A randomized controlled trial to assess if changing sleep timing can improve glucose metabolism in people with prediabetes and type 2 diabetes.

BACKGROUND: Social jetlag is a chronic disruption of sleep timing that is characterized by different sleep timing during workdays and free days. Social jetlag has been associated with disturbed glucose metabolism, insulin resistance, and increased risk of metabolic syndrome and type 2 diabetes. In this study, we aim to investigate whether a combination of bright light therapy in the morning, bright light reduction in the evening and sleep advance instructions for 3 weeks reduces social jetlag and if this results in improvement of glycemic and metabolic control, sleep, mood and quality of life after 3 and 12 weeks in people with prediabetes and type 2 diabetes and to assess possible mediators, compared to regular sleep habits. METHODS: In this randomized controlled trial, 60 people with prediabetes or type 2 diabetes with > 1 h social jetlag will be recruited. The intervention consists of bright light therapy (5000 lx) emitted by Vitamine-L (Lumie, UK) for 30 min each morning, combined with the advice to follow sleep advance instructions and to wear bright light-dimming goggles every evening for a period of 3 weeks. The control group adheres to their regular sleep habits and conditions. The primary outcome is glycated hemoglobin (HbA1c) after 12 weeks comparing the intervention and control in an intention-to-treat analysis. Secondary outcomes at 3 and 12 weeks are (1) social jetlag; (2) insulin sensitivity, fasting blood glucose, glucose-lowering medication use, and frequency of perceived hypoglycemia; (3) metabolic outcomes, including body mass index (BMI), waist circumference, body fat percentage, and blood pressure; (4) mood, including depression, fatigue and anxiety (measured with questionnaires); and (5) quality of life measured using EQ5D questionnaire. To assess other factors that might play a role as possible mediators, we will measure (para)sympathetic nervous system activity assessed with ECGs and electrochemical skin conductance tests, sleep quality and sleep phase distribution assessed with a sleep measuring headband (ZMax), the Dim Light Melatonin Onset in saliva samples (in a subgroup) at 3 and 12 weeks, the feeling of satiety and satiation with a 10-cm visual analog scale (VAS), diet using a food frequency questionnaire, and physical activity using an accelerometer (ActiGraph). DISCUSSION: Social jetlag can contribute to poorer glycemic control and metabolic control in those with type 2 diabetes. With this intervention, we aim to reduce social jetlag and thereby improve glycemic and metabolic control. This could offer a way to improve overall population health and to reduce the disease burden of type 2 diabetes. TRIAL REGISTRATION: ISRCTN registry ISRCTN11967109 . Registered on 9 May 2024.

The effect of cognitive behavioral therapy for insomnia on sleep and glycemic outcomes in people with type 2 diabetes: A randomized controlled trial.

STUDY OBJECTIVES: Investigate whether aiding sleep by online cognitive behavioral therapy for insomnia (CBT-I) can improve glycemic and metabolic control, mood, quality of life (QoL) and insomnia symptoms in people with type 2 diabetes and assess the mediating role of lifestyle factors. METHODS: Adults with type 2 diabetes and insomnia symptoms were randomly assigned to CBT-I or care as usual. At baseline, three and six months we assessed HbA1c as primary outcome and glycemic control, metabolic outcomes, sleep, mood and QoL as secondary outcomes. Mixed models were used to determine within-person and between-persons differences in outcomes and mediation analysis for lifestyle factors. RESULTS: We randomized 29 participants to CBT-I and 28 to care as usual. Intention-to-treat analysis showed no significant differences in glycemic control, metabolic outcomes, anger, distress or QoL, but showed a significantly larger decrease in insomnia (-1.37(2.65: 0.09)) and depressive symptoms (-0.92(-1.77: 0.06)) and increase in BMI (0.29 kg/m2(0.00:0.57)) in the intervention compared to the control group. Only half of the intervention participants completed the CBT-I. Per protocol analysis showed a not statistically significant decrease in HbA1c (-2.10 mmol/l(-4.83:0.63)) and glucose (-0.39 mmol/l(-1.19:0.42)), metabolic outcomes and increase in QoL. Furthermore, the intervention group showed a significant decrease in insomnia (-2.22(-3.65: 0.78)) and depressive symptoms (-1.18(-2.17: 0.19)) compared to the control group. Lifestyle factors partially mediated the effect of the intervention. CONCLUSIONS: CBT-I might improve insomnia symptoms and mood, and perhaps improves glycemic control, albeit not significant, in people with type 2 diabetes and insomnia symptoms, compared to care as usual.

