Increases in Prevalent Depressed Mood and Suicidal Ideation among Workers during the COVID-19 Pandemic-Findings from the California Health Interview Survey.
Kathryn GibbDavid Pham BuiXimena P VergaraPublished in: International journal of environmental research and public health (2023)
Limited data exist on COVID-19's mental health impact on non-healthcare workers. We estimated the prevalence of depressed mood and suicidal ideation experienced in the past year among California workers and assessed whether the prevalence changed during the COVID-19 pandemic. We analyzed 2013-2020 California Health Interview Survey data using survey-weighted methods to assess the change in the prevalence of depressed mood and suicidal ideation from 2019 to 2020 for working adults by demographics and occupational groups. We used trend-adjusted quasi-Poisson regressions and report rate ratios (RR), comparing the prevalence of outcomes during 2020 to the pre-pandemic period (2013-2019). We identified priority occupation groups with a higher-than-average outcome prevalence in 2020 and rate increases after adjusting for pre-pandemic trends. Our analysis included 168,768 respondents, of which 65% were workers. Production and service workers were the priority occupation groups for depressed mood (RR: 1.46, CI: 1.1-1.9; RR: 1.23, CI: 1.1-1.4) and suicidal ideation (RR: 1.86, CI: 1.0-3.6; RR: 1.47, CI: 1.1-1.9). Workers aged 45-65 years experienced over a 30% relative increase in both outcomes from 2019 to 2020. Depressed mood and suicidal ideation in the past year increased for production, service, and older workers during the pandemic. These groups should be considered for mental health interventions.
Keyphrases
- mental health
- coronavirus disease
- sars cov
- bipolar disorder
- risk factors
- healthcare
- sleep quality
- public health
- physical activity
- type diabetes
- mental illness
- magnetic resonance imaging
- computed tomography
- magnetic resonance
- depressive symptoms
- big data
- insulin resistance
- respiratory syndrome coronavirus
- climate change
- deep learning
- community dwelling