Impact of sleep behavior on glycemic control in type 1 diabetes: the role of social jetlag

Association Between Social Jetlag and Components of Metabolic Syndrome: A Systematic Review and Meta-Analysis

BACKGROUND

A mismatch between biological and social time, often referred to as social jetlag (SJL), can lead to inadequate sleep and activities or taking meals at times that do not align with our biological rhythms, increasing the risk of metabolic abnormalities. Although the association between sleep and metabolic syndrome (MetS) is well established, the effects of SJL on MetS and the components of MetS in adults remain unclear.

PURPOSE

This study was designed to explore the relationship between SJL and MetS components in adults.

METHODS

A systematic review and meta-analysis was conducted on studies registered in PubMed, Cochrane, Web of Science, and Embase between the inception of each database until November 15, 2023. We focused on studies designed to evaluate the relationship between SJL and either MetS or its components. Only studies using cross-sectional, prospective, or retrospective designs were considered for inclusion. The relationship between SJL and MetS was depicted as an odds ratio with a corresponding 95% confidence interval (CI). We determined the mean differences and 95% CIs to estimate the associations between SJL and MetS components. The Joanna Briggs Institute Critical Appraisal Checklist was used to evaluate the methodological rigor of the selected studies. Data were analyzed using RevMan software Version 5.4.

RESULTS

The systematic review included 16 studies, with five analyzed via a meta-analysis covering four outcomes, each based on two to three studies. When comparing SJL of less than 1 hour with SJL of 2 hours or more, the latter showed a higher likelihood of MetS (pooled odds ratio: 1.52). Although a significant decrease in systolic blood pressure (pooled mean differences = -3.52 mmHg, 95% CI [-6.41, -0.64]) and a significant increase in waist circumference (pooled mean differences = 2.17 cm, 95% CI [0.61, 3.73]) were observed, the correlation between SJL and diastolic blood pressure failed to reach statistical significance.

CONCLUSIONS/IMPLICATIONS FOR PRACTICE

The meta-analysis conducted in this study found an association between SJL and MetS. Healthcare practitioners should prioritize the management of sleep quality and duration, especially for individuals exhibiting substantial SJL. Improving sleep can aid in controlling blood pressure and managing weight and should form part of MetS management strategies.

Circadian dysfunction and cardio-metabolic disorders in humans

The topic of human circadian rhythms is not only attracting the attention of clinical researchers from various fields but also sparking a growing public interest. The circadian system comprises the central clock, located in the suprachiasmatic nucleus of the hypothalamus, and the peripheral clocks in various tissues that are interconnected; together they coordinate many daily activities, including sleep and wakefulness, physical activity, food intake, glucose sensitivity and cardiovascular functions. Disruption of circadian regulation seems to be associated with metabolic disorders (particularly impaired glucose tolerance) and cardiovascular disease. Previous clinical trials revealed that disturbance of the circadian system, specifically due to shift work, is associated with an increased risk of type 2 diabetes mellitus. This review is intended to provide clinicians who wish to implement knowledge of circadian disruption in diagnosis and strategies to avoid cardio-metabolic disease with a general overview of this topic.

Social jet lag impairs exercise volume and attenuates physiological and metabolic adaptations to voluntary exercise training

Social jet lag (SJL) is a misalignment between sleep and wake times on workdays and free days. SJL leads to chronic circadian rhythm disruption and may affect nearly 70% of the general population, leading to increased risk for cardiometabolic diseases. This study investigated the effects of SJL on metabolic health, exercise performance, and exercise-induced skeletal muscle adaptations in mice. Ten-week-old C57BL/6J mice (n = 40) were allocated to four groups: control sedentary (CON-SED), control exercise (CON-EX), social jet lag sedentary (SJL-SED), and social jet lag exercise (SJL-EX). CON mice were housed under a 12:12-h light-dark cycle. SJL was simulated by implementing a 4-h phase delay for 3 days to simulate "weekends," followed by a 4-h phase advance back to "weekdays," for 6 wk. EX mice had free access to a running wheel. Graded exercise tests (GXTs) and glucose tolerance tests (GTTs) were performed at baseline and after intervention to monitor the effects of exercise and social jet lag on cardiorespiratory and metabolic health, respectively. SJL led to alterations in activity and running patterns and clock gene expression in skeletal muscle and decreased average running distance (P < 0.05). SJL-SED mice gained significantly more weight compared with CON-SED and SJL-EX mice (P < 0.01). SJL impaired fasting blood glucose and glucose tolerance compared with CON mice (P < 0.05), which was partially restored by exercise in SJL-EX mice. SJL also blunted improvements in exercise performance and mitochondrial content in the quadriceps. These data suggest that SJL blunted some cardiometabolic adaptations to exercise and that proper circadian hygiene is necessary for maintaining health and performance.NEW & NOTEWORTHY In mice, disrupting circadian rhythms with social jet lag for 6 wk caused significant weight gain, higher fasting blood glucose, and impaired glucose tolerance compared with control. Voluntary exercise in mice experiencing social jet lag prevented weight gain, though the mice still experienced increased fasting blood glucose and impaired exercise performance compared with trained mice not experiencing social jet lag. Social jet lag seems to be a potent circadian rhythm disruptor that impacts exercise-induced training adaptations.

Lifestyle in Emerging Adults with Type 1 Diabetes Mellitus: A Qualitative Systematic Review

Emerging adulthood is a transitional stage with significant lifestyle changes, making it especially challenging for those living with type 1 diabetes mellitus. This systematic review synthesizes qualitative research to explore how emerging adulthood (18-29 years) influences lifestyle behaviors in individuals with type 1 diabetes mellitus. CINAHL, Cochrane Library, Global Health, Nursing & Allied Health Premium, PsycINFO, PubMed, Scopus, and WOS were searched for original qualitative studies addressing the lifestyle of 18-31-year-olds with type 1 diabetes mellitus, published between January 2010 and March 2021 following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Thirty-five studies met the inclusion criteria and their findings were categorized into eight topics (emotions and feelings, nutrition, perceptions, risky behaviors, self-care, sleep, social relationships, and stigma) using meta-aggregation, as outlined in the Joanna Briggs Institute Manual for Evidence Synthesis. The spontaneity characteristic of emerging adulthood can undermine self-care. This is because new environments, schedules, and relationships encountered during this life stage often lead to the neglect of diabetes management, owing to the various social, academic, and occupational demands. This review highlights the necessity of creating health promotion strategies tailored to the unique lifestyle aspects of emerging adults with type 1 diabetes mellitus.

Behavioural Parameters of Circadian Rhythm Are Not Correlated with Dim Light Melatonin Onset: An Observational Study on Healthy Volunteers

Dim light melatonin onset (DLMO) is considered the most reliable marker of the circadian rhythm phase in humans. DLMO may moderately correlate with sleep onset and sleep offset time. There are no sufficient data about the correlations between DLMO and clinical scales assessing sleep quality and daytime symptoms of poor night sleep. The aim of the study was to determine the association between DLMO and basic sleep parameters from actigraphy and sleep diaries, as well as the association between DLMO and the following insomnia clinical scales: the Athens Insomnia Scale (AIS), Insomnia Severity Index (ISI), Epworth Sleepiness Scale (ESS), and chronotype questionnaires: Morningness-Eveningness Questionnaire (MEQ) and Composite Scale of Morningness (CSM). Participants of the study were healthy volunteers. Sleep parameters were measured by sleep diaries and actigraphy, and the following clinical scales: the AIS, ISI, and ESS, and chronotype questionnaires: MEQ and CSM. DLMO was calculated based on plasma melatonin concentration. The blood samples were collected hourly at five time points between 20:00 and 00:00 during the session in dim red light (<50 lux). Melatonin concertation was determined by LC-MS/MS. Twenty-one volunteers participated in the study. DLMO was calculated in 12 participants. There was a significant correlation between DLMO and ISI (r = 0.60, p = 0.038) and ESS (r = 0.61, p = 0.034). The correlation coefficient between the DLMO and the AIS was also high, however insignificant (r = 0.57, p = 0.054). There were no significant correlations between DLMO and chronotype scales MEQ and CSM. DLMO did not correlate with sleep onset and sleep offset; however, DLMO correlated with the Sleep Fragmentation Index (SFI) (r = 0.67, p = 0.017). DLMO is associated with poorer sleep maintenance, a stronger feeling of insomnia, and sleepiness during the day. Simultaneously, chronotype pattern and circadian rhythm parameters do not correlate with DLMO. Biological circadian rhythm does not reflect the real-life sleep-wake rhythm, indicating that the lifestyle is more often disconnected from the biological clock.

