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1.
Appl Ergon ; 98: 103585, 2022 Jan.
Artículo en Inglés | MEDLINE | ID: mdl-34562780

RESUMEN

This work is directed to an understanding as to how the knowledge of, and the application of human factors and ergonomics (HF/E) can save lives. To achieve this, the paper features an assessment of the achievements of one particular scientist, Neville Anthony Stanton, and how his body of contributions has impacted the realm of ground transportation and, in particular, driver behavior assessment. On the widest scale, it is objectively and obviously the case that Stanton is one of the most fecund scientists of our discipline ever. His impact is evident globally and results not simply from the sum total of his written and published works but through an extensive record of international scientific presentations, mutual investigative collaborations across the globe, and mentoring at all levels of the Academy and beyond. As well as mastering and elucidating the HF/E dimensions of a number of content domains, he has generated vital, and even unique tools and methods through which we can explore and understand the problem space of HF/E. Placing those attainments in context permits us a wider window upon how the discipline itself exerts practical and positive influences across the wide swath of real-world systems.


Asunto(s)
Ergonomía , Transportes , Humanos
2.
Comput Intell Neurosci ; 2021: 1526792, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-34721561

RESUMEN

Intelligent methods and algorithms have promoted the development of the intelligent transportation system in many ways. In the rail transportation, the vertical performance of a high-speed train suspension system has a great impact on the riding comfort of the train. Based on the intelligent optimization method of particle swarm optimization (PSO) algorithm, different inerter-spring-damper (ISD) suspension layouts are proposed for better riding comfort. A 10-degree-of-freedom (10-DOF) vertical dynamic model of a high-speed train is established, and the new suspension layouts are applied to the primary and secondary suspension of the train at the same time. Optimizations are carried out for the suspension parameters of the high-speed train. Performances of different suspension layouts at different running speeds are analysed and compared. The best layout for suspension is concluded. What is more, the virtual prototype simulation and analysis of a high-speed train with consideration of nonlinear inerters are carried out. Friction of a rack-pinion inerter is simulated in the virtual prototype simulation. And the influence of nonlinearity is discussed compared with the ideal suspensions. All the results can represent a guidance for future train suspension design and help the intelligent rail transportation system to be more comfortable.


Asunto(s)
Algoritmos , Transportes , Simulación por Computador , Suspensiones
3.
BMC Geriatr ; 21(1): 635, 2021 11 06.
Artículo en Inglés | MEDLINE | ID: mdl-34742244

RESUMEN

BACKGROUND: People over 64 years have a high fatality rate when they are involved in traffic accidents. Besides, older victims of road crashes are expected to rise in the future due to population aging. The purpose of the study was to document their perception on the role of the family doctor, the main facilitating factors, and the perceived barriers to the temporary or permanent restriction of their driving. METHODS: This qualitative study used focus group methodology. A sample of 16 people over 65 years old was obtained through a series of segmentation criteria at an active participation centre for older adults in a small town in Jaén province (Spain). All were invited to participate in a discussion during which they were asked to express their opinions and subjective experiences concerning the role of their family doctor. The group conversation was taped, fully transcribed and analysed, and codes were generated with both deductive and inductive methods. RESULTS: After merging the codes to generate themes, we identified 9 relevant categories: perception of age-related risk, road safety, role of public authorities, driver assessment centre, role of the family doctor, role of the family, proposals for addressing traffic accidents in older adults, consequences of the driving prohibition, and public transport. All categories help to explain the subjective driving and traffic safety experiences of older road users. CONCLUSIONS: Although family doctors do not usually ask their older patients about road driving, they are highly valued by these patients. Thus, family doctors have a great potential to act, along with the family members, for the benefit of older patients' traffic safety, in ways that can prevent their involvement in road crashes and reduce the negative consequences of having to stop driving if necessary.


