Active transportation and public transportation use to achieve physical activity recommendations? A combined GPS, accelerometer, and mobility survey study

Is public transport a promising strategy for increasing physical activity? Evidence from a study of objectively measured public transport use and physical activity

BACKGROUND

Greater public transport use has been linked to higher physical activity levels. However, neither the amount of physical activity associated with each daily public transport trip performed, nor the potential total physical activity gain associated with an increase in trips/day, has been determined. Using objective measures, we aimed to quantify the association between public transport use, physical activity and sedentary time.

METHODS

A longitudinal study of Australian adults living in Hobart, Tasmania, who were infrequent bus users (≥ 18 years; used bus ≤ 2 times/week). The number of bus trips performed each day was determined from objective smartcard data provided by the public transportation (bus) provider across a 36-week study timeframe. Accelerometer measured steps/day (primary outcome), moderate-to-vigorous physical activity (min/day), and sedentary time (min/day) were assessed across four separate one-week periods.

RESULTS

Among 73 participants across 1483 day-level observations, on days that public transport was used, participants achieved significantly more steps (β = 2147.48; 95%CI = 1465.94, 2829.03), moderate to vigorous physical activity (β = 22.79; 95% CI = 14.33, 31.26), and sedentary time (β = 37.00; 95% CI = 19.80, 54.21) compared to days where no public transport trips were made. The largest increase in steps per day associated with a one-trip increase was observed when the number of trips performed each day increased from zero to one (β = 1761.63; 95%CI = 821.38, 2701.87). The increase in the number of steps per day was smaller and non-significant when the number of trips performed increased from one to two (β = 596.93; 95%CI=-585.16, 1779.01), and two to three or more (β = 632.39; 95%CI=-1331.45, 2596.24) trips per day. Significant increases in sedentary time were observed when the number of trips performed increased from zero to one (β = 39.38; 95%CI = 14.38, 64.39) and one to two (β = 48.76; 95%CI = 25.39, 72.12); but not when bus trips increased from two to three or more (β=-27.81; 95%CI=-76.00, 20.37).

CONCLUSIONS

Greater public transport use was associated with higher physical activity and sedentary behaviour. Bus use may yield cumulative increases in steps that amount to 15-30% of the daily recommended physical activity target. A policy and public health focus on intersectoral action to promote public transport may yield meaningful increases in physical activity and subsequent health benefits.

Neighborhood Public Transportation Access and Adolescent Body Mass Index: Results from the FLASHE Study

Background: Prior investigators have examined the relationship between neighborhood public transportation access and physical activity among adolescents, but research is lacking on the association with obesity in this age group. This study examines the association between neighborhood public transportation access and adolescent BMI using a national sample. Methods: We used cross-sectional data from the Family Life, Activity, Sun, Health, and Eating study, a national survey (2014) that assessed physical activity and diet, among adolescents (aged 12-17 years, N = 1737) and their parents. We ran crude and adjusted linear regression models to test the association between neighborhood-level public transportation access (less prevalent and prevalent) and individual participant-level BMI z-scores. Results: The analytic sample included 336 adolescents (50% female; 69% had healthy weight; 28% had overweight or obesity). Adjusted models showed a positive relationship between high public transportation access and adolescent z-BMI (b = 0.25, confidence interval [95% CI]: -0.01 to 0.50). In stratified analyses, high public transportation access was associated with higher z-BMI for high school students (b = 0.57, 95% CI: 0.23-0.91), males (b = 0.48, 95% CI: 0.09-0.87), and adolescents in households with an income below $99,999 (0.29, 95% CI: 0.02-0.56). Conclusion: Neighborhood public transportation access is associated with adolescent BMI, but the direction of this association varies across urban adolescent demographic subgroups. Further research is needed to clarify the relationships between individual and social-environmental factors that impact public transportation access and its association with adolescent BMI.

[Motivation for physical exercise: the benefits of active transport in the fight against sedentary lifestyles]

Our contemporary lifestyles offer little incentive to be physically active, and give us far fewer opportunities to be active than in the past, with many of our tasks being sedentary and most of our transport being motorized. While it's easy to acknowledge a lack of physical activity, putting it into practice is eminently more complex, and many researchers are trying to answer the thorny question: how can we enable people to be more physically active in their daily lives? With this in mind, the aim of this article is to show that active transport is an effective way of getting sedentary people to engage in regular physical activity.

Effects of public transportation use on non-exercise activity thermogenesis and health promotion: a mini-review

PURPOSE

Public transportation (PT) systems significantly shape urban mobility and have garnered attention owing to their potential impact on public health, particularly the promotion of physical activity. Beyond their transportation functions, PT systems also affect daily energy expenditure through non-exercise activity thermogenesis (NEAT). This mini-review surveys the existing literature to explore the effects of PT use on NEAT levels and subsequent health outcomes.

METHODS

A comprehensive literature search was conducted using the electronic databases PubMed, Google Scholar, and Web of Science. Keywords including "public transportation," "non-exercise activity thermogenesis," "physical activity," "health promotion," and related terms were used to identify relevant studies.

RESULTS

This review highlights the multifaceted relationship between PT use and health promotion, emphasizing the potential benefits and challenges of increasing NEAT through public transit utilization. Overall, the findings suggest that PT use contributes positively to NEAT levels, and thus improves health outcomes. However, the extent of this impact may vary depending on individual and contextual factors.

CONCLUSION

Interventions promoting active transportation modes, including public transit, hold promise for addressing sedentary behavior and fostering healthier lifestyles at the population level.

Does cycle commuting reduce the risk of mental ill-health? An instrumental variable analysis using distance to nearest cycle path

BACKGROUND

Previous studies have linked cycling with improved mental wellbeing but these studies tend to use cross-sectional survey data that have small sample sizes and self-reported health measures, and are potentially susceptible to omitted-variable bias and reverse causation. We use an instrumental variable approach and an objective measure of mental ill-health taken from linked administrative data to ask: 'Does cycle commuting reduce the risk of mental ill-health?'

METHODS

Our study links data on commuting in Edinburgh and Glasgow from the Scottish population census with mental health prescriptions from the National Health Service Prescribing Information System records. We use road distance from home to nearest cycle path as an instrumental variable for cycle commuting.

RESULTS

In total, 378 253 people aged 16-74 years living and working in the City of Edinburgh and Glasgow City council areas at the 2011 census were included in our study; 1.85% of commuters in Glasgow and 4.8% of commuters in Edinburgh cycled to work. Amongst cyclists, 9% had a prescription for mental health compared with 14% amongst non-cyclists. Using a bivariate probit model, we estimate a mean average reduction in prescriptions for antidepressants and/or anxiolytics in the 5 years following the census of -15.1% (95% CI: -15.3% to -15.0%) amongst cycle commuters compared with those who use any other mode to commute.

CONCLUSIONS

This work suggests that cycle commuting is causally related to reduced mental ill-health and provides further evidence in support of the promotion of active travel to encourage commuters travelling shorter distances to shift to cycle commutes.

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.

Different sedentary behavior domains present distinct associations with eating-related indicators

BACKGROUND

Unhealthful dietary patterns have been consistently associated with low levels of physical activity (PA), but studies dedicated to sedentary behavior (SB) are scarce, especially in adults. The few studies that investigated the association between SB and dietary patterns focused mostly on specific types of SB, such as TV-watching or screen time. SB can be accumulated in distinct domains (i.e., work, transport, and leisure-time), thus, it is key to investigate in depth the impact that different domains of SB can have on eating-related indicators. We aimed to investigate the associations between different SB domains and eating-related indicators, in a sample of adults.

METHODS

Cross-sectional data from students, teachers, and staff from a Portuguese University was collected in November/2021 through an anonymous online survey. Data analyses were performed using the IBM SPSS software (version 28.0) and included descriptive statistics, partial correlations, and group comparisons using one-way ANOVA. Daily average SB at work/study, transport, and in leisure-time were self-reported and eating-related indicators were measured with several items from the Mediterranean Diet Score. Specific eating-related behaviors reflecting a protective eating pattern (e.g., eating breakfast regularly), and eating behavior traits (e.g., external eating) were also assessed. Body mass index (BMI) was calculated as weight (kg)/height(m)2. The International Physical Activity Questionnaire/Short-Form was used to assess PA.