Association between sleep variability and time in range of glucose levels in patients with type 1 diabetes: Cross-sectional study

OBJECTIVE

Sleep and circadian disturbances emerge as novel factors influencing glycemic control in type 1 diabetes (T1D). We aimed to explore the associations among sleep, behavioral circadian parameters, self-care, and glycemic parameters in T1D.

METHODS

Seventy-six non-shift-working adult T1D patients participated. Blinded 7-day continuous glucose monitoring (CGM) and hemoglobin A1C (A1C) were collected. Percentages of time-in-range (glucose levels 70-180 mg/dL) and glycemic variability (measured by the coefficient of variation [%CV]) were calculated from CGM. Sleep (duration and efficiency) was recorded using 7-day actigraphy. Variability (standard deviation) of midsleep time was used to represent sleep variability. Nonparametric behavioral circadian variables were derived from actigraphy activity recordings. Self-care was measured by diabetes self-management questionnaire-revised. Multiple regression analyses were performed to identify independent predictors of glycemic parameters.

RESULTS

Median (interquartile range) age was 34.0 (27.2, 43.1) years, 48 (63.2%) were female, and median (interquartile range) A1C was 6.8% (6.2, 7.4). Sleep duration, efficiency, and nonparametric behavioral circadian variables were not associated with glycemic parameters. After adjusting for age, sex, insulin delivery mode/CGM use, and ethnicity, each hour increase in sleep variability was associated with 9.64% less time-in-range (B = -9.64, 95% confidence interval [-16.29, -2.99], p ≤ .001). A higher diabetes self-management questionnaire score was an independent predictor of lower A1C (B = -0.18, 95% confidence interval [-0.32, -0.04]).

CONCLUSION

Greater sleep timing variability is independently associated with less time spent in the desirable glucose range in this T1D cohort. Reducing sleep timing variability could potentially lead to improved metabolic control and should be explored in future research.

DATA AVAILABILITY STATEMENT

Data are available upon a reasonable request to the corresponding author.

Archaic Introgression Shaped Human Circadian Traits

When the ancestors of modern Eurasians migrated out of Africa and interbred with Eurasian archaic hominins, namely, Neanderthals and Denisovans, DNA of archaic ancestry integrated into the genomes of anatomically modern humans. This process potentially accelerated adaptation to Eurasian environmental factors, including reduced ultraviolet radiation and increased variation in seasonal dynamics. However, whether these groups differed substantially in circadian biology and whether archaic introgression adaptively contributed to human chronotypes remain unknown. Here, we traced the evolution of chronotype based on genomes from archaic hominins and present-day humans. First, we inferred differences in circadian gene sequences, splicing, and regulation between archaic hominins and modern humans. We identified 28 circadian genes containing variants with potential to alter splicing in archaics (e.g., CLOCK, PER2, RORB, and RORC) and 16 circadian genes likely divergently regulated between present-day humans and archaic hominins, including RORA. These differences suggest the potential for introgression to modify circadian gene expression. Testing this hypothesis, we found that introgressed variants are enriched among expression quantitative trait loci for circadian genes. Supporting the functional relevance of these regulatory effects, we found that many introgressed alleles have associations with chronotype. Strikingly, the strongest introgressed effects on chronotype increase morningness, consistent with adaptations to high latitude in other species. Finally, we identified several circadian loci with evidence of adaptive introgression or latitudinal clines in allele frequency. These findings identify differences in circadian gene regulation between modern humans and archaic hominins and support the contribution of introgression via coordinated effects on variation in human chronotype.

Exploring the relationship between social jetlag with gut microbial composition, diet and cardiometabolic health, in the ZOE PREDICT 1 cohort

PURPOSE

In this study, we explore the relationship between social jetlag (SJL), a parameter of circadian misalignment, and gut microbial composition, diet and cardiometabolic health in the ZOE PREDICT 1 cohort (NCT03479866).

METHODS

We assessed demographic, diet, cardiometabolic, stool metagenomics and postprandial metabolic measures (n = 1002). We used self-reported habitual sleep (n = 934) to calculate SJL (difference in mid-sleep time point of ≥ 1.5 h on week versus weekend days). We tested group differences (SJL vs no-SJL) in cardiometabolic markers and diet (ANCOVA) adjusting for sex, age, BMI, ethnicity, and socio-economic status. We performed comparisons of gut microbial composition using machine learning and association analyses on the species level genome bins present in at least 20% of the samples.

RESULTS

The SJL group (16%, n = 145) had a greater proportion of males (39% vs 25%), shorter sleepers (average sleep < 7 h; 5% vs 3%), and were younger (38.4 ± 11.3y vs 46.8 ± 11.7y) compared to the no-SJL group. SJL was associated with a higher relative abundance of 9 gut bacteria and lower abundance of 8 gut bacteria (q < 0.2 and absolute Cohen's effect size > 0.2), in part mediated by diet. SJL was associated with unfavourable diet quality (less healthful Plant-based Diet Index), higher intakes of potatoes and sugar-sweetened beverages, and lower intakes of fruits, and nuts, and slightly higher markers of inflammation (GlycA and IL-6) compared with no-SJL (P < 0.05 adjusted for covariates); rendered non-significant after multiple testing adjustments.

CONCLUSIONS

Novel associations between SJL and a more disadvantageous gut microbiome in a cohort of predominantly adequate sleepers highlight the potential implications of SJL for health.

Archaic Introgression Shaped Human Circadian Traits

Introduction

When the ancestors of modern Eurasians migrated out of Africa and interbred with Eurasian archaic hominins, namely Neanderthals and Denisovans, DNA of archaic ancestry integrated into the genomes of anatomically modern humans. This process potentially accelerated adaptation to Eurasian environmental factors, including reduced ultra-violet radiation and increased variation in seasonal dynamics. However, whether these groups differed substantially in circadian biology, and whether archaic introgression adaptively contributed to human chronotypes remains unknown.

Results

Here we traced the evolution of chronotype based on genomes from archaic hominins and present-day humans. First, we inferred differences in circadian gene sequences, splicing, and regulation between archaic hominins and modern humans. We identified 28 circadian genes containing variants with potential to alter splicing in archaics (e.g., CLOCK, PER2, RORB, RORC), and 16 circadian genes likely divergently regulated between present-day humans and archaic hominins, including RORA. These differences suggest the potential for introgression to modify circadian gene expression. Testing this hypothesis, we found that introgressed variants are enriched among eQTLs for circadian genes. Supporting the functional relevance of these regulatory effects, we found that many introgressed alleles have associations with chronotype. Strikingly, the strongest introgressed effects on chronotype increase morningness, consistent with adaptations to high latitude in other species. Finally, we identified several circadian loci with evidence of adaptive introgression or latitudinal clines in allele frequency.

Conclusions

These findings identify differences in circadian gene regulation between modern humans and archaic hominins and support the contribution of introgression via coordinated effects on variation in human chronotype.

Sleep health dimensions are associated with next-day symptoms in young adults with type 1 diabetes

OBJECTIVE

We investigated intra-individual reciprocal associations between sleep health dimensions (individual and composite) and symptoms among young adults with type 1 diabetes (T1D).

DESIGN AND MEASUREMENTS

Cross-lagged multilevel models were used to analyze electronic diary-reported sleep and symptom patterns over 7 days at waketime in 42 young adults with T1D. Sleep health dimensions included regularity, satisfaction, alertness, timing, efficiency (percentage of time spent asleep), and duration (total sleep time) and symptoms included mood, fatigue, and pain. Covariates included biological sex and age.

