Inconsistencies were found between residential greenness and the risk of gestational diabetes mellitus (GDM), possibly due to variations in susceptibility among populations with different characteristics. However, little is known about whether this association could be modified by population characteristics like socioeconomic status (SES). This multicenter study conducted in a dense megacity aims to clarify these associations and explore the modification effects of demographic and socioeconomic factors.

The study included 19,618 pregnant women in 20 hospitals throughout Shanghai, China, between 2015 and 2017. Multivariable logistic regression models were utilized to assess the associations of satellite-based greenness indicators [normalized difference vegetation index (NDVI) within 500 m- and 1000 m buffers] with GDM and whether demographic and socioeconomic factors modified the associations. Potential mediation effects of fine particulate matter (PM2.5) on the associations between greenness and GDM were also explored.

During the first two trimesters of pregnancy, an increase in NDVI-500 m or NDVI-1000 m interquartile range was consistently associated with lower GDM risks, with adjusted odds ratios (aORs) and 95% confidence interval (CI) ranging from 0.82 (0.76, 0.88) to 0.90 (0.85, 0.96). Stratified analyses revealed that the health benefits of residential greenness are more pronounced during the first two trimesters among unemployed women (aOR = 0.70; 95%CI: 0.60, 0.82), those with lower education levels (aOR = 0.72; 95%CI: 0.63, 0.82), and those without medical insurance (aOR = 0.76; 95%CI: 0.69, 0.84). Mediation analysis shows that PM2.5 reduction by greenness may explain 16.4% of the inverse association between the NDVI-500 m during early pregnancy and the risk of GDM.

Our research indicates that elevated residential greenness was associated with reduced GDM risks, partly attributed to decreased PM2.5 levels. Women with lower SES experience amplified benefits from greenness. These findings highlight the significance of bolstering urban green infrastructure, particularly in communities confronting socioeconomic challenges and areas with high levels of air pollution.

Continuous glucose monitoring (CGM) technology has grown rapidly to track real-time blood glucose levels and trends with improved sensor accuracy. The ease of use and wide availability of CGM will facilitate safe and effective decision making for diabetes management. Here, we developed an attention-based deep learning model, CGMformer, pretrained on a well-controlled and diverse corpus of CGM data to represent individual's intrinsic metabolic state and enable clinical applications. During pretraining, CGMformer encodes glucose dynamics including glucose level, fluctuation, hyperglycemia, and hypoglycemia into latent space with self-supervised learning. It shows generalizability in imputing glucose value across five external datasets with different populations and metabolic states (MAE = 3.7 mg/dL). We then fine-tuned CGMformer towards a diverse panel of downstream tasks in the screening of diabetes and its complications using task-specific data, which demonstrated a consistently boosted predictive accuracy over direct fine-tuning on a single task (AUROC = 0.914 for type 2 diabetes (T2D) screening and 0.741 for complication screening). By learning an intrinsic representation of an individual's glucose dynamics, CGMformer classifies non-diabetic individuals into six clusters with elevated T2D risks, and identifies a specific cluster with lean body-shape but high risk of glucose metabolism disorders, which is overlooked by traditional glucose measurements. Furthermore, CGMformer achieves high accuracy in predicting an individual's postprandial glucose response with dietary modelling (Pearson correlation coefficient = 0.763) and helps personalized dietary recommendations. Overall, CGMformer pretrains a transformer neural network architecture to learn an intrinsic representation by borrowing information from a large amount of daily glucose profiles, and demonstrates predictive capabilities fine-tuned towards a broad range of downstream applications, holding promise for the early warning of T2D and recommendations for lifestyle modification in diabetes management.

Diabetes poses a significant public health challenge. The Chinese community has unique cultural characteristics that can influence their understanding of the diabetes healthcare system and engagement with services. This study aims to explore the knowledge and awareness of the diabetes healthcare system and the uptake of healthcare services in the UK Chinese population.

This study adopted a qualitative design. Three focus group discussions (FGDs) were conducted on Zoom with 22 Chinese participants with self-reported type 2 diabetes living in the UK. Participants ranged from 24 to 85 years (mean age = 66 years, SD = 17.1). A purposive sample was recruited through study adverts in Chinese community centres and snowball sampling. Data were analysed using Braun and Clarke's thematic analysis (TA).

This paper discusses 4 themes: Awareness and understanding of diabetes, healthcare access and utilisation, attitudes towards diabetes prevention programmes and Chinese medicine vs. Western medicine. Limited knowledge and awareness of diabetes was highlighted, with cultural factors impacting this. Factors which impacted healthcare access and utilisation were linguistic/ communication challenges, and trust and perception of the NHS. Participants were unaware of diabetes prevention programmes and highlighted that these were culturally inappropriate. Generational preferences were noted in the way participants wished to receive diabetes education. The western medical system was viewed as medication focused, therefore the older Chinese community trusted familiar natural methods of illness management.

These findings highlight the importance of ensuring diabetes education is culturally appropriate. Generational differences in education preference should be recognised by healthcare professionals to increase healthcare engagement. These findings demonstrate the important need to educate UK healthcare professionals with the unique sociocultural contexts for this ethnic group. This study uncovers gaps in awareness and service uptake, highlighting the need for co-development of interventions that promote health equity and improve diabetes management within this population.

Previous studies have reported that the type of protein consumed as preloads significantly affects postprandial glucose and insulin excursions in healthy and type 2 diabetes. But little is known how protein synergistic preloading affects human health.

Using two typical Asian protein type (soya tofu and chicken) with carbohydrate (white rice), the aim of this study was to compare the effects of two different protein types presented synergistically as preloads on postprandial glycemia, insulinemia and incretin secretions in healthy adults.

Sixteen healthy Chinese male adults participated in a randomized, controlled, crossover meal trial. Subjects consumed, in random order, 4 experimental meals that differed in protein type and proportion. Glucose, insulin, incretins and triglyceride concentrations were measured over 3 h.

