Iranian Journal of

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Background: Moderate and intense aerobic exercise increases the production of free radicals, and on the other hand, the use of antioxidant supplements such as grape seed extract (GSE) has been suggested as one of the ways to deal with oxidative stress. Based on this, the aim of this study was to determine the interventions effect of combined exercise and consumption of GSE on some factors of oxidative and antioxidant stress in postmenopausal women with type 2 diabetes.
Methods: The current study was conducted as a clinical trial on the 80 women with type 2 diabetes, who were randomly divided into four groups (20 people): control, exercise, GSE supplement, exercise + GSE supplement. The combined exercise protocol consisted of aerobic (20 minutes of treadmill running at an intensity of 60–70% of reserve heart rate) and strength training (at an intensity of 70% of one repetition maximum), which was performed for eight weeks (five days/week). GSE supplement was taken in the form of 200 mg capsules daily (morning and noon). Samples (five cc) were taken before and after eight weeks of interventions. In order to determine the acceptance or rejection of the null hypothesis of intragroup and intergroup changes, was used the two-way AVOVA, and then Tukey's post hoc test to determine different groups by SPSS version 25 (P≤ 0.05).
Results: The values of total antioxidant capacity (TAC) and serum glutathione reduction (GSH) in the GSE and exercise + GSE groups increased significantly compared to the control and exercise groups (P= 0.001). Serum malondialdehyde (MDA) levels in the GSE group showed a significant decrease compared to the control and exercise groups (P= 0.001).
Conclusion: It seems that the intervention of grape seed extract is more effective in reducing oxidative stress than combined exercise. The consumption of this extract alone, as well as with combined exercise, has a significant effect on increasing the total antioxidant capacity and reducing GSH (glutathione).

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Background: Inflammatory protein C3 and IL-1β are significantly involved in the pathophysiology of type 2 diabetes (T2D) and Alzheimer's disease. Moreover, examining the importance of aerobic exercise timing (light vs. dark phase) can provide a better understanding of how exercise timing affects inflammatory markers associated with neurological diseases in older adult women with T2D. Therefore, this study aimed to investigate the effect of aerobic exercise timing on C3 and IL-1β levels in older adults’ women with T2D.
Methods: In this semi-experimental study, 45 women with T2D with an average age of 60 ± 5.07 years were divided into training groups (light and dark phase) and control (15 people in each group). Aerobic exercise was performed for 12 weeks at a moderate intensity (60-70% of heart rate reserve). Protein levels (C3 and IL-1β) were measured before and after the intervention using the ELISA method. Data were analyzed using SPSS27 software and ANOVA with a significance level of 0.05.
Results: Complement C3 was significantly lower in the dark phase exercise group compared to the control group (P= 0.0083). Additionally, the results showed that dark phase aerobic exercise significantly decreased C3 (P= 0.0028) and IL-1β (P= 0.0045) levels compared to baseline.
Conclusion: Aerobic exercise performed during the dark phase effectively reduced inflammatory protein levels of C3 and IL-1β in older adult women with T2D, suggesting it could be considered as a crucial strategy in managing this disease.

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Background: This study aimed to investigate the relationship between stigma associated with type 2 diabetes and subjective well-being measures (life satisfaction and positive/negative affect) mediated by emotional stress and illness perception in people with type 2 diabetes.
Methods: The present research was descriptive based on correlation models. The statistical population included patients with type 2 diabetes who referred to the diabetes clinic of Ayatollah Taleghani hospital in Kermanshah, 207 adults were selected using the convenient sampling method and data were collected using questionnaires Type 2 Diabetes Stigma Assessment Scale (DSAS-2) (Browne et al., 2016), life satisfaction (Diener, 1985), Positive/Negative Affect Schedule (Watson et al., 1988), Illness Perception (Broadbent et al., 2006) then analyzed with SPSS and Amos software.
Results: The results showed that there was a significant relationship between stigma, life satisfaction, and positive/negative affect (P < 0.01). Stigma was also able to predict life satisfaction indirectly and negatively through emotional distress, and negative affect indirectly and positively through emotional distress and illness perception.
Conclusion: The results indicate the need for interventions to reduce the stigma associated with type 2 diabetes and improve the mental well-being of people with this disease.

