Efficiently assessing glucose handling capacity is a critical public health challenge. This study assessed the utility of relatively easy-to-measure continuous glucose monitoring (CGM)-derived indices in estimating glucose handling capacities calculated from resource-intensive clamp tests.

We conducted a prospective study of 64 individuals without prior diabetes diagnosis. The study performed CGM, oral glucose tolerance tests (OGTT), and hyperglycemic and hyperinsulinemic-euglycemic clamp tests. We validated CGM-derived indices characteristics using an independent dataset from another country and mathematical models with simulated data.

A CGM-derived index reflecting the autocorrelation function of glucose levels (AC_Var) is significantly correlated with clamp-derived disposition index (DI), a well-established measure of glucose handling capacity and predictor of diabetes onset. Multivariate and machine learning models indicate AC_Var's contribution to predicting clamp-derived DI independent from other CGM-derived indices. The model using CGM-measured glucose standard deviation and AC_Var outperforms models using commonly used diabetes diagnostic indices, such as fasting blood glucose, HbA1c, and OGTT measures, in predicting clamp-derived DI. Mathematical simulations also demonstrate the association of AC_Var with DI.

CGM-derived indices, including AC_Var, serve as valuable tools for predicting glucose handling capacities in populations without prior diabetes diagnosis. We develop a web application that calculates these CGM-derived indices ( https://cgm-ac-mean-std.streamlit.app/ ).

This meta-analysis evaluated the prevalence of gastric acid suppressants (GASs) in patients receiving vascular endothelial growth factor receptor tyrosine kinase inhibitors (VEGFR-TKIs) and explored drug-drug interactions (DDIs).

PubMed, Embase, and Cochrane Library were searched upto 20 October 2024. Studies comparing VEGFR-TKIs monotherapy versus VEGFR-TKIs with GASs, reporting pharmacodynamic (PD), pharmacokinetic (PK), or adverse events (AEs), were analyzed using random-effects models. Subgroups included cancer types and VEGFR-TKI types.

24 studies comprising 6,406 patients were included. The prevalence of GASs use in VEGFR-TKIs users was 40% (95% CI 31-50%). GASs significantly impaired survival, increasing mortality risk by 29% (OS HR 1.29,95% CI 1.14-1.45) and progression risk by 31% (PFS HR 1.31, 95% CI 1.06-1.61). PK analyses revealed clinically meaningful exposure reductions (AUC0-24GMR 0.78, 90% CI 0.65-0.94; Cmax GMR 0.80, 90% CI 0.70-0.91). AE incidence (except vomiting) did not differ between groups.

GASs may reduce the efficacy of most types of VEGFR-TKIs by decreasing their bioavailability, thereby having a detrimental effect on patient survival outcomes. It is recommended to give priority to H2 receptor antagonists (H2RAs) and monitor blood drug concentrations to optimize efficacy.

www.crd.york.ac.uk/prospero identifier CRD42024597729.

Most existing studies have primarily focused on the effects of Traditional Chinese Exercises (TCEs) on glycemic control in individuals with prediabetes, while specific recommendations for managing dyslipidemia in this population remain insufficient. Moreover, there is a lack of systematic research and conclusive evidence regarding the optimal exercise dose required to achieve metabolic improvements in individuals with prediabetes. Therefore, this meta-analysis aims to comprehensively evaluate the efficacy of TCEs in improving glycemic and lipid profiles in individuals with prediabetes and to explore the potential impact of exercise dose on these metabolic parameters.

A comprehensive search of six databases (PubMed, Web of Science, Cochrane Library, Embase, CNKI, and WanFang Data) followed PRISMA guidelines to identify randomized controlled trials (RCTs) on TCEs (e.g., "Tai Chi," "Yijinjing," "Baduanjin") and prediabetes (e.g., "impaired glucose tolerance," "impaired glucose regulation") published up to November 10, 2024. Three reviewers independently screened studies, extracted data, and assessed bias risk. Meta-analysis and subgroup/meta-regression analyses were conducted using Stata 17 software. The review protocol is registered in PROSPERO (CRD42024615150).

A total of 15 studies involving 1,839 participants were included. The meta-analysis revealed that TCEs significantly improved HbA1c (MD = -0.28%; 95% CI: -0.38% to -0.18%; P = 0.001), FBG (MD = -0.44 mmol/L; 95% CI: -0.53 to -0.34 mmol/L; P < 0.001), 2hPG (MD = -1.16 mmol/L; 95% CI: -1.48 to -0.85 mmol/L; P < 0.001), TC (MD = -0.31 mmol/L; 95% CI: -0.50 to -0.11 mmol/L; P = 0.002), TG (MD = -0.28 mmol/L; 95% CI: -0.50 to -0.06 mmol/L; P = 0.012), and HDL (MD = -0.28 mmol/L; 95% CI: -0.50 to -0.06 mmol/L; P = 0.012) compared to control groups.

TCEs significantly improve prediabetics' blood glucose and lipid levels. The recommended exercise regimen is 30-50 min per session, 2-3 times per week, for at least three months.

The CDC's Diabetes Prevention Program (DPP) is an effective lifestyle intervention to prevent type 2 diabetes (T2D). However, DPP implementation in rural areas is limited. This study sought to address this gap by implementing DPP in rural church settings through a community-academic partnership and identifying implementation facilitators and barriers.

This was a cross-sectional qualitative study. Semistructured interviews guided by the Consolidated Framework for Implementation Research (CFIR) assessed church leaders' and lifestyle coaches' perceptions of implementing DPP in rural churches. Thematic analysis was used to identify key themes through an inductive approach; then, these emergent themes were deductively linked to CFIR constructs. COREQ guidelines were used to report study findings.

Twenty-five stakeholders participated. Facilitators to implementing DPP included its evidence-based effectiveness in preventing T2D, as well as support from the academic partner in terms of funding, training, and communication. Additionally, DPP's alignment with community needs, along with the active engagement of pastors in participant recruitment, supported implementation. Several barriers hindered DPP implementation, including transportation and childcare issues, as well as program participants' medical conditions/disabilities limiting their participation. Furthermore, rural residents' reluctance to adopt lifestyle changes and loyalty to family churches posed challenges to their engagement in DPP.

This study identified contextual factors influencing DPP implementation in rural communities. Findings highlight the importance of tailored strategies that leverage facilitators while proactively addressing barriers, including rural residents' reluctance to attend programs outside their church, resistance to lifestyle changes, and transportation issues to ensure successful DPP implementation in rural areas.

This review emphasizes a novel, multidisciplinary, coordinated approach in the management of chronic liver diseases (CLDs).