There were significant protein type preload treatment x time interaction effects on plasma glucose, insulin, glucagon-like peptide-1 (GLP-1), glucose-dependent insulinotropic polypeptide (GIP) and triglycerides concentrations (P < 0.001). In comparison with rice alone treatment, preloading with Soya, Chicken and Soya/Chicken (50% soya tofu combined with 50% chicken breast) prior to rice consumption all significantly attenuated postprandial glucose response. Soya + Rice treatment induced a significantly lower incremental peak and incremental area under curve (iAUC) (0-60 min) glucose level compared with Chicken + Rice. The postprandial insulin response (incremental peak, iAUC 0-180 min) was significantly lower after Soya + Rice than Chicken + Rice group. Soya/Chicken + Rice treatment did not induce any significant difference in glucose and insulin levels between Soya + Rice or Chicken + Rice group. Notably, Soya/Chicken + Rice as well as Soya + Rice induced a significantly higher GLP1 and GIP responses compared with Rice or Chicken + Rice groups. Soya + Rice and Soya/Chicken + Rice groups stimulated higher triglyceride concentration than the other two groups.

Different protein preload with rice can considerably influence its glycemic, insulinemic and incretin responses. Soya or Soya/Chicken protein synergistic preloading induced higher incretins responses to modulate glycemic response in healthy adults.

There is limited national data on the association between body roundness index (BRI) and type 2 diabetes (T2D). A total of 10,785 participants from the China Health and Retirement Longitudinal Study (CHARLS) with repeated BRI measurements from 2011 to 2020 were included. We used Cox proportional hazards model and restricted cubic splines (RCS) to examine the association between BRI and T2D. During a mean follow-up of 7.72 years, 1,653 incident T2D cases were documented. Multivariable Cox proportional hazards regression model demonstrated a significant correlation between the BRI and the risk of T2D. Specifically, every 1-SD increase in BRI corresponded to a 27% heightened risk of T2D (HR: 1.27, 95% CI 1.20-1.35). The analysis also uncovered a non-linear pattern in this relationship, pinpointed by an inflection point at a BRI value of 3.96. Before the inflection point, the HR was 0.85 (95% CI 0.74-0.96), while after the inflection point, the HR increased to 1.29 (95% CI 1.18-1.41). In the middle-aged and elderly Chinese population, elevated BRI was significantly and positively associated with T2D risk. BRI could be a valuable addition to current clinical and public health strategies aimed at reducing the burden of T2D.

East Asian populations, which account for approximately 20% of the global population, have become central to the worldwide rise of metabolic diseases over the past few decades. The prevalence of metabolic disorders, including type 2 diabetes mellitus, hypertension and metabolic dysfunction-associated steatotic liver disease, has escalated sharply, contributing to a substantial burden of complications such as cardiovascular disease, chronic kidney disease, cancer and increased mortality. This concerning trend is primarily driven by a combination of genetic predisposition, unique fat distribution patterns and rapidly changing lifestyle factors, including urbanization and the adoption of Westernized dietary habits. Current advances in genomics, proteomics, metabolomics and microbiome research have provided new insights into the biological mechanisms that might contribute to the heightened susceptibility of East Asian populations to metabolic diseases. This Review synthesizes epidemiological data, risk factors and biomarkers to provide an overview of how metabolic diseases are reshaping public health in East Asia and offers insights into biological and societal drivers to guide effective, region-specific strategies.

Patient-level simulation models, mainly developed in Western populations, capture complex interactions between risk factors and complications to predict the long-term effectiveness and cost-effectiveness of novel treatments and identify high-risk subgroups for personalized care. However, incidence of outcomes varies significantly by ethnicity and region. We used high-quality, patient-level register data to develop the Chinese Diabetes Outcomes Model (CDOM) for predicting incident and recurrent events in type 2 diabetes (T2D).

The CDOM was developed using the prospective Hong Kong Diabetes Register (HKDR) cohort (n = 21,453; median follow-up duration, 7.9 years; 166,433 patient-years). It was externally validated with a retrospective territory-wide cohort of Chinese patients with T2D attending Hong Kong publicly funded diabetes centers and community clinics (n = 176,120; follow-up duration, 7.2 years; 953,523 patient-years).

The CDOM predicted first and recurrent events with satisfactory performance during internal (C-statistic = 0.740-0.941) and external (C-statistic = 0.758-0.932) validation after calibration. The respective C-statistic values for cancer were 0.664 and 0.661. Subgroup analysis showed consistent performance during internal (C-statistic = 0.632-0.953) and external (C-statistic = 0.598-0.953) validation after calibration.

The CDOM, developed using comprehensive register data with long-term follow-up, is a robust tool for predicting long-term outcomes in Chinese patients with T2D. The model enables the identification of patient subgroups to augment study design and develop tailored novel treatment strategies, inform policy, and guide practice to improve cost-effectiveness of diabetes care.

This study aimed to assess the relationship between hemoglobin glycation index (HGI) and risk of rapid kidney function decline (RKFD) in diabetic patients.

HGI was calculated as actual measured HbA1c minus predicted HbA1c. RKFD was defined as a 30 % decline in estimated glomerular filtration rate during follow-up. Participants were categorized into three groups based on HGI levels: lower (HGI ≤ -0.55), medium (-0.55 < HGI ≤ 0.22) and higher (HGI > 0.23). To understand the association between HGI and risk of RKFD in diabetic patients, directed acyclic graph were drawn and multivariate Cox proportional hazards models were used to adjust for covariates.

During a median follow-up of 4.0 years, RKFD occurred in 43 patients (6.3 %) with diabetes. After adjusting for potential confounders, Compared to the lower-HGI group, the hazard ratios for RKFD were 1.75 (95 % confidence interval [95 % CI]: 0.72, 4.25) and 2.64 (95 % CI: 1.12, 6.21) in the medium- and higher-HGI groups, respectively. HGI showed a linearly associated with RKFD (Pfor nonlinear = 0.383). The magnitude of associations was not materially altered in all sensitivity analyses, but with none significantly.

Higher HGI may be associated with an increased risk of RKFD in diabetic patients.

