Associations between sleep characteristics and glycemic variability in youth with type 1 diabetes

Chronotype, sleep, and glycemic control in children and adolescents with type 1 diabetes: a case-control study

OBJECTIVES

This study aimed to explore the relationships between sleep parameters, chronotype preferences, and glycemic control in children and adolescents with type 1 diabetes (T1DM), compared to healthy peers.

METHODS

A total of 96 children and adolescents with T1DM and 95 healthy controls aged 8-18 years participated in this case-control study. Anthropometric measurements were collected, and participants completed the Munich Chronotype Questionnaire and the Pittsburgh Sleep Quality Index (PSQI). Glycemic control was assessed using HbA1c levels.

RESULTS

Children with T1DM demonstrated significantly shorter sleep durations, poorer sleep quality, and a later chronotype compared to controls (p<0.05). Poor glycemic control (HbA1c>7.5 %) was observed in 72.9 % of the T1DM group, with 34.3 % exhibiting very poor control (HbA1c>9 %). Logistic regression identified poor sleep quality (PSQI score, OR: 1.47, p<0.001) and later chronotype (OR: 5.14, p<0.01) as independent predictors of poor glycemic control. Generalized linear modeling (GLM) further revealed significant associations between HbA1c levels, insulin dosage (p<0.001), and chronotype (p=0.090).

CONCLUSIONS

Late chronotype and poor sleep quality are closely linked to suboptimal glycemic control in pediatric T1DM populations. These findings underscore the importance of integrating sleep-focused strategies into routine diabetes management.

The sleep health composite and chronotype among children and adolescents with type 1 diabetes compared to case-control peers without diabetes

STUDY OBJECTIVES

Our objectives were to compare sleep health composite dimensions and chronotype in children and adolescents with and without type 1 diabetes (T1D) and to explore the relationship between sleep and glycemic variability in T1D.

METHODS

The study comprised 84 participants with T1D aged between 6 to 18 years and age- and sex-matched controls. The sleep health composite was measured using actigraphy, sleep diaries, and self or parental reports. Sleep disturbance was evaluated using the DSM-5 Level 2 Sleep Disorders Scale Short Form. Chronotype was determined using the Children's Chronotype Questionnaire.

RESULTS

The median total sleep health composite score for both the T1D and control groups was 3.0 (3.0-4.0) (P = .485). Sleep quality was reported as good by 89.3% of participants with T1D and 96.4% of controls (P = .072). Objective data from actigraphy indicated poor sleep quality in 56% of participants with T1D and 59.5% of controls (P = .639). Additionally, 88% of participants with T1D and 84.5% of controls had inadequate total age-appropriate sleep duration (P = .501). Among participants with T1D, those with a stable glycemic variability (coefficient of variation < 36%) had an earlier midpoint sleep (P = .008).

CONCLUSIONS

Our study indicates that there are no significant differences in the sleep health composite and chronotype between children and adolescents with and without T1D. Although most participants reported good sleep quality, objective assessments indicated poor sleep quality. These findings suggest that children and adolescents may overestimate their sleep quality.

CLINICAL TRIAL REGISTRATION

Registry: ClinicalTrials.gov; Name: Sleep Patterns and Chronotype in Children With and Without Type 1 Diabetes; URL: https://clinicaltrials.gov/study/NCT06318611; Identifier: NCT06318611.

CITATION

İpar N, Boran P, Barış HE, et al. The sleep health composite and chronotype among children and adolescents with type 1 diabetes compared to case-control peers without diabetes. J Clin Sleep Med. 2025;21(5):825-834.

Sleep Disturbances in Type 1 Diabetes and Mitigating Cardiovascular Risk

Cardiovascular disease (CVD) is a major cause of morbidity and mortality in persons with type 1 diabetes (T1D). Despite control of known cardiovascular (CV) risk factors and better glycemic management, persons with T1D still face heightened CVD risk, suggesting additional contributing factors. Sleep has recently been recognized as a CV risk factor; however; the role of sleep in CVD specifically in T1D population has only started to emerge. Extensive evidence suggests that persons with T1D often encounter sleep disturbances. This review aims to comprehensively explore the relationship between sleep disturbances and CVD in T1D, proposed possible mediators including glycemic control, which has been studied more extensively, and less studied factors such as blood pressure, lipid metabolism, and weight management. Stress and self-care behaviors likely also play a role in the relationship between sleep disturbances and CVD. The evidence regarding sleep interventions in the context of T1D in mitigating these CV risk factors has recently been shown in early, small-scale studies. Sleep assessments should be a part of the standard of care in persons with T1D. Further research should focus on understanding the impact and mechanistic pathways of sleep disturbances on CV risk and developing T1D-specific sleep interventions to reduce CVD burden in this population.

Sleep disturbances in children and adolescents with type 1 diabetes mellitus: Prevalence, and relationship with diabetes management

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.

Discordance between Glucose Management Indicator and Glycated Hemoglobin in a Pediatric Cohort with Type 1 Diabetes: A Real-World Study

The introduction of continuous glucose monitoring (CGM) systems in clinical practice has allowed a more detailed picture of the intra- and interdaily glycemic fluctuations of individuals with type 1 diabetes (T1D). However, CGM-measured glucose control indicators may be occasionally inaccurate. This study aims to assess the discrepancy between the glucose management indicator (GMI) and glycated hemoglobin (HbA1c) (ΔGMI-HbA1c) within a cohort of children and adolescents with T1D, exploring its correlation with other CGM metrics and blood count parameters. In this single-center, cross-sectional study, we gathered demographic and clinical data, including blood count parameters, HbA1c values, and CGM metrics, from 128 pediatric subjects with T1D (43% female; mean age, 13.4 ± 3.6 years). Our findings revealed higher levels of the coefficient of variation (CV) (p < 0.001) and time above range > 250 mg/dL (p = 0.033) among subjects with ΔGMI-HbA1c > 0.3%. No association was observed between blood count parameters and ΔGMI-HbA1c. In conclusion, despite the advancements and the widespread adoption of CGM systems, HbA1c remains an essential parameter for the assessment of glycemic control, especially in individuals with suboptimal metabolic control and extreme glycemic variability.

Impact of 6-months of an advanced hybrid closed-loop system on sleep and psychosocial outcomes in youth with type 1 diabetes and their parents

INTRODUCTION

Youth with type 1 diabetes (T1D) and parents experience reduced quality of life and sleep quality due to nocturnal monitoring, hypoglycemia fear, and diabetes-related disruptions. This study examined the sleep and quality of life impact of advanced technology.

METHODS

Thirty-nine youth with T1D, aged 2-17 years, starting an advanced hybrid closed-loop (HCL) system and a parent participated in an observational study. Surveys, actigraphy, sleep diaries, and glycemic data (youth) were captured prior to HCL, at one week, 3 months, and 6 months. Outcomes were modeled using linear mixed effects models with random intercepts to account for within-subject correlation, with least-squares means at each timepoint compared to baseline.

RESULTS

Parents and youth reported improvements in health-related quality of life and fear of hypoglycemia after HCL initiation. Concurrently, nocturnal glycemia improved. Actigraphy-derived sleep outcomes showed improved 6 month adolescent efficiency and 3 and 6 month parent wake after sleep onset. Additionally, parents reported improved subjective sleep quality and child sleep-related impairment at 3 months.

CONCLUSIONS

With nocturnal glycemic improvements in youth using HCL technology, some aspects of parent and youth sleep and quality of life improved. This may reflect decreased parental monitoring and worry and highlights benefits for youth beyond glycemia.