Measuring variation in childhood mental health supports the development of local early intervention strategies. The methodological approach used to investigate mental health trends (often determined by the availability of individual level data) can affect decision making. We apply two approaches to identify geographic trends in childhood social, emotional, and behavioural difficulties using the Strengths and Difficulties Questionnaire (SDQ). SDQ forms were analysed for 35,171 children aged 4–6 years old across 180 preschools in Glasgow, UK, between 2010 and 2017 as part of routine monitoring. The number of children in each electoral ward and year with a high SDQ total difficulties score (≥15), indicating a high risk of psychopathology, was modelled using a disease mapping model. The total difficulties score for an individual child nested in their preschool and electoral ward was modelled using a multilevel model. For each approach, linear time trends and unstructured spatial random effects were estimated. The disease mapping model estimated a yearly rise in the relative rate (RR) of high scores of 1.5–5.0%. The multilevel model estimated an RR increase of 0.3–1.2% in average total scores across the years, with higher variation between preschools than between electoral wards. Rising temporal trends may indicate worsening social, emotional, and behavioural difficulties over time, with a faster rate for the proportion with high scores than for the average total scores. Preschool and ward variation, although minimal, highlight potential priority areas for local service provision. Both methodological approaches have utility in estimating and predicting children’s difficulties and local areas requiring greater intervention.
|Number of pages
|International Journal of Environmental Research and Public Health
|Early online date
|13 Sept 2022
|Published - 13 Sept 2022
Bibliographical noteFunding: CHiME research was funded by the Scottish Government Health Department, NHS, Greater Glasgow and Clyde, One Glasgow, and the Gillberg Neuropsychiatry Centre.
Acknowledgments: We would like to acknowledge all the preschools, parents, and staff who participated in generating and collecting ChiME data. We would like to thank all ChiME collaborators, in particular Morag Gunion, Michele McClung, Avril Williamson, John Butcher, Christine Wilson, Amanda Kerr, Helen Sweeting, and Kim Jones. We wish to thank Bonnie Auyeung for contributions to this paper
Data Availability StatementData are owned by Glasgow City Council Education Services and are not currently publicly available.
- child development
- disease mapping
- multilevel modelling
- social and emotional difficulties
- early years