Disrupted daily routines mediate the socioeconomic gradient of depression amid public health crises: A repeated cross-sectional study.

Abstract

OBJECTIVE\nThere is a socioeconomic gradient to depression risks, with more pronounced inequality amid macroenvironmental potential traumatic events. Between mid-2019 and mid-2020, the Hong Kong population experienced drastic societal changes, including the escalating civil unrest and the COVID-19 pandemic. We examined the change of the socioeconomic gradient in depression and the potential intermediary role of daily routine disruptions.\n\n\nMETHOD\nWe conducted repeated territory-wide telephone surveys in July 2019 and July 2020 with 1112 and 2034 population-representative Cantonese-speaking Hong Kong citizens above 15\u2009years old, respectively. Stratified by year, we examined the association between socioeconomic indicators (education attainment, household income, employment status and marital status) and probable depression (nine-item Patient Health Questionnaire [PHQ-9]\u2009⩾\u200910) using logistic regression. Differences in the socioeconomic gradient between 2019 and 2020 were tested. Finally, we performed a path analysis to test for the mediating role of daily routine disruptions.\n\n\nRESULTS\nLogistic regression showed that higher education attainment in 2019 and being married in 2020 were protective against probable depression. Interaction analysis showed that the inverse association of higher education attainment with probable depression attenuated in 2020 but that of being married increased. Path analysis showed that the mediated effects through daily routine disruptions accounted for 95.9% of the socioeconomic gradient of probable depression in 2020, compared with 13.1% in 2019.\n\n\nCONCLUSION\nFrom July 2019 to July 2020, the mediating role of daily routine disruptions in the socioeconomic gradient of depression in Hong Kong increased. It is thus implied that infection control measures should consider the relevant potential mental health impacts accordingly.