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Type 1 diabetes in North East England and North Cumbria: patterns and time trends in 0-14-year-olds from 2012 to 2020
Louise Hayes1, Tim Cheetham1, Colin Muirhead1
1Population Health Sciences and Translational and Clinical Research Institutes, Newcastle University, Newcastle upon Tyne, United Kingdom.
Insights
The incidence of type 1 diabetes in children aged 0-14 years in North East England and North Cumbria appears to be decreasing. Further research is needed to understand the underlying causes of this trend.
Area of Science:
- Pediatric Endocrinology
- Epidemiology
- Public Health
Background:
- Understanding type 1 diabetes epidemiology offers insights into its etiology.
- The North East and North Cumbria Young Persons diabetes register provides a valuable dataset for studying pediatric diabetes trends.
Purpose of the Study:
- To examine the incidence of type 1 diabetes in children aged 0-14 years.
- To analyze patient demographics and clinical parameters at presentation between 2012 and 2020.
Main Methods:
- Data collected from 943 children diagnosed with type 1 diabetes (0-14 years) from 2012-2020.
- Descriptive statistics, including crude and age-specific incidence rates, were calculated.
- Joinpoint regression analyzed temporal trends, with comparisons made based on age, sex, and socioeconomic status (Index of Multiple Deprivation).
Main Results:
- Crude incidence of type 1 diabetes decreased from 25.5 to 16.6 per 100,000 children (5.1% annual decrease).
- No significant trends were observed in median age, HbA1c, BMI, or birth weight at diagnosis.
- Higher incidence rates were noted in males aged 10-14 years, but no differences were found based on sex in younger children or socioeconomic deprivation levels.
Conclusions:
- The incidence of type 1 diabetes in young people may be declining in the studied region.
- The reasons for this decline are unclear, as no associations were found with deprivation or anthropometric measurements.
- Further research is warranted to investigate potential factors such as socioeconomic background or growth pattern alterations.
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.
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