International Journal of Injury Control and Safety Promotion最新文献

Occupational health and safety management systems (OHSMSs) have been proposed as a method of managing human health and safety risk and reduce injuries and illnesses. The investigation objective was to determine the association between OHSMS performance, as measured by scores from assessments and inspections, and mishap rates and mishap outcomes. Results for 55 OHSMS assessments/inspections across 15 organizations from the years 2017-2022 were analyzed. Results were paired with 545 mishaps and according to mishap classification, mishap category, and mishap severity. Correlation analysis was conducted to determine strength and significance of association between OHSMS performance and mishap rates. Improved OHSMS performance, as measured by scores from assessments and inspections, was associated with lower severity mishap occurrence such as reduced rates of fatalities, permanent total and partial disability, and property damage. Mishaps involving fatalities and permanent total disability had the strongest association with measured OHSMS performance. This research indicates that higher levels of OHSMS performance may help reduce severe worker injuries and illnesses and reduce mishap costs.

Traditional approaches to monitoring road safety have primarily focused on measuring outcomes such as the number of fatalities and injuries. While effective in capturing overall trends, this macroscopic approach often overlooks the underlying causes of unsafe conditions. Recognizing these limitations, many countries now embrace a safe system-based approach, which emphasizes a holistic view of road safety, considering various elements and their interactions. In response to this shift, this study introduces a five-step framework designed to provide comprehensive coverage and tailored assistance in selecting and utilizing appropriate Road Safety Indicators (RSIs) for more effective performance monitoring. The framework integrates a novel RSIs taxonomy aligned with critical elements of the safe system. It also incorporates an MCDA-based approach to account for decision-makers' preferences when selecting suitable RSIs. A case study demonstrates the practical application of the proposed steps, including the identification, classification, selection, and development of descriptive sheets for each selected RSI, as well as the continuous updating of the RSIs set. The findings offered valuable insights into the commonly used indicators in international road safety reports, while also revealing the limitations of currents metrics and data in fully capturing critical elements and hierarchical level within the road safety management system.

The rail construction industry is notable for its large scale, substantial investment, extensive stakeholders involvement, long construction period, and intricate operation and technology. This industry is among the most dangerous due to the highest number of occupational accident cases worldwide. Therefore, it is crucial to analyse and identify the existing literature on occupational accident factors in rail construction. To address the research aim, the study identified the factors that contribute to occupational accidents using systematic review methodology. This systematic literature review adheres to the rigorous Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement. Relevant publications from the past 25 years were retrieved from Scopus, Web of Science (WoS), and Science Direct electronic databases. Through a meticulous review of 43 selected publications, five accident factor themes were discovered: worker, workplace, materials and equipment, organizational, and environmental influences. The detailed analysis of these themes has led to the identification of 19 specific sub-factors within these categories, providing a granular understanding of the intricate elements contributing to accidents. This study offers a foundational understanding of accident factors in the rail construction industry, paving the way for targeted OSH interventions aimed at preventing occupational accidents in the future.

Even though accidents with pedestrians are more likely to have a severe or fatal outcome, most research concentrates on the vehicle part of the accidents. To make better policies and infrastructure decisions it is crucial to understand how and why such accidents happen. In this article, 2.588 pedestrian accidents from the year 2018 that resulted in injury or death in the city of Ankara, Türkiye are considered, and different attributes are analyzed co-location-wise. Three types of analysis will be undertaken for these accidents: temporal, natural environment, and pedestrian characteristics. The season of the year, weekend-weekday, and time of day will be explored for the temporal analysis. Visibility (daylight, twilight, and darkness) and rain are the natural surroundings of interest. The analyzed pedestrian characteristics are age group, gender, clothing colour, and nationality. Generally, the accident properties are evenly distributed and mostly the higher co-locations occur with themselves. Three important results stand out in this study. Firstly, the type of precaution appropriate to different time periods of the day should be applied, taking into account the locations that have the strongest co-location with themselves. Secondly, a seasonal approach should be adopted in determining places where pedestrian safety needs to be increased in the city. Lastly, pedestrian safety measures targeting especially both '0-14 and 65 + age groups' and 'foreign citizenship' should be prioritized in the identified locations. The results show that the co-location methodology is a good fit for analyzing pedestrian accidents and a wider use of this methodology for other accident types and in general might be beneficial.

