PurposeThe patient believes in adherence to medication rather than to self-care adherence and lifestyle changes for the management of diabetes. This study was carried out to establish the association of self-care adherence and their barriers in poor glycemic control in our diabetic population.Patients and methodsThis cross-sectional study was conducted among 480 already diagnosed diabetes outpatients attended in our two hospitals. Glycaemic control was defined by levels of HbA1c. Socio-demographic data, lifestyle variables and anthropometric measurements were recorded using a standard questionnaire. Fasting blood glucose, HbA1c and lipid profiles were estimated using the manufacturer’s guideline. Student’s t-test and one-way ANOVA were used for comparison between different groups and the correlation was established by Spearman correlation. Risk factors associated with poor glycaemic control were verified by logistic regression analysis.ResultsThe mean HbA1c of the study population was 7.4±1.3% and 65.4% had poor glycaemic control with mean 8.0±1.1%. Higher HbA1c levels were significantly associated with duration of diabetes, a number of drugs used, patient–physician relationship and knowledge about diabetes. The poor glycaemic control was significantly associated with low adherence of following the meal plan, regular medication and regular exercising (p<0.001). Among all the barriers, a too busy schedule for following the meal plan, taking medications and exercising regularly was significantly correlated with HbA1c levels. Multivariable logistic regression analysis showed irregular meal plan (OR=5.27), irregular exercise (OR=2.25), number of medication used (OR= 0.19) and lesser extent patient–physician relationship (OR=2.68) were independent risk factors for poor glycaemic control.ConclusionThe poor glycaemic control was associated with poor adherence to self-care adherence and their barriers in our diabetic population. Integrated knowledge on diabetes management should be targeted to improve glycaemic control in our communities.

Background: The widespread dissemination of unhealthy dietary habits, childhood-teenage obesity, and sedentary lifestyle in young adults has paved the way for public health burden metabolic syndrome and early onset of type 2 diabetes mellitus. The aim of this study was to assess the prevalence and risk factors for metabolic syndrome and diabetes among young adult students. Methods: This cross-sectional study was conducted among students of age group (18 to 25 years) studying at Manmohan Memorial Institute of Health Sciences and Central Institute of Science and Technology. The diabetes risk score of each individual was calculated by the Finnish Diabetes Risk Score (FINDRISC tool). Independent risk factors for diabetes and metabolic syndrome were measured by multivariable logistic regression analysis. The p-value of <0.05 was considered statistically significant in this study. Results: A total of 825 students were recruited and 739 (89.6%) students completed the study with all the fulfilled criteria. The metabolic syndrome (Harmonized Joint Scientific Statement (HJSS) criteria) was present in 7.1%, and the most prevalent defining component was low HDL-C (78%); 74.8% of students were under low risk, 22.18% were at slightly elevated risk, 2.02% were at moderate risk, and 1.01% were at high risk of diabetes. The cardiometabolic risk factors like BMI, TC, and LDL-C were higher at a significant level (p<0.001) with an increased diabetes risk score. Independent lifestyle risk factor for metabolic syndrome was current smoking (AOR, 4.49, 95% CI 1.38-14.62) whereas, an independent lifestyle risk factor for diabetes was low adherence to physical exercise (AOR, 4.81, 95% CI, 2.90-7.99). Conclusion: Metabolic syndrome is present, although in low numbers in young adults putting them at risk to develop diabetes in the near future. Early assessment of metabolic syndrome and diabetes risk in young may provide insights for preventive and control plans for risk population.

Background. Clinical laboratory diagnosis and prognosis for diabetes mellitus is performed using blood as a major specimen; however, saliva may represent as an alternative noninvasive specimen of choice. This study aims to evaluate salivary biochemical parameters in diabetic and healthy individuals to substantiate saliva’s role in the diagnosis and prognosis of type 2 diabetes mellitus (T2DM). Methods. This case-control study included 150 T2DM patients and 150 apparently healthy individuals. Socio-demographic data and anthropometric measurements were recorded using a standard questionnaire. Correlation between salivary and blood levels for each parameter was determined using Pearson correlation. Linear regression was performed to estimate the blood levels of the parameters from their salivary levels. Receiver operating characteristics (ROC) analysis was done to determine the diagnostic ability of salivary glucose and establish a sensitivity, specificity, and cut-off value. Results. Salivary glucose, TC, LDL-C, urea, and creatinine were significantly higher in people with diabetes than in the control population ( p < 0.05 ). A significant positive correlation was found between salivary and blood parameters including glucose, TC, TG, LDL-C, urea, and creatinine except for HDL-C in both case and control groups. The linear relationship for each parameter, except glucose in case population and HDL-C in case, control, and the total population was observed between blood and saliva. ROC analysis gave a cut-off value of 1.9 mg/dl for salivary glucose with 71.4% sensitivity and 72.3% specificity. Conclusion. Salivary estimation significantly reflects the blood parameters in this study, indicating that saliva can be a noninvasive specimen for the diagnosis and prognosis of T2DM.

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