Diabetes Prevention Research Articles

Camp-style lifestyle modification program (CAMP) for diabetes prevention among rural women with prior GDM: study protocol for a three-arm cluster hybrid type 2 randomized controlled trial

BackgroundIntensive lifestyle interventions were effective to reduce the risk of type 2 diabetes mellitus (T2DM) for women with gestational diabetes mellitus (GDM) history. However, reaching these mothers and maintaining participation in lifestyle interventions is suboptimal in real-world settings. Effective, feasible and sustainable new lifestyle interventions are needed. The objectives of this three-arm trial are to (1) compare diabetes risk outcomes of an evidence-based intensive lifestyle modification (ILSM) intervention, a camp-style lifestyle modification program (CAMP) intervention, and usual care among women with GDM history; and (2) evaluate the comparative efficacy of the CAMP versus ILSM intervention on implementation outcomes.MethodsA three-arm cluster randomized clinical trial (RCT) using a hybrid type 2 implementation design will be conducted in two counties in Hunan province in China. Six towns from each county will be randomly selected and assigned to CAMP, ILSM, and the usual care group (25 women from each of 12 towns, 100 women in each arm). The ILSM includes six biweekly in-person sessions and 3-month telephone health consultations, while the CAMP consists of a 2-day camp-based session and 3-month health consultations via a popular social media platform. Both interventions share the same session content, including six lifestyle skills. Efficacy (T2DM risk score and behavioral, anthropometric, psychosocial, and glycemic variables) and implementation outcomes (recruitment, acceptability, feasibility, fidelity, and cost-effectiveness) will be collected at baseline, 6-month, and 12-month. Pre-planned ANOVA F-test and generalized estimating equations will be included to test time-by-arm interactions.DiscussionThe CAMP intervention is expected to have better reach, better attendance, and comparable effectiveness in reducing the risk of T2DM, thus improving postpartum care for GDM in China. The delivery of a concentrated format supplemented with technology-based support may provide an efficient and effective delivery model for implementing maternal health promotion programs in primary care settings.Trial registrationRegistered in the Chinese Clinical Trial Registry (ChiCTR2200058150) on 31st March 2022.

Health disparities and inequalities in prevalence of diabetes in the Kingdom of Saudi Arabia

BackgroundOver time, global health systems have witnessed significant improvements in the delivery and coverage of healthcare services. Nevertheless, the increasing prominence of non-communicable diseases remains a persistent challenge. Diabetes is one such non-communicable chronic disease that poses a threat with respect to both mortality and morbidity. This study investigated the socio-economic determinants and inequalities in the prevalence of diabetes in the Kingdom of Saudi Arabia according to data collected from the 2018 Saudi Family Health Survey conducted by the General Authority for Statistics.MethodsThe analysis was limited to a sample of 11,528 respondents aged ≥ 18 years, selected across all 13 regions of Saudi Arabia, with complete responses for all variables of interest. Socio-economic determinants in diabetes prevalence were explored with univariate, bivariate, and multivariate logistic regression analyses. Furthermore, inequalities were visualised and quantitatively estimated according to construction of a concentration curve and calculation of the concentration index.ResultsThe prevalence of diabetes among the 11,528 respondents was 11.20%. Age, education, income, and residence area were significant determinants of diabetes prevalence, with a greater risk of diabetes found in older participants (odds ratio [OR]: 12.262, 95% confidence interval [CI]: 9.820–15.313, p < 0.01) compared to younger participants. Inequality analysis showed a negative education-based concentration index (–0.235, p < 0.01), indicating that diabetes prevalence is concentrated among people with relatively less formal education. For males, the income-based concentration index was significantly positive, whereas the education-based concentration index was significantly negative, indicating a greater concentration of diabetes among Saudi men with higher incomes and less education.ConclusionThese findings emphasize the need to prioritize policies and strategies for diabetes prevention and control with considerations of the socio-economic inequalities in prevalence. Key areas of focus should include improving education levels across all regions, raising awareness about diabetes and implementing nutritional interventions.

Longitudinal associations between microRNAs and weight in the diabetes prevention program.

