| Summary: | The aim of this thesis is to investigate whether compositional and contextual factors relating to neighbourhoods in which children live can explain differences in their wellbeing, over and above factors at the individual and family level. Data collected on young children, sampled from advantaged, disadvantaged and ethnic minority electoral wards within the UK Millennium Cohort Study (MCS) were used to explore the research objectives. 2001 census small area statistics were uniquely utilised to further characterise MCS wards. Multi-level statistical modelling techniques were employed to analyse these data. Findings suggest that individual and family level factors account for most of the differences in cognitive, behavioural and physical wellbeing. Wards in disadvantaged and ethnic minority areas were shown to be negatively associated with children's readiness to start school and their vocabulary abilities. Behavioural difficulties and the body mass index (BMI) of children were also associated with these wards. Alongside these factors, several subjective measures of the local area were associated with children's wellbeing. Poor local safety and problems with litter were negatively associated with school readiness and vocabulary skills respectively. Problems with noise, pollution, lack of places to play and poor access to shops were associated with children having behavioural difficulties. Problems with litter in the vicinity were also related to children having a higher BMI. Furthermore, some 2001 census small area statistics, characterising the demographic composition of each ward were also associated with child wellbeing. Wards with high numbers of children living in them were associated with poor school readiness scores and areas with high numbers of cohabiting childless couples were associated with children having lower vocabulary scores. Wards with high levels of female lone parents who were employed and married couples with children were associated with fewer child difficulties. None of these census factors were associated with BMI.
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