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Background: Type 2 diabetes is a prevalent metabolic disorder characterized by insulin resistance and impaired glucose absorption. The COVID-19 pandemic and associated quarantines led to significant lifestyle changes, including reduced physical activity among diabetic individuals. This study investigates the patterns of physical activity and perceptions among diabetic individuals in post-COVID Iran.
Methods: An online questionnaire was created using the "Pors Online" platform and shared via social media. Among 435 participants from 35 Iranian cities, 400 responses (200 diabetics and 200 healthy individuals) were deemed complete and valid for analysis. The data were analyzed using an independent t-test, with a significance level set at P< 0.05.
Results: The results showed that the physical activity level of diabetic individuals was significantly lower than that of non-diabetic individuals P< 0.05. Additionally, their preferred types of physical activities differed; both groups showed the most interest in walking and the least interest in traditional games. The primary motivation for exercise among diabetic individuals was disease prevention, but financial barriers had the greatest impact on reducing their physical activity P< 0.05. Their main sources of information about physical activity were magazines and books.
Conclusion: Improving access to sports facilities and tailored equipment for diabetics, coupled with awareness campaigns on the benefits of exercise, is essential. Developing customized sports programs suited to the health conditions of diabetics can enhance their participation and overall well-being.

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Background: The increasing trend of diabetes patients requires lifestyle interventions to improve the self-management ability of these patients, and achieving this requires the use of valid tools in this field. This study aimed to determine the psychometric properties of the Comprehensive Diabetes Self-Management Scale (CDSMS) in patients with type 2 diabetes.
Methods: The present study was methodological research that was conducted in 2023. At the beginning of the work, the CDSMS questionnaire was translated into Persian using the standard translation-back translation method. Then, face validity, content validity, convergent validity, internal consistency, and instrument stability were determined. Data analysis was performed using descriptive statistics, Cronbach's alpha calculation, Kappa index, Pearson correlation coefficient, and intra-cluster correlation coefficient in SPSS software version 24.
Results: Based on the results, all the items of the instrument were retained. The total content validity index score of the Persian version of this questionnaire was 0.987. Also, the Kuder-Richardson and Kappa indices were 0.704 and 0.730, respectively. The level of agreement at two measurement times, two weeks apart, ranged from 0.503 to 0.990. The intra-cluster correlation index was also observed to be in the range of 0.625 to 0.952 and was significant (P < 0.001). The Cronbach's alpha coefficient of the instrument was also 0.83.
Conclusion: The results of the present study showed that the Persian version of the CDSMS questionnaire with 14 items has good validity and reliability and can be used to evaluate the self-management status of patients with type 2 diabetes in Iran.

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Background: Exercise training represents an effective approach that contributes substantially to lowering chemerin and vaspin levels, enhancing body composition, and preventing complications related to overweight and obesity. In this context, the present study sought to examine the effects of exercise training on chemerin, vaspin, and body composition in individuals with type 2 diabetes.
Methods: A systematic review and meta-analysis was conducted to evaluate the effects of exercise interventions on various outcomes in patients with type 2 diabetes. A comprehensive search for English and Persian articles published up to )January 4, 2025( was performed across the following databases: PubMed, Web of Science, Scopus, Google Scholar, IranDoc, Magiran, Noormags, and SID (Scientific Information Database). Fifteen studies, including 19 exercise interventions and 440 participants with type 2 diabetes, were included. Data were analyzed using a random-effects model, and the mean differences with 95% confidence intervals (CI) were calculated. Heterogeneity was assessed using the I² statistic, and publication bias was evaluated through visual inspection of funnel plots and Egger’s test.
Results: A total of 15 studies (with 19 exercise interventions) involving 440 participants with type 2 diabetes were included in the meta-analysis. The results indicated that exercise interventions led to non-significant changes in c-Merlin [SMD= −0.967, 95% CI: −2.453 to 0.518, P= 0.202], body mass index (BMI) [SMD= −0.228, 95% CI: −0.470 to 0.013, P= 0.064], waist-to-hip ratio (WHR) [SMD= −0.038, 95% CI: −0.773 to 0.007, P= 0.054], and body fat percentage [SMD= 0.080, 95% CI: −0.524 to 0.685, P= 0.795] compared with the control group in individuals with type 2 diabetes.
Conclusion: The results of the present study demonstrated that exercise training significantly reduces vaspin levels in patients with type 2 diabetes, while it has no significant effect on chemerin, body composition, or body composition indices (including body mass index, body fat percentage, and waist-to-hip ratio). It appears that physical exercise may play an effective role in improving the metabolic status of patients with type 2 diabetes through the modulation of vaspin levels.

