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Socioeconomic differences in childhood injury: a population based epidemiologic study in Ontario, Canada

Abstract

Objective—To determine whether risks for childhood injury vary according to socioeconomic gradients.

Design—Population based, retrospective study. The percentage of individuals living below the poverty line (described ecologically using census data) was the primary measure of socioeconomic status.

Setting—Catchment area of a tertiary medical centre that provides emergency services to all area residents. Area residents aged 0–19 years during 1996 were included.

Observations—Injuries that occurred during 1996 were identified by an emergency department based surveillance system. The study population was divided into socioeconomic grades based upon percentages of area residents living below the poverty line. Multiple Poisson regression analyses were used to quantify associations and assess the statistical significance of trends.

Results—5894 childhood injuries were identified among 35 380 eligible children; 985 children with missing socioeconomic data were excluded. A consistent relation between poverty and injury was evident. Children in the highest grade (indicating higher poverty levels) experienced injury rates that were 1.67 (95% confidence interval 1.48 to 1.89) higher than those in the lowest grade (adjusted relative risk for grades 1-V: 1.00,1.10,1.22,1.42, 1.67; ptrend<0.001). These patterns were observed within age/sex strata; for home, recreational, and fall injuries; and for injuries of minor and moderate severities.

Conclusions—Socioeconomic differences in childhood injury parallel mortality and morbidity gradients identified in adult populations. This study confirms that this health gradient is observable in a population of children using emergency department data. Given the population based nature of this study, these findings are likely to be reflected in other settings. The results suggest the need for targeted injury prevention efforts among children from economically disadvantaged populations, although the exact requirements of the optimal prevention approach remain elusive.

  • injury surveillance
  • socioeconomic status
  • poverty

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