Walking to school and traffic exposure in Australian children

Aust N Z J Public Health. 1997 Jun;21(3):286-92. doi: 10.1111/j.1467-842x.1997.tb01701.x.


Daily patterns of pedestrian activity in young children have important health implications, primarily because of the risk of road traffic injury, but also because they may reflect the commencement of exercise habits with long-term consequences. A cross-sectional survey in two Australian cities, Melbourne and Perth, aimed to collect, by parent self-administered questionnaire, population-based data on modes of travel, numbers of street crossings (both accompanied and unaccompanied by an adult), and sociodemographic factors for six- and nine-year-old children. Results indicate that 35 per cent (95 per cent confidence interval (CI) 31 to 39 per cent) and 31 per cent (CI 28 to 34 per cent) walk to school in Melbourne and Perth respectively, while over 60 per cent are driven to school by car, with very small proportions riding bicycles or taking public transport. A higher level of walking was associated with lower levels of several indicators of socioeconomic status. Logistic regression analysis showed that the strongest predictor of walking activity was school type (government versus independent), and after adjusting for this, lesser car ownership, non-English-speaking background and lower occupational category were associated with walking to school, while a different set of predictors--age, sex and maternal education--was associated with the unaccompanied crossing of streets. There was little difference in overall walking levels between boys and girls, but boys were significantly more likely to cross streets unaccompanied (adjusted odds ratio 1.41, CI 1.14 to 1.72), providing a partial explanation of documented sex differences in injury rates.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Accidents, Traffic / statistics & numerical data*
  • Adult
  • Child
  • Cross-Sectional Studies
  • Female
  • Humans
  • Logistic Models
  • Male
  • Schools / classification
  • Students / statistics & numerical data*
  • Surveys and Questionnaires
  • Urban Health
  • Victoria
  • Walking / statistics & numerical data*