Sleep-wake characteristics, daytime sleepiness, and glycemia in young adults with type 1 diabetes

Nocturnal hypoglycemia is associated with next day cognitive performance in adults with type 1 diabetes: Pilot data from the GluCog study

OBJECTIVE

 Individuals with type 1 diabetes (T1D) have increased risk for cognitive dysfunction and high rates of sleep disturbance. Despite associations between glycemia and cognitive performance using cross-sectional and experimental methods few studies have evaluated this relationship in a naturalistic setting, or the impact of nocturnal versus daytime hypoglycemia. Ecological Momentary Assessment (EMA) may provide insight into the dynamic associations between cognition, affective, and physiological states. The current study couples EMA data with continuous glucose monitoring (CGM) to examine the within-person impact of nocturnal glycemia on next day cognitive performance in adults with T1D. Due to high rates of sleep disturbance and emotional distress in people with T1D, the potential impacts of sleep characteristics and negative affect were also evaluated.

METHODS

 This pilot study utilized EMA in 18 adults with T1D to examine the impact of glycemic excursions, measured using CGM, on cognitive performance, measured via mobile cognitive assessment using the TestMyBrain platform. Multilevel modeling was used to test the within-person effects of nocturnal hypoglycemia and hyperglycemia on next day cognition.

RESULTS

 Results indicated that increases in nocturnal hypoglycemia were associated with slower next day processing speed. This association was not significantly attenuated by negative affect, sleepiness, or sleep quality.

CONCLUSIONS

 These results, while preliminary due to small sample size, showcase the power of intensive longitudinal designs using ambulatory cognitive assessment to uncover novel determinants of cognitive fluctuation in real world settings, an approach that may be utilized in other populations. Findings suggest reducing nocturnal hypoglycemia may improve cognition in adults with T1D.

Impact of irregular sleep pattern, and sleep quality on glycaemic parameters and endothelial function in adolescents and young adults with type 1 diabetes

This study investigated the impact of comprehensive sleep patterns on glycaemic parameters and endothelial function in adolescents and young adults with type 1 diabetes (T1D). Thirty subjects with type 1 diabetes (aged 13-25) without chronic complications participated. For 1 week, glucose levels were monitored by real-time continuous glucose monitoring (CGM) and sleep was simultaneously assessed by actigraphy. Subjective sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). Flow-mediated dilatation (FMD) measured endothelial function at the brachial artery. Insulin sensitivity was determined by calculated estimated glucose disposal rate (eGDR). Glycaemic control was assessed using haemoglobin A1C (HbA1C) levels. To address potential confounding by metabolic syndrome on the FMD results, three affected subjects were excluded from FMD correlation analyses. Participants with PSQI scores >5 had a lower %FMD compared with those with scores ≤5 (4.6 ± 3.7% vs. 7.6 ± 3.0%, p = 0.03). Multivariate analysis indicated that lower sleep efficiency and higher sleep duration variability were associated with higher HbA1C levels (β = -0.076, 95%CI [-0.145, -0.008], p = 0.029; β = 0.012, 95%CI [0.001, 0.023], p = 0.033). Irregular sleep timing and lower sleep efficiency were related to decreased insulin sensitivity (sleep midpoint irregularity β = -1.581, 95%CI [-2.661, -0.502], p = 0.004, and sleep efficiency β = 0.147, 95%CI [0.060, 0.235], p = 0.001). No significant associations were found between glycaemic parameters and FMD. Our study demonstrated that sleep irregularity in type 1 diabetes was associated with glycaemic control and insulin resistance, while poor subjective sleep quality was linked to endothelial dysfunction. Promoting healthy sleep habits, including consistent sleep timing could benefit metabolic and cardiovascular health in type 1 diabetes.

Glucose variability and mood in people with type 1 diabetes using ecological momentary assessment

OBJECTIVE

Mood fluctuations related to blood glucose excursions are a commonly reported source of diabetes-distress, but research is scarce. We aimed to assess the relationship between real-time glucose variability and mood in adults with type 1 diabetes (T1D) using ecological momentary assessments.

METHODS

In this prospective observational study, participants wore a masked continuous glucose monitor and received prompts on their smartphone 6 times a day to answer questions about their current mood (Profile Of Mood States (POMS)-SF (dimensions: Anxiety, Depressive symptoms, Anger, Fatigue, Vigor)) for 14 days. Mixed model analyses examined associations over time between daily Coefficient of Variation (CV) of blood glucose and mean and variability (CV) of POMS scores. Further, within-person differences in sleep and nocturnal hypoglycemia were explored.

