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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.Electronic supplementary materialThe online version of this article (doi:10.1186/s12966-014-0124-x) contains supplementary material, which is available to authorized users.

Environmental health studies have examined associations between context and health with individuals as statistical units. However, investigators have been unable to investigate momentary exposures, and such studies are often vulnerable to confounding from, for example, individual-level preferences. We present a Global Positioning System (GPS)-based methodology for segmenting individuals' observation periods into visits to places and trips, enabling novel life-segment investigations and case-crossover analysis for improved inferences. We analyzed relationships between built environments and walking in trips. Participants were tracked for 7 days with GPS receivers and accelerometers and surveyed with a Web-based mapping application about their transport modes during each trip (Residential Environment and Coronary Heart Disease (RECORD) GPS Study, France, 2012-2013; 6,313 trips made by 227 participants). Contextual factors were assessed around residences and the trips' origins and destinations. Conditional logistic regression modeling was used to estimate associations between environmental factors and walking or accelerometry-assessed steps taken in trips. In case-crossover analysis, the probability of walking during a trip was 1.37 (95% confidence interval: 1.23, 1.61) times higher when trip origin was in the fourth (vs. first) quartile of service density and 1.47 (95% confidence interval: 1.23, 1.68) times higher when trip destination was in the fourth (vs. first) quartile of service density. Green spaces at the origin and destination of trips were also associated with within-individual, trip-to-trip variations in walking. Our proposed approach using GPS and Web-based surveys enables novel life-segment epidemiologic investigations.

BackgroundPhysical activity is considered as a major component of a healthy lifestyle. However, few studies have examined the relationships between the spatial accessibility to sport facilities and sport practice with a sufficient degree of specificity. The aim of this study was to investigate the associations between the spatial accessibility to specific types of sports facilities and the practice of the corresponding sports after carefully controlling for various individual socio-demographic characteristics and neighborhood socioeconomic variables.MethodsData from the RECORD Study involving 7290 participants recruited in 2007–2008, aged 30–79 years, and residing in the Paris metropolitan area were analyzed. Four categories of sports were studied: team sports, racket sports, swimming and related activities, and fitness. Spatial accessibility to sport facilities was measured with two complementary approaches that both take into account the street network (distance to the nearest facility and count of facilities around the dwelling). Associations between the spatial accessibility to sport facilities and the practice of the corresponding sports were assessed using multilevel logistic regression after adjusting for individual and contextual characteristics.ResultsHigh individual education and high household income were associated with the practice of racket sports, swimming or related activities, and fitness over the previous 7 days. The spatial accessibility to swimming pools was associated with swimming and related sports, even after adjustment for individual/contextual factors. The spatial accessibility to facilities was not related to the practice of other sports. High neighborhood income was associated with the practice of a racket sport and fitness.ConclusionsAccessibility is a multi-dimensional concept that integrates educational, financial, and geographical aspects. Our work supports the evidence that strategies to increase participation in sport activities should improve the spatial and financial access to specific facilities, but also address educational disparities in sport practice.

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Road traffic and related noise is a major source of annoyance and impairment to health in urban areas. Many areas exposed to road traffic noise are also exposed to rail and air traffic noise. The resulting annoyance may depend on individual/neighborhood socio-demographic factors. Nevertheless, few studies have taken into account the confounding or modifying factors in the relationship between transportation noise and annoyance due to road traffic. In this study, we address these issues by combining Geographic Information Systems and epidemiologic methods. Street network buffers with a radius of 500 m were defined around the place of residence of the 7290 participants of the RECORD Cohort in Ile-de-France. Estimated outdoor traffic noise levels (road, rail, and air separately) were assessed at each place of residence and in each of these buffers. Higher levels of exposure to noise were documented in low educated neighborhoods. Multilevel logistic regression models documented positive associations between road traffic noise and annoyance due to road traffic, after adjusting for individual/neighborhood socioeconomic conditions. There was no evidence that the association was of different magnitude when noise was measured at the place of residence or in the residential neighborhood. However, the strength of the association between neighborhood noise exposure and annoyance increased when considering a higher percentile in the distribution of noise in each neighborhood. Road traffic noise estimated at the place of residence and road traffic noise in the residential neighborhood (75th percentile) were independently associated with annoyance, when adjusted for each other. Interactions of effects indicated that the relationship between road traffic noise exposure in the residential neighborhood and annoyance was stronger in affluent and high educated neighborhoods. Overall, our findings suggest that it is useful to take into account (i) the exposure to transportation noise in the residential neighborhood rather than only at the residence, (ii) different percentiles of noise exposure in the residential neighborhood, and (iii) the socioeconomic characteristics of the residential neighborhood to explain variations in annoyance due to road traffic in the neighborhood.

