RESUMO
OBJECT: As part of their treatment, patients with type 1 diabetes mellitus (DM) have to be very careful with what they eat and with their insulin doses. Therefore, the risk of eating disorders increases in this patient group. In this study, we aimed to determine the disordered eating behaviors of patients with type 1 DM and to evaluate the sociodemographic characteristics, diabetes care behaviors, and quality-of-life scale results that these behaviors may be related to. METHOD: The sociodemographic characteristics and diabetes treatment data of 191 patients aged 9-18 years with type 1 DM were analyzed. The Pediatric Quality of Life Inventory (PedsQL), the PedsQL 3.0 Diabetes Module, and the Diabetes Eating Problem Survey-Revised (DEPS-R) were applied. RESULTS: The median DEPS-R score of the patients was 18 (19.00), and 44.5 % had a DEPS-R score above 20. A significant correlation was found between age, duration of diabetes, frequency of blood glucose measurement, hemoglobin A1c (HbA1c) level, body mass index standard deviation score (BMI-SDS), and DEPS-R score. There was no significant difference between girls and boys. Patients with a high DEPS-R score had low scores on the PedsQL and on the PedsQL 3.0 Diabetes Module. CONCLUSION: The DEPS-R scale is a diabetes-specific, easy-to-use, and effective method for screening patients with type 1 DM for disordered eating behaviors. It can help prevent the progression of disordered eating behaviors to clinical eating disorders in patients with type 1 DM. It would be beneficial to use this scale as a routine screening, especially in clinics where access to a psychologist is not possible.
RESUMO
OBJECTIVE: A decline in sleep quality and regularity has been reported in patients with type 1 diabetes mellitus (T1D) in many studies. However, research on medical-based sleep disorders in patients with T1D is limited. Diagnosing sleep disorders is crucial, as it negatively impacts academic performance, cardiovascular health, and cognitive functions among children as well as essential skills for effective diabetes management. Our objective was to assess sleep disturbances in patients diagnosed with T1D and explore whether these patients experience significantly more sleep disturbances compared to their healthy peers. METHODS: This study, designed as a cross-sectional case-control investigation, involved a cohort of 250 participants (144 T1D, 106 control cases) aged 6-15 years. The Sleep Disturbance Scale for Children (SDCS) scores of the T1D group were compared with those of the control group. Furthermore, the study explored the correlation between clinical/biochemical parameters and SDCS scores within the T1D group. RESULTS: The mean age of individuals in the T1D group was 10.27 ± 3.25 years, while the control group had a comparable mean age of 10.48 ± 3.5 years (P = 0.303). Within the T1D group, the median duration of diabetes was 5 (1-15) years, and the median glycosylated hemoglobin A1c (HbA1c) level for the past one year was 8.4 %. Although there was no significant difference in total SDSC scores between the T1D and control groups, both groups exhibited average scores that remained close to the threshold indicative of sleep disturbances (>39). Notably, individuals with total SDSC scores surpassing 39 were identified at rates of 48.6 % in the T1D group and 47.6 % in the control group, respectively. Furthermore, disorders of arousal nightmares (DA) were more prevalent in T1D patients compared to their healthy peers (P = 0.049). Additionally, HbA1c showed a positive correlation with scores for disorders of excessive somnolence (DOES) and total scores (P < 0.001, R = 0.368; P = 0.003, R = 0.243). CONCLUSION: Our study found that the prevalence of sleep disturbances among children and adolescents with T1D was not significantly higher than that observed in their healthy peers. Nevertheless, it is crucial to note that a notable portion, 48.6 % of T1D cases and 47.6 % of healthy cases, displayed sleep disturbances based on SDSC scores. To optimize diabetes management and proactively address potential challenges, incorporating routine screening for sleep disturbances in the monitoring of T1D patients can yield valuable benefits.