Risk factors predisposing to pedestrian road traffic injury in children living in Lima, Peru: A case-control study

Jeffrey M. Pernica, John C. LeBlanc, Giselle Soto-Castellares, Joseph Donroe, Bristan A. Carhuancho-Meza, Daniel G.C. Rainham, Robert H. Gilman

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Objective: To describe the epidemiology of pedestrian road traffic injury in Lima and to identify associated child-level, family-level, and school travel-related variables. Design: Case-control study. Setting: The Instituto Nacional de Salud del Niño, the largest paediatric hospital in the city. Participants Cases were children who presented because of pedestrian road traffic injury. Controls presented with other diagnoses and were matched on age, sex and severity of injury. Results: Low socioeconomic status, low paternal education, traffic exposure during the trip to school, lack of supervision during outside play, and duration of outside play were all statistically significantly associated with case-control status. In multivariate logistic regression, a model combining the lack of supervision during outside play and the number of the streets crossed walking to school best predicted case-control status (p<0.001). Conclusions: These results emphasise that an assessment of children's play behaviours and school locations should be considered and integrated into any plan for an intervention designed to reduce pedestrian road traffic injury. A child-centred approach will ensure that children derive maximum benefit from sorely needed public health interventions.

Original languageEnglish (US)
Pages (from-to)709-713
Number of pages5
JournalArchives of disease in childhood
Volume97
Issue number8
DOIs
StatePublished - Aug 2012

ASJC Scopus subject areas

  • Pediatrics, Perinatology, and Child Health

Fingerprint

Dive into the research topics of 'Risk factors predisposing to pedestrian road traffic injury in children living in Lima, Peru: A case-control study'. Together they form a unique fingerprint.

Cite this