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

To 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.