Modeling Injury Severity Among Motor Vehicle Occupants Using a Safe System–Aligned, Population-Based Framework: Evidence from Ohio Crash Data (2017–2023)

This dataset supports a multilevel Safe System analysis of motor vehicle crashes in Ohio between 2017 and 2023. Derived from the Ohio Department of Public Safety’s traffic crash reports, the dataset includes over 41,000 cases involving suspected serious injuries (SSIs) and fatalities. Each case is described across three hierarchical levels—Crash, Unit (vehicle), and Person—enabling multivariate modeling of injury severity. Data cleaning and validation were performed in R, and Vehicle Identification Numbers (VINs) were decoded using the NHTSA VIN Decoder to determine vehicle year and safety feature availability.Risk factors were coded into four Safe System domains—People, Vehicle, Road, and Speed—allowing both individual and combined effects to be examined. Key risk factors include impaired or distracted driving, non-use of seat belts, vehicle model year prior to 2010, road departures, and unsafe speed. Each injury case is annotated for the presence or absence of 12 system-level risk factors, enabling advanced modeling of injury probability based on factor combinations. This dataset facilitates exploration of systemic contributors to crash severity and supports the development of data-informed, integrated countermeasures to reduce severe and fatal outcomes. The structure, coding, and metadata make it readily adaptable for replication by other jurisdictions.