Relation between BMI and diabetes mellitus and its complications among US older adults

Prevalence, Awareness, Treatment, and Control of Type 2 Diabetes in South Korea (1998 to 2022): Nationwide Cross-Sectional Study

BACKGROUND

Type 2 diabetes poses an increasing disease burden in South Korea. The development and management of type 2 diabetes are closely related to lifestyle and socioeconomic factors, which have undergone substantial changes over the past few decades, including during the COVID-19 pandemic.

OBJECTIVE

This study aimed to investigate long-term trends in type 2 diabetes prevalence, awareness, treatment, and control. It also aimed to determine whether there were substantial alterations in the trends during the pandemic and whether these changes were more pronounced within specific demographic groups.

METHODS

This study examined the prevalence, awareness, treatment, and control of type 2 diabetes in a representative sample of 139,786 South Koreans aged >30 years, using data from the National Health and Nutrition Examination Survey and covering the period from 1998 to 2022. Weighted linear regression and binary logistic regression were performed to calculate weighted β coefficients or odds ratios. Stratified analyses were performed based on sex, age, region of residence, obesity status, educational background, household income, and smoking status. β (difference) was calculated to analyze the trend difference between the prepandemic period and the COVID-19 pandemic. To identify groups more susceptible to type 2 diabetes, we estimated interaction terms for each factor and calculated weighted odds ratios.

RESULTS

From 1998 to 2022, a consistent increase in the prevalence of type 2 diabetes was observed among South Koreans, with a notable rise to 15.61% (95% CI 14.83-16.38) during the pandemic. Awareness followed a U-shaped curve, bottoming out at 64.37% (95% CI 61.79-66.96) from 2013 to 2015 before increasing to 72.56% (95% CI 70.39-74.72) during the pandemic. Treatment also increased over time, peaking at 68.33% (95% CI 65.95-70.71) during the pandemic. Control among participants with diabetes showed no substantial change, maintaining a rate of 29.14% (95% CI 26.82-31.47) from 2020 to 2022, while control among treated participants improved to 30.68% (95% CI 27.88-33.48). During the pandemic, there was a steepening of the curves for awareness and treatment. However, while the slope of control among participants being treated increased, the slope of control among participants with diabetes showed no substantial change during the pandemic. Older populations and individuals with lower educational level exhibited less improvement in awareness and control trends than younger populations and more educated individuals. People with lower income experienced a deceleration in prevalence during the pandemic.

CONCLUSIONS

Over the recent decade, there has been an increase in type 2 diabetes prevalence, awareness, treatment, and control. During the pandemic, a steeper increase in awareness, treatment, and control among participants being treated was observed. However, there were heterogeneous changes across different population groups, underscoring the need for targeted interventions to address disparities and improve diabetes management for susceptible populations.

The effect of lifestyle factors on chronic complications of diabetes at public health hospitals in Southwest Ethiopia

Ethiopia faces a significant challenge with increasing non-communicable diseases like diabetes, ranking among the top four in sub-Saharan Africa. However, there is a lack of research on how lifestyle affects chronic complications of diabetes in Ethiopia, highlighting the need for urgent exploration to develop better intervention strategies. This study aimed to evaluate the link between lifestyle factors and chronic complications of diabetes in public health hospitals in Southwest Ethiopia. A cross-sectional study involving 389 diabetes patients from Mizan-Tepi University Teaching Hospital (MTUTH) and Gebretsadik Shawo General Hospital (GSGH) in Southwest Ethiopia was conducted. Data collection methods included interviewer-administered questionnaires, patient medical record reviews, physical examination, and serum analysis. SPSS version 25 was used for data analysis, including descriptive statistics and bivariate and multivariate logistic regression analyses. Statistical significance was determined at a p-value < 0.05. The study revealed a 32.1% prevalence of chronic complications of diabetes, with 13.4% having chronic kidney disease, 8.0% experiencing visual disturbances, and 16.7% suffering from peripheral sensory pain. After adjusting for confounding variables, age (41-60 years [AOR = 1.77; 95% CI 1.01, 3.15] and > 60 years [AOR = 2.18; 95% CI 1.20, 4.33]), duration of diabetes mellitus (> 6 years [AOR = 2.90; 95% CI 1.74, 4.85]), alcohol consumption [AOR = 2.30; 95% CI 1.33, 3.98], physical inactivity [AOR = 2.43; 95% CI 1.38, 4.27], and body mass index (underweight [AOR = 7.66; 95% CI 1.68, 34.8] and obese [AOR = 3.53; 95% CI 1.84, 10.5]) were significantly associated with chronic complications of diabetes. Chronic complications of diabetes are a major problem in the study area. Lifestyle factors strongly influence chronic diabetes complications, highlighting the importance of preventive measures. Implementing health education and prevention programs focusing on modifiable lifestyle factors is crucial.

Impact of Education as a Social Determinant on the Risk of Type 2 Diabetes Mellitus in Korean Adults

Education is correlated with health literacy, which is a combination of reading and listening skills, data analysis, and decision-making during the necessary health situations. This study aims to evaluate the effect of education on the risk of type 2 diabetes mellitus (T2DM). This is a population-based cross-sectional study using the 2019 nationwide survey data in Korea. There were 3951 study subjects, after excluding participants with missing data for key exposures and outcome variables. Descriptive statistics, χ2 (chi-square) test, and logistic regression were performed to analyze the data. The prevalence of T2DM was associated with educational attainment, sex, age, smoking status, physical activity, carbohydrate intake, and obesity. In the logistic regression model, the odds ratio (OR) of having T2DM was much lower among people educated in college or higher (OR = 0.49, 95% confidence interval [95% CI] = 0.34-0.64) than those with only or without primary education after adjusting for biological factors (sex, age) and health behaviors (smoking status, physical activity, carbohydrate intake, and obesity). This study shows that educational attainment is a significant social determinant influencing health outcomes both directly and indirectly. Therefore, it is necessary to develop policies to reduce the health inequity of T2DM caused by differences in educational attainment.

Impact of diabetes on the risk of subsequent fractures in 92,600 patients with an incident hip fracture: A Danish nationwide cohort study 2004-2018

PURPOSE

We investigated the incidence rates of a subsequent hip fracture (HF) and other subsequent fractures than HF after first incident HF, comparing patients with and without diabetes.

METHODS

Using Danish medical databases, we identified 92,600 incident HF patients in the period 2004-2018. Diabetes exposure was examined overall, by type of diabetes (T2D and T1D), and by presence of diabetes complications. We estimated cumulative incidence of subsequent HFs and fractures other than HF within two years of the incident HF. Using Cox regression, adjusted hazard ratios (aHRs) with 95 % confidence interval (CI) were calculated.

RESULTS

Among incident HF patients, 11,469 (12 %) had diabetes, of whom 10,253 (89 %) had T2D and 1216 (11 %) had T1D. The 2-year incidence rates for a new subsequent HF were 4.8 % (95 % CI: 4.6-4.9) for patients without diabetes (reference group), 4.1 % (95 % CI: 3.8-4.6) for T2D, and 4.3 % (95 % CI: 3.3-5.6) for T1D. Corresponding aHRs were 1.01 (95 % CI 0.90-1.14) for T2D and 1.17 (95 % CI 0.87-1.58) for T1D. There was effect modification by sex, as women with T1D had an aHR of 1.52 (95 % CI: 1.09-2.11) for subsequent HF, and by specific diabetes complications (for example, patients with T2D and prior hypoglycemia had an aHR of 1.75 (95 % CI: 1.24-2.42) for subsequent HF, while patients with T1D and neuropathy had an aHR of 1.73 (95 %: 1.09-2.75), when compared with patients without diabetes). For fractures other than HF, the 2-year incidence rates were 7.3 % (95 % CI: 7.2-7.5) for patients without diabetes, 6.6 % (95 % CI: 6.1-7.1) for T2D, and 8.5 % (95 % CI: 7.0-10.1) for T1D, with corresponding aHRs of 1.01 (95 % CI 0.92-1.11) for T2D and 1.43 (95 % CI: 1.16-1.78) for T1D. T2D was only a risk factor for other subsequent fractures among HF patients of high age (age 86-89 years: aHR 1.22 (95 % CI 0.99-1.55), age 90+ years: aHR 1.37 (95 % CI 1.08-1.74)), whereas T1D was robustly associated with increased risk of fractures other than HF in all subgroups.

CONCLUSION

Among HF patients, we found no strong overall association of T2D or T1D with increased risk of subsequent HF, but diabetes patients with prior hypoglycemic events or neuropathy were at increased risk. In contrast, patients with T1D had a clearly increased risk of subsequent fractures other than HF.

Improving outcomes of type 2 diabetes mellitus patients in primary care with Chronic Care Model: A narrative review

Designed and implemented over two decades ago, the Chronic Care Model is a well-established chronic disease management framework that has steered several healthcare systems in successfully improving the clinical outcomes of patients with type 2 diabetes mellitus. Research evidence cements the role of the Chronic Care Model (with its six key elements of organization of healthcare delivery system, self-management support, decision support, delivery system design, clinical information systems, and community resources and policies) as an integrated framework to revamp the type 2 diabetes mellitus-related clinical practice and care that betters the patient care and clinical outcomes. The current review is an evidence-lit summary of importance of use of Chronic Care Model in primary care and their impact on clinical outcomes for patients afflicted with one of the most debilitating metabolic diseases, type 2 diabetes mellitus.

Uric acid is associated with type 2 diabetes: data mining approaches

Background

Several blood biomarkers have been related to the risk of type 2 diabetes mellitus (T2D); however, their predictive value has seldom been assessed using data mining algorithms.

Methods

This cohort study was conducted on 9704 participants recruited from the Mashhad Stroke and Heart Atherosclerotic disorders (MASHAD) study from 2010 to 2020. Individuals who were not between the ages of 35 and 65 were excluded. Serum levels of biochemical factors such as creatinine (Cr), high-sensitivity C reactive protein (hs-CRP), Uric acid, alanine aminotransferase (ALT), aspartate aminotransferase (AST), direct and total bilirubin (BIL.D, BIL.T), lipid profile, besides body mass index (BMI), waist circumference (WC), blood pressure, and age were evaluated through Logistic Regression (LR) and Decision Tree (DT) methods to develop a predicting model for T2D.