SETTING AND PARTICIPANTS

We recruited young adults (mean age 21.5 ± 2.1 years, HbA1c 6.8%, 85% female, 10% gender minority) with T1D for at least 6 months and no other major medical or psychiatric comorbidity from social media platforms, the College Diabetes Network, and ResearchMatch.

RESULTS

On days with a better sleep health composite, participants reported lower next-day symptoms (higher mood, lower fatigue, and lower pain) and on days when participants reported lower symptoms, participants reported better sleep health (as a composite). Several individual sleep health dimensions led to lower next-day symptoms (eg, higher satisfaction, alertness, and efficiency and higher mood); however, symptoms were no longer predictive of next-day sleep when controlling for prior day sleep.

CONCLUSIONS

Optimal sleep health is an antecedent of fewer next day symptoms. Sleep health dimensions likely have positive additive effects on lower symptoms as some of the individual sleep health dimensions were not significantly associated with some symptoms among young adults with T1D.

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.

Is obstructive sleep apnea a circadian rhythm disorder?

Obstructive sleep apnea is the most common sleep-related breathing disorder worldwide and remains underdiagnosed. Its multiple associated comorbidities contribute to a decreased quality of life and work performance as well as an increased risk of death. Standard treatment seems to have limited effects on cardiovascular and metabolic aspects of the disease, emphasising the need for early diagnosis and additional therapeutic approaches. Recent evidence suggests that the dysregulation of circadian rhythms, processes with endogenous rhythmicity that are adjusted to the environment through various cues, is involved in the pathogenesis of comorbidities. In patients with obstructive sleep apnea, altered circadian gene expression patterns have been demonstrated. Obstructive respiratory events may promote circadian dysregulation through the effects of sleep disturbance and intermittent hypoxia, with subsequent inflammation and disruption of neural and hormonal homeostasis. In this review, current knowledge on obstructive sleep apnea, circadian rhythm regulation, and circadian rhythm sleep disorders is summarised. Studies that connect obstructive sleep apnea to circadian rhythm abnormalities are critically evaluated. Furthermore, pathogenetic mechanisms that may underlie this association, most notably hypoxia signalling, are presented. A bidirectional relationship between obstructive sleep apnea and circadian rhythm dysregulation is proposed. Approaching obstructive sleep apnea as a circadian rhythm disorder may prove beneficial for the development of new, personalised diagnostic, therapeutic and prognostic tools. However, further studies are needed before the clinical approach to obstructive sleep apnea includes targeting the circadian system.

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.

Is Being a Lark Healthier for Patients with Type 1 Diabetes Mellitus?

Background  Sleep quality and mood have been evaluated in type 1 diabetic (T1DM) patients, but chronotypes were not studied. Our objectives were to analyze chronotypes, sleep and mood variables and to describe their association with some metabolic variables in this population. Methods  An observational, cross-sectional study was performed. Adults with a diagnosis of T1DM were included. We evaluated chronotypes by the Morningness-Eveningness Questionnaires, sleep quality by Pittsburgh Sleep Quality Index (PSQI), excessive daytime sleepiness by Epworth Sleepiness Scale (ESS), symptoms of depression by Patient Health Questionnaire - 9 (PHQ-9) and emotional well-being by Emotional Well Being Index (IWHO-5). A few metabolic variables were included. Results  Ninety-five patients participated. The mean age was 38 years old (range 18-70). The average body mass index (BMI) was 24.4 Kg/m ² (standard deviation [SD]: 4.6). Out of the total sample, 52.6% were males. The Intermediate chronotype was predominant: n  = 56 (55%). We found poor quality of sleep in 67.4% of the sample, excessive daytime sleepiness in 14.7%, depressive symptoms in 6.3% by PHQ9 and low perception of well-being by IWHO-5 in 16.8%. Evening chronotype scored worse in sleep quality ( p  = 0.05) and had lower well-being ( p  = 0.03) compared with the other chronotypes. Higher MEQ values (morningness) correlated with lower height ( p  = 0.043), lower values in the PSQI ( p  = 0.021); and higher values in emotional well-being ( p  = 0.040). Conclusions  We found that the predominant chronotype in T1DM was the intermediate. Two-thirds reported poor quality of sleep and 14,7% excessive daytime sleepiness. Possible diagnosis of a depressive disorder in 6.3% and poor self-perception of emotional well-being in 16. 8% were observed. The morning chronotype had significant correlation with better sleep quality and higher scores in emotional well-being.

Evaluating the influence of sleep quality and quantity on glycemic control in adults with type 1 diabetes

BACKGROUND

Sleep quality disturbances are frequent in adults with type 1 diabetes. However, the possible influence of sleep problems on glycemic variability has yet to be studied in depth. This study aims to assess the influence of sleep quality on glycemic control.

MATERIALS AND METHODS

An observational study of 25 adults with type 1 diabetes, with simultaneous recording, for 14 days, of continuous glucose monitoring (Abbott FreeStyle Libre system) and a sleep study by wrist actigraphy (Fitbit Ionic device). The study analyzes, using artificial intelligence techniques, the relationship between the quality and structure of sleep with time in normo-, hypo-, and hyperglycemia ranges and with glycemic variability. The patients were also studied as a group, comparing patients with good and poor sleep quality.

RESULTS

A total of 243 days/nights were analyzed, of which 77% (n = 189) were categorized as poor quality and 33% (n = 54) as good quality. Linear regression methods were used to find a correlation (r =0.8) between the variability of sleep efficiency and the variability of mean blood glucose. With clustering techniques, patients were grouped according to their sleep structure (characterizing this structure by the number of transitions between the different sleep phases). These clusters showed a relationship between time in range and sleep structure.

CONCLUSIONS

This study suggests that poor sleep quality is associated with lower time in range and greater glycemic variability, so improving sleep quality in patients with type 1 diabetes could improve their glycemic control.

Extending sleep to improve glycemia: The Family Routines Enhancing Adolescent Diabetes by Optimizing Management (FREADOM) randomized clinical trial protocol

Sleep deficiencies amongst individuals with type 1 diabetes mellitus (T1DM) have been linked with dysregulated glycemic control and greater morbidities. Sleep extension (EXT) has been identified as a viable intervention target to improve adolescent outcomes. The intervention aims to emphasize collaborative work with families to engage in behaviors that increase the likelihood of the youth increasing their sleep duration consistently. This study will randomize up to 175 youth with T1DM and at least one caregiver to either an EXT intervention or a family routines support (FRS) consultation. It is hypothesized that the EXT condition will lead to improvements in sleep, which in turn, will contribute to improved glycemic control. The primary endpoint is improved glycemic control assessed via a continuous glucose monitor (CGM) to ascertain average glucose levels across a week, glycemic variability, and percent time in the target range at one month and HbA1c at three months. Analyses will control for co-morbid conditions, including sleep-disordered breathing and obesity. This study will provide the needed data to support addressing sleep as part of the standards of care in youth with T1DM.

Irregular sleep and cardiometabolic risk: Clinical evidence and mechanisms

Sleep regularity is an essential part of the multidimensional sleep health framework. The phenomenon of irregular sleep patterns is widespread in contemporary lifestyles. This review synthesizes clinical evidence to summarize the measures of sleep regularity and discusses the role of different sleep regularity indicators in developing cardiometabolic diseases (coronary heart disease, hypertension, obesity, and diabetes). Existing literature has proposed several measurements to assess sleep regularity, mainly including the standard deviation (SD) of sleep duration and timing, sleep regularity index (SRI), interdaily stability (IS), and social jetlag (SJL). Evidence on associations between sleep variability and cardiometabolic diseases varies depending on the measure used to characterize variability in sleep. Current studies have identified a robust association between SRI and cardiometabolic diseases. In comparison, the association between other metrics of sleep regularity and cardiometabolic diseases was mixed. Meanwhile, the associations of sleep variability with cardiometabolic diseases differ across the population. SD of sleep characteristics or IS may be more consistently associated with HbA1c in patients with diabetes compared with the general population. The association between SJL and hypertension for patients with diabetes was more accordant than in the general population. Interestingly, the age-stratified association between SJL and metabolic factors was observed in the present studies. Furthermore, the relevant literature was reviewed to generalize the potential mechanisms through which irregular sleep increases cardiometabolic risk, including circadian dysfunction, inflammation, autonomic dysfunction, hypothalamic-pituitary-adrenal (HPA) axis disorder, and gut dysbiosis. Health-related practitioners should give more attention to the role of sleep regularity on human cardiometabolic in the future.

