Physical behaviors and chronotype in people with type 2 diabetes

A Comparison of the Rates of Clock-Based Nocturnal Hypoglycemia and Hypoglycemia While Asleep Among People Living with Diabetes: Findings from the Hypo-METRICS Study

Introduction: Nocturnal hypoglycemia is generally calculated between 00:00 and 06:00. However, those hours may not accurately reflect sleeping patterns and it is unknown whether this leads to bias. We therefore compared hypoglycemia rates while asleep with those of clock-based nocturnal hypoglycemia in adults with type 1 diabetes (T1D) or insulin-treated type 2 diabetes (T2D). Methods: Participants from the Hypo-METRICS study wore a blinded continuous glucose monitor and a Fitbit Charge 4 activity monitor for 10 weeks. They recorded details of episodes of hypoglycemia using a smartphone app. Sensor-detected hypoglycemia (SDH) and person-reported hypoglycemia (PRH) were categorized as nocturnal (00:00-06:00 h) versus diurnal and while asleep versus awake defined by Fitbit sleeping intervals. Paired-sample Wilcoxon tests were used to examine the differences in hypoglycemia rates. Results: A total of 574 participants [47% T1D, 45% women, 89% white, median (interquartile range) age 56 (45-66) years, and hemoglobin A1c 7.3% (6.8-8.0)] were included. Median sleep duration was 6.1 h (5.2-6.8), bedtime and waking time ∼23:30 and 07:30, respectively. There were higher median weekly rates of SDH and PRH while asleep than clock-based nocturnal SDH and PRH among people with T1D, especially for SDH <70 mg/dL (1.7 vs. 1.4, P < 0.001). Higher weekly rates of SDH while asleep than nocturnal SDH were found among people with T2D, especially for SDH <70 mg/dL (0.8 vs. 0.7, P < 0.001). Conclusion: Using 00:00 to 06:00 as a proxy for sleeping hours may underestimate hypoglycemia while asleep. Future hypoglycemia research should consider the use of sleep trackers to record sleep and reflect hypoglycemia while asleep more accurately. The trial registration number is NCT04304963.

The association of self-reported sleep and circadian measures with glycemic control and diabetes complications among young adults with type 2 diabetes

We aim to examine the association of sleep duration, sleep quality, late chronotype, and circadian misalignment with glycemic control and risk of complications in young adults with youth-onset type 2 diabetes followed in the Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) study. Self-reported sleep duration, quality, timing, and circadian misalignment were assessed via a modified Pittsburgh Sleep Quality Index (PSQI) questionnaire, and chronotype was assessed via the Morningness-Eveningness Questionnaire (MEQ). We examined diabetes complications including loss of glycemic control (defined as hemoglobin A1c ≥8%), hypertension, dyslipidemia, albuminuria, and diabetic peripheral neuropathy. Multivariable logistic regression models were constructed to assess associations between sleep and circadian measures with outcomes of interest, such as loss of glycemic control and diabetes complications. A total of 421 participants (34.2% male), mean age 23.6 ± 2.5 yr, mean body mass index (BMI) of 36.1 ± 8.3 kg/m2, and mean diabetes duration of 10.0 ± 1.5 yr were evaluated. Self-reported short sleep duration, daytime sleepiness, and sleep quality were not associated with loss of glycemic control or diabetes complications. Late self-reported bedtime (after midnight) on work/school nights, rather than self-expressed chronotype or circadian misalignment, was independently associated with loss of glycemic control. An association was seen between late bedtimes and albuminuria but was attenuated after adjusting for depression. In conclusion, late bedtime on work/school days, rather than short sleep duration, daytime sleepiness, or poor sleep quality, was independently associated with loss of glycemic control in this longitudinal cohort of young adults with youth-onset type 2 diabetes.NEW & NOTEWORTHY The prevalence of type 2 diabetes in youth is increasing at an alarming rate. Identifying potentially modifiable factors modulating glycemic control is critically important to reduce micro and macrovascular complications. In a large cohort of youth-onset type 2 diabetes, self-reported late bedtime on work/school days was independently associated with loss of glycemic control in this longitudinal cohort of young adults with youth-onset type 2 diabetes.

The Regulate your Sitting Time (RESIT) intervention for reducing sitting time in individuals with type 2 diabetes: findings from a randomised-controlled feasibility trial

BACKGROUND

Reducing and breaking up sitting is recommended for optimal management of Type 2 diabetes mellitus (T2DM). Yet, there is limited evidence of interventions targeting these outcomes in individuals with this condition. The primary aim of this study was to assess the feasibility and acceptability of delivering and evaluating a tailored online intervention to reduce and break up sitting in adults with T2DM.

