Type 1 diabetes diagnosed before age 15 years in Canterbury, New Zealand: A 50 year record of increasing incidence

Increased incidence of pediatric type 1 diabetes during the pandemic in Biscay, Spain

OBJECTIVE

To update the incidence rate (IR) and trends of type 1 diabetes mellitus (T1DM) in children aged 0-14 years from 2003 to 2022, in Biscay, Spain.

SUBJECTS AND METHOD

We used the capture-recapture method: primary cases were prospectively extracted from the hospital registry and a secondary independent data source was obtained from diabetes associations and a public health database. The IRs standardized by age and sex were calculated using the direct method, assuming an equal distribution in each age/sex group. The IR occurring during the various COVID-19 waves was compared with the pre-pandemic IR.

RESULTS

A total of 378 new cases were identified. The mean age at diagnosis was 9.7 years (5.8-11.9). The completeness of ascertainment was 99.1%. The mean annual age-standardized IR was 12.92 (95%CI, 11.35-13.91). The mean IRs for the 0-4, 5-9, and 10-14 age groups were 7.67, 13.41 and 17.83 cases/100,000 children/year, respectively. The IR trend was statistically significant in the entire group and in the 5-9 year-old group with a mean annual increase of 1.9% (95%CI, 0.1-3.8) and 3.3% (95%CI, 1.002-1.065); p=0.039. The 5-year period analysis confirmed that the increase was significant only in the last 5 years (20%). When 2020-2022 (pandemic) and 2017-2019 (pre-pandemic) periods were compared this difference goes up to 44.5%; p=0.029.

CONCLUSIONS

After a long period of stability in the IR of T1DM in children younger than 15 years of age in Biscay, Spain, an increase in recent years has been reported, which is consistent with the SARS-CoV2 pandemic, with the largest increase being reported in the 5-to 9-year-old age group.

Fifty years of HLA-associated type 1 diabetes risk: history, current knowledge, and future directions

More than 50 years have elapsed since the association of human leukocyte antigens (HLA) with type 1 diabetes (T1D) was first reported. Since then, methods for identification of HLA have progressed from cell based to DNA based, and the number of recognized HLA variants has grown from a few to tens of thousands. Current genotyping methodology allows for exact identification of all HLA-encoding genes in an individual's genome, with statistical analysis methods evolving to digest the enormous amount of data that can be produced at an astonishing rate. The HLA region of the genome has been repeatedly shown to be the most important genetic risk factor for T1D, and the original reported associations have been replicated, refined, and expanded. Even with the remarkable progress through 50 years and over 5,000 reports, a comprehensive understanding of all effects of HLA on T1D remains elusive. This report represents a summary of the field as it evolved and as it stands now, enumerating many past and present challenges, and suggests possible paradigm shifts for moving forward with future studies in hopes of finally understanding all the ways in which HLA influences the pathophysiology of T1D.

Epidemiology of type 1 diabetes mellitus in children and adolescents: A 50-year, single-center experience

BACKGROUND

Global variations in epidemiology of type 1 diabetes mellitus (T1DM) exist. This study is designed to examine demographic and clinical features of T1DM over the past 3 decades as well as evolving trends in epidemiology over last 50 years.

METHODS

Clinical characteristics of 925 patients with T1DM over last 30 years (1990-2019) were evaluated and compared to previously published data of 477 patients diagnosed between 1969 and 1990 from one of the major referral centers for diabetes in Turkey.

RESULTS

Mean age at diagnosis decreased from 9.5 ± 4.0 to 7.1 ± 3.6 years within the past 50 years (p < .001). Age at diagnosis peaked at 12-14 years between 1969 and 1990, then fell to 10-11.9 years between 1990 and 1999, and to 4-5.9 years between 2000-2009 and 2010-2019 (p = .005). Although the percentage of patients diagnosed <6 years of age is gradually increasing, the percentage between the ages of 6 and 11.9 years is decreasing, and the percentage diagnosed ≥12 years remained stable. A total of 47.5% of patients had ketoacidosis, 38.2% had ketosis, and 14.3% had only hyperglycemia. 23% of patients had severe diabetic ketoacidosis (DKA), whereas 42% had moderate. Over last 3 decades, there has been no change in frequency of ketoacidosis at presentation, but there has been significant decline in severity (p = .865, and p < .001, respectively). Although the frequency of patients with mild DKA increased over time, frequency of patients with moderate DKA decreased; however, no significant difference was observed among patients with severe ketoacidosis. DKA was more frequent and severe in patients <6 years of age (p = .005, and p < .001, respectively).

CONCLUSION

Age at diagnosis shifted to younger ages in T1DM in the past 50 years. Half of patients had ketoacidosis at diagnosis and frequency of presentation with DKA did not decrease, but severity decreased slightly. Increase in prevalence of T1DM in the younger age group and the fact that half of patients present with DKA indicate that awareness should be increased in terms of early diagnosis and treatment.