RESULTS

The sample included 301 adults (60.1% women), with a mean age of 34.5 years. Overall, leisure-time SB was inversely associated with adherence to the Mediterranean diet (r = -0.20; p < 0.001) and with a protective eating profile (r = -0.31; p < 0.001). Higher transport SB was also related to lower adherence to the Mediterranean diet (r = -0.20; p < 0.001) and to an unhealthier eating profile (r = -0.22; p < 0.001), but no associations were found for work-related SB (p > 0.05). These results persisted after the adjustment for BMI, sex, and self-reported PA. These results were impacted by the age tertile.

CONCLUSIONS

Our findings suggest that adults with higher levels of SB in leisure-time and transport domains tend to report less healthy eating-related behaviors, irrespective of BMI, sex, and PA level. However, some differences in these associations were found according to the age tertile. This information may assist public health authorities in focusing their efforts in augmenting literacy on SB, namely on how SB can be accumulated via different settings. Furthermore, public health literacy efforts need to extend besides the more known deleterious effects of SB on health (e.g., diabetes, cardiovascular disease), to also include the interplay with eating indicators. Strategies to reduce SB and unhealthy eating should be particularly focused on promoting physically active forms of commuting and reducing SB in the leisure setting.

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

OBJECTIVE

Evidence on the influence of built environments on sedentary behaviors remains unclear and is often contradictory. The main limitations encompass the use of self-reported proxies of sedentary time (ST), the scarce consideration of the plurality of sedentary behaviors, and environmental exposures limited to the residential neighborhood. We investigated the relationships between GPS-based activity space measures of environmental exposures and accelerometer-based ST measured in total, at the place of residence, at all locations, and during trips.

METHODS

This study is part of the CURHA project, based on 471 older adults residing in Luxembourg, who wore a GPS receiver and a tri-axial accelerometer during 7 days. Daily ST was computed in total, at the residence, at all locations and during trips. Environmental exposures included exposure to green spaces, walking, biking, and motorized transportation infrastructures. Associations between environments and ST were examined using linear and negative binomial mixed models, adjusted for demographics, self-rated health, residential self-selection, weather conditions and wear time.

RESULTS

Participants accumulated, on average, 8 h and 14 min of ST per day excluding sleep time. ST spent at locations accounted for 83 % of the total ST. ST spent at the residence accounted for 87 % of the location-based ST and 71 % of the total ST. Trip-based ST represents 13 % of total ST, and 4 % remained unclassified. Higher street connectivity was negatively associated with total ST, while the density of parking areas correlated positively with total and location-based ST. Stronger associations were observed for sedentary bouts (uninterrupted ST over 20 and 30 min).

CONCLUSION

Improving street connectivity and controlling the construction of new parking, while avoiding the spatial segregation of populations with limited access to public transport, may contribute to limit ST. Such urban planning interventions may be especially efficient in limiting the harmful uninterrupted bouts of ST among older adults.

Effects of major urban redesign on sedentary behavior, physical activity, active transport and health-related quality of life in adults

BACKGROUND

The built environment is increasingly recognized as a determinant for health and health behaviors. Existing evidence regarding the relationship between environment and health (behaviors) is varying in significance and magnitude, and more high-quality longitudinal studies are needed. The aim of this study was to evaluate the effects of a major urban redesign project on physical activity (PA), sedentary behavior (SB), active transport (AT), health-related quality of life (HRQOL), social activities (SA) and meaningfulness, at 29-39 months after opening of the reconstructed area.

METHODS

PA and AT were measured using accelerometers and GPS loggers. HRQOL and sociodemographic characteristics were assessed using questionnaires. In total, 241 participants provided valid data at baseline and follow-up. We distinguished three groups, based on proximity to the intervention area: maximal exposure group, minimal exposure group and no exposure group.

RESULTS

Both the maximal and minimal exposure groups showed significantly different trends regarding transport-based PA levels compared to the no exposure group. In the exposure groups SB decreased, while it increased in the no exposure group. Also, transport-based light intensity PA remained stable in the exposure groups, while it significantly decreased in the no exposure group. No intervention effects were found for total daily PA levels. Scores on SA and meaningfulness increased in the maximal exposure group and decreased in the minimal and no exposure group, but changes were not statistically significant.

CONCLUSION

The results of this study emphasize the potential of the built environment in changing SB and highlights the relevance of longer-term follow-up measurements to explore the full potential of urban redesign projects.

TRIAL REGISTRATION

This research was retrospectively registered at the Netherlands Trial Register (NL8108).

Associations of air pollution mixtures with ambulatory blood pressure: The MobiliSense sensor-based study

Air pollution is acknowledged as a determinant of blood pressure (BP), supporting the hypothesis that air pollution, via hypertension and other mechanisms, has detrimental effects on human health. Previous studies evaluating the associations between air pollution exposure and BP did not consider the effect that air pollutant mixtures may have on BP. We investigated the effect of exposure to single species or their synergistic effects as air pollution mixture on ambulatory BP. Using portable sensors, we measured personal concentrations of black carbon (BC), nitrogen dioxide (NO2), nitrogen monoxide (NO), carbon monoxide (CO), ozone (O3), and particles with aerodynamic diameters below 2.5 μm (PM2.5). We simultaneously collected ambulatory BP measurements (30-min intervals, N = 3319) of 221 participants over one day of their lives. Air pollution concentrations were averaged over 5 min to 1 h before each BP measurement, and inhaled doses were estimated across the same exposure windows using estimated ventilation rates. Fixed-effect linear models as well as quantile G-computation techniques were applied to associate air pollutants' individual and combined effects with BP, adjusting for potential confounders. In mixture models, a quartile increase in air pollutant concentrations (BC, NO2, NO, CO, and O3) in the previous 5 min was associated with a 1.92 mmHg (95% CI: 0.63, 3.20) higher systolic BP (SBP), while 30-min and 1-h exposures were not associated with SBP. However, the effects on diastolic BP (DBP) were inconsistent across exposure windows. Unlike concentration mixtures, inhalation mixtures in the previous 5 min to 1 h were associated with increased SBP. Out-of-home BC and O3 concentrations were more strongly associated with ambulatory BP outcomes than in-home concentrations. In contrast, only the in-home concentration of CO reduced DBP in stratified analyses. This study shows that exposure to a mixture of air pollutants (concentration and inhalation) was associated with elevated SBP.

NO2, BC and PM Exposure of Participants in the Polluscope Autumn 2019 Campaign in the Paris Region

The Polluscope project aims to better understand the personal exposure to air pollutants in the Paris region. This article is based on one campaign from the project, which was conducted in the autumn of 2019 and involved 63 participants equipped with portable sensors (i.e., NO₂, BC and PM) for one week. After a phase of data curation, analyses were performed on the results from all participants, as well as on individual participants' data for case studies. A machine learning algorithm was used to allocate the data to different environments (e.g., transportation, indoor, home, office, and outdoor). The results of the campaign showed that the participants' exposure to air pollutants depended very much on their lifestyle and the sources of pollution that may be present in the vicinity. Individuals' use of transportation was found to be associated with higher levels of pollutants, even when the time spent on transport was relatively short. In contrast, homes and offices were environments with the lowest concentrations of pollutants. However, some activities performed in indoor air (e.g., cooking) also showed a high levels of pollution over a relatively short period.

Accuracy of steps measured by smartphones-based WeRun compared with ActiGraph-GT3X accelerometer in free-living conditions

Objectives

The purpose of this study was to evaluate the accuracy and reliability of steps tracked by smartphone-based WeChat app compared with Actigraph-GT3X accelerometer in free-living conditions.

Design

A cross-sectional study and repeated measures.

Methods

A total of 103 employees in the Pudong New Area of Shanghai, China, participated in this study. The participants wore an ActiGraph-GT3X accelerometer during the period of August to September 2019 (Time 1), December 2019 (Time 2) and September 2020 (Time 3). Each time, they wore the ActiGraph-GT3X accelerometer continuously for 7 days to assess their 7-day step counts. The smartphone-based WeRun step counts were collected in the corresponding period when subjects wore accelerometers. The subjects were invited to complete basic demographic characteristics questionnaires and to perform physical examination to obtain health-related results such as height, body weight, body fat percentage, waist circumference, hip circumference, and blood pressure.