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Background: Diabetes is a serious global health problem, and effective methods for its prediction and management are essential. Conventional diagnostic approaches typically rely on tests such as oral glucose tolerance test (OGTT), fasting plasma glucose (FPG) and glycated hemoglobin (HbA1c). Machine learning has the potential to enhance diagnostic accuracy; however, its performance and alignment with clinical guidelines require thorough evaluation.
Methods: This narrative review examines the effectiveness of machine learning in the early diagnosis of diabetes. Articles were selected based on predefined criteria and analyzed in terms of algorithm classification, output measures, involvement of clinical experts, and interpretability. Evaluation metrics such as accuracy, area under the curve (AUC), specificity and sensitivity were used to assess algorithmic performance. Relevant studies comparing prediabetes diagnosis using artificial intelligence and conventional methods were reviewed, and clinical guidelines from both domains were extracted and compared.
Results: Analysis of 41 articles showed that ANN, LR, and DNN were the most frequently used algorithms. Only 2% of the studies incorporated clinical rules and physician involvement, and 12% demonstrated model interpretability. While conventional methods rely on HbA1c and FPG tests, no clinical guidelines currently exist for AI-based diagnosis. Machine learning algorithms outperformed traditional methods, showing 29% higher sensitivity and 23% higher specificity.
Conclusion: Although artificial intelligence demonstrates superior performance in prediabetes diagnosis, limitations such as lack of interpretability and the absence of standardized clinical guidelines hinder its current clinical application. Addressing these challenges could enable AI to become a more efficient and reliable diagnostic tool.
 

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Background: Type 2 diabetes is a major public-health threat of the present century, imposing substantial clinical and economic burdens on health systems. Accurate forecasting of disease incidence can support resource allocation and the design of targeted interventions.
Methods: In this study, we developed a hybrid model that integrates Cellular Learning Automata (CLA) with a Susceptible–Infected–Recovered (SIR) framework to predict the 20-year spread of type 2 diabetes using real patient data from Kerman province. The dataset comprised demographic and laboratory features of patients with diabetes collected during the Persian calendar years 2005– 2013. After preprocessing and imputation of missing values, the proposed model was implemented in MATLAB.
Results: Results indicate that the CLA–SIR combination models the disease trajectory with high accuracy. Moreover, factors such as blood pressure, cholesterol, and body mass index were identified as key drivers influencing the activation states of model cells.
Conclusion: These findings suggest that intelligent hybrid approaches can be effective for health-data analysis and long-term prediction of chronic diseases.
 

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Background: In recent years, the prevalence of diabetes has increased significantly. Parents of children with diabetes suffer from many physical and psychological problems; Therefore, various interventions have been designed to improve their quality of life and well-being. These interventions have benefited from a wide range of approaches and methodologies. The present study was conducted with the aim of identifying and reviewing various psychological interventions for parents of children under 6 years old with diabetes and examining their strengths and weaknesses.
Methods: The search for interventional protocols was done through various databases such as Google Scholar, PubMed, Science Direct and Scopus. after checking the data entry criteria, 11 articles were selected and studied.
Results: The interventions used different approaches such as cognitive-behavioral, social learning, family therapy, and positive parenting. The intervention methods were mostly remote and had different consequences for the parent and the child, which has been highlighted. Also, the sample size in these studies was between 30 and 200 parents, and the satisfaction level of the main interventions was reported to be high.
Conclusion: In general, limited interventions have been conducted. Given that interventions focusing on the psychological state of parents can lead to increased social support and improved mental health in parents and children with diabetes, it is hoped that this article will pave the way for examining different approaches.
 