Comparative Analysis of Body Image Dissatisfaction, Depression, and Health-Related Quality of Life in Adults with Type 1 Diabetes: A Case-Control Study

(1) Objective: This case-control study investigated body image dissatisfaction, depression, and health-related quality of life (HRQoL) in adults with type 1 diabetes. (2) Methods: A total of 35 adults with diabetes and an equal number of age- and gender-matched controls were included. Assessment tools used were the Body Image Disturbance Questionnaire (BIDQ), the Hospital Anxiety and Depression Scale (HADS), and the RAND 36-Item Health Survey. Both quantitative and qualitative data were analyzed. (3) Results: Body image dissatisfaction did not differ significantly between the groups. However, adults with diabetes reported higher levels of depression (p = 0.002) and lower scores for physical health (p = 0.015) and general health (p < 0.001) on the HRQoL measure. Qualitative analysis identified common themes related to physical disturbance, effect on activities, and psychosocial concerns. (4) Conclusions: Despite similar body image dissatisfaction, adults with type 1 diabetes exhibited increased depression and reduced HRQoL. These findings emphasize the need to integrate psychological well-being into type 1 diabetes management. They also support further research into the impact of body image dissatisfaction in T1D and potential interventions to address it.

Prevalence and incidence of type 1 diabetes in children aged 0-14 years old in New Zealand in 2021

AIM

National prevalence and incidence data are important for understanding population trends and allocating health-care resources. We aimed to provide a current national snapshot of prevalence and annual incidence rates for children aged 0-14 with type 1 diabetes (T1D) in Aotearoa New Zealand and to identify differences associated with demographic variables.

METHODS

Paediatric diabetes centres across Aotearoa were invited to record anonymised demographic and diabetes data on children under their services between 1 October 2020 and 30 September 2021. National prevalence and incidence were calculated using usually resident population counts from the 2018 census. The effect of ethnicity on prevalence and incidence was assessed using Poisson regression.

RESULTS

There were 1209 children aged 0-14 with T1D in October 2021. The national prevalence was 131/100 000 (95% confidence interval (CI) 124-139). European children had twice the prevalence as those of Māori or Pacific ethnicity (P < 0.001). There was no effect by gender (P = 0.3) and prevalence predictably increased with age. The annualised incidence of T1D was 23/100 000 (95% CI 20-26). European children were 2.6 times as likely as Māori children to be diagnosed with T1D in that year (incidence rate ratio = 2.6, 95% CI 1.7-4.2). Regional differences in prevalence and incidence were noted, potentially due to the ethnicity differences across regions. Unadjusted prevalence and incidence decreased with lower socio-economic status, likely due to an over-representation of non-Europeans living in the most deprived areas.

CONCLUSIONS

T1D affects an ethnically diverse population in Aotearoa and important regional differences exist that may impact workforce planning.

Mental health comorbidity is common in children with type 2 diabetes

OBJECTIVE

To describe the prevalence of mental health comorbidity in children with type 2 diabetes compared to a matched population without diabetes and children with type 1 diabetes.

RESEARCH DESIGN AND METHODS

Population-based cohorts of 528 youth (7-18 years of age) with prevalent type 2 diabetes, 1519 matched children without diabetes and 778 youth with type 1 diabetes were identified from a clinical registry and linked to provincial health care records to assess the prevalence of mental health comorbidity using ICD-9CM, ICD-10CA and ATC codes.

RESULTS

The majority of children with type 2 diabetes were of First Nations heritage. Compared to their matched peers, children with type 2 diabetes where more likely to have a mood or anxiety disorder before and after diagnosis [RR 2.38 (1.63, 3.48) p < 0.001 and 1.70 (1.39, 2.08) p < 0.001 respectively], to attempt/complete suicide [RR 3.18 (1.30, 7.81) p = 0.012 and 2.18 (1.32, 3.60) p = 0.0002 respectively] and be prescribed an antipsychotic [RR 2.33 (1.23, 4.39) p = 0.009 and 1.76 (1.23, 2.52) p = 0.002 respectively]. Following adjustment for age and sex, children with type 2 diabetes, compared to children with type 1 diabetes where more likely to have a mood or anxiety disorder and be prescribed an antipsychotic after diagnosis [RR 1.43 (1.07, 1.91) p = 0.015; RR 2.41 (1.44, 4.06) p = 0.0009 respectively].

CONCLUSIONS

Children with type 2 diabetes have high rates of comorbid mental illness. Programs to provide care, support, and education must address the mental health comorbidity in the context of the demographic, socioeconomic, and psycho-cultural characteristics of the population.