Asunto(s)
Accidentes de Tránsito , Conducción de Automóvil , Accidentes de Tránsito/prevención & control , Anciano , Actitud , Humanos , Médicos de Familia , Transportes
4.
Sensors (Basel) ; 21(21)2021 Oct 25.
Artículo en Inglés | MEDLINE | ID: mdl-34770370

RESUMEN

Crude oil is one of the critically needed resources. It is the main pillar supporting almost everything we rely on in daily life. Unfortunately, due to many factors, crude oil costs too much. Transportation is one of the critical factors that affect such costs. Due to many environmental risks attached to the transportation process, many countries added very high tariffs to cover any hazards during the transportation, loading, and unloading process. Logistics concerns and political conflicts are the other key factors that can massively impact the transportation cost. This paper presents an Industry 4.0-compliant PeTroShare (PTS), a blockchain-powered trustworthy, logistics-friendly, and cost-efficient crude oil trading platform. PTS is a novel ride-sharing platform that enables an anonymous exchange of crude oil between oil producers and customers, focusing mainly on the product quality, not the source of origin. In our scenario, floating crude oil tankers will hold the cargo to an intermediate position in the open ocean. PTS will match the product availability based on the location and the needed quality of the customer requests. Consequently, the time and distance travelled are minimized. Our simulation results show that enabling the anonymous sharing of crude oil products can significantly enhance system efficiency and cost-effectiveness.


Asunto(s)
Cadena de Bloques , Petróleo , Industrias , Privacidad , Transportes
5.
Accid Anal Prev ; 163: 106431, 2021 Dec.
Artículo en Inglés | MEDLINE | ID: mdl-34758411

RESUMEN

With the fast development of economics, road safety is becoming a serious problem. Exploring macro factors is effective to improve road safety. However, the existing studies have some limitations: (1) The existing studies only considered one aspect of macro factors and constructed models based on a few data samples. (2) The methods commonly used cannot address the non-linear relationship or calculate the feature importance. The findings obtained from such models may be limited and biased. To address the limitations, this study proposes a BO-CV-XGBoost framework to explore the macro factors related to traffic fatality rate classes based on a high-dimensional dataset that fully considers the impact of multi-factor interaction with adequate data samples. The proposed framework is applied to a dataset in the US. 453 county-level macro factors are collected from various data sources, covering ten macro aspects, including topography, transportation, etc. The optimized BO-CV-XGBoost model obtains the best classification performance with an AUC of 0.8977 and an accuracy of 85.02%. Compared with other methods, the proposed model has superiority on fatality rate classification. Ten macro factors are identified, including 'Current-dollar GDP', 'highway miles per person', etc. The ten factors contain four aspects of information, including economics, transportation, education, and medical condition. Geographic information system (GIS) techniques are further used for spatial analysis of the identified macro factors. Therefore, targeted and effective measures are accordingly proposed to prevent traffic fatalities and improve road safety.


Asunto(s)
Accidentes de Tránsito , Sistemas de Información Geográfica , Accidentes de Tránsito/prevención & control , Humanos , Análisis Espacial , Transportes
6.
Artículo en Inglés | MEDLINE | ID: mdl-34769699

RESUMEN

The aims of this study were to describe patterns of active commuting to school (ACS) of preschool children, and to analyse the relationship between ACS and family socio-economic factors. A total of 2636 families of preschoolers (3-to-5 years old) were asked to complete a questionnaire at home about the mode of commuting to school of their children and marital status, educational level, and profession of both father and mother. Chi-square analyses were applied to compare ACS between school grades and gender of the children. To analyse the association of ACS with socio-economic factors, logistic regression analyses were performed. Almost 50% of participants reported ACS of their offspring, with a higher rate in 3rd preprimary grade (5 years old) than in 1st and 2nd preprimary grades (3- and 4-years old. All, p < 0.05). Those preschool children who had parents with lower educational level and no managerial work had higher odds to ACS than those who had parents with higher educational level and managerial work (all, p ≤ 0.001). Around half of the Spanish preschool children included in this study commuted actively to school and families with lower educational levels or worse employment situation were related to active commuting to school.


