Longitudinal dynamics of depression in risk groups of older individuals during the COVID-19 pandemic

Abstract

Background: Older individuals are most at risk of severe COVID-19 and particularly require protection causing (self)restriction of psychosocial interaction in daily living. So far, the impact of psychosocial withdrawal on mental health seems less pronounced in community-dwelling older individuals compared to younger individuals. However, dynamics and adverse long-term effects of the pandemic, such as increases in depression, are still mostly unclear, especially for vulnerable subgroups.

Methods: Pre-pandemic and 3-, 8-, 14-, 20-month peri-pandemic data were analyzed in 877 older participants (age at 3-month peri-pandemic: mean ± SD: 72.3 ± 6.3, range: 58-91 years) of the observational prospective TREND study in Germany. Severity of depression (Beck's Depression Inventory-II scores) and key factors of (mental) health were investigated for cross-sectional associations using path modeling. Risk groups defined by resilience, loneliness, history of depression, stress, health status and fear of COVID-19 were investigated for differences in depression between timepoints.

Findings: The early pandemic (3-month) severity of depression was most strongly associated with history of depression, stress and resilience. Overall increases in clinically relevant depression (mild-severe) from pre- to 3-month peri-pandemic were small (% with depression at pre-/3-month peri-pandemic: 8.3%/11.5%). Changes were most pronounced in risk groups with low resilience (27.2%/41.8%), loneliness (19.0%/28.9%), fear of COVID-19 (17.6%/31.4%), high stress (24.4%/34.2%), a history of depression (27.7%/36.9%), and low health status (21.8%/31.4%). Changes in depression were largely observed from pre- to 3-month and were sustained to the 20-month peri-pandemic timepoint, overall and in stratified risk groups defined by single and cumulative risk factors. Changes between timepoints were heterogenous as indicated by alluvial diagrams.

Conclusion: Only specific risk groups of older individuals showed a large increase in depression during the COVID-19 pandemic. Since these increases occurred early in the pandemic and were sustained over 20 months, these vulnerable risk groups need to be prioritized for counselling and risk mitigation of depression.

Keywords: COVID-19; corona; depression; older population; pandemic; psychosocial factors; resilience; stress.

Figure 1

Timing of Coro-Q surveys and 7-day incidence rates of SARS-CoV2 infections in Germany and the state of Baden-Württemberg (residence area of TREND participants) as reported by the Robert-Koch-Institute.

Figure 2

Boxplots (A,C,E,G) and alluvial diagrams (B,D,F,H) for pre-pandemic and 3-, 8-,14-, 20-month peri-pandemic assessments of the (clinically relevant) severity of depression, loneliness, health status and physical activity. Asterisks and lines indicate significant (p < 0.00139, Bonferroni corrected) differences between timepoints (red: deterioration, blue: improvement). Tests for depression and health status in the alluvial diagram are based on categorized data as shown in the plot.

Figure 3

Path model of the severity of depression and relevant factors at the 3-month peri-pandemic timepoint. Numbers indicate standardized regression coefficients of the path model. Solid lines indicate positive effects and dashed lines negative effects. Line widths reflect effect sizes.

Figure 4

Prevalence (in %) of clinically relevant depression at pre- and 3-month peri-pandemic timepoints for dichotomized variables of the path model of depression severity. Abbreviations and subgrouping criteria are given in Table 2.

Figure 5

Boxplots (A,C,E,G) and alluvial diagrams (B,D,F,H) for pre-pandemic and 3-, 8-,14-, 20-months peri-pandemic assessments by subgroup defined by the number of risk factors of depression. Asterisks and lines indicate significant (p < 0.00139, Bonferroni corrected) differences between timepoints (red: deterioration, blue: improvement). Tests in the alluvial diagram are based on categorized data as shown in the plot.