The association of cardiometabolic, diet and lifestyle parameters with plasma glucagon-like peptide-1: An IMI DIRECT study.

CONTEXT: The role of glucagon-like peptide-1(GLP-1) in Type 2 diabetes (T2D) and obesity is not fully understood. OBJECTIVE: We investigate the association of cardiometabolic, diet and lifestyle parameters on fasting and postprandial GLP-1 in people at risk of, or living with, T2D. METHOD: We analysed cross-sectional data from the two Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) cohorts, cohort 1(n=2127) individuals at risk of diabetes; cohort 2 (n=789) individuals with new-onset of T2D. RESULTS: Our multiple regression analysis reveals that fasting total GLP-1 is associated with an insulin resistant phenotype and observe a strong independent relationship with male sex, increased adiposity and liver fat particularly in the prediabetes population. In contrast, we showed that incremental GLP-1 decreases with worsening glycaemia, higher adiposity, liver fat, male sex and reduced insulin sensitivity in the prediabetes cohort. Higher fasting total GLP-1 was associated with a low intake of wholegrain, fruit and vegetables inpeople with prediabetes, and with a high intake of red meat and alcohol in people with diabetes. CONCLUSION: These studies provide novel insights into the association between fasting and incremental GLP-1, metabolic traits of diabetes and obesity, and dietary intake and raise intriguing questions regarding the relevance of fasting GLP-1 in the pathophysiology T2D.

The effect of preprandial versus postprandial physical activity on glycaemia: Meta-analysis of human intervention studies.

This meta-analysis aims to investigate the effect of preprandial physical activity (PA) versus postprandial PA on glycaemia in human intervention studies. Medline and Embase.com were searched until February 2023 for intervention studies in adults, directly comparing preprandial PA versus postprandial PA on glycaemia. Studies were screened using ASReview (34,837) and full texts were read by two independent reviewers (42 full text, 28 included). Results were analysed using pooled mean differences in random-effects models. Studies were either acute response studies (n = 21) or Randomized Controlled Trials (RCTs) over multiple weeks (n = 7). In acute response studies, postprandial outcomes followed the expected physiological patterns, and outcomes measured over 24 h showed no significant differences. For the RCTs, glucose area under the curve during a glucose tolerance test was slightly, but not significantly lower in preprandial PA vs postprandial PA (-0.29 [95 %CI:-0.66, 0.08] mmol/L, I2 = 64.36 %). Subgroup analyses (quality, health status, etc.) did not significantly change the outcomes. In conclusion, we found no differences between preprandial PA versus postprandial PA on glycaemia both after one PA bout as well as after multiple weeks of PA. The studies were of low to moderate quality of evidence as assessed by GRADE, showed contradictive results, included no long-term studies and used various designs and populations. We therefore need better RCTs, with more similar designs, in larger populations and longer follow-up periods (≥12 weeks) to have a final answer on the questions eat first, then exercise, or the reverse?

Genomics Research of Lifetime Depression in the Netherlands: The BIObanks Netherlands Internet Collaboration (BIONIC) Project.

In this cohort profile article we describe the lifetime major depressive disorder (MDD) database that has been established as part of the BIObanks Netherlands Internet Collaboration (BIONIC). Across the Netherlands we collected data on Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) lifetime MDD diagnosis in 132,850 Dutch individuals. Currently, N = 66,684 of these also have genomewide single nucleotide polymorphism (SNP) data. We initiated this project because the complex genetic basis of MDD requires large population-wide studies with uniform in-depth phenotyping. For standardized phenotyping we developed the LIDAS (LIfetime Depression Assessment Survey), which then was used to measure MDD in 11 Dutch cohorts. Data from these cohorts were combined with diagnostic interview depression data from 5 clinical cohorts to create a dataset of N = 29,650 lifetime MDD cases (22%) meeting DSM-5 criteria and 94,300 screened controls. In addition, genomewide genotype data from the cohorts were assembled into a genomewide association study (GWAS) dataset of N = 66,684 Dutch individuals (25.3% cases). Phenotype data include DSM-5-based MDD diagnoses, sociodemographic variables, information on lifestyle and BMI, characteristics of depressive symptoms and episodes, and psychiatric diagnosis and treatment history. We describe the establishment and harmonization of the BIONIC phenotype and GWAS datasets and provide an overview of the available information and sample characteristics. Our next step is the GWAS of lifetime MDD in the Netherlands, with future plans including fine-grained genetic analyses of depression characteristics, international collaborations and multi-omics studies.

