Design of a Location-Based Case-Control Study of Built Environment Risk Factors for Pedestrian Fatalities in the U.S.

The location-based case-control design is a useful approach for studies where the exposures of interest are aspects of the environment around the location of a health event such as a pedestrian fatality. In this design locations are the unit of analysis and an enumerated cohort of locations are followed through time for the health events of interest and a case-control study of locations is nested within the cohort. Locations where events occurred (case-locations) are compared to matched locations where these events did not occur (control-locations). We describe the application of this design to the issue of pedestrian fatalities using a cohort of 9,612,698 intersections, 17,737,728 road segments, and 222,318 entrance/exit ramp segments that existed in 2017 across all 384 U.S. Metropolitan Statistical Areas. This cohort of locations was followed up from Jan 1, 2017 to Dec 31, 2018 for pedestrian fatalities using the National Highway Traffic Safety Administration Fatality Analysis Reporting System. In total, 10,587 fatalities were identified as having occurred on cohort locations and 21,174 matched control locations were selected using incidence density sampling. Geographic information systems, spatially linked administrative data sets and virtual neighborhood audits via Google Street View are underway to characterize study locations.

Database Integration Correlates Street Crossing Design Strategies With Pedestrian Injury.

INTRODUCTION: Transportation databases have limited data regarding injury severity of pedestrian versus automobile patients. To identify opportunities to reduce injury severity, transportation and trauma databases were integrated to examine the differences in pedestrian injury severity at street crossings that were signalized crossings (SCs) versus nonsignalized crossings (NSCs). It was hypothesized that trauma database integration would enhance safety analysis and pedestrians struck at NSC would have greater injury severity. METHODS: Single-center retrospective review of all pedestrian versus automobile patients treated at a level 1 trauma center from 2014 to 2018 was performed. Patients were matched to the transportation database by name, gender, and crash date. Google Earth Pro satellite imagery was used to identify SC versus NSC. Injury severity of pedestrians struck at SC was compared to NSC. RESULTS: A total of 512 patients were matched (median age = 41 y [Q1 = 26, Q3 = 55], 74% male). Pedestrians struck at SC (n = 206) had a lower injury severity score (ISS) (median = 9 [4, 14] versus 17 [9, 26], P < 0.001), hospital length of stay (median = 3 [0, 7] versus 6 [1, 15] days, P < 0.001), and mortality (21 [10%] versus 52 [17%], P = 0.04), as compared to those struck at NSC (n = 306). The transportation database had a sensitivity of 63.4% (55.8%-70.4%) and specificity of 63.4% (57.7%-68.9%) for classifying severe injuries (ISS >15). CONCLUSIONS: Pedestrians struck at SC were correlated with a lower ISS and mortality compared to those at NSC. Linkage with the trauma database could increase the transportation database's accuracy of injury severity assessment for nonfatal injuries. Database integration can be used for evidence-based action plans to reduce pedestrian morbidity, such as increasing the number of SC.

A National Study on the Comparative Burden of Pedestrian Injuries from Falls Relative to Pedestrian Injuries from Motor Vehicle Collisions.

Pedestrian injuries from falls are an understudied cause of morbidity. Here, we compare the burden of pedestrian injuries from falls occurring on streets and sidewalks with that from motor vehicle collisions. Data on injurious falls on streets and sidewalks, and pedestrian-motor vehicle collisions, to which Emergency Medical Services responded, along with pedestrian and incident characteristics, were identified in the 2019 National Emergency Medical Services Information System database. In total, 118,520 injurious pedestrian falls and 33,915 pedestrians-motor vehicle collisions were identified, with 89% of the incidents occurring in urban areas. Thirty-two percent of pedestrians struck by motor vehicles were coded as Emergent or Critical by Emergency Medical Services, while 19% of pedestrians injured by falls were similarly coded. However, the number of pedestrians whose acuity was coded as Emergent or Critical was 2.1 times as high for injurious falls as compared with pedestrians-motor vehicle collisions. This ratio was 3.9 for individuals 50 years and older and 6.1 for those 65 years and older. In conclusion, there has been substantial and appropriate policy attention given to preventing pedestrian injuries from motor vehicles, but disproportionately little to pedestrian falls. However, the population burden of injurious pedestrian falls is significantly greater and justifies an increased focus on outdoor falls prevention, in addition to urban design, policy, and built environment interventions to reduce injurious falls on streets and sidewalks, than currently exists across the USA.