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Background: Diabetes is a chronic disease where the body cannot use or store glucose properly. Diabetes occurs when the pancreas is unable to produce insulin, or the body cannot use the insulin produced. Nowadays, diabetes is a common disease worldwide, and providing automated methods for its diagnosis is critically important.
Methods: This paper introduces a novel method for diagnosing diabetes using artificial intelligence (AI) algorithms. The proposed method is based on metaheuristic and classification algorithms. The simulated annealing (SA) metaheuristic algorithm was used for feature selection. Diabetes diagnosis was performed using the improved K-nearest neighbor (KNN) classification algorithm. In addition to the proposed method, the performance of two other methods, named MVMCNN and WKNN, was studied for diabetes diagnosis.
Results: The proposed method has been compared practically with the two other methods for diagnosing diabetes. The comparisons are based on the accuracy rate of disease diagnosis. In the experiments, the proposed method (SAKNN) demonstrated 95% accuracy, the MVMCNN method showed 93% accuracy, and the WKNN method demonstrated 90% accuracy. Thus, the proposed method outperformed the others. The proposed method also had acceptable performance in terms of time and several other criteria.
Conclusion: The proposed method for diagnosing diabetes, using metaheuristic and classification algorithms, provides higher accuracy compared to other methods. These results indicate that the proper use of AI techniques can offer effective solutions for the automatic diagnosis of diabetes and can be used as an auxiliary tool for doctors and researchers.
 

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Background: Recurrent diabetic ketoacidosis is one of the serious and life-threatening complications of diabetes that can lead to repeated hospitalizations and significant complications. This study was conducted with the aim of investigating the prevalence, risk factors, and clinical outcomes of recurrent diabetic ketoacidosis in southeast Iran.
Methods: In this retrospective descriptive-cross-sectional study, the medical records of 560 patients with diabetic ketoacidosis during the years 2017-2020 at Afzalipour Hospital in Kerman were reviewed. Patients with at least two admissions due to diabetic ketoacidosis were included in the study. Demographic, clinical, and laboratory data were collected and analyzed using a checklist. The collected data were analyzed using SPSS software version 25 with chi-square and independent t-tests at a significance level of 0.05.
Results: Of 560 patients, 40 patients (7.16%) had recurrent diabetic ketoacidosis. The mean age of patients was 28.36 ± 15.04 years, and 60% were women. 70% of patients had type 1 diabetes. The most common underlying causes included irregular consumption or discontinuation of insulin (72.5%) and presence of infection (55%). Substance abuse was reported in 25% of patients. The mean serum levels of urea, creatinine, and potassium were 55.23 ± 37.73 mg/dL, 0.98 ± 0.67 mg/dL, and 4.38 ± 0.64 mEq/L, respectively.
Conclusion: This study showed that patients with type 1 diabetes are at higher risk of recurrent diabetic ketoacidosis. Non-adherence to insulin therapy and infections were the most important identified risk factors. These findings emphasize the importance of patient education regarding regular insulin consumption and prevention of infections.
 

