Application of Bivariate Logistic Regression Model in the Determination of Factors Associated With Diabetes and Hypertension for 35-65 Aged people in Mashhad

One of the most important causes of death worldwide is cardiovascular diseases with blood pressure and diabetes as the leading causes of these diseases. Due to the high correlation between them, the associated factors can be more accurately investigated. Therefore, this study was conducted with the purpose of application of Bivariate Logistic Regression Model in the determination of factors associated with diabetes and hypertension among 35-65 years old  people in Mashhad.

This analytical cross-sectional study was performed on a cross-sectional phase of Mashhad study data. The variables included demographic information, employment status, smoking, BMI, physical activity, anxiety, depression, cholesterol, triglyceride, and waist to hip ratio (WHR). In this regard diabetes and high blood pressure were considered as dependent variables. Analyses were performed using R3.4.4 software at a significant level of P

The results of the study revealed a significant relationship between diabetes and some variables such as, age, education level, BMI, WHR, anxiety, depression, cholesterol, and triglyceride  (P <0.05). Furthermore, high blood pressure was found to be significantly associated with age, sex, employment status, BMI, WHR, anxiety, cholesterol, and triglyceride (P <0.05).

In terms of correlation, it is proposed to use a bivariate model instead of one-variable models to obtain more accurate results. Given that most of the relevant factors were controllable variables in lifestyle, it would be better to focus on the public education and prevention in order to promote a healthy lifestyle in the community.