Results

The comparison between diabetic and non-diabetic participants represented higher levels of triglyceride (TG), LDL, cholesterol, ALT, BIL.D, and Uric acid in diabetic cases (p-value < 0.05). The LR model indicated a significant association between TG, Uric acid, and hs-CRP, besides age, sex, WC, and blood pressure, hypertension and dyslipidemia history with T2D development. DT algorithm demonstrated dyslipidemia history as the most determining factor in T2D prediction, followed by age, hypertension history, Uric acid, and TG.

Conclusion

There was a significant association between hypertension and dyslipidemia history, TG, Uric acid, and hs-CRP with T2D development, along with age, WC, and blood pressure through the LR and DT methods.

Graphical abstract

Incidence of diabetic retinopathy in anti-tnf treated rheumatic disease patients with type 2 diabetes

OBJECTIVE

This study aimed to evaluate the impact of anti-TNF (biological) therapies on the incidence and progression of diabetic retinopathy.

MATERIALS AND METHODS

A cross-sectional analysis of 50 diabetic patients with rheumatic diseases (group 1) was performed. An age-, sex-, and HbA1c-matched control group (group 2) was formed from a pool of diabetic patients who underwent regular eye examinations. The presence or absence of diabetic retinopathy was also assessed. Comorbidities such as hypertension, coronary artery disease, and hyperlipidemia were also evaluated as possible confounding factors.

RESULTS

Hundred eyes of 50 patients were evaluated in each group. Only three patients in group 1 had non-proliferative retinopathy. The median duration of rheumatic disease was 9 years, whereas that of diabetes was 11 years. The mean duration of anti-TNF therapy was 4 years. In the control group of diabetes-only patients, 13 patients developed some form of newly diagnosed diabetic retinopathy during the last five years. The calculated retinopathy occurrence between the groups was statistically significant (p < 0.05). In this study, the incidence rate ratio for patients receiving anti-TNF treatment was calculated as 0.4 in the study.

CONCLUSION

TNF inhibitors, with their anti-inflammatory effects, positively impact diabetic complications by reducing the incidence of retinopathy. To our knowledge, this is the first study to evaluate retinopathy development after anti-TNF therapy.

Machine Learning Approach to Metabolomic Data Predicts Type 2 Diabetes Mellitus Incidence

Metabolomics, with its wealth of data, offers a valuable avenue for enhancing predictions and decision-making in diabetes. This observational study aimed to leverage machine learning (ML) algorithms to predict the 4-year risk of developing type 2 diabetes mellitus (T2DM) using targeted quantitative metabolomics data. A cohort of 279 cardiovascular risk patients who underwent coronary angiography and who were initially free of T2DM according to American Diabetes Association (ADA) criteria was analyzed at baseline, including anthropometric data and targeted metabolomics, using liquid chromatography (LC)-mass spectroscopy (MS) and flow injection analysis (FIA)-MS, respectively. All patients were followed for four years. During this time, 11.5% of the patients developed T2DM. After data preprocessing, 362 variables were used for ML, employing the Caret package in R. The dataset was divided into training and test sets (75:25 ratio) and we used an oversampling approach to address the classifier imbalance of T2DM incidence. After an additional recursive feature elimination step, identifying a set of 77 variables that were the most valuable for model generation, a Support Vector Machine (SVM) model with a linear kernel demonstrated the most promising predictive capabilities, exhibiting an F1 score of 50%, a specificity of 93%, and balanced and unbalanced accuracies of 72% and 88%, respectively. The top-ranked features were bile acids, ceramides, amino acids, and hexoses, whereas anthropometric features such as age, sex, waist circumference, or body mass index had no contribution. In conclusion, ML analysis of metabolomics data is a promising tool for identifying individuals at risk of developing T2DM and opens avenues for personalized and early intervention strategies.

Obesity, body fat distribution and eye diseases

BACKGROUND

The prevalence of obesity, a chronic disease, is increasing, and obesity is now considered a global epidemic. Eye diseases are also increasing worldwide and have serious repercussions on quality of life as well as increasingly high costs for the community. The relationships between obesity and ocular pathologies are not yet well clarified and are not pathologically homogeneous: they seem to be somehow linked to excess body fat, especially to the distribution of adipose tissue and its ectopic deposits.

PURPOSE

Our objective was to examine the associations between obesity and anthropometric indices, including body mass index (BMI), waist circumference (WC), and the waist/hip ratio (WHR), and the risk of most widespread eye diseases, with particular attention given to the most significant metabolic mechanisms.

METHODS

This article provides a narrative overview of the effect of obesity and anthropometric measurements of body fat on prevalent eye diseases. We used the MEDLINE/PubMed, CINAHL, EMBASE, and Cochrane Library databases from 1984 to 2024. In addition, we hand-searched references from the retrieved articles and explored a number of related websites. A total of 153 publications were considered.

RESULTS

There is significant evidence that obesity is associated with several eye diseases. Waist circumference (WC) and the waist/hip ratio (WHR) have been observed to have stronger positive associations with eye diseases than BMI.

CONCLUSIONS

Obesity must be considered a significant risk factor for eye diseases; hence, a multidisciplinary and multidimensional approach to treating obesity, which also affects ocular health, is important. In the prevention and treatment of eye diseases related to obesity, lifestyle factors, especially diet and physical activity, as well as weight changes, both weight loss and weight gain, should not be overlooked.

LEVEL OF EVIDENCE

Level V narrative review.

Banded One-Anastomosis Gastric Bypass (BOAGB) for Patients Living with Obesity and Extreme Obesity: A Single Institution's Experience

BACKGROUND

The prevalence of patients suffering from extreme obesity (body mass index (BMI) ≥ 50) has significantly increased over the past three decades, surpassing the rise in the general population of overweight patients. Weight loss outcomes after bariatric surgery in patients suffering from extreme obesity are less favorable, with a higher incidence of weight regain. Variations of existing bariatric procedures have been proposed to address this issue. One such variation is adding a gastric band to limit the expansion of the newly created pouch. Limited data exist regarding the effectiveness of this procedure, called the banded one-anastomosis gastric bypass (BOAGB) procedure, compared to other bariatric procedures.

METHOD

In this retrospective study, we compared all patients who underwent the BOAGB procedure at the Bariatric Surgery Unit in our Medical Center with a postoperative follow-up of at least 1 year with patients who underwent a one-anastomosis gastric bypass (OAGB) or sleeve gastrectomy (SG) procedures. Data collected included demographics, comorbidities, surgical outcomes, complications, and postoperative quality-of-life assessments.

RESULTS

One hundred eleven patients were enlisted to our study during the relevant study period-24 patients underwent the BOAGB procedure, 43 underwent OAGB, and 44 underwent a SG. Lost to follow-up beyond 30 days was 9% (at 1-year post-surgery, we were able to establish contact with 101 patients). The pre-op BMI was significantly higher in the BOAGB group compared to the other procedures. Additionally, a higher prevalence of diabetes was observed in the BOAGB group. The duration of surgery was significantly longer for the BOAGB procedure. No significant differences were found in surgical complications. Overall, all procedures resulted in significant excess weight loss (EWL) or change in BMI, improvement in comorbidities, and improved quality of life postoperatively.

CONCLUSIONS

The BOAGB procedure, like OAGB and SG, demonstrated favorable weight loss outcomes and weight maintenance 1 year postoperatively without significant differences between the procedures. The BOAGB procedure is relatively new, with good bariatric outcomes and a favorable safety profile. Long-term study is needed to evaluate these various bariatric procedures' efficacy further.

Augmenting authenticity for non-invasive in vivo detection of random blood glucose with photoacoustic spectroscopy using Kernel-based ridge regression

Photoacoustic Spectroscopy (PAS) is a potential method for the noninvasive detection of blood glucose. However random blood glucose testing can help to diagnose diabetes at an early stage and is crucial for managing and preventing complications with diabetes. In order to improve the diagnosis, control, and treatment of Diabetes Mellitus, an appropriate approach of noninvasive random blood glucose is required for glucose monitoring. A polynomial kernel-based ridge regression is proposed in this paper to detect random blood glucose accurately using PAS. Additionally, we explored the impact of the biological parameter BMI on the regulation of blood glucose, as it serves as the primary source of energy for the body's cells. The kernel function plays a pivotal role in kernel ridge regression as it enables the algorithm to capture intricate non-linear associations between input and output variables. Using a Pulsed Laser source with a wavelength of 905 nm, a noninvasive portable device has been developed to collect the Photoacoustic (PA) signal from a finger. A collection of 105 individual random blood glucose samples was obtained and their accuracy was assessed using three metrics: Root Mean Square Error (RMSE), Mean Absolute Difference (MAD), and Mean Absolute Relative Difference (MARD). The respective values for these metrics were found to be 10.94 (mg/dl), 10.15 (mg/dl), and 8.86%. The performance of the readings was evaluated through Clarke Error Grid Analysis and Bland Altman Plot, demonstrating that the obtained readings outperformed the previously reported state-of-the-art approaches. To conclude the proposed IoT-based PAS random blood glucose monitoring system using kernel-based ridge regression is reported for the first time with more accuracy.

Association of weight-adjusted waist index and diabetic kidney disease in type 2 diabetes mellitus

Objective

The aim of this study was to investigate the relationship between weight-adjusted-waist index (WWI) and diabetic kidney disease in individuals afflicted with type 2 diabetes.

Methods

Comprehensive data were ascertained from the National Health and Nutrition Examination Survey in 2013-March 2020. Weighted univariate, multivariate logistic regression models, subgroup analyses and tests for interaction were performed. Additionally, we employed smooth curve fitting to assess linear correlations and the threshold effects were calculated by applying a binary linear regression model. Breakpoints are identified by a model with maximum likelihood ratio and a two-step recursive approach. Receiver operating characteristic curve (ROC) along with the area under the curve (AUC) value predict the capability of WWI and body mass index for diabetic kidney disease.