Circulating microRNAs show cross-sectional associations with overweight and obesity. Few studies provided data to differentiate between a snapshot perspective on these associations versus how microRNAs characterize prodromal risk from disease pathology and complications. This study assessed longitudinal relationships between circulating microRNAs and weight at multiple time-points in the Diabetes Prevention Program trial. A subset of participants (n=150) from the Diabetes Prevention Program were included. MicroRNAs were measured from banked plasma using a Fireplex Assay. We used generalized linear mixed models to evaluate relationships between microRNAs and changes in weight at baseline, year-1, and year-2. Logistic regression was used to evaluate whether microRNAs at baseline were associated with weight change after 2 years. In fully adjusted models that included relevant covariates, seven miRs (i.e., miR-126, miR-15a, miR-192, miR-23a, and miR-27a) were statistically associated with weight over 2 years. MiR-197 and miR-320a remained significant after adjustment for multiple comparisons. Baseline levels of let-7f, miR-17, and miR-320c were significantly associated with 3% weight loss after 2 years in fully adjusted models. This study provided evidence for longitudinal relationships between circulating microRNAs and weight. Because microRNAs characterize the combined effects of genetic determinants and responses to behavioral determinants, they may provide insights about the etiology of overweight and obesity in the context or risk for common, complex diseases. Additional studies are needed to validate the potential genes and biological pathways that might be targeted by these microRNA biomarkers and have mechanistic implications for weight loss and disease prevention.

Diabetes Related Knowledge, Attitude and Practice among Diabetic Patients Attending at Chittagong Medical College Hospital

Background: Increased awareness among large population groups is a major determinant for the prevention of diabetes and its complications. Knowledge and attitude are the principal markers of awareness that need to be studied in various population groups in specific racial and cultural contexts. Therefore, good Knowledge, Attitude and Practices (KAP) regarding diabetes are necessary in promoting care. This study aimed to explore Knowledge, Attitude and Practices (KAP)-regarding Diabetes Mellitus (DM) among diabetic patients attending in Chittagong Medical College Hospital. Materials and methods: This cross-sectional study was conducted from January 2022 to December 2022 among 289 diabetic patients from the outpatient department of Chittagong Medical College Hospital, Chattogram. KAP were assessed by a pre-structured, interviewer-administered questionnaire and categorized using predefined scores of poor (&lt;&lt; 30%), average (30-70%) and good (70%). Chi-square test was done to examine the association between diabetes related KAP and other covariates. Results: Out of 289 participants 167(57.8%) of the participants had good knowledge, 208 (72%) had positive attitude and 173 (60%) had good practice related to DM. Poor knowledge was significantly associated with female gender (p=0.010), being housewife (p=0.023) and low socioeconomic status (p &lt;0.001). Conclusion: Present study identified some gap in KAP related to DM and some factors related to poor knowledge, negative attitude and poor practices among the diabetic patients, which highlighted the need of more comprehensive approach for DM related management in the study hospital. IAHS Medical Journal Vol 6(2), December 2023; 44-47

The challenges and lessons from a formative process and value-based evaluation of the wave 1 roll-out of the all Wales Diabetes Prevention Programme

BackgroundThe All Wales Diabetes Prevention Programme (AWDPP) is a Wales wide, public health initiative designed to systematically identify adults at risk of developing type 2 diabetes and offer a 30-minute person-centred lifestyle conversation focused on diet and physical activity. An independent formative process and value-based evaluation was commissioned to examine the implementation of this programme in 14 primary care cluster areas across Wales during the initial roll-out.MethodsThis evaluation was undertaken to ascertain the views on early implementation of the programme from service users, health care professionals and key stakeholders. The evaluation was informed by the Medical Research Council Framework for Process Evaluation and Wales Prudent Healthcare principles. As part of the value-based assessment, a preliminary cost-consequence analysis was conducted to understand the short-term economic impact of the implementation of the programme.ResultsService users who took part in the evaluation highly valued the programme and nearly half had been previously unaware that they were at risk of developing type 2 diabetes. Delivering the programme presented challenges but there was significant enthusiasm and support from all stakeholders. Overall, the programme was being delivered as intended albeit with evidence of some variation in the application of the programme eligibility criteria.ConclusionsIn Wave 1 of the AWDPP roll-out, the intent to deliver the programme in line with Prudent Healthcare was successful and promising in terms of demonstrating value. Opinions expressed by service users suggest the AWDPP matters to them; raising awareness, promoting knowledge and capacity to change behaviours and motivate and raise confidence.

