Investigating built environment and traffic flow impact on crash frequency in urban road networks.

While numerous studies have examined the factors that influence crash occurrence, there remains a gap in understanding the intricate relationship between built environment, traffic flow, and crash occurrences across different spatial units. This study explores how built environment attributes, and dynamic traffic flow characteristics affect crash frequency by focusing on proposed traffic density-based zones (TDZs). Utilizing a comprehensive dataset from Greater Melbourne, Australia, this research emphasizes on the dynamic traffic flow variables and insights from the Macroscopic Fundamental Diagram model, considering parameters such as shockwave velocity and congestion index. The association between the potential influencing factors and crash frequency is examined using a random parameter negative binomial regression model. Results indicate that the data segmentation based on TDZs is instrumental in establishing a more refined crash model compared to traditional planning-based zones, as demonstrated by improved goodness-of-fit measures. Factors including density (e.g., employment density), network design (e.g., road density and highway density), land use diversity (e.g., job-housing balance and land use mixture), and public transit accessibility (e.g., bus route density) are significantly associated with crash occurrence. Furthermore, the unobserved heterogeneity effects of the shockwave velocity and congestion index on crashes are revealed. The study highlights the significance of incorporating dynamic traffic flow variables in understanding crash frequency variations across different spatial units. These findings can inform optimal real-time traffic monitoring, environmental design, and road safety management strategies to mitigate crash risks.

Modeling the influence of bacteria concentration on the mechanical properties of self-healing concrete (SHC) for sustainable bio-concrete structures.

In this research paper, the intelligent learning abilities of the gray wolf optimization (GWO), multi-verse optimization (MVO), moth fly optimization, particle swarm optimization (PSO), and whale optimization algorithm (WOA) metaheuristic techniques and the response surface methodology (RSM) has been studied in the prediction of the mechanical properties of self-healing concrete. Bio-concrete technology stimulated by the concentration of bacteria has been utilized as a sustainable structural concrete for the future of the built environment. This is due to the recovery tendency of the concrete structures after noticeable structural failures. However, it requires a somewhat expensive exercise and technology to create the medium for the growth of the bacteria needed for this self-healing ability. The method of data gathering, analysis and intelligent prediction has been adopted to propose parametric relationships between the bacteria usage and the concrete performance in terms of strength and durability. This makes is cheaper to design self-healing concrete structures based on the optimized mathematical relationships and models proposed from this exercise. The performance of the models was tested by using the coefficient of determination (R2), root mean squared errors, mean absolute errors, mean squared errors, variance accounted for and the coefficient of error. At the end of the prediction protocol and model performance evaluation, it was found that the classified metaheuristic techniques outclassed the RSM due their ability to mimic human and animal genetics of mutation. Furthermore, it can be finally remarked that the GWO outclassed the other methods in predicting the concrete slump (Sl) with R2 of 0.998 and 0.989 for the train and test, respectively, the PSO outclassed the rest in predicting the flexural strength with R2 of 0.989 and 0.937 for train and test, respectively and the MVO outclassed the others in predicting the compressive strength with R2 of 0.998 and 0.958 for train and test, respectively.

Development, scoring, and reliability for the Microscale Audit of Pedestrian Streetscapes for Safe Routes to School (MAPS-SRTS) instrument.

BACKGROUND: Active commuting to school can be a meaningful contributor to overall physical activity in children. To inform better micro-level urban design near schools that can support active commuting to school, there is a need for measures that capture these elements. This paper describes the adaptation of an observational instrument for use in assessing micro-scale environments around urban elementary schools in the United States. METHODS: The Micro-scale Audit of Pedestrian Streetscapes for Safe Routes to School (MAPS-SRTS) was developed from existing audit instruments not designed for school travel environments and modifications for the MAPS-SRTS instrument include the structure of the audit tool sections, the content, the observation route, and addition of new subscales. Subscales were analyzed for inter-rater reliability in a sample of 36 schools in Austin, TX. To assess reliability for each subscale, one-way random effects single-measure intraclass correlation coefficients (ICC) were used. RESULTS: Compared to the 30 original subscales, the adapted MAPS-SRTS included 26 (86.6%) subscales with revised scoring algorithms. Most MAPS-SRTS subscales had acceptable inter-rater reliability, with an ICC of 0.97 for the revised audit tool. CONCLUSIONS: The MAPS-SRTS audit tool is a reliable instrument for measuring the school travel environment for research and evaluation purposes, such as assessing human-scale determinants of active commuting to school behavior and documenting built environment changes from infrastructure interventions.