This post hoc analysis evaluated subgroup data from China (Chinese mainland, n = 100; Taiwan, n = 45) in ONWARDS 3, a 26-week, randomized, double-blind, double-dummy, treat-to-target, phase 3a trial comparing the efficacy and safety of once-weekly insulin icodec (icodec) versus once-daily insulin degludec (degludec) in insulin-naive participants with type 2 diabetes (T2D).

Adults were randomized 1:1 to icodec and once-daily placebo (icodec; n = 72) or degludec and once-weekly placebo (degludec; n = 73). The primary endpoint was change in glycated hemoglobin (HbA1c) (baseline to week 26). Secondary assessments included change in fasting plasma glucose (FPG; baseline to week 26); total weekly insulin dose (weeks 24-26); body weight change (baseline to week 26); and clinically significant or severe hypoglycemia rates (baseline to week 31 [5-week follow-up included]).

At week 26, from baseline values of 8.22% (icodec) and 8.39% (degludec), estimated mean changes in HbA1c were - 1.38% points and - 1.10% points, respectively (estimated treatment difference [95% confidence interval], - 0.28%-points [- 0.50%-points, - 0.05%-points]; p = 0.0152). For icodec and degludec, estimated mean FPG change (- 2.3 mmol/L vs. - 2.3 mmol/L), estimated mean insulin doses (158 U/week vs. 142 U/week), and estimated body weight change (2.5 kg vs. 2.4 kg) were similar. Combined clinically significant or severe hypoglycemia rates were low (0.10 [icodec] vs. 0.07 [degludec] events per patient-year of exposure), with no statistically significant difference between groups.

In insulin-naive Chinese individuals with T2D, once-weekly icodec treatment showed significantly greater HbA1c reductions after 26 weeks than once-daily degludec, with low combined clinically significant or severe hypoglycemia rates across groups.

NCT04795531.

To reveal the changing pattern of anthropometry of middle-aged adults aged 40-59 in China from 2000-2020, and to predict the development trend in the next decade, to provide a reference basis for curbing the prevalence of overweight and obesity in them.

A grey GM(1,1) prediction model was established for the cross-sectional data on anthropometric measures of 422,851 adults obtained from five series of national physical fitness surveillance in China.

1) From 2000 to 2020, all anthropometric indicators of middle-aged people aged 40-59 years in China maintained growth, with waist circumference increasing at the highest rate, weight at the second highest rate, and height at the slowest rate; 2) Overweight and obesity rates are increasing rapidly, with an average annual increase of 0.37 percentage points and 0.30 percentage points, with a greater increase for men than for women.

Without stronger interventions, overweight and obesity rates among middle-aged adults are likely to continue to increase in the future, and coordinated efforts are needed to slow down the obesity epidemic and improve the physical health of middle-aged adults.

To assess the glycaemic status of Asian patients in a tertiary care dental setting and develop a risk model for undiagnosed diabetes mellitus (DM).

A total of 1074 participants completed a diabetes risk test questionnaire, full-mouth periodontal examination and a point-of-care HbA1c finger-prick blood test. Univariable logistic regression was performed to assess the effect of potential factors to predict DM, with confirmed diabetes as the outcome. Subsequently, multivariable logistic regression analysis with stepwise variable selection was employed to develop the final models for predicting DM.

Sixty-five (6.1%) and 83 (7.7%) of the 1074 participants were medically confirmed with T2DM and prediabetes, respectively. The 'best' predictive risk model for DM included body mass index (BMI), family history of diabetes, smoking and a diagnosis of Stage III/IV or severe periodontitis with an area under the curve (AUC) of 0.717 (95% confidence interval, CI [0.689-0.744]) and 0.721 (95% CI [0.693-0.748]), respectively. Including the oral health measure marginally increased the AUC.

Dental patients clinically diagnosed with advanced periodontitis in combination with high BMI, positive family history of DM and smoking are potentially at high risk for DM and should be screened for DM and referred for medical confirmation and management.

The definition of hyperfiltration, the main pathogenesis in renal impairment in obesity and diabetes mellitus, is uncertain. Glomerular filtration rate (GFR) declines physiologically with aging, and there is inaccuracy in GFR in obesity due to body surface area (BSA) correction. Here, we defined hyperfiltration using GFR without BSA correction, but with inclusion of aging, and investigated hyperfiltration using this definition and absolute GFR > 125 mL/min. The subjects were 180 kidney donor candidates (56.4 ± 11.3 years old, 79 males). GFR was evaluated using inulin clearance. A two-hour 75-g oral glucose tolerance test was also performed. The subjects were divided into four groups with and without a combination of glucose tolerance disorder and BMI. Normal glucose tolerance (NGT) and BMI < 25 kg/m2 were defined as normal, and hyperfiltration was defined as the upper 95% confidence interval of the relationship of aging and GFR in normal cases, and compared with GFR > 125 mL/min. RESULTS: GFR without BSA correction and UAE in non-NGT subjects with obesity were higher than in other groups, but GFR with BSA correction did not show this relationship. In multiple regression analysis, BMI was independently associated with GFR without BSA correction, but not with BSA correction. Aging was consistently associated with GFR. The prevalence of hyperfiltration by our definition (GFR = -0.883 × Age + 167.398) was significantly higher than that using GFR > 125 mL/min (P < 0.0001). Hyperfiltration in obesity and/or glucose tolerance disorder should be evaluated using GFR without BSA correction and including the decline of GFR due to aging.

Glycated hemoglobin (HbA1c) reflects average blood glucose levels over the preceding three months, independent of fasting state. It is widely used for diagnosing type 2 diabetes and prediabetes and monitoring glucose control in patients with diabetes. This study highlights how anthropometry, body composition, and physical fitness affect glycated hemoglobin (HbA1c) levels in a cohort of female university students.

