Variables incorporated in statistical analysis.

Studies have investigated various aspects of how the COVID-19 pandemic has impacted college students’ well-being. However, the complex relationships between stress and its correlates have received limited attention. Thus, the main objective of this study is to evaluate multiplicative associations between stress and demographic, lifestyle, and other negative emotion factors during the pandemic. We used data from a survey with 2,534 students enrolled in seven U.S. universities and analyzed such data with generalized additive Tobit models and pairwise interaction terms. The results highlighted associations and interactions between myriad factors such as students’ social class, income, parental education, body mass index (BMI), amount of exercise, and knowing infected people in the student’s communities. For instance, we found that the associations between feeling irritable and sad due to the pandemic were interactive, resulting in higher associated stress for students with higher levels of parents’ education. Furthermore, associations between taking precautionary actions (i.e., avoiding travel and large gatherings) and stress varied with the intensity of negative feelings (i.e., sadness and irritability). Considering these interaction terms, the results highlighted a great inequality in pandemic-related stress within low income, lower social class, and higher BMI students. This study is among the earliest that employed a stratified approach with numerous interaction terms to better understand the multiplicative associations between different factors during the COVID-19 pandemic.