Consequences of Sleep Deprivation in Adult Diabetes Mellitus Type 2 Patients: An Integrative Review

BACKGROUND: Sleep deprivation in individuals with diabetes mellitus type 2 is more prevalent than in ordinary people. At present, the adverse effects of diabetes type 2 people with sleep disorders and sleep deprivation on blood sugar control are irrefutable. Thorough assessments covering the whole structure should be of concern in health-care treatment. It is precipitated and delivered to the physical, mental health, and social environment, but no systematic review or minimal data were published. Furthermore, it may significantly affect the system more than existing research. AIM: An integrative review aims to clarify the results or consequences of sleep disturbance/deprivation or insomnia symptoms among diabetes mellitus type 2 patients. METHODS: The writers implemented a literature search in PubMed, CINAHL, and Medline using the terms DM type 2, insomnia, adult, effect, DM, sleep disturbance, sleep disorder, and a consequence between 2012 and 2022. Inclusion criteria selected through considering the entire article, and providing an abstract, were 20 articles. RESULTS: Integrative data extraction and information were analyzed thematically. Identified were nine ideas: Association with blood sugar control, blood pressure control, risk of CVD, diabetes self-care behavior, weight gained and Obstructive Sleep Apnea (OSA), lifestyle and physical activity, mood/depression and anxiety symptoms, daily calories distribution, cholesterol/triglyceride, and liver enzyme levels. CONCLUSION: The adverse effects of sleep deprivation in type 2 diabetes significantly affect all pathophysiologically, mentally, and lifestyle modifications, including diabetes self-care. Therefore, to highlight the importance of promoting optimum sleep in diabetes type2 patients, a health-care system is inevitably as necessary as diet and exercise management.

Impact of sleep and physical activity habits on real‐life glycaemic variability in patients with type 2 diabetes

The aim of this study was to better characterise whether sleep habits, eating schedule and physical activity in real-life are associated with glycaemic control in patients with type 2 diabetes. A total of 28 patients (aged 60 years [58; 66], 54% female) with type 2 diabetes treated with basal-bolus insulin therapy administered by insulin pumps were analysed. Glycaemic data measured by Flash Glucose Monitor System, physical activity and sleep data measured by accelerometer, and meal schedules were simultaneously collated with insulin pump administration data, for 7 days in real-life. Their respective impact on the time spent in target, in hypoglycaemia, in hyperglycaemia and on glycaemic variability was evaluated. Multiple regressions showed that the total daily dose of meal boluses of insulin was inversely associated with the coefficient of variation (CV; coefficient β = -0.073; 95% confidence interval: -0.130, -0.015; p = 0.016), as well as sleep duration. The higher the sleep duration, the lower the glycaemic variability (coefficient β = -0.012; 95% confidence interval: -0.023, -0.002; p = 0.027). The mean 7 days physical activity of the subjects was very low and was not associated with glycaemic control on the 7 days mean values. However, days with at least 1 hr spent in physical activity higher than 1.5 METs were associated with less glycaemic variability that same day. This real-life observation highlights the importance of sufficient sleep duration and regular physical activity to lessen the glycaemic variability of patients with type 2 diabetes.

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.

Sleep and Circadian Rhythm Disturbances in Diabetes: A Narrative Review

Sleep and circadian rhythm disturbances are less-known risk factors for the development and suboptimal outcomes of diabetes. The goal of this narrative review is to highlight the importance of sleep and circadian rhythm disturbances in the development and outcomes of type 1 diabetes (T1D) and type 2 diabetes (T2D), assess current treatment options and the possible mediating mechanisms. We performed a literature search using PubMed and selected relevant English and Dutch papers. Disturbances of sleep and circadian rhythm are common in people with diabetes. They are associated with an increased risk of developing T2D as well as with suboptimal diabetes outcomes (including higher HbA1c levels and reduced quality of life) for T1D and T2D. Preliminary data suggest that treatment of sleep and circadian rhythm disturbances could improve diabetes outcomes in people with T1D and T2D. Finally, the association with medical parameters appears to be mediated by disturbance in hormones, and by suboptimal self-care including forgetting or postponing glucose monitoring or medication use as well as higher consumption of high fat/high sugary foods. Diabetes may also disturb sleep, for example through nocturnal hypoglycemia and nocturia. We concluded that sleep and circadian rhythm disturbances are closely linked with diabetes. More attention to sleep in regular diabetes care is warranted, while further research is needed on treatment of sleep and circadian rhythm disturbances in the prevention of diabetes and its suboptimal outcomes.

The association between social jetlag and parameters of metabolic syndrome and type 2 diabetes: a systematic review and meta‐analysis

This study aims to determine the association between social jetlag and parameters of metabolic syndrome and type 2 diabetes (T2D) in a systematic review and meta-analysis. A systematic literature search was conducted in PubMed/Embase/Scopus until May 2022. Included studies described an association between social jetlag and parameters of the metabolic syndrome and/or T2D, were available full text and written in English or Dutch. Data extraction and quality assessment were performed on pre-piloted forms independently by two reviewers. Results were meta-analysed using random-effects analysis. A total of 6,290 titles/abstracts were screened, 176 papers were read full-text, 68 studies were included. Three studies were rated as low quality, 27 were moderate, and 38 were high quality. High quality studies showed that having social jetlag compared to no social jetlag was significantly associated with higher body mass index in 20 studies (0.49 kg/m² , 95% confidence interval [CI] 0.21-0.77; I²  = 100%), higher waist circumference in seven studies (1.11 cm, 95% CI 0.42-1.80; I²  = 25%), higher systolic blood pressure in 10 studies (0.37 mmHg, 95% CI 0.00-0.74; I²  = 94%) and higher glycated haemoglobin in 12 studies (0.42%, 95% CI 0.12- 0.72; I²  = 100%). No statistically significant associations were found for obesity, abdominal obesity, high- and low-density lipoprotein levels, cholesterol, triglycerides, diastolic blood pressure, hypertension, fasting glucose, homeostatic model assessment for insulin resistance, metabolic syndrome or T2D. Sensitivity analyses did not reduce heterogeneity. Despite substantial heterogeneity, social jetlag is associated with certain parameters of the metabolic syndrome and T2D, but not with prevalent metabolic syndrome or T2D. These findings should be interpreted with caution as the level of evidence is low and mostly based on cross-sectional data. Longitudinal studies are needed to further assess the direction of causality.

Sleep optimization to improve glycemic control in adults with type 1 diabetes: study protocol for a randomized controlled parallel intervention trial

BACKGROUND

Despite improvements in treatment regimens and technology, less than 20% of adults with type 1 diabetes (T1D) achieve glycemic targets. Sleep is increasingly recognized as a potentially modifiable target for improving glycemic control. Diabetes distress, poor self-management behaviors, and reduced quality of life have also been linked to sleep variability and insufficient sleep duration. A significant gap of knowledge exists regarding interventions to improve sleep and the effects of sleep optimization on glycemic control in T1D. The purpose of this study is to determine the efficacy of a T1D-specific sleep optimization intervention (Sleep-Opt) on the primary outcomes of sleep variability, sleep duration, and glycemic control (A1C); other glycemic parameters (glycemic variability, time-in-range [TIR]); diabetes distress; self-management behaviors; quality of life; and other patient-reported outcomes in adults with T1D and habitual increased sleep variability or short sleep duration.