Objective Analysis of Traditional Chinese Medicine Syndrome Differentiation of Patients With Diabetes and Prediabetes: Protocol for a Nonrandomized, Exploratory, Observational Case-Control Study Using Digitalized Traditional Chinese Medicine Diagnostic Tools.

Diabetes and prediabetes are diagnosed differentially by Western and Chinese medicine. While Western medicine uses objective laboratory analysis of biochemical parameters to define the severity of diabetes and prediabetes, Chinese medicine uses a comprehensive approach that integrates observation, inquiry, pulse palpation, and tongue diagnosis. The medical information collected is then categorized into different syndromes. However, traditional methods of pulse and tongue diagnoses used to determine syndrome differentiation are highly subjective and skill dependent. This study aims to identify the gap in conventional traditional Chinese medicine (TCM) diagnostic techniques for syndrome differentiation analysis using contemporary diagnostic devices. We devised a protocol for a nonrandomized, exploratory, observational case-control study with equal allocations in 5 arms to investigate the syndrome differentiation of diabetes and prediabetes. We hypothesize that the TCM syndrome differentiation of diabetes and prediabetes in the tropical climate may differ from that defined based on the Chinese demographic. We also speculate that the high-frequency spectral energy may reflect a difference in pulse wave intensity and density between the healthy and diabetes groups. A total of 250 eligible participants will be equally assigned to 1 of 5 arms (healthy or subhealthy, prediabetes, diabetes, prediabetes with hypertension and dyslipidemia, and diabetes with hypertension and dyslipidemia). Participants aged 21-75 years, of any sex or race, and have been diagnosed with diabetes (fasting plasma glucose [FPG] of 7 mmol/L, or 2-hour plasma glucose [2hPG] of 11.1 mmol/L) or prediabetes (impaired FPG of 6.1-6.9 mmol/L, or impaired glucose tolerance with an 2hPG of 7.8-11 mmol/L) will be included. The Health Evaluation Questionnaire, Physical Activity Questionnaire, sugar intake assessment, Constitution in Chinese Medicine Questionnaire, radial pulse diagnosis, and tongue diagnosis will be performed in a single visit. ANOVA for continuous data and chi-square tests of independence will be used for categorical data assessments, with a level of P<.05 considered significant. The recruitment is in progress. We anticipate that the study will conclude in June 2025. As of July 15, 2024, we have enrolled 140 individuals. To the best of our knowledge, this is the first study to use contemporary TCM diagnostic instruments to map expert and empirical knowledge of TCM to its scientific equivalents for the purpose of evaluating the syndrome differentiation of diabetes. We designed this protocol with the exploratory goal to examine objectively the syndrome differentiation of patients with diabetes and those with prediabetes using TCM diagnostic technologies. The data collected and evaluated under standardized conditions using these contemporary diagnostic devices will exhibit a higher degree of stability, hence yielding dependable and unbiased results for syndrome differentiation. Thus, our findings may potentially increase the accuracy of identification, diagnosis, treatment, and prevention of diabetes and prediabetes through a system of targeted treatment. ClinicalTrials.gov NCT05563090; https://clinicaltrials.gov/ct2/show/NCT05563090. DERR1-10.2196/56024.

Myoinositol and Metformin in the Prevention of Gestational Diabetes in High-Risk Patients: A Narrative Review.