Results

A total of 10,661 individuals diagnosed with type 2 diabetes were included, and the overall prevalence of diabetic kidney disease was 20.74%. WWI exhibited a positive correlation with the likelihood of diabetic kidney disease in type 2 diabetes patients (OR: 1.17, 95% CI: 1.03-1.33). The results of subgroup analysis showed significant interaction for gender (P < 0.05). Among female patients, U-shaped correlations were observed with a breakpoint at 11.48. Additionally, weight-adjusted waist index (AUC = 0.664) proved to be a more effective predictor of diabetic kidney disease compared to body mass index (AUC = 0.555).

Conclusion

In patients with type 2 diabetes, increased weight-adjusted-waist index is implicated with an increased risk of diabetic kidney disease. WWI can be used as a new anthropometric index to predict diabetic kidney disease, and its predictive ability is stronger than body mass index.

Gene Expression Analysis in T2DM and Its Associated Microvascular Diabetic Complications: Focus on Risk Factor and RAAS Pathway

Prolonged hyperglycemic conditions in type 2 diabetes mellitus (T2DM) cause pathological and functional damage to many organs and tissues, including the kidneys, retina, skin, and neuronal tissues, resulting in the development of microvascular diabetic complications. The altered renin angiotensin aldosterone system (RAAS) pathway has been reported to play an important role in the development of insulin resistance in T2DM and associated complications. The current study was carried out to evaluate the association of risk factors and altered expression of RAAS genes in T2DM patients without complications and T2DM patients with complications (retinopathy, nephropathy, and neuropathy). Four hundred and twenty subjects including 140 healthy controls, 140 T2DM patients with diabetic complications, and 140 T2DM patients without diabetic complications were included in the study. Risk factors associated with the development of T2DM and diabetic complications were evaluated. Further, expression analysis of RAAS genes (AGT, ACE, ACE2, and AGT1R) was carried out using qRTPCR in healthy controls, T2DM patients with complications, and T2DM patients without complications. Various risk factors like urban background, higher BMI, alcoholism, smoking, and family history of diabetes among others were found to be associated with the development of T2DM as well as diabetic complications. The expression level of AGT, ACE, and AGT1R was found to be upregulated whereas ACE2 was found to be downregulated in T2DM patients with complications and T2DM patients without complications as compared to controls. Altered expression of the studied genes of RAAS pathway is associated with the development of microvascular diabetic complications.

Hypolipidemic effect and modulation of hepatic enzymes by different edible oils in obese Wistar rats

The current study assessed the hypolipidemic effect and modulation of hepatic enzymes by different edible oils in obese Wistar rats. In order to conduct this study, 36 Wistar rats that were collected at 5 weeks of age and weighed an average of 70 g were split into two groups: 28 of them were fed a high-fat diet (HFD) and 8 of them were fed a control diet. After 5 weeks of feeding, rats from the HFD (obese, n = 4) and the control diet group (n = 4) were sacrificed. Subsequently, the rest of obese rats (n = 24) were separated into six groups, including the continuing high-fat (CHF) diet group, rice bran oil (RBO) diet group, olive oil (OO) diet group, soybean oil (SO) diet group, cod liver oil (CLO) diet group, and sunflower oil (SFO) diet group, and the continuing control diet group (n = 4). Rats from each group were sacrificed following an additional 5 weeks, and all analytical tests were carried out. The results found that the interventions of RBO, CLO, and SFO in obese rats reduced their body weight non-significantly when compared with CHF. It was also observed that a non-significant reduction in weight of the heart, AAT, and EAT occurred by RBO, OO, SO, and CLO, while SFO reduced the AAT level significantly (p < 0.05). Besides, RBO, OO, SO, CLO, and SFO decreased IBAT and liver fat significantly compared to CHF. Similarly, the administration of RBO, OO, SO, and CLO reduced ALT significantly. RBO reduced GGT (p < 0.05) significantly, but other oils did not. The given oil has the efficiency to reduce TC, TAG, and LDL-C but increase HDL-C significantly. These findings suggest that different edible oils can ameliorate obesity, regulate lipid profiles, and modulate hepatic enzymes.

Peripheral artery disease mediating the effect of metabolic syndrome related diseases on lower limb ulcers: Mendelian randomization analysis

Background

Previous observational studies have demonstrated a correlation between metabolic syndrome related diseases and an elevated susceptibility to ulcers of lower limb. It has been suggested that this causal relationship may be influenced by the presence of peripheral artery disease (PAD). Nevertheless, the precise contribution of these factors as determinants of ulcers of lower limb remains largely unexplored.

Method

This research incorporated information on hypertension, BMI, hyperuricemia, type 2 diabetes, PAD, and ulcers of lower limb sourced from the GWAS database. Univariate Mendelian randomization (SVMR) and multivariate Mendelian randomization (MVMR) methods were employed to assess the association between metabolic syndrome related diseases, including hypertension, obesity, hyperuricemia, and type 2 diabetes, as well as to investigate whether this association was influenced by PAD.

Results

Univariate Mendelian randomization analysis showed that genetically predicted hypertension, BMI, and type 2 diabetes were associated with an increased risk of PAD and ulcers of lower limb, and PAD was associated with an increased risk of ulcers of lower limb, but there is no causal relationship between hyperuricemia and ulcers of lower limb. The results of multivariate Mendelian randomization showed that PAD mediated the causal relationship between hypertension, obesity and ulcers of lower limb, but the relationship between type 2 diabetes and ulcers of lower limb was not mediated by PAD.

Conclusion

Hypertension, BMI and type 2 diabetes can increase the risk of ulcers of lower limb, and PAD can be used as a mediator of hypertension and obesity leading to ulcers of lower limb, These findings may inform prevention and intervention strategies directed toward metabolic syndrome and ulcers of lower limb.

Genetic Investigation of the Trail Mechanism in Diabetic and Non-diabetic Obese Patients

Obesity is an important healthcare issue caused by abnormally increased adipose tissue because of energy-intake overcoming energy expenditure. Disturbances in the physiological function of adipose tissue mediate the development of diabetes. It is a metabolic disease that results from decreased insulin-levels and/or changes in the insulin action mechanism. Tumor Necrosis Factor-Associated Apoptosis-Inducing Ligand(TRAIL), which is a member of the Tumor Necrosis Factor(TNF)-family with an important role in adipose tissue biology, is included in many studies with its ability to induce apoptosis in cancer cells, but the number of human-studies conducted on the gene related to its protective-role against diabetes and obesity at this level is insufficient. Our study was carried out as a case and control and included three groups (80 diabetic obese, 80 non-diabetic obese, and 80 healthy individuals as the control group). The Real-Time-PZR(RT-qPZR), and DNA Sanger-Sequencing Methods were used for gene expression and gene squences. As a result of the analyses, TRAIL gene expression level was found to be higher in the controls than in the diabetic-obese and non-diabetic-obese group. This change in TRAIL gene expression suggests that TRAIL maybe a protective factor against diabetes. The presence of rs781673405, rs143353036, rs1244378045, rs767450259, rs759369504, rs750556128, and rs369143448 mutations, which was determined with the Sequencing-Method, was shown for the first time in the present study. In addition, it is the first study in which human TRAIL gene-expression and sequencing were performed together. We believe that these data will make an important contribution to the literature.

Polygenic risk scores for cardiometabolic traits demonstrate importance of ancestry for predictive precision medicine

Polygenic risk scores (PRS) have predominantly been derived from genome-wide association studies (GWAS) conducted in European ancestry (EUR) individuals. In this study, we present an in-depth evaluation of PRS based on multi-ancestry GWAS for five cardiometabolic phenotypes in the Penn Medicine BioBank (PMBB) followed by a phenome-wide association study (PheWAS). We examine the PRS performance across all individuals and separately in African ancestry (AFR) and EUR ancestry groups. For AFR individuals, PRS derived using the multi-ancestry LD panel showed a higher effect size for four out of five PRSs (DBP, SBP, T2D, and BMI) than those derived from the AFR LD panel. In contrast, for EUR individuals, the multi-ancestry LD panel PRS demonstrated a higher effect size for two out of five PRSs (SBP and T2D) compared to the EUR LD panel. These findings underscore the potential benefits of utilizing a multi-ancestry LD panel for PRS derivation in diverse genetic backgrounds and demonstrate overall robustness in all individuals. Our results also revealed significant associations between PRS and various phenotypic categories. For instance, CAD PRS was linked with 18 phenotypes in AFR and 82 in EUR, while T2D PRS correlated with 84 phenotypes in AFR and 78 in EUR. Notably, associations like hyperlipidemia, renal failure, atrial fibrillation, coronary atherosclerosis, obesity, and hypertension were observed across different PRSs in both AFR and EUR groups, with varying effect sizes and significance levels. However, in AFR individuals, the strength and number of PRS associations with other phenotypes were generally reduced compared to EUR individuals. Our study underscores the need for future research to prioritize 1) conducting GWAS in diverse ancestry groups and 2) creating a cosmopolitan PRS methodology that is universally applicable across all genetic backgrounds. Such advances will foster a more equitable and personalized approach to precision medicine.