Understanding the nature of traffic accidents in relation to urban access networks is crucial for building safer and more resilient cities. This paper examines the issue of traffic accidents through the lenses of urban configurational theory and urban land use. Three data layers were used in the study, including space syntax analysis conducted in Depthmap X, geotagged traffic accidents collected by the police department, and geotagged land-use data. The method involved superimposing these data layers and exploring potential correlations using a geographic information system (GIS). The findings indicate significant correlations between the spatial frequency of traffic accidents and the choice measure (at 2500 m), local integration, and active land use. The findings of this study can help inform planners and policymakers about the best location to implement safety measures to reduce the risk of traffic accidents in urban access networks.

The shoulder width, as a geometric element, plays a crucial role in enhancing highway safety. Research from high-income countries indicates that improving shoulders on highways leads to substantial safety benefits. However, the safety effectiveness of paved shoulders for low- and middle-income countries (LMICs) highway contexts has limited evidence. This study evaluated the safety effectiveness of the paved shoulder width on 61 km, four-lane, divided rural intercity highways in India. The first objective was to evaluate highway crash patterns using data from 2016 to 2019. The second objective was to evaluate the safety effectiveness of paved shoulder width using the case-control approach. The findings of this study demonstrate a consistent decline in the likelihood of crashes as the shoulder's width increases within the range of zero to 2.5 m for the 100 m segment length and zero to 1.7 m for the 500 m segment length. Nevertheless, model estimates indicate an increased crash risk for shoulders wider than 2.5 m. The results also suggested that the odds ratio for paved shoulder widths ranging from no shoulder to 2.5 m is likely to follow the crash modification factor from the highway safety manual. The findings of this study hold significant implications for the design policy of shoulder width on rural highways in LMICs.

Machine learning (ML) models are widely employed for crash severity modelling, yet their interpretability remains underexplored. Interpretation is crucial for comprehending ML results and aiding informed decision-making. This study aims to implement an interpretable ML to visualize the impacts of factors on crash severity using 5 years of freeways data from Iran. Methods including classification and regression trees (CART), K-nearest neighbours (KNNs), random forest (RF), artificial neural network (ANN) and support vector machines (SVM) were applied, with RF demonstrating superior accuracy, recall, F1-score and ROC. The accumulated local effects (ALE) were utilized for interpretation. Findings suggest that light traffic conditions ($\text{volume}/\text{capacity}<0.5$) with critical values around 0.05 or 0.38, and higher proportion of large trucks and buses, particularly at 10% and 4%, are associated with severe crashes. Additionally, speeds exceeding 90 km/h, drivers younger than 30 years, rollover crashes, collisions with fixed objects and barriers, nighttime driving and driver fatigue elevate the likelihood of severe crashes.

This study examines the impact of urban form and street infrastructure on pedestrian safety in Atlanta, Georgia, and Boston, Massachusetts. With a significant rise in pedestrian fatalities over the past decade, understanding how cities' built environments influence safety is critical. We conducted geospatial analyses and statistical tests, revealing unique patterns in each city. Atlanta's sprawling, motorist-oriented layout is associated with increased pedestrian accidents, particularly at crosswalks, due to limited land use diversity, arterial roads, and streets with high speed limits and multiple lanes. In contrast, Boston's compact, pedestrian-oriented design leads to improved safety, featuring safer pedestrian crossings, greater land use diversity, reduced arterial roads and lower speed limits on single-lane streets. This study also highlights the importance of diverse urban forms and pedestrian infrastructure in shaping pedestrian safety. While population density and land use diversity impact accident rates, the presence of crosswalks and street configurations play crucial roles. Our findings underscore the urgency for urban planners to prioritize pedestrian safety through targeted interventions, such as enhancing crosswalks, reducing speed limits and promoting mixed land use. Future research should explore additional variables, alternative modelling techniques and non-linear approaches to gain a more comprehensive understanding of these complex relationships.

A well-developed road network plays a crucial role in fostering social and economic progress within a region. However, road crashes resulting in massive injuries and deaths profoundly affect socioeconomic development. There is a need therefore to identify working approaches used in road safety strategic management which provide evidence and a foundation to achieve safer road transport. This may be achieved through a systematic literature review considering both state-of-the-art technologies and best practice. Such a review is presented in this paper. The review involved searching twenty-six bibliographic databases and twenty-four websites of road-related organizations. Following the EPPI-Reviewer methodology, the researchers identified 30 studies that demonstrated various methods employed in the strategy development process. The review highlighted the prevalence of information technology in crash data analysis, particularly concerning big data applications. Moreover, existing resource allocation methods primarily focus on local countermeasures prioritization and ranking based on benefit cost analysis. However, the review identified a gap in comprehensive crash database understanding, and only a few single-objective optimization methods have been developed for strategy development, while there is a need for data mining methods and multi-objective optimisation methods supported by expert knowledge.