Our hypothesis is that myoinositol and metformin in pregnant women with high-risk factors for glucose intolerance would reduce insulin resistance and consequently lower the incidence of gestational diabetes mellitus (GDM), a metabolic disorder of pregnancy characterized by maternal hyperglycemia due to deficient response to physiological insulin resistance, which may have a negative impact on perinatal outcome and long-term sequelae. In recent years, this pathology has become increasingly important given the global obesity epidemic and the delay in becoming pregnant, especially in industrialized countries. For this reason, the attempt to prevent, rather than cure, gestational diabetes is particularly important. In addition to lifestyle changes (especially diet and doing more exercise), myoinositol and metformin are the most promising factors at the moment, although not all RCTs published so far agree on their real effectiveness. A review of the articles published so far allows us to assume, albeit with some distinctions, that they can play a positive role.

Testosterone and the prevention of type 2 diabetes mellitus: therapeutic implications from recent trials.

Type 2 diabetes (T2D) is increasing to epidemic proportions and frequently associated with obesity and a low serum testosterone concentration in men. This review valuates recent randomized controlled trials (RCTs) investigating the effect of testosterone treatment on glycemic control and T2D prevention. The 2-year Testosterone for the Prevention of Type 2 diabetes Trial (T4DM) study showed that in men aged 50 years and over with visceral obesity and impaired glucose tolerance, testosterone treatment on the background of a lifestyle intervention reduced T2D risk by 40%. The Testosterone Effects on Atherosclerosis Progression in Aging Men and Testosterone Trials demonstrated modest improvements in insulin sensitivity and body composition. However, the Testosterone Replacement Therapy for Assessment of Long-Term Vascular Events and Efficacy Response in Hypogonadal Men trial found no significant glycemic benefits over 2 years. Recent data from the Diabetes Prevention Program Outcome Study support the cost efficacy and durability of metformin. In men at high risk of T2D, treatment with testosterone prevents the disease; however, there are caveats to its use and other approaches may be more applicable. Differences in trial designs, age groups, and outcome measures contribute to varying results. HbA1C is a suboptimal outcome measure. Future research should explore potential synergies between testosterone and GLP-1 receptor agonists in T2D management, while considering cost-effectiveness.

Glucose metabolism and smaller hippocampal volume in elderly people with normal cognitive function

We investigated associations of glycemic measures, and insulin resistance and secretion measures with hippocampal and subfield volumes. In this cross-sectional study, 7400 community-dwelling participants underwent brain MRI and health checkups between 2016 and 2018. Hemoglobin A1c (HbA1c), glycated albumin (GA), homeostasis model assessment for insulin resistance (HOMA-IR), and HOMA of percent β-cell function (HOMA-β) were evaluated. The associations of each measure with a smaller volume of the hippocampus and twelve hippocampal subfields were investigated. As a result, higher HbA1c or GA and lower HOMA-β levels were significantly associated with smaller volumes in multiple hippocampal subfields. Furthermore, even when we analyzed non-diabetic individuals, substantial associations remained between higher GA or lower HOMA-β levels and smaller volumes of the whole hippocampus or the fimbria. Our findings indicate that postprandial glucose fluctuations, postprandial hyperglycemia, and low insulin secretion have a specific effect on the development of smaller hippocampal volume, suggesting that primary prevention of diabetes and/or sufficient glucose control are important for the prevention of dementia.

Gestational diabetes knowledge improves with interactive online training modules

BackgroundThe risk of developing type 2 diabetes mellitus (T2DM) is up to 50% among women with gestational diabetes mellitus (GDM). However, diabetes education during and after pregnancy is limited. To bridge this gap, our team developed four training modules on GDM for nurses and community health workers. This pilot study assesses changes in knowledge, self-efficacy for providing diabetes education, attitudes, and intentions to recommend diabetes prevention before and after training completion.MethodsInteractive online modules were disseminated to clinical staff providing care for women with GDM in the United States. Optional pre- and post-training surveys were conducted to gauge the effectiveness of the modules. GDM knowledge (scoring 0–100) was evaluated with a 23 question assessment with total score and individual module scores reported [(# correct/# total)*100]. Self-efficacy for providing diabetes education (scoring 1–10) was evaluated with a 15-question survey and intention to recommend diabetes prevention (scoring 1–5) was assessed with an 8-item survey. Attitudes were assessed with three subscales of the Diabetes Attitude Scale (scoring 1–5). Changes in scores on each scale before and after training are reported using non-parametric Wilcoxon matched-pair signed rank tests.ResultsEighty-two individuals completed baseline evaluation and 20 individuals accessed all modules and completed post-training assessments. Among those completing the training, improvement was noted in GDM knowledge [56.5 (16.0) v. 78.3 (22.0), p < 0.001], self-efficacy for providing diabetes education [6.60 (2.73) v. 9.33 (0.87), p < 0.001], attitudes toward the value of tight control [4.07 (0.79) v. 4.43 (0.86), p = 0.003], and intentions to recommend diabetes prevention measures [4.81 (0.63) v. 5.00 (0.00), p = 0.009)].ConclusionsCompletion of our interactive online modules improved knowledge, intention to recommend diabetes prevention, self-efficacy to provide diabetes education, and attitudes toward the value of tight control among individuals caring for women with GDM.Trial registrationThis study was registered at clinicaltrials.gov, identifier: NCT04474795.

