Background: Cardiovascular disease is considered as one of the most common diseases, causing many deaths worldwide annually. Objectives: The current study was aimed at diagnosing influencing factors of cardiovascular disease by comparison between implicational Logit and Probit models. Patients and Methods:This work is based on a study group approved by Mashhad University of Medical Sciences with the code of 85134 (Mashhad Study). Information was collected by the stratified-cluster sampling method and registering more than 7603 people randomly from Mashhad city. From them 682 were patients with cardiovascular disease. Data was analyzed using statistical Logit and Probit models. Results: After analyzing linearity and interactional effects between variables, by considering the other variables unchanged, the Odd Ratio of sex, age, high density lipoprotein-cholesterol (hdl-c), systolic blood pressure (sys-bp), body mass index (BMI), smoking, total cholesterol, High-Sensitivity C-Reactive Protein (hs-CRP) and history on cardiovascular disease were 4.231, 2.70, 0.98, 3.8, 3.421, 2.014, 1.5, 1.7 and 7.215 respectively. Conclusions: Independent variables such as sex, age, hdl-c, sys-bp, BMI, smoking, cholesterol and hs-CRP were considered as influencing variables, and education, marital status, disease history, height, waist circumference, diastolic blood pressure and low density lipoprotein were removed from the models.

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One of the most accessible and useful statistical tools for comparing independent populations in different research areas is the coefficient of variation (CV). In this study, first, the asymptotic distribution of the ratio of CV of two uncorrelated populations is investigated. Then, the outputs are used to create a confidence interval and to establish a test of hypothesis about the CV ratio of the populations. The proposed approach is compared with an alternative method, showing its superiority and effectiveness.

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