Type 1 diabetes affects approximately ******* children worldwide, with ******* new cases diagnosed annually. This chronic condition, requiring lifelong insulin treatment, impacts a significant portion of the global child population of **** billion. Global diabetes trends and projections The impact of diabetes extends far beyond childhood, with the total number of diabetics worldwide expected to reach *** million by 2050. This projected increase corresponds to a rise in global diabetes prevalence from ** percent in 2024 to ** percent by 2050. The Western Pacific region currently has the highest number of diabetics, with approximately *** million people aged 20-79 affected. Africa, has the lowest number of diabetics with **** million in 2024. However, the number of diabetics in Africa is expected to increase significantly in the coming decades. Regional disparities and health concerns The global distribution of diabetes cases varies significantly, with Africa expected to see a *** percent increase in diabetes cases from 2024 to 2050, compared to a ** percent rise in North America and the Caribbean. As diabetes remains a critical health issue worldwide, it contributes to various complications and was the eighth leading cause of death globally in 2021, resulting in approximately **** million deaths that year.

In 2021, Germany had the highest number of children and adolescents living with type 1 diabetes in Europe, with approximately **** thousand having this condition. The United Kingdom had the second highest amount, with roughly **** thousand young people diagnosed with type 1 diabetes. This statistic displays the number of children and adolescents with type 1 diabetes in Europe in 2021, by country.

Find data on pediatric diabetes in Massachusetts. This dataset contains information on the number of cases and prevalence of Type 1 and Type 2 diabetes among students, grades K-8, in Massachusetts.

The number of children with type 1 diabetes in Denmark in 2018 was increasing by age. Among adolescents from 15 to 19 years, *** per hundred thousand inhabitants were diagnosed with type 1 diabetes.

Type 1 diabetes and neurodevelopmental disorders are common chronic conditions in childhood and adolescence, and having one may lead to an increased chance of developing the other. Type 1 diabetes mellitus is mainly manifested by elevated blood glucose, while neurodevelopmental diseases are composed of a variety of diseases, which are relatively complex. The purpose of this meta-analysis was to find out the prevalence of type 1 diabetes-related neurodevelopmental disorders in children and adolescents and to explore the potential association between neurodevelopmental disorders and type 1 diabetes. PubMed, Embase and Web of science databases were searched from the inception to May 22, 2022 to identify relevant studies, Finally, 24 original studies were included in the meta-analysis. Prevalence estimates for neurodevelopmental disorders in the type 1 diabetes adolescent and their 95% confidence intervals were pooled using random effects models. The pooled estimates for autism spectrum disorders (ASD) and attention deficit hyperactivity disorder (ADHD) in the type 1 diabetes population were 1.2 and 5.3%, respectively, both of which are higher than the 2019 global prevalence of ASD and ADHD in the general population. The results of the subgroup analysis showed that the prevalence of ASD and ADHD in the T1DM population tended to increase with age. In conclusion, there may be a potential link between the occurrence of type 1 diabetes mellitus and the development of neurodevelopmental disorders in children and adolescents, but more relevant studies are needed to understand the link between the underlying pathogenesis of type 1 diabetes and neurodevelopmental disorders.Systematic review registration[https://www.crd.york.ac.uk/PROSPERO/], identifier [CDR42022333443].

2013 Medicaid figures for southeast Michigan counties of Wayne, Oakland, and Macomb at the ZCTA level. This data represent number of visits, they are not counts of different individuals, only of visits. One person could have had multiple visits and each visit would be counted. Blank cells indicate no visits. Whether a visit is coded as a hospital or ER visit depends on the DRG, Diagnosis-Related Group; that is, the diagnosis.

As of 2021, there were approximately *** thousand children under the age of ** with type * diabetes in the Middle East and North Africa (MENA) region. There were about *** thousand children and adolescents under the age of ** in the region with type * diabetes.

ObjectivesThe objective of this study was to evaluate the characteristics of children presenting with new onset diabetes and diabetic ketoacidosis (DKA) in the first COVID pandemic year, compared to pre-pandemic evidence and identify the factors associated with DKA at diagnosis.DesignRetrospective medical record review.SettingForty-nine pediatric Emergency Departments (EDs) across the UK and Ireland.PatientsAll children aged 6 months to 16 years presenting to EDs with new onset diabetes and DKA, during the COVID-19 pandemic (1 March 2020–28 February 2021) and the preceding year (1 March 2019–28 February 2020).ResultsThere were increases in children presenting with new onset diabetes in DKA (395–566, 43%) and severe DKA (141–252, 79%) in the first COVID pandemic year, with patient characteristics similar to the pre-pandemic period. Healthcare seeking delay did not appear to be the sole contributing factor to DKA during the COVID pandemic. The median duration of symptoms of 14 days for both children who presented with and without DKA and were similar across both years; those in severe DKA had shorter median duration of 7 days (IQR: 5–21 days).ConclusionsThere were significant increases in children with new onset diabetes presenting with DKA in the first COVID pandemic year. Increased DKA rates and severity despite a constant median symptom duration suggest a multifactorial process. Studies to determine checkpoints for intervention between symptom onset and diagnosis of diabetes are vital to mitigate the high incidence of DKA in new onset diabetes.