This cross-sectional study, conducted between October 2023 and January 2024 among university female students (n=86; ages 17-22 years) in the United Arab Emirates (UAE), aimed to determine the relationship between HbA1c, anthropometric indices, physical fitness, and body composition. Participants were recruited in person, provided written informed consent, and completed demographic and physical activity questionnaires. Weight, body mass index (BMI), visceral fat, and muscle and fat percentage were measured using a body composition monitor scale (Omron HBF-514C, OMRON Healthcare, Inc., Kyoto, Japan). A stadiometer was used to measure height and an electronic sphygmomanometer to measure blood pressure. The waist and hip circumferences were measured using a measuring tape, and the waist-to-hip ratio was further calculated. Glycated hemoglobin (HbA1c) was measured using an immunofluorescence assay analyzer (Getein 1160 Immunofluorescence Quantitative Analyzer, Getein Biotech, Inc., Nanjing, China).

The main objective of our study was to establish a relationship between anthropometric measurements and body composition with physical fitness levels, including sedentary time, and how it influences HbA1c levels in young female students. Of the 90 participants, data from 86 were analyzed. Significant correlations were found between HbA1c and diastolic blood pressure (BP) (r=0.227) and sedentary hours (r=0.206). Linear regression analysis revealed sedentary behavior (p=0.021) and diastolic BP (p=0.034) as significant predictors of HbA1c levels. In conclusion, our research study provides valuable insights into how lifestyle factors such as sedentary lifestyle and diastolic BP influence glycemic (HbA1c) control in a specific cohort of young female university students of ages 17-22 years. Although BMI was not a significant predictor in our study, sedentary hours and diastolic blood pressure were independently linked to HbA1c levels.

Early prediabetes screening holds immense significance in decreasing the incidence of diabetes. Therefore, we aimed to evaluate the association of hepatic enzymes with prediabetes and diabetes in the Azar cohort population in Iran.

This cross-sectional study utilized data from the Azar cohort study, initiated in 2014, with 14,865 participants aged 35-70 years. This study defines prediabetes, according to the American Diabetes Association (ADA), as fasting blood sugar (FBS) of 100-125 mg/dl. An FBS ≥ 126 mg/dL or a history of diabetes indicates diabetes. Serum liver enzymes including alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transferase (GGT), and alkaline phosphatase (ALP) were measured, and associations with prediabetes and diabetes were analyzed using binary logistic regression.

In a study of 14,865 participants, 16% had prediabetes and 14.1% had diabetes. The serum levels of ALT, AST, GGT, and ALP were significantly higher (P < 0.05) in the prediabetic and diabetic patients. The adjusted logistic regression model showed a dose-response increase for all hepatic enzymes, with the highest ORs in the fourth quartile for both prediabetes and diabetes. The highest OR for prediabetes and diabetes was in the fourth GGT quartile.

Our findings suggest that serum ALT, GGT, and ALP levels are strongly associated with prediabetes and diabetes. These hepatic enzymes may be considered easy and valuable early indicators of diabetes risk, prompting timely interventions to slow disease progression.

There is a lack of evidence regarding the trajectories of type 2 diabetes until the first clinic visit, including the untreated period after diagnosis.

We aimed to determine the real-world history of type 2 diabetes until the first clinic visit, including the untreated duration, and to assess the effective timing of the therapeutic intervention.

A total of 23,622 nondiabetic Japanese workers with a mean (SD) age of 38.8 (11.5) years were retrospectively followed from 2008 to 2022 for annual health checkups. The trajectories of glycated hemoglobin (HbA1c), fasting plasma glucose (FPG), and body mass index (BMI) until the first clinic visit in diabetes individuals were determined. ROC analysis was performed to assess the contribution of each measure to the first visit.

During a median follow-up of 12.0 years, 1,725 individuals developed type 2 diabetes, of whom 532 individuals visited clinics. HbA1c and FPG trajectories steeply rose in the year before the first clinic visit after their progressive upward trends. ROC analysis showed cutoff values for each measure. As the untreated duration increased, glycemia increased and BMI decreased among individuals who visited clinics.

To prevent the initial worsening of diabetes, early therapeutic intervention is necessary during the increasing trends before the steep rise in glycemia, regardless of the degree of obesity. HbA1c ≥6.5% (47.5 mmol/mol) and an HbA1c ≥0.2% (2.2 mmol/mol)/year increase may be an effective timing for therapeutic intervention.

Diabetes mellitus (DM) ranks among the most prevalent chronic metabolic diseases, characterized primarily by a persistent elevation in blood glucose levels. This condition typically stems from either insufficient insulin secretion or a functional defect in the insulin itself. Clinically, diabetes is primarily classified into type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM), with T2DM comprising nearly 90% of all diagnosed cases. Notably, the global incidence of T2DM has surged dramatically over recent decades. The adenylate-activated protein kinase (AMPK) signaling pathway is crucial in regulating cellular energy metabolism, marking it as a significant therapeutic target for diabetes and related complications. Natural products, characterized by their diverse origins, multifaceted bioactivities, and relative safety, hold considerable promise in modulating the AMPK pathway. This review article explores the advances in research on natural products that target the AMPK signaling pathway, aiming to inform the development of innovative antidiabetic therapies.

Obesity causes many complex diseases including type 2 diabetes (T2D). Obesity increases the risk of T2D in Europeans, but there are many non-obese (lean) T2D patients in East Asia.

To discover genetic factors enriched in obese or lean T2D patients, we conducted a genome-wide association (GWA) analysis for T2D stratified by BMI in the Korean population.

In the discovery stage, 654 and 247 individuals classified as obese (BMI > 25) and lean (BMI < 23) T2D patients, respectively, were compared with 3,842 control subjects for GWA analysis. Several BMI-stratified T2D variants detected in the discovery stage were further tested in the replication stage, which included 402 obese and 220 lean T2D cases, and 3,615 controls.

Meta-analysis combining the discovery and replication stages detected two variants with genome-wide significance: rs2356138 [P = 2.8 × 10-8, OR = 2.06 (1.59-2.65)] in obese T2D subjects and rs9295478 [P = 2.5 × 10-9, OR = 1.61 (1.38-1.88)] in lean ones. The SNP rs9295478 is located in CDKAL1, a well-known T2D gene previously identified in several GWA studies. Meanwhile, the SNP rs2356138 is a previously unknown variant located in PKP4.

We discovered genetic loci enriched in obese or lean T2D patients in the Korean population. Our findings should facilitate more effective control of T2D in Koreans.