Chronic liver diseases represent a significant global health burden, marked by a notable shift in the prevalence patterns from virus-related to metabolic and alcohol-related entities. Malnutrition, frailty, and sarcopenia exert a substantial impact on patients with cirrhosis, affecting 75%-90% of cases and escalating as the disease progresses. The European Association for the Study of the Liver recommends a comprehensive approach to nutritional care, emphasizing the need for detailed assessments in patients with cirrhosis, using diverse tools such as computed tomography scans, bioelectrical impedance analysis, and evaluations of muscle function. Considering the prevalence of nutritional and psychological disorders in the CLD population, the treatment of these patients should be founded indispensably on a multidisciplinary approach.

A systematic search was conducted of the PubMed, MEDLINE, and SCOPUS databases to identify trials investigating the health effects of nutritional and psychological assessments in patients with CLD.

In dealing with the treatment of patients with CLD, an exploration of the psychological domain emerges as crucial, because psychological distress, especially depression, exerts a tangible influence on patient outcomes. Thus, the engagement of psychologists and/or psychotherapists, who might use techniques such as cognitive behavioral therapy, could enhance patients' comprehension of nutritional implications in their treatment and make them more aware of their illness.

The review emphasizes the relevance of both nutritional and psychological assessments in patients with CLD that could improve patient education on the pivotal role of nutrition in disease management. Randomized controlled trials evaluating the combined impact of nutritional and psychological support are recommended to further investigate this complex clinical landscape.

Physical activity (PA) has an established role in the promotion of health and fitness and the prevention of disease. Expected overall benefits include reduction of all-cause morbidity and death, weight control, improved quality of life, improved bone health and decreased falls of elderly subjects, , deeper cognition, and reduced risk of depression, anxiety, and sleeplessness. Currently, PA is a mainstay in the management of cardiovascular diseases, metabolic syndrome, diabetes, and bone health. Recently, the perception of its role in primary and secondary prevention, interception, and treatment of cancer, however, is also gaining importance. Regular walking, the simplest type of PA, is associated with reduced all-cause and cardiovascular disease mortality, and a role in cancer prevention is of increasing interest. Furthermore, PA improves the quality of life of cancer patients, attenuating side effects of chemotherapy, decreasing sarcopenia, increasing fitness, and inhibiting the recurrence and progression of some cancer types. It promotes emotional and psychological benefits in patients, inducing positive changes. While mechanisms, effective levels and useful amount of PA practice are well established in cardiology, they are yet to be fully determined in oncology. Nevertheless, PA is recommended to reduce cancer risk in the general population, and it has been introduced in programs for the prevention of second cancers. In perspective, it will help as integrative therapy in cancer patients and for cancer survivors. The number of beneficial effects in the cancer continuum is highlighted in this review.

This study aims to explore the independent and combined associations of physical activity (PA) in different domains and inflammatory diet with type 2 diabetes mellitus (T2DM).

Data from 8736 American adults from the NHANES 2007-2016 were used. PA in different domains was assessed using the self-reported Global Physical Activity Questionnaire, and dietary inflammatory index was estimated based on 24 h dietary recalls. T2DM diagnosis was determined by a combination of self-report and laboratory data. A multivariate modified Poisson regression model was used to explore the independent and combined associations of moderate-vigorous intensity physical activity (MVPA) and inflammatory diet with T2DM.

PA in the Work MVPA, Recreational MVPA and Total MVPA domains was independently associated with reduced risk of T2DM, and an inflammatory diet was independently associated with elevated risk of T2DM. In the combined analysis, the combination of active and anti-inflammatory within the Work MVPA, Recreational MVPA and Total MVPA fields was associated with the greatest reduced risk of T2DM, and always associated with decreased risk of T2DM in the active group.

Our study emphasizes that the combination of active PA and anti-inflammatory diet is closely associated with the reduced risk of T2DM, and suggests the combination of both for the prevention and treatment of T2DM.

The purpose is to investigate the association between handgrip strength (HGS) and the risk of future diabetic complications in multicountry cohorts.

The association between HGS and diabetic complications was evaluated using cox models among 84 453 patients with pre-diabetes and diabetes from the UK Biobank with a 12-year follow-up. The association between HGS and longitudinal microcirculatory damage rates was assessed among 819 patients with diabetes from the Guangzhou Diabetic Eye Study (GDES) with a 3-year follow-up. Participants were divided into three age groups (<56, 56-65 and ≥65 years), and each group was further subdivided into three HGS tertiles.

A 5 kg reduction in HGS was associated with increased risk for all-cause mortality (women, HR=1.10, 95% CI: 1.05 to 1.14; p<0.001; men, HR=1.13, 95% CI: 1.11 to 1.15; p<0.001). Women and men in the lowest HGS group exhibited 1.6-times and 1.3-1.5-times higher risk of myocardial infarction and stroke compared with the highest HGS group. In men, there was a higher risk of developing end-stage renal disease (HR=1.83, 95% CI: 1.30 to 2.57; p=0.001), while this was not observed in women. Both sexes in the lowest HGS group had a 1.3-times higher risk of diabetic retinopathy compared with the highest HGS group. In the GDES group, individuals with the lowest HGS showed accelerated microcirculatory damage in retina (all p<0.05).

Reduced HGS is significantly associated with a higher risk of diabetic complications and accelerated microvascular damage. HGS could serve as a practical indicator of vascular health in patients with pre-diabetes and diabetes.

Type 2 diabetes prevention programs are effective but costly and intensive, making translation into routine primary care and community settings challenging. Identifying drivers of intervention effectiveness can inform pragmatic future implementation whilst maintaining effectiveness. Translational studies have demonstrated that delivery modalities impact their effectiveness. This systematic review and component network meta-analysis assessed which delivery modality components of non-pharmacological diabetes prevention programs are associated with reductions in type 2 diabetes incidence for individuals at high risk of type 2 diabetes (or pre-diabetes).

We searched MEDLINE, The Cochrane Library, Opengrey and clinicaltrials.gov from inception to November 17, 2022 for translational studies comparing lifestyle interventions with a minimum 12-month follow-up. Two investigators extracted the data. Random effects network meta-analyses and component network meta-analyses estimated the intervention effects.

We identified 50 eligible studies involving 29,286 participants including thirty-six (72.0 %) randomized controlled trials, 10 (20.0 %) cluster randomized controlled trials, and four (8.0 %) observational studies. Component network meta-analyses found in-person (individually) delivery was associated with greater reduction in incidence of type 2 diabetes (hazard ratio: 0.66, 95 % credible interval: 0.41, 0.96) and in-person (group-based) delivery was associated with greater reductions in weight (mean difference: -1.53 kg, 95 % credible interval: -2.18, -0.85) and HbA1c (mean difference: -0.74 mmol/mol, 95 % credible interval: -1.28, -0.17), relative to usual care.

This analysis suggests in-person delivery modalities are most effective for diabetes prevention. Future research should focus on improving the effectiveness of digital programs and ensuring preferential delivery for target populations to reduce health inequalities.

