High Risk Of Diabetes Research Articles

Transforming the diabetes outcomes for people with mental illness

AbstractThere is a complex bidirectional relationship between diabetes and mental illness, where diabetes is associated with an increased prevalence of a range of mental disorders and several mental illnesses increase the risk of diabetes. The reasons why people with mental illness are at higher risk of diabetes and vice versa are multifactorial. When diabetes and mental illness occur together, the outcomes for both conditions are worsened, and the co‐morbidity places a higher burden on the individual living with the conditions.Severe mental illness is associated with a twofold increased risk of diabetes, and the onset of diabetes is approximately 10 years earlier in people with mental illness than in the general population. Health behaviour interventions to reduce the incidence of diabetes may be less effective than previously thought. However, trials on obesity drugs, particularly glucagon‐like peptide‐1 receptor agonists, are showing promise. Diabetes care for people with severe mental illness seems to have improved in the past decade. Interventions have been developed to address the unique challenges of living with severe mental illness and diabetes.Depression is twice as common in people with diabetes. Depression increases the risk of diabetes and vice versa. Although general population risk factors for depression apply to people with diabetes, diabetes‐specific risk factors include the development of complications and insulin use in people with type 2 diabetes. Managing depression includes efforts to prevent depression, timely diagnosis and treatment with psychological or pharmacological treatments.Health care professionals have a responsibility to ensure that people with mental illness and diabetes are not disadvantaged.

Drug-coated balloons in high-risk patients and diabetes mellitus: A meta-analysis of 10 studies.

Despite the improvements in drug eluting stents (DES) technology, suboptimal results have been observed in certain higher-risk subsets of patients, as in diabetes mellitus (DM). Drug-coated balloons (DCB) could represent an alternative to DES in complex populations and anatomies, as in DM. The present meta-analysis aimed at assessing the role of DCBs in patients with diabetes mellitus. Studies comparing DCB versus percutaneous coronary revascularization (PCI) with/without DES for PCI in high-risk populations (>30% DM) were included. The primary efficacy endpoint was overall mortality, secondary endpoints were myocardial infarction, target lesion revascularization (TLR), and major adverse cardiovascular events (MACE). We included 10 studies, comprising 2026 patients. Among them, 1002 patients (49.5%) were treated with DCB and 1024 with DES implantation. Among the included studies, 6 only enrolled diabetic patients and 2 had a prevalence of diabetes of 50%. At a mean follow-up of 15.3 months, mortality rate was 3.8% (82 patients), significantly lower with DCB (3.2% vs. 4.9% with DES; odds ratio [OR] [95% confidence interval {CI}] = 0.61 [0.38, 0.97], p = 0.04 phet = 0.34. A similar reduction in favor of DCB was observed for MACE (13.6% vs. 17.6%; OR [95% CI] = 0.79 [0.61, 1.04], p = 0.09, phet = 0.25), while TLR was significantly reduced only in the diabetic-restricted sub-analysis. In the present meta-analysis, we showed a significant survival benefit and an absolute reduction in MACE and TLR with a DCB-based strategy as compared to DES in high-risk patients, mostly with DM. Future large-scale randomized trials, dedicated to this population, are deserved to confirm our findings. Complex coronary anatomies and diabetes mellitus (DM) represent the pitfall of drug eluting stents (DES), mainly due to inflammatory and thrombotic complications, which should be reduced with drug-coated balloons (DCB). We confirmed a significant advantage of DCB versus DES in the treatment of de novo lesions in high-risk patients and mainly in DM, reducing overall mortality, MACE and target lesion revascularization.

Global burden of high-risk cardiovascular patients without prior myocardial infarction or stroke: VESALIUS-REAL - preliminary results from Germany