Why Patient-Centered Built Environment Standards Matter More Than Numbers of Beds in Inpatient Psychiatry.

This article canvasses extant literature about values, evidence, and standards for inpatient psychiatry units' design. It then analyzes apparent trade-offs between quality of care and access to care using empirical and ethical lenses. From this analysis, the authors conclude that standards for the built environment of inpatient psychiatric care should align with patient-centeredness, even if a downstream consequence of implementing new patient-centered designs is a reduction in beds, although this secondary outcome is unlikely.

Unraveling the relation between cycling accidents and built environment typologies: Capturing spatial heterogeneity through a latent class discrete outcome model.

Today, cities seek to transition to more sustainable transportation modes. Cycling is critical in this shift, promoting a more beneficial lifestyle for most. However, cyclists are exposed to many hazardous circumstances or environments, resulting in accidents, injuries, and even death. Transport authorities must understand why accidents occur, to reduce the risk of those who cycle. This study applies a new modeling framework to analyze cycling accident severities. We employ a latent class discrete outcome model, where classes are derived from a Gaussian-Bernoulli mixture, applied to data from Berlin, and augmented with volunteered geographic information. We jointly estimate model components, combining machine learning and econometric approaches, allowing for more intricate and flexible representations while maintaining interpretability. Results show the potential of our approach. Risk factors are indexed depending on where accidents occurred and their contribution. We can discover complex relations between specific built environments and accident characteristics and uncover differences in the impact of certain accident factors on one environment typology but not others. Using multiple data sources also proves helpful as an additional layer of knowledge, providing unique value to understand and model cycling accidents. Another critical aspect of our approach is the potential for simulation, where locations can be examined through simulated accident features to understand the inherent risk of various locations. These findings highlight the ability to capture heterogeneity in accidents and their relation to the built environment. Capturing such relations allows for more direct countermeasures to risky situations or policies to be designed, simulated, and targeted.

Built environment and physical activity in adolescents: Use of the kernel density estimation and the walkability index.

The availability of places for physical activity (PA) and the walkability of the neighborhood can impact the level of PA of adolescents. However, studies of this nature are still limited in Latin America. This study had two objectives: 1- using kernel density estimative, it investigated whether individuals living near PA places that are more intensely distributed than dispersed are more likely to be sufficiently active; 2-checked whether adolescents who live in neighborhoods with better walkability have a greater chance of being sufficiently active. Were evaluated 292 adolescents and PA was measured by accelerometry. Were measured five environmental variables for composing the walkability index. 98 PA points (places) were identified and destinations within these areas were geocoded and kernel density estimates (KDE) of places intensity were created using kernels (radius) of 400m (meters), 800, 1200 and 1600m. Using Logistic Regression, the association between the intensity of PA places (classified into quartiles Q1(smallest)-Q4(largest)) and the probability of being "Sufficient PA"; and the association between walkability (quartiles Q1(least)-Q4(highest)) and the probability of being "PA Sufficient " were estimated (p≤0.05). There were associations only for the intensities of places with the largest radius. Among adolescents who lived in places with higher intensity compared with lower intensity places: 1200m (Q3, OR 2.18 95% CI 1.12-4.22; Q4, OR 2.77 95% CI 1.41-5.43) and 1600m (Q3, OR 3.68 95%CI 1.86-7.30; Q4, OR 3.69 95%CI 1.86-7.30) were more likely to be "Sufficient PA". There were also associations for walkability, where those living in places with better walkability (Q4, OR 2.58 95% CI 1.33-5.02) had greater chances of being "Sufficient PA" compared to Q1. In conclusion, living in places with bigger densities and better walkability increases adolescent's chances of being "Sufficient PA".

Factors associated with different types of freight crashes: A macro-level analysis.