Purpose: Polypharmacy presents many challenges to patient medication self-management. This study aims to explore the self-management processes of medication in polypharmacy from the perspectives of both patients and healthcare providers, which can help identify barriers and facilitators to effective management. Methods: A systematic review of qualitative studies was performed by searching seven databases: PubMed, Web of Science, Cochrane Library, Embase, CINAHL, PsycINFO, and MEDLINE, from their establishment until August 2024. The Critical Appraisal Skills Programme (CASP) tool was employed to evaluate the quality of the studies included. The extracted data were then analysed thematically and integrated into The Taxonomy of Everyday Self-management Strategies (TEDSS) framework. Results: A total of 16 studies were included, involving 403 patients and 119 healthcare providers. Patient management measures were mapped into TEDSS framework, including categories such as medical management, support-oriented domains, and emotional and role management. Conclusion: Enhancing patients' proactive health awareness, improving medication literacy, balancing lifestyle adjustments with medication therapy, dynamically reviewing and optimizing medications, strengthening patients' social support networks, and helping patients integrate medication management into their daily life are the key elements that can effectively assist patients in self-managing their medications. Future interventions to improve patient medication self-management ability should be designed for these issues. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42024524742.

Two Hong Kong Chinese non-laboratory-based prediabetes/diabetes mellitus (pre-DM/DM) risk models were developed using logistic regression (LR) and machine learning, respectively. We aimed to evaluate the models' validity in case finding of pre-DM/DM in a Chinese primary care (PC) population. We also evaluated the validity of a risk-scoring algorithm derived from the LR model.

This was a cross-sectional external validation study on Chinese adults, without a prior DM diagnosis, who were recruited from public/private PC clinics in Hong Kong. A total of 1,237 participants completed a questionnaire on the models' predictors. Of that, 919 underwent blood glucose testing. The primary outcome was the models' and the algorithm's sensitivity in finding pre-DM/DM cases. The secondary outcomes were the models' and the algorithm's specificity, positive/negative predictive values, discrimination and calibration.

The models' sensitivity were 0.70 (machine learning) and 0.72 (LR). Both showed good external discrimination (area under the receiver operating characteristic curve: machine learning 0.744, LR 0.739). The risks estimated by the models were lower than the observed incidence, indicating poor calibration. Both models were more effective among participants with lower pretest probabilities; that is, age 18-44 years. The algorithm's sensitivity was 0.77 at the cut-off score of ≥16 out of 41.

This study showed the validity of the models and the algorithm for finding pre-DM/DM cases in a Chinese PC population in Hong Kong. They can facilitate more cost-effective identification of high-risk individuals for blood testing to diagnose pre-DM/DM in PC. Further studies should recalibrate the models for more precise risk estimation in PC populations.

Prebiotic fibre represents a promising and efficacious treatment to manage pre-diabetes, acting via complementary pathways involving the gut microbiome and viscosity-related properties. In this study, we evaluated the effect of using a diverse prebiotic fibre supplement on glycaemic, lipid and inflammatory biomarkers in patients with pre-diabetes. Sixty-six patients diagnosed with pre-diabetes (yet not receiving glucose-lowering medications) were randomised into treatment (thirty-three) and placebo (thirty-three) interventions. Participants in the treatment arm consumed 20 g/d of a diverse prebiotic fibre supplement, and participants in the placebo arm consumed 2 g/d of cellulose for 24 weeks. A total of fifty-one and forty-eight participants completed the week 16 and week 24 visits, respectively. The intervention was well tolerated, with a high average adherence rate across groups. Our results extend upon previous work, showing a significant change in glycated haemoglobin (HbA1c) in the treatment group but only in participants with lower baseline HbA1c levels (< 6 % HbA1c) (P = 0·05; treatment -0·17 ± 0·27 v. placebo 0·07 ± 0·29, mean ± sd). Within the whole cohort, we showed significant improvements in insulin sensitivity (P = 0·03; treatment 1·62 ± 5·79 v. placebo -0·77 ± 2·11) and C-reactive protein (P FWE = 0·03; treatment -2·02 ± 6·42 v. placebo 0·94 ± 2·28) in the treatment group compared with the placebo. Together, our results support the use of a diverse prebiotic fibre supplement for physiologically relevant biomarkers in pre-diabetes.

This study aimed to investigate the association between serum levels of common and uncommon unsaturated fatty acids and prediabetes risk.

Data were collected from the National Health and Nutrition Examination Survey for 2003-2004 and 2011-2012. Weighted proportional and multivariate logistic regression analyses were performed to assess the association of serum PUFAs and MUFAs with prediabetes risk after adjusting for potential confounders.

A total of 3575 individuals were enrolled in this study. Serum levels of PUFAs EPA (20:5 n3) and GLA (18:3 n6) were associated with increased prediabetes risk (EPA (20:5 n3): OR = 1.878, 95% CI: 1.177-2.996, Ptrend = 0.002; GLA (18:3 n6): 1.702, 95% CI: 1.140-2.541, Ptrend = 0.016). The MUFAs PA (16:1 n7) and EA (20:1 n9) were associated with the risk of prediabetes (OR in quintile5: PA (16:1 n7): 1.780, 95% CI: 1.056-3.001, Ptrend = 0.003; EA (20:1 n9): 0.587, 95% CI: 0.347-0.994, Ptrend = 0.010). Moreover, nonlinear analysis revealed that serum levels of EPA (20:5 n3) and EA (20:1 n-9) were nonlinearly associated with prediabetes risk.

Some serum n-3 PUFAs are positively associated with prediabetes, several serum n-6 PUFAs are inversely associated with prediabetes. Regulating individual serum USFA levels may help prevent prediabetes, thereby providing evidence for clinical and nutritional practices.

Women with gestational diabetes mellitus (GDM) are at a greater risk of developing type 2 diabetes mellitus (T2DM) than women without GDM. Despite this elevated risk, few trials on the prevention of T2DM among South Asian women with GDM have been reported. Therefore, this study aimed to assess the feasibility of conducting a diabetes prevention program on women with a history of GDM to inform the development of a contextually relevant definitive trial.

Using a randomized controlled trial, women with GDM (n = 180) who delivered at the study hospitals (one public and one private teaching hospital, Karachi) with fasting blood glucose levels < 120 mg/dl at 6 weeks postpartum were randomized to the intervention (n = 88) or control arms (n = 92). Women in the intervention group received individualized home-based educational sessions from trained community health workers at 0, 1, 3, 6, and 9 months. In addition, they received short text messages, prerecorded messages, and printed educational material (calendars and pamphlets) for reinforcement. The intervention was centered on equipping women with knowledge, skills, and confidence to eat a healthy diet rich in fruits, vegetables, and low-fat dairy products and perform regular physical activity based on walking and household chores to reduce weight (up to 5% of their initial body weight). Women in the control arm received standard care. The feasibility outcomes of the study included screening, recruitment, and retention rates and in-depth interviews at 6 months post-intervention to explore women's experiences with the intervention. Descriptive analysis and thematic analysis were performed.