METHODS

A randomized controlled parallel-arm study will be employed in 120 adults (aged 18 to 65 years) with T1D. Participants will be screened for habitual sleep variability (> 1 h/week) or insufficient sleep duration (< 6.5 h per night). Eligible subjects will be randomized to the Sleep-Opt intervention group or healthy living attention control group for 12 weeks. A 1-week run-in period is planned, with baseline measures of sleep by actigraphy (sleep variability and duration), glycemia (A1C and related glycemic measures: glycemic variability and TIR using continuous glucose monitoring), and other secondary outcomes: diabetes distress, self-management behaviors, quality of life, and additional patient-reported outcomes. Sleep-Opt is a technology-assisted behavioral sleep intervention that we recently developed that leverages the rapidly increasing public interest in sleep tracking. Our behavioral intervention employs four elements: a wearable sleep tracker, didactic content, an interactive smartphone application, and brief telephone counseling. The attention control group will participate in a healthy living information program. Baseline measures will be repeated at midpoint, program completion, and post-program (weeks 6, 12, and 24, respectively) to determine differences between the two groups and sustainability of the intervention.

DISCUSSION

A better understanding of strategies to improve sleep in persons with T1D has the potential to be an important component of diabetes.

TRIAL REGISTRATION

Clinical Trial Registration: NCT04506151 .

Enhancing Night and Day Circadian Contrast through Sleep Education in Prediabetes and Type 2 Diabetes Mellitus: A Randomized Controlled Trial

BACKGROUND

Evidence supports a causal relationship between circadian disturbance and impaired glucose homeostasis.

METHODS

To determine the effect of an educational intervention delivered by primary care nurses to improve sleep hygiene, a parallel, open-label clinical trial in subjects aged 18 and older with impaired fasting glucose (IFG) or type 2 diabetes mellitus (T2DM) was performed. Study variables were sex, age, fasting glucose, glycated haemoglobin A1c (HbA1c), Pittsburgh Sleep Quality Index (PSQI), sleep duration and efficiency, body mass index, antidiabetic treatment, diet and physical exercise. An individual informative educational intervention was carried out following a bidirectional feedback method. The intervention aimed to develop skills to improve sleep through nine simple tips. An analysis of covariance was performed on all the mean centred outcome variables controlling for the respective baseline scores.

RESULTS

In the intervention group, PSQI dropped, the duration and quality of sleep increased, and a decrease in fasting glucose and in HbA1c levels was observed.

CONCLUSION

The proposed intervention is effective for improving sleep quality, length and efficiency, and for decreasing fasting glucose and HbA1c levels in only 3 months. These findings support the importance of sleep and circadian rhythm education focused on improving IFG and T2DM.

Association of accelerometry-derived social jetlag and sleep with temperament in children less than 6 years of age

STUDY OBJECTIVES

Social jetlag (SJL) measures the discrepancy between circadian and social clocks. Using accelerometry-derived data, our objective was to assess the prevalence of SJL in young healthy children and determine the association of SJL and sleep with temperament.

METHODS

Of 117 children participating in TARGet Kids!, a Canadian cohort of healthy preschool-aged children, 78 children (39 girls (50%)); mean age [SD]: 35.1[20.5] months) were included. Sleep was measured objectively using accelerometry. Temperament dimensions (surgency, negative affectivity, and effortful control) were assessed with the very short forms of Rothbart's child and infant behavior questionnaires. We examined associations of SJL and sleep with temperament using multivariable linear regression models adjusted for sex, age, ethnicity, and preschool/daycare attendance.

RESULTS

20 out of 78 (25.6%) experienced SJL of greater than 30 minutes. SJL was greater in children who attended preschool/daycare compared with children who did not (26.3[18.8]min vs. 17.6[14.8]min; p<0.05). There was no evidence of an association between SJL and any temperament dimension. We found evidence of an association between increased sleep duration and increased negative affectivity scores (longer 24h sleep (ß:0.347, 95% CI:0.182,0.512, p<0.0001); longer nighttime sleep duration (ß:0.413, 95% CI:0.163,0.663, p=0.002)).

CONCLUSIONS

In our cohort, 1 in 4 preschool-aged children experienced SJL. Increased sleep duration was associated with increased negative affect, which could have implications for children developing internalizing behavior such as depression or low-self-esteem. We found that sleep duration, but not SJL, was associated with temperament and may impact daytime behavior of young children.

Sleep improvements on days with later school starts persist after 1 year in a flexible start system

Early school times fundamentally clash with the late sleep of teenagers. This mismatch results in chronic sleep deprivation posing acute and long-term health risks and impairing students' learning. Despite immediate short-term benefits for sleep, the long-term effects of later starts remain unresolved. In a pre-post design over 1 year, we studied a unique flexible school start system, in which 10–12th grade students chose daily between an 8:00 or 8:50AM-start. Missed study time (8:00–8:50) was compensated for during gap periods or after classes. Based on 2 waves (6–9 weeks of sleep diary each), we found that students maintained their ~ 1-h-sleep gain on later days, longitudinally (n = 28) and cross-sectionally (n = 79). This gain was independent of chronotype and frequency of later starts but attenuated for boys after 1 year. Students showed persistently better sleep quality and reduced alarm-driven waking and reported psychological benefits (n = 93) like improved motivation, concentration, and study quality on later days. Nonetheless, students chose later starts only infrequently (median 2 days/week), precluding detectable sleep extensions in the flexible system overall. Reasons for not choosing late starts were the need to make up lost study time, preference for extra study time and transport issues. Whether flexible systems constitute an appealing alternative to fixed delays given possible circadian and psychological advantages warrants further investigation.

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.

An exploratory study of associations between sleep timing variability and cardiometabolic health in middle-aged adults with type 2 diabetes mellitus

Sleep is increasingly recognised as an important risk factor for metabolic disease, and as an important influence on severity in established metabolic disease. Recent evidence suggests that sleep timing variability (the day-to-day fluctuations of sleep timing) may be an important factor in metabolic diseases such as type 2 diabetes mellitus. In the current study, we explore the associations between measures of sleep timing variability and cardiometabolic measures in a group of healthy middle-aged adults with and without type 2 diabetes mellitus. Healthy controls (N = 27) and adults with well-controlled uncomplicated type 2 diabetes mellitus (N = 30) wore actiwatches for an average of 9 days for objective assessment of sleep timing parameters, and also underwent a detailed clinical assessment. We found greater self-reported social jetlag in the diabetes group, but no groupwise differences in measures of sleep timing variability. In the diabetes patients, HbA1c levels were inversely correlated with variability in the time of sleep onset and midsleep, and with sleep duration. HOMA-IR did not correlate with any sleep timing variability measure, nor were there associations between sleep timing variability and other metabolic biomarkers (cholesterol, LDL, HDL, triglycerides and uric acid). Systolic blood pressure was inversely correlated with actigraphically defined social jetlag in both the control and diabetes groups. The results of this study indicate associations between sleep timing variability and HbA1c, but the direction of these relationships is at variance with some other recent reports. Our results indicate a need for future hypothesis-testing studies to further explore the impact of sleep timing variance on metabolic health.

Exercise, type 1 diabetes mellitus and blood glucose: The implications of exercise timing

The scientific literature shows that exercise has many benefits for individuals with type 1 diabetes. Yet, several barriers to exercise in this population exist, such as post-exercise hypoglycaemia or hyperglycaemia. Several studies suggest that the timing of exercise may be an important factor in preventing exercise-induced hypoglycaemia or hyperglycaemia. However, there is a paucity of evidence solely focused on summarising findings regarding exercise timing and the impact it has on glucose metabolism in type 1 diabetes. This report suggests that resistance or high-intensity interval exercise/training (often known as HIIT) may be best commenced at the time of day when an individual is most likely to experience a hypoglycaemic event (i.e., afternoon/evening) due to the superior blood glucose stability resistance and HIIT exercise provides. Continuous aerobic-based exercise is advised to be performed in the morning due to circadian elevations in blood glucose at this time, thereby providing added protection against a hypoglycaemic episode. Ultimately, the evidence concerning exercise timing and glycaemic control remains at an embryonic stage. Carefully designed investigations of this nexus are required, which could be harnessed to determine the most effective, and possibly safest, time to exercise for those with type 1 diabetes.