INTRODUCTION: Despite evidence showing higher fatality rates in freight-related crashes, there has been limited exploration of their spatial distribution and factors associated with such distribution. This gap in the literature primarily stems from the focus of existing studies on micro-level factors predicting the frequency or severity of injuries in freight crashes. The present study delves into the factors contributing to freight crashes at the neighborhood level, particularly focusing on different types of freight crashes: collisions involving a freight vehicle and a passenger vehicle, crashes between freight vehicles, and freight vehicle-non-motorized crashes. METHOD: This study analyzes traffic crash data from the urbanized region of Seoul, collected between 2016 and 2019. To effectively deal with spatial autocorrelation and model different types of crashes in a unified framework, a Bayesian multivariate conditional autoregressive model was employed. RESULTS: Findings show substantial differences in the factors associated with various types of freight crashes. The predictors for crashes between freight vehicles diverge significantly from those for freight vehicle-non-motorized crashes. Crashes between freight vehicles are relatively more influenced by road network structure, while freight crashes involving non-motorized users are relatively more affected by the built environment and freight facilities than the other crash types examined. Freight vehicle-passenger vehicle crashes fall into an intermediate category, sharing most predictors with either of the other two types of freight crashes. CONCLUSIONS AND PRACTICAL APPLICATIONS: The findings of this study offer valuable lessons for transportation practitioners and policymakers. They can guide the formulation of effective land use policies and infrastructure planning, specifically designed to address the unique characteristics of different types of freight crashes.

Exploring non-linear effects of walking accessibility on well-being in rural older adults of Jintang County: a random forest analysis.

Objective: The global concern surrounding the aging population has brought the well-being of older individuals to the forefront of societal attention. Unfortunately, studies focusing on the well-being of older people residing in rural areas are frequently overshadowed by the developmental disparities between rural and urban regions. Thus, this study aims to delve into the non-linear impact of walking accessibility on the subjective well-being of rural older adults. The goal is to gain a comprehensive understanding of this relationship, ultimately contributing to an improved quality of life and health for older adults in rural areas. Methods: In this study, the Random Forest algorithm was employed to explore the non-linear effects of demographic variables, perceived safety, subjective built environment (including perceptions and preferences of the built environment), and walking accessibility on the subjective well-being of older adults. Results: The findings of this study underscore the pivotal role of walking accessibility in influencing the well-being of older adults, particularly in terms of access to bazaars and health centers, where non-linear and threshold effects are evident. Furthermore, community safety, road conditions, and walking preferences were identified as positive influencers on the well-being of older adults. Well-being trends varied with age, revealing noteworthy non-linear relationships for certain variables. Conclusion: The insights gained from this study provide crucial theoretical guidance for the development of policies tailored to the unique context of rural aging. By taking into account factors such as walking accessibility, community safety, health support, and social interaction, we can create an improved living environment for rural older adults, ultimately enhancing their happiness and overall quality of life.

Effects of neighborhood built environment on cognitive function in older adults: a systematic review.

BACKGROUND: In the background of an aging population, the risk of cognitive impairment in the older population is prominent. Exposure to complex neighborhood built environments may be beneficial to the cognitive health of older adults, and the purpose of this study was to systematically review the scientific evidence on the effects of neighborhood built environments on cognitive function in older adults. METHODS: Keywords and references were searched in Web of Science, Pubmed, PsycINFO, and MEDLINE. Studies examining the relationship between the built environment and cognitive function in older adults were included. The neighborhood built environment as an independent variable was classified according to seven aspects: density, design, diversity, destination accessibility, public transportation distance, blue/green space, and built environment quality. The cognitive function as the dependent variable was classified according to overall cognitive function, domain-specific cognitive function, and incidence of dementia. The quality of the included literature was assessed using the National Institutes of Health's Observational Cohort and Cross-Sectional Study Quality Assessment Tool. RESULTS: A total of 56 studies were included that met the inclusion criteria, including 31 cross-sectional studies, 23 longitudinal studies, 1 cross-sectional study design combined with a case-control design, and 1 longitudinal study design combined with a case-control design. Most of the studies reviewed indicate that the built environment factors that were positively associated with cognitive function in older adults were population density, street connectivity, walkability, number of public transportation stops around the residence, land use mix, neighborhood resources, green space, and quality of the neighborhood built environment. Built environment factors that were negatively associated with cognitive function in older adults were street integration, distance from residence to main road. The relationship between residential density, destination accessibility, and blue space with cognitive function in older adults needs to be further explored. CONCLUSION: Preliminary evidence suggests an association between the neighborhood built environment and cognitive function in older adults. The causal relationship between the built environment and cognitive function can be further explored in the future using standardized and combined subjective and objective assessment methods, and longitudinal or quasi-experimental study designs. For public health interventions on the cognitive health of older adults, it is recommended that relevant authorities include the neighborhood built environment in their intervention programs.

