cycling Tool (ICT) is an open source model with a web interface for visualising travel patterns and comparing the impacts of different scenarios of cycling uptake. It is currently applied to England. The ICT allows users to visualise individual and trip-level data from the English National Travel Survey (NTS), 2004-2014 sample, 132,000 adults. It models scenarios in which there is an increase in the proportion of the population who cycle regularly, using a distance-based propensity approach to model which trips would be cycled. From this, the model estimates likely impact on travel patterns, health, and greenhouse gas emissions. Estimates of nonoccupational physical activity are generated by fusing the NTS with the English Active People Survey (APS, 2013-2014, 559,515 adults) to create a synthetic population. Under 'equity' scenarios, we investigate what would happen if cycling levels increased equally among all age and gender categories, as opposed to in proportion to the profile of current cyclists. Under electric assist bike (pedelecs or 'e-bike') scenarios, the probability of cycling longer trips increases, based on the e-bike data from the Netherlands, 2013-2014 Dutch Travel Survey (50,868 adults).Outcomes are presented across domains including transport (trip duration and trips by mode), health (physical activity levels, years of life lost), and car transport-related CO2 emissions. Results can be visualised for the whole population and various subpopulations (region, age, gender, and ethnicity). The tool is available at www.pct.bike/ict. If the proportion of the English population who cycle regularly increased from 4.8% to 25%, then there would be notable reductions in car miles and passenger related CO2 emissions (2.2%) and health benefits (2.1% reduction in years of life lost due to premature mortality). If the new cyclists had access to e-bikes, then mortality reductions would be similar, while the reduction in car miles and CO2 emissions would be larger (2.7%). If take-up of cycling occurred equally by gender and age (under 80 years), then health benefits would be marginally greater (2.2%) but reduction in CO2 slightly smaller (1.8%). The study is limited by the quality and comparability of the input data (including reliance on self-report behaviours). As with all modelling studies, many assumptions are required and potentially important pathways excluded (e.g. injury, air pollution, and noise pollution).

CONCLUSION

This study demonstrates a generalisable approach for using travel survey data to model scenarios of cycling uptake that can be applied to a wide range of settings. The use of individual-level data allows investigation of a wide range of outcomes, and variation across subgroups. Future work should investigate the sensitivity of results to assumptions and omissions, and if this varies across setting.

Does exposure to new transport infrastructure result in modal shifts? Patterns of change in commute mode choices in a four-year quasi-experimental cohort study

BACKGROUND

Intervention studies suggest that changing the built environment may encourage a modal shift from car travel towards active travel. However, little is known about the detail of patterns of changes in travel behaviour.

METHOD

Adult commuters working in Cambridge (UK) completed annual questionnaires between 2009 and 2012. Commuting was assessed using a validated seven-day travel-to-work record. The intervention consisted of the opening of a guided busway with a path for walking and cycling in 2011. Exposure to the intervention was defined as the negative of the square root of the shortest road distance from home to the busway. We investigated the association between exposure to the intervention and specific modal shifts and patterns of change, along with individual mode choice patterns over the entire four-year period.

RESULTS

Five groups of patterns of change were found in our in-depth explorations: (1) no change, (2) a full modal shift, (3) a partial modal shift, (4) non-stable but patterned behaviour, and (5) complicated or apparently random patterns. A minority of participants had a directed change of either a full modal shift or, more commonly, a partial modal shift, whereas a large proportion showed a highly variable pattern. No significant associations were found between exposure to the intervention and specific modal shifts or patterns of change.

CONCLUSION

Our analyses revealed a large diversity in (changes in) travel behaviour patterns over time, and showed that the intervention did not result in one specific pattern of behaviour change or produce only full modal shifts. These insights are important for improving the measurement of travel behaviour, improving our understanding of how changes in travel behaviour patterns occur, and fully capturing the potential impacts of interventions.

Is Active Commuting to Work Related to Work Performance Among Male Office Workers?

OBJECTIVE

This study aimed to elucidate the association between active commuting to work (ACW) and work performance among male office workers.

