Virtual reality (VR) is becoming more and more present in our everyday life (education, industry, gaming, etc.). It allows an almost total immersion in the designed environment by using head-mounted displays (HMD). However, depending on the used content and device, the comfort of the user may be significantly altered. It appears very important to understand and model the factors involved in this process in order to improve the quality of experience (QoE) of users. Many authors investigated the potential factors leading to sickness or discomfort in immersive environments. These studies target a limited number of factors (often a single one) and do not propose a model for assessing their impact on comfort and/or QoE. Our aim is to get upstream of the content production workflow and propose a solution to predict the discomfort level that could be generated by VR. This implies building a metric combining different factors having a significant impact on comfort based on psychophysical experiments. In this study, we start by identifying the factors responsible for discomfort. Then, we build a reliable and reproducible experimental protocol to characterize their impact on the general comfort of the user. A deep statistical study of the results allows to understand the nature of this impact and helps in designing a model to predict it at the early stage of the content production for immersive applications.