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OP14 Funding for preventative Children’s services and rates of children entering care: a natural experiment using longitudinal area-level data in England
  1. Davara Bennett1,
  2. Calum Webb2,
  3. Kate Mason1,
  4. Daniela Schlüter1,
  5. Katie Fahy1,
  6. Alexandros Alexiou1,
  7. Sophie Wickham1,
  8. Ben Barr1,
  9. David Taylor-Robinson1
  1. 1Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK
  2. 2Department of Sociological Studies, University of Sheffield, Sheffield, UK


Background Children in state care face a range of adverse health outcomes, throughout the life course, relative to the general population. In England, over the last decade, the rate of children entering care has increased. The rate of change differs markedly for older and younger children, who may experience very different preventative services. Policies trailing the 2008 recession have led to inequitable reductions in spending on these services. Our aim was therefore to assess the impact of cuts to prevention on rates of preschool children and adolescents entering care between 2012 and 2019.

Methods Our outcomes were annual rates of children entering care across 150 English local authorities (LAs) (2012–19) for those aged 1–4, and young people aged 16–17. For the younger age group, count data were drawn from the Department for Education ‘children looked after data return’. For the older age group, a Freedom of Information request yielded count data excluding unaccompanied children seeking asylum, whose care status will be largely unaffected by changes in our exposure of interest. Our exposure was age-relevant Children’s Services prevention spend (2011–18), taken from LA expenditure outturns. Regression models were used to quantify, within LAs, associations between changing prevention spend and changing rates of children entering care the following year, while controlling for employment and child poverty rates. Models were estimated using the ‘panelr’ package, R version 3.6.3.

Results We found no association between changing prevention spend and changing rates of 1–4 year olds entering care. However, spending reductions were associated with rising rates for adolescents. We estimate that every £10 per child decrease in prevention spend was associated with an additional 1.9 per 100,000 children aged 16–17 entering care the following year (95% CI 0.7, 2.9). According to our model, between 2012 and 2019, approximately 1 in 25 care entries in this age group were linked to the cuts.

Conclusion This study offers evidence that rising rates of older children entering care were partly driven by cuts to prevention services. These children face significant health and social risks in adulthood. Policies to tackle adverse trends in adolescent care entry should promote reinvestment in youth services, placing ordinary help on a robust statutory footing. We did not find comparable evidence for the younger age group, for whom rising poverty may be more important risk factors for care entry. Limitations, including issues relating to aggregate data, data quality and specification of causal lags, are assessed.

  • child health
  • inequalities
  • longitudinal research
  • local government

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