The Impact of Public Health on Disease Prevention

Public health plays an important role in preventing diseases by supporting measures that prioritise the well-being of entire populations over individuals. This study investigates the history of public health, the approaches used in illness prevention, and the difficulties encountered in executing these tactics. Public health strategies, such as immunisation programs and lifestyle modifications, are critical in combating communicable and non-communicable diseases. Case studies like the Diabetes Prevention Program and REACH U.S. demonstrate the effectiveness of public health efforts. The paper also discusses current difficulties, such as limited resources, misinformation, and increasing dangers, as well as possible future strategies for improving public health systems through innovation, research, and community participation. Keywords: Public Health, Disease Prevention, Vaccination, Health Promotion, Preventive Healthcare.

Diabetes Prevention Strategies in Ghana: Opportunities for Community-Based Interventions

Diabetes was emerging as a critical public health challenge in Ghana, driven by rapid urbanization, lifestyle changes, and increasing rates of obesity. This article reviewed the growing prevalence of diabetes in Ghana, particularly type 2 diabetes, and highlighted the urgent need for effective prevention strategies. It also examined the epidemiological trends, identified key risk factors such as obesity, physical inactivity, and unhealthy diets, and discussed the role of genetic predisposition in the rising diabetes rates. The article explored various models of community-based interventions, including the Community Mobilization Model, Ecological Model, Social Marketing Model, Health Belief Model, and Participatory Action Research, as promising approaches to diabetes prevention in Ghana. These models leveraged local knowledge, cultural practices, and community structures to promote healthier lifestyles, increase awareness, and facilitate early detection. The article also identified challenges such as inadequate funding, healthcare infrastructure disparities, and cultural barriers that hinder the implementation of prevention programs. However, it highlighted opportunities for leveraging mobile health technologies, public-private partnerships, and the integration of diabetes prevention with existing health services. The methodology used involved a comprehensive review of relevant literature and case studies from other low- and middle-income countries to identify effective community-based strategies for diabetes prevention. The article concluded with recommendations for scaling up community-based interventions to reduce the incidence of diabetes and improve public health outcomes in Ghana. Keywords: Diabetes Prevention, Community-Based Interventions Ghana, Risk Factors, Health

Covariate-constrained randomization in cluster randomized 2 × 2 factorial trials: application to a diabetes prevention study

BackgroundCluster randomized trials (CRTs) are randomized trials where randomization takes place at an administrative level (e.g., hospitals, clinics, or schools) rather than at the individual level. When the number of available clusters is small, researchers may not be able to rely on simple randomization to achieve balance on cluster-level covariates across treatment conditions. If these cluster-level covariates are predictive of the outcome, covariate imbalance may distort treatment effects, threaten internal validity, lead to a loss of power, and increase the variability of treatment effects. Covariate-constrained randomization (CR) is a randomization strategy designed to reduce the risk of imbalance in cluster-level covariates when performing a CRT. Existing methods for CR have been developed and evaluated for two- and multi-arm CRTs but not for factorial CRTs.MethodsMotivated by the BEGIN study—a CRT for weight loss among patients with pre-diabetes—we develop methods for performing CR in 2 × 2 factorial cluster randomized trials with a continuous outcome and continuous cluster-level covariates. We apply our methods to the BEGIN study and use simulation to assess the performance of CR versus simple randomization for estimating treatment effects by varying the number of clusters, the degree to which clusters are associated with the outcome, the distribution of cluster level covariates, the size of the constrained randomization space, and analysis strategies.ResultsCompared to simple randomization of clusters, CR in the factorial setting is effective at achieving balance across cluster-level covariates between treatment conditions and provides more precise inferences. When cluster-level covariates are included in the analyses model, CR also results in greater power to detect treatment effects, but power is low compared to unadjusted analyses when the number of clusters is small.ConclusionsCR should be used instead of simple randomization when performing factorial CRTs to avoid highly imbalanced designs and to obtain more precise inferences. Except when there are a small number of clusters, cluster-level covariates should be included in the analysis model to increase power and maintain coverage and type 1 error rates at their nominal levels.

