International Journal of Injury Control and Safety Promotion最新文献

Wearable systems for knee pathology detection and prosthetic control remain constrained by diagnostic limitations or rigid actuation. This study introduces an integrated two-phase framework combining non-invasive screening with adaptive prosthetic control. Phase 1 employs novel time-frequency features (Enhanced Mean Absolute Value/Enhanced Wavelength), achieving 94.7% abnormality detection accuracy via Extra Trees classifier, a + 3.16% improvement over conventional features, which is validated through 10-fold cross-validation and rigorous statistical testing (Friedman/Nemenyi, 95% confidence intervals). SHAP analysis yields clinician-interpretable thresholds (e.g. Semitendinosus EMAV > 0.3 mV). Phase 2 utilises multimodal fusion (EMG, FSR, IMU) to achieve 99.2% gait phase accuracy with XGBoost, enabling real-time health-adaptive prosthetic control that dynamically modulates: phase-transition timing (400 ms abnormal vs. 300 ms normal), EMG thresholds (0.15 mV vs. 0.10 mV), and motor gains (2.5× vs. 1.0×) based on pathology status. Validated in a LabVIEW-based control environment across variable terrains and speeds, this end-to-end diagnostics-to-control implementation delivers superior screening accuracy (>4.7% gain vs. deep learning) while enabling context-aware prosthetic adaptation, establishing a new paradigm for accessible musculoskeletal rehabilitation.

Rear-end and side-impact crash risks are the two principal types of multi-vehicle crash risk on freeways. Most previous studies examine a single crash risk type, limiting understanding of their combined effects. This study employs a multilevel structural equation modelling (SEM) framework to investigate the sequential and joint impacts of roadway geometry, dynamic traffic flow, and driving behaviour on multi-type crash risks. The framework was calibrated using 1,762 rear-end and 1,243 lane-changing conflicts from 14 directional sites. The multilevel SEM accounts for site-level heterogeneity to produce more robust estimates. The path analysis identifies two dominant causal chains: 'Horizontal Curve - Density - Car-following Behaviour - Crash Risk' and 'Vertical Slope - Speed Distribution - Lane-changing Behaviour - Crash Risk'. Low-speed fluctuating traffic flow shows higher crash risks than high-speed stable traffic flow. Car-following behaviour increases both rear-end and side-impact risks, while lane-changing activity raises side-impact risk but reduces rear-end risk.

Disproportionately more of the world's fatalities and injuries on the roads occur in low- and middle-income countries, despite these countries having approximately only 60% of the world's vehicles. Injury rates due to motor-vehicles are related to a complex multidimensional array of risk factors, embedded in the social and economic infrastructure of a country or region. Whether environmental infrastructure factors differ in determining the risk of an injury for motor vehicle occupants compared to pedestrians and other vulnerable road users has not been extensively studied. We explored the role of environmental infrastructure factors on motor-vehicle-related non-fatal injury using the Prospective Urban and Rural Epidemiology (PURE) cohort study of 162,793 adults from 23 high-, middle- and low-income countries. As expected, low-income countries had slightly higher motor vehicle injury rates, with pedestrians tending to have higher injury rates in these countries. There was considerable variation in motor vehicle injury rates within country-income-categories, while there were similarities in motor vehicle injury rates despite large differences in motorization of countries. There was a meaningful community effect on motor vehicle injury rates. We found that community-level infrastructure risk factors for motor vehicle injuries differed for car occupants and for pedestrians, with road quality and alcohol use being the main factors associated with an injury for car occupants, while poor roadside infrastructure (streetlights, sidewalks) and alcohol use were the main risk factors for an injury as a pedestrian.

Active transport, such as walking and bicycling, are being promoted as leading to healthy lifestyle habits and reduced pollution. These require improved walkability for pedestrians, but also separation from motorized vehicles, which leads to recommending that low-and middle-income countries devote more funds for roadway quality and streetlight infrastructure. Policies to reduce motor vehicle injuries should be supported at the national level, but should be specific at the community level, since they must be focused on the specific local infrastructure. Countermeasures for reducing road transport injuries for pedestrians have different risk factors than for reducing injuries for car occupants.

This study evaluated how correct use of child protective equipment (child restraint systems, seat belts, and helmets) influences predicted injury severity for children involved in police-reported road crashes. Data from 69,108 participants under 18 years were analyzed, covering occupant, vehicle, roadway, environmental, and protection factors. An XGBoost classifier achieved ROC AUC = 0.8186 with balanced accuracy, precision, and recall. SHAP interpretation identified seating position and participant type as the most influential predictors. Counterfactual simulations, assuming full compliance with protective-equipment use, showed improved predicted outcomes in 64 cases, while 15 worsened. Helmet non-use was the most frequent lapse. Consistent, correct use of protective devices significantly shifts predicted outcomes toward less severe injuries. The explainable machine-learning and counterfactual framework quantifies the benefits of compliance and provides actionable evidence for targeted education, enforcement, and vehicle-safety design. The approach can be extended to other vulnerable groups, including pregnant occupants.