Q-learning and fuzzy logic multi-tier multi-access edge clustering for 5g v2x communication.

The 5th generation (5 G) network is required to meet the growing demand for fast data speeds and the expanding number of customers. Apart from offering higher speeds, 5 G will be employed in other industries such as the Internet of Things, broadcast services, and so on. Energy efficiency, scalability, resiliency, interoperability, and high data rate/low delay are the primary requirements and obstacles of 5 G cellular networks. Due to IEEE 802.11p's constraints, such as limited coverage, inability to handle dense vehicle networks, signal congestion, and connectivity outages, efficient data distribution is a big challenge (MAC contention problem). In this research, vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I) and vehicle-to-pedestrian (V2P) services are used to overcome bandwidth constraints in very dense network communications from cellular tool to everything (C-V2X). Clustering is done through multi-layered multi-access edge clustering, which helps reduce vehicle contention. Fuzzy logic and Q-learning and intelligence are used for a multi-hop route selection system. The proposed protocol adjusts the number of cluster-head nodes using a Q-learning algorithm, allowing it to quickly adapt to a range of scenarios with varying bandwidths and vehicle densities.

A Feasibility Randomized Trial Evaluating Safe Peds: A Virtual Reality Training Program to Teach Children When to Cross Streets Safely.

OBJECTIVE: Injury as pedestrians is a leading contributor to childhood deaths. This study evaluated the effectiveness of Safe Peds, a fully immersive virtual reality training program to teach children when to cross street safely, with the focus on a number of foundational skills and practicing these in traffic situations of varying complexity. METHODS: Children 7-10 years old were randomly assigned to a control (N = 31) or intervention (N = 26) group. Eligibility criteria included English speaking and typically developing. Testing took place on campus. All children completed pre- and post-testing measures, with those in the intervention group receiving training in between. Training comprised 1 session with 3 phases for a total of up to 1.5 hr and was tailored to each child's performance over trials. On each trial, children decided when to cross and fully executed this crossing, with measures automatically taken by the system as they did so. RESULTS: Negative binomial regression and analysis of covariance tests were applied, predicting post-test scores while controlling for pre-test scores, age, and sex. The intervention was effective in improving children's street crossing skills, including stopping and checking skills (stop at the curb, look left/right/left, check for traffic before crossing the yellow line), and choosing safe inter-vehicle gaps. Children in the control group did not show significant improvements in any crossing skills. CONCLUSIONS: The Safe Peds program effectively teaches children skills to support their deciding when to safely cross in a variety of traffic situations. Implications for pedestrian injury are discussed.

Teaching children pedestrian safety in virtual reality via smartphone: a noninferiority randomized clinical trial.

OBJECTIVE: To evaluate whether child pedestrian safety training in a smartphone-based virtual reality (VR) environment is not inferior to training in a large, semi-immersive VR environment with demonstrated effectiveness. METHODS: Five hundred 7- and 8-year-old children participated; 479 were randomized to one of two conditions: Learning to cross streets in a smartphone-based VR or learning in a semi-immersive kiosk VR. The systems used identical virtual environments and scenarios. At baseline, children's pedestrian skills were assessed in both VR systems and through a vehicle approach estimation task (judging speed/distance of oncoming traffic on monitor). Training in both conditions comprised at least six 30-min sessions in the randomly assigned VR platform and continued for up to 25 visits until adult-level proficiency was obtained. Following training and again 6 months later, children completed pedestrian safety assessments identical to baseline. Three outcomes were considered from assessments in each VR platform: Unsafe crossings (collisions plus close calls), time to contact (shortest time between child and oncoming simulated traffic), and missed opportunities (unselected safe opportunities to cross). RESULTS: Participants achieved adult-level street-crossing skill through VR training. Training in a smartphone-based VR system was generally not inferior to training in a large semi-immersive VR system. There were no adverse effects. CONCLUSIONS: Seven- and 8-year-old children can learn pedestrian safety through VR-based training, including training in a smartphone-based VR system. Combined with recent meta-analytic results, the present findings support broad implementation and dissemination of child pedestrian safety training through VR, including smartphone-based VR systems.