Abstract Background Clinical trial data has shown that low-density lipoprotein cholesterol (LDL-C) lowering with PCSK9-inhibitors reduced cardiovascular (CV) endpoints in patients with established atherosclerotic cardiovascular disease (ASCVD). Intervening early in patients with high CV risk prior to myocardial infarction (MI) or stroke, while perceived to be less urgent, may result in larger public health benefits. The effect of evolocumab in this population is investigated in a phase-3 clinical trial (NCT03872401: Effect of Evolocumab in Patients at High Cardiovascular Risk Without Prior Myocardial Infarction or Stroke [VESALIUS-CV]). This observational study examines the global burden of VESALIUS-CV-like population in the REAL-World ("VESALIUS-REAL") in eight regions (Germany, Hong Kong, Japan, South Korea, Sweden, Taiwan, UK and US) using a unified protocol across multiple databases. The multi-database study is ongoing, and the current analysis focuses on characteristics of VESALIUS-CV like patients in Germany. Methods Eligibility criteria are shown in the Figure. Data were obtained from the German Disease Analyzer (2013-2022), a representative claims database from Germany. Criteria were aligned with the clinical trial, and real-world definitions were created using diagnosis and procedure codes. Results A total of 195,621 patients were included in the present analysis (Table). At baseline, the median age was 71 years (Q1-Q3: 64-79) and 48% of patients were women. Approximately two-thirds of patients had atherosclerosis (48.5% had coronary artery disease, 13.8% had cerebrovascular disease and 13.8% had peripheral artery disease) and 33.7% had high-risk diabetes mellitus (DM), defined as DM with microvascular complications or chronic insulin use. The median baseline LDL-C was 139 (Q1-Q3: 113-166) mg/dL [3.6 (2.9 - 4.3) mmol/L] and 110,867 patients (57%) had an LDL-C ≥130 mg/dL (≥3.4 mmol/L). Overall, 69% of VESALIUS-CV like patients were receiving no background LLT. Conclusions Despite having atherosclerosis and/or high-risk DM and LDL-C exceeding target thresholds, a large proportion of VESALIUS-CV like patients were not on any LLT in Germany. Final results from VESALIUS-REAL will be able to report if this treatment gap is also observed in other countries.

Correction for Kwan et al., "Gut phageome in Mexican Americans: a population at high risk for metabolic dysfunction-associated steatotic liver disease and diabetes".

Correction for Kwan et al., "Gut phageome in Mexican Americans: a population at high risk for metabolic dysfunction-associated steatotic liver disease and diabetes".

Effect of shared decision-making model on the management of diabetes high-risk groups.

A shared decision-making (SDM) model-based intervention programme was implemented for a population at high risk for diabetes to explore its effectiveness in intervening with blood glucose levels in this population. One hundred residents were selected according to the principle of voluntary participation and divided into the intervention group (n = 50) and the control group (n = 50) by using multistage cluster sampling. The control group received only brief diabetes knowledge education through a disease brochure issued by the hospital; the intervention group implemented a SDM model based on large classroom and individualised education for 4 months. Univariate analysis and generalised estimating equation fitting model were used to analyse the effect of intervention on blood glucose parameters in the study subjects. Univariate analysis showed that after 4 months of intervention, fasting blood glucose was lower in the intervention group than in the control group (5.57 ± 0.56 vs. 6.07 ± 0.77, F = 45.721, p < 0.001); glycosylated hemoglobin was lower in the intervention group than in the control group (5.91 ± 0.28 vs. 6.02 ± 0.24, F = 25.998, p < 0.001), decreased by 0.26% in the intervention group and increased by 0.01% in the control group. One-way analysis of variance (ANOVA) showed that fasting blood glucose and glycosylated hemoglobin in the intervention group decreased to different extents from baseline. The generalised estimation equation was fitted with the intervention programme, gender, hypertension, smoking, alcohol consumption, physical activity, age, waist circumference, body mass index, baseline fasting blood glucose, and baseline glycosylated hemoglobin as independent variables, and fasting blood glucose and baseline glycosylated hemoglobin as dependent variables. Results showed that compared with the control group, fasting blood glucose and glycosylated hemoglobin levels were significantly different between the two groups (p < 0.001). Applying an intervention programme based on SDM model to people at high risk of diabetes can improve patients' adherence to self-management and establish a good lifestyle, thus contributing to their good glycemic control.

Clustering-based risk stratification of prediabetes populations: Insights from the Taiwan and UK Biobanks.

This study aimed to identify low- and high-risk diabetes groups within prediabetes populations using data from the Taiwan Biobank (TWB) and UK Biobank (UKB) through a clustering-based Unsupervised Learning (UL) approach, to inform targeted type 2 diabetes (T2D) interventions. Data from TWB and UKB, comprising clinical and genetic information, were analyzed. Prediabetes was defined by glucose thresholds, and incident T2D was identified through follow-up data. K-means clustering was performed on prediabetes participants using significant features determined through logistic regression and LASSO. Cluster stability was assessed using mean Jaccard similarity, silhouette score, and the elbow method. We identified two stable clusters representing high- and low-risk diabetes groups in both biobanks. The high-risk clusters showed higher diabetes incidence, with 15.7% in TWB and 13.0% in UKB, compared to 7.3% and 9.1% in the low-risk clusters, respectively. Notably, males were predominant in the high-risk groups, constituting 76.6% in TWB and 52.7% in UKB. In TWB, the high-risk group also exhibited significantly higher BMI, fasting glucose, and triglycerides, while UKB showed marginal significance in BMI and other metabolic indicators. Current smoking was significantly associated with increased diabetes risk in the TWB high-risk group (P < 0.001). Kaplan-Meier curves indicated significant differences in diabetes complication incidences between clusters. UL effectively identified risk-specific groups within prediabetes populations, with high-risk groups strongly associated male gender, higher BMI, smoking, and metabolic markers. Tailored preventive strategies, particularly for young males in Taiwan, are crucial to reducing T2D risk.

