Active Transport Modes Research Articles

Evaluation of long-term effect of pedestrian signage with time travel indication in Grenoble city (France)

Background:French population does not achieve recommended physical activity (PA) level. Promoting walking as an active transport mode through urban environment is a recommended strategy to maintain health. This study assessed long-term effect (1 year) of pedestrian signage in the city of Grenoble (France). The first part of our study focused on the attendance of general population living in Grenoble on two important crossroads in a neighborhood equipped with pedestrian signage. The second one studied the receptiveness to this signage of low to moderate socioeconomic status Grenoble citizens living in this neighborhood. In addition, we tried to evidence the potential impact of this signage in the latter population in term of walking activity, cardiometabolic health and motivation toward PA.Methods:For the first part of the study, we compared the attendance (number of passages manual counting) in Grenoble general population on 2 crossroads in a neighborhood equipped with signage (PSN) with 2 crossroads of a similar neighborhood not equipped (CN). For the second part of the study, we planned to specifically recruit 140 subjects (electoral lists, brochures, phone calls and mailing) in these two neighborhoods (pedestrian signage group: PSG; control group: CG). These subjects were proposed to participate in a follow-up of their health during one year. We asked if they have seen the pedestrian signage and compared these groups on daily steps number (pedometer), cardiometabolic risk (SCORE) and motivation toward PA (Self-Regulation Questionnaire for exercise) over one year period.Results:For the first part of the study, the attendance slightly increased between June and December (effect size: 0.5;p < 0.05) in PSN suggesting a transitory effect of the signage in general population. For the second part, only forty-two subjects (22 in PSG and 20 in CG) accepted to participate in this study. We failed to include low to moderate socio-economic citizens. Seventy percent of the recruited subjects did not see the pedestrian signage. This sample did not change its walking activity level, cardiometabolic risk as well as PA motivation.Conclusion:On the basis of attendance study, such a pedestrian signage might be incentive to increase PA in general population but this needs confirmation. The effects of a larger specific communication associated with this urban environment targeting particular population groups deserve to be studied.

Self-reported versus GPS-derived indicators of daily mobility in a sample of healthy older adults

In light of novel opportunities to use sensor data to observe individuals' day-to-day mobility in the context of healthy aging research, it is important to understand how meaningful mobility indicators can be extracted from such data and to which degree these sensor-derived indicators are comparable to corresponding self-reports. We used sensor (GPS and accelerometer) and self-reported data from 27 healthy older adults (≥67 years) who participated in the MOASIS project over a 30-day period. Based on sensor data we computed three commonly used daily mobility indicators: life space (LS), travel duration using passive (i.e., motorized) modes of transportation (pMOT) and travel duration using active (i.e., non-motorized) modes of transportation (aMOT). We assessed the degree to which these sensor-derived indicators compare to corresponding self-reports at a within-person level, computing intraindividual correlations (iCorrs), subsequently assessing whether iCorrs can be associated with participants’ socio-demographic characteristics on a between-person level. Moderate to large positive mean iCorrs between the respective self-reported and sensor-derived indicators were found (r = 0.75 for LS, 0.51 for pMOT and 0.36 for aMOT). In comparison to sensor-derived indicators, self-reported LS slightly underestimates, while self-reported aMOT as well as pMOT considerably overestimate the amount of daily mobility. Participants with access to a car have higher probabilities of agreement in the pMOT indicator. Sensor-based assessments are promising as they are “objective”, involve less participant burden and observations can be extended over long periods. The findings of this paper help researchers on mobility and aging to estimate the magnitude and direction of potential differences in the assessed variable due to the assessment methods.