Is the association between social jetlag and BMI mediated by lifestyle? A cross-sectional survey study in the Dutch general population.

OBJECTIVE: Social jetlag is a discordance between the social and biological rhythm and is associated with higher HbA1c, higher BMI, and higher odds of obesity. The pathways that could explain these associations are still debated. This study aims to assess the mediating role of several lifestyle factors in the cross-sectional association between social jetlag and BMI. METHODS: We used cross-sectional data from 1784 adults from urban areas in the Netherlands, collected in 2019. Social jetlag (difference in midpoint of sleep between week and weekend nights) was categorized as low(<1 h), moderate(1-2h), and high(>2 h). BMI(kg/m2) was calculated from self-reported height and weight. The association between social jetlag and BMI was assessed using linear regression, adjusted for sex, age, education, and sleep duration and stratified for the effect modifier stress (high vs. low). Mediation analysis was performed for self-reported smoking, physical activity, alcohol consumption, and adherence to a healthy diet. RESULTS: High social jetlag was associated with higher BMI (0.69 kg/m2,95%CI 0.05;1.33). This association was stronger in people with high stress (0.93 kg/m2,95%CI 0.09;1.76). Social jetlag was also associated with higher odds of smoking, lower physical activity, higher alcohol consumption, and lower healthy diet adherence. In people with high stress, these factors mediated 10-15% of the association between social jetlag and BMI. CONCLUSIONS: Social jetlag is associated with higher BMI and this association is stronger in people with high stress. In people with high stress, healthy diet adherence mediated 12% of this association. Other pathways involved in this association should be further investigated.

Cross-sectional associations between 24-hour movement behaviors and cardiometabolic health among adults with type 2 diabetes mellitus: A comparison according to weight status.

OBJECTIVES: Type 2 diabetes mellitus (T2DM) is a chronic disease associated with overweight and obesity. Evidence suggests that 24-hour movement behaviors (24 h-MBs) play a crucial role in cardiometabolic health. However, it is not yet known if 24 h-MBs differ between weight status groups among people with T2DM (PwT2DM) and how 24 h-MBs are associated with their cardiometabolic health. DESIGN: Cross-sectional study. METHODS: Cardiometabolic variables (i.e. Body Mass Index (BMI), waist circumference (WC), HbA1c, fasting glucose, triglycerides, total-cholesterol, HDL-cholesterol, LDL-cholesterol, blood pressure) and 24 h-MBs (accelerometry and sleep-diary) of 1001 PwT2DM were collected. Regression models using compositional data analysis explored differences in 24 h-MBs between weight status groups and analyzed associations with cardiometabolic variables. RESULTS: The 24 h-MBs of PwT2DM being obese consisted of less sleep, light physical activity (LPA) and moderate to vigorous physical activity (MVPA) and more sedentary time (ST) per day as compared to PwT2DM being overweight or normal weight (p < 0.001). Regardless of weight status, the largest associations were found when reallocating 20 min a day from ST into MVPA for BMI (-0.32 kg/m2; [-0.55; -0.09], -1.09 %), WC (-1.44 cm, [-2.26; -0.62], -1.35 %) and HDL-cholesterol (0.02 mmol/l, [0.01, 0.02], +1.59 %), as well as from ST into LPA for triglycerides (-0.04 mmol/l, [-0.05; -0.03], -2.3 %). Moreover, these associations were different when stratifying people by short-to-average (7.7 h/night) versus long sleep (9.3 h/night) period. CONCLUSIONS: This study highlights the importance of 24 h-MBs in the cardiometabolic health of PwT2DM. Shifting time from ST and/or sleep toward LPA or MVPA might theoretically benefit cardiometabolic health among relatively inactive PwT2DM, irrespective of weight status.

The interaction between the community food environment and cooking skills in association with diet-related outcomes in Dutch adults.