Results

Based on 103 participants' 21 days of data, we found that the Spearman correlation coefficient between them was 0.733 (P < 0.01). The average number of WeRun steps measured by smartphones was 8,975 (4,059) per day, which was higher than those measured by accelerometers (8,462 ± 3,486 per day, P < 0.01). Demographic characteristics and different conditions can affect the consistency of measurements. The consistency was higher in those who were male, older, master's degree and above educated, and traveled by walking. Steps measured by smartphone and accelerometer in working days and August showed stronger correlation than other working conditions and time. Mean absolute percent error (MAPE) for step counts ranged from 0.5 to 15.9%. The test-retest reliability coefficients of WeRun steps ranged from 0.392 to 0.646. A multiple regression analysis adjusted for age, gender, and MVPA/step counts measured during Time 1 showed that body composition (body weight, BMI, body fat percentage, waist circumference, and hip circumference) was correlated with moderate-to-vigorous intensity physical activity, but it was not correlated with WeRun step counts.

Conclusions

The smartphone-based WeChat app can be used to assess physical activity step counts and is a reliable tool for measuring steps in free-living conditions. However, WeRun step counts' utilization is potentially limited in predicting body composition.

Application of machine learning to predict transport modes from GPS, accelerometer, and heart rate data

BACKGROUND

There has been an increased focus on active transport, but the measurement of active transport is still difficult and error-prone. Sensor data have been used to predict active transport. While heart rate data have very rarely been considered before, this study used random forests (RF) to predict transport modes using Global Positioning System (GPS), accelerometer, and heart rate data and paid attention to methodological issues related to the prediction strategy and post-processing.

METHODS

The RECORD MultiSensor study collected GPS, accelerometer, and heart rate data over seven days from 126 participants living in the Ile-de-France region. RF models were built to predict transport modes for every minute (ground truth information on modes is from a GPS-based mobility survey), splitting observations between a Training dataset and a Test dataset at the participant level instead at the minute level. Moreover, several window sizes were tested for the post-processing moving average of the predicted transport mode.

RESULTS

The minute-level prediction rate of being on trips vs. at a visited location was 90%. Final prediction rates of transport modes ranged from 65% for public transport to 95% for biking. Using minute-level observations from the same participants in the Training and Test sets (as RF spontaneously does) upwardly biases prediction rates. The inclusion of heart rate data improved prediction rates only for biking. A 3 to 5-min bandwidth moving average was optimum for a posteriori homogenization.

CONCLUSION

Heart rate only very slightly contributed to better predictions for specific transport modes. Moreover, our study shows that Training and Test sets must be carefully defined in RF models and that post-processing with carefully chosen moving average windows can improve predictions.

InterMob: a 24-month randomised controlled trial comparing the effectiveness of an intervention including behavioural change techniques and free transport versus an intervention including air pollution awareness-raising on car use reduction among regular car users living in Grenoble, France

Background

Frequent car use contributes to health and environmental issues such as air pollution, climate change and obesity. Active and sustainable mobility (bike, walk, public transport, car sharing) may address these issues. Different strategies have been implemented in past research, involving hard levers, aimed at modifying the economical or geographical context (e.g., free public transport), and soft levers, aimed at modifying psychological processes (e.g., personalised transport advice). However, few studies have combined both hard and soft levers. In addition, few have used robust methodologies (e.g., randomised controlled trials), followed behavioural changes in the long-term, and been anchored in behaviour change theories. InterMob aims to address these limits by implementing a 24-month randomised controlled trial including hard and soft levers. The objectives of InterMob are to a) evaluate the effectiveness of an experimental arm versus an active controlled arm, and b) identify the processes of mobility change.

Methods

Regular car users living in Grenoble (N = 300) will be recruited and randomised to one of the two arms. The experimental arm consists in a six-month intervention combining hard levers (free access to transport/bikes), and soft levers (e.g., personalised transport advice). The control arm consists in a six-month intervention aimed at raising awareness on air pollution and its health effects. Both arms will include eight evaluation weeks (spread out over 24 months) based on a GPS, an accelerometer, and a pollution sensor. Moreover, participants will complete mobility logbooks and surveys measuring psychological constructs, socio-economical, and socio-spatial characteristics.

Discussion

InterMob will assess the effectiveness of two interventions aimed at reducing car use within regular car users in the short-, mid- and long-term. Moreover, InterMob will allow to better understand the psychological processes of behaviour change, and the socio-economical and geographical conditions under which the intervention is efficient in reducing car use. Finally, the benefits of mobility change in terms of physical activity, quality of life, and exposure to pollution will be quantified.

Trial registration

ClinicalTrials.gov: NCT05096000 on 27/10/2021 (retrospectively registered).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-14099-4.

A modifiable factors-based model for detecting inactive individuals: are the European assessment tools fit for purpose?

BACKGROUND

The lack of systematic factors affecting physical inactivity (PIA) challenges policymakers to implement evidence-based solutions at a population level. The study utilizes the Eurobarometer to analyse PIA-modifiable variables.

METHODS

Special Eurobarometer 412 physical activity (PA) data were analysed (n = 18 336), including 40 variables along with the International PA Questionnaire. PIA was used as the dependent variable. Variables considered were alternatives to car, places, reasons and barriers to engaging in PA, memberships to clubs and categorical responses about the agreement extent with the area, provision of activities and local governance statements. Logistic regression was used to identify variables contributing to PIA. Beta values (β), standard errors, 95% confidence intervals, the exponentiation for odds ratio and Cox & Snell and Nagelkerke R2 were indicated.

RESULTS

The resulting model correctly identified 10.7% inactives and 96.9% of actives (R2 of Nagelkerke: 0.153). Variables contributing to the detection of PIA were (P ≤ 0.01): having a disability or an illness, not having friends to do sport with, lacking motivation or interest in and being afraid of injury risk. Additionally, totally agreeing, tend to agree and tend to disagree regarding the extent of local providers offering enough opportunities to be more active also contributed to the model.

CONCLUSIONS

The model reported a limited ability to detect modifiable factors affecting PIA, identifying a small percentage of inactive individuals correctly. New questions focused on understanding inactive behaviour are needed to support the European PA public health agenda.

Day-to-day intrapersonal variability in mobility patterns and association with perceived stress: A cross-sectional study using GPS from 122 individuals in three European cities

Many aspects of our life are related to our mobility patterns and individuals can exhibit strong tendencies towards routine in their daily lives. Intrapersonal day-to-day variability in mobility patterns has been associated with mental health outcomes. The study aims were: (a) calculate intrapersonal day-to-day variability in mobility metrics for three cities; (b) explore interpersonal variability in mobility metrics by sex, season and city, and (c) describe intrapersonal variability in mobility and their association with perceived stress. Data came from the Physical Activity through Sustainable Transport Approaches (PASTA) project, 122 eligible adults wore location measurement devices over 7-consecutive days, on three occasions during 2015 (Antwerp: 41, Barcelona: 41, London: 40). Participants completed the Short Form Perceived Stress Scale (PSS-4). Day-to-day variability in mobility was explored via six mobility metrics using distance of GPS point from home (meters:m), distance travelled between consecutive GPS points (m) and energy expenditure (metabolic equivalents:METs) of each GPS point collected (n = 3,372,919). A Kruskal-Wallis H test determined whether the median daily mobility metrics differed by city, sex and season. Variance in correlation quantified day-to-day intrapersonal variability in mobility. Levene's tests or Kruskal-Wallis tests were applied to assess intrapersonal variability in mobility and perceived stress. There were differences in daily distance travelled, maximum distance from home and METS between individuals by sex, season and, for proportion of time at home also, by city. Intrapersonal variability across all mobility metrics were highly correlated; individuals had daily routines and largely stuck to them. We did not observe any association between stress and mobility. Individuals are habitual in their daily mobility patterns. This is useful for estimating environmental exposures and in fuelling simulation studies.

MobiliSense cohort study protocol: do air pollution and noise exposure related to transport behaviour have short-term and longer-term health effects in Paris, France?

INTRODUCTION

MobiliSense explores effects of air pollution and noise related to personal transport habits on respiratory and cardiovascular health. Its objectives are to quantify the contribution of personal transport/mobility to air pollution and noise exposures of individuals; to compare exposures in different transport modes; and to investigate whether total and transport-related personal exposures are associated with short-term and longer-term changes in respiratory and cardiovascular health.