Social Jetlag and Related Risks for Human Health: A Timely Review

The term social jetlag is used to describe the discrepancy between biological time, determined by our internal body clock, and social times, mainly dictated by social obligations such as school or work. In industrialized countries, two-thirds of the studying/working population experiences social jetlag, often for several years. Described for the first time in 2006, a considerable effort has been put into understanding the effects of social jetlag on human physiopathology, yet our understanding of this phenomenon is still very limited. Due to its high prevalence, social jetlag is becoming a primary concern for public health. This review summarizes current knowledge regarding social jetlag, social jetlag associated behavior (e.g., unhealthy eating patterns) and related risks for human health.

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).

Social Jetlag Is Associated With Impaired Metabolic Control During a 1-Year Follow-Up

Previous studies have identified social jetlag (SJL) as a risk factor for non-communicable chronic diseases (NCCDs), but its association with metabolic control over time is unclear in the literature. Therefore, we examined the influence of SJL on metabolic parameters and blood pressure (BP) in patients with NCCDs over a 1-year follow-up. This retrospective, longitudinal study included 625 individuals (age: 56.0 +12.0 years; 76% female) with NCCDs [type 2 diabetes mellitus (TD2), systemic arterial hypertension (SHA), obesity, or dyslipidemia]. SJL was calculated based on the absolute difference between mid-sleep time on weekends and weekdays. Current metabolic parameters and BP of the patients were compared with data from a year prior. Generalized estimating equations (GEE) and multiple linear regression analyses were used to examine the association among SJL, metabolic parameters, and BP. Multiple linear regression analyses adjusted for confounders showed that SJL was positively associated with the delta difference of fasting glucose (β = 0.11, p = 0.02) and triglyceride levels (β = 0.09, p = 0.04) among all subjects with NCCDs, and with fasting glucose (β = 0.30, p = 0.0001) and triglyceride levels (β = 0.22, p = 0.01) in the TD2 group. GEE analysis demonstrated an isolated effect of SJL on diastolic BP. High SJL impaired clinical and metabolic control in individuals with NCCDs, leading to a worse profile after a 1-year follow-up, particularly among type II diabetics.

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.

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

STUDY OBJECTIVES

The purpose of this study was to describe objective sleep-wake characteristics and glycemia over 7 - 14 days in young adults with type 1 diabetes (T1D). Additionally, person level associations among objective sleep-wake characteristics (total sleep time, sleep variability, and sleep fragmentation index), daytime sleepiness, and glycemia (glycemic control and glucose variability) were examined.

METHODS

In this cross-sectional study, objective sleep-wake characteristics were measured via actigraphy and glucose variability via continuous glucose monitoring (CGM) over 6-14 days. At baseline, participants completed a psychomotor vigilance test (PVT), Trail Making Test, and questionnaires on daytime sleepiness, sleep quality, and sleep disturbance including sleep diaries.

RESULTS

Forty-six participants (mean age 22.3 ± 3.2 years) wore a wrist actigraph and CGM concurrently for 6-14 days. Greater sleep variability was directly associated with greater glucose variability (mean of daily differences) (r = 0.33, p = .036). Higher daytime sleepiness was directly associated with greater glucose variability (mean of daily differences) (r = 0.50, p = .001). The association between sleep variability and glucose variability (mean of daily differences) was no longer significant when accounting for daytime sleepiness and controlling for T1D duration (p > .05). A higher sleep fragmentation index was associated with greater glucose variability (B = 1.27, p = .010, pr² = .40) after controlling for T1D duration and accounting for higher daytime sleepiness.

CONCLUSIONS

Sleep-wake variability, sleep fragmentation, daytime sleepiness, and the associations with glycemia are new dimensions to consider in young adults with T1D. Sleep habits in this population may explain higher glucose variability and optimizing sleep may improve overall diabetes management.

Characterizing Glycemic Control and Sleep in Adults with Long-Standing Type 1 Diabetes and Hypoglycemia Unawareness Initiating Hybrid Closed Loop Insulin Delivery

Nocturnal hypoglycemia is life threatening for individuals with type 1 diabetes (T1D) due to loss of hypoglycemia symptom recognition (hypoglycemia unawareness) and impaired glucose counter regulation. These individuals also show disturbed sleep, which may result from glycemic dysregulation. Whether use of a hybrid closed loop (HCL) insulin delivery system with integrated continuous glucose monitoring (CGM) designed for improving glycemic control, relates to better sleep across time in this population remains unknown. The purpose of this study was to describe long-term changes in glycemic control and objective sleep after initiating hybrid closed loop (HCL) insulin delivery in adults with type 1 diabetes and hypoglycemia unawareness. To accomplish this, six adults (median age = 58 y) participated in an 18-month ongoing trial assessing HCL effectiveness. Glycemic control and sleep were measured using continuous glucose monitoring and wrist accelerometers every 3 months. Paired sample t-tests and Cohen's d effect sizes modeled glycemic and sleep changes and the magnitude of these changes from baseline to 9 months. Reduced hypoglycemia (d = 0.47-0.79), reduced basal insulin requirements (d = 0.48), and a smaller glucose coefficient of variation (d = 0.47) occurred with medium-large effect sizes from baseline to 9 months. Hypoglycemia awareness improved from baseline to 6 months with medium-large effect sizes (Clarke score (d = 0.60), lability index (d = 0.50), HYPO score (d = 1.06)). Shorter sleep onset latency (d = 1.53; p < 0.01), shorter sleep duration (d = 0.79), fewer total activity counts (d = 1.32), shorter average awakening length (d = 0.46), and delays in sleep onset (d = 1.06) and sleep midpoint (d = 0.72) occurred with medium-large effect sizes from baseline to 9 months. HCL led to clinically significant reductions in hypoglycemia and improved hypoglycemia awareness. Sleep showed a delayed onset, reduced awakening length and onset latency, and maintenance of high sleep efficiency after initiating HCL. Our findings add to the limited evidence on the relationships between diabetes therapeutic technologies and sleep health. This trial is registered with ClinicalTrials.gov (NCT03215914).

Proinflammatory Cytokines Perturb Mouse and Human Pancreatic Islet Circadian Rhythmicity and Induce Uncoordinated β-Cell Clock Gene Expression via Nitric Oxide, Lysine Deacetylases, and Immunoproteasomal Activity

Pancreatic β-cell-specific clock knockout mice develop β-cell oxidative-stress and failure, as well as glucose-intolerance. How inflammatory stress affects the cellular clock is under-investigated. Real-time recording of Per2:luciferase reporter activity in murine and human pancreatic islets demonstrated that the proinflammatory cytokine interleukin-1β (IL-1β) lengthened the circadian period. qPCR-profiling of core clock gene expression in insulin-producing cells suggested that the combination of the proinflammatory cytokines IL-1β and interferon-γ (IFN-γ) caused pronounced but uncoordinated increases in mRNA levels of multiple core clock genes, in particular of reverse-erythroblastosis virus α (Rev-erbα), in a dose- and time-dependent manner. The REV-ERBα/β agonist SR9009, used to mimic cytokine-mediated Rev-erbα induction, reduced constitutive and cytokine-induced brain and muscle arnt-like 1 (Bmal1) mRNA levels in INS-1 cells as expected. SR9009 induced reactive oxygen species (ROS), reduced insulin-1/2 (Ins-1/2) mRNA and accumulated- and glucose-stimulated insulin secretion, reduced cell viability, and increased apoptosis levels, reminiscent of cytokine toxicity. In contrast, low (<5,0 μM) concentrations of SR9009 increased Ins-1 mRNA and accumulated insulin-secretion without affecting INS-1 cell viability, mirroring low-concentration IL-1β mediated β-cell stimulation. Inhibiting nitric oxide (NO) synthesis, the lysine deacetylase HDAC3 and the immunoproteasome reduced cytokine-mediated increases in clock gene expression. In conclusion, the cytokine-combination perturbed the intrinsic clocks operative in mouse and human pancreatic islets and induced uncoordinated clock gene expression in INS-1 cells, the latter effect associated with NO, HDAC3, and immunoproteasome activity.