OBJECTIVE: We examined whether associations between the food environment, frequency of home cooking, diet quality and BMI were modified by the level of cooking skills. DESIGN: Cross-sectional study using linear and modified Poisson regression models adjusted for age, sex, energy intake, education, income, household size and urbanisation. The frequency of home cooking was categorised into <6 and 6-7 d. Diet quality was based on a validated Dutch healthy diet index (0-150 points). Count of restaurants and food stores were determined by their count in a 1000m buffer around home and work. Cooking skills (score 1-5) were assessed using a validated questionnaire and added as interaction term. SETTING: The Netherlands. PARTICIPANTS: 1461 adults aged 18-65 years. RESULTS: Count of restaurants and food stores were not associated with the frequency of home cooking. A 10-unit higher count of food stores was associated with a higher diet quality (ß: 0·58 (95 % CI (0·04, 1·12)), and a 10-unit higher count of restaurants was associated with a lower BMI kg/m2 (ß: -0·02 (95 % CI (-0·04, -0·004)). Better cooking skills were associated with a higher likelihood of cooking 6-7 d compared with <6 d (risk ratio: 1·24 (95 % CI (1·16, 1·31)) and a higher diet quality (ß: 4·45 (95 % CI (3·27, 5·63)) but not with BMI. We observed no interaction between the food environment and cooking skills (P-for-interaction > 0·1). CONCLUSIONS: Exposure to food stores was associated with a higher diet quality and exposure to restaurants with a lower BMI. Better cooking skills were associated with a higher frequency of home cooking and better diet quality but did not modify associations with the food environment. Future studies should explore different approaches to understand how individuals interact with their food environment.

The entero-endocrine response following a mixed-meal tolerance test with a non-nutritive pre-load in participants with pre-diabetes and type 2 diabetes: A crossover randomized controlled trial proof of concept study.

INTRODUCTION: This crossover randomized controlled trial (RCT) investigated differences in short-term entero-endocrine response to a mixed-meal tolerance test preceded by nutrient sensing between participants with pre-diabetes (pre-T2D) and type 2 diabetes (T2D). Additionally, differences in gut and oral microbiome composition between participants with a high and low entero-endocrine response were investigated. RESEARCH DESIGN AND METHODS: Ten participants with pre-T2D and ten with T2D underwent three test days with pre-loads consisting of either swallowing water (control), or rinsing with a non-nutritive sweetener solution, or swallowing the sweetener solution before a mixed-meal tolerance test. Blood glucose-dependent insulinotropic polypeptide (GIP), glucagon-like peptide-1 (GLP-1), glucagon, glucose, insulin and peptide YY (PYY) were determined at t = -20, 0, 15, 30, 60, 120 and 240 minutes. The composition of the oral and gut microbiome at baseline were also determined. RESULTS: The entero-endocrine response differed by pre-loads, e.g. a lower PYY response after swallowing the non-nutritive sweetener (-3585.2pg/mL [95% CI: -6440.6; -729.8]; p = 0.01). But it also differed by T2D status, e.g. a higher glucose, glucagon and PYY response was found in participants with T2D, compared to those with pre-T2D. Evidence for associations between the oral and gut microbiome composition and the entero-endocrine response was limited. Still, the level of entero-endocrine response was associated with several oral microbiome measures. Higher oral anterior α-diversity was associated with a lower PYY response (e.g. Inverse Simpson index -1357pg/mL [95% CI -2378; -336; 1.24]), and higher oral posterior α-diversitywith a higher GIP response (e.g. Inverse Simpson index 6773pg/mL [95% CI 132; 13414]) in models adjusted for sex, age and T2D status. CONCLUSIONS: Non-nutritive pre-loads influence the entero-endocrine response to a mixed-meal, and this effect varies based on (pre-)T2D status. The entero-endocrine response is likely not associated with the gut microbiome, and there is limited evidence for association with the α-diversity of the oral microbiome composition. TRIAL REGISTRATION: Trial register: Netherlands Trial Register NTR7212, accessible through International Clinical Trials Registry Platform: ICTRP Search Portal (who.int).

Genetic analysis of blood molecular phenotypes reveals common properties in the regulatory networks affecting complex traits.

We evaluate the shared genetic regulation of mRNA molecules, proteins and metabolites derived from whole blood from 3029 human donors. We find abundant allelic heterogeneity, where multiple variants regulate a particular molecular phenotype, and pleiotropy, where a single variant associates with multiple molecular phenotypes over multiple genomic regions. The highest proportion of share genetic regulation is detected between gene expression and proteins (66.6%), with a further median shared genetic associations across 49 different tissues of 78.3% and 62.4% between plasma proteins and gene expression. We represent the genetic and molecular associations in networks including 2828 known GWAS variants, showing that GWAS variants are more often connected to gene expression in trans than other molecular phenotypes in the network. Our work provides a roadmap to understanding molecular networks and deriving the underlying mechanism of action of GWAS variants using different molecular phenotypes in an accessible tissue.