Of the 324 women screened during the antenatal care visits and after delivery, 255 (78.7%) were contactable 6 weeks postpartum, and 180 (70.6%) were eligible and randomized to intervention (n = 88) and control (n = 92) groups. Loss to follow-up in the intervention and control arms was 22.7% (n = 20/88) and 18.5% (n = 17/92), respectively. Women expressed satisfaction with home-based counseling and follow-up visits, text message reminders, and printed material in the form of a calendar through our qualitative interviews.

Home-based lifestyle modification intervention augmented with text messages and printed material is feasible. However, to evaluate the intervention's effectiveness, a larger trial is warranted to assess its long-term impact on diabetes prevention.

ISRCTN, ISRCTN11387113 . Registered 5 December 2017-retrospectively registered.

Data from mechanistic studies suggest flavonoids may benefit glucose metabolism, but their associations with type 2 diabetes (T2D) remain unclear. This study examined the prospective associations of dietary intake of total, classes, and individual flavonoids, as well as their source foods, with T2D in the CArdioVascular disease Association Study (CAVAS).

A total of 16,666 Korean men and women were enrolled at baseline, and 953 were newly diagnosed with T2D over a median follow-up of 5.96 years. Intake of flavonoids was cumulatively averaged using all food frequency questionnaires before the censoring events. A Poisson regression model was used to estimate incidence rate ratios (IRRs) and 95% confidence intervals (CIs).

Women with higher total flavonoid, flavonol, isoflavone, and proanthocyanidin intake had a lower risk of T2D (fourth vs. first quartile, IRR 0.62; 95% CI 0.44-0.89; P for linearity and non-linearity < 0.05 for total flavonoids), while in men, flavanones, anthocyanins, and proanthocyanidins, but not total flavonoids, were inversely associated with T2D risk (all P interaction for sex > 0.05). The key source foods contributing to flavonoid intake were also different between men and women, except for apples: tangerines and strawberries in men and green leafy vegetables and soy products in women.

A higher intake of total flavonoids, particularly from vegetables, soybeans, and apples, may be associated with lower risk of T2D in women. However, flavonoids from fruits, rather than total flavonoids, may be inversely associated in men. The association between flavonoid intake and the risk of T2D may be contingent upon the dietary sources of flavonoids consumed.

Rates of prediabetes, which can lead to type 2 diabetes, are increasing worldwide. Interventions for prediabetes mainly focus on lifestyle changes to diet and exercise. While these interventions are effective, they are often delivered face-to-face, which may pose a barrier to those with limited access to healthcare. Given the evidence for digital interventions addressing other noncommunicable diseases, these may also be effective for prediabetes self-management. The aim of this scoping review was to assess the breadth of evidence around digital interventions for prediabetes self-management.

We developed a targeted search strategy and relevant studies were identified through searches conducted in four bibliographic databases (Medline, Embase, PsycInfo, and Scopus). Published studies were eligible if they included a digital intervention to support adults aged 18+ with prediabetes self-management. Titles and abstracts were first screened for relevance by one researcher. Full texts of selected records were assessed against the review criteria independently by two researchers for inclusion in the final analysis.

Twenty-nine studies were included, of which nine were randomised controlled trials. Most efficacy studies reported significant changes in at least one primary and/or secondary outcome, including participants' glycaemic control, weight loss and/or physical activity levels. About one-third of studies reported mixed outcomes or early significant outcomes that were not sustained at long-term follow-up. Interventions varied in length, digital modalities, and complexity. Delivery formats included text messages, mobile apps, virtually accessible dietitians/health coaches, online peer groups, and web-based platforms. Approximately half of studies assessed participant engagement/acceptability outcomes.

Whilst the evidence here suggests that digital interventions to support prediabetes self-management are acceptable and have the potential to reduce one's risk of progression to type 2 diabetes, more research is needed to understand which interventions, and which components specifically, have the greatest reach to diverse populations, are most effective at promoting user engagement, and are most effective in the longer term.

Obesity has become a global epidemic in the modern world, significantly impacting the global healthcare economy. Lifestyle interventions remain the primary approach to managing obesity, with medical therapy considered a secondary option, often used in conjunction with lifestyle modifications. In recent years, there has been a proliferation of newer therapeutic agents, revolutionizing the treatment landscape for obesity. Notably, glucagon-like peptide-1 receptor agonists (GLP-1 RAs), such as semaglutide, liraglutide, and the recently approved dual GLP-1/GIP RAs agonist tirzepatide, have emerged as effective medications for managing obesity, resulting in significant weight loss. These agents not only promote weight reduction but also improve metabolic parameters, including lipid profiles, glucose levels, and central adiposity. On the other hand, bariatric surgery has demonstrated superior efficacy in achieving weight reduction and addressing overall metabolic imbalances. However, with ongoing technological advancements, there is an ongoing debate regarding whether personalized medicine, targeting specific components, will shape the future of developing novel therapeutic agents for obesity management.

Background: A healthy eating pattern characterized by a higher intake of healthy plant foods has been associated with a lower risk of premature mortality, but whether this applies to individuals with varying glycemic status remains unclear. Methods: This study included 4621 participants with diabetes and 8061 participants with prediabetes from the US National Health and Nutrition Examination Survey (2007-2016). Using the dietary data assessed by two 24 h dietary recalls, a healthful plant-based diet index (hPDI) and an unhealthful plant-based diet index (uPDI) were created based on 15 food groups and were assessed for their relationships with mortality risk. Results: Over a median follow-up of 7.2 years, there were 1021 deaths in diabetes and 896 deaths in prediabetes. A higher hPDI (highest vs. lowest quartile) was associated with a 41% (HR = 0.59, 95% CI: 0.49-0.72; P-trend < 0.001) lower risk of all-cause mortality in diabetes and a 31% (HR = 0.69, 95% CI: 0.55-0.85; P-trend < 0.001) lower risk in prediabetes. A higher uPDI was associated with an 88% (HR = 1.88, 95% CI: 1.55-2.28; P-trend < 0.001) higher risk of mortality in diabetes and a 63% (HR = 1.63, 95% CI: 1.33-1.99; P-trend < 0.001) higher risk in prediabetes. Mediation analysis suggested that C-reactive protein and γ-glutamine transaminase explained 6.0% to 10.9% of the relationships between hPDI or uPDI and all-cause mortality among participants with diabetes. Conclusions: For adults with diabetes as well as those with prediabetes, adhering to a plant-based diet rich in healthier plant foods is associated with a lower mortality risk, whereas a diet that incorporates less healthy plant foods is associated with a higher mortality risk.

Physical activity has the potential to reduce the risk of diabetes after cancer diagnosis. However, current evidence supporting its effects is limited. This study aims to examine the associations between changes in physical activity and subsequent risk of diabetes among cancer survivors.