Sleep, self-management, neurocognitive function, and glycemia in emerging adults with Type 1 diabetes mellitus: A research protocol

Type 1 Diabetes (T1D) affects 1.6 million Americans, and only 14% of emerging adults ages 18-25 years achieve targets for glycemic control (A1C < 7.0%). Sleep deficiency, including habitual short sleep duration (<6.5 hr total sleep time and high within-person variability in total sleep time), is associated with poorer glycemic control. Emerging adults with T1D have a more pronounced sleep extension on weekends compared with matched controls, consistent with sleep deficiency; however, associations among sleep variability and glycemic control have not been explored in this population. Sleep deficiency may affect the complex higher-order neurocognitive functioning needed for successful diabetes self-management (DSM). We report the protocol for an ongoing study designed to characterize sleep and the associations among sleep deficiency, neurocognitive function, DSM, diabetes quality of life, and glycemia among a sample of 40 emerging adults with T1D. We monitor sleep via wrist-worn actigraphy and glucose via continuous glucose monitoring concurrently over 14 days. We are collecting data on self-report and objective sleep, a 10-min psychomotor vigilance test on a PVT-192 device, a 3-min Trail Making Test on paper, and questionnaires, including twice-daily Pittsburgh sleep diaries using Research Electronic Data Capture (REDCap)TM . Results from this study will be used to support the development and testing of the efficacy of a tailored sleep self-management intervention that may improve total sleep time, sleep variability, neurocognitive function, DSM, glycemic control, and glucose variability among emerging adults with T1D.

Sleep-related disorders in patients with type 1 diabetes mellitus: current insights

Type 1 diabetes mellitus (T1DM) is an autoimmune condition that results from destruction of beta cells in the pancreas. Several reviews have concluded that sleep contributes to poor glycemic control, diabetes management, and diabetes-related complications in individuals with T1DM and represents an untapped opportunity for intervention. However, at the current juncture, the American Diabetes Association's Standards of Medical Care are devoid of recommendations about how to address sleep in the management of T1DM. This article summarizes reviews of sleep in youth and adults with T1DM and empirical studies that have examined various sleep parameters ranging from sleep disturbances (general, perceived sleep quality, sleepiness, awakenings, and sleep efficiency), sleep duration, sleep consistency, sleep-disordered breathing (SDB), and sleep architecture. The data show that many individuals with T1DM sleep less than recommendations; individuals with the poorest sleep have difficulties with diabetes management; and sleep deficiency including SDB often corresponds to several disease morbidities (neuropathy, nephropathy, etc). Mixed findings exist regarding direct associations of various sleep parameters and glycemic control. SDB appears to be just as prevalent, if not more, than other conditions that have been recommended for universal screening in individuals with T1DM. The article concludes with recommendations for collaborative research efforts to further elucidate the role of sleep in diabetes-related outcomes; investigations to test behavioral strategies to increase sleep quantity and consistency; and considerations for clinical care to address sleep.

Later school start times in a flexible system improve teenage sleep

Sleep deprivation in teenage students is pervasive and a public health concern, but evidence is accumulating that delaying school start times may be an effective countermeasure. Most studies so far assessed static changes in schools start time, using cross-sectional comparisons and one-off sleep measures. When a high school in Germany introduced flexible start times for their senior students—allowing them to choose daily between an 8 am or 9 am start (≥08:50)—we monitored students’ sleep longitudinally using subjective and objective measures. Students (10–12th grade, 14–19 y) were followed 3 weeks prior and 6 weeks into the flexible system via daily sleep diaries (n = 65) and a subcohort via continuous wrist-actimetry (n = 37). Satisfaction and perceived cognitive outcomes were surveyed at study end. Comparisons between 8 am and ≥9 am-starts within the flexible system demonstrated that students slept 1.1 h longer when starting school later—independent of gender, grade, chronotype, and frequency of later starts; sleep offsets were delayed but, importantly, onsets remained unchanged. Sleep quality was increased and alarm-driven waking reduced. However, overall sleep duration in the flexible system was not extended compared to baseline—likely because students did not start later frequently enough. Nonetheless, students were highly satisfied with the flexible system and reported cognitive and sleep improvements. Therefore, flexible systems may present a viable alternative for implementing later school starts to improve teenage sleep if students can be encouraged to use the late-option frequently enough. Flexibility may increase acceptance of school start changes and speculatively even prevent delays in sleep onsets through occasional early starts.

Intra-individual variability in sleep is related to glycaemic control in adults with type 2 diabetes

AIMS

To examine whether there were significant differences in sleep during weekdays/weekends and whether the intra-individual variability in sleep was related to glycaemic control in patients with type 2 diabetes.

DESIGN

Correlational, longitudinal design.

METHODS

Data were collected between February 2017-January 2018. In all, 56 adults with type 2 diabetes were included (60.7 years, 55.4% female). Sleep was measured using the Consensus Sleep Diary over 8 days. Intra-individual variability of sleep was calculated as the standard deviation of sleep variables. Standard deviations of sleep duration, sleep efficiency, sleep quality, and mid-sleep time were obtained. Glycaemic control was measured by haemoglobin A1C. Paired t test and multiple regression analysis were used.

RESULTS

Overall, there were no differences in sleep parameters between weekdays and weekends. Participants slept 20 min more over the weekends than during weekdays. The mid-sleep time during weekends was about 35 min later than during weekdays. Intra-individual variability of sleep duration and mid-sleep ranged from 27.6-167.4 min and 13-137 min, respectively. Controlling for covariates (e.g., distress, symptoms, and self-care), larger variability in sleep duration, and mid-sleep were significantly related to higher A1C levels.

CONCLUSION

Diabetes educators are recommended to include the assessment of intra-individual variability in sleep. Maintaining a regular sleep habit (e.g., sleep duration and sleep timing) should be highlighted during patient education.

IMPACT

Intra-individual variability in sleep is an alternative dimension for sleep assessment. This study examined whether intra-individual variability in sleep was related to glycaemic control in an older sample of type 2 diabetes patients using a sleep diary across 8 days. This sample had a similar sleep pattern during weekdays and weekends. Larger intra-individual variabilities in sleep duration and mid-sleep time were independently related to worse glycaemic control. Diabetes patients are recommended to maintain a regular sleep routine.

Sleep Apnea and Sleep Habits: Relationships with Metabolic Syndrome

Excess visceral adiposity is a primary cause of metabolic syndrome and often results from excess caloric intake and a lack of physical activity. Beyond these well-known etiologic factors, however, sleep habits and sleep apnea also seem to contribute to abdominal obesity and metabolic syndrome: Evidence suggests that sleep deprivation and behaviors linked to evening chronotype and social jetlag affect eating behaviors like meal preferences and eating times. When circadian rest and activity rhythms are disrupted, hormonal and metabolic regulations also become desynchronized, and this is known to contribute to the development of metabolic syndrome. The metabolic consequences of obstructive sleep apnea syndrome (OSAS) also contribute to incident metabolic syndrome. These observations, along with the first sleep intervention studies, have demonstrated that sleep is a relevant lifestyle factor that needs to be addressed along with diet and physical activity. Personalized lifestyle interventions should be tested in subjects with metabolic syndrome, based on their specific diet and physical activity habits, but also according to their circadian preference. The present review therefore focuses (i) on the role of sleep habits in the development of metabolic syndrome, (ii) on the reciprocal relationship between sleep apnea and metabolic syndrome, and (iii) on the results of sleep intervention studies.