Prolongation of the QTc interval is associated with an increased risk of cardiovascular diseases: The Hoorn study.

BACKGROUND/OBJECTIVE: Prolonged heart rate-corrected QT interval (QTc) on the electrocardiogram (ECG) is maybe associated with the occurrence of cardiovascular diseases (CVD), but the evidence is inconsistent. Therefore, we investigated whether baseline prolongation of the QTc interval is associated with CVD morbidity and mortality and its subtypes and whether glucose tolerance modifies this association in a population-based cohort study with a mean follow-up of 10.8 years. METHODS: We analyzed a glucose tolerance stratified sample (N = 487) from the longitudinal population-based Hoorn Study cohort (age 64 ± 7 years, 48% female). Cox regression was used to investigate the association between sex-specific baseline QTc quartiles and CVD morbidity and mortality. The risk was also estimated per 10 ms increase in QTc. All analyses were adjusted for age, sex, smoking status, systolic blood pressure, prevalent CVD, glucose tolerance status, hypertension and total cholesterol. In addition, stratified analyses were conducted for glucose tolerance status. RESULTS: During a mean follow-up of 10.8 years, 351 CVD events were observed. The adjusted hazard ratios (95% CI) for each 10 ms increase in QTc interval were 1.06 (95% CI: 1.02-1.10) for CVD, 1.06 (95% CI: 0.97-1.15) for acute myocardial infarction, 1.07 (95% CI: 1.01-1.13) for stroke, 1.12 (95% CI: 1.06-1.19) for heart failure, 1.04 (95% CI: 0.96-1.12) for peripheral arterial disease and 1.01 (95% CI:0.95-1.08) for coronary heart disease. Glucose tolerance status did not modify the association (P > 0.2). CONCLUSION/INTERPRETATION: Prolongation of the QTc interval is associated with morbidity and mortality due to general CVD. Glucose tolerance status did not modify these associations.

Patient-reported outcomes for people with diabetes: what and how to measure? A narrative review.

Patient-reported outcomes (PROs) are valuable for shared decision making and research. Patient-reported outcome measures (PROMs) are questionnaires used to measure PROs, such as health-related quality of life (HRQL). Although core outcome sets for trials and clinical practice have been developed separately, they, as well as other initiatives, recommend different PROs and PROMs. In research and clinical practice, different PROMs are used (some generic, some disease-specific), which measure many different things. This is a threat to the validity of research and clinical findings in the field of diabetes. In this narrative review, we aim to provide recommendations for the selection of relevant PROs and psychometrically sound PROMs for people with diabetes for use in clinical practice and research. Based on a general conceptual framework of PROs, we suggest that relevant PROs to measure in people with diabetes are: disease-specific symptoms (e.g. worries about hypoglycaemia and diabetes distress), general symptoms (e.g. fatigue and depression), functional status, general health perceptions and overall quality of life. Generic PROMs such as the 36-Item Short Form Health Survey (SF-36), WHO Disability Assessment Schedule (WHODAS 2.0), or Patient-Reported Outcomes Measurement Information System (PROMIS) measures could be considered to measure commonly relevant PROs, supplemented with disease-specific PROMs where needed. However, none of the existing diabetes-specific PROM scales has been sufficiently validated, although the Diabetes Symptom Self-Care Inventory (DSSCI) for measuring diabetes-specific symptoms and the Diabetes Distress Scale (DDS) and Problem Areas in Diabetes (PAID) for measuring distress showed sufficient content validity. Standardisation and use of relevant PROs and psychometrically sound PROMs can help inform people with diabetes about the expected course of disease and treatment, for shared decision making, to monitor outcomes and to improve healthcare. We recommend further validation studies of diabetes-specific PROMs that have sufficient content validity for measuring disease-specific symptoms and consider generic item banks developed based on item response theory for measuring commonly relevant PROs.

Higher Neighborhood Drivability Is Associated With a Higher Diabetes Risk in Younger Adults: A Population-Based Cohort Study in Toronto, Canada.