Spatial scale effects on associations between built environment and cognitive function: Multi-Ethnic Study of Atherosclerosis.

Built environments have the potential to favorably support cognitive function. Despite growing work on this topic, most of the work has ignored variation in the spatial scale of the effect. The issue with spatial scale effects is that the size and shape of the areal unit within which built environment characteristics are measured naturally influence the built environment exposure metric and thus the estimated associations with health. We used spatial distributed lag modeling (DLM) to estimate how associations between built environment exposures (walkable destinations [WD], social destinations [SD]) and change in cognition varied across distance of these destinations from participants' residences. Cognition was assessed as maintained/improved processing speed (PS) and global cognition (GC). Person-level data from Exam 5 (2010-2012) and Exam 6 (2016-2018) of the Multi-Ethnic Study of Atherosclerosis was used (N = 1380, mean age 67). Built environment data were derived from the National Establishment Time Series. Higher availability of walkable and social destinations at closer distance from participants' residence was associated with maintained/improved PS. The adjusted associations between maintained/improved PS and destinations waned with increasing distance from the residence; associations were evident until approximately 1.9-km for WD and 1.5-km for SD. Associations were most apparent for participants living in areas with high population density. We found little evidence for associations between change in GC and built environment at any distance. These results highlight the importance of identifying appropriate spatial scale to understand the mechanisms for built environment-cognition associations.

The built environment and cancer survivorship: A scoping review.

BACKGROUND: There are more than 32 million cancer survivors worldwide. The built environment is one of the contextual factors that may influence cancer survivorship. However, studies investigating the interdisciplinary field of the built environment and cancer survivorship are lacking. OBJECTIVE: To conduct a systematic review of the existing literature regarding the relationship between the built environment and cancer survivorship, identify any knowledge gaps, and recommend future research directions. METHODS: A systematic literature search was performed by searching OVID Medline, Embase, CINAHL, and Web of Science Core Collection. RESULTS: Of 4235 unique records identified, 26 studies met eligibility criteria. Neighborhood walkability and greenness were the most examined built environment characteristics among the included studies. Walkability was found to be associated with various cancer survivorship experience, including increased levels of physical activity, lowered body mass index, and improved quality of life. The association between greenness and cancer survivorship outcomes were inconsistent across the included studies. Additionally, studies have reported the relationship between light and noise pollution and sleep among cancer survivors. Regarding blue space, in one qualitative study, breast cancer survivors brought up the healing properties of water. CONCLUSION: Our scoping review demonstrated a breadth of current cancer survivorship research in the field of neighborhood walkability and greenness, but fewer studies detailing other aspects of the built environment as defined by this review, such as light pollution, noise pollution, and blue space. We identified future research directions for those interested in this interdisciplinary field, which can provide insights for urban planners and policy makers on how to best leverage the built environment to promote the health and wellbeing of cancer survivors.

Cities and mental health: The role of the built environment, and environmental and lifestyle factors in Barcelona.

Built environment characteristics and related environmental exposures and behaviors have been, separately, implicated in the development of poor mental health. However, it is unclear how these factors act together in relation to mental health. We studied these factors simultaneously to evaluate the impact of the built environment, and the mediating role of environmental exposures and physical activity, on mental health, while also studying moderation by sex, age, and length of residence. We used a cross-sectional population-based sample of 3145 individuals aged 15-97 years from Barcelona, Spain. Time spent walking and mental health status were assessed with validated questionnaires, administered through a face-to-face interview. We characterized the built environment (e.g., building, population and intersection density and green space), road traffic noise, and ambient air pollution at the residential level using land cover maps, remote sensing, noise maps and land use regression models. Adjusted regression models accounting for spatial clustering were analyzed to study associations between built environment attributes and mental health, and mediation and moderation effects. Density attributes were directly or indirectly, through air pollution and less consistently through walking, associated with poor mental health. Green space indicators were associated with lower prevalence of poor mental health, partly through lower air pollution exposure and more walking. In some cases, these associations differed by sex, age or length of residence. Non-linear associations of density indicators with environmental exposures, and of particulate matter with poor mental health indicated threshold effects. We conclude that living in dense areas with high air pollution concentrations was associated with poor mental health. On the other hand, green areas with lower air pollution concentrations were protective against poor mental health. Greater urban density might benefit health, but might only do so when air pollution concentrations are low.