METHODS

A mixed-methods two-arm randomised controlled feasibility trial was conducted in ambulatory adults with T2DM who were randomised 1:1 to the REgulate your SItting Time (RESIT) intervention or usual care control group. The intervention included online education, self-monitoring and prompt tools (wearable devices, smartphone apps, computer apps) and health coaching. Feasibility outcomes were recruitment, attrition, data completion rates and intervention acceptability. Measurements of device-assessed sitting (intended primary outcome for definitive trial), standing and stepping, and physical function, psychosocial health and wellbeing were taken at baseline, 3 months and 6 months. Individual semi-structured interviews were conducted at six-months (post intervention) to explore acceptability, feasibility and experiences of the trial and intervention using the Framework Method.

RESULTS

Seventy participants aged 55 ± 11 years were recruited. Recruitment rate (proportion of eligible participants enrolled into the study) was 67% and participant retention rate at 6 months was 93% (n = 5 withdrawals). Data completion rates for daily sitting were 100% at baseline and ranged from 83 to 91% at 3 months and 6 months. Descriptive analysis demonstrated potential for the intervention to reduce device-measured sitting, which was 30.9 ± 87.2 and 22.2 ± 82.5 min/day lower in the intervention group at 3 and 6 months, respectively, compared with baseline. In the control group, sitting was 4.4 ± 99.5 and 23.7 ± 85.2 min/day lower at 3 and 6 months, respectively. Qualitative analysis identified three themes: reasons for participating in the trial, acceptability of study procedures, and the delivery and experience of taking part in the RESIT intervention. Overall, the measurement visits and intervention were acceptable to participants.

CONCLUSIONS

This study demonstrated the feasibility and acceptability of the RESIT intervention and evaluation methods, supporting a future definitive trial. If RESIT is found to be clinically effective, this could lead to changes in diabetes healthcare with a focus on reducing sitting.

TRIAL REGISTRATION

The trial was registered with ISRCTN (number ISRCTN14832389).

Explanatory variables of objectively measured 24-h movement behaviors in people with prediabetes and type 2 diabetes: A systematic review

AIM

Physical activity (PA), sedentary behavior (SB) and sleep (i.e. 24-h movement behaviors) are associated with health indicators in people with prediabetes and type 2 diabetes (T2D). To optimize 24-h movement behaviors, it is crucial to identify explanatory variables related to these behaviors. This review aimed to summarize the explanatory variables of 24-h movement behaviors in people with prediabetes or T2D.

METHODS

A systematic search of four databases (PubMed, Web of Science, Scopus & Embase) was performed. Only objective measurements of 24-h movement behaviors were included in the search strategy. The explanatory variables were classified according to the levels of the socio-ecological model (i.e. intrapersonal, interpersonal and environmental). The risk of bias was assessed using the Joanna Briggs Institute appraisal checklist.

RESULTS

None of the 78 included studies investigated 24-h movement behaviors. The majority of the studies investigated PA in isolation. Most studied explanatory variables were situated at the intrapersonal level. Being male was associated with more moderate to vigorous PA but less light PA in people with T2D, and more total PA in people with prediabetes. An older age was associated with a decrease in all levels of PA in people with T2D. HbA1c was positively associated with sleep and SB in both groups. No associations were found at the interpersonal or environmental level.

CONCLUSION

The results of this review underscore the lack of a socio-ecological approach toward explanatory variables of 24-h movement behaviors and the lack of focus on an integrated 24-h movement behavior approach in both populations.

Waking Up to the Importance of Sleep in Type 2 Diabetes Management: A Narrative Review

For the first time, the latest American Diabetes Association/European Association for the Study of Diabetes (ADA/EASD) consensus guidelines have incorporated a growing body of evidence linking health outcomes associated with type 2 diabetes to the movement behavior composition over the whole 24-h day. Of particular note, the importance of sleep as a key lifestyle component in the management of type 2 diabetes is promulgated and presented using three key constructs: quantity, quality, and timing (i.e., chronotype). In this narrative review we highlight some of the key evidence justifying the inclusion of sleep in the latest consensus guidelines by examining the associations of quantity, quality, and timing of sleep with measures of glycemia, cardiovascular disease risk, and mortality. We also consider potential mechanisms implicated in the association between sleep and type 2 diabetes and provide practical advice for health care professionals about initiating conversations pertaining to sleep in clinical care. In particular, we emphasize the importance of measuring sleep in a free-living environment and provide a summary of the different methodologies and targets. In summary, although the latest ADA/EASD consensus report highlights sleep as a central component in the management of type 2 diabetes, placing it, for the first time, on a level playing field with other lifestyle behaviors (e.g., physical activity and diet), the evidence base for improving sleep (beyond sleep disorders) in those living with type 2 diabetes is limited. This review should act as a timely reminder to incorporate sleep into clinical consultations, ongoing diabetes education, and future interventions.

Physical Activity Pattern of Adults With Metabolic Syndrome Risk Factors: Time-Series Cluster Analysis

Background

Physical activity plays a crucial role in maintaining a healthy lifestyle, and wrist-worn wearables, such as smartwatches and smart bands, have become popular tools for measuring activity levels in daily life. However, studies on physical activity using wearable devices have limitations; for example, these studies often rely on a single device model or use improper clustering methods to analyze the wearable data that are extracted from wearable devices.

