Binary logistic regression model.

This study investigates the relationship between transportation modes and adolescent mental health, employing a natural experiment design to longitudinally track Brazilian high-school students amid the COVID-19 pandemic disruptions. We surveyed 213 students in the city of Curitiba during and after the COVID-19 lockdown period using the Depression, Anxiety, and Stress Scale (DASS-21) combined with a socioeconomic questionnaire. To analyze changes in DASS between these two times we used the paired-sample T-test, exploring association with school commuting modes through binomial logistic regression models. The use of public transportation emerges as a significant factor associated with a threefold odds of increasing depression levels among students (OR = 3.08). This likelihood nearly quadrupled (OR = 3.81) when considering students living 5 km or more from school. These findings unveil public transportation and home-school distance as critical factors in the development of depression among adolescents. For example, individuals who commute via individual motorized transportation demonstrate a markedly lower likelihood of experiencing depression, pointing to broader societal and environmental factors such as family income and access to opportunities. Despite appearing contradictory to the commonly understood impacts of car use on mental health, this observation may unveil overlapping layers of spatial inequality and underscore the nuanced dynamics between transportation modes and adolescent mental well-being.