In Vitro Alpha-Glucosidase Inhibitory Effect of Etlingera Elatior Ethanol Extract Growing in Gayo Highland, Aceh Province, Indonesia.

The prevalence of diabetes mellitus (DM) is increasing overtime, potentially leading to various severe health complications and mortality. Despite therapeutic agents have currently been developed, unexpected adverse effects are inevitable. Hence, safe and effective medications such as those of plant origin are critical to prevent unexpected complication in DM sufferers. Etlingera elatior has been widely used as spice and traditional medicine to treat diabetes in Aceh Province, Indonesia. However, study regarding α-glucosidase inhibitory effect of E. elatior growing in Gayo highlands, Aceh, Indonesia, is completely lacking. The aim of this study was to evaluate in vitro α-glucosidase inhibitory effect of E. elatior ethanol extracts (EEEE) growing in Gayo highlands, Aceh Province, Indonesia. Antioxidant activity was determined using DPPH procedure, whereas α-glucosidase inhibition assay was carried out using spectrophotometric method. Data analysis was performed using One-Way Analysis of Variance (ANOVA), followed by Duncan's multiple range test at α=0.05. Phytochemical analysis revealed the presence of total phenolic (TPC), total flavonoid (TFC), and total tannin (TTC) content in all E. elatior plant parts, in which the highest TPC was found in the stem (158.38 GAE/g), whereas the highest TFC and TTC was obtained in the rhizome extracts. The extract of fruit showed the strongest antioxidant activities, followed by the stem and leaf, with IC 50 of 2.381 μg/mL, 6.966 μg/mL, and 19.365 μg/mL, respectively. All E. elatior extracts revealed a significant inhibitory activity against α-glucosidase at the concentration of 500 μg/mL, in which the stem extract showed the most effective α-glucosidase inhibitory effect with IC 50 value of 5.15 μg/mL, suggesting its promising potential as antidiabetic agent. This study highlights E. elatior potency as a novel source of antioxidant and natural antidiabetic compounds that are useful for the prevention and treatment of diabetes.

Clinical application of cluster analysis in patients with newly diagnosed type 2 diabetes.