OBJECTIVE: Car dependency contributes to physical inactivity and, consequently, may increase the likelihood of diabetes. We investigated whether neighborhoods that are highly conducive to driving confer a greater risk of developing diabetes and, if so, whether this differs by age. RESEARCH DESIGN AND METHODS: We used administrative health care data to identify all working-age Canadian adults (20-64 years) who were living in Toronto on 1 April 2011 without diabetes (type 1 or 2). Neighborhood drivability scores were assigned using a novel, validated index that predicts driving patterns based on built environment features divided into quintiles. Cox regression was used to examine the association between neighborhood drivability and 7-year risk of diabetes onset, overall and by age-group, adjusting for baseline characteristics and comorbidities. RESULTS: Overall, there were 1,473,994 adults in the cohort (mean age 40.9 ± 12.2 years), among whom 77,835 developed diabetes during follow-up. Those living in the most drivable neighborhoods (quintile 5) had a 41% higher risk of developing diabetes compared with those in the least drivable neighborhoods (adjusted hazard ratio 1.41, 95% CI 1.37-1.44), with the strongest associations in younger adults aged 20-34 years (1.57, 95% CI 1.47-1.68, P < 0.001 for interaction). The same comparison in older adults (55-64 years) yielded smaller differences (1.31, 95% CI 1.26-1.36). Associations appeared to be strongest in middle-income neighborhoods for younger residents (middle income 1.96, 95% CI 1.64-2.33) and older residents (1.46, 95% CI 1.32-1.62). CONCLUSIONS: High neighborhood drivability is a risk factor for diabetes, particularly in younger adults. This finding has important implications for future urban design policies.

Social jet lag and (changes in) glycemic and metabolic control in people with type 2 diabetes.

OBJECTIVE: Social jet lag, i.e., the discordance among social and biological rhythms, is associated with poor metabolic control. This study aimed to assess cross-sectional and longitudinal associations among social jet lag and glycemic and metabolic control in people with type 2 diabetes. METHODS: In a prospective cohort (N = 990) with type 2 diabetes, social jet lag was measured at baseline using daily diaries and was categorized (high, moderate, or low). Metabolic outcomes were assessed at baseline and at 1 and 2 years of follow-up. Associations among social jet lag and glycemic and metabolic control were analyzed using linear regression and linear mixed models adjusted for confounding factors. Analyses were stratified for work status (retired vs. working; p value for interaction = 0.007 for glycated hemoglobin [HbA1c]). RESULTS: In working people, a cross-sectional association between high social jet lag and HbA1c (1.87 mmol/mol [95% CI: 0.75 to 2.99]) and blood pressure (5.81 mm Hg [95% CI: 4.04 to 7.59]) was observed. For retired people, high social jet lag was negatively associated with HbA1c (-1.58 mmol/mol [95% CI: -2.54 to -0.62]), glucose (-0.19 mmoL/L [95% CI:-0.36 to -0.01]), and blood pressure (-3.70 mm Hg [95% CI: -5.36 to -2.04]), and the association with BMI was positive (1.12 kg/m2 [95% CI: 0.74 to 1.51]). Prospective associations had the same direction as cross-sectional findings but were nonsignificant for working or retired people. CONCLUSIONS: Social jet lag was cross-sectionally, but not prospectively, associated with glycemic and metabolic markers. Interaction with work status was present, and directions of the associations were generally detrimental in the working population, whereas higher social jet lag was associated with improved glycemic and metabolic control for retired people.

Presence of retinopathy and incident kidney and cardiovascular events in type 2 diabetes with normoalbuminuria - A post-hoc analysis of the PRIORITY randomized clinical trial.

AIMS: Baseline diabetic retinopathy (DR) and risk of development of microalbuminuria, kidney function decline, and cardiovascular events (CVEs) in type 2 diabetes. METHODS: Post-hoc analysis of the PRIORITY study including 1758 persons with type 2 diabetes and normoalbuminuria followed for a median of 2.5 (IQR: 2.0-3.0) years. DR diagnosis included non-proliferative and proliferative abnormalities, macular oedema, or prior laser treatment. Cox models were fitted to investigate baseline DR presence with development of persistent microalbuminuria (urinary albumin-creatinine ratio > 30 mg/g); chronic kidney disease (CKD) G3 (eGFR <60 ml/min/1.73m2); and CVE. Models were adjusted for relevant risk factors. RESULTS: At baseline, 304 (17.3 %) had DR. Compared to persons without DR, they were older (mean ± SD: 62.7 ± 7.7 vs 61.4 ± 8.3 years, p = 0.019), had longer diabetes duration (17.9 ± 8.4 vs. 10.6 ± 7.0 years, p < 0.001), and higher HbA1c (62 ± 13 vs. 56 ± 12 mmol/mol, p < 0.001). The adjusted hazard ratios of DR at baseline for development of microalbuminuria (n = 197), CKD (n = 166), and CVE (n = 64) were: 1.50 (95%CI: 1.07, 2.11), 0.87 (95%CI: 0.56, 1.34), and 2.61 (95%CI: 1.44, 4.72), compared to without DR. CONCLUSIONS: Presence of DR in normoalbuminuric type 2 diabetes was associated with an increased risk of developing microalbuminuria and CVE, but not with kidney function decline.

