The prevalence of diabetes continues to increase - more than 38 million people in the US now have diabetes and 84 million have prediabetes. Because many new cases of incident diabetes may be attributed to suboptimal dietary quality, novel programs and policies to encourage healthy eating choices represent promising population-level approaches to reduce the number of new cases of diabetes.

To help estimate the potential impact of such programs and policies, we created the Microsimulation of Nutrition, Diabetes, and Cardiovascular Disease (MONDAC), a model to estimate the impact of simulated population-level dietary changes on downstream outcomes: body mass index, diabetes incidence, cardiovascular disease (CVD) incidence, all-cause mortality, quality-adjusted life years, direct medical costs, and cost-effectiveness.

We used 24-hour recall data from the National Health and Nutrition Examination Survey to categorize food and beverage consumption into 51 mutually exclusive categories to understand the effects of dietary changes. We simulated the energy intake and dietary quality effects that result from increasing, decreasing, or reallocating intake of these 51 food categories. Reductions in calories induce weight loss via an energy balance model. Weight loss and improvements in dietary quality drive annual reductions in diabetes and CVD risk. Mortality was modeled using a lifetable approach, and direct medical care costs were applied using estimates from the literature. We cross-validated MONDAC with existing models to assess reliability of estimates. We provide an example simulation for MONDAC, modeling a reduction in sugar-sweetened beverage consumption at the national level in the US.

MONDAC provides a flexible approach to policy analysis to allow the user to simulate various food-related policies.

We aimed to examine the individual and combined impact of prehypertension, prediabetes, and predyslipidemia on all-cause and cardiovascular disease (CVD) mortality in community-dwelling adults. A retrospective cohort study of 11 986 US adults from the 1999-2018 National Health and Nutrition Examination Survey was conducted. Participants were categorized into four mutually exclusive groups based on the cumulative number of these conditions. Multivariate Cox proportional hazards models were applied to calculate the hazard ratios (HRs) and 95% confidence intervals (CIs) for mortality outcomes. The prevalences of no, one, two, and all three preclinical conditions were 37.20%, 38.39%, 19.86%, and 4.55%, respectively. Over a median follow-up of 10 years, 636 (3.83%) deaths occurred, including 170 (26.73%) from CVD. In a dose-response manner, the adjusted HRs (95%CIs) for all-cause mortality among those with one, two, and three conditions were 1.87 (1.38-2.52), 2.49 (1.80-3.44), and 2.62 (1.76-3.90), respectively, compared to those with none. The corresponding HRs (95%CIs) for CVD mortality were 3.09 (1.66-5.78), 3.89 (2.06-7.36), and 4.20 (2.04-8.69), respectively. Thus, an increasing cumulative number of preclinical conditions is associated with graded elevated risk of all-cause and CVD mortality, underscoring the potential for early intervention during the preclinical phase to improve long-term health outcomes.

Ramadan fasting involves prolonged daily abstinence from food and water and may affect blood pressure (BP) regulation, particularly in individuals with chronic conditions. Evidence focusing specifically on ambulatory BP characteristics during Ramadan remains limited. This study evaluated 24-hour ambulatory BP monitoring (ABPM) parameters obtained during Ramadan in fasting and non-fasting individuals. In this prospective cross-sectional study, 231 adults underwent 24-hour ABPM during Ramadan between 2021 and 2023. Participants were classified as fasting or non-fasting and as hypertensive or non-hypertensive. Demographic characteristics, comorbidities, laboratory findings, and echocardiographic parameters were recorded. Ambulatory BP values were analyzed for 24-hour, daytime, and nighttime periods. Of the participants, 117 were fasting and 114 were non-fasting. Baseline demographic characteristics and cardiovascular comorbidities were similar between groups, although diabetes mellitus (DM) and chronic kidney disease (CKD) were more frequent in non-fasting individuals. No significant differences were observed in 24-hour or daytime systolic and diastolic BP values. Mean nighttime BP was lower in fasting participants (p = 0.032). Echocardiographic parameters were comparable. Fasting individuals had higher serum albumin levels (p = 0.027) and lower neutrophil counts (p = 0.030), while other biochemical markers did not differ significantly. Ramadan fasting was not associated with adverse ambulatory BP changes in hypertensive or normotensive individuals and may be considered safe in appropriately selected patients with well-controlled hypertension (HT).