Comparison of the number of pedestrian and cyclist injuries captured in police data compared with health service utilisation data in Toronto, Canada 2016-2021.

INTRODUCTION: Pedestrian and cyclist injuries represent a preventable burden to Canadians. Police-reported collision data include information on where such collisions occur but under-report the number of collisions. The primary objective of this study was to compare the number of police-reported collisions with emergency department (ED) visits and hospitalisations in Toronto, Canada. METHODS: Police-reported collisions were provided by Toronto Police Services (TPS). Data included the location of the collision, approximate victim age and whether the pedestrian or cyclist was killed or seriously injured. Health services data included ED visits in the National Ambulatory Care Reporting System and hospitalisations from the Discharge Abstract Database using ICD-10 codes for pedestrian and cycling injuries. Data were compared from 2016 to 2021. RESULTS: Injuries reported in the health service data were higher than those reported in the TPS for cyclists and pedestrians. The discrepancy was the largest for cyclists treated in the ED, with TPS capturing 7.9% of all cycling injuries. Cyclist injuries not involving a motor vehicle have increased since the start of the pandemic (from 3629 in 2019 to 5459 in 2020 for ED visits and from 251 in 2019 to 430 for hospital admissions). IMPLICATIONS: While police-reported data are important, it under-reports the burden. There have been increases in cyclist collisions not involving motor vehicles and decreases in pedestrian injuries since the start of the pandemic. The results suggest that using police data alone when planning for road safety is inadequate, and that linkage with other health service data is essential.

Ascertainment and description of pedestrian and bicycling injuries and fatalities in Ontario from administrative health records 2003-2017: contributions of non-collision falls and crashes.

INTRODUCTION: Pedestrian and bicycling injuries may be less likely to be captured by traffic injury surveillance relying on police reports. Non-collision injuries, including pedestrian falls and single bicycle crashes, may be more likely than motor vehicle collisions to be missed. This study uses healthcare records to expand the ascertainment of active transportation injuries and evaluate their demographic and clinical features. METHODS: We identified pedestrian and bicyclist injuries in records of deaths, hospitalisations and emergency department visits in Ontario, Canada, between 2002 and 2017. We described the most common types of clinical injury codes among these records and assessed overall counts and proportions of injury types captured by each ascertainment definition. We also ascertained relevant fall injuries where the location was indicated as 'street or highway'. RESULTS: Pedestrian falls represented over 50% of all pedestrian injuries and affected all age groups, particularly non-fatal falls. Emergency department records indicating in-traffic bicycle injuries not involving a collision with motor vehicles increased from 14% of all bicycling injury records in 2003 to 34% in 2017. The overall number of injuries indicated by these ascertainment methods was substantially higher than official counts derived from police reports. CONCLUSION: The use of healthcare system records to ascertain bicyclist and pedestrian injuries, particularly to include non-collision falls, can more fully capture the burden of injury associated with these transportation modes.

Familial aggregation of traffic risky behaviours among pedestrians: a cross-sectional study in northwestern Iran.

OBJECTIVE: This study aims to assess the familial aggregation of traffic risky behaviours among pedestrians and describe the sociodemographic profile of pedestrians in northwestern Iran. METHODS: A cross-sectional study was conducted among 933 pedestrians in 2023. Participants were selected using stratified random sampling. Traffic risky behaviour was measured using a validated instrument among heads of households and their first relatives. The generalised estimating equations were computed to estimate the adjusted OR and 95% CI for familial aggregation of traffic risky behaviours. RESULTS: Of the total sample, 52.2% and 27.7% of the participants were male and aged 41-50, respectively. The majority of respondents were categorised in middle socioeconomic class (36.9%). The OR for familial aggregation of traffic risky behaviours was 1.42 (95% CI 1.07 to 1.89), indicating that the presence of traffic risky behaviours in at least one family member increased the likelihood of similar behaviour in other members. Fathers showing violation behaviours were associated by 1.98-fold increase in violation behaviours among their offspring. Similarly, the existence of violation behaviour in one sibling increased the odds of violation behaviour among other siblings (OR 1.99, 95% CI 1.18 to 3.73). CONCLUSIONS: This study revealed the familial aggregation of traffic risky behaviours of pedestrians, with father-offspring and sibling aggregations emerging as prominent components of familial aggregation. The findings suggested that family-based prevention programmes may yield greater effectiveness than individual-based approaches. As such, implementing targeted interventions focusing on family might have a substantial impact on reducing pedestrian traffic risky behaviours.

