This study aims to identify key risk factors associated with OCD to provide a foundation for the development of effective prevention strategies. Using an online cross-sectional survey where factors such as lifestyle, demographics, and dietary habits were assessed using a validated classification scale, data was collected with a number of participants that satisfied the sample size needed for analysis (n=1585). Lasso and logistic regression analysis (LRA) were performed to identify the potential risk factors for OCD, and the importance of these factors were assessed using three kinds of machine learning models: the Support Vector model, the Random Forest model, and the Back Propagation Neural Network model. It was found that most participants were 30 and under with a bachelor’s degree of some sort. There were significant differences found on the basis of dietary habits and sleep quality, as those who were picky eaters or had poor quality sleep were at higher risk for OCD. Having a more extensive medical history and/or GI symptoms were also found to be risk factors. Out of all the participants, 30.4% were categorized as high-risk for OCD, with more men than women being high-risk. This reversal of the norm was attributed to cultural differences, where Chinese males face higher expectations and societal pressures.