Do Serum Nesfatin-1 Levels have A Predictive Role in Type-2 Diabetes Mellitus and its Microvascular Complications? A Case-Control Study

Background Type 2 diabetes mellitus (T2DM) is a chronic disease with macrovascular and microvascular complications. Nesfatin-1 is a neuropeptide that develops from a more substantial intermediate compound known as nucleobindin 2 (NUCB2). Nesfatin-1 is known to play a role in regulating various physiological processes related to appetite, energy balance, and body weight. The purpose of the current study was to investigate the serum levels of nesfatin-1 in Egyptian patients with type 2 diabetes mellitus (T2DM) in comparison to healthy subjects and to assess the association of serum nesfatin-1 levels with the occurrence of diabetic microvascular complications in those patients. Methods This matched case-control study was conducted on 90 subjects 40-80 years old, with normal hepatic, cardiac, and respiratory functions, and 60 of them had T2DM. The included participants were divided into two groups: group 1, which was the control group and included 30 healthy subjects, and group 2, which included 60 subjects with T2DM. Group 2 was subdivided according to the presence or absence of microvascular complications into group 2a, which included 30 patients having T2DM with no microvascular complications, and group 2b, which included 30 patients having T2DM with one or more microvascular complications. Results T2DM patients had significantly lower serum nesfatin-1 levels (5.07±1.78 versus 9.05±2.1 mmol/L, <0.001) compared to healthy controls. Also, T2DM patients with microvascular complications had lower serum nesfatin-1 levels (4.32±1.72 versus 5.83±1.51 mmol/L, <0.001) compared to T2DM patients without microvascular complications. Serum nesfatin-1 level at a cutoff value of <8.09 mmol/L can be a marker for the detection of diabetes mellitus (DM) with the area under the curve (AUC) of 94.3%, 95% sensitivity, 74.3% specificity, 77.9% positive predictive value (PPV), and 65.7% negative predictive value (NPV), and at a cutoff value of <5.87 mmol/L can be a marker for the detection of microvascular complications of diabetes mellitus at AUC of 75.5%, 76.7% sensitivity, 67.3% specificity, 77.1% PPV, and 62.9% NPV. Conclusions Serum Nesfatin-1 may play a potential protective role in diabetes mellitus (DM) and its microvascular complications, as it decreases in individuals with diabetes and those with diabetic microvascular complications compared to controls. Additionally, serum Nesfatin-1 levels may have predictive value for the early detection of Type 2 diabetes mellitus (T2DM) patients, diabetic microvascular complications, and diabetic kidney disease (DKD) at cut-off values of < 8.09 (mmol/L), < 5.87 (mmol/L), and < 5.46 (mmol/L), respectively. Therefore, targeted Nesfatin-1 drug therapy may be tried to reduce morbidity and mortality caused by microvascular complications of diabetes.

Observational, Multicenter, Retrospective, Study on the Usage Patterns of the Fixed Dose Combination of Glimepiride, Metformin, and Voglibose in Type 2 Diabetes Management

Objective This study aimed to evaluate and analyze the characteristics of Indian patients with type 2 diabetes mellitus (T2DM) in relation to the usage patterns of a fixed-dose combination (FDC) of glimepiride, metformin, and voglibose. Methods This retrospective, observational, multicentric analysis was conducted from March 2021 to September 2022. It involved adult patients (aged ≥18 years) with T2DM from 424 sites including a combination of hospitals and privately owned clinics across India to ensure comprehensive representation of the patient population The study included patients who had been treated with FDC of glimepiride, metformin, and voglibose of varying strengths for T2DM management. Data were collected through a pre-designed electronic form, which captured demographic details, medical history, T2DM history, and drug usage patterns from medical records. The collected data were then analyzed using descriptive statistical methods. Results This analysis encompassed a final cohort of 8,587 patients out of which 5,840 were males with a mean age of 54.91 years and a BMI of 28.41 kg/m2. Newly diagnosed T2DM cases were 35.23%, 54.79% had a family history, and 61.21% had risk factors such as smoking, sedentary lifestyle, and others. Dyslipidemia (13.94%) and neuropathy (14.48%) were common comorbidities. The most prescribed FDC was 1 mg glimepiride, 500 mg metformin, 0.2 mg voglibose (40.14%), the most preferred dosing frequency was once daily (52.92%) and the most common duration of treatment was one to three months (48.78%). Conclusion In routine Indian clinical practice, the triple drug FDC of 1 mg glimepiride, 500 mg metformin, and 0.2 mg voglibose, taken once daily for one to three months, was the most common treatment for both newly diagnosed and long-standing diabetes patients.

Exploratory Approach to Incorporating Carbon Footprint in Health Technology Assessment (HTA) Modelling: Cost-Effectiveness Analysis of Health Interventions in the United Kingdom

BACKGROUND

Health interventions contribute to the production of greenhouse gas emissions. Thus, reducing carbon footprint is essential in supporting the UK National Health Service (NHS) pathway to net zero. This study explores the approach in which carbon footprint can be included when applying Health Technology Assessment (HTA) modelling using obesity intervention in the United Kingdom (UK) as a case study.

METHODS

Using decision analytic modelling, we conducted an HTA incorporating the impacts of obesity-related treatment decisions on UK carbon emissions. A cohort Markov model was used to track the emissions of the UK population after receiving one of two obesity treatments: semaglutide and bariatric surgery.

RESULTS

This study introduced two new carbon measurement tools that may be useful for future policymaking, incremental carbon footprint effectiveness ratio (ICFER) and incremental carbon footprint cost ratio (ICFCR), which made it possible to assess the emission impacts of proposed health policies. Using the obesity intervention case study, we found that both treatments have an incremental cost-effectiveness ratio (ICER) of < £20,000 per quality-adjusted life-years (QALYs) gained. This is below the UK threshold, indicating that these are cost-effective treatments for obesity, but could increase the NHS carbon footprint. However, it could reduce the overall UK societal carbon footprint by reducing the number of people with obesity. The ICFCR shows a reduction of 1.13-4.51 kgCO2e (kilogram of carbon dioxide equivalent) for every pound spent on obesity treatment.

CONCLUSION

This study illustrates a case study for estimating the effect of health policies on carbon emissions and provides a quantitative measure for obesity-related treatment decisions.

The awareness and determinants of diabetic foot ulcer prevention among diabetic patients: Insights from NHANES (2011-2018)

The prevention of diabetic foot ulcers (DFU) precedes treatment, in that early prevention significantly reduces the incidence of foot ulcers. The main objectives of this study were to examine the current prevalence of proactive foot ulcer examinations among diabetic patients and analyze influencing factors, in order to provide a scientific reference for the prevention of DFU in diabetic patients. The National Health and Nutrition Examination Survey (NHANES) 2011-2018 (n = 1278) data were utilized in this cross-sectional study. The dependent variable was whether patients underwent self-initiated foot ulcer inspections; risk factors that may lead to foot ulcers were included as independent variables. To explore the connection between the patient's subjective motivation to inspect foot ulcers and risk variables, the weighted logistic regression model was further carried out. Among all risk factors, race, body mass index (BMI) and hypertension were statistically significant between whether patients were examined for foot ulcers or not. In the fully adjusted logistic regression model, only hypertension was positively correlated with diabetic patient-initiated examination for foot ulcers. This study suggests that there is still room for improvement in the knowledge and behavior of diabetic patients to be proactive in preventing DFU. Health care and community workers should conduct targeted training on diabetic foot prevention to reduce and prevent DFU by reinforcing knowledge to build positive attitudes and drive preventive behavior change.

The role of ultra-processed food consumption and depression on type 2 diabetes incidence: a prospective community study in Quebec, Canada

OBJECTIVES

The goal of the present study was to evaluate the association between depression and ultra-processed food (UPF) consumption as risk factors for developing type 2 diabetes (T2D).

DESIGN

A prospective community study.

SETTING

Baseline data (2009-2010) from CARTaGENE community health study from Quebec, Canada, were used. Food and drink consumption was assessed using the Canadian-Diet History Questionnaire II and grouped according to their degree of processing by the NOVA classification, and participants were categorised into tertiles of UPF (g/d). Depression was defined using either a validated cut-off score on the Patient Health Questionnaire-9 or antidepressant use. The outcome was the incidence of T2D, examined in 3880 participants by linking survey data with administrative health insurance data. Cox regression models estimated the associations between UPF, depression and incident T2D.

PARTICIPANTS

40-69-year-old individuals at baseline.

RESULTS

In total, 263 (6·8 %) individuals developed T2D. Participants with high depressive symptoms and high UPF consumption showed the highest risk for T2D (adjusted hazard ratios (aHR) = 1·58, 95 % CI (0·98, 2·68)), compared to those with low depressive symptoms and low UPF consumption. The risk for T2D was similar when high depressive symptoms and antidepressant use were combined with high UPF (aHR 1·62, 95 % CI (1·02, 2·57)).

CONCLUSIONS

This study shows that co-occurring depression and high UPF consumption were associated with a higher risk for T2D. Early management and monitoring of both risk factors might be essential for diabetes prevention.

Adipocyte dysfunction promotes lung inflammation and aberrant repair: a potential target of COPD

Background

Obesity and chronic obstructive pulmonary disease (COPD) are prevailing worldwide, bringing a heavy medical burden. Clinical and pathophysiological relationship between obesity and COPD is paradoxical and elusive. We aim to explore their inherent associations from clinical, genetic, and animal levels.

Methods

We performed literature review and cohort analysis of patients with COPD to compare lung function, symptom, and prognosis among different weight groups. After retrieving datasets of obesity and COPD in Gene Expression Omnibus (GEO) database, we carried out differentially expressed gene analysis, functional enrichment, protein-protein interactions network, and weighted gene co-expression network analysis. Then, we acquired paraffin-embedded lung tissues of fatty acid-binding protein 4-Cre-BMPR2fl/fl conditional knockout (CKO) mice that were characterized by adipocyte-specific knockout of bone morphogenetic protein receptor 2 (BMPR2) for staining and analysis.

Results

Our cohort study reports the effect of obesity on COPD is inconsistent with previous clinical studies. Lung function of overweight group was statistically superior to that of other groups. We also found that the inflammatory factors were significantly increased hub genes, and cytokine-associated pathways were enriched in white adipose tissue of patients with obesity. Similarly, injury repair-associated genes and pathways were further enhanced in the small airways of patients with COPD. CKO mice spontaneously developed lung injury, emphysema, and pulmonary vascular remodeling, along with increased infiltration of macrophages. BMPR2-defiecient adipocytes had dysregulated expression of adipocytokines.

Conclusion

Inflammation and abnormal repair might be potential mechanisms of the pathological association between obesity and COPD. BMPR2-associated adipocyte dysfunction promoted lung inflammation and aberrant repair, in which adipocytokines might play a role and thus could be a promising therapeutic target.