Objective

This study aimed to identify methods suitable for analyzing wearable data and determining daily physical activity patterns. This study also explored the association between these physical activity patterns and health risk factors.

Methods

People aged >30 years who had metabolic syndrome risk factors and were using their own wrist-worn devices were included in this study. We collected personal health data through a web-based survey and measured physical activity levels using wrist-worn wearables over the course of 1 week. The Time-Series Anytime Density Peak (TADPole) clustering method, which is a novel time-series method proposed recently, was used to identify the physical activity patterns of study participants. Additionally, we defined physical activity pattern groups based on the similarity of physical activity patterns between weekdays and weekends. We used the χ2 or Fisher exact test for categorical variables and the 2-tailed t test for numerical variables to find significant differences between physical activity pattern groups. Logistic regression models were used to analyze the relationship between activity patterns and health risk factors.

Results

A total of 47 participants were included in the analysis, generating a total of 329 person-days of data. We identified 2 different types of physical activity patterns (early bird pattern and night owl pattern) for weekdays and weekends. The physical activity levels of early birds were less than that of night owls on both weekdays and weekends. Additionally, participants were categorized into stable and shifting groups based on the similarity of physical activity patterns between weekdays and weekends. The physical activity pattern groups showed significant differences depending on age (P=.004) and daily energy expenditure (P<.001 for weekdays; P=.003 for weekends). Logistic regression analysis revealed a significant association between older age (≥40 y) and shifting physical activity patterns (odds ratio 8.68, 95% CI 1.95-48.85; P=.007).

Conclusions

This study overcomes the limitations of previous studies by using various models of wrist-worn wearables and a novel time-series clustering method. Our findings suggested that age significantly influenced physical activity patterns. It also suggests a potential role of the TADPole clustering method in the analysis of large and multidimensional data, such as wearable data.

Morning Chronotype Is Associated with Improved Adherence to Continuous Positive Airway Pressure among Individuals with Obstructive Sleep Apnea

Rationale: Poor adherence limits the effectiveness of continuous positive airway pressure (CPAP) therapy for obstructive sleep apnea (OSA). A better understanding of CPAP adherence is needed to develop novel strategies to improve it. Objectives: To determine if the chronotype (morning, evening, or intermediate) of patients with OSA is associated with differences in CPAP adherence. If such an association exists, determine the mechanisms underlying this association. Methods: We performed a secondary analysis of the APPLES (Apnea Positive Pressure Long-term Efficacy Study) clinical trial. We assessed chronotype using the Morningness-Eveningness Questionnaire (MEQ) among participants randomized to the CPAP arm with daily adherence data (n = 469). Evening (MEQ ⩽ 41), intermediate (41 < MEQ < 59), and morning type (MEQ ⩾ 59) categories were the exposures. We modeled daily CPAP use (hours per night) over a 6-month period, using a linear mixed model, adjusted for covariates (e.g., age, sex, marital status). To assess mechanisms of the association, we performed mediation analyses using sleep duration, weekend catch-up sleep, depression, and other factors. Results: Most participants were obese men with severe OSA (body mass index of 32.3 ± 7.3 kg/m2, 65% male, and apnea-hypopnea index 39.8 ± 24.6/h). Participants were 44% morning, 47% intermediate, and 8% evening chronotype. Participants with the morning chronotype reported the shortest sleep duration on weekends (7.3 vs. 7.6 and 7.9 h/night) compared with the intermediate and evening types. Participants with the morning chronotype exhibited a 40-min/night higher CPAP use (P = 0.001) than persons with the intermediate chronotype. This relationship was mildly attenuated (32.8 min/night; P = 0.011) after adjustment for covariates. None of the selected factors (e.g., sleep duration, weekend catch-up sleep) exhibited a significant mediation effect. Conclusions: Morning chronotype is associated with a clinically meaningful increase in CPAP adherence compared with other chronotypes. Mechanisms of this association require further study. Chronotype may be a novel predictor of CPAP adherence. Clinical trial registered with www.clinicaltrials.gov (NCT00051363).

Habitual Physical Activity of People with or at Risk of Diabetes-Related Foot Complications

Regular physical activity is an important component of diabetes management. However, there are limited data on the habitual physical activity of people with or at risk of diabetes-related foot complications. The aim of this study was to describe the habitual physical activity of people with or at risk of diabetes-related foot complications in regional Australia. Twenty-three participants with diabetes from regional Australia were recruited with twenty-two participants included in subsequent analyses: no history of ulcer (N = 11) and history of ulcer (N = 11). Each participant wore a triaxial accelerometer (GT3X+; ActiGraph LLC, Pensacola, FL, USA) on their non-dominant wrist for 14 days. There were no significant differences between groups according to both participant characteristics and physical activity outcomes. Median minutes per day of moderate-to-vigorous physical activity (MVPA) were 9.7 (IQR: 1.6-15.7) while participants recorded an average of 280 ± 78 min of low-intensity physical activity and 689 ± 114 min of sedentary behaviour. The sample accumulated on average 30 min of slow walking and 2 min of fast walking per day, respectively. Overall, participants spent very little time performing MVPA and were largely sedentary. It is important that strategies are put in place for people with or at risk of diabetes-related foot complications in order that they increase their physical activity significantly in accordance with established guidelines.