Diagnostic analysis of the effects of weather condition on pedestrian crash severity

Pedestrians are vulnerable to severe injury and mortality in road crashes. Numerous studies have attempted to identify factors contributing to crashes and pedestrian injury risks. As an active transport mode, the act of walking is sensitive to changes in weather conditions. However, comprehensive real-time weather data are often unavailable for road safety analysis. In this study, we used a geographical information system approach to integrate high-resolution weather data, as well as their corresponding temporal and spatial distributions, with crash data. Then, we established a mixed logit model to determine the association between pedestrian crash severity and possible risk factors. The results indicate that high temperature and the presence of rain were associated with a higher likelihood of Killed and Severe Injury (KSI) crashes. Also, we found the interaction effects of weather condition (hot weather and presence of rain) on the association between pedestrian crash severity and pedestrian and driver behaviors to be significant. For instance, the effects of jaywalking and risky driving behavior on crash severity were more prevalent under rainy conditions. In addition, the effects of driver inattention and reckless crossing were more significant in hot weather conditions. This has critical policy implications for the development and implementation of proactive traffic management systems. For instance, real-time weather and traffic data should be incorporated into dynamic message signs and in-vehicle warning systems. Doing so will enhance the levels of safety awareness of drivers and pedestrians, especially in adverse weather conditions. As a result, pedestrian safety can be improved over the long term.

“If I had a regular bicycle, I wouldn’t be out riding anymore”: Perspectives on the potential of e-bikes to support active living and independent mobility among older adults in Waterloo, Canada

The predominance of automobile dependency in North America is associated with a host of negative health and environmental impacts and has sparked the promotion of low-carbon and active modes of transportation. Encompassing both priorities, electric-bicycles have become a popular mode of transportation in some parts of the world. While multiple studies have suggested older adult populations may be most likely to benefit from e-bike technology, few studies have exclusively focused on this demographic to identify the factors that may promote or inhibit e-bike adoption amongst this group. This study explores the potential for e-bikes to support independent mobility and active aging among the older adult population in Canada’s auto-dependent context. Guided by a conceptual framework for older adult mobility, this study used qualitative methods to gather perceptual and experiential data from 17 community stakeholders and 37 older adults in the Region of Waterloo, Ontario. The findings highlight the importance of cycling life histories, social connection and physical limitations to adopting cycling later in life. Specific individual and structural factors were discussed in relation to e-bike adoption including facilitators such as increased convenience, reduced physical exertion, reduced reliance on a vehicle and fun. Barriers included cycling infrastructure and road safety, regulation, and stigmatization barriers. E-bikes as a more convenient and supportive mode of transit for older adults is discussed alongside the importance of e-bikes as a replacement for traditional bicycles in a subset of this population.

Potentially Replaceable Car Trips: Assessment of Potential Modal Change towards Active Transport Modes in Vitoria-Gasteiz

Road traffic is the most important contributor to noise and air pollutant emissions in cities. Its substitution by non-motorized modes therefore has great potential to improve the urban environment while increasing levels of physical activity among the population. This paper identifies car trips that could potentially be transferred to active modes such as walking and cycling, and analyses the barriers perceived by people who travel by car. We detect potentially replaceable car trips based on a mobility survey, distance calculation, and a distance threshold approach. The answers to a set of questions in the mobility survey allow us to identify the perceived barriers for use of the bicycle, applied to Vitoria-Gasteiz (Spain). The results show that between 30% and 40% of car trips could be replaced by active modes. Personal safety and distance results are the most limiting barriers perceived by car users, while physical condition and technique are the most limiting ones for bicycle users. These results provide valuable information for implementing measures to promote the replacement of motorized trips with walking and cycling.

Workforce commuting and subjective well-being

Commuting to and from work can constitute a significant proportion of a person’s day and can have a considerable impact on one’s well-being. Using the UK Time Use Survey (UKTUS) dataset, the experienced well-being effects of commuting, in terms of enjoyment, were evaluated relative to other daily activities. Commutes using passive modes of transport (e.g., car, train) were found to be the least enjoyable activities carried out in the day. Commuting using active modes of transport (e.g., cycle, walk) was also amongst the least enjoyable activities, although enjoyment of active commuting was significantly higher than that of passive commuting. This paper also assessed differences in the experienced well-being of other daily activities (such as working and physical exercise) during the workday between those who did and those who did not commute. Using a series of multilevel analyses, commuting was shown to have little impact on an individual’s enjoyment of the other daily activities in which they partake. Enjoyment of all daily activities was found to be just as high on workdays on which participants commuted using active modes of transport as on non-commuting workdays. With the exception of only Personal Care activities and Sleep, there were no meaningful differences in enjoyment of any daily activities between any of the three commuting workday groups and non-commuting workdays.