Is isoenergetic high-intensity interval exercise superior to moderate-intensity continuous exercise for cardiometabolic risk factors in individuals with type 2 diabetes mellitus? A single-blinded randomized controlled study

The aim of this study was to compare the effect of high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) with equal energy expenditure on glycaemic and cardiometabolic risk factors in people with Type 2 Diabetes Mellitus (T2DM) when compared to the control. Sixty-three people with T2DM were randomly assigned to HIIT, MICT, or non-exercising controls. Individuals were trained with HIIT at 90 and 30% of their VO2peak (1:2 min ratio) starting from 8 up to 16 intervals and MICT at 50% of VO2peak, on a cycle ergometer, 3 times/week for 12 weeks under supervision. The primary outcome measure was the change in HbA1c. Aerobic capacity, cardiovascular responses, anthropometric measures, body composition, glycaemic, and cardiometabolic risk factors were measured at the beginning and the end of the 12-week training period. There was no significant difference between HIIT and MICT or when compared to the control for HbA1c, glucose, insulin resistance, blood lipids, cardiovascular responses, anthropometric measures, body composition, and abdominal and visceral fat (padj > 0.05). HIIT and MICT increased VO2peak significantly compared to controls (p < 0.05) but not to each other (p > 0.05). Both HIIT and MICT improved VO2peak and HbA1c after 12 weeks of training compared to their baseline, furthermore, only MICT caused additional improvements in cardiovascular responses, anthropometric measures, and abdominal fat compared to baseline (p < 0.05). As a conclusion, isoenergetic HIIT or MICT did not improve HbA1c. The two protocols were equally efficient for improvement in aerobic capacity but had little effect on other cardiometabolic factors.Trial registration: ClinicalTrials.gov identifier: NCT03682445.HighlightsHIIT and MICT with equal energy expenditure were equally efficient for aerobic capacity compared to controls.Isoenergetic HIIT or MICT were not superior for improving HbA1c.Isoenergetic HIIT and MICT were not superior to each other for anthropometric measures, body composition, and cardiometabolic risk factors.

Microvascular complications of obesity and diabetes-Role of bariatric surgery

Bariatric surgery in people with obesity can lead to long-term remission of type 2 diabetes mellitus (T2DM) and a reduction in the incidence of macrovascular complications. The impact of bariatric surgery on microvascular complications is less clear. In this narrative review, we sought to evaluate the effect of bariatric surgery on microvascular complications in patients with and without diabetes. The risk of developing microvascular complications is increased in people with obesity, and this is amplified in those with T2DM. The impact of metabolic surgery on microvascular complications is limited to a subgroup analysis of studies or statistical modeling to predict the glycemia-independent effect of bariatric surgery. While bariatric surgery halts the progression of retinopathy in those with minimal retinopathy, it may worsen in those with advanced retinopathy. Bariatric surgery improves proteinuria and major renal outcomes, regardless of the severity of renal impairment. Bariatric surgery in patients with obesity with or without diabetes is associated with an improvement in neuropathic symptoms and regeneration of small nerve fibers. In conclusion, bariatric surgery is associated with an improvement in microvascular complications. Further studies are needed to elucidate the underlying mechanisms for the favorable effect of bariatric surgery on microvascular outcomes.

The Effect of Fenugreek in Type 2 Diabetes and Prediabetes: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Fenugreek is a widely used herbal medicine as a complementary therapy for diabetes mellitus. Lots of clinical trials have proved its beneficial effect on glycemic control parameters and lipid profiles. Thus, we conducted a systematic review and meta-analysis to evaluate the effectiveness and safety of fenugreek as a treatment for type 2 diabetes mellitus. We searched PubMed, Embase, Cochrane, China Knowledge Resource Integrated Database (CNKI), Korean studies Information Service System (KISS), Research Information Sharing Service (RISS), and ScienceON to select RCTs which used fenugreek targeting hyperglycemia with a control group. We used either a random effect model or a fixed model in a meta-analysis of Fasting blood glucose (FBG), 2 h plasma glucose during a 75 g oral glucose tolerance test (OGTT) (2-hPG), homeostatic model assessment for insulin resistance (HOMA-IR), glycosylated hemoglobin (HbA1c)/total cholesterol (TC), triglyceride (TG), high density lipoprotein (HDL-C), low density lipoprotein (LDL-C), body mass index (BMI). After screening, a total of 10 studies (706 participants) remained. Fenugreek significantly reduced FBG, 2-hPG, and HbA1c, but it did not significantly decrease HOMA-IR. Moreover, it significantly improved TC, TG, and HDL-C, while there were no significant differences in LDL-C and BMI. Hepatic or renal toxicity was not observed, and there were no severe adverse events associated with fenugreek despite mild gastrointestinal side effects in some studies. In conclusion, fenugreek improves overall glycemic control parameters and lipid profile safely.

Correlation between diabetic retinopathy and Helicobacter pylori infection: a cross-sectional retrospective study

AIM

To explore the correlation between diabetic retinopathy (DR) and Helicobacter pylori (Hp) infection, based on data from a physical examination population.

METHODS

This cross-sectional retrospective analysis included data of 73 824 health examination participants from December 2018 to December 2019. Participants were divided into the diabetic group and non-diabetic group, non-diabetic retinopathy (NDR) group, non-proliferative diabetic retinopathy (NPDR) group, proliferative diabetic retinopathy (PDR) group, and Hp infection group. Gender, age, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), fasting plasma glucose (FPG), glycated hemoglobin A1c (HbA1c), triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and Hp data were recorded to compare the degree of DR lesions and Hp infection. Logistic regression analysis was used to evaluate the correlation between DR and Hp infection.

RESULTS

There was a statistically significant difference between the diabetic and non-diabetic group (χ2=94.17, P<0.0001). Logistic regression analysis showed that male sex, age, BMI, SBP, TG, LDL-C, and Hp infection were independent risk factors for DR. There was no correlation between the degree of DR lesions and Hp infection (ρ=-0.00339, P=0.7753). Age [odds ratio (OR)=1.035, 95%CI: 1.024, 1.046, P<0.0001] and SBP (OR=1.009, 95%CI: 1.004, 1.015, P=0.0013) were independent risk factors for the degree of DR.

CONCLUSION

There is a significant correlation between DR and Hp infection in the physical examination population. Hp infection is a risk factor for DR, and there is no significant difference between Hp infection and DR of different pathological degrees. Actively eradicating Hp may be of help to prevent DR.

The Impact of Pregnancy on Diabetic Retinopathy: A Single-Site Study of Clinical Risk Factors

INTRODUCTION

This study aimed to provide information on modifiable and non-modifiable risk factors for the progression and development of diabetic retinopathy (DR) and diabetic macular edema (DME). This retrospective chart review case-control study was designed to provide perspective on clinical variables.

METHODS

Single-center study analysis was completed with chart review, identifying 50 patients (100 eyes) ultimately included in the final analysis. Included patients were women with type 1 or 2 diabetes that entered prenatal care and had a delivery from January 2010 to December 2022. The primary outcome measure was clinical variables between progression and no progression groups. Data were analyzed via χ2 analysis and independent samples t test when appropriate. Significantly different variables were further analyzed by binary logistic regression.

RESULTS

The DR progression group had significantly higher prepregnancy HbA1c levels (9.9) when compared to the no progression group (8.5, p value 0.028). DR progression group also had higher rates (51.9%) of full-term births. The DME progression group had significantly higher rates of type 2 diabetics (100%) compared to the no progression group (30.9%, p value 0.029). Hypertension treatment before (81.8%; p value 0.008) pregnancy was also more common in the DME progression group. Intravitreal injections were more common in patients with visual acuity deterioration (26.7%, p value 0.046). The average number of fetal complications was significantly higher in the visual acuity non-worsening group (1.1) compared to the progression group (0.5, p value 0.04). These variables were not statistically significant after entry into multivariate analysis.

DISCUSSION

Severity and treatment of retinopathy before pregnancy, type of diabetes, and blood pressure control are all significant factors affecting the progression and development of severe ocular complications in pregnancy.

An early warning model of type 2 diabetes risk based on POI visit history and food access management

Type 2 diabetes (T2D) is a long-term, highly prevalent disease that provides extensive data support in spatial-temporal user case data mining studies. In this paper, we present a novel T2D food access early risk warning model that aims to emphasize health management awareness among susceptible populations. This model incorporates the representation of T2D-related food categories with graph convolutional networks (GCN), enabling the diet risk visualization from the geotagged Twitter visit records on a map. A long short-term memory (LSTM) module is used to enhance the performance of the case temporal feature extraction and location approximate predictive approach. Through an analysis of the resulting data set, we highlight the food effect category has on T2D early risk visualization and user food access management on the map. Moreover, our proposed method can provide suggestions to T2D susceptible patients on diet management.

Explainable artificial intelligence on life satisfaction, diabetes mellitus and its comorbid condition

This study uses artificial intelligence for testing (1) whether the comorbidity of diabetes and its comorbid condition is very strong in the middle-aged or old (hypothesis 1) and (2) whether major determinants of the comorbidity are similar for different pairs of diabetes and its comorbid condition (hypothesis 2). Three pairs are considered, diabetes-cancer, diabetes-heart disease and diabetes-mental disease. Data came from the Korean Longitudinal Study of Ageing (2016-2018), with 5527 participants aged 56 or more. The evaluation of the hypotheses were based on (1) whether diabetes and its comorbid condition in 2016 were top-5 determinants of the comorbidity in 2018 (hypothesis 1) and (2) whether top-10 determinants of the comorbidity in 2018 were similar for different pairs of diabetes and its comorbid condition (hypothesis 2). Based on random forest variable importance, diabetes and its comorbid condition in 2016 were top-2 determinants of the comorbidity in 2018. Top-10 determinants of the comorbidity in 2018 were the same for different pairs of diabetes and its comorbid condition: body mass index, income, age, life satisfaction-health, life satisfaction-economic, life satisfaction-overall, subjective health and children alive in 2016. In terms of SHAP values, the probability of the comorbidity is expected to decrease by 0.02-0.03 in case life satisfaction overall is included to the model. This study supports the two hypotheses, highlighting the importance of preventive measures for body mass index, socioeconomic status, life satisfaction and family support to manage diabetes and its comorbid condition.

