Incidence Rates Of Type 1 Diabetes Research Articles

No association between incidence of type 1 diabetes and rotavirus vaccination in Swedish children.

Rotavirus infection is a potential trigger of type 1 diabetes (T1D) and rotavirus vaccination is hypothesized to decrease the incidence of T1D. In Sweden, rotavirus vaccination was introduced in 2014 in two regions and from 2019, nationwide. This study aims to investigate the association between rotavirus vaccination and incidence of T1D in Swedish children and whether rotavirus vaccination is associated with a change in clinical manifestation at diabetes onset. A nationwide register-based study with all Swedish children <15 years of age, diagnosed with T1D 2009-2019 was conducted. 7893 children were retrieved. Nationwide vaccine coverage was collected from Child Health Services. Three vaccine groups were created: I: Vaccination start 2014; II: Gradual vaccination start 2016-2018; III: No vaccination. Incidence rates of T1D before (2009-2014) and after (2014-2019) introduction of rotavirus vaccine were compared. The mean incidence of T1D in children <15 years was 42·61 per 100 000 during the observed period. When comparing the years before and after 2014 the incidence rate ratio (IRR) for children <5 years was 0·86 in group I (p=0·10), 0·85 (p=0·05) in group II and 0·87 (p=0·06) in group III. A similar IRR reduction was also seen among older children who received no vaccine. Children developing or not developing T1D were vaccinated to the same extent. No differences regarding clinical manifestation at onset associated with rotavirus vaccination were seen. There is no association between rotavirus vaccination in children and incidence or clinical manifestation of T1D.

Variation in the incidence of type 1 diabetes mellitus in children and adolescents by world region and country income group: A scoping review.

Around 18.7 million of the 537 million people with diabetes worldwide live in low-income and middle-income countries (LMIC), where there is also an increase in the number of children, adolescents, and young adults diagnosed with type 1 diabetes (T1D). There are substantial gaps in data in the current understanding of the epidemiological patterns and trends in incidence rates of T1D at the global level. We performed a scoping review of published studies that established the incidence of T1D in children, adolescents, and young adults aged 0-25 years at national and sub-national levels using PubMed, Embase and Global Health. Data was analyzed using R programming. The scoping review identified 237 studies which included T1D incidence estimates from 92 countries, revealing substantial variability in the annual incidence of T1D by age, geographic region, and country-income classification. Highest rates were reported in the 5-9 and 10-14 year age groups than in the 0-4 and 15-19 year age groups, respectively. In the 0-14 year age group, the highest incidence was reported in Northern Europe (23.96 per 100,000), Australia/New Zealand (22.8 per 100,000), and Northern America (18.02 per 100,000), while the lowest was observed in Melanesia, Western Africa, and South America (all < 1 per 100,000). For the 0-19 year age group, the highest incidence was reported in Northern Europe (39.0 per 100,000), Northern America (20.07 per 100,000), and Northern Africa (10.1 per 100,000), while the lowest was observed in Eastern and Western Africa (< 2 per 100,000). Higher incidence rates were observed in high-income countries compared to LMICs. There was a paucity of published studies focusing on determining the incidence of T1D in LMICs. The review reveals substantial variability in incidence rates of T1D by geographic region, country income group, and age. There is a dearth of information on T1D in LMICs, particularly in sub-Saharan Africa, where incidence remains largely unknown. Investment in population-based registries and longitudinal cohort studies could help improve the current understanding of the epidemiological trends and help inform health policy, resource allocation, and targeted interventions to enhance access to effective, efficient, equitable, and responsive healthcare services.

Type 1 Diabetes incidence among youth in Utah: A geographical analysis

Type 1 Diabetes (T1D) poses an increasing threat to public health, as incidence rates continue to rise globally. However, the etiology of T1D is still poorly understood, especially from the perspective of geography. The objective of this research is to examine the incidence of T1D among youth and to identify high-risk clusters and their association with socio-demographic and geographic variables. The study area was the entire state of Utah and included youth with T1D from birth to 19 years of age from 1998 to 2015 (n = 4161). Spatial clustering was measured both globally and locally using the Moran's I statistic and spatial scan statistic. Ordinary least squares (OLS) regression was used to measure the association of high-risk clusters with certain risk factors at the Census Block Group (CBG) level. The mean age at diagnosis was 9.3 years old. The mean incidence rate was 25.67 per 100,000 person-years (95% CI, 24.57–26.75). The incidence rate increased by 14%, from 23.94 per100,000 person-years in 1998 to 27.98 per 100,000 person-years in 2015, with an annual increase of 0.80%. The results of the spatial scan statistic found 42 high-risk clusters throughout the state. OLS regression analysis found a significant association with median household income, population density, and latitude. This study provides evidence that incidence rates of T1D are increasing annually in the state of Utah and that significant geographic high-risk clusters are associated with socio-demographic and geographic factors.