Asunto(s)
Factores Económicos , Caminata , Ciclismo , Preescolar , Estudios Transversales , Humanos , Instituciones Académicas , Factores Socioeconómicos , Encuestas y Cuestionarios , Transportes
7.
Int J Public Health ; 66: 583613, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-34744555

RESUMEN

Objectives: We explored whether modes of transport (cycling, walking, public transport or private vehicle) between home and school are associated with mental well-being in children aged 10-17 years, participating in the Irish Health Behaviour in School-aged Children (HBSC) study. Methods: Scores on the World Health Organization Well-being Index and the Mental Health Inventory five-item versions, self-reported life satisfaction, happiness with self, body satisfaction, excellent self-rated health, and multiple health complaints of 9,077 schoolchildren (mean age: 13.99 ± 1.91 years, percentage girls: 52.2%) were compared across modes of transport, unadjusted and adjusted for gender, age, family affluence and area of residence. Results: Those who reported using public transport reported poorer mental well-being than those using other means of transport, but adjusting for sociodemographic variables obscured these differences. The only exception was excellent health, where children who cycled outperformed the other three groups, even after adjustment for sociodemographic variables. Conclusions: Cycling can improve well-being in children. However, in promotion of cycling, social and environmental determinants and inequalities which influence adolescents' and their parents' decisions on modes of transport, need to be considered.


Asunto(s)
Salud Mental , Instituciones Académicas , Estudiantes , Transportes , Adolescente , Niño , Femenino , Humanos , Irlanda , Masculino , Salud Mental/estadística & datos numéricos , Estudiantes/psicología , Estudiantes/estadística & datos numéricos , Transportes/métodos
8.
Artículo en Inglés | MEDLINE | ID: mdl-34769932

RESUMEN

Although direct contact is considered the main mode of transmission of SARS-CoV-2, environmental factors play an important role. In this study, we evaluated the presence of SARS-CoV-2 on bus and train surfaces. From the buses, we took samples from the following areas: handrails used to enter or exit the bus, stop request buttons and handles next to the seats. From the trains, the sampled surfaces were handrails used to enter or exit the train, door open/close buttons, handles next to the seats, tables and toilet handles. SARS-CoV-2 was detected on 10.7% of the tested surfaces overall, 19.3% of bus surfaces and 2% of train surfaces (p < 0.0001). On the buses, the most contaminated surfaces were the handles near the seats (12.8%), followed by door open/close buttons (12.5%) and handrails (10.5%). Of the five analyzed transport companies, bus companies were the most contaminated, in particular, companies C (40%) and B (23.3%). A greater number of positive samples were found among those taken at 10:00 a.m. and 10:55 a.m. (45% and 40%, respectively). The presence of the virus on many bus surfaces highlights how the sanitation systems on public transport currently in use are not sufficient to limit the spread of SARS-CoV-2.


Asunto(s)
COVID-19 , SARS-CoV-2 , Humanos , Vehículos a Motor , Saneamiento , Transportes
9.
Artículo en Inglés | MEDLINE | ID: mdl-34770064