High prevalence of prediabetes and type 2 diabetes, and identification of associated factors, in high-risk adults in Vietnam: A cross-sectional study

ObjectivesThe prevalences of diabetes and prediabetes have increased rapidly in recent years in emerging nations such as Vietnam, particularly in the population at high risk of diabetes. This study aimed to investigate the prevalence of prediabetes and undiagnosed diabetes in individuals at high risk of type 2 diabetes (T2D), as well as the related risk factors. MethodsThis cross-sectional study at the clinics of the University Medical Center in Ho Chi Minh City included 360 patients who were 18 years of age or older, and were at risk of developing T2D. The diagnosis of prediabetes and diabetes relied on measurements of fasting plasma glucose, HbA1c, and 2-hour plasma glucose after a 75 g oral glucose tolerance test. ResultsThe prevalence of prediabetes was 60.6 % (95 % CI: 55.3–65.6 %), and the prevalence of diabetes was 18.3 % (95 % CI: 14.6–22.8 %). Older age (OR = 1.06), obesity (OR = 3.89), hypertension (OR = 5.71), and dyslipidemia (OR = 2.01) were factors associated with increasing frequencies of undiagnosed T2D and prediabetes. ConclusionThe prevalences of prediabetes and undiagnosed diabetes were significantly higher among people with a high-risk of dysglycemia in Vietnam. There is a need for screening programs for such high-risk individuals.

Effects of Chronotherapeutic Interventions in Adults With ADHD and Delayed Sleep Phase Syndrome (DSPS) on Regulation of Appetite and Glucose Metabolism

Background: ADHD is highly comorbid with Delayed Sleep Phase Syndrome (DSPS). Both are associated with obesity and diabetes, which can be caused by long-term dysregulations of appetite and glucose metabolism. This study explores hormones involved in these processes and the effects of chronotherapeutic interventions in a small sample of adults with ADHD and DSPS. Methods: Exploratory, secondary analysis of data from the PhASE study, a three-armed randomized clinical trial, are presented, including 37 adults (18–53 years) with ADHD and DSPS receiving three weeks of 0.5 mg/day (1) placebo, (2) melatonin, or (3) melatonin plus 30 minutes of bright light therapy (BLT). Leptin (appetite-suppressing), ghrelin (appetite-stimulating), insulin, insulin-like growth factor-1 (IGF-1), and glucose were measured from blood collected at 08:00 hours. Salivary cortisol was collected during the first 30 minutes after awakening and self-reported appetite was assessed. Results: Baseline leptin and IGF-1 levels were higher than reference ranges, and ghrelin and cortisol levels were lower, while insulin and glucose were normal. Melatonin treatment decreased leptin and insulin. Other outcomes remained unchanged and melatonin + BLT had no effects. Conclusion: Due to the small sample size and exploratory nature of the study, results should be interpreted with caution. Overall, these results show no strong indications for dysregulation of appetite and glucose metabolism to suggest high risk of obesity and diabetes in this small sample of adults with ADHD and DSPS. However, baseline appetite was suppressed, likely because measurements took place in the early morning which could be considered the biological night for this study population. Melatonin treatment seemed to cause subtle changes in appetite-regulating hormones suggesting increased appetite. Chronotherapeutic treatment may affect appetite-regulating hormones by advancing the biological rhythm and/or altering eating behaviors, but this remains to be investigated in larger samples using detailed food diaries.

Gut phageome in Mexican Americans: a population at high risk for metabolic dysfunction-associated steatotic liver disease and diabetes.