METHODS AND ANALYSIS

MobiliSense uses sensors of location, behaviour, environmental nuisances and health in 290 census-sampled participants followed-up after 1/2 years with an identical sensor-based strategy. It addresses knowledge gaps by: (1) assessing transport behaviour over 6 days with GPS receivers and GPS-based mobility surveys; (2) considering personal exposures to both air pollution and noise and improving their characterisation (inhaled doses, noise frequency components, etc); (3) measuring respiratory and cardiovascular outcomes (smartphone-assessed respiratory symptoms, lung function with spirometry, resting blood pressure, ambulatory brachial/central blood pressure, arterial stiffness and heart rate variability) and (4) investigating short-term and longer-term (over 1-2 years) effects of transport.

ETHICS AND DISSEMINATION

The sampling and data collection protocol was approved by the National Council for Statistical Information, the French Data Protection Authority and the Ethical Committee of Inserm. Our final aim is to determine, for communicating with policy-makers, how scenarios of changes in personal transport behaviour affect individual exposure and health.

Transit Use and Health Care Costs: A Cross-sectional Analysis

INTRODUCTION

Greater transit use is associated with higher levels of physical activity, which is associated with lower health risks and better health outcomes. However, there is scant evidence about whether health care costs differ based on level of transit ridership.

METHODS

A sample (n=947) of members of Kaiser Permanente in the Portland, Oregon area were surveyed in 2015 about their typical use of various modes of travel including transit. Electronic medical record-derived health care costs were obtained among these members for the prior three years. Analysis examined proportional costs between High transit users (3+ days/week), Low transit users (1-2 days/week), and Non-users adjusting for age and sex, and then individually (base models) and together for demographic and health status variables.

RESULTS

In separate base models across individual covariates, High transit users had lower total health care costs (59-69% of Non-user's costs) and medication costs (31-37% of Non-users' costs) than Non-users. Low transit users also had lower total health care (69%-76% of Non-users' costs) and medication costs (43-57% transit of Non-user's costs) than Non-users. High transit users' outpatient costs were also lower (77-82% of Non-users). In fully-adjusted models, total health care and medication costs were lower among High transit users' (67% and 39%) and Low transit users' (75% and 48%) compared to Non-users, but outpatient costs did not differ by transit use.

CONCLUSIONS

Findings have implications for the potential cost benefit of encouraging and supporting more transit use, although controlled longitudinal and experimental evidence is needed to confirm findings and understand mechanisms.

Assessing the Impact of a New Urban Greenway Using Mobile, Wearable Technology-Elicited Walk- and Bike-Along Interviews

Physical inactivity is the fourth leading risk factor for global mortality, causing an estimated 3.3 million deaths worldwide. Characteristics of the built environment, including buildings, public spaces, pedestrian and cycling infrastructure, transportation networks, parks, trails and green spaces can facilitate or constrain physical activity. However, objective study of built environment interventions on physical activity remains challenging due to methodological limitations and research gaps. Existing methods such as direct observations or surveys are time and labour intensive, and only provide a static, cross-sectional view of physical activity at a specific point in time. The aim of this study was to develop a novel method for objectively and inexpensively assessing how built environment changes may influence physical activity. We used a novel, unobtrusive method to capture real-time, in situ data from a convenience sample of 25 adults along a newly constructed urban greenway in an area of high deprivation in Belfast, UK. Walk/bike-along interviews were conducted with participants using a body-worn or bicycle-mounted portable digital video camera (GoPro HERO 3+ camera) to record their self-determined journeys along the greenway. This is the first study to demonstrate the feasibility of using wearable sensors to capture participants’ responses to the built environment in real-time during their walking and cycling journeys. These findings contribute to our understanding of the impact of real-world environmental interventions on physical activity and the importance of precise, accurate and objective measurements of environments where the activity occurs.

Personal exposure to concentrations and inhalation of black carbon according to transport mode use: The MobiliSense sensor-based study

INTRODUCTION

Epidemiological evidence suggests that motorized vehicle users have a higher air pollutant exposure (especially from vehicle exhaust) than active (walking or cycling) transport users. However, studies often relied on insufficiently diverse sample and ignored that minute ventilation has an effect on individuals' inhaled dose. This study examined commuters' breathing zone concentration and inhaled doses of black carbon (BC) when travelling by different transport modes in the Grand Paris region.

METHODS

Personal exposure to BC was continuously measured with MicroAethalometer (MicroAeth AE51) portable monitors strapped on participants' shoulder with tube inlet at the level of the neck (breathing zone), and inhaled doses were derived from several methods estimating ventilation [based on metabolic equivalents from accelerometry [METs], heart rate, and breathing rate]. Trip stages and transport modes were assessed from GPS and mobility survey data. Breathing zone concentrations and inhaled doses of BC were compared across transport modes at the trip stage level (n = 7495 for 283 participants) using linear mixed effect models with a random intercept at individual level.

RESULTS

Trip stages involving public transport and private motorized transport were associated with a 2.20 µg/m³ (95% CI: 1.99, 2.41) and 2.29 µg/m³ (95% CI: 2.10, 2.48) higher breathing zone concentration to BC than walking, respectively. Trip stages with other active modes had a 0.41 µg (95% CI: 0.25, 0.57) higher inhaled dose, while those involving public transport and private motorized transport had a 0.25 µg (95% CI: -0.35, -0.15) and 0.19 µg (95 %CI: -0.28, -0.10) lower inhaled dose of BC per 30 min than walking.

CONCLUSION

The ranking of transport modes in terms of personal exposure was markedly different when breathing zone concentrations and inhaled doses were considered. Future studies should take both into account to explore the relationship of air pollutants in transport microenvironments with physiological response.

From urban neighbourhood environments to cognitive health: a cross-sectional analysis of the role of physical activity and sedentary behaviours

BACKGROUND

There is a dearth of studies on the effects of the neighbourhood environment on adults' cognitive function. We examined how interrelated aspects of the built and natural neighbourhood environment, including air pollution, correlate with adults' cognitive function, and the roles of physical activity and sedentary behaviours in these associations.

METHODS

We used data from 4,141 adult urban dwellers who participated in the Australian Diabetes, Obesity and Lifestyle 3 study on socio-demographic characteristics, neighbourhood self-selection, physical activity and sedentary behaviours, and cognitive function. Neighbourhood environmental characteristics included population density, intersection density, non-commercial land use mix, and percentages of commercial land, parkland and blue space, all within 1 km residential buffers. We also calculated annual mean concentrations of NO2 and PM2.5. Generalised additive mixed models informed by directed acyclic graphs were used to estimate the total, direct and indirect effects of environmental attributes on cognitive functions and the joint-significance test was used to examine indirect effects via behaviours.

RESULTS

In the total effects models, population density and percentage of parkland were positively associated with cognitive function. A positive association of PM2.5 with memory was also observed. All neighbourhood environmental attributes were directly and/or indirectly related to cognitive functions via other environmental attributes and/or physical activity but not sedentary behaviours. Engagement in transportation walking and gardening frequency partially mediated the positive effects of the neighbourhood environment on cognitive function, while frequency of transportation walking mediated the negative effects.

CONCLUSIONS

In the context of a low-density country like Australia, denser urban environments with access to parkland may benefit residents' cognitive health by providing opportunities for participation in a diversity of activities. A more fine-grained characterisation of the neighbourhood environment may be necessary to tease out the negative and positive impacts of inter-related characteristics of urban neighbourhood environments on cognitive function.

Validity of a Global Positioning System-Based Algorithm and Consumer Wearables for Classifying Active Trips in Children and Adults

Objective

To investigate the convergent validity of a global positioning system (GPS)-based and two consumer-based measures with trip logs for classifying pedestrian, cycling, and vehicle trips in children and adults.

Methods

Participants (N = 34) wore a Qstarz GPS tracker, Fitbit Alta, and Garmin vivosmart 3 on multiple days and logged their outdoor pedestrian, cycling, and vehicle trips. Logged trips were compared with device-measured trips using the Personal Activity Location Measurement System (PALMS) GPS-based algorithms, Fitbit's SmartTrack, and Garmin's Move IQ. Trip- and day-level agreement were tested.

