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Objectives: To assess the optimal setting of the predictive low glucose management (PLGM) algorithm for preventing exercise‐induced hypoglycemia in adolescents with type 1 diabetes. Methods: Thirty‐four adolescents, 15 to 20 years, wearing PLGM system, were followed during 3 days exercise during a diabetes camp. PLGM threshold was set at 70 mg/dL between 8 am and 10 pm and 90 mg/dL during 10 pm and 8 am Adolescents were divided into group A and B, with PLGM threshold at 90 and 70 mg/dL, respectively, during exercise. Time spent in hypoglycemia and AUC for time slots 8 am to 1 pm, 1 to 4 pm, 4 to 11 pm, 11 pm to 3 am, 3 to 8 am, in 3 days were compared between groups by Wilcoxon rank sum test. Results: We analyzed 31 patients (median age 15.0 years, 58.1% males, median diabetes duration 7.0 years, hemoglobin A1c [HbA1c] 7.1%). No significant difference has been observed in time spent in hypoglycemia between groups using threshold 70 or 90. Time spent in target was similar in both groups, as well as time spent in hypo or hyperglycemia. The trends of blood glucose over the 3 days in the 2 groups over‐lapped without significant differences. Conclusions: A PLGM threshold of 90 mg/dL during the night was associated with reduced time in hypoglycemia in adolescents doing frequent physical exercise, while maintaining 65.1% time in range during the day. However, a threshold of 70 mg/dL seems to be safe in the duration of the physical exercise. PLGM system in adolescents with type 1 diabetes was effective to prevent hypoglycemia during and after exercise, irrespective of the PLGM thresholds used. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the association of clinical, metabolic and socioeconomic factors with disordered eating behaviors (DEB) among adolescents with type 1 diabetes screened using the Diabetes Eating Problem Survey‐Revised (DEPS‐R). Methods: A cross‐sectional, population‐based study involved 163 adolescents with type 1 diabetes, aged 11–20 years, recruited from the registry for type 1 diabetes of Marche Region, Italy, who completed the DEPS‐R (response rate 74.4%). Clinical characteristics, lipid profile, HbA1c, family profile of education and occupation were evaluated. The Italian version of DEPS‐R was validated, and the prevalence of DEB estimated. The association of demographic, socioeconomic, and clinical factors with DEB was evaluated by multiple correspondence analysis and multiple logistic regression. Results: The prevalence of DEPS‐R‐positive (score ≥20) was 27% (95% CI 17–38) in boys and 42% (95% CI 31–53) in girls. A clinical profile of DEPS‐R‐positive was identified: overweight, little time spent in physical activity, low socioeconomic status, poor metabolic control, skipping insulin injections. Furthermore, the probability of DEPS‐R‐positive increased 63% for every added unit of HbA1c, 36% for every added number of insulin injections skipped in a week and decreased about 20% for every added hour/week spent in physical activity. Overweight youth were six times more likely to be DEPS‐R‐positive. Discussion: A specific clinical profile of DEPS‐R‐positive was identified. A multidisciplinary clinical approach aimed to normalize eating behaviors and enhance self‐esteem should be used to prevent the onset of these behaviors, and continuous educational programs are needed to promote healthy behaviors and lifestyles. [ABSTRACT FROM AUTHOR]

Objective To identify the role of the family's socio-economic and clinical characteristics on metabolic control in children and adolescents with type 1 diabetes. Methods In this cross-sectional, multicentre study, 768 subjects with type 1 diabetes under 18 years of age were consecutively recruited from January 2008 to February 2009. Target condition was considered for HbA1c values <7.5% (<58 mmol/mol). A multiple correspondence analysis ( MCA) was performed to analyze the association between the socio-economic and clinical characteristics of the participants. A logistic regression analysis was performed to identify factors associated with the subjects metabolic control. In both analyses, the family's socio-economic status was represented, measured by the Hollingshead Four-Factor Index of Social Status ( SES) or by parental years of education. Results A total of 28.1% of subjects reached target HbA1c values. The MCA identified a strong association between at-target condition and several factors: high levels of SES or high levels of parental education, the use of the carbohydrate counting system, the use of insulin pumps, the use of the insulin delivery system over a short period of time, a normal body mass index. The logistic regression analysis showed that SES and the mother's years of education were significantly associated with the target condition [odds ratio ( OR): 1.01, 95% confidence interval ( CI): 1.01-1.03, p = 0.029; OR: 1.05, 95% CI: 1.01-1.10, p = 0.027, respectively). Conclusions Personal, clinical, and family characteristics were found to be associated with HbA1c target. Their identification can be crucial in addressing strategies to optimize metabolic control and improve diabetes management. [ABSTRACT FROM AUTHOR]