Diabetic kidney disease (DKD) is a severe microvascular complication of diabetes characterized by complex pathogenesis in which renal cellular senescence is a critical pathological element. Traditionally, hyperglycemia has been regarded as a uniform stressor inducing cellular senescence; however, significant heterogeneity exists in different renal cell types' responses to high glucose (HG) stimulation. This review systematically elucidates mechanisms underlying senescence of major renal cell types under hyperglycemic conditions. Hyperglycemia acts as a common initiator triggering senescence via shared pathways, including oxidative stress and metabolic dysregulation. However, owing to distinct structural, functional, and molecular profiles across cell types, divergent senescence programs are activated. Specifically, podocyte senescence centers on GSK3β-mediated collapse of metabolic homeostasis and GPR124 axis-related mechanosensing dysfunction; mesangial cell (MC) senescence manifests as STAT5- and Caveolin-1 signaling-mediated "senescence-fibrosis" vicious cycles; glomerular endothelial cell (GEC) senescence is characterized by dysregulation of the NOS/NO signaling axis and glycocalyx damage; and renal tubular epithelial cell (TEC) senescence is initiated by mitochondrial damage under metabolic overload, promoting interstitial fibrosis through the senescence-associated secretory phenotype (SASP). By revealing this heterogeneous mechanism shifting from "common stress" to "specific responses," this review offers a novel perspective on DKD pathogenesis and establishes a theoretical foundation for developing targeted anti-senescence therapies. It further discusses implications for the clinical translation of renal protective agents.

The haemoglobin glycation index (HGI) reflects individual variations in glycation tendency and may offer additional value beyond HbA1c in predicting diabetes-related complications. This study aimed to evaluate the association and predictive value of HGI for diabetic kidney disease (DKD) in patients with type 2 diabetes mellitus (T2DM).

A total of 400 T2DM patients were enrolled. Predicted HbA1c was calculated using a linear regression equation (R2=0.454) derived from fasting plasma glucose (FPG) and HGI was defined as the difference between measured and predicted HbA1c. Paired t-tests and Pearson correlation assessed the relationship between measured and predicted HbA1c. Multivariate logistic regression and receiver operating characteristic (ROC) analysis used to evaluate HGI as a predictor of DKD.

A strong positive correlation observed (r=0.674, p<0.001) between measured and predicted HbA1c and no significant difference observed (p=0.964) among the T2DM population. DKD was identified in 192 participants, who demonstrated significantly higher HGI compared to non-DKD patients (p=0.002). Multivariate analysis showed HGI (OR: 1.249, 95% CI: 1.053-1.482, p=0.011) and eGFR (OR: 0.964, 95% CI: 0.952-0.976, p<0.001) were independent risk factors for DKD. ROC analysis showed HGI as a moderate predictor of DKD (AUC=0.722, p<0.001), with an optimal cutoff of 0.53 carries 56.3% sensitivity and 81.2% specificity.

HGI is independently associated with DKD in T2DM and may serve as a useful adjunct marker, complimenting HbA1c and urinary albumin-to-creatinine ratio (UACR) for early identification of those at increased risk of kidney complications.

This study aimed to evaluate the effect of a 50% reduction in preprandial bolus insulin (50%-B) on plasma glucose (PG) responses during postprandial exercise of continuous moderate intensity (CONT) and intermittent high intensity (INT) in individuals with type 1 diabetes (T1D).