Leukocyte cell-derived chemotaxin 2 (LECT2) is an obesity-associated hepatokine that causes skeletal muscle insulin resistance. Since LECT2 is up-regulated by the inactivation of the energy sensor AMPK in the liver, we hypothesized that LECT2 has potential as a biomarker for metabolic dysfunction-associated steatotic liver disease (MASLD). Therefore, we investigated whether circulating LECT2 levels are associated with insulin sensitivity, liver enzymes, and MASLD.

This cross-sectional study included 138 Japanese individuals. Plasma LECT2 levels were measured using fasting blood samples. B-mode ultrasonography was used to assess hepatic steatosis.

The mean age and body mass index (BMI) of participants were 63.5 ± 10.2 years and 23.0 ± 3.1 kg/m2, respectively. Higher LECT2 levels positively correlated with homeostatic model assessment for insulin resistance (HOMA-IR) values and negatively correlated with the quantitative insulin sensitivity check index (QUICKI) among all participants (HOMA-IR; non-standardized β (B) = 6.38, P < 0.01: QUICKI; B = -161, P < 0.01). These correlations were stronger in the low BMI group (HOMA-IR; B = 13.85, P < 0.01: QUICKI; B = -180, P < 0.01). LECT2 levels also positively correlated with gamma-glutamyl transferase levels (B = 0.01, P = 0.01) and alanine aminotransferase levels (B = 0.33, P = 0.02). Higher LECT2 levels correlated with the prevalence of MASLD (odds ratio = 1.14, P = 0.02).

The present results suggest the potential of plasma LECT2 levels as a biomarker for insulin resistance in individuals who are not overweight and the prevalence of MASLD in the general population.

In East Asians, type 2 diabetes mellitus (T2DM) is primarily characterized by significant defects in insulin secretion and comparatively low insulin resistance. Recently, the prevalence of T2DM has rapidly increased in East Asian countries, including Korea, occurring concurrently with rising obesity rates. This trend has led to an increase in the average body mass index among East Asian T2DM patients, highlighting the influence of insulin resistance in the development of T2DM within this group. Currently, the incidence of T2DM in Korea is declining, which may indicate potential adaptive changes in insulin secretory capacity. This review focuses on the changing epidemiology of T2DM in East Asia, with a particular emphasis on the characteristics of peak functional β-cell mass.

The prevalence of type-2 diabetes mellitus (T2DM) has increased over 10-fold in the past 40 years in China, which now has the largest T2DM population in the world. Insulin resistance and β-cell dysfunction are the typical features of T2DM. Although both factors play a role, decreased β-cell function and β-cell mass are the predominant factors for progression to T2DM. Considering the differences between Chinese T2DM patients and those of other ethnicities, it is important to characterize β-cell dysfunction in Chinese patients during T2DM progression. Herein, we reviewed the studies on the relationships between β-cell function and T2DM progression in the Chinese population and discussed the differences among individuals of varying ethnicities. Meanwhile, we summarized the risk factors and current treatments of T2DM in Chinese individuals and discussed their impacts on β-cell function with the hope of identifying a better T2DM therapy.

Background/Objectives: Metabolic syndrome is a significant public health issue, particularly in urbanizing regions like the Peruvian Amazon, where lifestyle changes have increased the prevalence of metabolic disorders. This study aimed to develop and validate a simple, cost-effective diagnostic model for early detection of metabolic syndrome in the urban population of San Juan Bautista, Iquitos. Methods: A cross-sectional study was conducted with 251 adults aged over 18 years. Data collection included anthropometric measurements, body composition analysis, and biochemical assessments. Logistic regression analyses identified key predictors of metabolic syndrome, and clinical decision trees were developed to enhance diagnostic accuracy. Results: The prevalence of metabolic syndrome was 47.9%. Systolic blood pressure, triglycerides, and very-low-density lipoprotein cholesterol were the strongest predictors. The most effective diagnostic model, combining very-low-density lipoprotein cholesterol and systolic blood pressure, achieved a sensitivity of 91.6% and a specificity of 78.5%, demonstrating high diagnostic accuracy. Conclusions: The proposed model offers a practical, low-cost tool for early detection of metabolic syndrome in resource-limited urban settings. However, its findings are limited by the small sample size and the lack of external validation, requiring further studies to confirm its generalizability and applicability to other populations. Its implementation in primary healthcare could facilitate timely interventions, reducing the risk of chronic diseases in vulnerable populations.

Many tools have been developed to predict the risk of diabetes in a population without diabetes; however, these tools have shortcomings that include the omission of race, inclusion of variables that are not readily available to patients, and low sensitivity or specificity.

We aimed to develop and validate an easy, systematic index for predicting diabetes risk in the Asian population.

We collected the data from the NAGALA (NAfld [nonalcoholic fatty liver disease] in the Gifu Area, Longitudinal Analysis) database. The least absolute shrinkage and selection operator model was used to select potentially relevant features. Multiple Cox proportional hazard analysis was used to develop a model based on the training set.

The final study population of 15464 participants had a mean age of 42 (range 18-79) years; 54.5% (8430) were men. The mean follow-up duration was 6.05 (SD 3.78) years. A total of 373 (2.41%) participants showed progression to diabetes during the follow-up period. Then, we established a novel parameter (the FHTHWA index), to evaluate the incidence of diabetes in a population without diabetes, comprising 6 parameters based on the training set. After multivariable adjustment, individuals in tertile 3 had a significantly higher rate of diabetes compared with those in tertile 1 (hazard ratio 32.141, 95% CI 11.545-89.476). Time receiver operating characteristic curve analyses showed that the FHTHWA index had high accuracy, with the area under the curve value being around 0.9 during the more than 12 years of follow-up.

This research successfully developed a diabetes risk assessment index tailored for the Japanese population by utilizing an extensive dataset and a wide range of indices. By categorizing the diabetes risk levels among Japanese individuals, this study offers a novel predictive tool for identifying potential patients, while also delivering valuable insights into diabetes prevention strategies for the healthy Japanese populace.