METHODS

This cross-sectional study included 331 male office workers (age 44.0 ± 11.5 years), with ACW assessed on a self-reported questionnaire and then categorized into non-ACW (0 to 19 minutes) and ACW (≥20 minutes). Work performance [World Health Organization Health and Work Performance Questionnaire (HPQ)] was categorized as high (≥50) and low (<50). Multiple logistic regression models were used to examine the association between ACW and HPQ.

RESULTS

We found that 42.2% respondents adopted ACW. After adjusting for demographic data, lifestyle factors, and depressive symptoms, ACW was significantly associated with high HPQ (odds ratio: 2.43; 95% confidence interval: 1.30 to 4.54).

CONCLUSIONS

In male office workers, ACW was independently associated with higher work performance.

The effectiveness of the use of a digital activity coaching system in addition to a two-week home-based exercise program in patients after total knee arthroplasty: study protocol for a randomized controlled trial

BACKGROUND

There is consistent evidence that supervised programs are not superior to home-based programs after total knee arthroplasty (TKA), especially in patients without complications. Home-based exercise programs are effective, but we hypothesize that their effectiveness can be improved by increasing the adherence to physical therapy advice to reach an adequate exercise level during the program and thereafter. Our hypothesis is that an activity coaching system (accelerometer-based activity sensor), alongside a home-based exercise program, will increase adherence to exercises and the activity level, thereby improving physical functioning and recovery. The objective of this study is to determine the effectiveness of an activity coaching system in addition to a home-based exercise program after a TKA compared to only the home-based exercise program with physical functioning as outcome.

METHODS

This study is a single-blind randomized controlled trial. Both the intervention (n = 55) and the control group (n = 55) receive a two-week home-based exercise program, and the intervention group receives an additional activity coaching system. This is a hand-held electronic device together with an app on a smartphone providing information and advice on exercise behavior during the day. The primary outcome is physical functioning, measured with the Timed Up and Go test (TUG) after two weeks, six weeks and three months. Secondary outcomes are 1) adherence to the activity level (activity diary); 2) physical functioning, measured with the 2-Minute Walk Test (2MWT) and the Knee Osteoarthritis Outcome Score; 3) quality of life (SF-36); 4) healthcare use up to one year postoperatively and 5) cost-effectiveness. Data are collected preoperatively, three days, two and six weeks, three months and one year postoperatively.

DISCUSSION

The strengths of the study are the use of both performance-based tests and self-reported questionnaires and the personalized tailored program after TKA given by specialized physical therapists. Its weakness is the lack of blinding of the participants to treatment allocation. Outcomes are generalizable to uncomplicated patients as defined in the inclusion criteria.

TRIAL REGISTRATION

The trial is registered in the Dutch Trial Register ( www.trialregister.nl , NTR 5109) (March 22, 2015).

Active Commuting: Workplace Health Promotion for Improved Employee Well-Being and Organizational Behavior

Objective: This paper describes a behavior change intervention that encourages active commuting using electrically assisted bikes (e-bikes) for health promotion in the workplace. This paper presents the preliminary findings of the intervention’s impact on improving employee well-being and organizational behavior, as an indicator of potential business success.

Method: Employees of a UK-based organization participated in a workplace travel behavior change intervention and used e-bikes as an active commuting mode; this was a change to their usual passive commuting behavior. The purpose of the intervention was to develop employee well-being and organizational behavior for improved business success. We explored the personal benefits and organizational co-benefits of active commuting and compared these to a travel-as-usual group of employees who did not change their behavior and continued taking non-active commutes.

Results: Employees who changed their behavior to active commuting reported more positive affect, better physical health and more productive organizational behavior outcomes compared with passive commuters. In addition, there was an interactive effect of commuting mode and commuting distance: a more frequent active commute was positively associated with more productive organizational behavior and stronger overall positive employee well-being whereas a longer passive commute was associated with poorer well-being, although there was no impact on organizational behavior.

Conclusion: This research provides emerging evidence of the value of an innovative workplace health promotion initiative focused on active commuting in protecting and improving employee well-being and organizational behavior for stronger business performance. It considers the significant opportunities for organizations pursuing improved workforce well-being, both in terms of employee health, and for improved organizational behavior and business success.

