Age-related risk factors with nonfatal traffic accidents in urban areas in Maringá, Paraná, Brazil

Traffic Inj Prev. 2017 Feb 17;18(2):157-163. doi: 10.1080/15389588.2016.1235786. Epub 2016 Sep 13.

Abstract

Objective: The present study aimed to analyze the factors associated with the occurrence of nonfatal traffic accidents regarding age.

Methods: A retrospective, transversal, and analytical study was carried out in the municipality of Maringá, Paraná, Brazil, based on data from Boletins de Ocorrência de Acidente de Trânsito ("Police Occurrence Bulletins"; BOATs). Following probability sampling, the sociodemographic aspects, logistics, environmental conditions, and time of occurrence of 418 cases of accidents were analyzed. The age of the victims was considered to be the dependent variable. The data were analyzed using descriptive statistics and bivariate, multivariate, and variance analysis, considering a confidence interval of 95% and a significance level of 5% (P <.05).

Results: Results revealed that young people (15-29 years) were twice as likely to be hospitalized due to severe injuries. Young motorcyclists had a 2.5 times greater chance of suffering accidents (P <.001); the use of other vehicles such as cars, bicycles, buses, and trucks represented a protective factor for this group (P <.05). Multiple logistic regression revealed that the main predictors for the occurrence of accidents were being single, having over 8 years of education, having had a driver's license for less than 3 years, roads with low luminosity, and driving at night.

Conclusions: Demographic, environmental, and logistical factors were associated with morbidity due to traffic accidents among young people. These results challenge society and policy makers to create more effective strategies to minimize this serious public health problem.

Keywords: Injury prevention; nonfatal victims; risk factors; traffic accident; urban area.

MeSH terms

  • Accidents, Traffic / statistics & numerical data*
  • Adolescent
  • Adult
  • Age Factors
  • Automobile Driving / statistics & numerical data*
  • Brazil / epidemiology
  • Female
  • Humans
  • Logistic Models
  • Male
  • Retrospective Studies
  • Risk Factors
  • Urban Population
  • Young Adult