Investigating effective factors on rural crash severity at marginal areas around cities in Iran: a partial proportional odds modelling approach

Int J Inj Contr Saf Promot. 2024 Jun;31(2):225-233. doi: 10.1080/17457300.2023.2300439. Epub 2024 Jan 4.


Over the past decade, rural crashes have been responsible for an average of 65% of crash-induced casualties in Iran. Evidence from prior studies reveals that a significant number of these rural crashes occur at marginal areas around cities. Thus, Exclusive crash severity models should be developed to identify the factors associated with higher injury and fatality probabilities in these areas. In this study, a partial proportional odds (PPO) model was formulated using the rural crash data collected from roads leading to the city of Isfahan. The PPO model holds the ordinal nature of crash observations and allows for different influences of independent variables on various crash severity levels. Insights derived from the results reveal that factors such as vehicle traffic maintaining an average speed exceeding 95 km/h, the occurrence of multi-vehicle crashes, the incidence of overturn-type crashes, the at-fault vehicle being a truck/trailer and at-fault or not-at-fault vehicle being a motorcycle, increase the likelihood of more severe rural crashes. Conversely, a foreign vehicle being at-fault, and the driver of the at-fault vehicle aged between 30 and 40 years, tend to diminish the occurrence of severe crashes at marginal areas around cities.

Keywords: Rural highway; crash severity; multinomial logit model; ordered logit model; partial proportional odds model.

MeSH terms

  • Accidents, Traffic* / statistics & numerical data
  • Adolescent
  • Adult
  • Cities
  • Female
  • Humans
  • Iran / epidemiology
  • Male
  • Middle Aged
  • Models, Statistical
  • Risk Factors
  • Rural Population*
  • Young Adult