Bicycle ridership and intention in a northern, low-cycling city

Cycling as a mode of transportation (i.e. utility cycling) has been given heavy attention and investment in North America over the last decade. It is perceived as an environmentally friendly way to travel, leading to benefits for health and traffic alleviation. This study examines the determinants of utility cycling behaviour and intent, and more broadly, active transportation (i.e. cycling and walking) behaviour in Edmonton, Canada – the northernmost North American city with a metropolitan population over one million. With harsh winter weather and low cycling rates, the city presents a unique case study for cycling behavior. In this research, we analyzed 646 responses to a bike ridership survey conducted in 2014 by the City of Edmonton. Borrowing concepts from behaviour theory, public health and transportation engineering we seek to quantify the effects of infrastructure density, traffic attitude, perceived control over time and distance, and traffic stress tolerance perception on cycling for utility purposes, the intention to cycle more frequently, and the use of an active mode of transportation, specifically for a northern and low-cycling city. Three empirical models were developed to describe cycling behaviour using binary logistic regression. Most variables were significant and in line with other study findings in the current literature. Results point at the importance of perceived safety in deciding or intending to cycle, as well as perceived time and distance of travel. Broad policy implications and suggestions for future research are discussed.

Optimizing Safe Routes to School

Safe Routes to School (SRTS) programs provide funding for infrastructure improvements that encourage children to use active transportation (AT) modes such as walking for travel between home and school. In the United States, the federal government distributes funding to states that can be used for SRTS infrastructure improvements. A Safe Routes to School Infrastructure Improvement Model is proposed that can help decision makers prioritize infrastructure improvement projects. This model is applied to the pedestrian network surrounding a school in Santa Barbara, California to demonstrate how it can be used to recommend specific SRTS infrastructure improvements that minimize pedestrian risk while accounting for funding constraints.

Effect of distance from home to school and spatial dependence between homes on mode of commuting to school

Active commuting to school (i.e., walking and cycling) has health implications for young people. Therefore, it of interest to determine how the distance students walk to school varies depending on where they live and how their decision to walk is affected by contextual/environmental variables. This study aimed to examine which of the distances (Euclidean, Manhattan, walking-network and driving-network) is the best predictor of the decision to walk to school and determine the areas of influence of active commuting to school for four high schools in Granada, Spain. To achieve these aims, the regression-kriging method was used. The results indicated that the Euclidean and the walking distances were the best predictors of the decision to walk to school. Spatial dependence produced by some locational variables and spatial contagion among students was found to be moderate to strong. In addition, the spatial range of this spatial dependence is approximately 1000 m to 1600 m. Regression-kriging could be implemented in a geographic information system to determine the areas of influence of schools and aid urban designers and planners in developing neighborhoods that support active modes of commuting. Identifying the areas of influence is important for promoting active modes of transport by local governments.

A Novel Technique to Identify Hot Zones for Active Commuters’ Crashes

This paper presents an approach to identify and rank accident-prone (hot) zones for active transportation modes. The approach aims to extend the well-known empirical Bayes (EB) potential for safety improvement (PSI) method to cases where multiple crash modes are modeled jointly (multivariate modeling). In this study, crash modeling was pursued with a multivariate model, incorporating spatial effects, using the full Bayes (FB) technique. Cyclist and pedestrian crash data for the City of Vancouver (British Columbia, Canada) were analyzed for 134 traffic analysis zones (TAZs) to detect active transportation hot zones. The hot zones identification (HZID) process was based on the estimation of the Mahalanobis distance, which can be considered an extension to the PSI method in the context of multivariate analysis. In addition, a negative binomial model was developed for cyclist and pedestrian crashes, where the EB PSI for each mode crash was quantified. The cyclist and pedestrian PSIs were combined to detect active transportation hot zones. Overall, the Mahalanobis distance method is found to outperform the PSI method in terms of consistency of results; and discrepancy is observed between the hot zones identified using both approaches.