RESUMEN

This study aimed to examine the associations between active transportation and public transport and the objectively measured meeting of moderate-to-vigorous physical activity (MVPA) and steps per day guidelines in adults by sex from eight Latin American countries. As part of the Latin American Study of Nutrition and Health (ELANS), data were collected from 2524 participants aged 18-65 years. MVPA and steps per day were evaluated using Actigraph GT3X accelerometers. The mode of transportation, its frequency and duration were collected using a self-reported questionnaire. The average time dedicated to active transportation was 12.8 min/day in men (IQR: 2.8-30.0) and 12.9 min/day in women (IQR: 4.3-25.7). A logistic regression analysis was conducted, showing that active transportation (≥10 min) was associated with higher odds of meeting MVPA guidelines (men: OR: 2.01; 95%CI: 1.58-2.54; women: OR: 1.57; 95%CI: 1.25-1.96). These results show a greater association when considering active transportation plus public transport (men: OR: 2.98; 95%CI: 2.31-3.91; women: OR: 1.82; 95%CI: 1.45-2.29). Active transportation plus public transport was positively associated with meeting steps per day guidelines only in men (OR: 1.55; 95%CI: 1.15-2.10). This study supports the suggestion that active transportation plus public transport is significantly associated with meeting the MVPA and daily steps recommendations.


Asunto(s)
Hispanoamericanos , Transportes , Adulto , Ejercicio Físico , Femenino , Humanos , América Latina , Masculino , Estado Nutricional
10.
Sci Rep ; 11(1): 21707, 2021 11 04.
Artículo en Inglés | MEDLINE | ID: mdl-34737382

RESUMEN

We investigate the connection between the choice of transportation mode used by commuters and the probability of COVID-19 transmission. This interplay might influence the choice of transportation means for years to come. We present data on commuting, socioeconomic factors, and COVID-19 disease incidence for several US metropolitan areas. The data highlights important connections between population density and mobility, public transportation use, race, and increased likelihood of transmission. We use a transportation model to highlight the effect of uncertainty about transmission on the commuters' choice of transportation means. Using multiple estimation techniques, we found strong evidence that public transit ridership in several US metro areas has been considerably impacted by COVID-19 and by the policy responses to the pandemic. Concerns about disease transmission had a negative effect on ridership, which is over and above the adverse effect from the observed reduction in employment. The COVID-19 effect is likely to reduce the demand for public transport in favor of lower density alternatives. This change relative to the status quo will have implications for fuel use, congestion, accident frequency, and air quality. More vulnerable communities might be disproportionally affected as a result. We point to the need for additional studies to further quantify these effects and to assist policy in planning for the post-COVID-19 transportation future.


Asunto(s)
COVID-19/transmisión , Transportes/economía , Transportes/estadística & datos numéricos , Ciudades , Empleo/tendencias , Humanos , Vehículos a Motor/economía , Vehículos a Motor/estadística & datos numéricos , Pandemias , Densidad de Población , Dinámica Poblacional/tendencias , SARS-CoV-2/patogenicidad , Factores Socioeconómicos , Transportes/métodos , Estados Unidos/epidemiología
11.
Sci Rep ; 11(1): 19623, 2021 10 04.
Artículo en Inglés | MEDLINE | ID: mdl-34608178

RESUMEN

One of the lessons from the COVID-19 pandemic is the importance of social distancing, even in challenging circumstances such as pre-hurricane evacuation. To explore the implications of integrating social distancing with evacuation operations, we describe this evacuation process as a Capacitated Vehicle Routing Problem (CVRP) and solve it using a DNN (Deep Neural Network)-based solution (Deep Reinforcement Learning) and a non-DNN solution (Sweep Algorithm). A central question is whether Deep Reinforcement Learning provides sufficient extra routing efficiency to accommodate increased social distancing in a time-constrained evacuation operation. We found that, in comparison to the Sweep Algorithm, Deep Reinforcement Learning can provide decision-makers with more efficient routing. However, the evacuation time saved by Deep Reinforcement Learning does not come close to compensating for the extra time required for social distancing, and its advantage disappears as the emergency vehicle capacity approaches the number of people per household.


