Associations Between Objective Sleep Behaviors and Blood Glucose Variability in Young Children With Type 1 Diabetes

Adherence to the Mediterranean diet and sleep quality are inter-correlated with flash glucose monitoring (FGM)-measured glycemia among children with type 1 diabetes

BACKGROUND

We examined the inter-correlation between diet quality, objectively measured sleep duration, and subjectively measured sleep quality with flash glucose monitoring (FGM)-measured glycemia among young patients with type 1 diabetes (T1D).

MATERIALS AND METHODS

Following cross-sectional design, Fitbit® accelerometers were used to objectively assess sleep duration, while the validated questionnaires Pittsburgh sleep quality index and Mediterranean diet (MD) adherence were used to subjectively assess sleep quality and diet quality, respectively. Glycated hemoglobin (HbA1c) and FGM-reported glycemia components among children with T1D were assessed as well.

RESULTS

Of the 47 participants surveyed (25 boys, 22 girls, 9.31 ± 2.88 years), the majority reported high HbA1c, good sleep quality, and high adherence to the MD. However, only one-third of the participants reported a healthy sleep duration. Only the sleep latency was significantly (P < 0.05) associated with the time above range level 2 and time below range level 2 (P = 0.048) components of the FGM. A positive correlation (r = 0.309, P = 0.035) was reported between adherence to MD and time in range of the FGM.

CONCLUSIONS

Diet quality and sleep quality are variably inter-correlated with FGM-measured glycemia among young patients with T1D and are suggested to be considered influential factors in FGM-monitored diabetes research on this age group.

Prolonged Use of an Automated Insulin Delivery System Improves Sleep in Long-Standing Type 1 Diabetes Complicated by Impaired Awareness of Hypoglycemia

BACKGROUND

This study assessed changes in actigraphy-estimated sleep and glycemic outcomes after initiating automated insulin delivery (AID).

METHODS

Ten adults with long-standing type 1 diabetes and impaired awareness of hypoglycemia (IAH) participated in an 18-month clinical trial assessing an AID intervention on hypoglycemia and counter-regulatory mechanisms. Data from eight participants (median age = 58 years) with concurrent wrist actigraph and continuous glucose monitoring (CGM) data were used in the present analyses. Actigraphs and CGM measured sleep and glycemic control at baseline (one week) and months 3, 6, 9, 12, 15, and 18 (three weeks) following AID initiation. HypoCount software integrated actigraphy with CGM data to separate wake and sleep-associated glycemic measures. Paired sample t-tests and Cohen's d effect sizes modeled changes and their magnitude in sleep, glycemic control, IAH (Clarke score), hypoglycemia severity (HYPO score), hypoglycemia exposure (CGM), and glycemic variability (lability index [LI]; CGM coefficient-of-variation [CV]) from baseline to 18 months.

RESULTS

Sleep improved from baseline to 18 months (shorter sleep latency [P < .05, d = 1.74], later sleep offset [P < .05, d = 0.90], less wake after sleep onset [P < .01, d = 1.43]). Later sleep onset (d = 0.74) and sleep midpoint (d = 0.77) showed medium effect sizes. Sleep improvements were evident from 12 to 15 months after AID initiation and were preceded by improved hypoglycemia awareness (Clarke score [d = 1.18]), reduced hypoglycemia severity (HYPO score [d = 2.13]), reduced sleep-associated hypoglycemia (percent time glucose was < 54 mg/dL, < 60 mg/dL,< 70 mg/dL; d = 0.66-0.81), and reduced glucose variability (LI, d = 0.86; CV, d = 0.62).

CONCLUSION

AID improved sleep initiation and maintenance. Improved awareness of hypoglycemia, reduced hypoglycemia severity, hypoglycemia exposure, and glucose variability preceded sleep improvements.This trial is registered with ClinicalTrials.gov NCT03215914 https://clinicaltrials.gov/ct2/show/NCT03215914.

