Neighbourhood school environment and dental care needs amongst 5-to-11-year-old children attending a local dental facility in South-East England

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To investigate the relationship between neighbourhood school environment and dental care needs of 5-to-11-year-olds attending a local dental facility in Portsmouth, South-East England. Secondary analyses were undertaken using three cross-sectional, open-access datasets. Data included 4 years of children’s electronic dental records from the University of Portsmouth Dental Academy comprising age, gender, tooth extraction history and residential postcodes converted to Index of Multiple Deprivation (IMD) quintiles for census-based geographies called middle-layer super output areas (MSOAs). Additionally, overall effectiveness scores (OES) (1=Outstanding to 4=Inadequate) from Office for Standards in Education, Children’s Services and Skills of neighbouring schools were computed to ‘population-weighted mean OES’. Descriptive, univariate logistic regression and multilevel-modelling analyses investigated contextual-level influence of school-OES on tooth extraction. There were 429-patients [mean-age 7.78 years (SD 1.97 years), female 50.1%] living across 23-MSOAs. Seventy had undergone tooth extraction treatment. Population-weighted mean OES range was 1.74–3.00, while 3.5% and 48% of patients belonged to the most and least deprived IMD-quintiles, respectively. Univariate models revealed age and population-weighted mean OES as statistically significant predictors of tooth extraction ( p < 0.05). Multilevel modelling, controlling for age and population-weighted mean OES indicated likelihood of tooth extraction increased by 15% with increasing age and by 161% for patients living in MSOAs with higher population-weighted mean OES (i.e. poor school-performance). School effectiveness scores remained a significant predictor of tooth extraction in our study when controlling for individual predictors of dental health. Further research is required to assess the role of neighbourhood school environment in predicting child dental health at the national level.

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