Early prevention and treatment of type 2 diabetes mellitus (T2DM) is still a huge challenge for patients and clinicians. Recently, a novel cluster-based diabetes classification was proposed which may offer the possibility to solve this problem. In this study, we report our performance of cluster analysis of individuals newly diagnosed with T2DM, our exploration of each subtype's clinical characteristics and medication treatment, and the comparison carried out concerning the risk for diabetes complications and comorbidities among subtypes by adjusting for influencing factors. We hope to promote the further application of cluster analysis in individuals with early-stage T2DM. In this study, a k-means cluster algorithm was applied based on five indicators, namely, age, body mass index (BMI), glycosylated hemoglobin (HbA1c), homeostasis model assessment-2 insulin resistance (HOMA2-IR), and homeostasis model assessment-2 β-cell function (HOMA2-β), in order to perform the cluster analysis among 567 newly diagnosed participants with T2DM. The clinical characteristics and medication of each subtype were analyzed. The risk for diabetes complications and comorbidities in each subtype was compared by logistic regression analysis. The 567 patients were clustered into four subtypes, as follows: severe insulin-deficient diabetes (SIDD, 24.46%), age-related diabetes (MARD, 30.86%), mild obesity-related diabetes (MOD, 25.57%), and severe insulin-resistant diabetes (SIRD, 20.11%). According to the results of the oral glucose tolerance test (OGTT) and biochemical indices, fasting blood glucose (FBG), 2-hour postprandial blood glucose (2hBG), HbA1c, total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C) and triglyceride-glucose index (TyG) were higher in SIDD and SIRD than in MARD and MOD. MOD had the highest fasting C-peptide (FCP), 2-hour postprandial C-peptide (2hCP), fasting insulin (FINS), 2-hour postprandial insulin (2hINS), serum creatinine (SCr), and uric acid (UA), while SIRD had the highest triglycerides (TGs) and TyG-BMI. Albumin transaminase (ALT) and albumin transaminase (AST) were higher in MOD and SIRD. As concerms medications, compared to the other subtypes, SIDD had a lower rate of metformin use (39.1%) and a higher rate of α-glucosidase inhibitor (AGI, 61.7%) and insulin (74.4%) use. SIRD showed the highest frequency of use of sodium-glucose cotransporter-2 inhibitors (SGLT-2i, 36.0%) and glucagon-like peptide-1 receptor agonists (GLP-1RA, 19.3%). Concerning diabetic complications and comorbidities, the prevalence of diabetic kidney disease (DKD), cardiovascular disease (CVD), non-alcoholic fatty liver disease (NAFLD), dyslipidemia, and hypertension differed significantly among subtypes. Employing logistic regression analysis, after adjusting for unmodifiable (sex and age) and modifiable related influences (e.g., BMI, HbA1c, and smoking), it was found that SIRD had the highest risk of developing DKD (odds ratio, OR = 2.001, 95% confidence interval (CI): 1.125-3.559) and dyslipidemia (OR = 3.550, 95% CI: 1.534-8.215). MOD was more likely to suffer from NAFLD (OR = 3.301, 95%CI: 1.586-6.870). Patients with newly diagnosed T2DM can be successfully clustered into four subtypes with different clinical characteristics, medication treatment, and risks for diabetes-related complications and comorbidities, the cluster-based diabetes classification possibly being beneficial both for prevention of secondary diabetes and for establishment of a theoretical basis for precision medicine.

Health Care Expenditure of Patients With Type 2 Diabetes Mellitus in Bangladesh: A Review

The main objectives of this review are to offer an in-depth examination of the analysis of health care expenditure of patients with type 2 diabetes mellitus in covering its epidemiology, causes, clinical manifestations, diagnostic techniques, treatment approaches, and prognosis in Bangladesh. Most of the information and data are mainly involved in a critical review of various studies from sample groups of different ethnicities, age groups and genders. This study employs a systematic review and meta-analysis approach to compile and analyze existing research on health care expenditure of patients with type 2 diabetes mellitus. The study follows the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to ensure comprehensive and transparent reporting of the review process. Results on the basis of various reports showed that the length of diabetes and the number of co-morbidities and complications raise the cost of healthcare. The data confirms the previously reported conclusion that patients treated with insulin monotherapy or an insulin and oral hypoglycemic agents (OHAs) combination had higher direct costs and overall costs than patients treated with OHAs alone. Overall, it was discovered that the main contributing factors to the cost of therapy were the length of diabetes, the quantity of co-morbidities and complications, and the type of treatment. The prevalence of type 2 diabetes is increasing in Bangladesh, where out-of-pocket medical expenses are higher and universal health insurance is not available to the general public. Planning cost-effective diabetes management and prevention measures is necessary. A suitable insurance plan should be created with special services for diabetic patients. To reduce the negative effects of the condition, early detection of diabetes is essential as reported by several studies compiled herein. This can be accomplished through raising awareness and eradicating the social stigma, especially for women in Bangladesh. J. Bio-Sci. 32(2): 93-106, 2024

Counseling and examination related to the prevention of hypertension and diabetes in the elderly