Pneumonia Hospitalization Risk in the Elderly Attributable to Cold and Hot Temperatures in Hong Kong, China

The growth of pathogens potentially relevant to respiratory tract infection may be triggered by changes in ambient temperature. Few studies have examined the association between ambient temperature and pneumonia incidence, and no studies have focused on the susceptible elderly population. We aimed to examine the short-term association between ambient temperature and geriatric pneumonia and to assess the disease burden attributable to cold and hot temperatures in Hong Kong, China. Daily time-series data on emergency hospital admissions for geriatric pneumonia, mean temperature, relative humidity, and air pollution concentrations between January 2005 and December 2012 were collected. Distributed-lag nonlinear modeling integrated in quasi-Poisson regression was used to examine the exposure-lag-response relationship between temperature and pneumonia hospitalization. Measures of the risk attributable to nonoptimal temperature were calculated to summarize the disease burden. Subgroup analyses were conducted to examine the sex difference. We observed significant nonlinear and delayed associations of both cold and hot temperatures with pneumonia in the elderly, with cold temperatures having stronger effect estimates. Among the 10.7% of temperature-related pneumonia hospitalizations, 8.7% and 2.0% were attributed to cold and hot temperatures, respectively. Most of the temperature-related burden for pneumonia hospitalizations in Hong Kong was attributable to cold temperatures, and elderly men had greater susceptibility.

Longitudinal associations of active commuting with body mass index

OBJECTIVE

To investigate the longitudinal associations between active commuting (walking and cycling to work) and body mass index (BMI).

METHOD

We used self-reported data on height, weight and active commuting from the Commuting and Health in Cambridge study (2009 to 2012; n=809). We used linear regression to test the associations between: a) maintenance of active commuting over one year and BMI at the end of that year; and b) change in weekly time spent in active commuting and change in BMI over one year.

RESULTS

After adjusting for sociodemographic variables, other physical activity, physical wellbeing and maintenance of walking, those who maintained cycle commuting reported a lower BMI on average at one year follow-up (1.14kg/m(2), 95% CI: 0.30 to 1.98, n=579) than those who never cycled to work. No significant association remained after adjustment for baseline BMI. No significant associations were observed for maintenance of walking. An increase in walking was associated with a reduction in BMI (0.32kg/m(2), 95% CI: 0.03 to 0.62, n=651, after adjustment for co-variates and baseline BMI) only when restricting the analysis to those who did not move. No other significant associations between changes in weekly time spent walking or cycling on the commute and changes in BMI were observed.

CONCLUSIONS

This work provides further evidence of the contribution of active commuting, particularly cycling, to preventing weight gain or facilitating weight loss. The findings may be valuable for employees choosing how to commute and engaging employers in the promotion of active travel.

Causal pathways linking environmental change with health behaviour change: Natural experimental study of new transport infrastructure and cycling to work

BACKGROUND

Mechanisms linking changes to the environment with changes in physical activity are poorly understood. Insights into mechanisms of interventions can help strengthen causal attribution and improve understanding of divergent response patterns. We examined the causal pathways linking exposure to new transport infrastructure with changes in cycling to work.

METHODS

We used baseline (2009) and follow-up (2012) data (N=469) from the Commuting and Health in Cambridge natural experimental study (Cambridge, UK). Exposure to new infrastructure in the form of the Cambridgeshire Guided Busway was defined using residential proximity. Mediators studied were changes in perceptions of the route to work, theory of planned behaviour constructs and self-reported use of the new infrastructure. Outcomes were modelled as an increase, decrease or no change in weekly cycle commuting time. We used regression analyses to identify combinations of mediators forming potential pathways between exposure and outcome. We then tested these pathways in a path model and stratified analyses by baseline level of active commuting.

RESULTS

We identified changes in perceptions of the route to work, and use of the cycle path, as potential mediators. Of these potential mediators, only use of the path significantly explained (85%) the effect of the infrastructure in increasing cycling. Path use also explained a decrease in cycling among more active commuters.

CONCLUSION

The findings strengthen the causal argument that changing the environment led to changes in health-related behaviour via use of the new infrastructure, but also show how some commuters may have spent less time cycling as a result.

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.

