National patterns in paediatric hospital admissions for dental extractions in England.

OBJECTIVES

Paediatric hospital admissions for dental extractions remain a cause for concern, despite decreasing levels of dental diseases in some areas of the country. While local investigations have taken place, little is known about national patterns, and how the relationship between the number of hospital admissions and key independent variables differs across England. The aim of this study was to examine spatial differences in the number of paediatric hospital admissions for extractions in relation to four key independent variables: dental caries, deprivation, units of dental activity and child access to dentists.

METHODS

Hospital admissions data (for all dental-related reasons) were taken from the Hospital Episode Statistics (HES) for England (2017/18) for children and adolescents aged up to 19 years. All data were collected at local authority level. Geographically weighted regression was used to examine associations between the number of hospital admissions and the independent variables, as well as the strength of these associations and how they differed spatially.

RESULTS

Geographically weighted regression revealed considerable differences in the associations between the number of paediatric hospital admissions and the independent variables across England, with distinct regional clusters identified in the data. Some areas exhibited positive associations between independent variables and the number of hospital admissions, such as in Yorkshire and areas of south-west, south-east and north-west England, where greater mean dmft scores were associated with greater numbers of hospital admissions. Negative associations were also found, such as in south-west, north-west and North East England, where higher deprivation scores were associated with lower admission numbers. Despite the patterns found, a much smaller sample of the associations between the independent variables and the number of hospital admissions was statistically significant.

CONCLUSIONS

This analysis allows for a better understanding of the spatial associations between the number of hospital admissions and key independent variables, as well as how changes to these independent variables may affect the number of admissions in each local authority. These findings should be considered in the context of the limitations of HES dataset.