A zonal level safety investigation of pedestrian crashes in Riyadh, Saudi Arabia

In the recent decade, walking has been encouraged as an active mode of transportation, which could reduce congestion and air pollution and also improve community health. However, pedestrians are more vulnerable to traffic crashes compared with other road users, especially in developing countries such as Saudi Arabia. This paper examines the association among traffic volume, land-use, socio-demographic and roadway characteristics factors, and the frequency of pedestrian crashes based on macro-level safety analysis using data from Riyadh, the Capital of Saudi Arabia. Two Bayesian spatial Poisson-lognormal models for total and severe pedestrian crashes are developed in this study. The results show that the factors that affect total pedestrian crash occurrence are different from those affecting severe pedestrian crash. Several implications for pedestrian safety policies in Riyadh are suggested based on the results.

Evaluation of Preferences for Alternative Transportation Services and Loyalty towards Active Transportation during a Major Transportation Infrastructure Disruption

This paper investigates active transportation mode users’ preferences for alternative services during the temporary closure event of a bridge and its active transportation (AT) lanes. It also evaluates the loyalty of AT users during the event. The study uses data from a travel survey distributed to cyclists and pedestrians, who are the regular AT lane users of the Macdonald Bridge in Halifax, Canada. Random parameter logit models are developed in this study that examine the effects of socio-demographic, travel and neighborhood characteristics on active transportation users’ preferences. Four alternative transportation services are considered in this study: free shuttle services, frequent ferry services, frequent bus services and other services. Results suggest that higher-income individuals are more likely to prefer frequent ferry services during the AT lane closure event. Transit commuters are found to prefer frequent bus services. Probability of preferring free shuttle services increases if individuals use AT lanes for cost savings. Loyalty towards AT is explored in this study by means of anticipated modal shift. For instance, higher mixed land use area dwellers tend to be loyal towards AT during the disruption event, as demonstrated by their lower probability to shift from current AT mode. This study offers critical behavioral insights, which would assist transportation planning and policies that aim to adopt sustainable transportation planning measures to retain current users’ loyalty towards active transportation and prevent a long-term behavioral shift.

2448 - Toward Zero Road Death Vision Assessment the Role Auto-Dependency, Public Health, and Active Transportation Modes: 2nd Highest Scoring Abstract: Early career/Post-doctoral

Background One of the most significant costs associated with automobile travel in the US is the number of road accidents and fatalities that this type of transportation incurs. To control these costs, in 2015, the USDOT announced that “zero road deaths” is the official policy of the US federal government transportation safety. This policy envisions zero deaths as the ultimate road safety goal. To achieve this ambition, we need a consistent understanding of all potential determinants of road safety in the national level. Accordingly, this research provides a framework to investigate the impact of a wide range of variables on traffic fatality rates (defined as deaths per 100,000 people). We particularly examine the effect of auto-dependency indicators, public health factors, and active transportation modes on the road safety outcomes. Methods For this purpose, a previously developed conceptual framework has been used which classified road safety contributing factors into seven separate sets: exposure, travel behavior, socio-economics, infrastructure and urban form, safety policies, and mitigating factors such as health care. This framework is tested using series of panel data models. These models investigate both spatial and temporal variations in safety patterns for the fifty states, along with DC, using annual data from 1997 to 2014. A complimentary analysis is conducted to assess the impact of factors which just available for few years of analysis like walking and biking variables. Results The results of our panel models illustrate that two variables Vehicle Miles Traveled and Vehicles per Capita , representing the level of auto-dependency, have the strongest impact on traffic fatalities. The elasticity analysis reveals that a 10% increase in VMT per vehicle is associated with 8.6% increase in road fatalities. Likewise, a 10% increase in vehicle ownership rate results in a 8.0% increase in road fatalities. This is closely followed by Infant Mortality Rates, the proxy that we used to represent the public health care. The results of complimentary analysis show that states with higher urban density, more walking, and more cycling are associated with lower traffic fatality rates. Conclusions Our findings suggest that if additional progress is to be made in reducing traffic fatalities, emphasis needs to move beyond simply focusing on policies such as seat belt laws. This research provides an order of factors influencing road fatalities, this order can help American policy makers to provide a more efficient road map for progress towards zero road death target.