Longitudinal associations of active commuting with wellbeing and sickness absence

OBJECTIVE

Our aim was to explore longitudinal associations of active commuting (cycling to work and walking to work) with physical wellbeing (PCS-8), mental wellbeing (MCS-8) and sickness absence.

METHOD

We used data from the Commuting and Health in Cambridge study (2009 to 2012; n=801) to test associations between: a) maintenance of cycling (or walking) to work over a one year period and indices of wellbeing at the end of that one year period; and b) associations between change in cycling (or walking) to work and change in indices of wellbeing. Linear regression was used for testing associations with PCS-8 and MCS-8, and negative binomial regression for sickness absence.

RESULTS

After adjusting for sociodemographic variables, physical activity and physical limitation, those who maintained cycle commuting reported lower sickness absence (0.46, 95% CI: 0.14-0.80; equivalent to one less day per year) and higher MCS-8 scores (1.50, 0.10-2.10) than those who did not cycle to work. The association for sickness absence persisted after adjustment for baseline sickness absence. No significant associations were observed for PCS-8. Associations between change in cycle commuting and change in indices of wellbeing were not significant. No significant associations were observed for walking.

CONCLUSIONS

This work provides some evidence of the value of cycle commuting in improving or maintaining the health and wellbeing of adults of working age. This may be important in engaging employers in the promotion of active travel and communicating the benefits of active travel to employees.

Impact of New Transport Infrastructure on Walking, Cycling, and Physical Activity

INTRODUCTION

Walking and cycling bring health and environmental benefits, but there is little robust evidence that changing the built environment promotes these activities in populations. This study evaluated the effects of new transport infrastructure on active commuting and physical activity.

STUDY DESIGN

Quasi-experimental analysis nested within a cohort study.

SETTING/PARTICIPANTS

Four hundred and sixty-nine adult commuters, recruited through a predominantly workplace-based strategy, who lived within 30 kilometers of Cambridge, United Kingdom and worked in areas of the city to be served by the new transport infrastructure.

INTERVENTION

The Cambridgeshire Guided Busway opened in 2011 and comprised a new bus network and a traffic-free walking and cycling route. Exposure to the intervention was defined using the shortest distance from each participant's home to the busway.

MAIN OUTCOME MEASURES

Change in weekly time spent in active commuting between 2009 and 2012, measured by validated 7-day recall instrument. Secondary outcomes were changes in total weekly time spent walking and cycling and in recreational and overall physical activity, measured using the validated Recent Physical Activity Questionnaire. Data were analyzed in 2014.

RESULTS

In multivariable multinomial regression models--adjusted for potential sociodemographic, geographic, health, and workplace confounders; baseline active commuting; and home or work relocation-exposure to the busway was associated with a significantly greater likelihood of an increase in weekly cycle commuting time (relative risk ratio=1.34, 95% CI=1.03, 1.76) and with an increase in overall time spent in active commuting among the least active commuters at baseline (relative risk ratio=1.76, 95% CI=1.16, 2.67). The study found no evidence of changes in recreational or overall physical activity.

CONCLUSIONS

Providing new sustainable transport infrastructure was effective in promoting an increase in active commuting. These findings provide new evidence to support reconfiguring transport systems as part of public health improvement strategies.

Health impacts of the Cambridgeshire Guided Busway: a natural experimental study

Background

Improving transport infrastructure to support walking and cycling on the journey to and from work – active commuting – could help to promote physical activity and improve population health.

Aims

To assess whether or not investment in new high-quality transport infrastructure was associated with an increase in active commuting; wider health impacts of changes in travel behaviour; determinants of the use and uptake of active commuting; and how changes in travel behaviour were distributed in the population and related to the wider social context.

Design

The Commuting and Health in Cambridge study, comprising a quasi-experimental cohort study combined with both nested and supplementary in-depth quantitative and qualitative studies.

Setting

Cambridgeshire, UK.

Participants

A cohort of 1143 adults living within 30 km of Cambridge, working in the city and recruited in 2009; and a separate sample of 1710 users intercepted on the Cambridgeshire Guided Busway in 2012.

Intervention

The Cambridgeshire Guided Busway, comprising a new bus network using 22 km of guideway (segregated bus track) accompanied by a traffic-free path for pedestrians and cyclists, opened in 2011.