Longitudinal association of electrocardiogram abnormalities with major adverse cardiac events in people with Type 2 diabetes: the Hoorn Diabetes Care System cohort.

AIMS: To investigate the association of (changes in) electrocardiogram (ECG) abnormalities with incident major adverse cardiac events (MACE) in people with Type 2 diabetes (T2D) without pre-existing cardiovascular disease (CVD). METHODS AND RESULTS: A prospective longitudinal study of 11 993 people with T2D without known CVD from the Hoorn Diabetes Care System cohort. Annually repeated measurements (1998-2018), included cardiovascular risk factors, over 70 000 ECG, and self-reported cardiovascular events. ECG abnormalities were classified according to the Minnesota Classification as prolonged PR duration, prolonged QRS duration, left QRS-axis, QS pattern, ST-segment/T-wave abnormalities, or tall R-wave. The association of ECG abnormalities with MACEs was assessed using time-dependent Cox-regression models, adjusted for time-varying cardiovascular risk factors, and medication use [hazard ratios (HRs) with 95% confidence intervals (CIs)]. During a median follow-up of 6.6 (IQR, 3.1-10.7) years, 5445 (45.4%) of the participants had an ECG abnormality (prevalent or incident) at any of the median 6 (IQR, 3-10) annual ECG recordings, and 905 people (7.5%) had a MACE (529 coronary heart disease (CHD), 250 heart failure (HF), and 126 sudden cardiac arrest (SCA)). After adjustment, most ECG abnormalities were associated with HF: prolonged QRS duration [HR, 4.01 (95% CI, 2.67-6.03)], QS pattern [2.68 (0.85-8.49)], ST-segment/T-wave abnormalities [4.26 (2.67-6.80)], and tall R-wave [2.23 (1.33-3.76)]. Only QS pattern [2.69 (1.20-6.03)] and ST-segment/T-wave abnormalities [2.11 (1.48-3.02)] were associated with CHD. These associations were robust across age, sex, hypertension, or estimated CVD risk subgroups. CONCLUSION: In people with T2D without pre-existing CVD, ECG abnormalities related to decelerated conduction, ischaemia, and hypertrophy are predominantly early signs of emerging HF, while only abnormalities related to ischaemic disorders are signs of CHD.

In this cohort study of 11 993 people with Type 2 diabetes (T2D) that were still free of cardiovascular disease (CVD), the people with electrocardiogram (ECG) abnormalities were up to four times as likely to experience heart failure and up to twice as likely to experience a heart attack, regardless of their age, sex, blood pressure, or estimated risk of CVD. • Most ECG abnormalities are related to a higher risk of heart failure, but only ECG abnormalities that indicate reduced oxygen supply to the heart are related to a higher risk of a heart attack. • Periodical ECG examinations can help detect developing heart disease in an early stage for all people with T2D still free of CVD.

The prevalence of self-reported insomnia symptoms and association with metabolic outcomes in people with type 2 diabetes: the Hoorn Diabetes Care System cohort.