Mexican Americans are disproportionally affected by metabolic dysfunction-associated steatotic liver disease (MASLD), which often co-occurs with diabetes. Despite extensive evidence on the causative role of the gut microbiome in MASLD, studies determining the involvement of the gut phageome are scarce. In this cross-sectional study, we characterized the gut phageome in Mexican Americans of South Texas by stool shotgun metagenomic sequencing of 340 subjects, concurrently screened for liver steatosis by transient elastography. Inter-individual variations in the phageome were associated with gender, country of birth, diabetes, and liver steatosis. The phage signatures for diabetes and liver steatosis were subsequently determined. Enrichment of Inoviridae was associated with both diabetes and liver steatosis. Diabetes was further associated with the enrichment of predominantly temperate Escherichia phages, some of which possessed virulence factors. Liver steatosis was associated with the depletion of Lactococcus phages r1t and BK5-T, and enrichment of the globally prevalent Crassvirales phages, including members of genus cluster IX (Burzaovirus coli, Burzaovirus faecalis) and VI (Kahnovirus oralis). The Lactococcus phages showed strong correlations and co-occurrence with Lactococcus lactis, while the Crassvirales phages, B. coli, B. faecalis, and UAG-readthrough crAss clade correlated and co-occurred with Prevotella copri. In conclusion, we identified the gut phageome signatures for two closely linked metabolic diseases with significant global burden. These phage signatures may have utility in risk modeling and disease prevention in this high-risk population, and identification of potential bacterial targets for phage therapy.IMPORTANCEPhages influence human health and disease by shaping the gut bacterial community. Using stool samples from a high-risk Mexican American population, we provide insights into the gut phageome changes associated with diabetes and liver steatosis, two closely linked metabolic diseases with significant global burden. Common to both diseases was an enrichment of Inoviridae, a group of phages that infect bacterial hosts chronically without lysis, allowing them to significantly influence bacterial growth, virulence, motility, biofilm formation, and horizontal gene transfer. Diabetes was additionally associated with the enrichment of Escherichia coli-infecting phages, some of which contained virulence factors. Liver steatosis was additionally associated with the depletion of Lactococcus lactis-infecting phages, and enrichment of Crassvirales phages, a group of virulent phages with high global prevalence and persistence across generations. These phageome signatures may have utility in risk modeling, as well as identify potential bacterial targets for phage therapy.

Transcultural adaptation and validation of Persian Version of Patient Assessment of Chronic Illness Care (PACIC-5As) Questionnaire in Iranian older patients with type 2 diabetes

BackgroundThe Patient Assessment of Chronic Illness Care (PACIC-5As) questionnaire has been designed to evaluate the healthcare experiences of individuals with chronic diseases such as diabetes. Older adults are at higher risk for diabetes and its associated complications. The aim of this study was transcultural adaptation and evaluation of the validity and reliability of the PACIC-5As questionnaire in older patients with diabetes residing in Qazvin City, Iran.MethodIn this validation study, we recruited 306 older patients with diabetes from Comprehensive Health Centers in Qazvin, Iran. The multi-stage cluster sampling technique was used to choose a representative sample. The PACIC-5As questionnaire was translated into Persian using the World Health Organization (WHO) standardized method. The validity (face, content, and construct) and reliability (Cronbach’s alpha) of the PACIC-5As were assessed. Data analysis was conducted using R software and the Lavaan package.ResultsThe mean age of the older patients was 69.99 ± 6.94 years old. Most older participants were female (n = 180, 58.82%) and married (n = 216, 70.59%). Regarding face validity, all items of PACIC-5As had impact scores greater than 1.5. In terms of content validity, all items had a content validity ratio > 0.49 and a content validity index > 0.79. The results of confirmatory factor analysis demonstrated that the model exhibited satisfactory fit across the expected five factors, including assess, advise, agree, assist, and arrange, for the 25 items of the PACIC-5As questionnaire. The Cronbach’s alpha coefficient for the PACIC-5As questionnaire was 0.805.ConclusionThis study indicates that the Persian version of the PACIC-5As questionnaire is valid and reliable for assessing healthcare experiences in older patients with diabetes. This means that the questionnaire can be effectively used in this population.

Association of Prepregnancy Cardiometabolic Factors With Gestational Diabetes Among Asian Populations in the United States

BackgroundAsian individuals are among the highest immigrant group to the United States and at particularly high risk of gestational diabetes, which is associated with long-term maternal cardiovascular disease. Limited data are available on the association of prepregnancy cardiometabolic risk factors with gestational diabetes among Asian American subjects. ObjectivesThis study sought to determine the association of prepregnancy hypertension and body mass index (BMI) among Asian ancestry subgroups and by maternal nativity. MethodsUsing data from the National Vital Statistics System from 2016 to 2019, the prevalence of gestational diabetes, stratified according to prepregnancy hypertension and obesity, was examined according to maternal race. Predicted probability of gestational diabetes with continuous BMI was calculated across Asian ancestry subgroups and by maternal nativity. ResultsAmong 13.3 million pregnancies, gestational diabetes occurred in 6.5%. Asian subjects had the highest prevalence (12.3%). Among those with prepregnancy hypertension, Asian subjects had the highest prevalence (29.3%). Across the range of BMI (18-42 kg/m2), Asian subjects had the highest predicted probability. There was substantial heterogeneity across Asian ancestry subgroups between the association of BMI with gestational diabetes, with highest probability among Japanese and Korean American subjects at BMI >23 kg/m2. Predicted probability of gestational diabetes was higher for mothers born outside the United States among all Asian subgroups, except for Japanese American subjects. ConclusionsAsian American individuals have the highest prevalence of gestational diabetes at any BMI and with hypertension. Substantial variation in risk is present across Asian subgroups. Findings suggest a need for more tailored screening and intervention for gestational diabetes among Asian American subjects, with a specific focus on risk for individuals born outside the United States.