Main outcome measure

Change in time spent in active commuting from 2009 to 2012, using a self-reported measure validated using georeferenced combined heart rate and movement sensor data.

Methods

A delay from 2009 to 2011 in completing the intervention entailed some changes to the original design and attrition of the cohort. A period of methodological and observational research on active commuting preceded the evaluation, which was based on a quasi-experimental cohort analysis together with the intercept and qualitative data. A graded measure of each participant’s exposure to the intervention, based on the proximity of the busway to his or her home, served as the basis for controlled comparisons.

Results

Commuting practices were complex and shaped by various changeable social and environmental factors. Walking and cycling were often incorporated into longer commuting journeys made predominantly by car or public transport. In multivariable multinomial regression analyses, exposure to the intervention was associated with a greater likelihood of a large increase in the proportion of commuting trips involving any active travel [adjusted relative risk ratio (RRR) 1.80, 95% confidence interval (CI) 1.27 to 2.55], of a large decrease in the proportion of trips made entirely by car (RRR 2.09, 95% CI 1.35 to 3.21), and of an increase in weekly cycle commuting time (RRR 1.34, 95% CI 1.03 to 1.76). There was a mixed pattern of effects at the individual level, with the intervention providing a more supportive environment for active commuting for some and not for others. There was some evidence that the effect was most pronounced among those who reported no active commuting at baseline, and observational evidence suggesting a relationship between active commuting, greater overall physical activity, and improved well-being and weight status.

Conclusions

These findings provide new empirical support and direction for reconfiguring transport systems to improve population health and reduce health inequalities. They should be combined with evidence from research evaluating related environmental changes in other settings, preferably using longer periods of observation and controlled comparisons, to support more generalisable causal inference.

Funding

The National Institute for Health Research Public Health Research programme.

Changes in active commuting and changes in physical activity in adults: a cohort study

Background

Active travel is associated with greater physical activity, but there is a dearth of research examining this relationship over time. We examined the longitudinal associations between change in time spent in active commuting and changes in recreational and total physical activity.

Methods

Adult commuters working in Cambridge, United Kingdom completed questionnaires in 2009 and 2012, and a sub-set completed objective physical activity monitoring in 2010 and 2012. Commuting was assessed using a validated seven-day travel to work record. Moderate-to-vigorous physical activity was assessed using the Recent Physical Activity Questionnaire and combined heart rate and movement sensing. We used multivariable multinomial logistic regression models to examine associations between change in time spent in active commuting and tertiles of changes in time spent in recreational and total physical activity.

Results

Four hundred sixty-nine participants (67 % female, mean age 44 years) provided valid travel and self-reported physical activity data. Seventy-one participants (54 % female, mean age 45 years) provided valid travel and objectively measured physical activity data. A decrease in active commuting was associated with a greater likelihood of a decrease in self-reported total physical activity (relative risk ratio [RRR] 2.1, 95 % CI 1.1, 4.1). Correspondingly, an increase in active commuting was associated with a borderline significantly greater likelihood of an increase in self-reported total physical activity (RRR 1.8, 95 % CI 1.0, 3.4). No associations were seen between change in time spent in active commuting and change in time spent in either self-reported recreational physical activity or objectively measured physical activity.

Conclusions

Changes in active commuting were associated with commensurate changes in total self-reported physical activity and we found no compensatory changes in self-reported recreational physical activity. Promoting active commuting has potential as a public health strategy to increase physical activity. Future longitudinal research would be useful to verify these findings.

Electronic supplementary material

The online version of this article (doi:10.1186/s12966-015-0323-0) contains supplementary material, which is available to authorized users.

Quantifying the physical activity energy expenditure of commuters using a combination of global positioning system and combined heart rate and movement sensors

BACKGROUND

Active commuting may help to increase adults' physical activity levels. However, estimates of its energy cost are derived from a small number of studies which are laboratory-based or use self-reported measures.