Management of hyperglycaemia in type 2 diabetes, 2022. A consensus report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD)

The American Diabetes Association and the European Association for the Study of Diabetes convened a panel to update the previous consensus statements on the management of hyperglycaemia in type 2 diabetes in adults, published since 2006 and last updated in 2019. The target audience is the full spectrum of the professional healthcare team providing diabetes care in the USA and Europe. A systematic examination of publications since 2018 informed new recommendations. These include additional focus on social determinants of health, the healthcare system and physical activity behaviours including sleep. There is a greater emphasis on weight management as part of the holistic approach to diabetes management. The results of cardiovascular and kidney outcomes trials involving sodium-glucose cotransporter-2 inhibitors and glucagon-like peptide-1 receptor agonists, including assessment of subgroups, inform broader recommendations for cardiorenal protection in people with diabetes at high risk of cardiorenal disease. After a summary listing of consensus recommendations, practical tips for implementation are provided.

Historical development of accelerometry measures and methods for physical activity and sedentary behavior research worldwide: A scoping review of observational studies of adults

This scoping review identified observational studies of adults that utilized accelerometry to assess physical activity and sedentary behavior. Key elements on accelerometry data collection were abstracted to describe current practices and completeness of reporting. We searched three databases (PubMed, Web of Science, and SPORTDiscus) on June 1, 2021 for articles published up to that date. We included studies of non-institutionalized adults with an analytic sample size of at least 500. The search returned 5686 unique records. After reviewing 1027 full-text publications, we identified and abstracted accelerometry characteristics on 155 unique observational studies (154 cross-sectional/cohort studies and 1 case control study). The countries with the highest number of studies included the United States, the United Kingdom, and Japan. Fewer studies were identified from the continent of Africa. Five of these studies were distributed donor studies, where participants connected their devices to an application and voluntarily shared data with researchers. Data collection occurred between 1999 to 2019. Most studies used one accelerometer (94.2%), but 8 studies (5.2%) used 2 accelerometers and 1 study (0.6%) used 4 accelerometers. Accelerometers were more commonly worn on the hip (48.4%) as compared to the wrist (22.3%), thigh (5.4%), other locations (14.9%), or not reported (9.0%). Overall, 12.7% of the accelerometers collected raw accelerations and 44.6% were worn for 24 hours/day throughout the collection period. The review identified 155 observational studies of adults that collected accelerometry, utilizing a wide range of accelerometer data processing methods. Researchers inconsistently reported key aspects of the process from collection to analysis, which needs addressing to support accurate comparisons across studies.

Type 2 diabetes

Type 2 diabetes accounts for nearly 90% of the approximately 537 million cases of diabetes worldwide. The number affected is increasing rapidly with alarming trends in children and young adults (up to age 40 years). Early detection and proactive management are crucial for prevention and mitigation of microvascular and macrovascular complications and mortality burden. Access to novel therapies improves person-centred outcomes beyond glycaemic control. Precision medicine, including multiomics and pharmacogenomics, hold promise to enhance understanding of disease heterogeneity, leading to targeted therapies. Technology might improve outcomes, but its potential is yet to be realised. Despite advances, substantial barriers to changing the course of the epidemic remain. This Seminar offers a clinically focused review of the recent developments in type 2 diabetes care including controversies and future directions.

Management of Hyperglycemia in Type 2 Diabetes, 2022. A Consensus Report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD)

The American Diabetes Association and the European Association for the Study of Diabetes convened a panel to update the previous consensus statements on the management of hyperglycemia in type 2 diabetes in adults, published since 2006 and last updated in 2019. The target audience is the full spectrum of the professional health care team providing diabetes care in the U.S. and Europe. A systematic examination of publications since 2018 informed new recommendations. These include additional focus on social determinants of health, the health care system, and physical activity behaviors, including sleep. There is a greater emphasis on weight management as part of the holistic approach to diabetes management. The results of cardiovascular and kidney outcomes trials involving sodium-glucose cotransporter 2 inhibitors and glucagon-like peptide 1 receptor agonists, including assessment of subgroups, inform broader recommendations for cardiorenal protection in people with diabetes at high risk of cardiorenal disease. After a summary listing of consensus recommendations, practical tips for implementation are provided.