Incidence and predictors of type 1 diabetes among younger adults aged 20–45 years: The diabetes in young adults (DiYA) study

AimsTo estimate incidence of type 1 diabetes (T1D) and to develop a T1D prediction model among young adults. MethodsAdults 20–45 years newly-diagnosed with diabetes in 2017 were identified within Kaiser Permanente’s healthcare systems in California and invited for diabetes autoantibody (DAA) testing. Multiple imputation was conducted to assign missing DAA status. The primary outcome for incidence rates (IR) and the prediction model was T1D defined by ≥1 positive DAA. ResultsAmong 2,347,989 persons at risk, 7862 developed diabetes, 2063 had DAA measured, and 166 (8.0%) had ≥1 positive DAA. T1D IR (95% CI) per 100,000 person-years was 15.2 (10.2–20.1) for ages 20–29 and 38.2 (28.6–47.8) for ages 30–44 years. The age-standardized IRs were 32.5 (22.2–42.8) for men and 27.2 (21.0–34.5) for women. The age/sex-standardized IRs were 30.1 (23.5–36.8) overall; 41.4 (25.3–57.5) for Hispanics, 37.0 (11.6–62.4) for Blacks, 21.4 (14.3–28.6) for non-Hispanic Whites, and 19.4 (8.5–30.2) for Asians. Predictors of T1D among cases included female sex, younger age, lower BMI, insulin use and having T1D based on diagnostic codes. ConclusionsT1D may account for up to 8% of incident diabetes cases among young adults. Follow-up is needed to establish the clinical course of patients with one DAA at diagnosis.

Incidence of type 1 diabetes by socio-demographic characteristics among South Australian children: Whole-of-population study.

To describe and compare the incidence of type 1 diabetes (T1D) in South Australia by individual and area-level socio-economic characteristics among children aged ≤11 years. This is a whole-of-population, data linkage study (n = 231 685) conducted in South Australia, and included children born from 2002 to 2013, hospitalisation followed from 2002 to 2014. The study used de-identified, linked administrative hospitalisation, birth and perinatal data from the South Australian Early Childhood Data Project. Incidence was calculated by identifying T1D cases from T1D-related hospitalisations using International Classification of Disease, 10th Revision, Australian Modification diagnosis codes (E10, E101-E109). Overall, 333 children aged ≤11 years (173 boys) were identified as having T1D. The T1D incidence rate was 23.0 per 100 000 person-years (95% confidence interval (CI): 20.7-25.7), with no sex difference. T1D incidence was higher among children whose mothers were Caucasian, private patients and whose parents were employed. For example, T1D incidence was 26.0 per 100 000 (95% CI: 22.8-29.5) among children with both parents employed, compared to 20.0 per 100 000 (95% CI: 12.3-30.6) among children with both parents unemployed. There was no clear gradient in the association between area-level socio-economic position and T1D, with highest incidence for the fourth quintile (26.5 per 100 000 (95% CI: 20.9-33.1)). The most advantaged area (19.4 per 100 000 (95% CI: 13.8-26.5)) had lower incidence than the most disadvantaged area (23.5 per 100 000 (95% CI: 18.9-28.9)). T1D incidence rates differed depending on the measures of socio-economic characteristics. Individual-level indicators showed higher incidence among more advantaged children; however, there was no clear area-level socio-economic patterning of T1D.

