T-Space at The University of Toronto Libraries >
School of Graduate Studies - Theses >
Please use this identifier to cite or link to this item:
|Title: ||Neighbourhood Correlates of Child Injury: A Case Sudy of Toronto, Canada|
|Authors: ||Morton, Tanya Rosemary|
|Advisor: ||Hulchanski, J. David|
|Department: ||Social Work|
|Issue Date: ||30-Aug-2012|
|Abstract: ||This study identifies the extent to which neighbourhood socioeconomic trends are related to intentional and unintentional child injuries in Toronto, Ontario. Children living in lower socioeconomic status (SES) neighbourhoods have often been found to face a higher injury death and morbidity rate than more well‐off children. A likely explanation is an increase in the unequal exposure to injury-promoting environments on the basis of the income polarization (a declining middle income group). However, the strength of the inverse relationship between SES and injury is related to a number of factors, including the SES indicator chosen by the researcher. Hence, a goal of the study is to determine whether neighbourhood socioeconomic trends toward income polarization have predictive power in explaining variation in injury rates in young children aged 0-6, over and above more typical measures of SES and neighbourhood disadvantage.
Census data were used to determine socioeconomic trends. Neighbourhoods (census tracts) were divided into three distinct categories based on neighbourhood change in average individual income: neighbourhoods that have been improving, declining, and those displaying mixed trends. This analysis of neighbourhoods was merged with geo-coded hospital-based emergency department data to calculate rates of overall injuries, falls, burns and poisoning. The predictive power of neighbourhood socioeconomic trends on injury was compared to more typical neighbourhood disadvantage measures such as income (high, medium, low), neighbourhood employment rates, education levels, and housing quality from the 2006 census.
Socioeconomic trends contributed significantly to injury outcomes, but the contribution of other neighbourhood disadvantage indicators was higher. Housing in need of repair and individuals with no university degree in a neighbourhood were positively correlated with three of four outcomes. A high immigrant population in a neighbourhood was negatively correlated with three of four outcomes. Neighbourhood socioeconomic trends had slightly more predictive power than the more typical measure of SES (high, medium or low income). Researchers should carefully consider their socioeconomic status measures when predicting injury outcomes.|
|Appears in Collections:||Doctoral|
Items in T-Space are protected by copyright, with all rights reserved, unless otherwise indicated.