Asunto(s)
Algoritmos , Distanciamiento Físico , COVID-19/patología , COVID-19/prevención & control , COVID-19/virología , Aprendizaje Profundo , Urgencias Médicas , Refugio de Emergencia , Humanos , Redes Neurales de la Computación , SARS-CoV-2/aislamiento & purificación , Transportes
12.
Comput Intell Neurosci ; 2021: 6262194, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-34630550

RESUMEN

Road surface defects are crucial problems for safe and smooth traffic flow. Due to climate changes, low quality of construction material, large flow of traffic, and heavy vehicles, road surface anomalies are increasing rapidly. Detection and repairing of these defects are necessary for the safety of drivers, passengers, and vehicles from mechanical faults. In this modern era, autonomous vehicles are an active research area that controls itself with the help of in-vehicle sensors without human commands, especially after the emergence of deep learning (DNN) techniques. A combination of sensors and DNN techniques can be useful for unmanned vehicles for the perception of their surroundings for the detection of tracks and obstacles for smooth traveling based on the deployment of artificial intelligence in vehicles. One of the biggest challenges for autonomous vehicles is to avoid the critical road defects that may lead to dangerous situations. To solve the accident issues and share emergency information, the Intelligent Transportation System (ITS) introduced the concept of vehicular network termed as vehicular ad hoc network (VANET) for achieving security and safety in a traffic flow. A novel mechanism is proposed for the automatic detection of road anomalies by autonomous vehicles and providing road information to upcoming vehicles based on Edge AI and VANET. Road images captured via camera and deployment of the trained model for road anomaly detection in a vehicle could help to reduce the accident rate and risk of hazards on poor road conditions. The techniques Residual Convolutional Neural Network (ResNet-18) and Visual Geometry Group (VGG-11) are applied for the automatic detection and classification of the road with anomalies such as a pothole, bump, crack, and plain roads without anomalies using the dataset from different online sources. The results show that the applied models performed well than other techniques used for road anomalies identification.


Asunto(s)
Accidentes de Tránsito , Aprendizaje Profundo , Accidentes de Tránsito/prevención & control , Inteligencia Artificial , Humanos , Redes Neurales de la Computación , Transportes
13.
Sensors (Basel) ; 21(19)2021 Sep 30.
Artículo en Inglés | MEDLINE | ID: mdl-34640859

RESUMEN

Constrained by traditional fuel-saving technologies that have almost reached the limit of fuel-saving potential, the difficulty in changing urban congestion, and the low market penetration rate of new energy vehicles, in the short term, eco-driving seems to be an effective way to achieve energy-saving and emissions reduction in the transportation industry. This paper reviews the energy-saving theory and technology of eco-driving, eco-driving capability evaluation, and the practical application of eco-driving, and points out some limitations of previous studies. Specifically, the research on eco-driving theory mostly focuses on a single vehicle in a single scene, and there is a lack of eco-driving research for fleets or regions. In addition, the parameters used to evaluate eco-driving capabilities mainly focus on speed, acceleration, and fuel consumption, but external factors that are not related to the driver will affect these parameters, making the evaluation results unreasonable. Fortunately, vehicle big data and the Internet of Vehicles (V2I) provides an information basis for solving regional eco-driving, and it also provides a data basis for the study of data-driven methods for the fair evaluation of eco-driving. In general, the development of new technologies provides new ideas for solving some problems in the field of eco-driving.


Asunto(s)
Conducción de Automóvil , Aceleración , Tecnología , Transportes
14.
Sensors (Basel) ; 21(19)2021 Sep 30.
Artículo en Inglés | MEDLINE | ID: mdl-34640894

RESUMEN

COVID-19 has dramatically struck each section of our society: health, economy, employment, and mobility. This work presents a data-driven characterization of the impact of COVID-19 pandemic on public and private mobility in a mid-size city in Spain (Fuenlabrada). Our analysis used real data collected from the public transport smart card system and a Bluetooth traffic monitoring network, from February to September 2020, thus covering relevant phases of the pandemic. Our results show that, at the peak of the pandemic, public and private mobility dramatically decreased to 95% and 86% of their pre-COVID-19 values, after which the latter experienced a faster recovery. In addition, our analysis of daily patterns evidenced a clear change in the behavior of users towards mobility during the different phases of the pandemic. Based on these findings, we developed short-term predictors of future public transport demand to provide operators and mobility managers with accurate information to optimize their service and avoid crowded areas. Our prediction model achieved a high performance for pre- and post-state-of-alarm phases. Consequently, this work contributes to enlarging the knowledge about the impact of pandemic on mobility, providing a deep analysis about how it affected each transport mode in a mid-size city.