RESULTS

18 people with T1D (10 female, mean age 44.3 years) participated. A total of 264 out of 367 days (70.2%) could be included in the analyses. No overall significant associations were found between CV of blood glucose and mean and CV of POMS scores, however, nocturnal hypoglycemia moderated the associations between CV of blood glucose and POMS scales (mean Fatigue Estimate 1.998, p < .006, mean Vigor Estimate -3.308, p < .001; CV Anger Estimate 0.731p = 0.02, CV Vigor Estimate -0.525, p = .006).

CONCLUSION

We found no overall relationship between real-time glycemic variability and mood per day. Further research into within-person differences such as sleep and nocturnal hypoglycemia is warranted.

Objective sleep characteristics and continuous glucose monitoring profiles of type 2 diabetes patients in real-life settings

AIM

To investigate the association between objective sleep parameters and glycaemic variability determined by continous glucose monitoring (CGM) among patients with type 2 diabetes, given the significant role of sleep in glycaemic control.

METHODS

In this study, CGM was carried out in 28 patients with T2D (aged 62.3 ± 4.8 years, 57% women). Sleep characteristics were assessed by actigraphy within the CGM period. CGM-derived outcomes included glucose level, and percentages of time in range (TIR) and time above range (TAR) during the monitoring period. Associations between intraindividual night-to-night variations in sleep characteristics and overall CGM outcomes were analysed using linear regression. Associations between sleep characteristics during each night and time-matched CGM outcomes were analysed using linear mixed models.

RESULTS

A total of 249 person-days of CGM, coupled with 221 nights of sleep characteristics, were documented. Greater standard deviation (SD) of objective sleep duration (minutes) between measurement nights was associated with higher glucose level (coefficient 0.018 mmol/L [95% confidence interval {CI} 0.004, 0.033], P = 0.017), smaller proportion of TIR (% in observation period; coefficient -0.20% [95% CI -0.36, -0.03], P = 0.023), and greater proportion of TAR (coefficient 0.22% [95% CI 0.06, 0.39], P = 0.011). Later sleep midpoint (minutes from midnight) was associated with greater SD of glucose during the same sleep period (coefficient 0.002 minutes [95% CI 0.0001, 0.003], P = 0.037), longer nocturnal sleep duration was associated with smaller coefficient of variation of glucose level in the upcoming day (-0.015% [95% CI -0.03, -0.001], P = 0.041).

CONCLUSION

Objectively determined sleep duration and sleep midpoint, as well as their daily variability, are associated with CGM-derived glucose profiles in T2D patients.

Cognitive Behavioral Sleep Self-Management Intervention for Young Adults With Type 1 Diabetes (NCT04975230)

The purpose of this study was to explore perceptions of the first dose of a cognitive behavioral sleep self-management intervention (CB-sleep) among young adults aged 18 to 25 years with type 1 diabetes (T1D). We used a qualitative descriptive approach to conduct in-depth semi-structured focused interviews with a purposive sample of 16 young adults with T1D, transitioning from adolescence to early adulthood. Interviews were audio-recorded, transcribed verbatim, and analyzed using qualitative content analysis. Participants described their sleep knowledge (previous, new, and additional), sleep health goals, along with barriers and facilitators of the CB-sleep intervention. Based on these results, we suggest CB-sleep is a useful modality with the potential to support sleep self-management in young adults with T1D during this complex life transition. Furthermore, CB-sleep could be incorporated into an existing diabetes self-management education and support program after pilot testing and determining efficacy to improve sleep and glycemic health.

A multimeal paradigm producing a low glycemic response is associated with modest cognitive benefits relative to a high glycemic response: a randomized, crossover trial in patients with type 2 diabetes

BACKGROUND

Type 2 diabetes (T2DM) and poor glucose regulation in the immediate postprandial period are both associated with impairments in cognitive function. There is evidence that foods that generate a better postprandial glycemic response, such as low GI foods (which produce a lower glycemic peak, less variability, and a more sustained decline), are associated with cognitive benefits over the morning. However, the potential impact of consuming multiple meals of this nature over the course of a day on cognition in T2DM has not been explored.

OBJECTIVES

The primary aim of this research was to investigate whether a multimeal paradigm producing a low glycemic response was associated with cognitive benefits in patients with noninsulin-dependent T2DM relative to a multimeal paradigm producing a high glycemic response.

