Ruben Brondeel

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

BackgroundAccurate information is lacking on the extent of transportation as a source of physical activity, on the physical activity gains from public transportation use, and on the extent to which population shifts in the use of transportation modes could increase the percentage of people reaching official physical activity recommendations.MethodsIn 2012-2013, 234 participants of the RECORD GPS Study (French Paris region, median age = 58) wore a portable GPS receiver and an accelerometer for 7 consecutive days and completed a 7-day GPS-based mobility survey (participation rate = 57.1%). Information on transportation modes and accelerometry data aggregated at the trip level [number of steps taken, energy expended, moderate to vigorous physical activity (MVPA), and sedentary time] were available for 7,644 trips. Associations between transportation modes and accelerometer-derived physical activity were estimated at the trip level with multilevel linear models.ResultsParticipants spent a median of 1 h 58 min per day in transportation (8.2% of total time). Thirty-eight per-cent of steps taken, 31% of energy expended, and 33% of MVPA over 7 days were attributable to transportation. Walking and biking trips but also public transportation trips with all four transit modes examined were associated with greater steps, MVPA, and energy expenditure when compared to trips by personal motorized vehicle. Two simulated scenarios, implying a shift of approximately 14% and 33% of all motorized trips to public transportation or walking, were associated with a predicted 6 point and 13 point increase in the percentage of participants achieving the current physical activity recommendation.ConclusionsCollecting data with GPS receivers, accelerometers, and a GPS-based electronic mobility survey of activities and transportation modes allowed us to investigate relationships between transportation modes and physical activity at the trip level. Our findings suggest that an increase in active transportation participation and public transportation use may have substantial impacts on the percentage of people achieving physical activity recommendations.

Residential buffer, perceived neighborhood, and individual activity space: New refinements in the definition of exposure areas - The RECORD Cohort Study.

Neighborhood effects on health have been widely investigated; yet the definition of neighborhoods is usually arbitrary. This study analyses how disparities in environmental exposure according to urbanicity vary when considering a home-centered network-buffer, the perceived residential neighborhood, or the activity space. Exposures to the density of destinations and proportion of green space were compared for three spatial definitions of exposure areas, overall and stratified by urbanicity of the residence. Environmental exposure levels and gradients by urbanicity were found to vary depending on the spatial definition of the exposure area.

Accounting for the daily locations visited in the study of the built environment correlates of recreational walking (the RECORD Cohort Study)

BACKGROUND Understanding how built environment characteristics influence recreational walking is of the utmost importance to develop population-level strategies to increase levels of physical activity in a sustainable manner. PURPOSE This study analyzes the residential and non-residential environmental correlates of recreational walking, using precisely geocoded activity space data. METHODS The point-based locations regularly visited by 4365 participants of the RECORD Cohort Study (Residential Environment and CORonary heart Disease) were collected between 2011 and 2013 in the Paris region using the VERITAS software (Visualization and Evaluation of Regular Individual Travel destinations and Activity Spaces). Zero-inflated negative binomial regressions were used to investigate associations between both residential and non-residential environmental exposure and overall self-reported recreational walking over 7 days. RESULTS Density of destinations, presence of a lake or waterway, and neighborhood education were associated with an increase in the odds of reporting any recreational walking time. Only the density of destinations was associated with an increase in time spent walking for recreational purpose. Considering the recreational locations visited (i.e., sports and cultural destinations) in addition to the residential neighborhood in the calculation of exposure improved the model fit and increased the environment-walking associations, compared to a model accounting only for the residential space (Akaike Information Criterion equal to 52797 compared to 52815). CONCLUSIONS Creating an environment supportive to walking around recreational locations may particularly stimulate recreational walking among people willing to use these facilities.

Using GPS, GIS, and Accelerometer Data to Predict Transportation Modes.

INTRODUCTION Active transportation is a substantial source of physical activity, which has a positive influence on many health outcomes. A survey of transportation modes for each trip is challenging, time-consuming, and requires substantial financial investments. This study proposes a passive collection method and the prediction of modes at the trip level using random forests. METHODS The RECORD GPS study collected real-life trip data from 236 participants over 7 d, including the transportation mode, global positioning system, geographical information systems, and accelerometer data. A prediction model of transportation modes was constructed using the random forests method. Finally, we investigated the performance of models on the basis of a limited number of participants/trips to predict transportation modes for a large number of trips. RESULTS The full model had a correct prediction rate of 90%. A simpler model of global positioning system explanatory variables combined with geographical information systems variables performed nearly as well. Relatively good predictions could be made using a model based on the 991 trips of the first 30 participants. CONCLUSIONS This study uses real-life data from a large sample set to test a method for predicting transportation modes at the trip level, thereby providing a useful complement to time unit-level prediction methods. By enabling predictions on the basis of a limited number of observations, this method may decrease the workload for participants/researchers and provide relevant trip-level data to investigate relations between transportation and health.