A total of 264,250 cancer survivors (mean age 56.7 (12.5) years, 44.2% males) without a prior history of diabetes were assessed for adherence to physical activity both before and after their diagnosis. The primary outcome was incident diabetes. The Fine-Gray proportional sub-distribution hazards model was used to calculate sub-distribution hazard ratios (sHRs) and 95% confidence intervals (CIs) for diabetes risk, considering death as a competing risk.

Over a follow-up of 1,065,802 person-years, maintaining regular physical activity from pre-diagnosis was associated with a 10% reduced risk of diabetes after cancer diagnosis (sHR 0.90, 95% CI 0.85-0.96), considering traditional diabetes risk factors, sociodemographics, and primary cancer sites. Cancer survivors who became active and inactive after their cancer diagnosis exhibited a marginally decreased risk of diabetes (sHR 0.98, 95% CI 0.93-1.03; sHR 0.97, 95% CI 0.92-1.03). The strength and direction of the association varied depending on the primary site of cancer.

Regular physical activity starting before a cancer diagnosis is associated with a lower risk of diabetes following the diagnosis, independent of established diabetes risk factors.

The study underscores the importance of engaging in sufficient physical activity to mitigate the risk of diabetes in cancer survivors.

Observational studies have shown that obesity considerably affects the cardiovascular system. Thus we conducted this Mendelian randomization (MR) analysis to evaluate the causal effect of childhood obesity on heart failure (HF) and its risk factors.

We obtained genetic instruments from genome-wide association studies (GWAS) that investigated childhood obesity, HF, type 2 diabetes mellitus (T2DM), atrial fibrillation (AF), coronary artery disease (CAD), myocardial infarction (MI), chronic kidney disease (CKD), valvular heart disease, myocarditis, hypertrophic cardiomyopathy, and hyperthyroidism. Inverse variance weighting (IVW), weighted median analysis, MR-Egger, and MR-pleiotropy residual sum and outlier (MR-PRESSO) were employed for MR analyses. In addition, the leave-one-out sensitivity test, MR-PRESSO global test, and Cochran's Q test were used for sensitivity analyses. Genetic evaluations showed that childhood obesity increases the risk of HF (odds ratio [OR] = 1.11, 95%CI: 1.05-1.17, p = 1.26 × 10-4), T2DM (OR = 1.17, 95%CI: 1.12-1.23, p = 8.80 × 10-12), AF (OR = 1.08, 95%CI: 1.05-1.12, p = 2.66 × 10-7), MI (OR = 1.08, 95%CI: 1.04-1.13, p = 3.35 × 10-4), and CAD (OR = 1.08, 95%CI: 1.03-1.13, p = 1.48 × 10-3). We found no association between childhood obesity and CKD, valvular heart disease, myocarditis, hypertrophic cardiomyopathy, or hyperthyroidism. Sensitivity analysis and Bonferroni's correction showed consistent results.

Our study provides new evidence for the relationship between childhood obesity and HF and its risk factors. The results indicate that individuals with a history of childhood obesity require more clinical attention to prevent the development of HF.

In diabetes, pancreatic β-cells gradually lose their ability to secrete insulin with disease progression. β-cell dysfunction is a contributing factor to diabetes severity. Recently, islet cell heterogeneity, exemplified by β-cell dedifferentiation and identified in diabetic animals, has attracted attention as an underlying molecular mechanism of β-cell dysfunction. Previously, we reported β-cell dedifferentiation suppression by calorie restriction, not by reducing hyperglycemia using hypoglycemic agents (including sodium-glucose cotransporter inhibitors), in an obese diabetic mice model (db/db). Here, to explore further mechanisms of the effects of food intake on β-cell function, db/db mice were fed either a high-carbohydrate/low-fat diet (db-HC) or a low-carbohydrate/high-fat diet (db-HF) using similar calorie restriction regimens. After one month of intervention, body weight reduced, and glucose intolerance improved to a similar extent in the db-HC and db-HF groups. However, β-cell dedifferentiation did not improve in the db-HC group, and β-cell mass compensatory increase occurred in this group. More prominent fat accumulation occurred in the db-HC group livers. The expression levels of genes related to lipid metabolism, mainly regulated by peroxisome proliferator-activated receptor α and γ, differed significantly between groups. In conclusion, the fat/carbohydrate ratio in food during calorie restriction in obese mice affected both liver lipid metabolism and β-cell dedifferentiation.

Many individuals with intermediate hyperglycaemia (IH), including impaired fasting glycaemia (IFG) and impaired glucose tolerance (IGT), as presently defined, will progress to type 2 diabetes (T2D). There is confirmatory evidence that T2D can be prevented by lifestyle modification and/or medications, in people with IGT diagnosed by 2-h plasma glucose (PG) during a 75-gram oral glucose tolerance test (OGTT). Over the last 40 years, a wealth of epidemiological data has confirmed the superior value of 1-h plasma glucose (PG) over fasting PG (FPG), glycated haemoglobin (HbA1c) and 2-h PG in populations of different ethnicity, sex and age in predicting diabetes and associated complications including death. Given the relentlessly rising prevalence of diabetes, a more sensitive, practical method is needed to detect people with IH and T2D for early prevention or treatment in the often lengthy trajectory to T2D and its complications. The International Diabetes Federation (IDF) Position Statement reviews findings that the 1-h post-load PG ≥ 155 mg/dL (8.6 mmol/L) in people with normal glucose tolerance (NGT) during an OGTT is highly predictive for detecting progression to T2D, micro- and macrovascular complications, obstructive sleep apnoea, cystic fibrosis-related diabetes mellitus, metabolic dysfunction-associated steatotic liver disease, and mortality in individuals with risk factors. The 1-h PG of 209 mg/dL (11.6 mmol/L) is also diagnostic of T2D. Importantly, the 1-h PG cut points for diagnosing IH and T2D can be detected earlier than the recommended 2-h PG thresholds. Taken together, the 1-h PG provides an opportunity to avoid misclassification of glycaemic status if FPG or HbA1c alone are used. The 1-h PG also allows early detection of high-risk people for intervention to prevent progression to T2D which will benefit the sizeable and growing population of individuals at increased risk of T2D. Using a 1-h OGTT, subsequent to screening with a non-laboratory diabetes risk tool, and intervening early will favourably impact the global diabetes epidemic. Health services should consider developing a policy for screening for IH based on local human and technical resources. People with a 1-h PG ≥ 155 mg/dL (8.6 mmol/L) are considered to have IH and should be prescribed lifestyle intervention and referred to a diabetes prevention program. People with a 1-h PG ≥ 209 mg/dL (11.6 mmol/L) are considered to have T2D and should have a repeat test to confirm the diagnosis of T2D and then referred for further evaluation and treatment. The substantive data presented in the Position Statement provides strong evidence for redefining current diagnostic criteria for IH and T2D by adding the 1-h PG.