At the Interface of Lifestyle, Behavior, and Circadian Rhythms: Metabolic Implications

Nutrient metabolism is under circadian regulation. Disruption of circadian rhythms by lifestyle and behavioral choices such as work schedules, eating patterns, and social jetlag, seriously impacts metabolic homeostasis. Metabolic dysfunction due to chronic misalignment of an organism's endogenous rhythms is detrimental to health, increasing the risk of obesity, metabolic and cardiovascular disease, diabetes, and cancer. In this paper, we review literature on recent findings on the mechanisms that communicate metabolic signals to circadian clocks and vice versa, and how human behavioral changes imposed by societal and occupational demands affect the physiological networks integrating peripheral clocks and metabolism. Finally, we discuss factors possibly contributing to inter-individual variability in response to circadian changes in the context of metabolic (dys)function.

Social jetlag, sleep-related parameters, and glycemic control in adults with type 1 diabetes: Results of a cross-sectional study

BACKGROUND

Social jetlag (SJL) is a small recurrent circadian rhythm disruption and the most frequent form of circadian rhythm misalignment. The main aim of this study was to investigate the effect of SJL on glycemic control, as assessed by HbA1c, in real-life settings.

METHODS

In all, 115 consecutive patients with type 1 diabetes (T1D) were analyzed cross-sectionally. Data on bedtime, sleep onset latency, and wake up time on weekdays and weekends during the previous month were collected from all participants and used to calculate SJL, chronotype, and sleep duration. Sleep quality was assessed by the Pittsburgh Sleep Quality Index (PSQI). A PSQI score > 5 was considered as an indicator of poor sleep quality.

RESULTS

Patients with SJL ≥ 1 hour had significantly higher adjusted values of HbA1c than those with SJL <1 hour (8.7% vs 8.0%; P = 0.029). In unadjusted multivariate regression analysis, SJL ≥ 1 hour and poor sleep quality were significant predictors of HbA1c values, explaining 22.7% and 23.5%, respectively, of the increase in HbA1c. After adjusting for age, sex, diabetes duration, insulin dose (kg/d), insulin regimen and body mass index, only SJL ≥ 1 hour remained associated with HbA1c (β = 0.253; P = 0.026). There was no significant interaction between SJL ≥ 1 hour and poor sleep quality in either the unadjusted or adjusted models (P_interaction  = 0.914).

CONCLUSIONS

In patients with T1D, SJL is associated with poor glycemic control, acting independently of sleep quality, sleep duration, and chronotype to exert a deleterious effect on glycemic control.

A novel comprehensive paradigm for the etiopathogenesis of multiple sclerosis: therapeutic approaches and future perspectives on its treatment

It is well recognized that variation in the geographical distribution of prevalence of multiple sclerosis (MS) exists: increasing the latitude its prevalence increases as well, but the underlying causes of such dissimilarity still remained elusive as of today. Currently, the most accredited hypothesis is that the closer to the equator the more pronounced is the amount of sunlight which, in turn, increases the production of vitamin D. Cholecalciferol is indeed deficient in MS patients, but this factor does not explain by itself the etiopathogenesis of the disease. In the present study, to search for a pattern and provide a model of the disease's etiology consistent with this regional factor, as well with its changing ethnic, sex-ratio, lifestyle variations and the other unexplained aspects of MS, an extensive analysis of peer-reviewed literature and data was conducted. The arisen hypothesis was that, increasing the latitude, the factor that varies and can have the stronger effect on the human organism, is the continuous and ever-increasing diversity of the natural light-dark cycle. The consequent effort of the suprachiasmatic nucleus to entrain the organism's circadian rhythm affects the hypothalamic-pituitary-adrenal axis resulting in desynchronizing the central and peripheral circadian clocks and pathologizing the immunitary system. To verify such hypothesis, a theoretical framework of the etiopathogenesis, coherent with the gathered literature, was conceived and a demonstration to corroborate it was eventually devised and performed. The results underscored that people living in countries subjected to a further circadian disruptive factor, as daylight saving time, have a 6.35 times higher prevalence of MS than States placed on their same latitude that do not observe it, thus strongly supporting the hypothesis. As further reinforcement of the conclusions, it is worth mentioning that the levels of polyamines rise abruptly in autoimmune diseases. Moreover, among their numerous roles, these polycations participate to the regulation of the circadian clock so their sudden variation might disrupt it. Following these interesting findings, new perspectives in therapies are, therefore, proposed.

Association between social jetlag food consumption and meal times in patients with obesity-related chronic diseases

Chronic disruption of the synchronous relationship between endogenous and exogenous circadian timing is associated with the development of obesity and metabolic disease. Social jetlag is a measure of circadian misalignment and has been identified as a risk factor for overweight and related diseases. However, the mechanisms involved in this relationship remain underexplored. The objective of this study was to investigate the association between social jetlag and food consumption at late meal timing in patients with obesity-related chronic diseases. This study included 792 individuals (73% female; age 55.9 ± 12.4 years) in which the prevalence of social jetlag (>1h) was 24.4% (n = 194). Participants with social jetlag reported late meal timing for breakfast, early afternoon snack and dinner. Individuals with social jetlag also reported a higher intake of total calories (kcal), protein, total fat, saturated fat, cholesterol, and servings of meat and eggs and sweets in relation to those without social jetlag. Regarding the consumption during each meal of the day, participants with social jetlag had consumed more calories, saturated fat and cholesterol during dinner; more protein, total fat, saturated fat, and cholesterol during lunch; and more total fat and saturated fat during morning snack. In addition, individuals with social jetlag had a higher risk of inadequate consumption of total fat, saturated fat and cholesterol intake when compared with those without social jetlag. We conclude that social jetlag is associated with a poor diet and later meal times, which should be avoided in individuals with obesity-related chronic diseases. More studies are needed to confirm these findings.

Does sleep duration, napping, and social jetlag predict hemoglobin A1c among college students with type 1 diabetes mellitus?

AIMS

The first aim examined the relationship between sleep behaviors (duration, napping, and social jetlag) and hemoglobin A1c (HbA1c) among emerging young adults (EYAs) with T1DM between 18 and 25 years old, who are living on a college campus. The second aim characterized the gender differences in glucose management, sleep behaviors, caffeine intake, and nighttime technology.

METHODS

A cross-sectional study of eligible participants used a convenience sample of eligible participants. Using Research Electronic Data Capture (REDCap), participants completed surveys about diabetes management, caffeine intake, nighttime technology use, and sleep-related behaviors. Data were analyzed using correlation and multiple linear regression to predict HbA1c from sleep behaviors, adjusting for covariates.

RESULTS

Participants (N = 76) average years with T1DM was 10.25 ± 5.70. Compared to females, males had a longer sleep duration lower HbA1c levels. HbA1c levels were negatively correlated with weekday sleep (r = -0.24, p = 0.03) and positively correlated with napping (r = 0.34, p = 0.003). After adjusting for covariates, participants who napped had a higher HbA1c level (β = 0.74, p = 0.03) compared with non-nappers.

CONCLUSIONS

Higher HbA1c levels were found among EYAs with T1DM in college who were nappers and had a longer sleep duration. Modifying sleep behaviors may be an appropriate target to improve glycemic control.

Sleep and type 1 diabetes in children and adolescents: Proposed theoretical model and clinical implications

Youth with type 1 diabetes mellitus (T1D) experience more sleep disturbances and shorter sleep durations compared to their healthy peers. Researchers have now uncovered the negative mental health and physical health outcomes associated with poor sleep in youth with T1D. The field of T1D sleep research currently operates under the broad notion that sleep behaviors impact treatment adherence, which ultimately lead to worse long-term health outcomes. This model however does not explain how behavior influences T1D management and sleep outcomes on a day-to-day basis, leading to difficulties in providing tailored treatment recommendations. In this review, we present a theoretical framework that describes the recursive cycle between sleep behaviors, T1D outcomes, and symptoms of negative affect/stress over a 24-hour period. This model is guided by the sleep literature, showing a clear relationship between poor sleep and negative affect, and the T1D literature demonstrating a link between poor sleep and disease management for youth with T1D. Further, emerging literature indicates a need for additional parent sleep assessment considering that T1D management and fear of hypoglycemia negatively impact parent sleep behaviors. Recommendations are provided to move the field toward effective intervention studies and new areas of research to evaluate and modify the proposed model.