2448 - Toward Zero Road Death Vision Assessment the Role Auto-Dependency, Public Health, and Active Transportation Modes

2nd Highest Scoring Abstract: Early Career/Post-doctoral Background One of the most significant costs associated with automobile travel in the US is the number of road accidents and fatalities that this type of transportation incurs. To control these costs, in 2015, the USDOT announced that “zero road deaths” is the official policy of the US federal government transportation safety. This policy envisions zero deaths as the ultimate road safety goal. To achieve this ambition, we need a consistent understanding of all potential determinants of road safety in the national level. Accordingly, this research provides a framework to investigate the impact of a wide range of variables on traffic fatality rates (defined as deaths per 100,000 people). We particularly examine the effect of auto-dependency indicators, public health factors, and active transportation modes on the road safety outcomes. Methods For this purpose, a previously developed conceptual framework has been used which classified road safety contributing factors into seven separate sets: exposure, travel behavior, socio-economics, infrastructure and urban form, safety policies, and mitigating factors such as health care. This framework is tested using series of panel data models. These models investigate both spatial and temporal variations in safety patterns for the fifty states, along with DC, using annual data from 1997 to 2014. A complimentary analysis is conducted to assess the impact of factors which just available for few years of analysis like walking and biking variables. Results The results of our panel models illustrate that two variables Vehicle Miles Traveled and Vehicles per Capita , representing the level of auto-dependency, have the strongest impact on traffic fatalities. The elasticity analysis reveals that a 10% increase in VMT per vehicle is associated with 8.6% increase in road fatalities. Likewise, a 10% increase in vehicle ownership rate results in a 8.0% increase in road fatalities. This is closely followed by Infant Mortality Rates, the proxy that we used to represent the public health care. The results of complimentary analysis show that states with higher urban density, more walking, and more cycling are associated with lower traffic fatality rates. Conclusions Our findings suggest that if additional progress is to be made in reducing traffic fatalities, emphasis needs to move beyond simply focusing on policies such as seat belt laws. This research provides an order of factors influencing road fatalities, this order can help American policy makers to provide a more efficient road map for progress towards zero road death target.

2459 - Active Transport and Health: Is Employment Essential to Community Change in Developing Countries?

The links between health and physical activity and between physical activity and habitual travel by passive (cars) and active (principally walking and cycling) transport modes have been well explored. As a result, the potential of urban planning strategies that mobilize their potential for achieving significant health and environmental benefits is well established. In developing countries, however, travel patterns are already far more centred on walking, cycling and increasingly, motor cycles. In many cities, this has occurred despite car-centred urban planning, which has boosted road-related deaths and caused air pollution and other related phenomena to soar. In these very different contexts, will strategies tested in developed countries really serve us well, or should we consider employment generation as integral to behavioural change for low- and middle-income communities? Santiago Chile has transitioned rapidly to a car-centred urban transport model, with massive subsidies for highways and other infrastructure that has encouraged sprawling land use policies and high levels of car use. Cars, however, remain the privilege of just 40% of households, given the severe concentration of wealth in this recently democratizing, post-dictatorial society. Health and environmental impacts have been very negative. So too, the effect on social equality, in a city that is already extremely segregated and excluding, as part of the legacy from the military regime's urban policies (1973–1990).Based on recent research (2016–2017) that has combined qualitative (workshops, focus groups) and quantitative methods (surveys, data mining and analysis) under the umbrella of a participation action research methodology this presentation considers the implications, for social change, of high levels of walking, Uneven cycling patterns and spatial segregation in a developing context concludes that including employment programs and cross-cutting gender policies could be essential to fostering active transport and achieving the health, environmental and social equity objectives defined in the Sustainable Development and other global goals. Carefully developed, employment-related measures could make a substantial contribution to health and social equity.