Diabetes mellitus (DM) is a widespread disease that poses a major threat to millions of people. To address this issue, we have synthesized seventeen new 4-(adamantan-1-yl)-(2-(arylidene)hydrazinyl)thiazoles (3a-q) via Hantzsch synthetic approach. The molecular structures of all the compounds were confirmed using FT-IR, 1H- and 13C-NMR spectroscopy, and HR-mass spectrometry. Protein kinase, α-amylase, glycation, and oxidation inhibition potential of all compounds were also investigated, and it was found that compounds 3b, 3c, 3e-3g, and 3i-3q have shown excellent α-amylase inhibition (IC50 = 7.91 ± 0.07 to 28.57 ± 0.1 µM), compounds 3c, 3e, 3i, 3k, and 3p (IC50 = 30.6 ± 0.06 to 37.8 ± 0.005 ppm) were found to be highly potent anti-glycating agents, and compounds 3c, 3g, 3h, 3k, and 3m were found to be more potent protein kinase inhibitors as compared to standards. The compounds 3b, 3c, 3d, 3e, 3f, 3g, 3i, 3k, 3l, 3m, 3n, 3p, and 3q have shown good antioxidant potential (IC50 = 27.5 ± 0.09 to 48.8 ± 0.09 µM) as compared to standard ascorbic acid (IC50 = 51.3 ± 0.1 µM). The biocompatibility of all samples was also tested by employing brine shrimp lethality and in vitro hemolytic assays and was found to be safe to human erythrocytes at tested concentrations. Furthermore, the molecular docking simulation study also revealed that almost all synthesized compounds have potential interactions with target proteins at the molecular level.

Prediabetes, impacting a third of the adult Chinese population, is linked to a variety of detrimental health outcomes. However, scant research has delved into the factors that affect a regression from prediabetes to normal glucose regulation (NGR) in middle-aged and elderly Chinese adults.

We conducted a longitudinal analysis of 2,655 adults, aged 45 years and above, drawing data from wave 1 and wave 3 of the China Health and Retirement Longitudinal Study (CHARLS). We employed a stepwise logistic regression model to identify factors associated with the regression to NGR. Restricted Cubic Spline (RCS) analysis was used to evaluate the dose-response relationships between baseline fasting plasma glucose (FPG) and glycated hemoglobin (HbA1c) levels and the likelihood of regression to NGR. Attribution fraction (AF) analysis was conducted to measure the impact of modifiable factors on the regression of prediabetes. We further examined how changes in these factors were associated with regression to NGR.

During the 4-year follow-up, 570 of 2,655 prediabetes participants regressed to NGR. The stepwise logistic regression model identified older age, female sex, abdominal obesity (OR 0.70, 95% CI 0.57-0.86), elevated LDL-C (OR 0.69, 95% CI 0.48-0.97), higher FPG (OR 0.68, 95% CI 0.52-0.90), and higher HbA1c (OR 0.23, 95% CI 0.18-0.30) as factors associated with regression to NGR. AF analysis showed that a lower initial HbA1c was the most influential factor for regression to NGR. Additionally, evaluated blood lipid profiles reduced the odds of regression to NGR.

This study underscores the influence of age, gender, abdominal obesity, LDL-C levels, FPG, HbA1c, and blood lipid profiles on the likelihood of regressing from prediabetes to NGR. It suggests that adopting a healthy lifestyle and preemptively mitigating these risks may be more beneficial than addressing them after they have been identified in clinical settings.

Although diabetes is now a global epidemic, China has the highest number of affected people, presenting profound public health and socioeconomic challenges. In China, rapid ecological and lifestyle shifts have dramatically altered diabetes epidemiology and risk factors. In this Review, we summarize the epidemiological trends and the impact of traditional and emerging risk factors on Chinese diabetes prevalence. We also explore recent genetic, metagenomic and metabolomic studies of diabetes in Chinese, highlighting their role in pathogenesis and clinical management. Although heterogeneity across these multidimensional areas poses major analytic challenges in classifying patterns or features, they have also provided an opportunity to increase the accuracy and specificity of diagnosis for personalized treatment and prevention. National strategies and ongoing research are essential for improving diabetes detection, prevention and control, and for personalizing care to alleviate societal impacts and maintain quality of life.

Our study aimed to identify the trajectory patterns of lipid accumulation product (LAP) and investigate their association with the incident risk of type 2 diabetes mellitus (T2DM) in China.

This study included 37,316 eligible participants, with data collected between1998 and 2021. The LAP trajectory patterns were identified through latent mixture modeling. Logistic regression models were used to examine the association between different LAP trajectory patterns and the incident risk of T2DM.

Over an average period of 12.7 years, 3195 participants developed T2DM. Four LAP trajectory patterns were identified: low stable, moderate slow-increasing, high decreasing, and moderate fast-increasing. After adjusting for demographic and clinical confounders, the odds ratios (ORs) and 95 % confidence intervals (CIs) for T2DM were 1.67 (1.50, 1.86) for the moderate slow-increasing group, 1.63 (1.38, 1.94) for the high decreasing group, and 2.43 (2.07, 2.85) for the moderate fast-increasing group compared with the low stable group. Similar trajectory patterns were found in sex-specific populations as in the general population, while the elevated LAP trajectory pattern was more strongly associated with an increase in the incident risk of T2DM in females.

Individuals with moderate fast-increasing LAP trajectory patterns had a 2.4 times higher risk of developing T2DM compared to those with low stable LAP patterns. More attention should be paid to preventing T2DM in people with high levels of LAP, especially females, the elderly, drinkers, and people with a history of diabetes.

Postprandial glucose concentration 1-h (1 h-PG) after an oral glucose tolerance test (OGTT) has similar or superior performance to 2 h-PG in predicting type-2 diabetes mellitus (T2DM) in several populations, and is simpler to obtain in clinical practice. However, studies in Asians are scarce. We investigated the utility of elevated baseline 1 h-PG in predicting T2DM incidence within three years, and its relationship with β-cell function in 1250 non-diabetic Asian participants.