Sixteen adults with T1D (31% male), treated with multiple daily insulin injections (MDI), participated in a randomized crossover study comprising four experimental conditions, separated by a washout period of at least 48 hours. Participants performed two 30-minute, preceded by a 3-minute warm-up without weights:• CONT: continuous cycling at 60% of maximal aerobic power (MAP).• INT: 2-minute intervals alternating between 40% and 80% of MAP, repeated for 7 intervals, with the last interval adjusted so that the total exercise time is exactly 30 minutes. Each exercise modality was performed under two insulin conditions: a full preprandial bolus (100%-B) and a 50% reduction (50%-B). Plasma glucose, insulin, and cortisol were measured before, during, and after exercise. Linear mixed models were used to analyze temporal changes and condition effects.

Blood glucose decreased significantly over time for both exercise types (p < 0.001). During CONT, the decline in PG was similar between doses (Δ100%-B: -3.01 ± 2.96 vs. Δ50%-B: -2.82 ± 2.28 mmol/L; p = 0.18), However, the nadir PG was higher with 50%-B compared to 100%-B (8.59 ± 4.07 vs. 5.69 ± 3.06 mmol/L, respectively; β = +2.91 mmol/L; p = 0.026), and hypoglycemia was less frequent (2 vs. 18 episodes; p = 0.028). During INT, PG decreased less with 50%-B than with 100%-B (Δ: -2.03 ± 1.63 vs. -3.62 ± 2.76 mmol/L; p = 0.022), with no hypoglycemic episodes under 50%-B compared to six with 100%-B. Mean PG remained higher with 50%-B across both exercise types (p < 0.01). Plasma insulin decreased over time (p = 0.038) regardless of bolus condition, while cortisol increased more during INT with 100%-B than with 50%-B (p = 0.02).

Reducing the preprandial bolus insulin by 50% effectively attenuates exercise-induced declines in plasma glucose and substantially reduces hypoglycemia risk, particularly during intermittent high-intensity exercise. These results emphasize the clinical relevance of personalized insulin adjustments to enhance metabolic safety during exercise in individuals with T1D.

To investigate the role of early pregnancy thyroid function in gestational diabetes mellitus (GDM) development and its influencing factors.

This large-scale retrospective cohort study assessed the associations between early pregnancy thyroid hormones and GDM subtypes, as well as their non-linear relationship with oral glucose tolerance test (OGTT) glucose levels, using multivariate logistic regression and restricted cubic spline models. Subgroup analyses were conducted within the normal thyroid function range to evaluate the risk associated with low-normal FT4 levels.

A total of 40,682 pregnant women were included and classified into four groups based on glucose levels: isolated fasting hyperglycemia (IFH), isolated post-load hyperglycemia (IPH), combined hyperglycemia (CH), and normal glucose tolerance (NGT). Free thyroxine (FT4) showed strong capability in differentiating among the subtypes, while thyroid-stimulating hormone (TSH) had limited effects. Multivariate and non-linear analyses showed a J-shaped association between FT4 and fasting/1-hour OGTT glucose, with strong protection below 15.4 pmol/L. In contrast, TSH showed weaker associations without a clear threshold effect. Importantly, low-normal FT4 (11.6-15.4 pmol/L), even within the normal range, independently increased GDM risk, especially in nulliparous and overweight/obese women.

FT4 is an independent risk factor for GDM, with parity and pre-pregnancy BMI serving as important effect modifiers. Even the low-normal FT4 levels are associated with a higher risk of developing GDM and macrosomia.

Diabetic kidney disease (DKD) is a highly significant microvascular complication that arises from diabetes. Therefore, this study aimed to ascertain the traditional risk factors for DKD in type 2 diabetes mellitus (T2DM) in Asia, raising awareness of these risk factors among patients with T2DM.

PubMed, Embase, Web of Science, and Cochrane Library were systematically searched until 13 Mar 2026. Case-control or cohort studies in Asia on the risk factors for DKD were included. Egger's test and funnel plots were used to assess publication bias. Stata 15 was used for statistical analysis.