We aimed to examine the concordance of type-2 diabetes, prediabetes and the metabolic syndrome in couples. In cross-sectional analyses, we used data from 1173 couples with index persons from the Heinz Nixdorf Recall Study (2011-2015), a population-based cohort study in Western Germany, and partners from the associated Heinz Nixdorf Multigeneration Study (2013-2016). Mean age (standard deviation) was 67.2 (6.6) years in index persons, and 67.8 (7.7) years in partners. The exposure was the presence of diabetes, prediabetes or metabolic syndrome in index persons, the outcome was the presence of the same health status in partners. Diabetes was defined by either self-reported diagnosis, intake of antidiabetic drugs or insulin, or HbA1c ≥ 6.5%. If the index person had prediabetes or diabetes, the partner was 1.46 (95% CI 1.07-2.00) times more likely to have diabetes than partners of index persons without the condition in the crude model (adjusted model: 1.33 (0.97-1.83)). For self-reported diabetes and for the metabolic syndrome, the corresponding prevalence ratios were 1.33 (0.90-1.97) and 1.17 (1.03-1.32), respectively (adjusted models: 1.23 (0.77-1.94), 1.04 (0.91-1.18)). In German couples, there was weak to moderate concordance of type-2 diabetes, prediabetes and the metabolic syndrome in crude, but poor concordance in adjusted models.

The study aimed to identify the most predictive factors for the development of type 2 diabetes. Using an XGboost classification model, we projected type 2 diabetes incidence over a 10-year horizon. We deliberately minimized the selection of baseline factors to fully exploit the rich dataset from the UK Biobank. The predictive value of features was assessed using shap values, with model performance evaluated via Receiver Operating Characteristic Area Under the Curve, sensitivity, and specificity. Data from the UK Biobank, encompassing a vast population with comprehensive demographic and health data, was employed. The study enrolled 450,000 participants aged 40-69, excluding those with pre-existing diabetes. Among 448,277 participants, 12,148 developed type 2 diabetes within a decade. HbA1c emerged as the foremost predictor, followed by BMI, waist circumference, blood glucose, family history of diabetes, gamma-glutamyl transferase, waist-hip ratio, HDL cholesterol, age, and urate. Our XGboost model achieved a Receiver Operating Characteristic Area Under the Curve of 0.9 for 10-year type 2 diabetes prediction, with a reduced 10-feature model achieving 0.88. Easily measurable biological factors surpassed traditional risk factors like diet, physical activity, and socioeconomic status in predicting type 2 diabetes. Furthermore, high prediction accuracy could be maintained using just the top 10 biological factors, with additional ones offering marginal improvements. These findings underscore the significance of biological markers in type 2 diabetes prediction.

Diabetes patients can draw on an increasing number of eHealth apps to support them in the self-management of their disease. While studies so far have focused on patients with type 1 diabetes, we explored how patients with type 2 diabetes mellitus (T2DM) integrate eHealth apps into their practices aimed at managing and coping with the disease, which aspects were considered particularly valuable and which challenges users encountered.

Semi-structured interviews and focus group sessions were conducted to explore how patients cope with T2DM in their daily lives and their attitude towards eHealth. In a further step, four eHealth apps were tested by patients and their expectations and experiences studied by way of qualitative interviews and focus groups.

The analysis showed that the study participants valued in particular the possibility to use eHealth apps to sense and gain a better understanding of their own body, to learn about specific responses of their body to nutrition and physical activity, and to support changes in daily routines and lifestyle. Key challenges encountered related to difficulties in interpreting the data, matching the data to other bodily sensations, getting overly occupied with the disease and difficulties in integrating the apps into personal, family, and care practices.

Under certain conditions, eHealth can play an important role for patients in developing a nuanced, personal understanding of their body and coping with T2DM. A prerequisite is that eHealth needs to be fitted into the specific practices of users, and patients desire a strong role by their care professionals in providing support in interpretation of data.

The identification of people who are at high risk of developing type 2 diabetes is a key part of population-level prevention strategies. Previous studies have evaluated the predictive utility of omics measurements, such as metabolites, proteins or polygenic scores, but have considered these separately. The improvement that combined omics biomarkers can provide over and above current clinical standard models is unclear. The aim of this study was to test the predictive performance of genome, proteome, metabolome and clinical biomarkers when added to established clinical prediction models for type 2 diabetes.

We developed sparse interpretable prediction models in a prospective, nested type 2 diabetes case-cohort study (N=1105, incident type 2 diabetes cases=375) with 10,792 person-years of follow-up, selecting from 5759 features across the genome, proteome, metabolome and clinical biomarkers using least absolute shrinkage and selection operator (LASSO) regression. We compared the predictive performance of omics-derived predictors with a clinical model including the variables from the Cambridge Diabetes Risk Score and HbA1c.

Among single omics prediction models that did not include clinical risk factors, the top ten proteins alone achieved the highest performance (concordance index [C index]=0.82 [95% CI 0.75, 0.88]), suggesting the proteome as the most informative single omic layer in the absence of clinical information. However, the largest improvement in prediction of type 2 diabetes incidence over and above the clinical model was achieved by the top ten features across several omic layers (C index=0.87 [95% CI 0.82, 0.92], Δ C index=0.05, p=0.045). This improvement by the top ten omic features was also evident in individuals with HbA1c <42 mmol/mol (6.0%), the threshold for prediabetes (C index=0.84 [95% CI 0.77, 0.90], Δ C index=0.07, p=0.03), the group in whom prediction would be most useful since they are not targeted for preventative interventions by current clinical guidelines. In this subgroup, the type 2 diabetes polygenic risk score was the major contributor to the improvement in prediction, and achieved a comparable improvement in performance when added onto the clinical model alone (C index=0.83 [95% CI 0.75, 0.90], Δ C index=0.06, p=0.002). However, compared with those with prediabetes, individuals at high polygenic risk in this group had only around half the absolute risk for type 2 diabetes over a 20 year period.

Omic approaches provided marginal improvements in prediction of incident type 2 diabetes. However, while a polygenic risk score does improve prediction in people with an HbA1c in the normoglycaemic range, the group in whom prediction would be most useful, even individuals with a high polygenic burden in that subgroup had a low absolute type 2 diabetes risk. This suggests a limited feasibility of implementing targeted population-based genetic screening for preventative interventions.

The increasing prevalence of diabetes is strongly associated with visceral adipose tissue (VAT), and gender differences in VAT remarkably affect the risk of developing diabetes. This study aimed to assess the predictive significance of lipid accumulation products (LAP) for the future onset of diabetes from a gender perspective.

A total of 8,430 male and 7,034 female non-diabetic participants in the NAGALA (NAfld in the Gifu Area, Longitudinal Analysis) program were included. The ability of LAP to assess the risk of future new-onset diabetes in both genders was analyzed using multivariate Cox regression. Subgroup analysis was conducted to explore the impact of potential modifiers on the association between LAP and diabetes. Additionally, time-dependent receiver operator characteristics (ROC) curves were used to assess the predictive power of LAP in both genders for new-onset diabetes over the next 2-12 years.

