مجله دیابت و متابولیسم ایران
سال بیست و سوم شماره 1 (پیاپی 110، فروردین و اردیبهشت 1402)

Control of Type 2 Diabetes Mellitus (T2DM) is influenced by lifestyle. The aim of this research was to determine the predictors of treatment adherence behaviors among T2DM based on Social Cognitive Theory (SCT).

This descriptive-analytical research was done among 500 T2DM patients in Tehran during 2021. Simple random sampling was performed among patients based their medical records in the Diabetes Control Clinic of Tehran's District Five. The data collection tools were written questionnaire based on the SCT determinants. Data were analyzed using descriptive statistics (frequency, percentage, mean, standard deviation) and analytical statistics (Pearson's correlation and linear regression) in SPSS software version 16.

The mean score of treatment adherence behaviors was 56.34 [SD: 10.41], ranged from 16 to 80. The outcome expectations, perceived self-efficacy, and social support accounted for 43% of the variation in the outcome measure of the treatment adherence behaviors. Self-efficacy was the strongest predictor (Beta = 0.430 and P<0.001). Increasing age (ß= -0.126 and P= 0.004), insulin treatment (ß= -0.250 and P<0.001) and smoking (ß= -0.146 and P= 0.001) conversely and having health insurance (ß= 0.181 and P<0.001) were positively predictive of treatment adherence behaviors.

The development, implementation and evaluation of educational interventions based on SCT with emphasis on promoting perceived self-efficacy can lead to useful findings in promoting treatment adherence behaviors among T2DM patients.

The release of adipokines from adipose tissue depots plays a key role in regulating metabolic homeostasis and several other physiological processes, including diabetes, obesity, and vascular diseases. This study investigated the effect of eight weeks of high intensity interval training (HIIT) on asprosin, lipid profile and insulin resistance in type 2 diabetic male rats.

24 male Sprague Dawley rats were randomly divided into four equal groups: control (C), control traning (C+T), diabet (D) and diabet traning (D+T). Diabetes was induced by the combined method of high fat diet and low dose strepotozocin injection. The traning group performed the HIIT program on the treadmill for eight weeks. Data were analyzed using one-way ANOVA and bonferroni post hoc test at a significance level of P<0.05.

The results showed increased plasma asprosin in D group compared to C (P=0.0001) and decreased in C+T group compared to C (P=0.03) and D+T group compared to D (P=0.04). There was no significant difference in HOMA-IR between the C and C+T group (P=0.9) but decreased in D+T compared to D (P=0.0001). HDL increased in D+T group compared to the D (P=0.0001) and decreased TG and LDL (P=0.001). There was no significant difference between TG and LDL in the C group compared to the C+T, but HDL increased in C+T (P=0.01).

Plasma asprosin increases in rats with type 2 diabetes and HIIT can reduce the complications of diabetes by improved lipid profile and reduce asprosin and insulin resistance.

Impaired insulin function with exogenous changes is a major cause of heart failure. The purpose of this study was to investigate the effect of four weeks of high intensity interval training with curcumin supplement on the expression of IRS-1 and IRE-1α gene in the Left ventricle of type 2 diabetic rats.

In the present experimental study, 30 male mice with diabetes were divided into five groups of 6; high intensity interval training (HIIT), High intensity interval Training+Curcumin(S+HIIT), Diabetic control+curcumin(S+DC), Diabetic Control (DC), Normal control (NC). The High intensity interval training protocol was performed five days a week for four weeks. Curcumin gavage at a dose of 100 mg/kg was performed daily. The expression of IRS-1 and IRE-1α were measured by the qReal-TimePCR method, and data were analyzed by one-way ANOVA at the alpha level of 0.05.

IRS-1 gene expression in the S+HIIT group compared to the DC (P=0.003) and S+DC (P=0.001) groups and in the HIIT group compared to the DC (P=0.002), and S groups +DC had a significant decrease (P=0.019). IRE-1α gene was significantly decreased in S+HIIT group compared to DC (P=0.003), S+DC (P=0.001) and HIIT (P=0.008) groups.