Attrition Bias Related to Missing Outcome Data: A Longitudinal Simulation Study

Background: Most longitudinal studies do not address potential selection biases due to selective attrition. Using empirical data and simulating additional attrition, we investigated the effectiveness of common approaches to handle missing outcome data from attrition in the association between individual education level and change in body mass index (BMI). Methods: Using data from the two waves of the French RECORD Cohort Study (N = 7,172), we first examined how inverse probability weighting (IPW) and multiple imputation handled missing outcome data from attrition in the observed data (stage 1). Second, simulating additional missing data in BMI at follow-up under various missing-at-random scenarios, we quantified the impact of attrition and assessed how multiple imputation performed compared to complete case analysis and to a perfectly specified IPW model as a gold standard (stage 2). Results: With the observed data in stage 1, we found an inverse association between individual education and change in BMI, with complete case analysis, as well as with IPW and multiple imputation. When we simulated additional attrition under a missing-at-random pattern (stage 2), the bias increased with the magnitude of selective attrition, and multiple imputation was useless to address it. Conclusions: Our simulations revealed that selective attrition in the outcome heavily biased the association of interest. The present article contributes to raising awareness that for missing outcome data, multiple imputation does not do better than complete case analysis. More effort is thus needed during the design phase to understand attrition mechanisms by collecting information on the reasons for dropout.

What happened in the ‘Move for Well-being in School’: a process evaluation of a cluster randomized physical activity intervention using the RE-AIM framework

BackgroundThe aim of this study was to address the gap in the translation of research into practice through an extensive process evaluation of the Move for Well-being in School programme using the RE-AIM framework. The purpose was to gain insight into the extent by which the intervention was adopted and implemented as intended and to understand how educators observed its effectiveness and maintenance.MethodsPublic schools located in seven municipalities in Denmark were invited to enroll their 4th to 6th grade classes in the project. Of these, 24 school decided to participate in the project in the school-year 2015–16 and were randomly (cluster) allocated to either intervention or control group. A process survey was completed online by school personnel at the start, at midterm, and at the end of the school year. Additionally, informal interviews and observations were conducted throughout the year.ResultsAt the 12 intervention schools, a total of 148 educators were involved in the implementation of the programme over the school-year. More than nine out of ten educators integrated brain breaks in their lessons and practically all the physical education teachers used the physical education lesson plans. The educators delivered on average 4.5 brain breaks per week and up to 90% of the physical education teachers used the project lesson plans for at least half of their classes. Half of the educators initiated new recess activities.A total of 78%, 85% and 90% of the educators believed that the implemented recess, brain break and physical education components ‘to a high degree’ or ‘to some degree’ promoted the pupils’ well-being, respectively.ConclusionsThis study shows that it is possible to design a school-based PA intervention that educators largely adopt and implement. Implementation of the PA elements was stable throughout the school year and data demonstrate that educators believed in the ability of the intervention to promote well-being among the pupils. Finally, the study show that a structured intervention consisting of competence development, set goals for new practices combined with specific materials, and ongoing support, effectively reached a vast majority of all teachers in the enrolled schools with a substantial impact.Trial registrationDate of registration: retrospectively registered on 24 April 2015 at Current Controlled Trials (DOI 0.1186/ISRCTN12496336 – named: “The role of physical activity in improving the well-being of children and youth”).

Short-term association between personal exposure to noise and heart rate variability: The RECORD MultiSensor Study

BACKGROUND Studies revealed long-term associations between noise exposure and cardiovascular health, but the underlying short-term mechanisms remain uncertain. OBJECTIVES To explore the concomitant and lagged short-term associations between personal exposure to noise and heart rate variability (HRV) in a real life setting in the Île-de-France region. METHODS The RECORD MultiSensor Study collected between July 2014 and June 2015 noise and heart rate data for 75 participants, aged 34-74 years, in their living environments for 7 days using a personal dosimeter and electrocardiography (ECG) sensor on the chest. HRV parameters and noise levels were calculated for 5-min windows. Short-term relationships between noise level and log-transformed HRV parameters were assessed using mixed effects models with a random intercept for participants and a temporal autocorrelation structure, adjusted for heart rate, physical activity (accelerometry), and short-term trends. RESULTS An increase by one dB(A) of A-weighted equivalent sound pressure level (Leq) was associated with a 0.97% concomitant increase of the Standard deviation of normal to normal intervals (SDNN) (95% CI: 0.92, 1.02), of 2.08% of the Low frequency band power (LF) (95% CI: 1.97, 2.18), of 1.30% of the High frequency band power (HF) (95% CI: 1.17, 1.43), and of 1.16% of the LF/HF ratio (95% CI: 1.10, 1.23). The analysis of lagged exposures to noise adjusted for the concomitant exposure illustrates the dynamic of recovery of the autonomic nervous system. Non-linear associations were documented with all HRV parameters with the exception of HF. Piecewise regression revealed that the association was almost 6 times stronger below than above 65 Leq dB(A) for the SDNN and LF/HF ratio. CONCLUSION Personal noise exposure was found to be related to a concomitant increase of the overall HRV, with evidence of imbalance of the autonomic nervous system towards sympathetic activity, a pathway to increased cardiovascular morbidity and mortality.