Insulin Resistance and Impaired Insulin Secretion Predict Incident Diabetes: A Statistical Matching Application to the Two Korean Nationwide, Population-Representative Cohorts.

To evaluate whether insulin resistance and impaired insulin secretion are useful predictors of incident diabetes in Koreans using nationwide population-representative data to enhance data privacy. This study analyzed the data of individuals without diabetes aged >40 years from the Korea National Health and Nutrition Examination Survey (KNHANES) 2007-2010 and 2015 and the National Health Insurance Service-National Health Screening Cohort (NHIS-HEALS). Owing to privacy concerns, these databases cannot be linked using direct identifiers. Therefore, we generated 10 synthetic datasets, followed by statistical matching with the NHIS-HEALS. Homeostasis model assessment of insulin resistance (HOMA-IR) and homeostasis model assessment of β-cell function (HOMA-β) were used as indicators of insulin resistance and insulin secretory function, respectively, and diabetes onset was captured in NHIS-HEALS. A median of 4,580 (range, 4,463 to 4,761) adults were included in the analyses after statistical matching of 10 synthetic KNHANES and NHIS-HEALS datasets. During a mean follow-up duration of 5.8 years, a median of 4.7% (range, 4.3% to 5.0%) of the participants developed diabetes. Compared to the reference low-HOMA-IR/high-HOMA-β group, the high-HOMA-IR/low- HOMA-β group had the highest risk of diabetes, followed by high-HOMA-IR/high-HOMA-β group and low-HOMA-IR/low- HOMA-β group (median adjusted hazard ratio [ranges]: 3.36 [1.86 to 6.05], 1.81 [1.01 to 3.22], and 1.68 [0.93 to 3.04], respectively). Insulin resistance and impaired insulin secretion are robust predictors of diabetes in the Korean population. A retrospective cohort constructed by combining cross-sectional synthetic and longitudinal claims-based cohort data through statistical matching may be a reliable resource for studying the natural history of diabetes.

Trajectory Patterns of Macronutrient Intake and Their Associations with Obesity, Diabetes, and All-Cause Mortality: A Longitudinal Analysis over 25 Years.

Over the past decades, China has been undergoing rapid economic growth, which may have significantly influenced the dietary patterns and health status of the Chinese population. Our study aimed to assess the associations of potential macronutrient trajectory patterns with chronic diseases and all-cause mortality using the latent class trajectory model (LCTM) and the longitudinal data of the China Health and Nutrition Survey obtained between 1991 and 2015. A 24-hour diet recall was used to assess the dietary intake. The Poisson regression model was employed to investigate the correlations between trajectory patterns and chronic diseases and all-cause mortality. A total of 8115 participants were included in the final analysis. We explored four and three trajectory patterns for male and female populations, respectively. We found that a decreasing very high-carbohydrate trajectory together with a U-shape protein trajectory was associated with a higher risk of diabetes in the male population (odds ratio (OR): 2.23; 95% confidence interval (CI): 1.31-3.77). A similar pattern for moderate protein intake was also associated with the risk of diabetes in the female population (OR: 1.82; 95% CI: 1.18-2.79). In addition, we show that a decreasing low-carbohydrate trajectory and an increasing high-fat trajectory were associated with a lower risk of all-cause mortality (OR: 0.76; 95% CI: 0.60-0.96) and a higher risk of obesity (OR: 1.24; 95% CI: 1.05-1.47) in males. Our results shed light on some salient nutritional problems in China, particularly the dual challenges of undernutrition and overnutrition.

Automated Comprehensive CT Assessment of the Risk of Diabetes and Associated Cardiometabolic Conditions.