The relationship between chronotype, night eating behavior and fear of COVID-19 in academics

Academics are an occupational group that works at an intense pace. The number of studies on chronotype and night eating behavior in academics is limited, and there is insufficient data on whether fear of COVID-19 is also a risk for developing eating disorders. This study aimed to investigate the relationship between chronotype and night eating syndrome (NES) and examine the influence of fear of COVID-19 on night eating behavior in academics. The study data were collected using the personal information form, "Morningness-Eveningness Questionnaire, The Night Eating Questionnaire (NEQ), and the Fear of COVID-19 Scale." According to the chronotypes of the academicians, it was determined that the score compatible with NES and the scores of the Fear of COVID-19 Scale differed statistically significantly, and the score compatible with NES and Fear of COVID-19 Scale scores were also higher in the evening type at a rate of 29.2% compared to other chronotypes (p < .05). The Fear of COVID-19 scale and Morningness-Eveningness Questionnaire scores were significantly correlated with the Night Eating Questionnaire (R = .391 R² = .153 p < .05). The variables of the Fear of COVID-19 Scale and the Morningness-Eveningness Questionnaire explained 15% of the total variance of the Night Eating Questionnaire scores. Considering that academics are a group that works without the concept of overtime and whose work intensity is high, it is clear that studies should be conducted to raise awareness to protect the physical health of academics and prevent the development of eating disorders. There is a need for studies that question the relationship between chronotype, diet, and health.

Association between Chronotype, Physical Activity and Sedentary Behaviour: A Systematic Review

BACKGROUND

The aim of this systematic review is to compile and assess the scientific evidence about the relationship between chronotypes and physical activity (PA). Methods: A systematic review was executed using a structured electronic search in PubMED, Cochrane Library, PsycInfo and Trip Database. The searches employed keywords such as chronotype, sleep, acrophase, chronotype preference, morningness, physical activity and sedentary, using MeSH terms. JBI critical tools were used to appraise methodological aspects.

RESULTS

This systematic review includes 23 studies and a total of 505,375 participants. The results show that evening chronotypes are associated with less PA and more time in sedentary activities. It occurs independently of the instruments used to collect information about chronotype and PA. Nevertheless, this association could be mitigated in young populations and university stages.

CONCLUSIONS

The chronotypes are clearly associated with the PA level and the sedentary behaviour, especially in the population over their mid-twenties. Evening chronotypes are associated with less PA and more time in sedentary activities compared to morning chronotypes.

Device-assessed sleep and physical activity in individuals recovering from a hospital admission for COVID-19: a multicentre study

Background

The number of individuals recovering from severe COVID-19 is increasing rapidly. However, little is known about physical behaviours that make up the 24-h cycle within these individuals. This study aimed to describe physical behaviours following hospital admission for COVID-19 at eight months post-discharge including associations with acute illness severity and ongoing symptoms.

Methods

One thousand seventy-seven patients with COVID-19 discharged from hospital between March and November 2020 were recruited. Using a 14-day wear protocol, wrist-worn accelerometers were sent to participants after a five-month follow-up assessment. Acute illness severity was assessed by the WHO clinical progression scale, and the severity of ongoing symptoms was assessed using four previously reported data-driven clinical recovery clusters. Two existing control populations of office workers and individuals with type 2 diabetes were comparators.

Results

Valid accelerometer data from 253 women and 462 men were included. Women engaged in a mean ± SD of 14.9 ± 14.7 min/day of moderate-to-vigorous physical activity (MVPA), with 12.1 ± 1.7 h/day spent inactive and 7.2 ± 1.1 h/day asleep. The values for men were 21.0 ± 22.3 and 12.6 ± 1.7 h /day and 6.9 ± 1.1 h/day, respectively. Over 60% of women and men did not have any days containing a 30-min bout of MVPA. Variability in sleep timing was approximately 2 h in men and women. More severe acute illness was associated with lower total activity and MVPA in recovery. The very severe recovery cluster was associated with fewer days/week containing continuous bouts of MVPA, longer total sleep time, and higher variability in sleep timing. Patients post-hospitalisation with COVID-19 had lower levels of physical activity, greater sleep variability, and lower sleep efficiency than a similarly aged cohort of office workers or those with type 2 diabetes.

Conclusions

Those recovering from a hospital admission for COVID-19 have low levels of physical activity and disrupted patterns of sleep several months after discharge. Our comparative cohorts indicate that the long-term impact of COVID-19 on physical behaviours is significant.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12966-022-01333-w.

Effect of exercises according to the circadian rhythm in type 2 diabetes: Parallel-group, single-blind, crossover study

BACKGROUND AND AIM

To evaluate the effectiveness of structured exercise appropriate the circadian rhythm in terms of blood sample test (BST), functionality and quality of life (QoL) in individuals with type 2 diabetes.

METHODS AND RESULTS

This was a parallel-group, single-blind, crossover study. Thirty individuals with type 2 diabetes aged 35-65 years were enrolled in the study and allocated into 2 groups as the Morning Chronotype (MC) Group (n = 15) and the Evening Chronotype (EC) Group (n = 15) using Morningness-Eveningness Questionnaire which was used to determine the chronotypes. Participants were evaluated in terms of BST, functionality and QoL at the beginning of the study (T0), at 6 (T1), 12 (T2), and 18 (T3) weeks after the study started. A structured exercise program for 3 days a week over 6 weeks was applied in accordance with the chronotypes (T1-T2) and cross-controlled for the chronotypes (T2-T3). Significant differences were found in favor of the exercise given at the appropriate time for the chronotype in all parameters in both groups within groups (T0-T1-T2-T3) (p < 0.05). In the time∗group interactions, exercise in accordance with the appropriate chronotype in both groups provided the highest statistical improvement in all parameters (p < 0.05).