The Incidence and Demographic Distribution of Type 1 Diabetes Mellitus in Children Aged 16 or Younger Between 2000 and 2016 in Cyprus

Objective:Type 1 diabetes (T1D) is a disease characterized by severe insulin deficiency. In 2008 our group studied the prevalence of diabetes in adults between 20-80 years of age in Cyprus but data regarding this incidence in the pediatric population is lacking. The objective of this study was to report the incidence of T1D among permanent inhabitants aged 16 years or younger between 2001-2016 in Cyprus.Methods:This study was a retrospective analysis. The patients were mainly evaluated and recorded at Dr. Burhan Nalbantoğlu Hospital, Nicosia. Data was also reviewed from Famagusta Government Hospital, Kyrenia Government Hospital, Near East University Hospital and the Cyprus Turkish Diabetes Association.Results:A total of 107 subjects were diagnosed as T1D between 2001 and 2016 in the pediatric age group. Forty-nine (45.7%) were girls and 58 (54.3%) were boys. Of these 38.7% were resident in Nicosia, 30.2% Famagusta, 12.3% Kyrenia, 9.4% Guzelyurt and 7.5% Iskele. The proportion of newly diagnosed T1D was highest among children aged 9-12 years (35.5%) followed by children aged 5-8 years (32.7%). Newly diagnosed T1D most frequently presented in March and April. The overall mean incidence rate was 11.1/100,000 between 2001 and 2016. The incidence rates were similar and comparable among the years.Conclusion:This study is the first to analyze the incidence of T1D in Cyprus. Compared to other countries the incidence rate is intermediate. Our findings are similar to the incidence rates of T1D in South Cyprus and Turkey.

The Role of Gut Microbiota and Environmental Factors in Type 1 Diabetes Pathogenesis.

Type 1 Diabetes (T1D) is regarded as an autoimmune disease characterized by insulin deficiency resulting from destruction of pancreatic β-cells. The incidence rates of T1D have increased worldwide. Over the past decades, progress has been made in understanding the complexity of the immune response and its role in T1D pathogenesis, however, the trigger of T1D autoimmunity remains unclear. The increasing incidence rates, immigrant studies, and twin studies suggest that environmental factors play an important role and the trigger cannot simply be explained by genetic predisposition. Several research initiatives have identified environmental factors that potentially contribute to the onset of T1D autoimmunity and the progression of disease in children/young adults. More recently, the interplay between gut microbiota and the immune system has been implicated as an important factor in T1D pathogenesis. Although results often vary between studies, broad compositional and diversity patterns have emerged from both longitudinal and cross-sectional human studies. T1D patients have a less diverse gut microbiota, an increased prevalence of Bacteriodetes taxa and an aberrant metabolomic profile compared to healthy controls. In this comprehensive review, we present the data obtained from both animal and human studies focusing on the large longitudinal human studies. These studies are particularly valuable in elucidating the environmental factors that lead to aberrant gut microbiota composition and potentially contribute to T1D. We also discuss how environmental factors, such as birth mode, diet, and antibiotic use modulate gut microbiota and how this potentially contributes to T1D. In the final section, we focus on existing recent literature on microbiota-produced metabolites, proteins, and gut virome function as potential protectants or triggers of T1D onset. Overall, current results indicate that higher levels of diversity along with the presence of beneficial microbes and the resulting microbial-produced metabolites can act as protectors against T1D onset. However, the specifics of the interplay between host and microbes are yet to be discovered.

A stochastic epigenetic Mendelian oligogenic disease model for type 1 diabetes

The incidence of type 1 diabetes (T1D) and some other complex diseases is increasing. The cause has been attributed to an undefined changing environment. We examine the role of the environment (or any changing non-genetic mechanism) in causing the rising incidence, and find much evidence against it: 1) Dizygotic twin T1D concordance is the same as siblings of patients in general; 2) If the environment is responsible for both the discordance among identical twins of patients with T1D and its rising incidence, the twin concordance rate should be rising, but it is not; 3) Migrants from high-to low-incidence countries continue to have high-incidence children; 4) TID incidence among the offspring of two T1D parents is identical to the monozygotic twin rate. On the other hand, genetic association studies of T1D have revealed strong susceptibility in the major histocompatibility complex and many optional additive genes of small effect throughout the human genome increasing T1D risk. We have, from an analysis of previously published family studies, developed a stochastic epigenetic Mendelian oligogenic (SEMO) model consistent with published observations. The model posits a few required recessive causal genes with incomplete penetrance explaining virtually all of the puzzling features of T1D, including its rising incidence and the specific low T1D incidence rates among first-degree relatives of patients. Since historic selection against any causal gene could prevent T1D, we postulate that the rising incidence is because of increasing population mixing of parents from some previously isolated populations that had selected against different causal genes.