2458 - Assessment of Advantages of Transit-oriented Developments over Traditional Auto-oriented Land Development: A Case Study

Background Transit oriented developments (TOD's) are a type of urban development that emphasize diversity in land use and concurrence of more sustainable modes of transport. Particular emphasis in TOD is given to active (Waling and Cycling) and semi-active (Transit) transport modes. The aim of the study is two-fold: demonstrates the advantages of transit-oriented developments including benefits to public health, and demonstrate a suitable analysis framework and structure for conducting similar studies. Methods A residential area at the outskirts of Dubai is used as a case study. Travel demand forecasting models were used to estimate changes in trip generation, distribution, mode choice, and route assignment brought about by the relocation of destinations. To account for normal variation and uncertainty, three travel mode choice shift scenarios and corresponding changes in distances walked and cycled were estimated based on published rates, local conditions and culture. Changes were mapped to health, environmental, energy, and economic benefits. On health, reductions in obesity, high blood pressure and high blood cholesterol, and heart attach were estimated based on published rates. Economic benefits (reduced mortality) were evaluated using HEAT (Health Economic Assessment Tool). Aggregate reductions in energy consumption, carbon dioxide emissions, travel time and operating costs (of private vehicles) were all estimated. Health benefits due to reductions in pollution were not estimated. Results A framework quantifying the health benefits of TOD was proposed and implemented. Travel demand changes were mapped to health benefits. The walk/cycle plus transit (to reach destination) scenario and yearly benefits due to reduced mortality was $1,797 and $8,343 for the conservative and optimistic scenarios, respectively; for the Walk/Cycle the values are $10,973 and $50,941. That a specific amount of health-induced economic gain may be estimated in conjunction with TOD's using the proposed framework is the more relevant outcome. Conclusions Estimating health gains, environmental improvements, and economic benefits of TOD implementation were possible using standard travel demand forecasting models. Mapping travel changes to health and other benefits is key to quantifying different benefits of TOD's. Normal variation and uncertainty precipitated by variations in policies, local environments and cultures may be accounted for by considering a range of scenarios.

Park ‘n’ Roll: Identifying and Prioritizing Locations for New Bicycle Parking in Québec City, Canada

Promoting active modes of transportation, such as cycling, is an ongoing challenge faced by many cities around the world. Fostering a bicycle culture in an auto-dominant region is riddled with challenges, but success has been achieved with investments in bicycle infrastructure, including bicycle parking. This study presents a new methodology to identify the optimal locations to install short-term (bicycle racks) and long-term (bicycle lockers or indoor locking facilities) bicycle parking using a GIS-based approach that considers multiple criteria. Using Québec City, Canada, as a case study, our methodology considers multiple criteria related to the demand for bicycle parking, including the destinations of existing and potential cyclists and proximity to a frequent bus service. A prioritization index is developed to identify the optimal locations for long-term and short-term bicycle parking. This is followed by a recommendation of the number of bicycle parking spaces required to meet existing and potential demand. This paper aims to provide practitioners with an easy-to-use method to aid in the planning of new bicycle parking infrastructure, which is designed to be flexible and adaptable to other contexts.