Analysis of retinal and choroidal characteristics in patients with early diabetic retinopathy using WSS-OCTA

Introduction

Diabetic retinopathy (DR) is one of the most common and destructive microvascular complications of DM, and has become a major cause of irreversible visual impairment. The purpose of this study was to evaluate the changes in fundus microcirculation in non-diabetic retinopathy (NDR) and mild non-proliferative diabetic retinopathy (NPDR) in patients with type 2 diabetic mellitus (T2DM) using widefield swept-source optical coherence tomography angiography (WSSOCTA), and to investigate the correlation with laboratory indices of T2DM.

Methods

Eighty nine, 58 and 28 eyes were included in the NDR, NPDR and Control groups, respectively, were enrolled in this study. The 12mm×12mm fundus images obtained by WSS-OCTA were divided into 9 regions (supratemporal, ST; temporal, T; inferotemporal, IT; superior, S; central macular area, C; inferior, I; supranasal, SN; nasal, N; inferonasal, IN) to evaluate changes in vessel density (VD) of the superficial capillary plexus (SCP), deep capillary plexus (DCP), choriocapillaris, and mid-large choroidal vessel (MLCV), as well as changes in inner retinal thickness (IRT), outer retinal thickness (ORT), and choroidal thickness (CT). Results: Compared with control group, MLCV VD (I, N, IN) was significantly decreased in NDR group, SCP VD (IT, C, I) and DCP VD (T, IT, I) were significantly decreased in NPDR group. In NPDR group, DCP VD (IT) was significantly decreased compared with that in NDR group. Compared with control group, CT (ST, T, IT, S, SN, IN) was significantly declined in NDR group, and IRT (ST, IT) and ORT (ST, N) were significantly increased in NPDR group. In NPDR group, IRT (ST) and ORT (T, S) were significantly increased compared with NDR group. Correlation analysis showed that age, body mass index, fasting blood glucose, fasting insulin, fasting C-peptide, and estimated glomerular filtration rate in T2DM patients were statistically correlated with retinal and choroidal thickness/VD.

Discussion

Structural and blood flow changes in the choroid occur before the onset of DR and precede changes in the retinal microcirculation, and MLCV thickness/VD is a more sensitive imaging biomarker for the clinical detection of DR. WSS-OCTA enables large-scale non-invasive visual screening and follow-up of the retinal and choroidal vasculature in DR patients, providing a new strategy for the prevention and monitoring of DR in patients with T2DM.

Effectiveness of telemonitoring intervention on glycaemic control in patients with type 2 diabetes mellitus: A systematic review and meta-analysis

BACKGROUND

Type 2 diabetes mellitus (T2DM) is a rising global health concern that requires long-term treatment and close monitoring. Telemonitoring has been shown to be a promising tool to facilitate patient-physician interaction and improve glycaemic control.

METHOD

Randomised controlled trials (RCT) of telemonitoring in T2DM published between 1990 and 2021 were searched through multiple electronic databases. The primary outcome variables included HbA1c and fasting blood glucose (FBG), and BMI was a secondary outcome variable.

RESULTS

Thirty RCT with a total of 4,678 participants were included in this study. Twenty-six studies reported on HbA1c, which was shown to be significantly lower in participants on telemonitoring when compared to conventional care. Ten studies investigated FBG which collectively showed no statistically significant difference. Subgroup analysis demonstrated the effect of telemonitoring on glycaemic control is influenced by a range of factors concerning system practicality, user engagement, patient characteristics and disease education.

CONCLUSION

Telemonitoring exhibited a great potential to improve T2DM management. Several technical features and patient factors may influence the effectiveness of telemonitoring. Further studies are needed to verify the findings and address limitations before its implementation into routine practice.

Obesity Measured via Body Mass Index May Be Associated with Increased Incidence but Not Worse Outcomes of Immune-Mediated Diarrhea and Colitis

Obesity defined by high body mass index (BMI) has traditionally been associated with gastrointestinal inflammatory processes but has recently been correlated with better survival in patients receiving immune checkpoint inhibitors (ICI). We sought to investigate the association between BMI and immune-mediated diarrhea and colitis (IMDC) outcomes and whether BMI reflects body fat content on abdominal imaging. This retrospective, single-center study included cancer patients with ICI exposure who developed IMDC and had BMI and abdominal computed tomography (CT) obtained within 30 days before initiating ICI from April 2011 to December 2019. BMI was categorized as <25, ≥25 but <30, and ≥30. Visceral fat area (VFA), subcutaneous fat area (SFA), total fat area (TFA: VFA+SFA), and visceral to subcutaneous fat (V/S) ratio were obtained from CT at the umbilical level. Our sample comprised 202 patients; 127 patients (62.9%) received CTLA-4 monotherapy or a combination, and 75 (37.1%) received PD-1/PD-L1 monotherapy. Higher BMIs ≥ 30 were associated with a higher incidence of IMDC than BMIs ≤ 25 (11.4% vs. 7.9%, respectively; p = 0.029). Higher grades of colitis (grade 3-4) correlated with lower BMI (p = 0.03). BMI level was not associated with other IMDC characteristics or did not influence overall survival (p = 0.83). BMI is strongly correlated with VFA, SFA, and TFA (p < 0.0001). Higher BMI at ICI initiation was linked to a higher incidence of IMDC but did not appear to affect outcomes. BMI strongly correlated with body fat parameters measured by abdominal imaging, suggesting its reliability as an obesity index.

Machine Learning as a Support for the Diagnosis of Type 2 Diabetes

Diabetes is a chronic, metabolic disease characterized by high blood sugar levels. Among the main types of diabetes, type 2 is the most common. Early diagnosis and treatment can prevent or delay the onset of complications. Previous studies examined the application of machine learning techniques for prediction of the pathology, and here an artificial neural network shows very promising results as a possible valuable aid in the management and prevention of diabetes. Additionally, its superior ability for long-term predictions makes it an ideal choice for this field of study. We utilized machine learning methods to uncover previously undiscovered associations between an individual’s health status and the development of type 2 diabetes, with the goal of accurately predicting its onset or determining the individual’s risk level. Our study employed a binary classifier, trained on scratch, to identify potential nonlinear relationships between the onset of type 2 diabetes and a set of parameters obtained from patient measurements. Three datasets were utilized, i.e., the National Center for Health Statistics’ (NHANES) biennial survey, MIMIC-III and MIMIC-IV. These datasets were then combined to create a single dataset with the same number of individuals with and without type 2 diabetes. Since the dataset was balanced, the primary evaluation metric for the model was accuracy. The outcomes of this study were encouraging, with the model achieving accuracy levels of up to 86% and a ROC AUC value of 0.934. Further investigation is needed to improve the reliability of the model by considering multiple measurements from the same patient over time.

Screening for Diabetes Mellitus in Patients with Hidradenitis Suppurativa—A Monocentric Study in Germany

Hidradenitis suppurativa (HS) is a chronic skin disease that is often associated with metabolic disorders. Diabetes mellitus (DM) is a frequent comorbidity in HS. There is currently no established screening for DM in HS patients. The aim of our study was to identify high-risk groups of HS patients that develop DM and to assess the frequency of different types of DM present in HS patients. To do so, we conducted a monocentric study in 99 patients with HS. All patients underwent detailed clinical and laboratory assessments, including the determination of glycated hemoglobin. Among the 20.2% of patients that presented with DM, type 2 was by far the most prevalent (19 out of 20 patients). Moreover, male gender, age, BMI, Hurley stage, modified Hidradenitis Suppurativa Score (mHSS), DLQI and hypertension all correlated with the glycated hemoglobin levels in the HS patients. In the multivariable analysis, Hurley stage III, older age, and higher BMI were significantly associated with DM. Specifically, patients at Hurley stage III were at a 5.3-fold increased risk of having DM type II compared to patients at earlier Hurley stages. Since many of the HS patients had not been diagnosed, our study reveals shortcomings in the screening for DM and suggest that this should be routinely performed in HS patients at high risk to avoid secondary complications.

Uncovering the NAFLD burden in people living with HIV from high- and middle-income nations: a meta-analysis with a data gap from Subsaharan Africa

INTRODUCTION

Non-alcoholic fatty liver disease (NAFLD) has become a significant concern among people living with HIV (PLHIV), albeit its burden remains unclear. The primary objective of this systematic review (SR) and meta-analysis (MA) was to estimate the prevalence of NAFLD and significant fibrosis in PLHIV. The secondary objective was to determine the risk factors for NAFLD among PLHIV.

METHODS

We searched MEDLINE and Scopus from inception to 30 December 2022 for peer-reviewed studies that included PLHIV and reported the prevalence of NAFLD. MA of proportions was used to estimate the pooled prevalence of NAFLD and significant fibrosis. MA of pre-calculated effect estimates examined risk factors for NAFLD in PLHIV.

RESULTS

We included 24 articles published between 2009 and 2022, encompassing 6326 PLHIV. The pooled prevalence of NAFLD was 38% (95% CI: 31-45%) with high heterogeneity (I² = 96.3%). The pooled prevalence of significant fibrosis was 13% (95% CI: 8-18%) with high heterogeneity (I² = 92.09%). Subgroup analyses showed a NAFLD prevalence of 40% (95% CI: 24-57%) in the United States, 33% (95% CI: 31-36) in Asia, 42% (95% CI: 24-61%) in Europe and 33% (95% CI: 29-37) in South America. When stratifying by income level, NAFLD was 39% (95% CI: 31-48) prevalent in PLHIV from high-income economies and 34% in both upper-middle-income (95% CI: 31-37%) and lower-middle-income economies (95% CI: 28-41%). Higher body mass index (BMI) (OR = 1.32, 95% CI: 1.13-1.55; I² = 89.9%), increasing triglycerides (OR = 1.48, 95% CI: 1.22-2.79; I² = 27.2%) and dyslipidaemia (OR = 1.89, 95% CI: 1.32-2.71; I² = 15.5%) were all associated with higher risk-adjusted odds of NAFLD in PLHIV.