Background CT performed for various clinical indications has the potential to predict cardiometabolic diseases. However, the predictive ability of individual CT parameters remains underexplored. Purpose To evaluate the ability of automated CT-derived markers to predict diabetes and associated cardiometabolic comorbidities. Materials and Methods This retrospective study included Korean adults (age ≥ 25 years) who underwent health screening with fluorine 18 fluorodeoxyglucose PET/CT between January 2012 and December 2015. Fully automated CT markers included visceral and subcutaneous fat, muscle, bone density, liver fat, all normalized to height (in meters squared), and aortic calcification. Predictive performance was assessed with area under the receiver operating characteristic curve (AUC) and Harrell C-index in the cross-sectional and survival analyses, respectively. Results The cross-sectional and cohort analyses included 32166 (mean age, 45 years ± 6 [SD], 28833 men) and 27 298 adults (mean age, 44 years ± 5 [SD], 24 820 men), respectively. Diabetes prevalence and incidence was 6% at baseline and 9% during the 7.3-year median follow-up, respectively. Visceral fat index showed the highest predictive performance for prevalent and incident diabetes, yielding AUC of 0.70 (95% CI: 0.68, 0.71) for men and 0.82 (95% CI: 0.78, 0.85) for women and C-index of 0.68 (95% CI: 0.67, 0.69) for men and 0.82 (95% CI: 0.77, 0.86) for women, respectively. Combining visceral fat, muscle area, liver fat fraction, and aortic calcification improved predictive performance, yielding C-indexes of 0.69 (95% CI: 0.68, 0.71) for men and 0.83 (95% CI: 0.78, 0.87) for women. The AUC for visceral fat index in identifying metabolic syndrome was 0.81 (95% CI: 0.80, 0.81) for men and 0.90 (95% CI: 0.88, 0.91) for women. CT-derived markers also identified US-diagnosed fatty liver, coronary artery calcium scores greater than 100, sarcopenia, and osteoporosis, with AUCs ranging from 0.80 to 0.95. Conclusion Automated multiorgan CT analysis identified individuals at high risk of diabetes and other cardiometabolic comorbidities. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Pickhardt in this issue.

Association Between Accelerometer-Measured Irregular Sleep Duration and Type 2 Diabetes Risk: A Prospective Cohort Study in the UK Biobank.

To evaluate the association between irregular sleep duration and incident diabetes in a U.K. population over 7 years of follow-up. Among 84,421 UK Biobank participants (mean age 62 years) who were free of diabetes at the time of providing accelerometer data in 2013-2015 and prospectively followed until May 2022, sleep duration variability was quantified by the within-person SD of 7-night accelerometer-measured sleep duration. We used Cox proportional hazard models to estimate hazard ratios (HRs) for incident diabetes (identified from medical records, death register, and/or self-reported diagnosis) according to categories of sleep duration SD. There were 2,058 incident diabetes cases over 622,080 person-years of follow-up. Compared with sleep duration SD ≤ 30 min, the HR (95% CI) was 1.15 (0.99, 1.33) for 31-45 min, 1.28 (1.10, 1.48) for 46-60 min, 1.54 (1.32, 1.80) for 61-90 min, and 1.59 (1.33, 1.90) for ≥91 min, after adjusting for age, sex, and race. We found a nonlinear relationship (P nonlinearity 0.0002), with individuals with a sleep duration SD of >60 vs. ≤60 min having 34% higher diabetes risk (95% CI 1.22, 1.47). Further adjustment for lifestyle, comorbidities, environmental factors, and adiposity attenuated the association (HR comparing sleep duration SD of >60 vs. ≤60 min: 1.11; 95% CI 1.01, 1.22). The association was stronger among individuals with lower diabetes polygenic risk score (PRS; P interaction ≤ 0.0264) and longer sleep duration (P interaction ≤ 0.0009). Irregular sleep duration was associated with higher diabetes risk, particularly in individuals with a lower diabetes PRS and longer sleep duration.

Ultra-processed food consumption and risk of diabetes: results from a population-based prospective cohort.

Understanding the impact of the overall construct of ultra-processed foods on diabetes risk can inform dietary approaches to diabetes prevention. In this study, we aimed to evaluate the association between ultra-processed food consumption and risk of diabetes in a community-based cohort of middle-aged adults in the USA. We hypothesised that a higher intake of ultra-processed foods is associated with a higher risk of incident diabetes. The study included 13,172 participants without diabetes at baseline (1987-1989) in the Atherosclerosis Risk in Communities (ARIC) study. Dietary intake was assessed with a 66-item semiquantitative food frequency questionnaire, and foods were categorised by processing level using the Nova classification system. Ultra-processed food was analysed categorically (quartiles of energy-adjusted intake) and continuously (per one additional serving/day). We used Cox regression to evaluate the association of ultra-processed food intake with risk of diabetes with adjustment for sociodemographic characteristics, total energy intake, health behaviours and clinical factors. Over a median follow-up of 21 years, there were 4539 cases of incident diabetes. Participants in the highest quartile of ultra-processed food intake (8.4 servings/day on average) had a significantly higher risk of diabetes (HR 1.13; 95% CI 1.03, 1.23) compared with participants in the lowest quartile of intake after adjustment for sociodemographic, lifestyle and clinical factors. Each additional serving of ultra-processed food consumed daily was associated with a 2% higher risk of diabetes (HR 1.02; 95% CI 1.00, 1.04). Highest quartile consumption of certain ultra-processed food groups, including sugar- and artificially sweetened beverages, ultra-processed meats and sugary snacks, was associated with a 29%, 21% and 16% higher risk of diabetes, respectively, compared with the lowest quartile. We found that a higher intake of ultra-processed food was associated with higher risk of incident diabetes, particularly sugar- and artificially sweetened beverages, ultra-processed meats and sugary snacks. Our findings suggest interventions reducing ultra-processed food consumption and specific food groups may be an effective strategy for diabetes prevention.