METHODS

Twenty-five adults with noninsulin-dependent T2DM (mean age: 57 y) consumed 2 multimeal profiles consisting of a breakfast, lunch, and afternoon snack on 2 separate test days following a randomized, counterbalanced, crossover design. The 2 conditions were a low GI profile (LGIP) and a high GI profile (HGIP).

RESULTS

Cognitive function, glycemic response, mood, and satiety were assessed over the day from 8:30 to 17:00. Overall, there were limited cognitive effects. However, there was evidence for cognitive benefits in the period before lunch, as demonstrated by better global cognitive and executive functions for the LGIP relative to the HGIP. No clear effects were observed for mood.

CONCLUSIONS

This study shows that a multimeal paradigm producing a low glycemic response was associated with some benefits for cognitive function in patients with T2DM.

CLINICAL TRAIL REGISTRY REFERENCE

NCT03360604 (clinical trial.gov).

Transition From Pediatric to Adult Care for Individuals With Type 1 Diabetes: Opportunities and Challenges

OBJECTIVES

Type 1 diabetes (T1D) is a chronic disease with patients across the age spectrum that has high potential for morbidity and mortality. Unfortunately, patients transitioning from pediatric to adult care continue to demonstrate worsened glycemic control in part due to lack of understanding of transition of care best practices.

METHODS

This review highlights the impact of existing transition of care interventions, assessment tools, and other recently published strategies for providers to consider to improve care of adolescent and young adult (AYA) patients with T1D in both hospital- and clinic-based settings.

RESULTS

Many barriers impact patients with T1D during the transition period and disparities by race, sex, insurance status, and comorbid illness persist. As diabetic care continues to evolve and the prevalence of adolescents and young adults living with T1D increases, an intentional approach to transition of care is more pressing than ever. While current literature on transition of care models is limited, many show promise in improving clinic attendance and decreasing hospitalization. There are critical discussions that providers should lead with AYA patients to improve their outcomes and increase diabetes self-management, such as re-addressing carbohydrate counseling, sleep hygiene, and reproductive planning.

CONCLUSION

While further research on transition of care is needed, many care models offer the promise of improved T1D outcomes, enhancements in our approach to care, and increased value for our health care system at large.

Associations between sleep variability and cardiometabolic health: A systematic review

This review explored the associations between sleep variability and cardiometabolic health. It was performed following PRISMA guidelines. We identified 63 studies. Forty-one studies examined the association between sleep variability and body composition, with 29 examined body mass index (BMI). Thirteen studies used social jet lag (SJL), n = 30,519, with nine reporting a null association. Eight studies used variability in sleep duration (n = 33,029), with five reporting a correlation with BMI. Fourteen studies (n = 133,403) focused on overweight/obesity; significant associations with sleep variability were found in 11 (n = 120,168). Sleep variability was associated with weight gain (seven studies; n = 79,522). Twenty-three studies examined glucose outcomes. The association with hemoglobin A1c (16 studies, n = 11,755) differed depending on populations, while associations with diabetes or glucose were mixed, and none were seen with insulin resistance (five studies; n = 6416). Sixteen studies examined cardiovascular-related outcomes, with inconsistent results. Overall significant associations were found in five studies focusing on metabolic syndrome (n = 7413). In summary, sleep variability was likely associated with obesity, weight gain, and metabolic syndrome. It might be associated with hemoglobin A1c in people with type 1 diabetes. The associations with other outcomes were mixed. This review highlighted the possible association between sleep variability and cardiometabolic health.

A composite measure of sleep health is associated with glycaemic target achievement in young adults with type 1 diabetes

We investigated whether sleep health (each individual dimension and a composite measure) was associated with better glycaemia among a cohort of young adults with type 1 diabetes (mean age 21.5 years, mean body mass index 24.55 kg m^-2 ). Multiple validated self-report questionnaires were completed, and raw continuous glucose monitor data were shared. One self-reported sleep characteristic for each of the five sleep health dimensions was selected. A composite score was calculated by summing the number of "good" sleep health dimensions. We evaluated the associations between sleep health and glycaemia, and whether covariates, including age, type 1 diabetes duration and sleep apnea risk, influenced the relationships among the study variables using multivariable linear regression. Individual dimensions of sleep satisfaction (β = 0.380, p = 0.019; β = -0.414, p = 0.010), timing (β = 0.392, p = 0.015; β = -0.393, p = 0.015) and sleep efficiency (β = 0.428, p = 0.007) were associated with higher achievement of glycaemic targets (J-index and time in range); however, these associations did not persist after considering covariates. A better Sleep Health Composite score was associated with higher achievement of glycaemic targets even after considering covariates. Using a multidimensional framework can guide future research on causal pathways between sleep and diabetes health, interventions to target sleep health profiles, and may improve sleep screening in routine diabetes care.