Community and multisector partner engagement in US Vision Zero plan development.

BACKGROUND: Vision Zero aims to eliminate serious and fatal road injuries using a Safe System approach. Safe System principles establish that safety is a shared responsibility; this involves both multisector partners and community engagement. This descriptive study explored multisector partners and community engagement in the development of municipal Vision Zero plans. METHODS: We reviewed all first edition Vision Zero plans published by US municipalities from 2014 to 2022. Using a structured coding tool, we abstracted partner involvement and community engagement strategies used in the development of Vision Zero plans. RESULTS: We identified, reviewed and abstracted 64 plans. The average number of partner groups per plan was 11.5 (12.0 for municipalities with a population ≥150 000; 10.1 for municipalities <150 000) and was higher for later plans (11.9 for plans published 2019-2022; 10.0 for plans published 2014-2018). Common partner groups engaged in the plan were law enforcement (85.9% of plans), local transportation planning (78.3%), mayor/city council/city manager (78.1%), engineering/public works (78.1%) and schools (73.4%). Community engagement strategies were reported in 71.9% of the plans and were more frequent among municipalities with a population ≥150 000 (76.1%) compared with a population <150 000 (61.1%), and in those with more recent plans (82.1%) versus earlier ones (56.0%). The most common community engagement strategies were public meetings, online surveys and map mark-ups. CONCLUSIONS: These findings highlight the extent to which Vision Zero plans were aligned with core Safe System tenets regarding diverse partner involvement and community engagement. Plan developers should consider the translation of Safe System principles in Vision Zero plan development.

Physical environmental roadway interventions and injury and death for vulnerable road users: a natural experiment in New York City.

INTRODUCTION: This study examined the effectiveness of three physical environmental roadway interventions (enhanced crossings, speed humps, and turn traffic calming) in preventing crashes involving pedestrian and cyclist injury and mortality in New York City. METHODS: We examined crashes that occurred within a 100-foot radius of intervention and control sites from 2015 to 2019. We used a staggered difference-in-difference design to estimate the association between each intervention type and pedestrian and cyclist crash outcomes. RESULTS: Estimates for enhanced crossings and speed humps included the possibility of no association with crashes, but estimates for turn traffic calming interventions showed reduced odds of crashes involving pedestrian injury by 16% (OR 0.84, 95% CI 0.74 to 0.95) and crashes involving pedestrian fatality by 80% (OR 0.20, 95% CI 0.08 to 0.47). When stratifying by street segment length as a proxy for areas with high speeding risk, turn traffic calming treatments appeared to be most effective at intersections connected to long street segments. DISCUSSION: Turn traffic calming may substantially reduce crash risks for pedestrians. Municipalities can prioritise this physical environmental intervention, especially at turns near long street segments, as a low-cost intervention with substantial public health impact.

Prevalence of vision zero action plans or strategies: USA, 2021.

BACKGROUND: Vision Zero is a strategy to eliminate traffic fatalities and to promote equitable mobility options for all road users. Using a nationally representative survey, we aimed to estimate the prevalence of Vision Zero action plans or strategies in the USA. METHODS: Municipal officials were surveyed in 2021. In this cross-sectional study, we calculated the prevalence of Vision Zero plans or strategies and compared municipalities with adjusted prevalence ratios (PR) to account for region and sociodemographic characteristics. RESULTS: Among 1955 municipalities participating in the survey (question-specific response rate: 44.3%), the prevalence of a Vision Zero action plan or strategy was 7.7%; 70.5% responded no and 21.8% don't know. Prevalence was 4.8% in small municipalities (1000-2499 residents), 20.3% in medium-large municipalities (50 000-124 999 residents; PR=4.1), and 37.8% in large municipalities (≥125 000 residents; PR=7.6). CONCLUSION: The prevalence of Vision Zero plans and strategies across the USA is low. Additional adoption of Vision Zero plans and strategies could help address traffic fatalities.

