Abstract
INTRODUCTION: It is important to understand patterns in the epidemiology of type 1 diabetes because they may provide insight into its etiology. We examined the incidence of type 1 diabetes in children aged 0-14 years, and patient demographics and clinical parameters at presentation, over the period 2012-2020 using the North East and North Cumbria Young Persons diabetes register. METHODS: Patients up to the age of 14 years with type 1 diabetes, and their families- managed in a total of 18 young persons diabetes clinics-were approached in person at the time of clinic appointments or in the days following diagnosis and they consented to their data being included in the register. Data were submitted regionally to a central unit. Descriptive statistics including crude and age-specific incidence rates were calculated. Temporal trends were analyzed using Joinpoint regression. Comparisons in incidence rates were made between age, sex and areas of higher and lower affluence as measured by the Index of Multiple Deprivation (IMD). RESULTS: A total of 943 cases were recorded between January 2012 and December 2020. Median age at diagnosis was 8.8 years (Q1: 5.3, Q3: 11.7). There were more males than females (54% male). The median HbA1c at diagnosis was 100 mmoL/L (IQR: 39) and over one third (35%) were in ketoacidosis (pH < 7.3). Crude incidence decreased from 25.5 (95% confidence interval [CI] 20.9, 29.9) in 2012 to 16.6 (95% CI: 13.0, 20.2) per 100,000 in 2020 (5.1% per annum, 95% CI 1.1, 8.8%). During the period of the study there was no evidence of any trends in median age, HbA1c, BMI or birthweight (p = 0.18, 0.80, 0.69, 0.32) at diagnosis. Higher rates were observed in males aged 10-14 years, but similar rates were found for both sexes aged 0-9 years and there was no difference between areas of higher or lower deprivation (p = 0.22). CONCLUSION: The incidence of diabetes in the young may be falling in the North East of England and North Cumbria. The reasons are unclear as there were no associations identified between levels of deprivation or anthropometric measurements. Potential mechanisms include alterations in socioeconomic background or growth pattern. Further research is needed to understand the reasons behind this finding.