Evidence for a persistent, major excess in all cause admissions to hospital in children with type-1 diabetes: results from a large Welsh national matched community cohort study

Objectives To estimate the excess in admissions associated with type1 diabetes in childhood.

Design Matched-cohort study using anonymously linked hospital admission data.

Setting Brecon Group Register of new cases of childhood diabetes in Wales linked to hospital admissions data within the Secure Anonymised Information Linkage Databank.

Population 1577 Welsh children (aged between 0 and 15 years) from the Brecon Group Register with newly-diagnosed type-1 diabetes between 1999–2009 and 7800 population controls matched on age, sex, county, and deprivation, randomly selected from the local population.

Main outcome measures Difference in all-cause hospital admission rates, 30-days post-diagnosis until 31 May 2012, between participants and controls.

Results Children with type-1 diabetes were followed up for a total of 12 102 person years and were at 480% (incidence rate ratios, IRR 5.789, (95% CI 5.34 to 6.723), p<0.0001) increased risk of hospital admission in comparison to matched controls. The highest absolute excess of admission was in the age group of 0–5 years, with a 15.4% (IRR 0.846, (95% CI 0.744 to 0.965), p=0.0061) reduction in hospital admissions for every 5-year increase in age at diagnosis. A trend of increasing admission rates in lower socioeconomic status groups was also observed, but there was no evidence of a differential rate of admissions between men and women when adjusted for background risk. Those receiving outpatient care at large centres had a 16.1% (IRR 0.839, (95% CI 0.709 to 0.990), p=0.0189) reduction in hospital admissions compared with those treated at small centres.

Conclusions There is a large excess of hospital admissions in paediatric patients with type-1 diabetes. Rates are highest in the youngest children with low socioeconomic status. Factors influencing higher admission rates in smaller centres (eg, “out of hours resources”) need to be explored with the aim of targeting modifiable influences on admission rates.