Youth-onset type 2 diabetes in Israel: A national cohort

BACKGROUND

Prevalence of youth-onset type 2 diabetes (T2D) has increased worldwide, paralleling the rise in pediatric obesity. Occurrence and clinical manifestations vary regionally and demographically.

OBJECTIVES

We assessed the incidence, and clinical and demographic manifestations of youth-onset T2D in Israel.

METHODS

In a national observational study, demographic, clinical, and laboratory data were collected from the medical records of children and adolescents, aged 10-18 years, diagnosed with T2D between the years 2008 and 2019.

RESULTS

The incidence of youth-onset T2D in Israel increased significantly from 0.63/100,000 in 2008 to 3.41/100,000 in 2019. The study cohort comprised 379 individuals (228 girls [59.7%], 221 Jews [58.3%], mean age 14.7 ± 1.9 years); 73.1% had a positive family history of T2D. Mean body mass index (BMI) z-score was 1.96 ± 0.7, higher in Jews than Arabs. High systolic (≥ 130 mmHg) and diastolic blood pressure (≥ 85 mmHg) were observed in 33.7% and 7.8% of patients, respectively; mean glycosylated hemoglobin (A1c) level at diagnosis was 8.8 ± 2.5%. Dyslipidemia, with high triglyceride (>150 mg/dl) and low HDL-c (<40 mg/dl) levels, was found in 45.6% and 56.5%, respectively. Microalbuminuria and retinopathy were documented at diagnosis, 15.2% and 1.9%, respectively) and increased (36.7% and 4.6%, respectively) at follow-up of 2.9 ± 2.1 years. Criteria of metabolic syndrome were met by 224 (62.2%) patients, and fatty liver documented in 65%, mainly Jews. Psychosocial comorbidity was found in 31%. Treatment with metformin (45.6%), insulin (20.6%), and lifestyle modification (18%) improved glycemic control.

CONCLUSION

Youth-onset T2D in Israel has increased significantly and presents a unique profile.

Prediction of Personal Glycemic Responses to Food for Individuals With Type 1 Diabetes Through Integration of Clinical and Microbial Data

OBJECTIVE

Despite technological advances, results from various clinical trials have repeatedly shown that many individuals with type 1 diabetes (T1D) do not achieve their glycemic goals. One of the major challenges in disease management is the administration of an accurate amount of insulin for each meal that will match the expected postprandial glycemic response (PPGR). The objective of this study was to develop a prediction model for PPGR in individuals with T1D.

RESEARCH DESIGN AND METHODS

We recruited individuals with T1D who were using continuous glucose monitoring and continuous subcutaneous insulin infusion devices simultaneously to a prospective cohort and profiled them for 2 weeks. Participants were asked to report real-time dietary intake using a designated mobile app. We measured their PPGRs and devised machine learning algorithms for PPGR prediction, which integrate glucose measurements, insulin dosages, dietary habits, blood parameters, anthropometrics, exercise, and gut microbiota. Data of the PPGR of 900 healthy individuals to 41,371 meals were also integrated into the model. The performance of the models was evaluated with 10-fold cross validation.

RESULTS

A total of 121 individuals with T1D, 75 adults and 46 children, were included in the study. PPGR to 6,377 meals was measured. Our PPGR prediction model substantially outperforms a baseline model with emulation of standard of care (correlation of R = 0.59 compared with R = 0.40 for predicted and observed PPGR respectively; P < 10-10). The model was robust across different subpopulations. Feature attribution analysis revealed that glucose levels at meal initiation, glucose trend 30 min prior to meal, meal carbohydrate content, and meal's carbohydrate-to-fat ratio were the most influential features for the model.

CONCLUSIONS

Our model enables a more accurate prediction of PPGR and therefore may allow a better adjustment of the required insulin dosage for meals. It can be further implemented in closed loop systems and may lead to rationally designed nutritional interventions personally tailored for individuals with T1D on the basis of meals with expected low glycemic response.

Birth during the moderate weather seasons is associated with early onset of type 1 diabetes in the Mediterranean area

AIM

To assess the association of seasonal and perinatal parameters with early age of type 1 diabetes (T1D) onset.

METHODS

A cross-sectional review of all medical records of T1D patients born between the years 1990 and 2005, and diagnosed before/by the age of 10 years, from 13 university-affiliated paediatric medical centres in Israel, was performed. Data included: gender, ethnicity, seasons of birth and disease onset, birth gestational age and weight, and autoimmune diseases of the probands and their first-degree family members. Statistical analysis included the Chi-square test or Mann-Whitney test, as appropriate and multivariate regression analysis.

RESULTS

Enrolled were 1571 T1D patients at a median age of T1D onset 6.9 years (IQR 4.4,8.4); 336 of them presented before 4 years of age. The median age of this group was 2.5 years (IQR 1.7,3.2), and of the 1235 patients who presented after 4 years of age, median presentation age was 7.5 years (IQR 6.1,8.8). Multivariate regression analysis demonstrated that a more recent birth year; OR = 1.06, 95% CI 1.02-1.1, P = 0.003, and birth during the moderate weather months (September, October, March, and April) were significantly associated with younger age at T1D onset; OR = 1.68, 95% CI 1.17-2.4, P = 0.005.

