Modeling injury severity among motor vehicle occupants using a safe system-aligned, population-based framework: evidence from Ohio crash data (2017-2023).
DOI: 10.1186/s40621-026-00676-3
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Summary
This study addresses the fragmented nature of traditional crash safety research, which often examines risk factors in isolation rather than evaluating how they interact within a broader system. Motivated by the Safe System Approach (SSA), which posits that serious injuries result from the simultaneous failure of multiple system layers, the authors sought to quantify the population-level probability of suspected serious injury (SSI) or fatality associated with combinations of crash-related factors. The research aims to move beyond siloed analyses to identify system vulnerabilities and prioritize integrated countermeasures. The researchers analyzed statewide crash data from Ohio spanning 2017 to 2023, sourced from the Ohio Department of Public Safety. The final analytic dataset included 578,796 injured vehicle occupants, comprising 36,061 SSIs and 5,152 fatalities. Variables were categorized into four SSA domains: People (e.g., impairment, restraint use), Vehicle (e.g., model year), Road (e.g., roadway departure, curves), and Speed (e.g., unsafe speed). Using multivariable proportional odds logistic regression, the study estimated adjusted odds and predicted probabilities of severe outcomes for individual risk factors and their co-occurring combinations. Marginal effects were calculated to assess changes in predicted risk across varying profiles. Results indicated that behavioral factors, specifically driver impairment and lack of restraint use, were associated with the largest increases in the predicted probability of serious or fatal injury. Vehicle factors, such as older model years (pre-2010), and roadway characteristics, including roadway departure and curved alignments, also significantly contributed to injury risk. Crucially, the highest predicted probabilities of severe outcomes occurred when multiple risk factors were present simultaneously across different SSA domains. For instance, the presence of people-related factors alone increased risk, but the convergence of people, vehicle, road, and speed factors compounded the likelihood of SSI or fatality, demonstrating that severe outcomes are driven by interactions among system elements rather than isolated conditions. The study concludes that serious and fatal crash outcomes arise when layers of protection fail simultaneously, consistent with Safe System principles. By quantifying conditional probabilities for specific combinations of risk factors, the research provides a scalable, data-driven framework for identifying system vulnerabilities. The findings support a shift toward coordinated, multi-domain safety programs, suggesting that strategies simultaneously addressing behavioral risks, vehicle fleet modernization, roadway design improvements, and speed management will yield greater reductions in severe injuries and fatalities than single-domain approaches. This evidence underscores the importance of integrated countermeasures for future transportation safety and Vision Zero efforts.
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | PubMed Central | — | — | 1 | 2026-06-19 |
| archive | success | unpaywall | — | — | 2 | 2026-06-26 |
| extract | success | cached | — | — | 2 | 2026-06-26 |
| clean | success | clean | — | — | 1 | 2026-06-20 |
| chunk | success | chunk | — | — | 1 | 2026-06-20 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-20 |
| enrich | success | openalex | — | — | 1 | 2026-06-20 |
| promote | success | — | — | — | 1 | 2026-06-19 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 1 | 2026-06-26 |
| tag | success | vector_similarity | — | — | 6 | 2026-06-20 |
| verify | success | — | — | — | 1 | 2026-06-26 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.
Topics
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- demographic disparities
- causation analyses
- induced exposure
- incidence prevalence
- fatality injury trends
- comparative international
Information type
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- Empirical Findings: crash risk outcomes