Participants underwent an OGTT, an intravenous glucose challenge and a hyperinsulinemic-euglycemic clamp to determine glucose tolerance, acute insulin response (AIR) and insulin sensitivity at baseline. OGTTs were repeated every six months until study completion to monitor T2DM conversion.

The area under the receiver operating characteristic curve of 1 h-PG was not significantly different from 2 h-PG (AUC1h-PG = 0.883 vs. AUC2h-PG = 0.907; ΔAUC = -0.024, P = 0.124) and the optimal 1 h-PG cut-off was ≥10.7 mmol/L. When groups of high/low 1 h-PG and 2 h-PG at baseline were compared, AIR and disposition index were significantly lower in groups with high 1 h-PG, and both had a stronger correlation with 1 h-PG, indicating that impaired β-cell function was more strongly associated with elevated 1 h-PG than 2 h-PG.

The ability of 1 h-PG to detect Asians at risk of developing T2DM within three years is on par with 2 h-PG and the optimal cut-off is 10.7 mmol/L. Elevated 1 h-PG is associated with β-cell dysfunction. We conclude that 1 h-PG can be considered as a primary OGTT time point to identify Asians at risk for T2DM, allowing for screening at a reduced time and cost, and with lower patient burden.

National Medical Research Council (NMRC), Ministry of Health (MOH; Singapore) Industry Alignment Fund [NMRC/MOHIAFCat1/0048/2016] and Janssen Pharmaceuticals Inc. (USA).

We examined incremental healthcare costs (inpatient and outpatient) related to complications in Chinese patients with type 2 diabetes (T2D) during the year of occurrence and post-event years, utilizing the Joint Asia Diabetes Evaluation (JADE) Register cohort of Hong Kong Chinese patients with T2D between 2007 and 2019.

19,440 patients with T2D underwent structured evaluation utilizing the JADE platform with clinical outcomes data retrieved from territory-wide electronic medical records including inpatient, outpatient and emergency care. Two-part model was adopted to account for skewed healthcare costs distribution. Incremental healthcare costs associated with nine non-fatal diabetes complications and all-cause death were estimated, adjusted for demographic, clinical, lifestyle factors and comorbidities.

In this prospective cohort [mean ± SD age:59.9 ± 11.9 years, 56.6 % men, duration of diabetes:7.3 ± 7.5 years, HbA1C:7.5 ± 1.6 %] observed for 7 (interquartile range:4-9) years (142,132 patient-years), the mean annual healthcare costs, mainly due to inpatient cost, were USD$2,990 ± 9,960. Lower extremity amputation (LEA) (USD$31,302; 95 %CI: 25,706-37,004), hemorrhagic stroke (USD$21,164; 17,680-24,626), ischemic stroke (USD$17,976; $15,937-20,352) and end-stage disease (ESRD) (USD$14,774; 13,405-16,250) in the year of event incurred the highest cost. Residual healthcare costs in the post-event years were highest for ESRD, LEA, haemorrhagic stroke and incident cancer.

These comprehensive temporal healthcare cost estimates for diabetes-related complications allows the performance of long-term, patient-level, cost-effectiveness analyses on T2D prevention and treatment strategies relevant to an Asian and possibly global contexts. These may inform decision-makers on resource allocation aimed at reducing the burden of T2D and chronic diseases.

The aim of this study was to analyse the allelic distribution of selected genes in the Czech and Vietnamese populations. We analysed samples from 94 Vietnamese volunteers and 2,859 Czech population-based subjects (2,559 from the Czechs post-MONICA and 300 volunteers from the South region of the Czech Republic). There were significant differences between the two populations for most, but not all, of the SNPs analysed. In particular, the prevalence of risk alleles in the analysed polymorphisms tended to be lower in the Vietnamese community compared to the Czech population, especially within the FTO (rs17817449; associated with obesity risk, P < 0.0001), TCF7L2 (rs7903146; linked to type 2 dia-betes, P < 0.0001) and ADH1B (rs1229984; related to alcohol consumption, P < 0.0001) genes. The genotype within the MCM6/LCT cluster (rs4988235) associated with lactase persistence was not present in the Vietnamese population. Slight genotype differences were detected for one HFE polymorphism (rs1799945 with P = 0.005; but not for rs1800562). Only the genotype frequencies within the MC4R and APOE genes were almost identical in both populations. We conclude that the Vietnamese population may have a lower genetic predisposition to the non-communicable diseases such as obesity or diabetes mellitus.

Background: There are higher numbers of Asian individuals with metabolically obese, normal weight (MONW) who are susceptible to diabetes than other ethnic groups. The homeostatic model assessment for insulin resistance (HOMA-IR) has been used for years to evaluate IR; however, the triglyceride-glucose (TyG) index has been highlighted as a reliable and cost-effective insulin resistance indicator. Thus, this study explored the association of the HOMA-IR versus the TyG index with diabetes in individuals without underweight or obesity. Methods: This cross-sectional study included 10,471 Korean individuals whose body mass index was ≥18.5 and <25.0 kg/m2. Depending on metabolic syndrome criteria, subjects with no conditions, one or two conditions, and three or more conditions were assigned to the metabolically healthy and normal weight (MHNW), pre-MONW, and MONW groups, respectively. Diabetes was diagnosed based on HbA1C and medication information. Results: The HOMA-IR and TyG index discriminated between each group, showing an increasing trend from the MHNW group to the MONW group. However, this trend was more robust for the TyG index. The cut-off values in the TyG index and HOMA-IR were >8.9 and >1.6 in males and >8.7 and >1.6 in females, respectively. The TyG index's area under the curve was higher than that of the HOMA-IR in both sexes. MONWs distinguished by the cut-off values of the TyG index and HOMA-IR were 2.370 and 1.726 for males and 2.249 and 1.710 for females times more likely to develop diabetes. Conclusions: The TyG index showed a stronger association with diabetes in Korean individuals without underweight or obesity than the HOMA-IR.

To explore the efficacy and safety of once-weekly insulin icodec (icodec) in Japanese adults (≥20 years old) with type 2 diabetes from the global ONWARDS 1, 2 and 4 trials.