STUDY OBJECTIVES: We investigated the prevalence of self-reported insomnia symptoms in people with type 2 diabetes and assessed the association with metabolic outcomes and the mediating role of lifestyle factors. METHODS: In a prospective cohort of 1,272 participants with type 2 diabetes (63.4% male, age 68.7 ± 9 years) we measured insomnia symptoms using the Insomnia Severity Index and metabolic outcomes as hemoglobin A1c, glucose, lipids, and body mass index at baseline and at 1 year follow-up. Linear regression analyses assessed the association between insomnia symptoms and metabolic outcomes, corrected for demographic factors, comorbidities, and body mass index. Mediation analyses were conducted for lifestyle factors. RESULTS: The prevalence of mild and severe insomnia symptoms was 23.0% and 10.7%, respectively. When adjusted for demographic factors and comorbidities, cross-sectionally severe insomnia symptoms were associated with higher body mass index (ß = 0.97 kg/m2; 95% confidence interval 0.04: 1.89) compared to no insomnia symptoms. Cross-sectionally, no associations were observed for the other metabolic outcomes. Additionally, no prospective associations were observed with any of the outcomes. Finally, physical activity mediated the association between severe insomnia symptoms and body mass index by 29.3%. CONCLUSIONS: About a third of people with type 2 diabetes experience self-reported insomnia symptoms, but insomnia symptoms were not associated with metabolic outcomes in people with type 2 diabetes. CITATION: Groeneveld L, den Braver NR, Beulens JWJ, et al. The prevalence of self-reported insomnia symptoms and association with metabolic outcomes in people with type 2 diabetes: the Hoorn Diabetes Care System cohort. J Clin Sleep Med. 2023;19(3):539-548.

Validation of an Announced Telephone Pill Count Compared to a Home-Visit Pill Count in People With Type 2 Diabetes or Cardiovascular Disease.

We aimed to assess the validity of an announced telephone pill count in people with type 2 diabetes or cardiovascular disease by comparing this method to a home-visit pill count. We also assessed whether a second telephone pill count improved accuracy. People aged ≥35 years using oral type 2 diabetes or cardiovascular disease medication were included. Thirty-four participants completed a telephone pill count followed by a home-visit pill count, and a subsample of this population (n = 11) completed a second telephone pill count. Scatterplots were used for a visual representation of the number of pills counted with both methods, intraclass correlation coefficients for agreement, and Bland-Altman plots for absolute differences and outliers. A total of 203 pill counts were conducted. The study population consisted of 53% men, with a mean age of 69.6 (±9.2) years and an average of 6.1 (±2.8) medication prescriptions per participant. Scatterplots showed that pills counted with both methods were mostly scattered around the y = x equation. Agreement between the first telephone pill count and home-visit pill count was high, with intraclass correlation coefficients of 0.96 (medication count level) and 0.98 (individual level). No learning effects were observed in the subsample (n = 11), the intraclass correlation coefficient for the first telephone pill count was 0.88 versus 0.89 for the second telephone pill count. Bland-Altman plots indicated high agreement between the two methods. An announced telephone pill count is considered a valid alternative for a home-visit pill count in people with type 2 diabetes or cardiovascular disease. A single pill count appears sufficient.

Sociodemographic, lifestyle and clinical characteristics of energy-related depression symptoms: A pooled analysis of 13,965 depressed cases in 8 Dutch cohorts.

BACKGROUND: In a substantial subgroup of depressed patients, atypical, energy-related depression symptoms (e.g. increased appetite/weight, hypersomnia, loss of energy) tend to cluster with immuno-metabolic dysregulations (e.g. increased BMI and inflammatory markers). This clustering is proposed to reflect a more homogeneous depression pathology. This study examines to what extent energy-related symptoms are associated and share sociodemographic, lifestyle and clinical characteristics. METHODS: Data were available from 13,965 participants from eight Dutch cohorts with DSM-5 lifetime major depression assessed by the Lifetime Depression Assessment Self-report (LIDAS) questionnaire. Information on four energy-related depression symptoms were extracted: energy loss, increased appetite, increased weight, and hypersomnia. Tetrachoric correlations between these symptoms, and associations of these symptoms with sociodemographic (sex, age, education), lifestyle (physical activity, BMI, smoking) and clinical characteristics (age of onset, episode duration, history, treatment and recency, and self-reported comorbidity) were computed. RESULTS: Correlations between energy-related symptoms were overall higher than those with other depression symptoms and varied from 0.90 (increased appetite vs increased weight) to 0.11 (increased appetite vs energy loss). All energy-related symptoms were strongly associated with higher BMI and a more severe clinical profile. Patients with increased appetite were more often smokers, and only patients with increased appetite or weight more often had a self-reported diagnosis of PTSD (OR = 1.17, p = 2.91E-08) and eating disorder (OR = 1.40, p = 4.08E-17). CONCLUSIONS: The symptom-specific associations may have consequences for a profile integrating these symptoms, which can be used to reflect immuno-metabolic depression. They indicate the need to study immuno-metabolic depression at individual symptom resolution as a starting point.

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.