Aging brings various health challenges, including hypertension and diabetes mellitus, which can affect the quality of life of the elderly. This study aims to identify the prevalence of these two diseases in Kepatihan Village, Kaliwates District, Jember Regency, and evaluate the effectiveness of health education in managing them. Community service activities include initial examinations that show a high prevalence of hypertension and prediabetes among the elderly, with only a few having normal blood pressure and blood sugar levels. The program involves health examinations, disease prevention and control education, and re-examination two weeks after the education. The results showed that older adults with normal blood pressure increased from 3 to 8 people, and regular blood sugar levels increased from 5 to 21 people. A significant decrease in cases of prehypertension and diabetes indicates the success of the education in increasing participants' awareness and knowledge about managing their health. However, high initial health conditions and limited resources remain barriers. This program shows the effectiveness of education in reducing the prevalence of non-communicable diseases among the elderly but requires continued efforts to support more sustainable health improvements

The Analysis Study of The Effect Vitamin D to Risk for Type 2 Diabetes Mellitus in People with Pre-Diabetes : A Comprehensive Systematic Review

Background: Individuals with prediabetes are at a 50% increased risk of advancing to Type 2 Diabetes Mellitus (T2DM). Deficient levels of vitamin D are associated with higher risks of insulin resistance and diabetes. Methods: This systematic review adhered to PRISMA 2020 guidelines, focusing exclusively on full-text articles published in English between 2012 and 2024. Result: The review process involved analyzing over 300 publications from the selected databases. After an initial screening, eight studies met the criteria for detailed examination. These studies underwent an in-depth review to ensure a rigorous and comprehensive evaluation of their findings. Conclusion: Vitamin D supplementation may offer potential benefits in reducing the risk of T2DM in individuals with prediabetes by enhancing insulin synthesis and sensitivity. However, the overall effectiveness of diabetes prevention is still debated, with recent large-scale trials reporting nonsignificant results. The fat-soluble nature of vitamin D may limit its effectiveness in obese individuals. The American Diabetes Association advocates for further research to explore the potential advantages of combining vitamin D supplementation with lifestyle interventions.

Enhancing Health Data Assessment Performance: A Multi-Sensor Focused Study for Public Health

The term health data assessment performance described the process of assessing efficacy of acquiring and reporting health data. Multi sensor approach for predicting diabetes in public health scenarios, multi sensor for public health assimilates assorted data source and addresses community health challenges widely and efficiently. In this study, we proposed a Horse Herd Fused Discriminant Generative Adversarial Network (HHF-DGAN) algorithm for diabetes prediction. Sensor-based diabetes data is gathered from kaggle, and then data preprocessing using z-score normalization is inaccurate records from a dataset. To extract feature from the pre-processed data, Short-Time Fourier Transform (STFT) is used for dimensionality reduction. HHF-DGAN is a public health technique that addresses diabetes prevention and management while also including multi sensor assessment data. The proposed methods are to evaluate F1-score (86%), precision (92%), recall (93%), and accuracy (93%). The effectiveness of the suggested strategy in improving prediction reliability for diabetes detection in public health circumstances has been established by comparing it with existing methods. The study concludes field of healthcare assessments with a robust framework for leveraging multi sensor data and deep learning methods in disease prediction.

Artificial intelligence-driven transformations in diabetes care: a comprehensive literature review.

Artificial intelligence (AI) has been applied in healthcare for diagnosis, treatments, disease management, and for studying underlying mechanisms and disease complications in diseases like diabetes and metabolic disorders. This review is a comprehensive overview of various applications of AI in the healthcare system for managing diabetes. A literature search was conducted on PubMed to locate studies integrating AI in the diagnosis, treatment, management and prevention of diabetes. As diabetes is now considered a pandemic now so employing AI and machine learning approaches can be applied to limit diabetes in areas with higher prevalence. Machine learning algorithms can visualize big datasets, and make predictions. AI-powered mobile apps and the closed-loop system automated glucose monitoring and insulin delivery can lower the burden on insulin. AI can help identify disease markers and potential risk factors as well. While promising, AI's integration in the medical field is still challenging due to privacy, data security, bias, and transparency. Overall, AI's potential can be harnessed for better patient outcomes through personalized treatment.