Motor vehicle collision (MVC) emergency department (ED) visits and hospitalisations in Ontario during the COVID-19 pandemic.

BACKGROUND: The COVID-19 pandemic policy response dramatically changed local transportation patterns. This project investigated the impact of COVID-19 policies on motor vehicle collision (MVC)-related emergency department (ED) visits and hospitalisations in Ontario. METHODS: Data were collected on MVC-related ED visits and hospitalisations in Ontario between March 2016 and December 2022. Using an interrupted time series design, negative binomial regression models were fitted to the pre-pandemic data, including monthly indicator variables for seasonality and accounting for autocorrelation. Extrapolations simulated expected outcome trajectories during the pandemic, which were compared with actual observed outcome counts using the overall per cent change and mean monthly difference. Data were modelled separately for vehicle occupants, pedestrians and cyclists (MVC and non-MVC injuries). RESULTS: There was a 31.5% decrease in observed ED visits (95% CI -35.4 to -27.3) and a 6.0% decrease in hospitalisations (95% CI -13.2 to 1.6) among vehicle occupants, relative to expected counts during the pandemic. Results were similar for pedestrians. Among cyclist MVCs, there was an increase in ED visits (12.8%, 95% CI -8.2 to 39.4) and hospitalisations (46.0%, 95% CI 11.6 to 93.6). Among non-MVC cyclists, there was also an increase in ED visits (47.0%, 95% CI 12.5 to 86.8) and hospitalisations (50.1%, 95% CI 8.2 to 101.2). CONCLUSIONS: We observed fewer vehicle occupant and pedestrian collision injuries than expected during the pandemic. By contrast, we observed more cycling injuries than expected, especially in cycling injuries not involving motor vehicles. These observations may be attributable to changes in transportation patterns during the pandemic and increased uptake of recreational cycling.

Economic impact on local businesses of road safety improvements in Seattle: implications for Vision Zero projects.

BACKGROUND: Local transportation agencies implementing Vision Zero road safety improvement projects often face opposition from business owners concerned about the potential negative impact on their sales. Few studies have documented the economic impact of these projects. METHODS: We examined baseline and up to 3 years of postimprovement taxable sales data for retail, food and service-based businesses adjacent to seven road safety projects begun between 2006 and 2014 in Seattle. We used hierarchical linear models to test whether the change in annual taxable sales differed between the 7 intervention sites and 18 nearby matched comparison sites that had no road safety improvements within the study time frame. RESULTS: Average annual taxable sales at baseline were comparable at the 7 intervention sites (US$44.7 million) and the 18 comparison sites (US$56.8 million). Regression analysis suggests that each additional year following baseline was associated with US$1.20 million more in taxable sales among intervention sites and US$1.14 million more among comparison sites. This difference is not statistically significant (p=0.64). Sensitivity analyses including a random slope, using a generalised linear model and an analysis of variance did not change conclusions. DISCUSSION: Results suggest that road safety improvement projects such as those in Vision Zero plans are not associated with adverse economic impacts on adjacent businesses. The absence of negative economic impacts associated with pedestrian and bicycle road safety projects should reassure local business owners and may encourage them to work with transportation agencies to implement Vision Zero road safety projects designed to eliminate traffic-related injuries.

Did 'long COVID' increase road deaths in the USA?

OBJECTIVE: To examine data on COVID-19 disease associated with a 10% increase in US road deaths from 2020 to 2021 that raises the question of the potential effect of pandemic stress and neurological damage from COVID-19 disease. METHODS: Poisson regression was used to estimate the association of recent COVID-19 cases, accumulated cases, maximum temperatures, truck registrations and gasoline prices with road deaths monthly among US states in 2021. Using the regression coefficients, changes in each risk factor from 2020 to 2021 were used to calculate expected deaths in 2021 if each factor had remained the same as in 2020. RESULTS: Corrected for the other risk factors, road deaths were associated with accumulated COVID-19 cases but not concurrent cases. More than 20 700 road deaths were associated with the changes in accumulated COVID-19 cases but were substantially offset by about 19 100 less-than-expected deaths associated with increased gasoline prices. CONCLUSIONS: The lingering effects of COVID-19 on neurological function may be a risk factor for behaviour leading to road deaths.

