The prevalence and risk of depression in aged COVID‐19 survivors: a bibliometric and meta‐analysis

Abstract

AbstractTo explore depression prevalence and related risk factors among elderly coronavirus disease 2019 (COVID‐19) survivors, while also evaluating research characteristics. We searched Web of Science, PubMed, Embase, Scopus, CNKI and Wanfang Data for studies that reported COVID‐19 and depression in older adults. ‘Bibliometrix’ facilitated bibliometric analysis and information visualisation. Random‐effects models merged depression prevalence and relevant risks. Publication bias and its impact were examined using funnel plots, Begg's test, Egger's linear regression, and trim‐and‐fill method. Meta‐regression, bubble plots, and Baujat plots probed heterogeneity. Sensitivity analysis applied the leave‐one‐out method. The study is registered with PROSPERO, CRD42023417706. The bibliometric analysis comprised 138 studies. Publication frequency peaked in the US, China, and Italy, reflecting significant growth. The meta‐analysis comprised 43 studies. Elderly COVID‐19 patients exhibit 28.33% depression prevalence (95% CI: 21.24–35.97). Severe cases (43.91%, 95% CI: 32.28–55.88) experienced higher depression prevalence than mild cases (16.45%, 95% CI: 11.92–21.50). Sex had no depression prevalence impact based on bubble plots. Notably, depression risk did not significantly differ between elderly and young COVID‐19 patients (odds ratio (OR) = 1.1808, 95% CI: 0.7323–1.9038). However, COVID‐19 infection emerged as a substantial elderly depression risk factor (OR = 1.8521, 95% CI: 1.2877–2.6639). Sensitivity analysis confirmed result robustness. Elderly COVID‐19 survivors are likely to develop depression symptoms with regional variations. Severe cases are associated with heightened depression prevalence. COVID‐19 infection stands out as a key elderly depression risk factor, while sex does not influence prevalence. The field's expansion necessitates sustained collaboration and extensive research endeavours.