Iranian Journal of

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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: 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: 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: 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: 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.