Objectives: The prevalence of type 1 diabetes mellitus (T1D) in children is growing, but its relation to other autoimmune disorders that coexist since the onset of diabetes is not recognized. The objective of this study was to assess the incidence of T1D and the prevalence of autoimmune illnesses additionally coexisting since the diabetes mellitus onset in children during a period of 9 years' observation.Methods: In this retrospective study, the incidence rate (IR) of the T1D was calculated as the total number of all cases that were newly diagnosed per 100,000 population people between 0 and 18 years of age. The selected age groups (0–4, 5–9, 10–14, and 15–18 years) were examined, respectively. The studied group included 493 children (264 [53.55%] boys) between 0 and 18 years old newly diagnosed with T1D in one of the Polish centers in the years 2010–2018. Other autoimmune illnesses diagnoses were obtained from medical records taken from the first hospital treatment, when T1D was recognized.Results: The annual standardized IR of T1D increased from 19.2/100,000 in year 2010 to 31.7/100,000 in 2018 (1.7-fold over 9 years' observation), with an increase in the incidence rate ratio (IRR) by 4% per year. The highest growth in IR was recorded in 5- to 9-year-olds (from 19.61 in 2010 to 43.45 in 2018). In 61 (12.4%) of the studied group, at least one additional autoimmune disease was diagnosed. The prevalence doubled from 10.4% in the year 2010 to 20.8% in the year 2018. Autoimmune thyroid illnesses were found in 37 children (7.5%); their incidence increased from 6.3% to almost 2-fold, 12.5%, in 2018. In 26 children (5.3%), celiac disease was recognized; the prevalence increased from 4.2 to 9.8% in the study period. The prevalence of additional autoimmune thyroid disease was higher in glutamic acid decarboxylase–positive antibodies (χ2 = 3.4, p = 0.04) patients, the oldest age group (15–18 years) (χ2 =7.1, p = 0.06), and in girls (χ2 =7.1, p = 0.007).Conclusions:The standardized IR of T1D in children increased 1.7-fold over the 9-year observation period, and IRR increased 4% per year. Additional autoimmunity represents a significant comorbidity in patients with new-onset T1D. The number of children diagnosed with additional autoimmune diseases that accompany T1D is rapidly growing in all age groups throughout recent years.

ObjectiveWe analyzed the annual prevalence of onset-DKA (diabetic ketoacidosis) from 2012 to 2020 with a sub-analysis for lockdown-periods during the COVID-19 pandemic in 2020.DesignAll newly diagnosed children with type 1 diabetes (T1D) aged

The “hygiene hypothesis” postulates that reduced exposure to infections favours the development of autoimmunity and childhood type 1 diabetes (T1D). But on the other side, viruses, notably enteroviruses, are suspected to trigger T1D. The assessment of the possible relationships between infections and T1D still defies the classical tools of epidemiology. We report the methods and results of a geographical approach that maps the addresses of patients to a communicable diseases surveillance database. We mapped the addresses of patients at birth, infancy and T1D diagnosis to the weekly estimates of the regional incidences of 5 frequent communicable diseases routinely collected since 1984 by the French Sentinel network. The pre-diagnostic infectious environment of 3548 patients with T1D diagnosed between 0.5 and 15 years was compared to those of 100 series of age-matched “virtual controls” drawn randomly on the map. Associations were classified as “suggestive” (summer diarrhea, SD, and varicella, V) when p< 0.05, or “significant” (influenza-like infections, ILI) when they passed the Bonferroni correction for FDR. Exposure to ILI and SD were associated with T1D risk, while V seemed protective. In the subset of 2521 patients for which we had genome wide data, we used a case-only approach to search for interactions between SNPs and the infectious environment as defined by the Sentinel database. Two SNPs, rs116624278 and rs77232854, showed significant interaction with exposure to V between 1 and 3 years of life. The infectious associations found should be taken as possible markers of patients’ environment, not as direct causative factors of T1D. They require replication in other populations. The increasing public availability of geographical environmental databases will expand the present approach to map thousands of environmental factors to the lifeline of patients affected by various diseases.