Analysis of the influencing factors of vitality and built environment of shopping centers based on mobile-phone signaling data.

Nowadays, shopping centers not only provides commercial function but also serve as a public space. In this article, we take Nanshan district of Shenzhen as an example, based on the characteristics information of people activities provided by Mobile-phone Signaling Data, using the standard deviation ellipse method to classify the direction of people in shopping centers, and then applying the entropy weighting method to analyze the vitality factors of shopping centers from three perspectives: visitors' density, revisit rate, and the average length of stay. Finally, we analyzed the influence factors of the surrounding built environment based on correlation analysis to discuss the results with field survey data. The results show that (1) shopping centers in Nanshan District are classified into wide-area type and geo-regional type according to the gathering of visitors. The shopping centers with high comprehensive vitality are basically wide-area type. (2) The factors influencing the vitality of shopping centers are different between wide-area type and geo-regional type. The vitality of wide-area type is mainly influenced by the traffic accessibility and whether they are located in adjacent to large public spaces such as squares and green public; the vitality of geo-regional type shopping centers is mainly influenced by the number of people within a 15-minute walking circle, and the high-vitality of geo-regional shopping centers are generally located in densely populated areas.

Impact of green space and built environment on metabolic syndrome: A systematic review with meta-analysis.

Metabolic Syndrome presents a significant public health challenge associated with an increased risk of noncommunicable diseases such as cardiovascular conditions. Evidence shows that green spaces and the built environment may influence metabolic syndrome. We conducted a systematic review and meta-analysis of observational studies published through August 30, 2023, examining the association of green space and built environment with metabolic syndrome. A quality assessment of the included studies was conducted using the Office of Health Assessment and Translation (OHAT) tool. The Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) assessment was used to evaluate the overall quality of evidence. Our search retrieved 18 studies that met the inclusion criteria and were included in our review. Most were from China (n = 5) and the USA (n = 5), and most used a cross-sectional study design (n = 8). Nine studies (50 %) reported only green space exposures, seven (39 %) reported only built environment exposures, and two (11 %) reported both built environment and green space exposures. Studies reported diverse definitions of green space and the built environment, such as availability, accessibility, and quality, particularly around participants' homes. The outcomes focused on metabolic syndrome; however, studies applied different definitions of metabolic syndrome. Meta-analysis results showed that an increase in normalized difference vegetation index (NDVI) within a 500-m buffer was associated with a lower risk of metabolic syndrome (odds ratio [OR] = 0.90, 95%CI = 0.87-0.93, I2 = 22.3 %, n = 4). A substantial number of studies detected bias for exposure classification and residual confounding. Overall, the extant literature shows a 'limited' strength of evidence for green space protecting against metabolic syndrome and an 'inadequate' strength of evidence for the built environment associated with metabolic syndrome. Studies with more robust study designs, better controlled confounding factors, and stronger exposure measures are needed to understand better what types of green spaces and built environment features influence metabolic syndrome.

Making cities mental health friendly for adolescents and young adults.

Urban life shapes the mental health of city dwellers, and although cities provide access to health, education and economic gain, urban environments are often detrimental to mental health1,2. Increasing urbanization over the next three decades will be accompanied by a growing population of children and adolescents living in cities3. Shaping the aspects of urban life that influence youth mental health could have an enormous impact on adolescent well-being and adult trajectories4. We invited a multidisciplinary, global group of researchers, practitioners, advocates and young people to complete sequential surveys to identify and prioritize the characteristics of a mental health-friendly city for young people. Here we show a set of ranked characteristic statements, grouped by personal, interpersonal, community, organizational, policy and environmental domains of intervention. Life skills for personal development, valuing and accepting young people's ideas and choices, providing safe public space for social connection, employment and job security, centring youth input in urban planning and design, and addressing adverse social determinants were priorities by domain. We report the adversities that COVID-19 generated and link relevant actions to these data. Our findings highlight the need for intersectoral, multilevel intervention and for inclusive, equitable, participatory design of cities that support youth mental health.

Biocontrol in built environments to reduce pathogen exposure and infection risk.