Sleep and psychological characteristics of children with cancers and type 1 diabetes and their caregivers

OBJECTIVES

Children with chronic illnesses and their parents are more at risk to develop sleep problems, which are linked to worse psychological and physical well-being. This study aimed to assess sleep patterns and their connections with psychological outcomes in children with type 1 diabetes (T1D) and cancer and their caregivers, compared to a control sample. In addition, we explored the associations between caregiver and child's sleep quality across the three groups.

METHODS

We enrolled 56 children with T1D, 33 children with cancer, and 61 healthy children between 7 and 15, and their respective caregivers. Caregivers filled out an ad-hoc survey assessing their sleep disturbances, parenting stress, general well-being, anxiety, and their children's sleep patterns and psychological adjustments.

RESULTS

Children with cancer showed lower sleep quality than the other groups. Moreover, worse psychological adjustment was associated with greater sleep disturbances in both clinical groups. As for caregivers, the cancer group reported the worst sleep quality and greater anxiety compared to the other samples. Greater anxiety was also linked to worse sleep quality. Furthermore, greater sleep problems in children were associated with poorer caregivers' sleep quality in the whole sample and the T1D group.

CONCLUSIONS

A better understanding of sleep patterns and problems for chronically ill children and their parents is fundamental to provide adequate care for these vulnerable populations. Furthermore, an illness-specific approach may better inform and guide the practitioners in clinical practice.

Safety and user experience with off-label use of a flash glucose monitor (FreeStyle Libre® 1) among very young children with type 1 diabetes mellitus

OBJECTIVES

FreeStyle Libre 1 (FGM) has been approved by the FDA for children older than 4 years. It enables noninvasive glucose monitoring without the need for finger pricking. Parents of very young children often use the device off-label. Thus, we aimed to evaluate the safety of and user experience with FreeStyle Libre^® 1 and determine its impact on sleep and glycemic control.

METHODS

This was an ambi-directional cohort study. We recruited parents of very young children with type 1 diabetes mellitus (T1DM) who were less than 5 years old when they started using FGM at the King Saud University Diabetes Center. The parents filled out a survey evaluating their experience with the system. In addition, the glucose metrics of the children were also obtained from the Libre View system.

RESULTS

We included 31 children with mean age of the children when they started using FGM was 3.88 ± 1.10 years (range, 1.46-5.4 years), and the mean sensor use was 2.3 ± 1.3 years. During the use of the device, the parents had increased sleep duration of 0.71 h (p-value=0.04), had earlier bedtime by 2.8 h (p-value=0.04), and were able to sleep in a separate room from their children. In addition, the time in range improved by 9.9%, the time above range decreased by 8.8%, and the HbA_1c level reduced by 1.56%.

CONCLUSIONS

The safety profile of FGM used for very young children with T1DM is the same for older children, which leads to improved metabolic control and sleep quality of both the parent and the child.

Sleep-Opt-In: A Randomized Controlled Pilot Study to Improve Sleep and Glycemic Variability in Adults With Type 1 Diabetes

PURPOSE

The purpose of this study was to evaluate the feasibility and acceptability of a technology-assisted behavioral sleep intervention (Sleep-Opt-In) and to examine the effects of Sleep-Opt-In on sleep duration and regularity, glucose indices, and patient-reported outcomes. Short sleep duration and irregular sleep schedules are associated with reduced glycemic control and greater glycemic variability.

METHODS

A randomized controlled parallel-arm pilot study was employed. Adults with type 1 diabetes (n = 14) were recruited from the Midwest and randomized 3:2 to the sleep-optimization (Sleep-Opt-In) or Healthy Living attention control group. Sleep-Opt-In was an 8-week, remotely delivered intervention consisting of digital lessons, sleep tracker, and weekly coaching phone calls by a trained sleep coach. Assessments of sleep (actigraphy), glucose (A1C, continuous glucose monitoring), and patient-reported outcomes (questionnaires for daytime sleepiness, fatigue, diabetes distress, and depressive mood) were completed at baseline and at completion of the intervention.