DISCUSSION

The burden of NAFLD and significant fibrosis in PLHIV is significant. Therefore, targeted efforts to screen and diagnose NAFLD in this population are needed. Health services for PLHIV could include ways to target NAFLD risk factors, screen for liver disease and implement interventions to treat those with significant fibrosis or more advanced stages of liver disease. Taking no action to address NAFLD in PLHIV should not be an option.

CONCLUSIONS

This SR and MA found a 38% NAFLD and 13% significant fibrosis prevalence in PLHIV. Increasing triglyceride levels, higher BMI values and dyslipidaemia were associated with higher risk-adjusted odds of NAFLD among PLHIV.

Lipoxin and glycation in SREBP signaling: Insight into diabetic cardiomyopathy and associated lipotoxicity

Diabetes and cardiovascular diseases are the leading cause of morbidity and mortality worldwide. Diabetes increases cardiovascular risk through hyperglycemia and atherosclerosis. Chronic hyperglycemia accelerates glycation reaction, which forms advanced glycation end products (AGEs). Additionally, hyperglycemia with enhanced levels of cholesterol, native and oxidized low-density lipoproteins, free fatty acids, and oxidative stress induces lipotoxicity. Accelerated glycation and disturbed lipid metabolism are characteristic features of diabetic heart failure. SREBP signaling plays a significant role in lipid and glucose homeostasis. AGEs increase lipotoxicity in diabetic cardiomyopathy by inhibiting SREBP signaling. While anti-inflammatory lipid mediators, lipoxins resolve inflammation caused by lipotoxicity by upregulating the PPARγ expression and regulating CD36. PPARγ connects the bridge between glycation and lipoxin in SREBP signaling. A summary of treatment modalities against diabetic cardiomyopathy is given in brief. This review indicates the novel therapeutic approach in the crosstalk between glycation and lipoxin in SREBP signaling.

Association of anthropometric parameters as a risk factor for development of diabetic retinopathy in patients with diabetes mellitus

OBJECTIVE

To study the relationship of body fat distribution in patients with diabetes mellitus (DM), and its long-term complications like diabetic retinopathy (DR), in Indian population.

METHODS

This was a prospective, cross-sectional observational study involving 1773 subjects diagnosed with DM and 1778 age and gender-matched individuals. The patients with DM were assessed for the presence and severity of DR. Severe non-proliferative DR and proliferative DR were categorised as sight threatening DR (STDR). Anthropometric parameters, i.e., neck circumference (NC); mid-upper arm circumference (MAC); waist circumference (WC); hip circumference (HC); mid-thigh circumference (MTC) and body mass index (BMI) were measured using standardised technique.

RESULTS

The mean age was 59.33 ± 9.32 for DM group, and 66.03 ± 11.04 for non-DM group. DM group showed significantly greater NC, WC, and MTC and significantly reduced MAC and weight. HC and BMI were comparable between the groups. There was a significant positive correlation of MAC and WC (with any level of DR) and MAC, WC, and weight (for STDR); and a significant negative correlation of HC and MTC (with any level of DR) and NC, HC, MTC, and BMI (for STDR). Multiple logistic regression analysis confirmed that WC was the single most important predictor for any level of DR and STDR.

CONCLUSIONS

Association of body fat distribution with DM and DR appears multifactorial. However, central obesity signified by waist circumference appears to be the significant risk related to the development of DR and STDR in Indian population.

Cardiovascular complications in a diabetes prediction model using machine learning: a systematic review

Prediction model has been the focus of studies since the last century in the diagnosis and prognosis of various diseases. With the advancement in computational technology, machine learning (ML) has become the widely used tool to develop a prediction model. This review is to investigate the current development of prediction model for the risk of cardiovascular disease (CVD) among type 2 diabetes (T2DM) patients using machine learning. A systematic search on Scopus and Web of Science (WoS) was conducted to look for relevant articles based on the research question. The risk of bias (ROB) for all articles were assessed based on the Prediction model Risk of Bias Assessment Tool (PROBAST) statement. Neural network with 76.6% precision, 88.06% sensitivity, and area under the curve (AUC) of 0.91 was found to be the most reliable algorithm in developing prediction model for cardiovascular disease among type 2 diabetes patients. The overall concern of applicability of all included studies is low. While two out of 10 studies were shown to have high ROB, another studies ROB are unknown due to the lack of information. The adherence to reporting standards was conducted based on the Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) standard where the overall score is 53.75%. It is highly recommended that future model development should adhere to the PROBAST and TRIPOD assessment to reduce the risk of bias and ensure its applicability in clinical settings. Potential lipid peroxidation marker is also recommended in future cardiovascular disease prediction model to improve overall model applicability.

The prevalence, awareness, management and influencing factors of diabetes in middle-aged and elderly in China, evidence from the CHARLS in 2015

Diabetes seriously affects the health of middle-aged and elderly. What we can do is to suppress the progression and avoid complications of diabetes. The aim of this study was to evaluate the prevalence, management and influencing factors in middle-aged and elderly diabetics. The data used in our study came from the follow-up survey (2015) of China Health and Retirement Longitudinal Study. After all the questionnaire data of participants was acquired, the first screening step was conducted and the participants without blood glucose or glycosylated hemoglobin test results were excluded. In the second screening step, participants without self-reported diabetes, age <45 were excluded. After data screening, STATA 16.0 software (StataCorp, USA) was used to conduct statistical analysis. Multiple logistics regression was used to analyze the influencing factors of diabetes in middle-aged and elderly. After data screening, A total of 9738 participants were enrolled in the survey of the China Health and Retirement Longitudinal Study in 2015, including diabetes 1965 and control 7773. The prevalence of diabetes in age >60 (22.20%) was significantly higher than that in age 45 to 60 (16.60%). Age, residence, physical activity, drinking, smoking and body mass index were key influencing factors according to the results of logistics regression. 46.92% diabetics were diagnosed in hospital, 22.14% were diagnosed by community medical care. 1298 among 1965 diabetes patients had standardized medication to control blood glucose, the rate was only 66.01%. The awareness rate of diabetes was only 28.75%, and the monitoring, treatment and accepting medical advice rates were 68.32%, 66.01% and 56.99% separately. The follow-up rate of diabetes was only 14.16%. Diabetes is widely prevalent in the middle-aged and elderly with the prevalence of 16.60% in the participants with age 45 to 60. The rate of self-rated diabetics underestimated the true prevalence of diabetes. Age, residence, physical activity, drinking, smoking and body mass index are key influencing factors to diabetes. Although a national diabetes health management model has been established, the awareness of diabetes was only 28.75%. Standardized diabetes registration and regular follow up should also be strictly implemented.

Identification of the Optimal Model for the Prediction of Diabetic Retinopathy in Chinese Rural Population: Handan Eye Study

Background

To identify an optimal model for diabetic retinopathy (DR) prediction in Chinese rural population by establishing and comparing different algorithms based on the data from Handan Eye Study (HES).

Methods

Five algorithms, including multivariable logistic regression (MLR), classification and regression trees (C&RT), support vector machine (SVM), random forests (RF), and gradient boosting machine (GBM), were used to establish DR prediction models with HES data. The performance of the models was assessed based on the adjusted area under the ROC curve (AUROC), sensitivity, specificity, and accuracy.

Results

The data on 4752 subjects were used to build the DR prediction model, and among them, 198 patients were diagnosed with DR. The age of the included subjects ranged from 30 to 85 years old, with an average age of 50.9 years (SD = 3.04). The kappa coefficient of the diagnosis between the two ophthalmologists was 0.857. The MLR model revealed that blood glucose, systolic blood pressure, and body mass index were independently associated with the development of DR. The AUROC obtained by GBM (0.952), RF (0.949), and MLR (0.936) was similar and statistically larger than that of CART (0.682) and SVM (0.765).

Conclusions

The MLR model exhibited excellent prediction performance and visible equation and thus was the optimal model for DR prediction. Therefore, the MLR model may have the potential to serve as a complementary screening tool for the early detection of DR, especially in remote and underserved areas.

Gastric bypass versus best medical treatment for diabetic kidney disease: 5 years follow up of a single-centre open label randomised controlled trial

BACKGROUND

We compared the albuminuria-lowering effects of Roux-en-Y gastric bypass (RYGB) to best medical treatment in patients with diabetic kidney disease and obesity to determine which treatment is better.

METHODS

A 5 year, open-label, single-centre, randomised trial studied patients with diabetic kidney disease and class I obesity after 1:1 randomization to best medical treatment (n = 49) or RYGB (n = 51). The primary outcome was the proportion of patients achieving remission of microalbuminuria after 5 years. Secondary outcomes included improvements in diabetic kidney disease, glycemic control, quality of life, and safety. For efficacy outcomes, we performed an intention-to-treat (ITT) analysis. This study was registered with ClinicalTrials.gov, NCT01821508.

FINDINGS

88% of patients (44 per arm) completed 5-year follow-up. Remission of albuminuria occurred in 59.6% (95% CI = 45.5-73.8) after best medical treatment and 69.7% (95% CI = 59.6-79.8) after RYGB (risk difference: 10%, 95% CI, -7 to 27, P = 0.25). Patients after RYGB were twice as likely to achieve an HbA1c ≤ 6.5% (60.2% versus 25.4%, risk difference, 34.9%; 95% CI = 15.8-53.9, P < 0.001). Quality of life after five years measured by the 36-Item Short Form Survey questionnaire (standardized to a 0-to-100 scale) was higher in the RYGB group than in the best medical treatment group for several domains. The mean differences were 13.5 (95% CI, 5.5-21.6, P = 0.001) for general health, 19.7 (95% CI, 9.1-30.3, P < 0.001) for pain, 6.1 (95% CI, -4.8 to 17.0, P = 0.27) for social functioning, 8.3 (95% CI, 0.23 to 16.3, P = 0.04) for emotional well-being, 12.2 (95% CI, 3.9-20.4, P = 0.004) for vitality, 16.8 (95% CI, -0.75 to 34.4, P = 0.06) for mental health, 21.8 (95% CI, 4.8-38.7, P = 0.01) for physical health and 11.1 (95% CI, 2.24-19.9, P = 0.01) for physical functioning. Serious adverse events were experienced in 7/46 (15.2%) after best medical treatment and 11/46 patients (24%) after RYGB (P = 0.80).