7 case-control studies (including 3,312 participants) and 17 cohort studies (including 8,735 participants) were included. All the included studies were of high quality according to the Newcastle-Ottawa Scale (NOS). Systolic blood pressure (SBP), hypertension, glycosylated hemoglobin (HbA1c), waist-to-hip ratio (WHR), fasting blood glucose (FBG), uric acid (UA), creatinine (Cr), age and diabetes duration were risk factors for DKD in T2DM. Diabetic retinopathy (DR) was closely associated with DKD, and this association was also evident in subgroups defined by pathological diagnosis. SBP was a risk factor in both the clinical diagnosis group and the pathological diagnosis group.

This meta-analysis preliminarily demonstrates that SBP, hypertension, HbA1c, WHR, FBG, UA, Cr, age, diabetes duration and DR are associated with DKD in Asia. SBP and DR are associated with renal biopsy-confirmed DKD.

https://www.crd.york.ac.uk/PROSPERO/recorddashboard, identifier CRD42024529789.

Achieving rapid glycemic stabilization is a critical goal in the inpatient management of type 2 diabetes mellitus(T2DM). This study aimed to develop and validate a nomogram incorporating the hemoglobin, albumin, lymphocyte, and platelet (HALP) score and key clinical parameters to predict the time to glycemic stability in hospitalized T2DM patients.

We conducted a retrospective analysis of 356 hospitalized T2DM patients. Baseline demographic, clinical, and laboratory data, including the HALP score, were collected. Univariate and multivariate Cox proportional hazards regression analyses were performed to identify independent predictors for the time to glycemic stability. The model's discriminative ability was assessed using the concordance index, and its calibration was evaluated with calibration curves. Decision curve analysis (DCA) was used to estimate clinical utility.

Multivariate Cox regression analysis identified older age, lower hemoglobin level, higher hemoglobin A1c (HbA1c), and a lower HALP score as independent risk factors associated with a longer time to glycemic stability. These four variables were integrated into a prognostic nomogram, which demonstrated good predictive accuracy, with a C-index of 0.81(95% CI:0.78 - 0.84) in the training cohort. The calibration curves showed satisfactory agreement between predicted and observed probabilities. Decision curve analysis (DCA) indicated favorable clinical net benefit across a reasonable range of threshold probabilities.

We developed and validated a practical nomogram that effectively predicts the time to glycemic stability in hospitalized T2DM patients, that may assist clinicians in early identification of patients at risk for delayed stabilization, thereby facilitating personalized management strategies and optimizing inpatient diabetes care.

This study aimed to evaluate the clinical utility of novel inflammatory and metabolic composite indices in early risk prediction of microvascular complications in patients with type 2 diabetes mellitus (T2DM), and to provide reliable evidence for early precision risk stratification.

A retrospective analysis was conducted on 964 hospitalized patients with T2DM admitted to the Department of Endocrinology, First Affiliated Hospital of Xinjiang Medical University, from September 2023 to March 2025. Patients were randomly assigned to a training cohort and a validation cohort at a ratio of 7:3 using a random number table. In the training cohort, least absolute shrinkage and selection operator (LASSO) regression was applied for variable selection and to reduce multicollinearity, followed by univariate and multivariate logistic regression analyses to identify independent risk factors for T2DM related microvascular complications. Receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) were employed to comprehensively assess the predictive performance and clinical utility of the model.

Multifactorial logistic regression analysis showed that age, duration of diabetes, duration of hypertension, urine albumin-to-creatinine ratio (UACR) > 30 mg/g, as well as core indicators SIRI and TyG index, were significantly associated with the occurrence of microvascular complications in type 2 diabetes mellitus (T2DM) (P < 0.05). The predictive model constructed based on LASSO-logistic regression demonstrated an AUC of 0.869 (95% CI: 0.842-0.895) in the training set and an AUC of 0.864 (95% CI: 0.824-0.905) in the validation set, indicating stable and excellent discriminatory ability.

This study confirms that SIRI and TyG index can serve as independent risk factors for microvascular complications in T2DM. The nomogram model constructed based on LASSO-logistic regression shows significantly better predictive performance than single indicators, with good model calibration, demonstrating excellent clinical net benefit. This model can accurately assess the risk of microvascular complications, providing reliable decision support for early clinical screening and risk stratification management.