It seems that HIIT with curcumin supplement can reduce the process of myocardial apoptosis in diabetic patients by improving metabolic conditions and genetic factors.

Type 2 diabetes is the most common metabolic disease, a chronic and progressive disorder that causes permanent complications and increased cardiovascular, cerebrovascular, peripheral vascular disease, nephropathy, retinopathy, neuropathy, diabetic foot, amputation and death in patients.The aim of the present study was to examine the predictor role of negative repeating thoughts, emotion regulation strategies and self-care in remedial acceptance and adherence of patients with type 2 diabetes.

The method of the present study was descriptive, correlation type, and the population was from all the patients with type 2 diabetes who were members of Diabetes Association in Chahar-Mahal-o Bakhtiyari. Among this group, using the convenience sampling method, and on the basis of Morganʼs table, 300 patients with type 2 diabetes were recruitment. Using MackEuy and othersʼ negative repeating thoughts questionnaire (2014), Mans & Malouf emotion regulation strategies questionnaire (2009), Toobert & Glasgow self-care questionnaire (2000) & Modanloo acceptance and treatment follow-up questionnaire (2014), the experiment group was investigated. The data were analyzed by SPSS software.

Our findings have shown that negative repeating thoughts, emotion regulation strategies and self-care predict the remedial acceptance and adherence of patients with type 2 diabetes significantly.

With pay attention to identify of the predictor role of negative repeating thoughts, emotion regulation strategies and self-care in remedial acceptance and adherence of patients with type 2 diabetes, and high prevalence of this disease too, it seems that psychological intermediations, with pay attention to role of mentioned variables to decrease of psychological problems and increase of adherence in them, pay attention to role of negative repeating thoughts too, compatible and incompatible strategies of emotion regulation and adhere to self-care could be taken as prevention of deterioration type 2 diabetes and better controlling.

Animal studies have shown maternal low/ high-calorie diet during pregnancy can alter metabolism of offspring through change in Sirtuin 1 (SIRT1) expression, as a metabolic sensor. However, there is no study on the effects of isocalorie diet. Herein, effects of two isocalorie diets with different amounts of fat were assessed on SIRT1 gene and protein level in the liver of male and female offspring.

The control group received AIN93G diet. In this diet, 16% and 64% of total calorie were prepared from fat and carbohydrate, respectively. The intervention group received high fat AIN93G diet contained 48% and 32% of calorie from fat and carbohydrate, respectively. In both diets, fat was prepared from soy oil. Diets were isocaloric and 20% of total calorie was provided from protein. Mothers categorized to one of these diets and offspring received the control diet after weaning (3 weeks after the birth).

SIRT1 gene and protein levels were lower in male and female offspring born from mothers received high-fat diet than the controls (p<0.001).

Change in maternal dietary fat, without increase in calorie, effects on gene and protein levels of SIRT-1 in the liver of next generation.

Diabetes entails a great quantity of deaths each year and a great quantity of people living with the disease do not find out their health status early sufficient. In this paper, we advance a data mining-based model for prematurely diagnosis and prediction of diabetes.

Although K-means is simple and can be utilized for a vast diversity of data kinds, it is wholly sensitive to initial locations of cluster centers which specify the final cluster result, which either enables an efficiently and adequate clustered dataset for the logistic regression model, or presents a lesser amount of data as a result of wrong clustering of the main dataset, thereby restricting the proficiency of the logistic regression model. The main purpose of this study is was to specify procedures of ameliorating the k-means clustering and logistic regression accuracy consequence. Therefore, our algorithm comprises of principal component analysis technique, k-means technique and logistic regression model.

The results obtained from this study show that the ability to obtain the result of K-means clustering accuracy is much higher than what other researchers have obtained in similar studies. Also, compared to the results obtained from other algorithms, the logistic regression model was implemented at an improved level in predicting the onset of diabetes. Another real advantage is that the proposed algorithm was able to successfully model a new dataset.

In general, the proposed approach can be effectively used in predicting and early diagnosis of diabetes.