Insulin-naive (ONWARDS 1) and insulin-experienced (ONWARDS 2 and 4) individuals were randomized to icodec or a once-daily insulin comparator: insulin glargine U100 [ONWARDS 1 (basal insulin only) and 4 (basal-bolus regimen)] or insulin degludec [ONWARDS 2 (basal insulin only)]. The primary outcome was change in glycated haemoglobin from baseline to end of treatment (EOT) (ONWARDS 1: Week 52; ONWARDS 2 and 4: Week 26). Here, we present the Japanese subgroup results.

Similar reductions in glycated haemoglobin from baseline to EOT were observed in each trial for icodec and comparators. The proportion of time in range (blood glucose 3.9-10.0 mmol/L) at EOT was also comparable across treatment groups (time in range: 58%-68%), as was time spent with blood glucose below 3.0 mmol/L (<1.0%). Combined clinically significant (blood glucose <3.0 mmol/L) or severe (requiring external assistance for recovery) hypoglycaemia rates were low, with no severe events (ONWARDS 1 and 2) or a single severe event (ONWARDS 4; icodec group) reported. These results generally aligned with findings from the respective global populations. No new safety issues were identified.

Icodec improved glycaemic control to a similar degree as once-daily basal insulin comparators while maintaining low levels of clinically significant or severe hypoglycaemia. The findings support icodec use in Japanese individuals with different levels of type 2 diabetes progression.

The 2023 Delphi consensus recommended the use of new term, metabolic dysfunction-associated steatotic liver disease (MASLD), aiming conceptual shift from the conventional non-alcoholic fatty liver disease (NAFLD). The association between NAFLD and type 2 diabetes mellitus (T2DM) development is well known. This study aimed to examine the correlation between MASLD and T2DM development, comparing their utility as predictors.

This retrospective cohort study obtained data from a medical health checkup program conducted at Asahi University Hospital, Japan, between 2004 and 2021. Logistic regression analysis was used to assess the association between MASLD and incident T2DM over 5 years. To compare the predictive utility of NAFLD and MASLD, receiver operating characteristic curves were drawn, followed by area under the curve (AUC) comparisons.

In total, 15,039 participants (59.6% males; median [interquartile range {IQR}] age, 44 [38, 50] years) were included. Out of 2,682 participants meeting the criteria for MASLD, 234 individuals (8.7%) developed T2DM. Multivariate analysis revealed a significantly elevated risk of T2DM in MASLD compared with the reference healthy group (without steatotic liver disease or cardiometabolic risk), presenting an OR of 127.00 (95% CI 40.40-399.00, P < 0.001). The concordance rate of diagnosis between NAFLD and MASLD was 98.7%. The AUC values were 0.799 for NAFLD and 0.807 for MASLD, respectively. Comparative analysis of the AUC showed a statistical difference between NAFLD and MASLD (P < 0.001).

MASLD was shown to be a significant risk factor for incident T2DM, exhibiting a potentially higher predictive capacity than conventional NAFLD.

The association between body shape and depressive symptoms has been reported in adults. The present study aimed to investigate the association between body shape-specific abdominal obesity and depressive symptoms among multi-regional Asian adults.

The 2011-2012 China Health and Retirement Longitudinal Study and 2022-2023 Hangzhou study were used as the discovery and validation datasets, respectively. Body shape was assessed by body mass index categories. Abdominal obesity was defined as a body shape index (ABSI) ≥ 75th centile. Depression was measured using 10-item Centre for Epidemiological Studies Depression Scale and Geriatric Depression Scale short 15-item version, respectively. General linear and multinomial logistic models were used to explore the association of ABSI, abdominal obesity with depressive scores and presence, respectively.

A total of 12,229 and 1210 participants were included in the discovery and validation datasets, respectively. A non-linear reverse L-shaped association was found between ABSI and depressive scores. Participants with abdominal obesity had higher depressive scores (β = 0.05, 95%CI = 0.01-0.09; and β = 0.13, 95%CI = 0.01-0.24; respectively). Stratified analyses showed that abdominal obesity was associated with higher depressive scores (β = 0.09, 95%CI = 0.00-0.17; and β = 0.25, 95%CI = 0.05-0.46; respectively) and presence (OR = 1.46, 95%CI = 1.02-2.10; and OR = 3.95, 95%CI = 1.58-9.84; respectively) in overweight adults. Furthermore, abdominal obesity was associated with depressive symptoms among overweight females, but not among males.

Causal links weren't addressed because of the observational study design.

Abdominal obesity exhibited a positive association with depressive symptoms among Asian overweight adults, particularly in females. Prevention and early diagnosis of depressive symptoms should focus on overweight females.

To evaluate the association between changes in haemoglobin A1c (HbA1c) and the concurrent incidence of cardiovascular disease (CVD) in type 2 diabetes mellitus (T2DM) patients.

We conducted a retrospective cohort study among T2DM patients with HbA1c measurement after T2DM diagnosis between August 2009 and September 2010. The patients were classified into six subgroups based on baseline HbA1c (<7%; 7%-7.9%; ≥8%) and age (<65; ≥65 years), and then clustered into classes by HbA1c trajectory and CVD incidence over the 12-year follow-up period using joint latent class mixture models. We explored the HbA1c trajectories and CVD incidences in each latent class. Multinomial logistic regression was used to compare the baseline characteristics among different latent classes.

A total of 128 843 T2DM patients were included with a median follow-up period of 11.7 years. Ten latent classes were identified in patients with baseline HbA1c ≥ 8% and age <65 years, while seven classes were identified in the other five groups. Among all the identified latent classes, patients with fluctuating HbA1c trajectories, characterized by alternating periods of increase and decrease, had higher CVD incidences. Male patients, and patients with higher baseline HbA1c and use of antidiabetic drugs were more likely to have a fluctuating HbA1c trajectory. More specifically, patients aged < 65 years with younger age or a smoking habit, and patients aged ≥ 65 years with a longer duration of T2DM were more likely to have a fluctuating HbA1c trajectory.

We found that T2DM patients with fluctuating HbA1c trajectories could have a higher CVD risk. Different trajectory-associated characteristics in age subgroups highlight the need for individualized management of T2DM patients.