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A growing number of studies have investigated the relationship between commuting to work and mental health, usually with cross-sectional data. In these studies, lengthy commutes are typically associated with stress, time scarcity, and lower well-being. However, the more salient measures of mental health, such as the likelihood of depression, have been more rarely studied, and longitudinal data, which have the potential to provide more robust causal inference, have typically not been used. Using data from the 2016 and 2018 China Family Panel Studies, I examine the relationship between commuting and depression employing multinomial logistic regressions. My findings challenge the existing literature. Controlling for life events, sociodemographic characteristics, and neighborhood satisfaction, individuals who increased their commute distances were more likely to enter any level of depression and major depression than those without a change, consistent with current studies. However, a reduction in commute distance was also significantly associated with an increased onset of major depression and a lower probability of recovery. Higher income moderates these pathways by reducing the risk of an increase in commute distance on entering depression in general and a decrease in commute distance on entering major depression. Furthermore, major life events confound these relationships. For example, individuals who changed jobs and moved house were more likely to enter general depression. These results suggest the complexity of the relationship between travel and mental health, a complexity the literature needs to address.
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Yage Liu (2026) studied this question.
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