Over an average follow-up of 6.13 years (maximum 13.14 years), 373 participants developed diabetes. Multivariate Cox regression analysis showed a significant gender difference in the association between LAP and future diabetes risk (P-interaction<0.05): the risk of diabetes associated with LAP was greater in females than males [hazard ratios (HRs) per standard deviation (SD) increase: male 1.20 (1.10, 1.30) vs female 1.35 (1.11, 1.64)]. Subgroup analysis revealed no significant modifying effect of factors such as age, body mass index (BMI), smoking history, drinking history, exercise habits, and fatty liver on the risk of diabetes associated with LAP (All P-interaction <0.05). Time-dependent ROC analysis showed that LAP had greater accuracy in predicting diabetes events occurring within the next 2-12 years in females than males with more consistent predictive thresholds in females.

This study highlighted a significant gender difference in the association between LAP and future diabetes risk. The risk of diabetes associated with LAP was greater in females than in males. Furthermore, LAP showed superior predictive ability for diabetes at different time points in the future in females and had more consistent and stable predictive thresholds in females, particularly in the medium and long term.

Diabetes mellitus (DM) is a metabolic disease characterized by chronic hyperglycemia associated with impaired carbohydrate, lipid, and protein metabolism, with concomitant absence of insulin secretion or reduced sensitivity to its metabolic effects. Patients with diabetes mellitus have a 30% more risk of developing heart failure and cardiovascular disease compared to healthy people. Heart and cardiovascular problems are the first cause of death worldwide and the main complications which lead to high healthcare costs. Such complications can be delayed or avoided by taking prescribed medications in conjunction with a healthy lifestyle (i.e., diet and physical activity). The American College of Sports Medicine and the American Diabetes Association recommend that diabetic people reduce total sedentary time by incorporating physical activity into their weekly routine. This narrative literature review aims to summarize and present the main guidelines, pre-exercise cardiovascular screening recommendations, and considerations for patients with diabetes and comorbidities who are planning to participate in physical activity programs.

Precision prevention involves using the unique characteristics of a particular group to determine their responses to preventive interventions. This study aimed to systematically evaluate the participant characteristics associated with responses to interventions in gestational diabetes mellitus (GDM) prevention.

We searched MEDLINE, EMBASE, and Pubmed to identify lifestyle (diet, physical activity, or both), metformin, myoinositol/inositol and probiotics interventions of GDM prevention published up to May 24, 2022.

From 10347 studies, 116 studies (n = 40940 women) are included. Physical activity results in greater GDM reduction in participants with a normal body mass index (BMI) at baseline compared to obese BMI (risk ratio, 95% confidence interval: 0.06 [0.03, 0.14] vs 0.68 [0.26, 1.60]). Combined diet and physical activity interventions result in greater GDM reduction in participants without polycystic ovary syndrome (PCOS) than those with PCOS (0.62 [0.47, 0.82] vs 1.12 [0.78-1.61]) and in those without a history of GDM than those with unspecified GDM history (0.62 [0.47, 0.81] vs 0.85 [0.76, 0.95]). Metformin interventions are more effective in participants with PCOS than those with unspecified status (0.38 [0.19, 0.74] vs 0.59 [0.25, 1.43]), or when commenced preconception than during pregnancy (0.21 [0.11, 0.40] vs 1.15 [0.86-1.55]). Parity, history of having a large-for-gestational-age infant or family history of diabetes have no effect on intervention responses.

GDM prevention through metformin or lifestyle differs according to some individual characteristics. Future research should include trials commencing preconception and provide results disaggregated by a priori defined participant characteristics including social and environmental factors, clinical traits, and other novel risk factors to predict GDM prevention through interventions.

This meta-analysis aimed to compare the effectiveness of metformin versus lifestyle interventions in preventing diabetes in individuals with prediabetes. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and conducted a comprehensive search of databases (PubMed, Cochrane Library, EMBASE) up to September 1, 2023. Five eligible studies were included. The results showed that there was no significant difference in the risk of developing diabetes between the metformin and lifestyle intervention groups (RR: 1.14, 95% CI: 0.77-1.68). Similarly, when comparing metformin with lifestyle intervention, the risk of diabetes was slightly higher in the metformin group, but this difference was not statistically significant (RR: 1.31, 95% CI: 0.93-1.86). When comparing metformin with lifestyle intervention to lifestyle intervention alone, no significant difference was observed in the incidence of diabetes (RR: 0.88, 95% CI: 0.74-1.04). In conclusion, our analysis found that the incidence of type 2 diabetes was slightly higher in patients receiving metformin alone compared to lifestyle intervention, but this difference did not reach statistical significance. Further trials are necessary to better evaluate these interventions for preventing type 2 diabetes in high-risk individuals.

We compared the impact of 2 lifestyle modifying physical activities, yoga (YBLM) or walking (WBLM) on impaired beta cell function (IBF) or insulin resistance (IR) in restoring acute phase insulin release (APIR) among prediabetes at high risk for type 2 diabetes (HRDM).

Male and female adults (N = 42, 38.1 ± 4.8 years) with abdominal obesity (Male:103 ± 8.1 cm) Female: 92 ± 11.1 cm), randomized into YBLM (n = 20) and WBLM (n = 22), were monitored for the practice of the intervention, 45 min a day/5 days a week for 12 weeks. Blood sample was collected at 0th minute to estimate the level of Fasting Blood Glucose (FBG), Sr. Insulin and lipid profile and at 10th minute (APIR). IBF, IR and sensitivity (IS) reading were checked in HOMA-2 calculator.

Wilcoxon sign rank t-test denoted an improved APIR among the subjects with IBF (p = 0.008) and not among the subjects with IR (p = 0.332). However, regression analysis yielded an improved APIR among subjects with IBF (F(1,10) = 7.816, p = 0.002) with the management of body weight and lipid profile and IR (F(1,13) = 17.003, p = 0.001) being found influenced with selected lipid components. In all, during the post assessment period, an impressive boost in APIR was manifested among people shifted to Normoglycemia (n = 14, 35.9%).

Intriguingly, we postulate the potential role of YBLM over WBLM in the management of lipid profile and body weight on accelerating APIR either through improved Beta cell compensation or by sensitizing skeletal muscles regulating IR, helping improve glucose tolerance resulting in either remission or management of prediabetes.

Concerning ascending trend in the prevalence of chronic type II diabetes, prevention and the development of an effective approach after the recognition of at-risk individuals is crucial. This study aims to investigate comparing the influence of lifestyle modification and metformin interventions in the prevention of type II diabetes developments.

The search was conducted using PubMed, Google Scholar, Scopus and Web of Science databases. The inclusion criteria include randomized controlled trials (RCT) which studied both lifestyle modification and metformin interventions in the population above 18 years old without a history of any type of diabetes. After excluding studies with intervention time of fewer than 6 months, a systematic review and meta-analysis were performed to evaluate relative risk (RR) with a confidence interval (CI) of 95% of type II diabetes development.