CONCLUSION

It was concluded that structured exercise performed at the appropriate time for chronotype improves HbA_1c, fasting blood glucose, HDL-LDL cholesterol, triglyceride, total cholesterol, functionality and quality of life in type 2 diabetes. This variation in blood values was observed to reflect the quantitative effects of exercise administered according to the circadian rhythm in individuals with type 2 diabetes.

TRIAL REGISTRATION

ClinicalTrials.gov (NCT04427488). The protocol of the study was registered at ClinicalTrials.gov (NCT04427488).

Chronotype and well-being in adults with established type 2 diabetes: A cross-sectional study

AIMS

'Chronotype' describes an individual's sleep-wake schedule, and can be classified into morning, intermediate or evening types. Evening chronotype has been widely associated with increased cardiometabolic risk and mortality in people with type 2 diabetes. We explored associations between chronotype and markers of well-being in people with type 2 diabetes.

METHODS

Participants of the 'Chronotype of Patients with Type 2 Diabetes and Effect on Glycaemic Control' (CODEC) observational study completed questionnaires to determine chronotype (Morningness-Eveningness Questionnaire, MEQ) and concurrent measures of well-being (Diabetes-related Distress scale, Patient Health Questionnaire-9 to measure depression, and Self-Compassion Scale), as a secondary endpoint of the study. Adjusted generalised linear models were used to compare well-being between chronotype subgroups in this cohort.

RESULTS

Of the 808 individuals included in the CODEC study, from convenience sampling, 476 individuals completed the psychosocial questionnaire substudy. Of these, 67% (n = 321) were male, and 86% (n = 408) were white European. From the MEQ, 24% (n = 114) were morning chronotype, 24% (n = 113) were evening and 52% (n = 249) were intermediate chronotype. Diabetes-related distress was significantly higher in evening chronotypes (exponentiated adjusted coefficient = 1.18 (CI: 1.05-1.32)), compared to morning (p_adjusted  = 0.005) and intermediate chronotypes (p_adjusted  = 0.039). Similarly, depression was significantly higher in evening chronotypes (exponentiated adjusted coefficient = 1.84 (CI: 1.28-2.65)) compared to morning (p_adjusted  = 0.001) and intermediate chronotypes (p_adjusted  = 0.016).

DISCUSSION

Evening chronotype in people with type 2 diabetes may be associated with higher levels of diabetes-related distress and depression. These findings warrant further investigation to establish causality and evidence-based interventions that negate the effects of evening chronotype in people with type 2 diabetes.

The association between metabolic parameters and evening chronotype and social jetlag in non-shift workers: A meta-analysis

AIMS

The aim of the study was to evaluate the association between evening chronotype and social jetlag (SJL) with obesity, blood glucose and lipid levels in non-shift working adults.

METHODS

The databases of MEDLINE, EMBASE and Cochrane Reviews were searched for studies analyzing the metabolic parameters among groups of different chronotypes or SJL until Feb 2022. Weighted mean difference (WMD) and 95% confidence intervals (CI) were used to analyze the association between these parameters and chronotypes or SJL.

RESULTS

A total of 27 studies were included in this meta-analysis. Compared with morning chronotype, the participants with evening chronotype had higher body mass index (BMI) (WMD= 0.44 kg/m², 95%CI, 0.30 to 0.57 kg/m², p<0.001), higher fasting blood glucose level (WMD= 5.83mg/dl, 95%CI, 3.27to 8.38 mg/dl, p<0.001), higher total cholesterol level (WMD= 6.63mg/dl, 95%CI, 0.69 to 12.56 mg/dl, p=0.03), and lower high density lipoprotein cholesterol (HDL-C) level (WMD= -1.80mg/dl, 95%CI, -2.30 to -1.31 mg/dl, p<0.001). Compared with the participants with small SJL, the participants with large SJL had larger waist circumference (WMD= 0.80cm, 95%CI, 0.77 to 0.83cm, p<0.001).

CONCLUSIONS

Evening chronotype and SJL were associated with obesity and unfavorable metabolic parameters of glucose and lipid metabolism.

SYSTEMATIC REVIEW REGISTRATION

https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42022303401.

The cross talk between chronotype, depression symptomatology, and glycaemic control among sudanese patients with diabetes mellitus: A case-control study

Aim of the Study:

There is an increasing awareness about chronotype and depression among patients with diabetes mellitus as commonly ignored serious association. We aimed to investigate the same among patients with type 2 diabetes mellitus and their relation to glycaemic control.