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Background: Type 1 diabetes is the most common type of diabetes affecting children and adolescents. Nursing interventions for children with type 1 diabetes include recognizing the adolescent's problems and providing technical care and emotional support. Nurses play an important role in helping adolescents and their families manage emotions, adjust treatment regimens, and integrate new routines into daily life. The aim of this systematic review is to identify and analyze effective nursing interventions in the management of type 1 diabetes in children and support their families. This study, by reviewing the available evidence, attempts to explain the role of nurses in improving clinical, psychological, and behavioral outcomes in children and promoting awareness, self-care skills, and quality of life in families.
Methods: A systematic search was conducted in the scientific databases PubMed, Scopus, Web of Science, CINAHL, SID and Magiran between 2010 and 2025. The search strategy was created using the PubMed keywords (Nursing Interventions) [title/abstract], (Type 1 Diabetes), (Child) and (Family). Systematic search with English keywords: ((Nursing Interventions[title/abstract]) AND (Type 1 Diabetes [title/abstract])) AND (Child[title/abstract])) AND (Family[title/abstract]). Out of 500 studies on nursing interventions in pediatric type 1 diabetes with more detailed review, a total of 10 studies met the inclusion criteria and were included in the final analysis.
Results: The findings showed that nursing interventions can have a significant impact on diabetes management by children and families, leading to improved adherence to treatment regimens, better blood sugar control, and increased quality of life for children and families.
Conclusion: Nursing interventions play a significant role in improving blood sugar control, increasing awareness and self-care of children with type 1 diabetes, and supporting their families. Interventions such as patient and family education, psychological counseling, regular follow-up, use of educational and care-oriented technologies, and team collaboration have been able to provide favorable results in reducing disease complications, improving quality of life, and increasing psychosocial adjustment. Accordingly, the development and implementation of evidence-based intervention programs, taking into account the individual, cultural, and social characteristics of families, is recommended to improve nursing care in children with diabetes.
 

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Background: The impact of psychological factors on physical diseases has highlighted the need to recognize these factors in the process of preventive and therapeutic interventions. In this regard, the aim of the present study was to compare personality traits, resilience, and coping strategies in diabetic patients and healthy individuals.
Methods: A causal-comparative method was used in a sample of 75 diabetic patients and 75 healthy individuals, who were selected by convenience sampling. Data collection was carried out using resilience, five-factor personality, and coping strategies questionnaires. Independent t-test and multivariate analysis of variance in SPSS 62 software were used to examine the hypotheses.
Results: The mean scores of resilience and the personality traits of extraversion and conscientiousness were higher in healthy individuals, and the mean score of neuroticism was higher in diabetic individuals. No significant difference was observed in the personality traits of agreeableness and openness between these two groups. The findings showed that the average scores of healthy individuals in using problem-oriented strategies and the average scores of diabetic individuals in using emotion-oriented strategies were higher than the other group.
Conclusion: The findings indicate that psychological factors play a significant role in the emergence and intensification of problems in diabetic patients. Addressing these factors and incorporating appropriate psychological strategies may therefore contribute to more effective prevention and treatment of diabetes.
 

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Background: Diabetes is a chronic condition that can significantly impairs quality of life and requires long-term care due to its complications. Effective self-care education plays a key role in blood glucose control and in the prevention of diabetes-related complications. Telenursing is considered a promising approach to enhance self-care education in patients with type 2 diabetes.
Methods: This study was a systematic review conducted using a three-stage search strategy. Using Persian and English keywords including "telenursing," "self-care," and "diabetes," as well as their MeSH equivalents, relevant literature was searched in Persian databases (Magiran, SID) and international databases (PubMed, Scopus, Google Scholar) within the time frame of 2000 to 2023. After applying inclusion criteria, 17 out of 1,092 retrieved articles were selected for final review and analysis.
Results: A total of 1,092 articles were initially retrieved. After removing duplicates and applying the inclusion criteria, 17 relevant articles were included in the review. These studies evaluated the use of telenursing—either via telephone or in combination with other technologies—for effectively improving self-care behaviors in diabetic patients. 
Conclusion: The findings indicated that telephone calls can serve as a potential method of remote nursing care for educating patients on diabetes self-management. Nurses can utilize telenursing as an effective and efficient educational tool to enhance blood glucose control in diabetic patients. This approach not only improves the quality of healthcare services but also empowers patients to manage their disease more consciously and prevent its complications.
 