RESULTS

Sleep-Opt-In was feasible and acceptable. Those in Sleep-Opt-In with objectively confirmed short or irregular sleep demonstrated an improvement in sleep regularity (25 minutes), reduced glycemic variability (3.2%), and improved time in range (6.9%) compared to the Healthy Living attention control group. Patient-reported outcomes improved only for the Sleep-Opt-In group. Fatigue and depressive mood improved compared to the control.

CONCLUSIONS

Sleep-Opt-In is feasible, acceptable, and promising for further evaluation as a means to improve sleep duration or regularity in the population of people with type 1 diabetes.

Physical Activity, Glycemic Variability, and Parental Hypoglycemia Fear in Preschoolers With Type 1 Diabetes

PURPOSE

The authors examined associations between preschoolers' daily glycemic variability, parents' report of hypoglycemia fear, and preschoolers' daily moderate to vigorous physical activity (MVPA) and sedentary behavior (SB) in 25 families of preschoolers with type 1 diabetes.

METHODS

Parents completed a valid measure of hypoglycemia fear, and their child wore an accelerometer for up to 7 days. Parents provided glucose data from their child's devices. The authors used multiple regression and multilevel modeling to analyze their data.

RESULTS

Preschoolers (mean age 4.2 [1.7] y; 50% boys) engaged in a mean of 154.5 (59.6) and 339.2 (85.1) minutes of MVPA and SB per day, respectively, and parents reported relatively low levels of hypoglycemia worry and avoidance behaviors. Preschoolers' SB (r = .19, P = .02) and MVPA (r = -.20, P = .01) levels were significantly correlated with parental hypoglycemia worry scores but not with parents' hypoglycemia behavior scores (P = .15 and P = .92, respectively). While multilevel models did not show an association between MVPA and preschoolers' glycemic variability, preschoolers who engaged in more daily SB experienced higher glycemic variability (P = .04).

CONCLUSIONS

Research exploring MVPA, SB, and parental hypoglycemia fear in preschoolers with type 1 diabetes could have important clinical implications because it may reveal modifiable treatment targets that can impact preschoolers' health and activity patterns.

Childhood diabetes and sleep

Sleep modulates glucose metabolism, both in healthy states and in disease. Alterations in sleep duration (insufficient and excessive) and obstructive sleep apnea may have reciprocal ties with obesity, insulin resistance and Type 2 diabetes, as demonstrated by emerging evidence in children and adolescents. Type 1 diabetes is also associated with sleep disturbances due to the influence of wide glycemic fluctuations upon sleep architecture, the need to treat nocturnal hypoglycemia, and the need for glucose monitoring and insulin delivery technologies. In this article, we provide an extensive and critical review on published pediatric literature regarding these topics, reviewing both epidemiologic and qualitative data, and provide an overview of the pathophysiology linking sleep with disorders of glucose homeostasis.

Friend or Foe: a Narrative Review of the Impact of Diabetes Technology on Sleep

PURPOSE OF REVIEW

The purpose of this review is to present a review of sleep science, the relationship between sleep and type 1 diabetes, and highlight the current literature on sleep outcomes in adult and pediatric diabetes technology research.

RECENT FINDINGS

Sleep quality is associated with glycemic outcomes, diabetes self-management, and mental health in people with type 1 diabetes. Diabetes technologies, including insulin pumps, continuous glucose monitors, and hybrid closed-loop systems improve glycemic outcomes. However, many people find this technology challenging for a variety of reasons, including increased burden and frequent alarms, especially during the night. The impact of different devices on sleep quality and quantity has been mixed. The newest technology, the hybrid closed-loop systems, offers the best opportunity for nocturnal glycemic regulation and has improved patient and family perspectives on sleep quality. However, objective sleep assessment has not shown significant improvement on sleep duration. Sleep quality and quantity in people with type 1 diabetes are widely recognized as an important component of health care, and the literature regarding the impact of diabetes devices on sleep is increasing. However, sleep disruptions are common and a barrier to device use. Despite finding minimal changes to sleep duration with device use, subjective accounts of sleep quality are overall positive, especially in those using hybrid closed-loop systems. Sleep quantity and quality are important outcomes to consider as diabetes technology continues to evolve.

