Depression deterioration of older adults during the first wave of the COVID-19 outbreak in Europe.

RATIONALE

Determining who is particularly vulnerable to mental health deterioration during the COVID-19 pandemic is essential when designing and targeting interventions to mitigate the adverse psychological impacts of the outbreak. Older people have appeared to be less exposed to mental health deterioration compared with younger individuals, but most exposed to the risk of severe illness and death from the virus, as well as less equipped to use technologies for coping with lockdown measures.

OBJECTIVE

Amongst the old population, we aim at determining how depressive symptoms have changed during the first wave of the COVID-19 pandemic and identifying individual risk factors associated with changes in reporting depression. We are particularly interested in exploring the role of pre-existing mental health problems and evaluating gender differences.

METHOD

Data come from the Survey of Health, Ageing and Retirement in Europe, in particular from the first COVID-19 survey administered in summer 2020. Logistic models are estimated and Average Marginal Effects computed to take the degree of individual unobserved heterogeneity into account comparing point estimates across samples. Multiple Imputation (implemented through Multivariate Imputation by Chained Equations) is used to replace missing data. Statistical power of the effect sizes is estimated by a simulation approach.

RESULTS

Pre-existing mental health problems, a diagnosis of affective/emotional disorders, a recent diagnosis of a major illness, and (only for men) job loss during the first wave of the outbreak are the most important risk factors. Statistical differences between genders emerge, with women experiencing higher levels of depression and greater worsening of mental health than men.

CONCLUSIONS

To identify people at greater risk of depression deterioration during an outbreak it is very important to consider their pre-existing mental and general health, distinguishing severity level. On population level, it is also crucial to evaluate depression disorders separately by gender.