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Blood glucose variability, defined as variations in blood glucose levels over time, is increasingly recognized as a significant factor in the pathology of diabetes complications. While chronic hyperglycemia has been linked to microvascular complications (retinopathy, nephropathy, and neuropathy) and macrovascular complications (coronary artery disease, stroke, and peripheral artery disease), emerging evidence suggests that glucose variability is an independent risk factor for these conditions. This review examined the relationship between blood glucose variability and the development of microvascular and macrovascular complications in diabetes, highlighting the underlying mechanisms, clinical implications, and therapeutic approaches.

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Background: Type 2 diabetes is rapidly increasing, particularly in the Middle East where central obesity is a major contributor to disease burden. Identifying high-risk individuals requires indices that assess visceral adiposity more effectively than body mass index (BMI). This study compared nine anthropometric indices in relation to diabetes and determined their predictive capacity and optimal cut-off values.
Methods: This cross-sectional analysis included 10,103 adults aged 35–70 years from the FASA cohort. Diabetes was defined as fasting glucose ≥126 mg/dL or antidiabetic medication use. Measurements included BMI, waist circumference (WC), hip circumference (HC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), body roundness index (BRI), body adiposity index (BAI), a body shape index (ABSI), abdominal volume index (AVI), and weight-adjusted waist index (WWI). Associations were examined using logistic regression (crude and adjusted models). Discriminatory accuracy was assessed using receiver operating characteristic (ROC) curves, area under the curve (AUC), and Youden's index. 
Results: Individuals with diabetes exhibited higher values across anthropometric indices (p< 0.05). In adjusted models, WC, WHR, WHtR, AVI, and WWI remained significant predictors (p< 0.05). WHR demonstrated the highest AUC (0.651, p< 0.001). Optimal cut-off values with high sensitivity and specificity included WHR= 0.91, WHtR= 0.53, and BRI= 4.1. 
Conclusion: Central obesity indices—particularly WHR, WHtR, and BRI—demonstrated superior discriminatory capacity for diabetes and support the use of simple waist-based indices for early screening.

 

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Background: This study investigated the efficacy of the “Rehacom” cognitive rehabilitation software on five key cognitive domains—working memory, information processing speed, attention, inhibition, and executive functions—in patients diagnosed with Type 1 and Type 2 Diabetes Mellitus.
Methods: A pre-test/post-test experimental design with a control group was employed. A sample of 30 diabetic patients was recruited via convenience sampling and randomly allocated to either the experimental group (receiving Rehacom software intervention for 12 sessions) or the control group. Cognitive performance was assessed using the Rehacom software itself and the Barkley Deficits in Executive Functioning Scale (BDEFS). Each session lasted 45 minutes.
Results: Multivariate Analysis of Covariance (MANCOVA) revealed a significant overall effect of the intervention on the composite of dependent variables (Wilks’ Lambda= 0.184, F (5.24)= 7.978, P< 0.001). Subsequent Analysis of Covariance (ANCOVA) indicated that the intervention significantly enhanced “attention” (η²= 0.236, P= 0.016) and “executive functions” (η²= 0.621, P< 0.001). However, no significant impact was observed on working memory, information processing speed, or inhibition.
Conclusion: The findings suggest that the Rehacom software serves as an effective tool for improving attention and executive functions in diabetic patients. The notable effect sizes for these two domains underscore its clinical utility in cognitive rehabilitation programs for chronic patients. The absence of effects on other components may be attributable to factors such as the limited duration of the intervention, specific software exercises, or the underlying neurochemical and pathophysiological characteristics of diabetes, warranting further investigation with more robust designs.
 