Replication of a local record keeping method for collecting road crash data in low resource settings: lessons from Bangladesh and Nepal.

BACKGROUND: Police road crash and injury data in low-income and middle-income countries are known to under-report crashes, fatalities and injuries, especially for vulnerable road users. Local record keepers, who are members of the public, can be engaged to provide an additional source of crash and injury data. METHODS: This paper compares the application of a local record keeper method to capture road crash and injury data in Bangladesh and Nepal, assesses the quality of the data collected and evaluates the replicability and value of the methodology using a framework developed to evaluate the impact of being a local record keeper. OUTCOME: Application in research studies in both Bangladesh and Nepal found the local record keeper methodology provided high-quality and complete data compared with local police records. The methodology was flexible enough to adapt to project and context differences. The evaluation framework enabled the identification of the challenges and unexpected benefits realised in each study. This led to the development of an 11-step process for conducting road crash data collection using local record keepers, which is presented to facilitate replication in other settings. CONCLUSION: Data collected by local record keepers are a flexible and replicable method to understand the strengths and limitations of existing police data, adding to the evidence base and informing local and national decision-making. The method may create additional benefits for data collectors and communities, help design and assess road safety interventions and support advocacy for improved routine police data.

Leveraging computer vision for predicting collision risks: a cross-sectional analysis of 2019-2021 fatal collisions in the USA.

OBJECTIVE: The USA has higher rates of fatal motor vehicle collisions than most high-income countries. Previous studies examining the role of the built environment were generally limited to small geographic areas or single cities. This study aims to quantify associations between built environment characteristics and traffic collisions in the USA. METHODS: Built environment characteristics were derived from Google Street View images and summarised at the census tract level. Fatal traffic collisions were obtained from the 2019-2021 Fatality Analysis Reporting System. Fatal and non-fatal traffic collisions in Washington DC were obtained from the District Department of Transportation. Adjusted Poisson regression models examined whether built environment characteristics are related to motor vehicle collisions in the USA, controlling for census tract sociodemographic characteristics. RESULTS: Census tracts in the highest tertile of sidewalks, single-lane roads, streetlights and street greenness had 70%, 50%, 30% and 26% fewer fatal vehicle collisions compared with those in the lowest tertile. Street greenness and single-lane roads were associated with 37% and 38% fewer pedestrian-involved and cyclist-involved fatal collisions. Analyses with fatal and non-fatal collisions in Washington DC found streetlights and stop signs were associated with fewer pedestrians and cyclists-involved vehicle collisions while road construction had an adverse association. CONCLUSION: This study demonstrates the utility of using data algorithms that can automatically analyse street segments to create indicators of the built environment to enhance understanding of large-scale patterns and inform interventions to decrease road traffic injuries and fatalities.

Pedestrian wintertime slip and fall injuries-effectiveness of weather warning service in prevention.

BACKGROUND AND AIM: In climates with wintry conditions, slip and fall injuries of pedestrians during wintertime can result in high healthcare and societal costs. The aim of this study was to evaluate the effectiveness of early warnings about slipperiness in preventing such injuries in Finland. Since 2004, the Finnish Meteorological Institute (FMI) has been providing a weather service for pedestrians, which has been developed continuously over time. DATA AND METHODS: Time series of pedestrian slip and fall injuries in commuting on foot in the 19 regions of Finland in 2005-2022 was obtained from the Finnish Workers' Compensation Center and analysed for trends. We also analysed daily warnings about slippery sidewalks from the FMI archives for the period 2011-2022. To identify steps in the service chain that require improvement, we conducted a weather service chain analysis (WSCA) based on a slip and fall accident storyline. RESULTS: There was no significant trend in the number of slipping injuries during the study period. The exposure of the Finnish population to slippery conditions varies according to the climate of the region and characteristics of the winters. We found that the responses of the users of the warning information may be inadequate. CONCLUSIONS: Changes in the behaviour of individuals and more efficient winter maintenance of sidewalks are required. Furthermore, it is necessary to promote the role and safety of walking in the planning of traffic systems and urban planning. Further improvements to the pedestrian weather service are needed as well.