Results

The PALMS identified and correctly classified the mode of 75.6%, 94.5%, and 96.9% of pedestrian, cycling, and vehicle trips (84.5% of active trips, F1 = 0.84 and 0.87) as compared with the log. Fitbit and Garmin identified and correctly classified the mode of 26.8% and 17.8% (22.6% of active trips, F1 = 0.40 and 0.30) and 46.3% and 43.8% (45.2% of active trips, F1 = 0.58 and 0.59) of pedestrian and cycling trips. Garmin was more prone to false positives (false trips not logged). Day-level agreement for PALMS and Garmin versus logs was favorable across trip modes, though PALMS performed best. Fitbit significantly underestimated daily cycling. Results were similar but slightly less favorable for children than adults.

Conclusions

The PALMS showed good convergent validity in children and adults and were about 50% and 27% more accurate than Fitbit and Garmin (based on F1). Empirically-based recommendations for improving PALMS' pedestrian classification are provided. Since the consumer devices capture both indoor and outdoor walking/running and cycling, they are less appropriate for trip-based research.

The Association Between Neighborhood Public Transportation Usage and Youth Physical Activity

INTRODUCTION

Routine adolescent physical activity is a well-established predictor of positive health across the lifespan, although wide disparities in youth physical activity engagement persist across sex and race/ethnicity. Transportation barriers may be related to adolescents' ability to access physical activity opportunities. This study examines the association between neighborhood public transportation usage and adolescent physical activity using a national sample.

METHODS

Cross-sectional data were drawn from the Family Life, Activity, Sun, Health, and Eating study (2014), a national sample of adolescents aged 12-17 years. Linear regression examined the association between neighborhood public transportation usage on the basis of neighborhood-level public transportation use and individual-level youth moderate-to-vigorous physical activity minutes per week. Models were developed for weekday, weekend, and combined moderate-to-vigorous physical activity for all youth and across sex and race/ethnicity subgroups. Analyses were run in 2020.

RESULTS

The final analytic data set included 1,247 adolescents aged 12-17 years (71% non-Hispanic White, 49% male, mean age=14.52 [SD=1.59] years). Adjusted models showed a stronger magnitude of association between high neighborhood public transportation usage and both weekday (β=8.79, 95% CI=1.00, 16.59) and combined (β=13.74, 95% CI=1.14, 26.35) moderate-to-vigorous physical activity than between low/moderate neighborhood public transportation usage and moderate-to-vigorous physical activity. The magnitude of the neighborhood public transportation usage-moderate-to-vigorous physical activity association was strongest among non-Hispanic Black and Hispanic adolescent girls.

CONCLUSIONS

This study found an association between neighborhood public transportation usage and adolescent moderate-to-vigorous physical activity, particularly among non-Hispanic Black and Hispanic adolescent girls. Findings from this research have the potential to inform targeted interventions for promoting adolescent physical activity to ultimately reduce chronic health disparities across the lifespan.

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.

Planning for the First and Last Mile: A Review of Practices at Selected Transit Agencies in the United States

A transit trip involves travel to and from transit stops or stations. The quality of what are commonly known as first and last mile connections (regardless of their length) can have an important impact on transit ridership. Transit agencies throughout the world are developing innovative approaches to improving first and last mile connections, for example, by partnering with ride-hailing and other emerging mobility services. A small but growing number of transit agencies in the U.S. have adopted first and last mile (FLM) plans with the goal of increasing ridership. As this is a relatively new practice by transit agencies, a review of these plans can inform other transit agencies and assist them in preparing their own. Four FLM plans were selected from diverse geographic contexts for review: Los Angeles County Metropolitan Transportation Authority (LA Metro), Riverside (CA) Transit Agency (RTA), and Denver Regional Transit District (RTD), and City of Richmond, CA. Based on the literature, we developed a framework with an emphasis on transportation equity to examine these plans. We identified five common approaches to addressing the FLM issue: spatial gap analysis with a focus on socio-demographics and locational characteristics, incorporation of emerging mobility services, innovative funding approaches for plan implementation, equity and transportation remedies for marginalized communities, and development of pedestrian and bicycle infrastructures surrounding transit stations. Strategies in three of the plans are aligned with regional goals for emissions reductions. LA Metro and Riverside Transit incorporate detailed design guidelines for the improvement of transit stations. As these plans are still relatively new, it will take time to evaluate their impact on ridership and their communities’ overall transit experience.

National and metropolitan trends in public transit use, transit-related walking, and ridesharing between 2009 and 2017

Introduction

Walking is a common form of physical activity and is the most frequent way to access public transit. On-going changes in the US transportation system are occurring, notably increases in smartphone application-based ridesharing. The goal of this research is to assess whether increasing use of ridesharing was associated with a change in transit-related walking. This is important to both public health and transportation, as it can inform changes in active transportation which promotes both physical activity and transit use.

Methods

We examined the association between change in transit use, transit-related walking, and ridesharing nationally and for selected metropolitan areas using the 2009 and 2017 National Household Travel Survey (≥18 years; n = 263,572 and n = 230,592, respectively). Analyses were conducted in 2019. Covariates included sex, age, race/ethnicity, education, employment, work from home, household size, number of vehicles, population density, Census region, metro area size and heavy rail transit category and season.

Results

The national prevalence of transit use in the past month in 2009 was 16.9% (95% CI: 16.4%-17.4%) and in 2017 was 16.1% (15.6%-16.6%), a significant decrease (p < 0.02). The prevalence of daily transit-related walking in 2009 was 4.2% (4.0%-4.4%) and in 2017 was 4.4% (4.2%-4.6%; p = 0.22). The prevalence of daily taxi use in 2009 was 0.5% (0.4%-0.6%) and taxi/rideshare in 2017 was 1.1% (1.0%-1.2%), a significant increase (p < 0.0001). The relationships remained after covariate adjustment. Finally, there was not a significant change in transit-related walking or interaction between year and taxi/rideshare use after additional adjustment for taxi/rideshare. Changes in transit-related walking in metros were largely not significant, whereas increases in taxi/rideshare were largely significant.

Conclusions

Results suggest that increased use of ridesharing may not be linked with changes in transit-related walking. Continued surveillance of travel mode prevalence is required to track potential reductions in population-level physical activity with technology-related changes in travel.

Map-based assessment of older adults' life space: validity and reliability

Background

Map-based tools have recently found their way into health-related research. They can potentially be used to quantify older adults’ life-space. This study aimed to evaluate the validity (vs. GPS) and the test-retest reliability of a map-based life-space assessment (MBA).

Methods

Life-space of one full week was assessed by GPS and by MBA. MBA was repeated after approximately 3 weeks. Distance-related (mean and maximum distance from home) and area-related (convex hull, standard deviational ellipse) life-space indicators were calculated. Intraclass correlations (MBA vs. GPS and test-retest) were calculated in addition to Bland-Altman analyses (MBA vs. GPS).

Results

Fifty-eight older adults (mean age 74, standard deviation 5.5 years; 39.7% women) participated in the study. Bland-Altman analyses showed the highest agreement between methods for the maximum distance from home. Intraclass correlation coefficients ranged between 0.19 (95% confidence interval 0 to 0.47) for convex hull and 0.72 (95% confidence interval 0.52 to 0.84) for maximum distance from home. Intraclass correlation coefficients for test-retest reliability ranged between 0.04 (95% confidence interval 0 to 0.30) for convex hull and 0.43 (95% confidence interval 0.19 to 0.62) for mean distance from home.

Conclusions

While acceptable validity and reliability were found for the distance-related life-space parameters, MBA cannot be recommended for the assessment of area-related life-space parameters.

Physical activity and sedentary behaviour related to transport activity assessed with multiple body-worn accelerometers: the RECORD MultiSensor Study

OBJECTIVES

The study explored the physical activity and sedentary behaviours related to transport activity. The aim was to provide evidence to support public health and transport policies encouraging people to reach daily recommendations of physical activity.

STUDY DESIGN

The study design of this study is a cross-sectional study design.

METHODS

Between 2013 and 2015, the RECORD MultiSensor Study collected data from 155 participants using two accelerometers worn on the thigh and trunk. In addition, data were collected from Global Positioning System (GPS) receivers and a GPS-based mobility survey. Relationships between transport modes and the durations and partition patterns of physical behaviours were established at the trip stage (n = 7692) and trip levels (n = 4683) using multilevel linear models with a random effect at the individual level and taking into account temporal autocorrelation.

RESULTS

Participants travelled for a median of 1 h 45 min per day. Trip stages and trips involving walking, other active modes or public transport were associated with a lower sitting duration and a higher moderate-to-vigorous physical activity (MVPA) duration than trips with a personal motorised vehicle. Using public transport was associated with a lower number of transitions between sedentary behaviours and non-sedentary behaviours, and with a higher number of transitions between non-sedentary behaviours and MVPA than relying on a private motorised vehicle.