Trends of diabetes in Beijing, China.

The global rise in diabetes prevalence is a pressing concern. Despite initiatives like "The Healthy Beijing Action 2020-2030" advocating for increased awareness, treatment, and control, the specific situation in Beijing remains unexplored. This study aimed to analyze the trends in diabetes prevalence, awareness, treatment, and control among Beijing adults. Through a stratified multistage probability cluster sampling method, a series of representative cross-sectional surveys were conducted in Beijing from 2005 to 2022, targeting adults aged 18-79 years. A face-to-face questionnaire, along with body measurements and laboratory tests, were administered to 111,943 participants. Data from all survey were age- and/or gender-standardized based on the 2020 Beijing census population. Annual percentage rate change (APC) or average annual percentage rate change (AAPC) was calculated to determine prevalence trends over time. Complex sampling logistic regression models were employed to explore the relationship between various characteristics and diabetes. From 2005 to 2022, the total prevalence of diabetes among Beijing adults aged 18-79 years increased from 9.6% (95% CI: 8.8-10.4%) to 13.9% (95% CI: 13.1-14.7%), with an APC/AAPC of 2.1% (95% CI: 1.1-3.2%, P<0.05). Significant increases were observed among adults aged 18-39 years and rural residents. Undiagnosed diabetes rose from 3.5% (95% CI: 3.2-4.0%) to 7.2% (95% CI: 6.6-7.9%) with an APC/AAPC of 4.1% (95% CI: 0.5-7.3%, P<0.05). However, diabetes awareness and treatment rates showed annual declines of 1.4% (95% CI: -3.0% to -0.2%, P<0.05) and 1.3% (95% CI: -2.6% to -0.2%, P<0.05), respectively. The diabetes control rate decreased from 21.5% to 19.1%, although not statistically significant (APC/AAPC=-1.5%, 95% CI: -5.6% to 1.9%). Overweight and obesity were identified as risk factors for diabetes, with ORs of 1.65 (95% CI: 1.38-1.98) and 2.48 (95% CI: 2.07-2.99), respectively. The prevalence of diabetes in Beijing has significantly increased between 2005 and 2022, particularly among young adults and rural residents. Meanwhile, there has been a concerning decrease in diabetes awareness and treatment rates, while control rates have remained stagnant. Regular blood glucose testing, especially among adults aged 18-59 years, should be warranted. Furthermore, being male, elderly, overweight, or obese was associated with higher diabetes risk, suggesting the needs for targeted management strategies.

Covid-19 vaccine hesitancy and its predictors among diabetic patients on follow-up at public hospitals in Nekemte Town, Western Ethiopia.

Understanding and addressing the concerns of vaccine-hesitant individuals, including those with chronic diseases, is key to increasing vaccine acceptance and uptake. However, in Ethiopia, there is limited evidence on the COVID-19 vaccine hesitancy and predictor variables among diabetic patients. Hence, the study aimed to assess Covid-19 Vaccine Hesitancy and Predictor variables among Diabetic Patients on Follow-Up at Public Hospitals in Nekemte Town, Western Ethiopia. Facility based cross sectional study was conducted among 422 diabetic patients attending public hospitals at Nekemte Town, Western Ethiopia between January, to February, 2023. Study participants were recruited by systematic random sampling. The data were collected interviewee administered pre-tested structured survey questioner. The collected data were entered and cleaned using Epi-Data software 4.6 version. The cleaned data were analyzed using SPSS. 25.0 Statical software. Descriptive statistics like frequency, mean and percentage, and binary logistic regression was applied to identify independent predictors of Covid-19 vaccine hesitancy and association between variables were declared at p-value of 0.05. The overall magnitude of COVID-19 vaccine hesitancy was 15.2% (95% CI: 11.6-18.7). The top three listed reasons for the COVID-19 vaccine hesitancy were: negative information about the vaccine (32.90%), lack of enough information (21.80%), and vaccine safety concern (19.40%). The hesitancy of the COVID-19 vaccination uptake among diabetes patients was independently influenced by age between 40-49 (Adjusted Odd Ratio [AOR] = 4.52(1.04-19.66)), having vaccine awareness (AOR = 0.029(0.001-0.86)), having a great deal of trust on vaccine development (AOR = 0.028(0.002-0.52)), and a fear amount trust (AOR = 0.05(0.003-0.79)) on the vaccine preparation, vaccinated for COVID-19 (AOR = 0.13(0.04-0.51)), perceived exposure to COVID-19 infection after having the vaccine as strongly agree/agree (AOR = 0.03(0.01-0.17))and neither agree nor disagree (AOR = 0.07(0.02-0.30)). COVID-19 vaccine hesitancy among diabetic patients was relatively low. The identified independent predictors were age, vaccine awareness, COVID-19 vaccination history, awareness on vaccine preparation and exposure status to COVID-19 infection. The relevant agency should focus on efforts to translating these high levels of vaccine acceptance into actual uptake, through targeting identifying predictor variables and vaccine availability for a high-risk diabetes patient.