The association between health literacy and pedestrian safety behavior among adults: a cross-sectional study.

INTRODUCTION: Pedestrians are considered the most vulnerable and complex road users as human behavior constitutes one of the fundamental reasons for traffic-related incidents involving pedestrians. However, the role of health literacy as a predictor of Pedestrian safety behavior remains underexplored. Therefore, the current study was designed to examine the level of health literacy and its association with the safety behavior of adult pedestrians in the city of Tabriz. METHODS: This cross-sectional analytical study was conducted among individuals aged 18 to 65 years in the metropolitan area of Tabriz from January to April 2023. Data were collected using the HELIA standard questionnaire (Health Literacy Instrument for adults), comprising 33 items across 5 domains (access, reading, understanding, appraisal, decision-making and behavior), as well as the Pedestrian Behavior Questionnaire (PBQ) consisting of 29 items. Data were analyzed using descriptive and analytical statistics (independent t-tests, ANOVA, and Pearson correlation coefficient) via SPSS-22 software. RESULTS: Based on the results, 94% (376 individuals) had excellent health literacy levels, and their safety behavior scores were at a good level. Health literacy and safety behavior were higher among the age group of 31 to 45 years, women, married individuals, those who read books, and individuals with higher education. However, safety behavior showed no significant association with education level (P > 0.05). There was a significant and positive relationship between health literacy and all its domains and pedestrian safety behavior (r = 0.369, P < 0.001). CONCLUSION: This study underscores the significant impact of health literacy on pedestrians' safety behavior. The findings reveal that higher levels of health literacy are associated with better safety behavior among individuals aged 18 to 63. Demographic factors such as age, gender, marital status, and education level also play a role in shaping both health literacy and safety behavior. By recognizing these relationships, interventions can be tailored to improve health literacy levels and promote safer pedestrian practices, ultimately contributing to a healthier and safer community in Tabriz city.

Validity across four common street-crossing distraction indicators to predict pedestrian safety.

BACKGROUND: Multiple distraction indicators have been applied to measure street-crossing distraction but their validities in predicting pedestrian safety are poorly understood. METHODS: Based on a video-based observational study, we compared the validity of four commonly used distraction indicators (total duration of distraction while crossing a street, proportion of distracted time over total street-crossing time, duration of the longest distraction time, and total number of distractions) in predicting three pedestrian safety outcomes (near-crash incidence, frequency of looking left and right, and speed crossing the street) across three types of distraction (mobile phone use, talking to other pedestrians, eating/drinking/smoking). Change in Harrell's C statistic was calculated to assess the validity of each distraction indicator based on multivariable regression models including only covariates and including both covariates and the distraction indicator. RESULTS: Heterogeneous capacities in predicting the three safety outcomes across the four distraction indicators were observed: 1) duration of the longest distraction time was most predictive for the occurrence of near-crashes and looks left and right among pedestrians with all three types of distraction combined and talking with other pedestrians (Harrell's C statistic changes ranged from 0.0310 to 0.0335, P < 0.05), and for the occurrence of near-crashes for pedestrians involving mobile phone use (Harrell's C statistic change: 0.0053); 2) total duration of distraction was most predictive for speed crossing the street among pedestrians with the combination and each of the three types of distraction (Harrell's C statistic changes ranged from 0.0037 to 0.0111, P < 0.05), frequency of looking left and right among pedestrians distracted by mobile phone use (Harrell's C statistic change: 0.0115), and the occurrence of near-crash among pedestrians eating, drinking, or smoking (Harrell's C statistic change: 0.0119); and 3) the total number of distractions was the most predictive indicator of frequency of looking left and right among pedestrians eating, drinking, or smoking (Harrell's C statistic change: 0.0013). Sensitivity analyses showed the results were robust to change in grouping criteria of the four distraction indicators. CONCLUSIONS: Future research should consider the pedestrian safety outcomes and type of distractions to select the best distraction indicator.