This statistic shows the top 10 countries based on number of new cases of type 1 diabetes per 100,000 children aged 0 to 14 years, in 2021. Finland had the highest rate with 52.2 new cases per 100,000 children per year.

This dataset presents the crude rate of emergency hospital admissions for insulin-dependent diabetes mellitus (Type 1 diabetes) among children and young people aged under 19. It provides insight into the burden of acute diabetic complications requiring urgent care and supports the evaluation of diabetes management in paediatric populations.

Rationale Reducing emergency admissions for diabetes in children is a key public health objective. High admission rates may indicate challenges in managing the condition, such as poor glycaemic control, lack of access to specialist care, or gaps in education and support for families. Monitoring this indicator helps inform strategies to improve diabetes care and reduce preventable hospitalisations.

Numerator The numerator is the number of emergency hospital admissions for individuals aged under 19 with a primary diagnosis of insulin-dependent diabetes mellitus, identified using ICD-10 code E10. Data are sourced from NHS England’s Secondary Uses Service (SUS).

Denominator The denominator is the total resident population aged under 19, based on the 2021 Census.

Caveats No specific caveats were noted for this dataset. However, as with all hospital admission indicators, local variations in clinical coding, referral practices, and healthcare access may influence the results.

External References Fingertips Public Health Profiles – Diabetes Admissions (Under 19)

Click here to explore more from the Birmingham and Solihull Integrated Care Partnerships Outcome Framework.

Aims/hypothesis: 40-year-long longitudinal observation of long-term trends of type 1 diabetes incidence and prevalence in children in Central Poland

Methods: This was a prospective observational study performed by a reference regional center for pediatric diabetes care for Lodz Province (currently 2·4M inhabitants, 360K children). We registered each case of new-onset type 1 diabetes admitted to regional pediatric diabetes centers between the years 1983 and 2022 in children between 0 and 14 y.o. The diagnosis was based on currently available guidelines. Cases of other types of diabetes (e.g., monogenic) were excluded upon identification from incidence and prevalence rates. Yearly data on the at-risk population were acquired from Poland`s General Statistical Office. Sex-specific data on population structure were available from 1989 onwards.

Results: In the analyzed period, the incidence rate of type 1 diabetes increased tenfold from 3·29/100,000 (95%CI: 1·85-4·73) in 1983 to 32.43 (26·42-38·44) in 2022, with an average annual percentage change of 5·73% (95%CI: 4·99%-6·44%). Joinpoint analysis detected two distinct periods of increase: rapid in 1983-2005 (annual percentage increase of 7·38%, 95%CI: 6·30-10·52%) and a slower one in 2005-2022 (3·65%, 95%CI: -0·86-5·13%). Incidence rates among the youngest children (0-4 y.o.) were significantly lower than in 5-9 y.o. (β±SE: -0·567±0·059, p<0·0001) and 10-14 y.o. (β±SE: -0·520±0·060, p<0·0001). The incidence growth dynamic for the two older groups showed a consistent increase, whereas the incidence in 0-4 year-olds plateaued after 2007. Incidence rates varied seasonally, with the most cases diagnosed during the winter months (December, January, and February; mean difference from remaining seasons of 29±11·6 percentage points, p<0·0001). Corresponding with increasing incidence rate, estimated prevalence of type 1 diabetes increased over the years and reached 177·21/100,000 (95%CI: 163·18-191·24) for children 0-14 y.o., and 17·11 (95%CI: 9·2-25·02), 190·54 (95%CI: 165·03-215·75), 238·73 (95%CI: 211·7-265·76) for 0-4, 5-9, and 10-14 y.o., respectively.

Conclusion/interpretation: Over the past 40 years, the incidence of type 1 diabetes in children in Central Poland has increased significantly, but the rate of increase appears to be slowing. As majority of patients with type 1 diabetes are 10 years old or older, with the most new cases occurring in that age group the healthcare systems should prepare for care of young adults who are extensive users of new diabetes technologies.

Descriptive statistics for age at onset of T1D.