Asunto(s)
COVID-19 , Pandemias , Humanos , SARS-CoV-2 , España , Transportes
15.
Sensors (Basel) ; 21(19)2021 Oct 05.
Artículo en Inglés | MEDLINE | ID: mdl-34640940

RESUMEN

Collaborative part transportation is an interesting application as many industrial sectors require moving large parts among different areas of the workshops, using a large amount of the workforce on this tasks. Even so, the implementation of such kinds of robotic solutions raises technical challenges like force-based control or robot-to-human feedback. This paper presents a path-driven mobile co-manipulation architecture, proposing an algorithm that deals with all the steps of collaborative part transportation. Starting from the generation of force-based twist commands, continuing with the path management for the definition of safe and collaborative areas, and finishing with the feedback provided to the system users, the proposed approach allows creating collaborative lanes for the conveyance of large components. The implemented solution and performed tests show the suitability of the proposed architecture, allowing the creation of a functional robotic system able to assist operators transporting large parts on workshops.


Asunto(s)
Brazo , Robótica , Algoritmos , Ambiente , Humanos , Transportes
16.
Artículo en Inglés | MEDLINE | ID: mdl-34639475

RESUMEN

The conditions of work for professional drivers can contribute to adverse health and well-being outcomes. Fatigue can result from irregular shift scheduling, stress may arise due to the intense job demands, back pain may be due to prolonged sitting and exposure to vibration, and a poor diet can be attributed to limited time for breaks and rest. This study aimed to identify working conditions and health outcomes in a bussing company by conducting focus groups and key informant interviews to inform a Total Worker Health® organizational intervention. Our thematic analysis identified three primary themes: lack of trust between drivers and supervisors, the scheduling of shifts and routes, and difficulty performing positive health behaviors. These findings demonstrate the value of using participatory methods with key stakeholders to determine the unique working conditions and pathways that may be most critical to impacting safety, health, and well-being in an organization.


Asunto(s)
Conducción de Automóvil , Vehículos a Motor , Fatiga , Humanos , Ocupaciones , Transportes
17.
Sensors (Basel) ; 21(20)2021 Oct 11.
Artículo en Inglés | MEDLINE | ID: mdl-34695948

RESUMEN

Timely and accurate traffic speed predictions are an important part of the Intelligent Transportation System (ITS), which provides data support for traffic control and guidance. The speed evolution process is closely related to the topological structure of the road networks and has complex temporal and spatial dependence, in addition to being affected by various external factors. In this study, we propose a new Speed Prediction of Traffic Model Network (SPTMN). The model is largely based on a Temporal Convolution Network (TCN) and a Graph Convolution Network (GCN). The improved TCN is used to complete the extraction of time dimension and local spatial dimension features, and the topological relationship between road nodes is extracted by GCN, to accomplish global spatial dimension feature extraction. Finally, both spatial and temporal features are combined with road parameters to achieve accurate short-term traffic speed predictions. The experimental results show that the SPTMN model obtains the best performance under various road conditions, and compared with eight baseline methods, the prediction error is reduced by at least 8%. Moreover, the SPTMN model has high effectiveness and stability.