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Background: Type 2 diabetes is a common chronic metabolic disease whose effective management requires attention to psychological and interpersonal factors. This study aimed to examine the relationship between the Perceived Spousal Sacrificial Behavior and self-efficacy with behavior management in patients with type2 diabetes.
Methods: This descriptive-correlational and cross-sectional study was conducted among married patients with type 2 diabetes who were referred to endocrinology and metabolism centers and primary health care units in Sari, Iran. Based on inclusion and exclusion criteria, 97 participants were selected using purposive sampling. The research instruments included the Perceived Spousal Sacrifice Scale (Harper & Figuerres, 2008), the Diabetes Self-Efficacy Scale (Fappa et al 2016), and the Behavioral Management Scale (Toobert et al., 2000). Data were analyzed using SPSS version 24 through descriptive statistics (mean, standard deviation) and inferential statistics (Pearson correlation coefficient and multiple regression analysis).
Results: Perception of the Perceived Spousal Sacrificial Behavior and self-efficacy showed a significant positive correlation with behavioral management among diabetic patients (p < 0.01). Together, these variables explained 30% of the variance in behavioral management, with Perceived Spousal Sacrificial Behavior making a greater contribution to prediction.
Conclusion: The findings highlight the significant role of Perceived Spousal Sacrificial Behavior and self-efficacy in improving behavioral management among patients with type 2 diabetes. Enhancing spousal support and strengthening patients’ self-efficacy through educational and psychological interventions may promote better self-care behaviors and disease control.

 

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Background: Obesity is one of the causes of diabetes. On the other hand, exercise along with cinnamon supplementation has been recommended as an important approach for controlling and preventing obesity and its related complications, such as diabetes and insulin resistance. Therefore, the aim of the present study is to investigate the combined effect of exercise training and cinnamon supplementation on glycemic indices in individuals with obesity and type 2 diabetes.
Methods: A systematic search of English and Persian articles published in PubMed, Web of Science, Scopus, Magiran, Google Scholar, NorMags, Irandoc, and SID databases was conducted up to January 2025. In data analysis, a random-effects model was used to calculate the weighted mean difference (WMD), standardized mean difference (SMD) and 95% confidence interval (CI). Also, heterogeneity of studies was assessed with the I² test.
Results: In total, 11 studies involving 230 participants with obesity and type 2 diabetes were meta-analyzed. The results indicated that the combination of exercise training and cinnamon supplementation significantly reduced glucose (WMD = -13.317 [95% CI: -19.599 to -7.034]; P = 0.001) and insulin resistance (WMD = -1.098 [95% CI: -1.577 to -0.618]; P = 0.001) compared to the control group in individuals with obesity and type 2 diabetes. However, insulin levels did not show a significant change (WMD = -2.123 [95% CI: -4.333 to 0.088]; P = 0.060).
Conclusion: The results of the present meta-analysis demonstrated that the combination of exercise training and cinnamon supplementation improves glucose and insulin resistance in individuals with obesity and type 2 diabetes. These beneficial effects are not accompanied by changes in insulin levels.

 

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Background: Sexual dysfunction is a prevalent, underdiagnosed, and impactful complication of type 2 diabetes in men, involving multiple physiological, psychological, and social dimensions. This narrative review aimed to comprehensively examine the current evidence regarding the role of exercise interventions in improving sexual function among men with type 2 diabetes through a multidimensional lens.
Methods: A narrative review was conducted based on a systematic search of PubMed, Scopus, Web of Science, and Google Scholar databases. Eligible studies included clinical trials, systematic reviews, and basic research focused on exercise and sexual function in men with diabetes. The analysis addressed physiological mechanisms, clinical outcomes, psychological factors, and research gaps.
Results: The evidence suggests that exercise improves sexual function in men with type 2 diabetes through multiple pathways, including enhanced insulin sensitivity, increased testosterone levels, improved penile vascular function, and psychological benefits such as reduced performance anxiety, depression, and improved body image. The type, intensity, and duration of exercise were found to be crucial in determining the outcomes. This review also identified significant research gaps, such as the lack of long-term trials and limited focus on neurohormonal mechanisms.
Conclusion: It seems that exercise is a safe, non-pharmacological, and effective intervention with substantial potential to improve sexual function in men with type 2 diabetes. The findings of this review can inform integrated therapeutic protocols and guide clinical practices aimed at enhancing sexual health in this population. A personalized exercise approach, supported by a multidisciplinary team, is recommended as part of formal care for diabetic men experiencing sexual dysfunction.