Maternally Inherited Diabetes and Deafness (MIDD) is a rare form of diabetes due to defects in mitochondrial DNA (mtDNA). 3243 A>G is the mutation most frequently associated with this condition, but other mtDNA variants have been linked with a diabetic phenotype suggestive of MIDD. From 1989 to 2009, we clinically diagnosed mitochondrial diabetes in 11 diabetic children. Diagnosis was based on the presence of one or more of the following criteria: 1) maculopathy; 2) hearing impairment; 3) maternal heritability of diabetes/impaired fasting glucose and/or hearing impairment and/or maculopathy in three consecutive generations (or in two generations if 2 or 3 members of a family were affected). We sequenced the mtDNA in the 11 probands, in their mothers and in 80 controls. We identified 33 diabetes-suspected mutations, 1/33 was 3243A>G. Most patients (91%) and their mothers had mutations in complex I and/or IV of the respiratory chain. We measured the activity of these two enzymes and found that they were less active in mutated patients and their mothers than in the healthy control pool. The prevalence of hearing loss (36% vs 75–98%) and macular dystrophy (54% vs 86%) was lower in our mitochondrial diabetic adolescents than reported in adults. Moreover, we found a hitherto unknown association between mitochondrial diabetes and celiac disease. In conclusion, mitochondrial diabetes should be considered a complex syndrome with several phenotypic variants. Moreover, deafness is not an essential component of the disease in children. The whole mtDNA should be screened because the 3243A>G variant is not as frequent in children as in adults. In fact, 91% of our patients were mutated in the complex I and/or IV genes. The enzymatic assay may be a useful tool with which to confirm the pathogenic significance of detected variants.

Aim/HypothesisTo compare the frequency of diabetic ketoacidosis (DKA) at diagnosis of type 1 diabetes in Italy during the COVID-19 pandemic in 2020 with the frequency of DKA during 2017-2019.MethodsForty-seven pediatric diabetes centers caring for >90% of young people with diabetes in Italy recruited 4,237 newly diagnosed children with type 1 diabetes between 2017 and 2020 in a longitudinal study. Four subperiods in 2020 were defined based on government-imposed containment measures for COVID-19, and the frequencies of DKA and severe DKA compared with the same periods in 2017-2019.ResultsOverall, the frequency of DKA increased from 35.7% (95%CI, 33.5-36.9) in 2017-2019 to 39.6% (95%CI, 36.7-42.4) in 2020 (p=0.008), while the frequency of severe DKA increased from 10.4% in 2017-2019 (95%CI, 9.4-11.5) to 14.2% in 2020 (95%CI, 12.3-16.4, p<0.001). DKA and severe DKA increased during the early pandemic period by 10.4% (p=0.004) and 8% (p=0.002), respectively, and the increase continued throughout 2020. Immigrant background increased and high household income decreased the probability of presenting with DKA (OR: 1.55; 95%CI, 1.24-1.94; p<0.001 and OR: 0.60; 95 CI, 0.41-0.88; p=0.010, respectively).Conclusions/InterpretationThere was an increase in the frequency of DKA and severe DKA in children newly diagnosed with type 1 diabetes during the COVID-19 pandemic in 2020, with no apparent association with the severity of COVID-19 infection severity or containment measures. There has been a silent outbreak of DKA in children during the pandemic, and preventive action is required to prevent this phenomenon in the event of further generalized lockdowns or future outbreaks.

The main purpose of creating an electronic database was to assess indicators of glycemic variability in adolescents and children diagnosed with diabetes mellitus type 1. The database presents the results of prospective, open, controlled, clinical study obtained over a period of one and a half years. Base data includes information on 307 patients (children and adolescents) aged 3 to 17 years inclusive. The observed patients were divided into two groups: Group 1 - patients diagnosed with type 1 diabetes mellitus and with diabetic complications, 152 people, Group 2 – patients diagnosed with type 1 diabetes mellitus and without diabetic complications, 155 people. All database registrants were assigned individual codes, which made it possible to exclude personal data (full name) from the database.

During the study, an analysis of carbohydrate metabolism was carried out with an assessment HbA1c (glycated hemoglobin), CGMS (continuous glucose monitoring), FMG (flash glucose monitoring) with face-to-face consultations with an endocrinologist and analysis of the data obtained. Obtained monitoring results were processed using a specialized variability calculator glycemia (EasyGV®, ver. 9), the following indicators and indices were calculated variability: average glycemic level (Mean), standard deviation (SD); index prolonged increase in glycemia (CONGA); glycemic lability index (LI); index risk of hypoglycemia (LBGI); hyperglycemia risk index (HBGI), average value overall risk (ADRR), average amplitude of glycemic fluctuations (MAGE); grade inter-day GV (MODD), rate of change in glycemia (MAG), J-index - indicator quality of glycemic control. The database is intended for entering, organizing, storing and displaying all of the above data.

A register of children diagnosed with type 1 diabetes, collected from Paediatric diabetes clinics in Wales. Maintained by the Brecon Group. Data has been collected since 1995 and is complete since then, but some people diagnosed earlier are also included.