CONCLUSIONS

Our novel finding demonstrates the association between younger than 4 years old age at presentation and birth during moderate weather months. The results also support previous reports, that there is a slight increase in the annual incidence of T1D in the youngest age groups.

Glycemic control in adolescents with type 1 diabetes: Are computerized simulations effective learning tools?

OBJECTIVE

Type 1 diabetes mellitus (T1DM) in adolescent patients is often characterized by poor glycemic control. This study aimed at exploring the contribution of learning with computerized simulations to support: (a) mechanistic understanding of the biochemical processes related to diabetes; (b) diabetes self-management knowledge; and (c) glycemic control. We hypothesized that learning with such simulations might support adolescents in gaining a better understanding of the biochemical processes related to glucose regulation, and consequently improve their glycemic control.

METHODS

A prospective case-control study was conducted in 12- to 18-year-old adolescents with T1DM (n = 85) who were routinely treated at an outpatient diabetes clinic. While the control group (n = 45) received the routine face-to-face follow-up, the intervention group (n = 40) learned in addition with computerized simulations that were embedded in pedagogically supportive activities. Participants in both groups completed a set of questionnaires regarding sociodemographic characteristics, diabetes mechanistic reasoning and diabetes self-management. Clinical data and serum glycated hemoglobin (HbA1c) levels were gathered from medical records. All the data was collected at recruitment and 3 months later.

RESULTS

Analysis revealed improvement HbA1c levels in the intervention group (8.7% ± 1.7%) vs the controls (9.6% ± 1.6%) after 3 months (P < .05). Regression analysis showed that levels of diabetes mechanistic understanding and diabetes self-management knowledge, in addition to sociodemographic parameters, accounted for 31% of the HbA1c variance (P < .001).

CONCLUSION

These results suggest that learning with computerized simulations about biochemical processes can improve adolescents' adherence to medical recommendations and result in improved glycemic control. Implementing scientific learning into the hospital educational setting is discussed.

Adherence to diabetes care: Knowledge of biochemical processes has a high impact on glycaemic control among adolescents with type 1 diabetes

AIM

To evaluate the impact of patients' understanding of biochemical processes involved in glucose regulation (causal-biochemical knowledge) and of diabetes self-management knowledge on adherence to treatment recommendations among adolescents with type 1 diabetes mellitus.

DESIGN

A cross-sectional study.

METHODS

Adolescents with type 1 diabetes mellitus, aged 12-18 years and able to read and write in Hebrew or in Arabic were eligible. Participants were recruited between August 2016 - January 2018 during routine visits to the Paediatric Diabetes Clinic; informed consent was obtained as customary. Patients completed sociodemographic, clinical and type 1 diabetes mellitus self-management and biochemical knowledge questionnaires. Adherence to treatment was assessed by patients' serum HbA1c levels, collected from medical records.

RESULTS

Ninety-seven patients participated in the study. Mean HbA1c levels were 9.2% (1.9%) and only 24 (24.7%) patients met the recommended HbA1c ≤ 7.5%. Lower HbA1c levels were strongly associated with higher family income, older age at diagnosis and with better type 1 diabetes mellitus self-management and causal-biochemical knowledge. A regression model showed that causal-biochemical knowledge contributed to the variance in HbA1c levels. Furthermore, causal-biochemical knowledge, but not self-management knowledge, was found to mediate the negative relationship between low family income and high HbA1c levels.

CONCLUSIONS

Causal-biochemical knowledge is a valuable component for the adherence to diabetes care and glycaemic control.

IMPACT

Our study suggests that causal knowledge is a valuable component that should be included in nursing and healthcare educational programmes for adolescents with type 1 diabetes mellitus.

Increased prevalence of disordered eating in the dual diagnosis of type 1 diabetes mellitus and celiac disease

BACKGROUND

Disordered eating behaviors (DEBs) may lead to full blown eating disorders. Both type 1 diabetes mellitus (T1DM) and celiac disease (CD) have been linked to DEBs.

OBJECTIVE

To compare the presence of DEBs between adolescents and young adults with a dual diagnosis of T1DM and CD, and individuals with only one of the diagnoses.

METHODS

Individuals with a dual diagnosis of T1DM and CD ("T1DM + CD group" n = 39), with a diagnosis of T1DM only ("T1DM group" n = 97) and with a diagnosis of CD only ("CD group" n = 267) filled the Eating Attitude Test-26 (EAT-26) questionnaire. Those with T1DM completed in addition to the Diabetes Eating Problem Survey-Revised (DEPS-R).

RESULTS

The study population comprised of 403 individuals, of whom 65% were females. There were no statistically significant differences among the groups in distribution of sex, age, hemoglobin A1c (HbA1c) levels, age of disease diagnosis and duration. The prevalence of DEBs in the T1DM + CD group was 3-fold higher (26.0%) than in the T1DM (8.2%) and CD (8.2%) groups (P = .003). This trend was observed for both females and males. Multivariate analysis demonstrated that the T1DM + CD group had an increased risk for DEBs (odds ratio, OR: 4.7, 95% confidence interval, CI: 1.9-11.2, P = .001) after adjustment for age, sex, and body mass index. Additionally, being female, older and overweight increased the risk for DEBs. HbA1c values were not associated with an increased DEBs rate.

CONCLUSIONS

Individuals with the dual diagnoses of T1DM and CD have an increased likelihood to develop DEBs compared to those with only one of these diagnoses.