The Plasma Levels of Protein Adiponectin (AdipoQ) and Meteorin-Like (Metrnl) in Newly Diagnosed Type 2 Diabetes Mellitus.

This study aimed to measure the concentrations of the Adiponectin and Meteorin - Like (Metrnl) in newly diagnosed type 2 diabetes patients. A comparative cross-sectional study contained two groups: Group 1 (86 newly diagnosed diabetes mellitus type 2 patients) and group 2 (71 healthy persons). The plasma concentrations of Adiponectin and Metrnl were measured by Enzyme Link Immunosorbent Assay (ELISA). The plasma level of Adiponectin of the newly diagnosed diabetes mellitus type 2 group and the healthy group were 1219.82 ng/mL (1132.43-2772.50) and 1187.25 ng/mL (1160.66-3807.50) respectively. The plasma level of Metrnl of two groups were 757.60 pg/mL (564.15-994.00) and 697.60 pg/mL (538.50-986.10) respectively. There were no significant difference between two groups. Metrnl had no correlation with glucose, HbA1c, lipid profile, BMI. Adiponectin had correlation with Metrnl and HDL-cholesterol. Adiponectin had no correlation to glucose, HbA1c, LDL-cholesterol, total cholesterol, triglyceride, BMI. People with the lower Adiponectin concentration had the higher risk of diabetes (OR=6.52; 95% CI: 2.43 -17.55). Adiponectin and Metrnl were not significantly different in newly diagnosed type 2 diabetes and healthy people. The lower concentration of Adiponectin might increase the risk of type 2 diabetes.

Sodium Intake and Incident Atrial Fibrillation in Individuals With Vascular Disease

Numerous prospective cohort studies have reported a J-shaped association of urinary sodium excretion with cardiovascular events and mortality. To study the association between sodium intake and incident atrial fibrillation (AF). This cohort study included participants in the Ongoing Telmisartan Alone and in Combination with Ramipril Global Endpoint Trial (ONTARGET) and Telmisartan Randomised Assessment Study in ACE Intolerant Subjects With Cardiovascular Disease (TRANSCEND) multicenter, randomized clinical trials comparing the effect of ramipril 10 mg daily with telmisartan 80 mg daily, or their combination (ONTARGET) or 80 mg telmisartan daily with placebo (TRANSCEND) for the outcome of death from cardiovascular causes, myocardial infarction, stroke, or hospitalization for heart failure. ONTARGET and TRANSCEND included 31 546 participants with vascular disease or high-risk diabetes, and this study excluded participants without a urine sample for sodium measurement, missing data for key covariates, a history of AF, or AF detected in the first year after enrollment. Analyses were performed in July 2023 to May 2024. Estimated sodium intake from a morning fasting urine sample (Kawasaki formula). The main outcome was incident AF. The association between estimated sodium intake and incident AF was modeled using multivariable adjusted Cox regression and cubic splines. A total of 27 391 participants (mean [SD] age, 66.3 [7.2] years; 19 310 [70.5%] male) were included. Mean (SD) estimated sodium intake was 4.8 (1.6) g/d. During a mean (SD) follow-up of 4.6 (1.0) years, 1562 participants (5.7%) had incident AF. After multivariable adjustment, a J-shaped association between sodium intake and AF risk was observed (P for nonlinearity = .03). Sodium intake of 8 g/d or greater (3% of participants) was associated with incident AF (hazard ratio, 1.32; 95% CI, 1.01-1.74) compared with sodium intake of 4 to 5.99 g/d. Cubic splines showed that sodium intake greater than 6 g/d (19% of participants) was associated with a 10% increased AF risk per additional 1-g/d sodium intake (hazard ratio, 1.10; 95% CI, 1.03-1.18), but with no further lowering of AF risk at lower levels of sodium intake. In this cohort study of sodium intake and AF risk, there was a J-shaped association between sodium intakes and AF risk in patients with cardiovascular disease or diabetes. Lowering sodium intake for AF prevention is best targeted at individuals who consume high sodium diets.