Sex Differences in Depression and Sleep Disturbance as Inter-Related Risk Factors of Diabetes

Objectives

Previous studies identified depression and sleep disturbance as risk factors for diabetes. Sleep disturbance and depression are known to be inter-related. Further, women relative to men are more prone to depression. Here, we investigated how depression and sleep disturbance may jointly influence the risk of diabetes and the effects of sex on these influences.

Methods

Using the data of 21,229 participants from the 2018 National Health Interview Survey, we performed multivariate logistic regression with diabetes diagnosis as the dependent variable, sex, self-reported frequency of weekly depression and nightly sleep duration, and their interactions with sex as independent variables, and age, race, income, body mass index and physical activity as covariates. We employed Bayesian and Akaike Information criteria to identify the best model, evaluated the accuracy of the model in predicting diabetes using receiver operating characteristic analysis, and computed the odds ratios of these risk factors.

Results

In the two best models, depression frequency and sleep hours interact with sex in determining the diagnosis of diabetes, with higher depression frequency and nightly duration of sleep longer or shorter than 7 to 8 hours associated with higher likelihood of diabetes. The two models both predicted diabetes at an accuracy (area under the receiver operating characteristic curve) of 0.86. Further, these effects were stronger in men than in women at each depression and sleep level.

Conclusions

Depression and sleep inter-relatedly rather than independently contributes to diabetes. Depression and sleep hours associate with diabetes more significantly in men than in women. The current findings indicate a sex-dependent relationship between depression, sleep disturbance and diabetes risk and add to a growing body of evidence linking mental and physical health.

Objective Sleep-Wake Characteristics Are Associated With Diabetes Symptoms in Young Adults With Type 1 Diabetes

PURPOSE

The primary purpose of this descriptive cross-sectional study was to examine the associations between sleep-wake characteristics (total sleep time, sleep variability, sleep onset latency, and sleep efficiency), distress symptoms (general and diabetes), and diabetes physical symptoms in young adults ages 18 to 30 years with type 1 diabetes (T1D). The secondary purpose was to determine whether biological sex, body mass index (BMI), and T1D duration (covariates) influence the relationships among the study variables.

METHODS

Forty-six young adults with T1D, recruited from diabetes clinics from December 2018 to February 2020, wore a wrist actigraph and continuous glucose monitor concurrently for 6 to 14 days and completed the PROMIS Emotional Distress Scale, Diabetes Distress Scale, and Diabetes Symptom Checklist-Revised.

RESULTS

Shorter total sleep time and poorer sleep efficiency were associated with higher diabetes emotional distress symptoms. Higher sleep variability was associated with higher neurological pain symptoms. A longer sleep onset latency was associated with higher symptoms of diabetes distress, including psychological, cognitive, hyperglycemia, and a higher total symptom burden. Associations remained statistically significant after adjusting for biological sex and BMI, with the exception of sleep onset latency and total symptom burden.

CONCLUSIONS

Poorer objective sleep-wake characteristics were associated with higher diabetes symptoms even after considering biological sex and BMI among young adults with T1D.

Glucose and unstructured physical activity coupling during sleep and wake in young adults with type 1 diabetes

Glucose variations have a bidirectional relationship with the sleep/wake and circadian systems in type 1 diabetes (T1D); however, the mechanisms remain unclear. The aim of this study was to describe the coupling between glucose and unstructured physical activity over 168 h in young adults with T1D. We hypothesized that there would be differences in sleep and wake characteristics and circadian variations. Glucose was measured with a continuous glucose monitoring device every 5 min and activity with a non-dominant wrist-worn actigraph in 30-s epochs over 6–14 days. There was substantial glucose and unstructured physical activity coupling during sleep and wake, along with circadian variation based on the wavelet coherence analysis. The extent to which glucose fluctuations result in disrupted sleep over longer than one week should be examined considering the harmful effects on achieving glycemic targets. Further studies are needed to delineate the respective roles of glucose production and utilization and the potential for improved meal and insulin timing to optimize glucose and sleep in this population reliant on exogenous insulin.

Variations in Sleep Characteristics and Glucose Regulation in Young Adults With Type 1 Diabetes

CONTEXT

Short sleep duration and sleep disruptions are associated with impaired glucoregulation in type 1 diabetes (T1D). However, the mechanistic pathways between sleep and glucose variability remain unclear.