Despite advancements in occupational safety management, injury prevention remains a persistent challenge across industries. This study presents a data-driven investigation into severe occupational injuries using publicly available reports from the U.S. OSHA. Employing Association Rule Mining (ARM) combined with thematic analysis, we identify distinct industry-specific injury profiles and uncover interrelated risk patterns. Key findings indicate a prevalence of finger injuries in manufacturing, falls and burns in construction, lower limb injuries in transportation and wholesale sectors, frequent fall-related incidents in retail, burn and hand injuries in mining and high rates of lower back injuries in healthcare settings. The analysis reveals complex co-occurrence patterns among contributing risk factors, such as task type, environmental conditions and body part affected, that influence both the type and severity of injuries. These insights offer valuable guidance for designing targeted, sector-specific safety interventions and underscore the importance of leveraging occupational injury data to inform evidence-based prevention strategies.

This study examined visual attention in children's street-crossing behaviour using a virtual reality (VR) environment with integrated eye-tracking. We hypothesized that older children would spend more time and a higher proportion of time focusing on vehicles, that boys would spend less time looking at vehicles than girls, and that greater visual attention would be associated with fewer dangerous crossings. A total of 377 children aged 7 to 10 completed six VR street-crossing trials, during which their gaze behaviour was recorded and analysed using linear regression. Results showed that older children spent a higher proportion of time looking at vehicles, indicating developmental improvements in attention. Boys spent less total time focusing on vehicles. Greater visual attention to vehicles was associated with fewer dangerous crossings, underscoring its role in pedestrian safety. These findings highlight developmental differences in gaze and the importance of attention to traffic-relevant elements.

The Bedouin population of the Negev experiences the highest child mortality rate from unintentional childhood injury (UCI) in Israel. This study examines the underlying mechanisms of fatal UCI in Bedouin communities and proposes the culturally tailored prevention strategies. Data were collected from multiple sources, including national mortality records, hospitalization and emergency department data, and the Israel Trauma Registry. UCI mortality among Arabs was 2.9 times higher than among Jews, with traffic accidents as the leading cause. Bedouin communities had a 3.14-fold higher UCI mortality rate than other Muslim communities and 2.7 times higher than Arab municipalities with religious heterogeneity. Over half (53.3%) of UCI deaths in Bedouin towns and villages occurred near the home, significantly higher than the national average, often involving toddlers (0-4 years) run over by family members. These findings underscore the need for community-driven, evidence-based interventions to reduce UCI mortality in Bedouin populations and improve child safety in marginalized communities.

Road traffic accidents (RTAs) remain a significant public health challenge in India, causing substantial fatalities, injuries, and economic losses. Despite global improvements in road safety, India's performance has been subpar, accounting for a significant portion of the worldwide number of road fatalities. Between 2012 and 2022, RTA-related deaths in India rose by 23%, contrasting with a 5% global decline. This study employs the Seasonal Autoregressive Integrated Moving Average with Exogenous variables (SARIMAX) model to forecast future RTA trends in India, taking into account the COVID-19 pandemic as an external factor. While traditional models, such as SARIMA, effectively capture historical patterns, they often overlook external shocks, including pandemic-induced changes in mobility. By integrating pandemic-related disruptions, the SARIMAX model offers more robust, data-driven forecasts. Analysis of monthly RTA data from 2010 to 2022 suggests that, without intervention, annual crash rates could exceed 440,000 cases. The findings underscore the urgent need for comprehensive measures, including stronger policies, improved infrastructure, stricter law enforcement, and advanced technologies like AI-driven monitoring systems, to enhance road safety in the post-pandemic era.

The achievement of Sustainable Development Goals 3 (Good Health and Well-Being) and 8 (Decent Work and Economic Growth) requires addressing the occupational health challenges and unsafe working conditions faced by industrial workers in slums, particularly migrant laborers lacking adequate training and literacy. This study examines health challenges among 320 slum-dwelling workers across 17 industries in West Bengal, categorized into civil/mechanical, textile, consumable, and chemical sectors. employed across 17 industries in West Bengal, categorized into civil/mechanical, textile, consumable, and chemical sectors. Using multi-stage random sampling, findings reveal that chronic illnesses are more prevalent in textile and consumable industries, while acute injuries dominate civil/mechanical and chemical sectors due to hazardous conditions. It may create a significant financial burden exacerbated by the absence of sick leave or insurance benefits. The study underscores the urgent need for industry-specific interventions, including accessible healthcare, safety training, and comprehensive insurance schemes. .

The promotion of cycling as one of the most popular measures to drive sustainable urban mobility, and the rise in bicycle usage have triggered a debate on the consequences of the coexistence of different transportation modes. This interaction process has been developed rapidly in countries like Spain, where cycling has been fast-tracked. This paper analyzes the safety effect of coexistence in terms of urban traffic accidents. Our case study comprises 50 Spanish NUTS-3 regions, with an econometric model applied to a data panel based on Big Data for the period 2008-2019. The results point to a lack of equilibrium between the rapidly rising number of urban cycling trips and the adaptation of specific regulations and road user behavior. The development of specific awareness strategies, investment in clear and specific signage, traffic surveillance, and a more standardized regulation framework during the first month of bicycle promotion policies is recommended, with the appropriate data collection and monitoring of bicycle trips.