Modeling mental health trajectories during the COVID-19 pandemic using UK-wide data in the presence of sociodemographic variables
Glenna Nightingale, Karthik Mohan, Eloi Ribe, Valentin Popov, Shakes Wang, Clara Calia, Luciana Brondi, Sohan Seth

TL;DR
This study analyzes how sociodemographic factors influenced mental health changes during COVID-19 in the UK, revealing significant disparities based on age, gender, income, and living situation, using longitudinal data and GAMs.
Contribution
It introduces a comprehensive analysis of mental health trajectories during COVID-19 in the UK, highlighting key sociodemographic determinants with advanced statistical modeling.
Findings
Women had higher GHQ36 scores than men.
Living without a partner was associated with worse mental health.
Lower income correlated with poorer mental health.
Abstract
Background: The negative effects of the COVID-19 pandemic on the mental health and well-being of populations are an important public health issue. Our study aims to determine the underlying factors shaping mental health trajectories during the COVID-19 pandemic in the UK. Methods: Data from the Understanding Society COVID-19 Study were utilized and the core analysis focussed on GHQ36 scores as the outcome variable. We used GAMs to evaluate trends over time and the role of sociodemographic variables, i.e., age, sex, ethnicity, country of residence (in UK), job status (employment), household income, living with a partner, living with children under age 16, and living with a long-term illness, on the variation of mental health during the study period. Results: Statistically significant differences in mental health were observed for age, sex,ethnicity, country of residence (in UK), job…
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Taxonomy
TopicsCOVID-19 and Mental Health · Mental Health Treatment and Access · Suicide and Self-Harm Studies
