Logit model with social factors for motorcycle accident gravity
DOI:
https://doi.org/10.14295/transportes.v29i1.2349Keywords:
Motorcycle, Rural transport, Accidents, Social inclusion, LogitAbstract
This paper aims to assess whether the victims' socioeconomic attributes, such as education, income and gender, are decisive in increasing the likelihood of being involved in a fatal crash. A stepwise logit model was used to determine factors that influence traffic accident’s severity. 689 questionnaires with socioeconomic and crash related data, from DPVAT (Brazil’s crash victims’ universal insurance) applicants from the state of Alagoas, between 2013 and 2019 were used to estimate the model. Results show that the variables sex, education, motorcycle size, helmet, being licensed and accidents on weekends are significant. That is, in addition to crash related factors, factors inherent to the individual's social group influence his/her probability of death. Knowing such factors is crucial to identify the social groups that are most vulnerable to traffic mortality and thus develop focused public policies.
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Copyright (c) 2021 Jessica Helena de Lima, Maria Leonor Alves Maia, Anderson Moreira Aristides dos Santos
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