Subjects' and Methods:

This case-control study conducted at two diabetes centers in Omdurman, Sudan during the period from April 2019 to September 2019. Ninety-two patient with type 2 diabetes and 94 controls signed a written informed consent then interviewed using a structured questionnaire based on the morningness–eveningness scale and the 12-item general health questionnaire; A blood sample was taken for the glycated haemoglobin to assess glycaemic control. The Statistical Package for Social Silences was used for Data analysis.

Results:

They were 92 patients with diabetes (58.7% women) and 94 healthy control subjects (52.1% women); matched for ages (57.03 ± 8.59 for diabetic patients and 58.46 ± 10.58 years for control subjects) and sex. Morning chronotype was reported in 95.3% vs. 47.5% and intermediate chronotype was evident in 52.4% vs. 4.3% in controls and patients respectively, P < 0.05. Depression symptomatology was found in 76.1% of patients with diabetes vs. 40.4% of control subjects, P < 0.05. No association was shown between depression symptomatology, chronotype, age, sex, and HbA1c, P > 0.05.

Conclusion:

Sudanese patients with diabetes were more likely intermediate, less morning chronotype, and more depressed compared to their counterparts. No association was found between depression symptomatology and other patient's characters. Larger studies investigating the risk behind depression, chrono-nutrition, and social jetlag among patients with diabetes are needed.

Timing of objectively-collected physical activity in relation to body weight and metabolic health in sedentary older people: a cross-sectional and prospective analysis

BACKGROUND

Little is known about the impact of timing as opposed to frequency and intensity of daily physical activity on metabolic health. Therefore, we assessed the association between accelerometery-based daily timing of physical activity and measures of metabolic health in sedentary older people.

METHODS

Hourly mean physical activity derived from wrist-worn accelerometers over a 6-day period was collected at baseline and after 3 months in sedentary participants from the Active and Healthy Ageing study. A principal component analysis (PCA) was performed to reduce the number of dimensions (e.g. define periods instead of separate hours) of hourly physical activity at baseline and change during follow-up. Cross-sectionally, a multivariable-adjusted linear regression analysis was used to associate the principal components, particularly correlated with increased physical activity in data-driven periods during the day, with body mass index (BMI), fasting glucose and insulin, HbA1c and the homeostatic model assessment for insulin resistance (HOMA-IR). For the longitudinal analyses, we calculated the hourly changes in physical activity and change in metabolic health after follow-up.

RESULTS

We included 207 individuals (61.4% male, mean age: 64.8 [SD 2.9], mean BMI: 28.9 [4.7]). Higher physical activity in the early morning was associated with lower fasting glucose (-2.22%, 95% CI: -4.19, -0.40), fasting insulin (-13.54%, 95%CI: -23.49, -4.39), and HOMA-IR (-16.07%, 95%CI: -27.63, -5.65). Higher physical activity in the late afternoon to evening was associated with lower BMI (-2.84%, 95% CI: -4.92, -0.70). Higher physical activity at night was associated with higher BMI (2.86%, 95% CI: 0.90, 4.78), fasting glucose (2.57%, 95% CI: 0.70, 4.30), and HbA1c (2.37%, 95% CI: 1.00, 3.82). Similar results were present in the prospective analysis.

CONCLUSION

Specific physical activity timing patterns were associated with more beneficial metabolic health, suggesting particular time-dependent physical activity interventions might maximise health benefits.

Chronotype Differences in Energy Intake, Cardiometabolic Risk Parameters, Cancer, and Depression: A Systematic Review with Meta-Analysis of Observational Studies

Chronotype is a behavioral manifestation of the internal circadian clock system. It refers to the specific activity-rest preference of an individual over a 24-h period and can be assessed using different methodologies that classify individuals into morning or evening chronotype. In recent years, several studies have suggested a relation between individual chronotype, eating habits, and the risk of developing obesity and other conditions. Our aim was to evaluate the association between chronotype, energy intake, and health status through a meta-analytic approach. A comprehensive search of MEDLINE, Embase, Scopus, Web of Science, and Cochrane Database was conducted. Observational studies that reported a measure of association between chronotype, energy intake, and health indicators were considered eligible. Overall, 39 observational studies (37 cross-sectional studies, 2 prospective cohort studies) were included in the systematic review, with a total of 377,797 subjects. By comparing morning and evening subjects, pooled analyses of cross-sectional studies showed significantly (P < 0.001) higher concentrations of blood glucose [mean difference (MD): 7.82; 95% CI: 3.18, 12.45], glycated hemoglobin (MD: 7.64; 95% CI: 3.08, 12.21), LDL cholesterol (MD: 13.69; 95% CI: 6.84, 20.54), and triglycerides (MD: 12.62; 95% CI: 0.90, 24.35) in evening subjects. Furthermore, an association between evening type and the risk of diabetes (OR: 1.30; 95% CI: 1.20, 1.41), cancer (OR: 1.18; 95% CI: 1.08, 1.30), and depression (OR: 1.86; 95% CI: 1.20, 2.88) was reported. Regarding the other outcomes examined, no significant differences were observed between the groups in terms of energy intake, anthropometric parameters, blood pressure, insulin, total and HDL cholesterol, and hypertension risk. In conclusion, evening chronotype was associated with a worse cardiometabolic risk profile and higher risk of diabetes, cancer, and depression. Further studies are needed to confirm these results and to better elucidate the interplay between chronotype, nutrition, and health status. This systematic review was registered at www.crd.york.ac.uk/prospero/ as CRD42021231044.