BackgroundWalkable neighborhoods are purported to impact a range of cardiometabolic outcomes through increased walking, but there is limited research that examines multiple cardiometabolic outcomes. Additionally, few Walk Score (a novel measure of neighborhood walkability) studies have been conducted in a European context. We evaluated associations between neighborhood Walk Score and selected cardiometabolic outcomes, including obesity, hypertension and heart rate, among adults in the Paris metropolitan area.Methods and resultsWe used data from the second wave of the RECORD Study on 5993 participants recruited in 2011–2014, aged 34–84 years, and residing in Paris (France). To this existing dataset, we added Walk Score values for participants’ residential address. We used multilevel linear models for the continuous outcomes and modified Poisson models were used for our categorical outcomes to estimate associations between the neighborhood Walk Score (both as a continuous and categorical variable) (0–100 score) and body mass index (BMI) (weight/height2 in kg/m2), obesity (kg/m2), waist circumference (cm), systolic blood pressure (SBP) (mmHg), diastolic blood pressure (DBP) (mmHg), hypertension (mmHg), resting heart rate (RHR) (beats per minute), and neighborhood recreational walking (minutes per week). Most participants lived in Walker’s Paradise (48.3%). In multivariate models (adjusted for individual variables, neighborhood variables, and risk factors for cardiometabolic outcomes), we found that neighborhood Walk Score was associated with decreased BMI (β: -0.010, 95% CI: -0.019 to −0.002 per unit increase), decreased waist circumference (β: -0.031, 95% CI: -0.054 to −0.008), increased neighborhood recreational walking (β: +0.73, 95% CI: +0.37 to +1.10), decreased SBP (β: -0.030, 95% CI: -0.063 to −0.0004), decreased DBP (β: -0.028, 95% CI: -0.047 to −0.008), and decreased resting heart rate (β: -0.026 95% CI: -0.046 to −0.005).ConclusionsIn this large population-based study, we found that, even in a European context, living in a highly walkable neighborhood was associated with improved cardiometabolic health. Designing walkable neighborhoods may be a viable strategy in reducing cardiovascular disease prevalence at the population level.

Background: Few studies have used GPS data to analyze the relationship between Walk Score, transportation choice and walking. Additionally, the influence of Walk Score is understudied using trips rather than individuals as statistical units. The purpose of this study is to examine associations at the trip level between Walk Score, transportation mode choice, and walking among Paris adults who were tracked with GPS receivers and accelerometers in the RECORD GPS Study. Methods: In the RECORD GPS Study, 227 participants were tracked during seven days with GPS receivers and accelerometers. Participants were also surveyed with a GPS-based web mapping application on their activities and transportation modes for all trips (6969 trips). Walk Score, which calculates neighborhood walkability, was assessed for each origin and destination of every trip. Multilevel logistic and linear regression analyses were conducted to estimate associations between Walk Score and walking in the trip or accelerometry-assessed number of steps for each trip, after adjustment for individual/neighborhood characteristics. Results: The mean overall Walk Scores for trip origins were 87.1 (SD = 14.4) and for trip destinations 87.1 (SD = 14.5). In adjusted trip-level associations between Walk Score and walking only in the trip, we found that a walkable neighborhood in the trip origin and trip destination was associated with increased odds of walking in the trip assessed in the survey. The odds of only walking in the trip were 3.48 (95% CI: 2.73 to 4.44) times higher when the Walk Score for the trip origin was “Walker’s Paradise” compared to less walkable neighborhoods (Very/Car-Dependent or Somewhat Walkable), with an identical independent effect of trip destination Walk Score on walking. The number of steps per 10 min (as assessed with accelerometry) was cumulatively higher for trips both originating and ending in walkable neighborhoods (i.e., “Very Walkable”). Conclusions: Walkable neighborhoods were associated with increases in walking among adults in Paris, as documented at the trip level. Creating walkable neighborhoods (through neighborhood design increased commercial activity) may increase walking trips and, therefore, could be a relevant health promotion strategy to increase physical activity.