Using propensity score matching technique to address self-selection in transit-oriented development (TOD) areas

Many studies have investigated the effects of transit-oriented development (TOD) on travel behavior, especially on transit ridership. However, most studies do not explicitly and effectively address the issue of residential self-selection in their analyses. The aim of this paper is to use cross-sectional data and propensity score matching (PSM) technique to quantify the contribution of residential self-selection to the analysis of mode choice in TOD areas across the metropolitan areas of Washington, D.C. and Baltimore, MD. The authors use PSM because it does not make substantive assumptions to the structure of the self-selection problem (e.g., explicit modeling of outcome and treatment). The results of PSM indicate that, even though the self-selection effect is considerable in the analysis of mode choice in TOD areas (about 7.65% in Washington, D.C. and 5.05% in Baltimore), living in TOD still has a significant impact on encouraging transit and other active modes of transportation.

Impact of weather conditions on middle school students’ commute mode choices: Empirical findings from Beijing, China

Weather conditions have been recognized as important factors affecting school commute mode choices. This paper aims to explore the modal shift of middle school commutes with respect to the variation in weather-related variables, with empirical emphases on the situation in Beijing, China. Data from the latest Beijing School Commute Survey (2014–2015) were adopted, and multinomial probit (MNP) and multinomial logit (MNL) models were developed. The modeling results are in favor of the MNP model because it has better statistical performance. Weather-related variables, including sky condition, wind speed, highest temperature, humidity, air quality index (AQI), and some interaction terms, were found to have a significant impact on students' commute mode choices. Based on these models, an empirical sensitivity measure was defined as the expected percentage change in the probability of choosing each mode with respect to an order of magnitude change in the influential factors. Most of the results are in line with those of previous studies, and some unique results reflect features of Beijing. For example, on days with extremely poor air quality, students are more likely to turn to public transport rather than use a car from active transportation modes. This is probably due to the special urban traffic regulations that restrict household car ownership and car travel in Beijing. These findings could have implications for promoting active transportation for students and serve as references for policymakers and planners.

Associations Between School Transport And Obesity By Gender, Grade, Physical Activity, Ethnicity, And Economic Disadvantage

PURPOSE: To examine the prevalence of school transport modes and obesity by gender, grade, physical activity, race/ethnicity, and economic disadvantage in a representative sample of Texas school children. METHODS: Cross-sectional data on reported sociodemographic characteristics, school transport mode, and physical activity behavior were collected from the Texas School Physical Activity and Nutrition (SPAN) Survey, 2015-2016. Measured height and weight were used to calculate BMI and classify 4th, 8th, and 11th grade students by obesity status. The sampling frame had 14,976 students from 452 schools to provide weighted state-level estimates by grade. Descriptive statistics and associations were conducted between school transport modes and obesity. Interaction terms were included to test if school transport mode-obesity associations differed by gender, grade, physical activity, race/ethnicity, or economic disadvantage. RESULTS: Participants were predominately Hispanic (69.8%), normal weight (55.8%), used passive school transport modes (90.9%), and did not meet physical activity guidelines (82.4%). Active and passive school transport modes were not significantly associated with obesity (all ps>0.05). Gender, race/ethnicity, physical activity, and economic disadvantage were significantly associated with obesity (all ps<0.05). Bike to school by race/ethnicity and walk to school by grade were significantly associated with obesity (all ps<0.05). Hispanic/AA students who biked to school were significantly more likely to have obesity compared to White/Other students who did not bike to school (OR=5.48, p<0.05, 95% CI: 1.25, 24.00). Students in 8th grade who walked to school were significantly less likely to have obesity than 4th/11th grade students who did not walk to school (OR=0.42, p<0.05, 95% CI: 0.19, 0.91). CONCLUSIONS: These findings suggest that associations between active school transport modes and obesity differ by sociodemographic characteristics, including race/ ethnicity and grade. Population-based approaches to childhood obesity prevention may benefit from understanding disparities in opportunities for school transport modes. Supported by the Texas DSHS with funds from the Title V MCH Block Grant to Texas, the CDC HHS Block Grant, and the Michael & Susan Dell Foundation.