Evening chronotype is associated with elevated biomarkers of cardiometabolic risk in the EpiHealth cohort: a cross-sectional study

STUDY OBJECTIVES

Individuals with evening chronotype have a higher risk of cardiovascular and metabolic disorders, although the underlying mechanisms are not well understood. In a population-based cohort, we aimed to investigate the association between chronotype and 242 circulating proteins from three panels of established or candidate biomarkers of cardiometabolic processes.

METHODS

In 2,471 participants (49.7% men, mean age 61.2±8.4 SD years) from the EpiHealth cohort, circulating proteins were analyzed with a multiplex proximity extension technique. Participants self-reported their chronotype on a five-level scale from extreme morning to extreme evening chronotype. With the intermediate chronotype set as the reference, each protein was added as the dependent variable in a series of linear regression models adjusted for confounders. Next, the chronotype coefficients were jointly tested and the resulting p-values adjusted for multiple testing using false discovery rate (5%). For the associations identified, we then analyzed the marginal effect of each chronotype category.

RESULTS

We identified 17 proteins associated with chronotype. Evening chronotype was positively associated with proteins previously linked to insulin resistance and cardiovascular risk, namely retinoic acid receptor protein 2, fatty acid-binding protein adipocyte, tissue-type plasminogen activator, and plasminogen activator inhibitor 1 (PAI-1). Additionally, PAI-1 was inversely associated with the extreme morning chronotype.

CONCLUSIONS

In this population-based study, proteins previously related with cardiometabolic risk were elevated in the evening chronotypes. These results may guide future research in the relation between chronotype and cardiometabolic disorders.

Morningness-eveningness assessment from mobile phone communication analysis

Human behaviour follows a 24-h rhythm and is known to be governed by the individual chronotypes. Due to the widespread use of technology in our daily lives, it is possible to record the activities of individuals through their different digital traces. In the present study we utilise a large mobile phone communication dataset containing time stamps of calls and text messages to study the circadian rhythms of anonymous users in a European country. After removing the effect of the synchronization of East-West sun progression with the calling activity, we used two closely related approaches to heuristically compute the chronotypes of the individuals in the dataset, to identify them as morning persons or “larks” and evening persons or “owls”. Using the computed chronotypes we showed how the chronotype is largely dependent on age with younger cohorts being more likely to be owls than older cohorts. Moreover, our analysis showed how on average females have distinctly different chronotypes from males. Younger females are more larkish than males while older females are more owlish. Finally, we also studied the period of low calling activity for each of the users which is considered as a marker of their sleep period during the night. We found that while “extreme larks” tend to sleep more than “extreme owls” on the weekends, we do not observe much variation between them on weekdays. In addition, we have observed that women tend to sleep even less than males on weekdays while there is not much difference between them on the weekends.

Associations of midpoint of sleep and night sleep duration with type 2 diabetes mellitus in Chinese rural population: the Henan rural cohort study

Background

The study aimed to investigate the independent and combined effects of midpoint of sleep and night sleep duration on type 2 diabetes mellitus (T2DM) in areas with limited resources.

Methods

A total of 37,276 participants (14,456 men and 22,820 women) were derived from the Henan Rural Cohort Study. Sleep information was assessed based on the Pittsburgh Sleep Quality Index. Logistic regression models and restricted cubic splines were used to estimate the relationship of the midpoint of sleep and night sleep duration with T2DM.

Results

Of the 37,276 included participants, 3580 subjects suffered from T2DM. The mean midpoint of sleep among the Early, Intermediate and Late groups were 1:05 AM ±23 min, 1:56 AM ±14 min, and 2:57 AM ±34 min, respectively. Compared to the Intermediate group, adjusted odds ratios (ORs) and 95% confidence interval (CI) of T2DM were 1.13 (1.04–1.22) and 1.14 (1.03–1.26) in the Early group and the Late group. Adjusted OR (95% CI) for T2DM compared with the reference (7- h) was 1.28 (1.08–1.51) for longer (≥ 10 h) night sleep duration. The combination of late midpoint of sleep and night sleep duration (≥ 9 h) increased 38% (95% CI 10–74%) prevalence of T2DM. These associations were more obvious in women than men.

Conclusions

Late and early midpoint of sleep and long night sleep duration were all associated with higher prevalence of T2DM. Meanwhile, midpoint of sleep and night sleep duration might have combined effects on the prevalence of T2DM, which provided potential health implications for T2DM prevention, especially in rural women.

Trial registration

The Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699). Date of registration: 2015-07-06.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-10833-6.