METHODS

Adults working in Cambridge (UK) recruited through a predominantly workplace-based strategy wore combined heart rate and movement sensors and global positioning system (GPS) devices for one week, and completed synchronous day-by-day travel diaries in 2010 and 2011. Commuting journeys were delineated using GPS data, and metabolic intensity (standard metabolic equivalents; MET) was derived and compared between journey types using mixed-effects linear regression.

RESULTS

182 commuting journeys were included in the analysis. Median intensity was 1.28 MET for car journeys; 1.67 MET for bus journeys; 4.61 MET for walking journeys; 6.44 MET for cycling journeys; 1.78 MET for journeys made by car in combination with walking; and 2.21 MET for journeys made by car in combination with cycling. The value for journeys made solely by car was significantly lower than those for all other journey types (p<0.04). On average, 20% of the duration of journeys incorporating any active travel (equating to 8 min) was spent in moderate-to-vigorous physical activity (MVPA).

CONCLUSIONS

We have demonstrated how GPS and activity data from a free-living sample can be used simultaneously to provide objective estimates of commuting energy expenditure. On average, incorporating walking or cycling into longer journeys provided over half the weekly recommended activity levels from the commute alone. This may be an efficient way of achieving physical activity guidelines and improving population health.

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.

Are income-related differences in active travel associated with physical environmental characteristics? A multi-level ecological approach

Background

Rates of active travel vary by socio-economic position, with higher rates generally observed among less affluent populations. Aspects of both social and built environments have been shown to affect active travel, but little research has explored the influence of physical environmental characteristics, and less has examined whether physical environment affects socio-economic inequality in active travel. This study explored income-related differences in active travel in relation to multiple physical environmental characteristics including air pollution, climate and levels of green space, in urban areas across England. We hypothesised that any gradient in the relationship between income and active travel would be least pronounced in the least physically environmentally-deprived areas where higher income populations may be more likely to choose active transport as a means of travel.

Methods

Adults aged 16+ living in urban areas (n = 20,146) were selected from the 2002 and 2003 waves of the UK National Travel Survey. The mode of all short non-recreational trips undertaken by the sample was identified (n = 205,673). Three-level binary logistic regression models were used to explore how associations between the trip being active (by bike/walking) and three income groups, varied by level of multiple physical environmental deprivation.

Results

Likelihood of making an active trip among the lowest income group appeared unaffected by physical environmental deprivation; 15.4% of their non-recreational trips were active in both the least and most environmentally-deprived areas. The income-related gradient in making active trips remained steep in the least environmentally-deprived areas because those in the highest income groups were markedly less likely to choose active travel when physical environment was ‘good’, compared to those on the lowest incomes (OR = 0.44, 95% CI = 0.22 to 0.89).

Conclusions

The socio-economic gradient in active travel seems independent of physical environmental characteristics. Whilst more affluent populations enjoy advantages on some health outcomes, they will still benefit from increasing their levels of physical activity through active travel. Benefits of active travel to the whole community would include reduced vehicle emissions, reduced carbon consumption, the preservation or enhancement of infrastructure and the presentation of a ‘normalised’ behaviour.

Generating GPS activity spaces that shed light upon the mobility habits of older adults: a descriptive analysis

Background

Measuring mobility is critical for understanding neighborhood influences on older adults’ health and functioning. Global Positioning Systems (GPS) may represent an important opportunity to measure, describe, and compare mobility patterns in older adults.

Methods

We generated three types of activity spaces (Standard Deviation Ellipse, Minimum Convex Polygon, Daily Path Area) using GPS data from 95 older adults in Vancouver, Canada. Calculated activity space areas and compactness were compared across sociodemographic and resource characteristics.

Results

Area measures derived from the three different approaches to developing activity spaces were highly correlated. Participants who were younger, lived in less walkable neighborhoods, had a valid driver’s license, had access to a vehicle, or had physical support to go outside of their homes had larger activity spaces. Mobility space compactness measures also differed by sociodemographic and resource characteristics.

Conclusions

This research extends the literature by demonstrating that GPS tracking can be used as a valuable tool to better understand the geographic mobility patterns of older adults. This study informs potential ways to maintain older adult independence by identifying factors that influence geographic mobility.

Electronic supplementary material

The online version of this article (doi:10.1186/1476-072X-13-51) contains supplementary material, which is available to authorized users.