Data from 5 studies were included in the meta-analysis. The population also consists of individuals with a mean age of 50 years old with BMI and FBS of 35.5 and 104.7 mg/dl respectively. Participants range of prevention years was between 2-3 years with a mean of 2.8 years. Lifestyle modification decreases the probability of the incidence of type II diabetes by 25.3% (RR: 0.747, 95% CI, 0.6-0.92) compared to the metformin intervention (p-value = 0.007). Our results indicate that long-term lifestyle modifications can prevent diabetes type II and decrease diabetes mellitus incidence down to one-quarter in comparison to metformin.

Lifestyle modification can be more efficacious than metformin in diminishing the incidence of type II diabetes. Therefore, lifestyle modification can be a therapeutic strategy for controlling type II diabetes incidence, especially in high-risk individuals.

To investigate the association of updated cardiovascular health (CVH) metrics, including sleep health, with the risk of diabetes and major adverse cardiovascular events (MACE) in older adults with prediabetes.

A total of 7,948 older adults with prediabetes aged ≥ 65 years were included in this study. CVH was assessed using seven baseline metrics according to the modified American Heart Association recommendations.

During a median follow-up time of 11.9 years, 2,405 (30.3%) cases of diabetes and 2,039 (25.6%) MACE were recorded. Compared with the poor composite CVH metrics group, the multivariable-adjusted hazard ratios (HRs) in the intermediate and ideal composite CVH metrics groups were respectively 0.87 (95% confidence intervals [CI] = 0.78-0.96) and 0.72 (95% CI = 0.65-0.79) for diabetes events and 0.99 (95% CI = 0.88-1.11) and 0.88 (95% CI = 0.79-0.97) for MACE. The ideal composite CVH metrics group had a lower risk of diabetes and MACE in older adults aged 65-74 years, but not in those aged ≥ 75 years.

Ideal composite CVH metrics in older adults with prediabetes were associated with a lower risk of diabetes and MACE.

Previous research has shown that lifestyle modification can delay or prevent the onset of type 2 diabetes in high-risk individuals. The Norfolk Diabetes Prevention Study (NDPS) was a parallel, three-arm, randomized controlled trial with up to 46 months follow-up that tested a group-delivered, theory-based lifestyle intervention to reduce the incidence of type 2 diabetes in high-risk groups. The current study aimed to evaluate if the NDPS intervention was delivered to an acceptable standard and if any part(s) of the delivery required improvement.

A sub-sample of 30, 25 for inter-rater reliability and audio-recordings of the NDPS intervention education sessions were assessed independently by two reviewers (CT, TW) using a 12-item checklist. Each item was scored on a 0-5 scale, with a score of 3 being defined as 'adequate delivery'. Inter-rater reliability was assessed. Analysis of covariance (ANCOVA) was used to assess changes in intervention fidelity as the facilitators gained experience.

Inter-rater agreement was acceptable (86%). A mean score of 3.47 (SD = .38) was achieved across all items of the fidelity checklist and across all intervention facilitators (n = 6). There was an apparent trend for intervention fidelity scores to decrease with experience; however, this trend was non-significant (p > .05) across all domains in this small sample.

The NDPS was delivered to an acceptable standard by all Diabetes Prevention Facilitators. Further research is needed to better understand how the intervention's delivery characteristics can be optimized and how they might vary over time.

To assess three well-established type 2 diabetes (T2D) risk prediction models based on fasting plasma glucose (FPG) in Chinese, Malays, and Indians, and to develop simplified risk models based on either FPG or HbA1c.

We used a prospective multiethnic Singapore cohort to evaluate the established models and develop simplified models. 6,217 participants without T2D at baseline were included, with an average follow-up duration of 8.3 years. The simplified risk models were validated in two independent multiethnic Singapore cohorts (N = 12,720).

The established risk models had moderate-to-good discrimination (area under the receiver operating characteristic curves, AUCs 0.762 - 0.828) but a lack of fit (P-values < 0.05). Simplified risk models that included fewer predictors (age, BMI, systolic blood pressure, triglycerides, and HbA1c or FPG) showed good discrimination in all cohorts (AUCs ≥ 0.810), and sufficiently captured differences between the ethnic groups. While recalibration improved fit the simplified models in validation cohorts, there remained evidence of miscalibration in Chinese (p ≤ 0.012).

Simplified risk models including HbA1c or FPG had good discrimination in predicting incidence of T2D in three major Asian ethnic groups. Risk functions with HbA1c performed as well as those with FPG.

Diabetes mellitus is a global epidemic disease. Long-time exposure of patients to hyperglycemia can lead to various type of chronic tissue damage. Early diagnosis of and screening for diabetes are crucial to population health.

We collected the national physical examination data in Xinjiang, China, in 2020 (a total of more than 4 million people). Three types of physical examination indices were analyzed: questionnaire, routine physical examination and laboratory values. Integrated learning, deep learning and logistic regression methods were used to establish a risk model for type-2 diabetes mellitus. In addition, to improve the convenience and flexibility of the model, a diabetes risk score card was established based on logistic regression to assess the risk of the population.

An XGBoost-based risk prediction model outperformed the other five risk assessment algorithms. The AUC of the model was 0.9122. Based on the feature importance ranking map, we found that hypertension, fasting blood glucose, age, coronary heart disease, ethnicity, parental diabetes mellitus, triglycerides, waist circumference, total cholesterol, and body mass index were the most important features of the risk prediction model for type-2 diabetes.

This study established a diabetes risk assessment model based on multiple ethnicities, a large sample and many indices, and classified the diabetes risk of the population, thus providing a new forecast tool for the screening of patients and providing information on diabetes prevention for healthy populations.

Women with polycystic ovary syndrome (PCOS) are at increased risk for dysglycemia and type 2 diabetes compared to healthy BMI-matched women of reproductive age: robust evidence exists supporting this notion. The presence of altered glycemic status in young women with the syndrome presents a distinct challenge for the clinician for several reasons. Firstly, the reported incidence of this disorder varies among the limited available studies. Furthermore, there is a lack of consensus on the best screening method, which women to screen, at what frequency, and which strategies need to be implemented to reduce the above risk. We provide data regarding the prevalence of dysglycemia in young women suffering from PCOS and the pathophysiological mechanisms underlying the disorder. In addition, we present evidence suggesting universal screening with the oral glucose tolerance test in young women with the syndrome, irrespective of age or BMI status, to identify and manage glycemic abnormalities in a timely manner. Regarding follow-up, oral glucose testing should be carried out at regular intervals if there are initial abnormal findings or predisposing factors. Finally, the efficacy of a well-balanced diet in conjunction with regular exercise and the use of non-pharmacologic agents in this specific population is discussed.