BACKGROUND: Child poverty rates are compared throughout Europe to monitor how countries are caring for their children. Child poverty reduction measures need to consider the importance of safe living environments for all children. In this study we investigate how European country-level economic disparity and housing conditions relate to one another, and whether they differentially correlate with child injury mortality. METHODS: We used an ecological, cross-sectional study design of 26 European countries of which 20 high-income and 6 upper-middle-income. Compositional characteristics of the home and its surroundings were extracted from the 2006 European Union Income Social Inclusion and Living Conditions Database (n = 203,000). Mortality data of children aged 1-14 years were derived from the World Health Organization Mortality Database. The main outcome measure was age standardized cause-specific injury mortality rates analysed by income inequality and housing and neighbourhood conditions. RESULTS: Nine measures of housing and neighbourhood conditions highly differentiating European households at country level were clustered into three dimensions, labelled respectively housing, neighbourhood and economic household strain. Income inequality significantly and positively correlated with housing strain (r = 0.62, P = 0.001) and household economic strain (r = 0.42, P = 0.009) but not significantly with neighbourhood strain (r = 0.34, P = 0.087). Child injury mortality rates correlated strongly with both country-level income inequality and housing strain, with very small age-specific differences. CONCLUSIONS: In the European context housing, neighbourhood and household economic strains worsened with increasing levels of income inequality. Child injury mortality rates are strongly and positively associated with both income inequality and housing strain, suggesting that housing material conditions could play a role in the association between income inequality and child health.
BACKGROUND:Child poverty rates are compared throughout Europe to monitor how countries are caring for their children. Child poverty reduction measures need to consider the importance of safe living environments for all children. In this study we investigate how European country-level economic disparity and housing conditions relate to one another, and whether they differentially correlate with child injury mortality. METHODS: We used an ecological, cross-sectional study design of 26 European countries of which 20 high-income and 6 upper-middle-income. Compositional characteristics of the home and its surroundings were extracted from the 2006 European Union Income Social Inclusion and Living Conditions Database (n = 203,000). Mortality data of children aged 1-14 years were derived from the World Health Organization Mortality Database. The main outcome measure was age standardized cause-specific injury mortality rates analysed by income inequality and housing and neighbourhood conditions. RESULTS: Nine measures of housing and neighbourhood conditions highly differentiating European households at country level were clustered into three dimensions, labelled respectively housing, neighbourhood and economic household strain. Income inequality significantly and positively correlated with housing strain (r = 0.62, P = 0.001) and household economic strain (r = 0.42, P = 0.009) but not significantly with neighbourhood strain (r = 0.34, P = 0.087). Child injury mortality rates correlated strongly with both country-level income inequality and housing strain, with very small age-specific differences. CONCLUSIONS: In the European context housing, neighbourhood and household economic strains worsened with increasing levels of income inequality. Child injury mortality rates are strongly and positively associated with both income inequality and housing strain, suggesting that housing material conditions could play a role in the association between income inequality and child health.
Authors: Mathilde Sengoelge; Merel Leithaus; Matthias Braubach; Lucie Laflamme Journal: Int J Environ Res Public Health Date: 2019-02-22 Impact factor: 3.390