CONCLUSIONS

This study is the first to assess the association of transport mode with physical activity and sedentary behaviours captured with thigh- and trunk-worn accelerometers at both the trip stage and trip levels. The results demonstrate that, in addition to active transport modes, encouraging people to use public transport increases physical activity and reduces sedentary time.

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

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

Physical activity accrued as part of public transport use in England

BACKGROUND

Walking and cycling for transport (active travel) is an important source of physical activity with established health benefits. However, levels of physical activity accrued during public transport journeys in England are unknown.

METHODS

Using the English National Travel Survey 2010-14 we quantified active travel as part of public transport journeys. Linear regression models compared levels of physical activity across public transport modes, and logistic regression models compared the odds of undertaking 30 min a day of physical activity.

RESULTS

Public transport users accumulated 20.5 min (95% confidence interval=19.8, 21.2) a day of physical activity as part of public transport journeys. Train users accumulated 28.1 min (26.3, 30.0) with bus users 16.0 min (15.3, 16.8). Overall, 34% (32%, 36%) of public transport users achieved 30 min a day of physical activity in the course of their journeys; 21% (19%, 24%) of bus users and 52% (47%, 56%) of train users.

CONCLUSION

Public transport use is an effective way to incorporate physical activity into daily life. One in three public transport users meet physical activity guidelines suggesting that shifts from sedentary travel modes to public transport could dramatically raise the proportion of populations achieving recommended levels of physical activity.

Associations between commute mode and cardiovascular disease, cancer, and all-cause mortality, and cancer incidence, using linked Census data over 25 years in England and Wales: a cohort study

BACKGROUND

Active travel is increasingly recognised as an important source of physical activity. We aimed to describe associations between commute mode and cardiovascular disease, cancer, and all-cause mortality.

METHODS

We analysed data from the Office for National Statistics Longitudinal Study of England and Wales (ONS-LS), which linked data from the Census of England and Wales (henceforth referred to as the Census) for 1991, 2001, and 2011 to mortality and cancer registrations. The cohort included individuals traced in the ONS-LS who were economically active (ie, aged ≥16 years, not retired from work, and not a full-time carer). Commuting by private motorised transport, public transport, walking, and cycling were compared in terms of all-cause mortality, cancer mortality, cardiovascular disease mortality, and cancer incidence, using Cox proportional-hazards models with time-varying covariates. Models were adjusted for age, sex, housing tenure, marital status, ethnicity, university education, car access, population density, socioeconomic classification, Carstairs index quintile, long-term illness, and year entered the study, and were additionally stratified by socioeconomic group.

FINDINGS

Between the 1991 Census and the 2011 Census, 784 677 individuals contributed data for at least one Census, of whom 394 746 were included in the ONS-LS and were considered to be economically active working-age individuals. 13 983 people died, 3172 from cardiovascular disease and 6509 from cancer, and there were 20 980 incident cancer cases. In adjusted models, compared with commuting by private motorised vehicle, bicycle commuting was associated with a 20% reduced rate of all-cause mortality (hazard ratio [HR] 0·80, 95% CI 0·73-0·89), a 24% decreased rate of cardiovascular disease mortality (0·76, 0·61-0·93), a 16% lower rate of cancer mortality (0·84, 0·73-0·98), and an 11% reduced rate of incident cancer (0·89, 0·82-0·97). Compared with commuting by private motorised vehicle, rail commuters had a 10% lower rate of all-cause mortality (HR 0·90, 95% CI 0·83-0·97) and a 21% decreased rate of cardiovascular disease mortality (0·79, 0·67-0·94), in addition to a 12% reduced rate of incident cancer (0·88, 0·83-0·94). Walk commuting was associated with 7% lower cancer incidence (HR 0·93, 95% CI 0·89-0·97) Stratified analyses did not indicate differences in associations between socioeconomic groups.

INTERPRETATION

Our findings augment existing evidence for the beneficial health effects of physically active commute modes, particularly cycling and train use, and suggest that all socioeconomic groups could benefit.

FUNDING

National Institute for Health Research.

Effects of active commuting on health-related quality of life and sickness-related absence

Increased physical activity is associated with numerous health benefits. This study investigated the effect of active commuting (walking and cycling to work) on health-related quality of life (HRQoL) and absence days from work due to sickness in healthy working adults. In total, 73 participants (age: 46 ± 9 years), all working at a tertiary university hospital in Salzburg, Austria, were randomized into an intervention group (IG, n = 51) and a control group (CG, n = 22). The IG was asked to commute actively for twelve months, whereas the CG did not have to change their usual commuting behavior. IG was divided into two subgroups: IG-C (cycling, n = 26) was asked to commute by bicycle and IG-PT (public transport, n = 25) partially using public transportation and walked the remaining distance to work. Significant positive changes in IG were observed in four subcomponents of the SF-36 (physical functioning (95 [10] to 100 [8.8], P = .023), mental health (82 [15] to 86 [15], P = .036), vitality (65 [20] to 70 [14], P = .005), and general health (70 [19] to 80 [24], P = .004)) as well as the physical component summary score (56.5 [9] to 59.2 [6.3], P = .002). IG-C showed greater and more statistically significant changes regarding HRQoL compared to IG-PT. Associations between active commuting and sick-leave days were only observed in IG-PT (7.5 [14.8] to 4.0 [11.3] days, P = .038). In conclusion, active commuting improves various components of HRQoL and might therefore be a possible strategy to increase quality of life in the workforce.

The short-term association between exposure to noise and heart rate variability in daily locations and mobility contexts

BACKGROUND

Personal exposure to noise has been shown to be associated with concomitant increases and lagged decreases of short-term heart rate variability (HRV). It is however unknown whether this association differs between contexts defined by visited places or mobility as both exposure sources and expectations may be different between these contexts.

METHOD

Between July 2014 and June 2015, the RECORD MultiSensor Study collected sound level and heart rate data for 75 participants, aged 34-74 years, in their living environments for 7 days using a personal dosimeter and electrocardiography sensor on the chest. Their whereabouts were collected using a GPS receiver and a mobility survey. Short-term concomitant and lagged associations between sound level and HRV parameters were assessed within types of visited places and transport modes using mixed effects models with a random intercept for participants.

RESULTS

Increases in sound level were associated with a concomitant increase in all HR/HRV parameters, and delayed decreases in the overall HRV. Interactions between the sound level and the visited place/mobility context were documented. Compared with home, the concomitant association of sound level with HR and rMSSD was doubled within active and private-motorized transport modes, respectively.

CONCLUSIONS

The association of sound level with HR/HRV varies between visited places/mobility contexts. Future studies investigating these context-dependent associations in ambulatory settings will need to assess additional acoustical factors relating to the visited environments as well as non-acoustical factors impacting the perception of noise.

Prognostic value of instrumental activity of daily living in initial heart failure hospitalization patients aged 65 years or older

Although the Tokyo Metropolitan Institute of Gerontology Index of Competence (TMIG-IC) is useful to assess decline of instrumental activities of daily living (IADL) in Japanese individuals, limited data are available in patients with heart failure (HF). This study was performed to investigate the prognostic value of IADL evaluated by TMIG-IC in initial HF hospitalization patients aged ≥ 65 years. We reviewed 297 elderly HF patients with independent basic ADL before hospitalization. Patients with prior HF were excluded. Five TMIG-IC items were investigated as IADL parameters. Patients with full IADL scores were defined as "independent" and others were defined as "dependent". The endpoint was all-cause mortality, and multivariable analysis was performed to identify IADL risk. The median age was 76 years, and 55% of the patients were male. Forty-one deaths occurred over a median follow-up period of 1.01 years. After adjusting for existing risk factors, including Seattle Heart Failure Score, dependent patients had higher mortality risk than independent patients [hazard ratio 3.64, 95% confidence interval (CI) 1.57-8.43], and mortality risk decreased by 16% for each 1-point increase in IADL score (hazard ratio 0.84, 95% CI 0.71-0.99). In conclusion, limited IADL indicated by TMIG-IC was associated with poorer long-term mortality rate in elderly patients with HF. This inexpensive and easily applicable tool will support decision making in cardiac rehabilitation.