INTERPRETATION

Albuminuria remission was not statistically different between best medical treatment and RYGB after 5 years in participants with diabetic kidney disease and class 1 obesity, with 6-7 in ten patients achieving remission of microalbuminuria (uACR <30 mg/g) in both groups. RYGB was superior in improving glycemia, diastolic blood pressure, lipids, body weight, and quality of life.

FUNDING

The study was supported by research grants from Johnson & Johnson Brasil, Oswaldo Cruz German Hospital, and by grant 12/YI/B2480 from Science Foundation Ireland (Dr le Roux) and grant 2015-02733 from the Swedish Medical Research Council (Dr le Roux). Dr Pereira was funded by the Chevening Scholarship Programme (Foreign and Commonwealth Office, UK).

ExPRSweb: An online repository with polygenic risk scores for common health-related exposures

Complex traits are influenced by genetic risk factors, lifestyle, and environmental variables, so-called exposures. Some exposures, e.g., smoking or lipid levels, have common genetic modifiers identified in genome-wide association studies. Because measurements are often unfeasible, exposure polygenic risk scores (ExPRSs) offer an alternative to study the influence of exposures on various phenotypes. Here, we collected publicly available summary statistics for 28 exposures and applied four common PRS methods to generate ExPRSs in two large biobanks: the Michigan Genomics Initiative and the UK Biobank. We established ExPRSs for 27 exposures and demonstrated their applicability in phenome-wide association studies and as predictors for common chronic conditions. Especially the addition of multiple ExPRSs showed, for several chronic conditions, an improvement compared to prediction models that only included traditional, disease-focused PRSs. To facilitate follow-up studies, we share all ExPRS constructs and generated results via an online repository called ExPRSweb.

Interaction analysis of lipid accumulation product and family history of diabetes on impaired fasting glucose and diabetes risk in population with normotension in Eastern China: a community-based cross-sectional survey

BACKGROUND

Lipid accumulation product (LAP) is considered to be a new convenient useful indicator to assess the visceral fat. Therefore, we aimed to evaluate the risk factors of impaired fasting glucose (IFG) and diabetes, and explore the possible interacting influences of LAP with other factors on the risk of IFG and diabetes among Chinese normotension adults.

METHODS

A multistage stratified cluster sampling method was conducted to select urban residents in Bengbu, China. For each eligible participant, data on questionnaire survey, anthropometric measurements and laboratory tests were obtained. The effects of body mass index (BMI), waist circumference (WC), waist to height ratio (WHtR) and LAP for predicting IFG and diabetes were performed by multiple logistic regressions and receiver operating characteristic (ROC) analyses. The interaction effects were evaluated by relative excess risk of interaction (RERI), attributable proportion due to interaction (AP) and synergy index (SI).

RESULTS

Six thousand, four hundred sixty-seven normotension subjects (2695 men and 3772 women) were enrolled in our study, the prevalence of IFG and diabetes were 9.37% and 14.33%, respectively. When assessed using ROC curve analysis, LAP exhibited higher diagnostic accuracy for identifying IFG and diabetes than BMI, the area under the AUC curve was 0.650 (95% CI: 0.637 to 0.662). After adjustment for age, sex, educational level and other confounding factors, multivariate logistic regression analyses indicated that subjects with the fourth quartile of LAP were more likely to develop IFG (adjusted OR: 2.735, 95% CI: 1.794-4.170) and diabetes (adjusted OR: 1.815, 95% CI: 1.297-2.541) than those with the first quartile. A significant interaction between LAP and family history of diabetes was observed in participants (RERI = 1.538, 95%CI: 0.167 to 3.612; AP = 0.375, 95%CI: 0.118 to 0.631; SI = 1.980, 95%CI: 1.206 to 3.251). However, a significant interaction between LAP and abdominal obesity was indicated by the value of RERI (1.492, 95%CI: 0.087 to 3.723) and AP (0.413, 95%CI: 0.014 to 0.756), but not the value of SI (1.824, 95%CI: 0.873 to 3.526).

CONCLUSION

Our results demonstrated that there might be synergistic effect between LAP and family history of diabetes on the risk of IFG and diabetes.

Effect of lactic acid fermented foods on glycemic control in diabetic adults: a systemic review and meta-analysis of randomized controlled trials

Lactic acid bacteria (LAB) fermented foods are reported to have potential in managing glycemic control. This systematic review aimed to evaluate the effectiveness of LAB-fermented foods on improving glycemic control in adults with prediabetics or type 2 diabetes mellitus (T2DM). Randomized controlled trials (RCTs) on LAB fermentation-related foods were searched on PubMed, Cochrane, Excerpta Medica database (EMBASE), Cumulative Index to Nursing and Allied Health Literature (CINAHL), and Web of Science. Sixteen RCTs were included, and the results concluded LAB-fermented food had significant effects in HbA1c (Z = 6.24, MD = -0.05, CI: -0.07 to -0.04, p ≤ 0.00001), fasting plasma glucose (Z = 2.50, MD = -0.16, CI: -0.29 to -0.04, p = 0.01) and fasting serum insulin (Z = 2.51, MD = -0.20, CI: -0.35 to -0.04, p = 0.01). There were significant effects on lipid profile, inflammatory markers, and body mass index in secondary analyses. Subgroup analysis suggests LAB-fermented consumption with a longer duration, younger age group and adults with T2DM, had a larger effect size. Clinicians could offer LAB-fermented food as dietary recommendations for prediabetic and diabetic adults. Larger trials are warranted to verify LAB-fermented food benefits on glycemic control. Systematic Review Registration: PROSPERO Registration No. CRD42022295220.

Association of Personality Traits with Life and Work of Medical Students: An Integrative Review

BACKGROUND

Personality traits are the basic components of an individual's personality. Although there are many published articles about the impact of personality traits on medical students, there is a lack of integrative reviews of existing articles. To close this gap, this review aims to summarize the impact of personality traits on medical students from two perspectives: life and work.

METHODS

The search was performed using the following databases: PubMed, Web of Science, Google Scholar, and EMBASE. All publications that assessed the impact of personality traits on life and work until February 2022 were selected.

RESULTS

Ninety-seven studies were included. The results suggest that personality traits could affect life performance, health outcomes, life satisfaction, the formation of doctor-patient relationships, mastery of knowledge, academic performance, and career planning. Different personality traits can have positive or negative impacts on these aspects.

CONCLUSIONS

The results of this review suggest that personality traits can affect medical students' lives and work. Therefore, based on the evaluation of the personality traits of medical students, it is necessary to design targeted courses and training for students to improve their personality traits, to bring about better results in their lives and work.

Elevated gamma-glutamyl transferase to high-density lipoprotein cholesterol ratio has a non-linear association with incident diabetes mellitus: A second analysis of a cohort study

OBJECTIVE

Evidence regarding the association between the GGT/HDL-c ratio and incident diabetes is still limited. On that account, our research aims to survey the link of the GGT/HDL-c ratio with the risk of diabetes.

METHODS

In this retrospective cohort study, data of 15,171 participants who participated in the medical examination program were collected in Murakami Memorial Hospital in Japan from 2004 to 2015. The independent and dependent variables were the baseline GGT/HDL-c ratio and diabetes during the follow-up, respectively. The Cox proportional-hazards regression model was used to explore the association between the GGT/HDL-c ratio and diabetes risk. A Cox proportional hazards regression with the cubic spline smoothing was used to recognize non-linear relationships between the GGT/HDL-c ratio and incident diabetes.

RESULTS

After adjusting covariates, the results showed that the GGT/HDL-c ratio was positively associated with incident diabetes (HR = 1.013, 95% CI: 1.002, 1.024). There was also a non-linear relationship between the GGT/HDL-c ratio and the risk of diabetes, and the inflection point of the GGT/HDL-c ratio was 6.477. The HR on the left and right sides of the inflection point was 2.568 (1.157, 5.699) and 1.012 (1.001, 1.023), respectively. The sensitivity analysis demonstrated the robustness of the results. Besides, the performance of the FPG + GGT/HDL-c ratio was better than FPG + GGT, FPG + HDL-c, and FPG in predicting diabetes.

CONCLUSION

This study demonstrates a positive and non-linear relationship between the GGT/HDL-c ratio and incident diabetes in the Japanese population. The GGT/HDL-c ratio is strongly related to diabetes risk when it is <6.477.

Is predicted body-composition and relative fat mass an alternative to body-mass index and waist circumference for disease risk estimation?

BACKGROUND AND AIMS

New methods to estimate body-composition have recently been proposed, but their relation to diseases, such as diabetes and coronary heart disease, needs further investigation. The purpose of this study was to investigate the association between proposed prediction of body-composition (PBC); Relative Fat Mass (RFM), Body Mass Index (BMI), Waist Circumference (WC) and disease.

METHODS

In a cross-sectional cohort (NHANES) the association between the four body measures and diabetes, high blood pressure, coronary heart disease, cancer, arthritis, and hospitalization were assessed. A total of 13,348 people was included in this study. Receiver operating characteristic (ROC), Area Under Curve (AUC) and statistical testing were used to evaluate the differences.

RESULTS

PBC/RFM had significant higher AUC than BMI or WC for diabetes, high blood pressure, hospitalization, and arthritis. PBC had a significant higher AUC than RFM, BMI, WC for Cancer and coronary heart disease.

CONCLUSIONS

RFM and PBC could be a better indicator to distinguish amongst people with a risk of diseases compared to traditional measures such as BMI and WC. However, future studies need to investigate the longitudinal association between RFM, PBC and the risk of disease development to assess if these measures are better suited for risk-stratification.