Type 1 Diabetes, Sleep, and Hypoglycemia

PURPOSE OF REVIEW

To review the relationship between sleep and hypoglycemia, sleep characteristics, and their associations with glycemic control in persons with type 1 diabetes (T1D). The effects of sleep interventions and diabetes technology on sleep are summarized.

RECENT FINDINGS

Nocturnal hypoglycemia affects objective and subjective sleep quality and is related to behavioral, psychological, and physiological factors. Sleep disturbances are common, including inadequate sleep, impaired sleep efficiency, poor subjective satisfaction, irregular timing, increased daytime sleepiness, and sleep apnea. Some have a bidirectional relationship with glycemic control. Preliminary evidence supports sleep interventions (e.g., sleep extension and sleep coach) in improving sleep and glycemic control, while diabetes technology use could potentially improve sleep. Hypoglycemia and sleep disturbances are common among persons with T1D. There is a need to develop sleep promotion programs and test their effects on sleep, glucose, and related outcomes (e.g., self-care, psychological health).

A 25-Year Review of Nighttime Fears in Children: Past, Present, and Future

Nighttime fears in children are common, interfere with daily functioning, and result in considerable disruption in the family. The aim of the present review was to examine empirical literature from the past 25 years that investigated the assessment of nighttime fears in young children and the efficacy and effectiveness of psychosocial treatments for children's nighttime fears. The last review of this literature was in 1997 and examined studies conducted in and prior to 1995 (King et al. in Clin Psychol Rev 17:431-443, 1997). Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we conducted a systematic review of the literature aimed at providing a synthesis of the Randomized Control Trials (RCTs) and controlled single-case multiple baseline design studies (MBLs) on the treatment of nighttime fears in children. A search of the literature identified 12 articles, with nine studies utilizing a between-group randomized controlled trial design and three studies utilizing a multiple baseline design. Results demonstrated significant improvements in children's nighttime fears and reductions in disruptive nighttime behaviors using behavioral interventions and cognitive-behavioral strategies. This review provides a commentary on the effectiveness and limitations of the assessment and treatment approaches for nighttime fears in children and suggests directions for future research.

Technological Ecological Momentary Assessment Tools to Study Type 1 Diabetes in Youth: Viewpoint of Methodologies

Type 1 diabetes (T1D) is one of the most common chronic childhood diseases, and its prevalence is rapidly increasing. The management of glucose in T1D is challenging, as youth must consider a myriad of factors when making diabetes care decisions. This task often leads to significant hyperglycemia, hypoglycemia, and glucose variability throughout the day, which have been associated with short- and long-term medical complications. At present, most of what is known about each of these complications and the health behaviors that may lead to them have been uncovered in the clinical setting or in laboratory-based research. However, the tools often used in these settings are limited in their ability to capture the dynamic behaviors, feelings, and physiological changes associated with T1D that fluctuate from moment to moment throughout the day. A better understanding of T1D in daily life could potentially aid in the development of interventions to improve diabetes care and mitigate the negative medical consequences associated with it. Therefore, there is a need to measure repeated, real-time, and real-world features of this disease in youth. This approach is known as ecological momentary assessment (EMA), and it has considerable advantages to in-lab research. Thus, this viewpoint aims to describe EMA tools that have been used to collect data in the daily lives of youth with T1D and discuss studies that explored the nuances of T1D in daily life using these methods. This viewpoint focuses on the following EMA methods: continuous glucose monitoring, actigraphy, ambulatory blood pressure monitoring, personal digital assistants, smartphones, and phone-based systems. The viewpoint also discusses the benefits of using EMA methods to collect important data that might not otherwise be collected in the laboratory and the limitations of each tool, future directions of the field, and possible clinical implications for their use.