Exploring Children's Physical Activity Behaviours According to Location: A Mixed-Methods Case Study

The school environment is ideally placed to facilitate physical activity (PA) with numerous windows of opportunity from break and lunch times, to lesson times and extracurricular clubs. However, little is known about how children interact with the school environment to engage in PA and the other locations they visit daily, including time spent outside of the school environment i.e., evening and weekend locations. Moreover, there has been little research incorporating a mixed-methods approach that captures children’s voices alongside objectively tracking children’s PA patterns. The aim of this study was to explore children’s PA behaviours according to different locations. Sixty children (29 boys, 31 girls)—35 key stage 2 (aged 9–11) and 25 key stage 3 (aged 11–13)—wore an integrated global positioning systems (GPS) and heart rate (HR) monitor over four consecutive days. A subsample of children (n = 32) were invited to take part in one of six focus groups to further explore PA behaviours and identify barriers and facilitators to PA. Children also completed a PA diary. The KS2 children spent significantly more time outdoors than KS3 children (p = 0.009). Boys engaged in more light PA (LPA) when on foot and in school, compared with girls (p = 0.003). KS3 children engaged in significantly more moderate PA (MPA) at school than KS2 children (p = 0.006). Focus groups revealed fun, enjoyment, friends, and family to be associated with PA, and technology, costs, and weather to be barriers to PA. This mixed methodological study highlights differences in the PA patterns and perceptions of children according to age and gender. Future studies should utilize a multi-method approach to gain a greater insight into children’s PA patterns and inform future health policies that differentiate among a range of demographic groups of children.

Combining sensor tracking with a GPS-based mobility survey to better measure physical activity in trips: public transport generates walking

Background

Policymakers need accurate data to develop efficient interventions to promote transport physical activity. Given the imprecise assessment of physical activity in trips, our aim was to illustrate novel advances in the measurement of walking in trips, including in trips incorporating non-walking modes.

Methods

We used data of 285 participants (RECORD MultiSensor Study, 2013–2015, Paris region) who carried GPS receivers and accelerometers over 7 days and underwent a phone-administered web mobility survey on the basis of algorithm-processed GPS data. With this mobility survey, we decomposed trips into unimodal trip stages with their start/end times, validated information on travel modes, and manually complemented and cleaned GPS tracks. This strategy enabled to quantify walking in trips with different modes with two alternative metrics: distance walked and accelerometry-derived number of steps taken.

Results

Compared with GPS-based mobility survey data, algorithm-only processed GPS data indicated that the median distance covered by participants per day was 25.3 km (rather than 23.4 km); correctly identified transport time vs. time at visited places in 72.7% of time; and correctly identified the transport mode in 67% of time (and only in 55% of time for public transport). The 285 participants provided data for 8983 trips (21,163 segments of observation). Participants spent a median of 7.0% of their total time in trips. The median distance walked per trip was 0.40 km for entirely walked trips and 0.85 km for public transport trips (the median number of accelerometer steps were 425 and 1352 in the corresponding trips). Overall, 33.8% of the total distance walked in trips and 37.3% of the accelerometer steps in trips were accumulated during public transport trips. Residents of the far suburbs cumulated a 1.7 times lower distance walked per day and a 1.6 times lower number of steps during trips per 8 h of wear time than residents of the Paris core city.

Conclusions

Our approach complementing GPS and accelerometer tracking with a GPS-based mobility survey substantially improved transport mode detection. Our findings suggest that promoting public transport use should be one of the cornerstones of policies to promote physical activity.

Electronic supplementary material

The online version of this article (10.1186/s12966-019-0841-2) contains supplementary material, which is available to authorized users.

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.

Associations of Public Transportation Use With Cardiometabolic Health: A Systematic Review and Meta-Analysis

Public transportation provides an opportunity to incorporate physical activity into journeys, but potential health impacts have not been systematically examined. We searched the literature for articles on public transportation and health published through December 2017 using Google (Google Inc., Mountain View, California), 5 medical databases, and 1 transportation-related database. We identified longitudinal studies which examined associations between public transportation and cardiometabolic health (including adiposity, type 2 diabetes mellitus, and cardiovascular disease). We assessed study quality using the Newcastle-Ottawa Scale for cohort studies and performed meta-analyses where possible. Ten studies were identified, 7 investigating use of public transportation and 3 examining proximity to public transportation. Seven studies used individual-level data on changes in body mass index (BMI; weight (kg)/height (m)²), with objective outcomes being measured in 6 studies. Study follow-up ranged from 1 year to 10 years, and 3 studies adjusted for nontransportation physical activity. We found a consistent association between use of public transportation and lower BMI. Meta-analysis of data from 5 comparable studies found that switching from automobile use to public transportation was associated with lower BMI (−0.30 units, 95% confidence interval: −0.47, −0.14). Few studies have investigated associations between public transportation use and nonadiposity outcomes. These findings suggest that sustainable urban design which promotes public transportation use may produce modest reductions in population BMI.

ROUTINE: The Development of a Physical Activity Promoting Journey Planner Web App

Behavior change apps are widespread, but the scientific base of the app-concept is rarely disclosed. The aim of this article is to present the methodological approach used for the development of a so-called “fitness feedback demonstrator” within an already existing journey planner web app to motivate people to increase their physical activity behavior while using public transport. Firstly, we introduce the behavior change theories applied for the design of the feedback, followed by the analysis of focus-group discussions about the desired content of the fitness feedback. Secondly, we describe how we conducted a field test to measure the number of steps taken when using public transport. Finally, we used the feedback from potential users in terms of design/attractiveness and comprehensibility of the added fitness information. The “fitness feedback demonstrator” is a good practical example of how to make use of the different research expertise to develop a theory-based tool to encourage persons to integrate physical activity into their daily routines.

Evidence synthesis - Where are children and adults physically active and sedentary? - a rapid review of location-based studies

INTRODUCTION

Geographical positioning systems (GPS) have the capacity to provide further context around where physical activity (PA) and sedentary time (ST) are accrued especially when overlaid onto objectively measured movement. The objective of this rapid review was to summarize evidence from location-based studies which employed the simultaneous use of GPS and objective measures of PA and/or ST.

METHODS

Six databases were searched to identify studies that employed the simultaneous use of GPS and objective measures of PA or ST to quantify location of movement. Risk of bias was assessed, and a qualitative synthesis completed.

RESULTS

Searching identified 3446 articles; 59 were included in the review. A total of 22 studies in children, 17 in youth and 20 in adults were captured. The active transportation environment emerged as an important location for moderate-to-vigorous intensity physical activity (MVPA) in children, youth and adults. In children and youth, the school is an important location for MVPA, especially the schoolyard for children. Indoor locations (e.g., schools, homes) appear to be greater sources of lighter intensities of PA and ST. The review was limited by a lack of standardization in the nomenclature used to describe the locations and methods, as well as measures of variance.

CONCLUSION

Evidence suggests that the active transportation environment is a potentially important contributor of MVPA across an individual's lifespan. There is a need for future location-based studies to report on locations of all intensity of movement (including minutes and proportion) using a whole-day approach in larger representative samples.

Natural movement: A space syntax theory linking urban form and function with walking for transport

Walking to get to and from local destinations including shops, services, and transit stops is a major source of adults' health-related physical activity. Research has been using space syntax measures in examining how urban form is related to such routine walking for transport. This paper proposes to apply a theory of space syntax, natural movement, which posits street layout as a primary factor influencing pedestrian movement. Discussing how this theory can link urban form (street layout) and function (land use) with walking for transport, we propose a research agenda to produce new insights and advance methods in active living research.

Is the built environment associated with morbidity and mortality? A systematic review of evidence from Germany

The empirical evidence on this relationship mainly comes from Anglo-American countries whereas evidence from Germany is only emerging. Our objective is to provide a narrative overview and critical appraisal of the existing empirical evidence on the relationship between the built environment and morbidity/mortality in Germany. We conducted a systematic literature search where we included all empirical studies that linked the built environment aspects with morbidity or mortality outcomes. Findings were summarized and critically evaluated according to the Newcastle Ottawa Scale. Eighteen studies met the inclusion criteria and underwent in-depth analysis. Findings indicate that traffic exposure and green space tend to be associated with acute respiratory symptoms but not with chronic respiratory conditions. Evidence was inconsistent for the role of infrastructural aspects and urbanicity. Our review confirms the well-established association between traffic and respiratory health. Yet, the consistency between self-reported and objective measures of respiratory health should be investigated in more detail.