Asunto(s)
Redes Neurales de la Computación , Transportes
18.
Sensors (Basel) ; 21(20)2021 Oct 18.
Artículo en Inglés | MEDLINE | ID: mdl-34696118

RESUMEN

Internet of Things (IoT) and 5G are enabling intelligent transportation systems (ITSs). ITSs promise to improve road safety in smart cities. Therefore, ITSs are gaining earnest devotion in the industry as well as in academics. Due to the rapid increase in population, vehicle numbers are increasing, resulting in a large number of road accidents. The majority of the time, casualties are not appropriately discovered and reported to hospitals and relatives. This lack of rapid care and first aid might result in life loss in a matter of minutes. To address all of these challenges, an intelligent system is necessary. Although several information communication technologies (ICT)-based solutions for accident detection and rescue operations have been proposed, these solutions are not compatible with all vehicles and are also costly. Therefore, we proposed a reporting and accident detection system (RAD) for a smart city that is compatible with any vehicle and less expensive. Our strategy aims to improve the transportation system at a low cost. In this context, we developed an android application that collects data related to sound, gravitational force, pressure, speed, and location of the accident from the smartphone. The value of speed helps to improve the accident detection accuracy. The collected information is further processed for accident identification. Additionally, a navigation system is designed to inform the relatives, police station, and the nearest hospital. The hospital dispatches UAV (i.e., drone with first aid box) and ambulance to the accident spot. The actual dataset from the Road Safety Open Repository is used for results generation through simulation. The proposed scheme shows promising results in terms of accuracy and response time as compared to existing techniques.


Asunto(s)
Internet de las Cosas , Accidentes , Simulación por Computador , Primeros Auxilios , Transportes
19.
Artículo en Inglés | MEDLINE | ID: mdl-34682469

RESUMEN

The health and welfare of older adults have raised increasing attention due to global aging. Cycling is a physical activity and mode of transportation to enhance the mobility and quality of life among older adults. Nevertheless, the planning strategies to promote cycling among older adults are underutilized. Therefore, this paper describes the nonlinear associations of the built environment with cycling frequency among older adults. The data were collected from the Zhongshan Household Travel Survey (ZHTS) in 2012. The modeling approach was the eXtreme Gradient Boosting (XGBoost) model. The findings demonstrated that nonlinear relationships exist among all the selected built environment attributes. Within specific intervals, the population density, the land-use mixture, the distance from home to the nearest bus stop, and the distance from home to CBD are positively correlated to the cycling among older adults. Additionally, an inverse "U"-shaped relationship appears in the percentage of green space land use among all land uses. Moreover, the intersection density is inversely related to the cycling frequency among older adults. These findings provide nuanced and appropriate guidance for establishing age-friendly neighborhoods.


Asunto(s)
Entorno Construido , Planificación Ambiental , China , Calidad de Vida , Características de la Residencia , Transportes , Caminata
20.
Artículo en Inglés | MEDLINE | ID: mdl-34682631

RESUMEN

Perceived safety remains one of the main barriers for children to participate in active commuting to school (ACS). This ecological study examined the associations between the number of police-reported crimes in school neighborhoods and ACS. The percentage of active travel trips was assessed from a teacher tally survey collected from students across 63 elementary schools that were primarily classified as high-poverty (n = 27). Geographic Information System (GIS) was used to create a detailed measure of police-reported crimes during 2018 and neighborhood covariates that occurred within a one-mile Euclidean buffer of the schools. Statistical analyses included linear fixed effects regressions and negative binomial regressions. In fully-adjusted models, reported crime did not exhibit significant associations with ACS. Medium-poverty schools were indirectly associated with ACS when compared to high- and low-poverty schools in all models (p < 0.05). Connectivity and vehicle ownership were also directly associated with ACS (p < 0.05). Low- and medium-poverty schools were indirectly associated with all types of reported crime when compared to high-poverty schools (p < 0.05). Although reported crime was not associated with school-level ACS, differences in ACS and reported crime do exist across school poverty levels, suggesting a need to develop and promote safe and equitable ACS interventions.


Asunto(s)
Policia , Caminata , Niño , Crimen , Estudios Transversales , Humanos , Características de la Residencia , Instituciones Académicas , Transportes
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