The microbiome of the built environment comprises bacterial, archaeal, fungal, and viral communities associated with human-made structures. Even though most of these microbes are benign, antibiotic-resistant pathogens can colonize and emerge indoors, creating infection risk through surface transmission or inhalation. Several studies have catalogued the microbial composition and ecology in different built environment types. These have informed in vitro studies that seek to replicate the physicochemical features that promote pathogenic survival and transmission, ultimately facilitating the development and validation of intervention techniques used to reduce pathogen accumulation. Such interventions include using Bacillus-based cleaning products on surfaces or integrating bacilli into printable materials. Though this work is in its infancy, early research suggests the potential to use microbial biocontrol to reduce hospital- and home-acquired multidrug-resistant infections. Although these techniques hold promise, there is an urgent need to better understand the microbial ecology of built environments and to determine how these biocontrol solutions alter species interactions. This review covers our current understanding of microbial ecology of the built environment and proposes strategies to translate that knowledge into effective biocontrol of antibiotic-resistant pathogens.

Life-course socioeconomic status and obesity: a scoping review protocol.

OBJECTIVE: We aim to explore the literature that studies the links between life-course socioeconomic status and weight status and characterize the life-course approach used. INTRODUCTION: Obesogenic environments are increasing rapidly in deprived environments, and cross-sectional studies have shown limitations in explaining the links between these environments and obesity. The life-course approach has been proposed recently to better understand the links between socioeconomic status and weight status. INCLUSION CRITERIA: Studies that identify life-course socioeconomic status and longitudinal built environment indicators and associate them with body weight indicators between January 2000 and January 2023. METHODS: Studies in French or English were searched in Medline (PubMed), Web of Science and GeoBase (Embase) according to the strategies formulated for each database. The selected studies were exported to Covidence for evaluation according to the inclusion/exclusion criteria. RESULTS: The main results retained are the association between longitudinal socioeconomic indicators and weight measures; longitudinal built environment indicators and the measures of weight.

A spatiotemporal deep learning approach for pedestrian crash risk prediction based on POI trip characteristics and pedestrian exposure intensity.

Pedestrians represent a population of vulnerable road users who are directly exposed to complex traffic conditions, thereby increasing their risk of injury or fatality. This study first constructed a multidimensional indicator to quantify pedestrian exposure, considering factors such as Point of Interest (POI) attributes, POI intensity, traffic volume, and pedestrian walkability. Following risk interpolation and feature engineering, a comprehensive data source for risk prediction was formed. Finally, based on risk factors, the VT-NET deep learning network model was proposed, integrating the algorithmic characteristics of the VGG16 deep convolutional neural network and the Transformer deep learning network. The model involved training non-temporal features and temporal features separately. The training dataset incorporated features such as weather conditions, exposure intensity, socioeconomic factors, and the built environment. By employing different training methods for different types of causative feature variables, the VT-NET model analyzed changes in risk features and separately trained temporal and non-temporal risk variables. It was used to generate spatiotemporal grid-level predictions of crash risk across four spatiotemporal scales. The performance of the VT-NET model was assessed, revealing its efficacy in predicting pedestrian crash risks across the study area. The results indicated that areas with concentrated crash risks are primarily located in the city center and persist for several hours. These high-risk areas dissipate during the late night and early morning hours. High-risk areas were also found to cluster in the city center; this clustering behavior was more prominent during weekends compared to weekdays and coincided with commercial zones, public spaces, and educational and medical facilities.

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.

How does the built environment affect patient safety in relation to physical activity? Experiences at a rehabilitation center.

Physical activity benefits patients in rehabilitation yet comes with various safety issues. The built environment impacts on both safety and physical activity. We aim to explore the role of the built environment in safety issues related to being physically active in rehabilitation. We conducted a case study at a free-standing rehabilitation center for patients with Multiple Sclerosis, neurologic, or locomotor issues. Patients participated in two interviews supported by activity tracking data. Care professionals participated in focus group interviews respectively with two therapists and four head nurses. Accessibility and physical barriers, visual connections and (in)dependence, and spatial familiarity are important themes when identifying aspects of the built environment in relation to reducing safety issues patients encounter during physical activity. Raising awareness about each of these among care and design professionals could help them to balance safety issues in relation to physical activity and to communicate about them in a nuanced way.