Quantification of Free-Living Community Mobility in Healthy Older Adults Using Wearable Sensors

Introduction: Understanding determinants of community mobility disability is critical for developing interventions aimed at preventing or delaying disability in older adults. In an effort to understand these determinants, capturing and measuring community mobility has become a key factor. The objectives of this paper are to present and illustrate the signal processing workflow and outcomes that can be extracted from an activity and community mobility measurement approach based on GPS and accelerometer sensor data and 2) to explore the construct validity of the proposed measurement approach using data collected from healthy older adults in free-living conditions. Methods: Personal, functional impairment and environmental variables were obtained by self-report questionnaires in 75 healthy community-living older adults (mean age = 66 ± 7 years old) living on the island of Montreal, QC, Canada. Participants wore, for 14 days during waking hours on the hip, a data logger incorporating a GPS receiver with a 3-axis accelerometer. Time at home ratio (THR), Trips out (TO), Destinations (D), Maximal distance of destinations (MDD), Active time ratio (ATR), Steps (S), Distance in a vehicle (DV), Time in a vehicle (TV), Distance on foot (DF), Time on foot (TF), Ellipse area (EA), and Ellipse maximum distance (EMD) were extracted from the recordings. Results: After applying quality control criteria, the original data set was reduced from 75 to 54 participants (28% attrition). Results from the remaining sample show that under free-living conditions in healthy older adults, location, activity and community mobility outcomes vary across individuals and certain personal variables (age, income, living situation, professional status, vehicle access) have potential mitigating effects on these outcomes. There was a significant (yet small) relationship (rho < 0.40) between self-reported life space and MDD, DV, EA, and EMD. Conclusion: Wearability and usability of the devices used to capture free-living community mobility impact participant compliance and the quality of the data. The construct validity of the proposed approach appears promising but requires further studies directed at populations with mobility impairments.

Applications of Space Technologies to Global Health: Scoping Review

Background

Space technology has an impact on many domains of activity on earth, including in the field of global health. With the recent adoption of the United Nations’ Sustainable Development Goals that highlight the need for strengthening partnerships in different domains, it is useful to better characterize the relationship between space technology and global health.

Objective

The aim of this study was to identify the applications of space technologies to global health, the key stakeholders in the field, as well as gaps and challenges.

Methods

We used a scoping review methodology, including a literature review and the involvement of stakeholders, via a brief self-administered, open-response questionnaire. A distinct search on several search engines was conducted for each of the four key technological domains that were previously identified by the UN Office for Outer Space Affairs’ Expert Group on Space and Global Health (Domain A: remote sensing; Domain B: global navigation satellite systems; Domain C: satellite communication; and Domain D: human space flight). Themes in which space technologies are of benefit to global health were extracted. Key stakeholders, as well as gaps, challenges, and perspectives were identified.

Results

A total of 222 sources were included for Domain A, 82 sources for Domain B, 144 sources for Domain C, and 31 sources for Domain D. A total of 3 questionnaires out of 16 sent were answered. Global navigation satellite systems and geographic information systems are used for the study and forecasting of communicable and noncommunicable diseases; satellite communication and global navigation satellite systems for disaster response; satellite communication for telemedicine and tele-education; and global navigation satellite systems for autonomy improvement, access to health care, as well as for safe and efficient transportation. Various health research and technologies developed for inhabited space flights have been adapted for terrestrial use.

Conclusions

Although numerous examples of space technology applications to global health exist, improved awareness, training, and collaboration of the research community is needed.

The "Residential" Effect Fallacy in Neighborhood and Health Studies: Formal Definition, Empirical Identification, and Correction

BACKGROUND

Because of confounding from the urban/rural and socioeconomic organizations of territories and resulting correlation between residential and nonresidential exposures, classically estimated residential neighborhood-outcome associations capture nonresidential environment effects, overestimating residential intervention effects. Our study diagnosed and corrected this "residential" effect fallacy bias applicable to a large fraction of neighborhood and health studies.

METHODS

Our empirical application investigated the effect that hypothetical interventions raising the residential number of services would have on the probability that a trip is walked. Using global positioning systems tracking and mobility surveys over 7 days (227 participants and 7440 trips), we employed a multilevel linear probability model to estimate the trip-level association between residential number of services and walking to derive a naïve intervention effect estimate and a corrected model accounting for numbers of services at the residence, trip origin, and trip destination to determine a corrected intervention effect estimate (true effect conditional on assumptions).

RESULTS

There was a strong correlation in service densities between the residential neighborhood and nonresidential places. From the naïve model, hypothetical interventions raising the residential number of services to 200, 500, and 1000 were associated with an increase by 0.020, 0.055, and 0.109 of the probability of walking in the intervention groups. Corrected estimates were of 0.007, 0.019, and 0.039. Thus, naïve estimates were overestimated by multiplicative factors of 3.0, 2.9, and 2.8.

CONCLUSIONS

Commonly estimated residential intervention-outcome associations substantially overestimate true effects. Our somewhat paradoxical conclusion is that to estimate residential effects, investigators critically need information on nonresidential places visited.

Sub-population differences in the relationship between the neighborhood environment and Latinas' daily walking and vehicle time

BACKGROUND

Over 60% of Latinas report not meeting moderate to vigorous physical activity (MVPA) guidelines of 150 minutes/week. Ecological models of health posit that intrapersonal and environmental factors interact with one another to influence physical activity. Understanding their interactions in relation to transportation behaviors may inform interventions to increase Latinas' physical activity.

PURPOSE

To 1) objectively estimate walking and vehicle time in Latinas, 2) examine the association of, and interactions between, intrapersonal (socio-demographics and weight status) and neighborhood environmental correlates with objective daily walking and vehicle time.

METHODS

A subsample of Latinas (n=87) participating in a health intervention wore an accelerometer and GPS device for at least two valid wear days at baseline. The Personal Activity Location and Measurement System (PALMS) software estimated daily walking and vehicle time. Participants' anthropometrics were measured, and they completed a survey assessing socio-demographic characteristics and perceived neighborhood environment. Generalized linear mixed models examined main effects and interactions of four intrapersonal and five environmental factors on daily walking and vehicle time.

RESULTS

On average, participants walked 16 min/day and spent 69 min/day in a vehicle. Overweight/obesity was negatively associated with walking time (p=.04) and positively associated with vehicle time (p=0.01). Household income was positively associated with vehicle time (p=0.02). For daily walking time, two interactions were significant: perceived access to destinations X household income (p=0.01), and perceived sidewalk maintenance X acculturation (p= 0.01). For daily vehicle time, two interactions were significant: perceived access to destinations X weight status (p<0.001), and perceived safety from crime X education (p=0.01).

CONCLUSION

Latinas participated in relatively low walking time and high amounts of vehicle time. Findings suggest intrapersonal sub-group differences in the association of the neighborhood environment with walking and vehicle time. Improving neighborhood environments to promote walking and reduce vehicle time may help improve Latinas' overall physical activity.

Examining the Influence of a New Light Rail Line on the Health of a Demographically Diverse and Understudied Population within the Washington, D.C. Metropolitan Area: A Protocol for a Natural Experiment Study

Approximately two-thirds of adults and youth in Prince George's County, Maryland, a suburb of Washington, D.C. are overweight or obese and less than half are achieving daily physical activity recommendations. Active transportation (AT), such as walking, biking or using public transportation (PT), is a strategic pathway to improving physical activity levels and thus reducing excess weight. Utilizing an expansion of the Washington, D.C. area transportation system with a new light rail line, the Purple Line Outcomes on Transportation (PLOT) Study will exam pre- and post-Purple Line PT use, AT behaviors and attitudes and physical activity among Prince George's County adults and youth. The PLOT Study will take advantage of this natural experiment in an area enduring significant racial/ethnic and gender-based overweight or obesity and physical inactivity disparities. While similar natural experiments on AT have been conducted in other U.S. cities, those studies lacked diverse and representative samples. To effectively evaluate these physical activity outcomes among this population, efforts will be used to recruit African American and Latino populations, the first and second most common racial/ethnic groups in Prince George's County. Finally, the PLOT Study will also examine how contextual effects (e.g., neighborhood built environment) impact PT, AT and physical activity.