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Table 5 Predicted probabilities of injury or death for drivers and passengers in varying farm crash scenarios using the model 3 estimated coefficients from Table 1

From: Public health application of predictive modeling: an example from farm vehicle crashes

The risk or injury or death in a farm crash in Iowa for a 25–34 year old, male, in growing season, clear weather, between 6:00–11:59 am, daylight, heading straight, passengers on board (for single vehicle crash, manner of collision = non collision; for multiple vehicle crash, manner of collision = rear end)
Vehicle/ occupant type Seat belt Driver contributing circumstances Risk of injury or death (%)
Single vehicle crash Multiple vehicle crash
Farm vehicle driver Yes None 16.7% 7.3%
Farm vehicle passenger 17.8% 7.8%
Non-farm vehicle driver   28.7%
Non-farm vehicle passenger   30.3%
Farm vehicle driver Yes Disregarded traffic regulations 22.2% 10.1%
Farm vehicle passenger 23.6% 10.8%
Non-farm vehicle driver   36.4%
Non-farm vehicle passenger   38.2%
Farm vehicle driver No None 39.8% 20.6%
Farm vehicle passenger 41.6% 21.8%
Non-farm vehicle driver   57.0%
Non-farm vehicle passenger   58.8%
Farm vehicle driver No Disregarded traffic regulations 48.5% 26.9%
Farm vehicle passenger 50.4% 28.4%
Non-farm vehicle driver   65.3%
Non-farm vehicle passenger   67.0%