Multifaceted Scoping Review of Black/African American Transportation and Land Use Expert Recommendations on Activity-Friendly Routes to Everyday Destinations.

Promoting physical activity (PA) at the community level is a complex, multisector approach requiring researchers and practitioners to impact the individual, interpersonal, environment, and policy levels. One such strategy aiming to impact systems, policies, and environments is the Centers for Disease Control and Prevention's Activity Friendly Routes to Everyday Destinations (Routes to Destinations). This strategy specifically aims to connect pedestrian, bicycle, and public transportation systems with built environment and land use destinations. This article examines Black/African American transportation and land use experts' perspectives and concerns-across multiple mediums-around inequities that have discouraged PA among Black/African American persons specifically Routes to Destinations strategies. In March 2021, a multifaceted scoping review was conducted of peer-reviewed literature, gray literature, and social media authored by Black/African American transportation and land use experts focusing on policy, system, and environmental changes which promote or discourage equitable and inclusive access to physical activity. Themes from peer-reviewed and gray literature resources included: (1) Assessing Racism, Discrimination, and Segregation; (2) Addressing Equity and Inclusion Through Policy; (3) Community Engagement and Place-Based Interventions; (4) Infrastructure Changes; (5) Safety; and (6) Reporting Health Disparities. Twitter topic models suggested the main topics included elements of race/racism, equity, safety, infrastructure, and advancing social justice. Experts called for systemic and systematic change through new policies and implementation of existing policies as well as enhanced community inclusion in decision-making through ownership of policy and built environment change. Safety was discussed differently between peer-reviewed and gray literature and Twitter discussions indicating a publication bias.

Investigation on the driver-victim pairs in pedestrian and bicyclist crashes by latent class clustering and random forest algorithm.

Pedestrians and bicyclists from marginalized and underserved populations experienced disproportionate fatalities and injury rates due to traffic crashes in the US. This disparity among road users of different races and the increasing trend of traffic risk for underserved racial groups called for an urgent agenda for transportation policy making and research to ensure equity in roadway safety. Pedestrian and bicyclist crashes involved drivers and pedestrians/bicyclists; the latter were usually victims. Traditional safety studies did not account for the interaction between the two parties and assumed that they were independent from each other. In this study we paired the driver and pedestrian/bicyclist involved in the same crash to understand the socioeconomic and demographic make-up of the two parties involved in crashes and assessed the geographic distribution of these crashes and crash-contributing factors. For this purpose, we applied thelatent class clustering analysis (LCA) to classify different crash types and analyze the patterns of the crashes based on the income and ethnicity of both drivers and victims involved in pedestrian and bicyclist crashes. We then used random forest algorithms and partial dependence plots (PDPs) to model and interpreted the contributing factors of the clusters in both pedestrian and bicyclist models. The clustering results showed a pattern of social segregation in pedestrian and bicyclist crashes that drivers and victims with similar socioeconomic characteristics tend to be involved in one crash. Pedestrian/bicyclist exposure, driver's age, victim's age, year of the car in use, annual average daily traffic (AADT), speed limit, roadbed width, and lane width were the most influential factors contributing to this pattern. Crashes that involved drivers and victims with lower income and non-white ethnicity tended to happen in the location with higher pedestrian/bicyclist exposure, higher speed limit, and wider road. The findings of this research can help to inform the decision-making process for improving safety to ensure equitable and sustainable safety for all road users and communities.

Exploration of the effect of violent crime on recreational and transportation walking by path and structural equation models.

To examine how violent crime affects people's recreational and transportation walking duration in daytime and after dark on a typical day, this study undertakes associative and causal analyses with geo-referenced crime data, street-audit data, and data collected through an intercept survey in a three-municipality region of New Jersey that is predominantly inhabited by low-income and minority populations. Survey data was collected from 1173 respondents at 87 intersections selected by stratified random sampling. Similar to many past studies using associative methods, correlation analysis and ordered logit models showed mostly counterintuitive results. However, sequential or causal models, including path and structural equation (SE) models, showed that recorded crime increases fear of crime and chances of victimization, which in turn decrease walking duration for both recreation and transportation. The study concludes that even if people walk more in high-crime areas because of nearby destinations and lack of alternatives, crime may still have an adverse effect on walking, meaning that people in those neighborhoods would have walked even more if not for high crime.