Functional data analysis and prediction tools for continuous glucose-monitoring studies

Introduction

To identify phenotypes of type 1 diabetes based on glucose curves from continuous glucose-monitoring (CGM) using functional data (FD) analysis to account for longitudinal glucose patterns. We present a reliable prediction model that can accurately predict glycemic levels based on past data collected from the CGM sensor and real-time risk of hypo-/hyperglycemic for individuals with type 1 diabetes.

Methods

A longitudinal cohort study of 443 type 1 diabetes patients with CGM data from a completed trial. The FD analysis approach, sparse functional principal components (FPCs) analysis was used to identify phenotypes of type 1 diabetes glycemic variation. We employed a nonstationary stochastic linear mixed-effects model (LME) that accommodates between-patient and within-patient heterogeneity to predict glycemic levels and real-time risk of hypo-/hyperglycemic by creating specific target functions for these excursions.

Results

The majority of the variation (73%) in glucose trajectories was explained by the first two FPCs. Higher order variation in the CGM profiles occurred during weeknights, although variation was higher on weekends. The model has low prediction errors and yields accurate predictions for both glucose levels and real-time risk of glycemic excursions.

Conclusions

By identifying these distinct longitudinal patterns as phenotypes, interventions can be targeted to optimize type 1 diabetes management for subgroups at the highest risk for compromised long-term outcomes such as cardiac disease or stroke. Further, the estimated change/variability in an individual's glucose trajectory can be used to establish clinically meaningful and patient-specific thresholds that, when coupled with probabilistic predictive inference, provide a useful medical-monitoring tool.

Reducing Emotional Distress for Childhood Hypoglycemia in Parents (REDCHiP): Protocol for a Randomized Clinical Trial to Test a Video-Based Telehealth Intervention

Background

Despite the introduction of new insulin analogs, insulin pumps, and continuous glucose monitoring (CGM), young children with type 1 diabetes mellitus (T1D) remain vulnerable to episodes of hypoglycemia because of their unpredictable eating and activity patterns and high degree of insulin sensitivity. Caregivers and young children living with T1D learn to fear hypoglycemia because it is uncomfortable, unpredictable, and dangerous. Up to 60% of caregivers of young children with T1D report moderate to severe levels of fear of hypoglycemia, and caregiver fear of hypoglycemia relates to lower quality of life for families and suboptimal child glycemic control. Yet, until recently, there have been no studies reporting on a targeted intervention to treat caregiver fear of hypoglycemia in families of young children.

Objective

The aim of this project is to conduct a randomized clinical trial of an innovative, video-based telehealth intervention to treat fear of hypoglycemia in caregivers of young children with T1D versus a relevant, age-appropriate attention control intervention.

Methods

We created the Reducing Emotional Distress for Childhood Hypoglycemia in Parents (REDCHiP) intervention by merging age-appropriate T1D education and behavioral parenting strategies with cognitive behavioral therapy strategies that are effective for reducing fear and promoting adaptive coping. REDCHiP uses 10 video-based telehealth sessions that are a combination of group and individual sessions. We will recruit up to 180 families of young children with T1D to participate in this clinical trial from two pediatric diabetes clinics located in the midwestern and southern United States. Once families have been enrolled, we will randomize caregivers based on child age (age 2-3 years or 4-5 years), child sex, and family CGM use to participate in the REDCHiP or attention control intervention. Families will complete 3 assessment visits that coincide with study entry, end of treatment, and 3-month posttreatment. At each assessment visit, we will collect questionnaire data from caregivers, accelerometry data from caregivers and children, CGM data from children, and a blood sample to measure glycated hemoglobin levels from children.

Results

Recruitment began in July 2019, and enrollment is ongoing. The first wave of intervention delivery began in December 2019. We anticipate completing enrollment in 2023. Final reporting of results will occur within 12 months of the primary completion date.

Conclusions

If the REDCHiP intervention is efficacious, next steps will be to examine multiple implementation strategies to determine how best to disseminate the intervention to pediatric diabetes clinics around the world.

Trial Registration

ClinicalTrials.gov NCT03914547; https://clinicaltrials.gov/ct2/show/NCT03914547

International Registered Report Identifier (IRRID)

PRR1-10.2196/17877