Incidence of type 1 diabetes in Navarre (2009-2016): higher in the southern regions of the autonomous community

Geographical and seasonal variations of type 1 diabetes (T1D) are useful for establishing the key ethio-pathogenic factors of the disease. The present work seeks to analyze the incidence rates of T1D in Navarre for the 2009-2016 period, its geographical distribution and seasonal variations in birth and diagnosis in affected persons. Prospective study with one primary and three secondary sources. The completeness of the registry, determined using the capture-recapture method, was 96.08%. The confidence intervals of zone and onset season incidence rates were determined assuming an underlying Poisson distribution. Adjusted effect of onset age, sex, onset season and geographical area over changes in incidence rates were analyzed using a Poisson regression model. Comparison among areas was carried out after the corresponding adjustments of incidence by the indirect standardization method. Four hundred and twenty-eight new cases were detected (incidence= 8.36/100,000 inhabitants per year, CI95%: 7.58-9.19). The disease is predominant in males (63% of patients). The incidence in children under 15 years was higher than in adults (21.54, CI95%: 18.43-25.02 vs. 5.94, CI95%: 5.23-6.71; p<0.001). Incidence was highest in the four southern regions of Navarre, most of the cases being in winter and spring. No differences were found regarding birth season over incidence. Navarre maintains a high T1D incidence in childhood that decreases progressively with age. Sex, age group, geographical zone and onset season are independently associated with the incidence rates observed in the study.

Characterizing subgroups of type 1 diabetes.

The prevailing model of type 1 diabetes (T1D) evolution is based on a now classic 1986 article by the late George Eisenbarth (1). A recent review noted that although the model still holds to a large extent, there are subtleties that suggest it is not as simple as originally proposed (2). The 1997 American Diabetes Association Expert Committee divided T1D into type 1A (immune mediated) and type 1B (idiopathic) (3), although this classification is not commonly used. Earlier, in 1977, Irvine (4) divided the disease into three subtypes: severe autoimmune/nonviral, moderate autoimmune/moderate viral, and severe viral/nonautoimmune. The severe viral subgroup appears to be rare and may have an explosive onset with a fatal outcome (5,6). The Japan Diabetes Society divides T1D into three categories depending on the manner of onset and progression—namely fulminant, acute-onset, or slowly progressive type 1 diabetes (SPID) (7). It is likely that the severe viral subgroup noted by Irvine and the Japanese fulminant subgroup are the same. It is clear that the rate of decline of β-cell function differs by age (8). It also has been noted that incidence rates of T1D have been increasing, particularly in children under the age of 5 years (9,10). Thus, the progressive linear decline originally outlined by Eisenbarth (1) cannot be simply applied. If nothing else, the T1D disease process evolves at different rates. The number of …

Prediction model for the incidence and prevalence of type 1 diabetes in childhood and adolescence: evidence for a cohort-dependent increase within the next two decades in Germany

To provide data on type 1 diabetes (T1D) epidemiology in childhood over a period of 20 years and to predict prevalence and cohort-age-specific incidence rates (IRs) for the next two decades in Germany. The Baden-Wuerttemberg Diabetes Incidence Registry (DIARY) includes children and adolescents below 15 years of age with new onset of T1D (period 1987-2006, n = 5108 cases). The mean age- and sex-standardized IR was 15.3/100 000/year (95% CI 14.8-15.7) and the average increase in the IR was 4.4% per year (95% CI 3.9-4.9). Within the next 20 years (2007-2026), the risk for developing diabetes will increase like the square of a linear function with calendar year for all age ranges. There is a strong correlation between the predicted IRs of the cohorts and the observed IRs (n = 300; root mean square error = 0.56; r(2) = 0.71) and a negative correlation between mean age at onset and T1D IR (p = 0.02). On 31 December 2006, the prevalence of T1D was 0.126% (95% CI 0.121-0.132). The predicted prevalence (end of 2026) is estimated to be 0.265% (95% CI 0.25-0.28; predicted cases: n = 2950; 95% CI 2900-3000). In comparison to observations made in the past, the risk of disease rises even faster than expected: The younger the child, the quicker the increase of the cohort-age-specific IR and the higher the risk for T1D during lifetime.