OBJECTIVE

To determine within- and between-person associations between objective sleep-wake characteristics and glucose variability indices.

METHODS

Multilevel models were used to analyze concurrent sleep and glucose patterns over 7 days in 42 young adults with T1D in their natural home environment. Young adults with T1D (mean age 22.2 ± 3.0 years, HbA1c 7.2%, 32.6% male) for at least 6 months with no other medical or major psychiatric comorbidity were included. Sleep-wake characteristics were measured via wrist actigraphy and glucose variability indices via a continuous glucose monitor (CGM).

RESULTS

Lower sleep efficiency predicted higher glucose variability (less time in range β = 0.011 and more time in hyperglycemia β = -0.011) within-person. A longer wake after sleep onset and more sleep disruptions were associated with higher glucose variability between persons (β = 0.28 and 0.31). Higher glucose variability predicted poorer sleep within-person (delayed bedtime, waketime, mid-sleep time, and lower sleep efficiency), while higher glucose variability was associated with poorer sleep and more sleep disruptions between persons (lower sleep efficiency, longer wake after sleep onset, and a higher sleep fragmentation index).

CONCLUSION

Clinicians can address the reciprocal nature of the sleep-glucose relationship by optimizing sleep and targeting efforts toward a euglycemic range overnight. Sleep habits are a modifiable personal target in diabetes care.

Too Much Dietary Flexibility May Hinder, Not Help: Could More Specific Targets for Daily Food Intake Distribution Promote Glycemic Management among Youth with Type 1 Diabetes?

Average glycemic levels among youth with type 1 diabetes (T1D) have worsened in some parts of the world over the past decade despite simultaneous increased uptake of diabetes technology, thereby highlighting the persistent need to identify effective behavioral strategies to manage glycemia during this life stage. Nutrition is fundamental to T1D management. We reviewed the evidence base of eating strategies tested to date to improve glycemic levels among youth with T1D in order to identify promising directions for future research. No eating strategy tested among youth with T1D since the advent of flexible insulin regimens—including widely promoted carbohydrate counting and low glycemic index strategies—is robustly supported by the existing evidence base, which is characterized by few prospective studies, small study sample sizes, and lack of replication of results due to marked differences in study design or eating strategy tested. Further, focus on macronutrients or food groups without consideration of food intake distribution throughout the day or day-to-day consistency may partially underlie the lack of glycemic benefits observed in studies to date. Increased attention paid to these factors by future observational and experimental studies may facilitate identification of behavioral targets that increase glycemic predictability and management among youth with T1D.

Circadian characteristics of the rest-activity rhythm, executive function, and glucose fluctuations in young adults with type 1 diabetes

Circadian alignment is an important element in individual health, and one behavioral marker, rest-activity rhythm, could influence self-management in young adults with type 1 diabetes (T1D). Little is known about the rest-activity rhythms, executive function, and glycemia among young adults with type 1 diabetes (T1D). The purpose of this study was to evaluate parametric and nonparametric circadian characteristics of the rest-activity rhythm and the associations between these variables, sleep-wake behavior, executive function, and glycemia among young adults with T1D. Young adults with T1D, recruited from diabetes clinics, wore wrist actigraphs and a continuous glucose monitor (CGM) concurrently for 6-14 days. Participants completed a 3-minute Trail Making Test on paper and electronic questionnaires - 8-item PROMIS v1.0 Emotional Distress Scale, 17-item Diabetes Distress Scale, including twice-daily Pittsburgh sleep diaries. Cosinor and nonparametric analyses were used to compute the rest-activity rhythm parameters, and linear regression modeling procedures were performed to determine the associations among the study variables. The sample included 46 young adults (mean age 22.3 ± 3.2; 32.6% male; 84.8% non-Hispanic White, HbA1c mean 7.2 ± 1.1%, BMI mean 27.0 ± 4.4 kg/m²). A number of parametric associations were observed between a stronger rhythm, better objective sleep-wake characteristics, and less daytime sleepiness. Nonparametric circadian parameters were significantly associated with several outcomes: a stronger rhythm adherence (higher inter-daily stability) with better objective sleep-wake characteristics, better executive function, lower diabetes distress, less hyperglycemia risk, and more time spent in hypoglycemia/hypoglycemia risk; and a more robust rhythm (higher relative amplitude) with better objective sleep-wake characteristics and more time spent in hypoglycemia/higher hypoglycemia risk. Future work should be directed at designs that test causality, such as interventions directed at the strength and stability of rest-activity rhythms, for the potential to improve glucoregulation and other diabetes outcomes.