Exploring the association between epilepsy and depression: A systematic review and meta-analysis

PLoS One. 2022 Dec 15;17(12):e0278907. doi: 10.1371/journal.pone.0278907. eCollection 2022.

Abstract

Objective: This study offers meta-analytic data on the potential association between epilepsy and depression especially for the prevalence of depression in epilepsy or vice versa.

Methods: The relevant studies were searched and identified from nine electronic databases. Studies that mentioned the prevalence and/or incidence of epilepsy and depression were included. Hand searches were also included. The search language was English and the search time was through May 2022. Where feasible, random-effects models were used to generate pooled estimates.

Results: After screening electronic databases and other resources, 48 studies from 6,234 citations were included in this meta-analysis. The period prevalence of epilepsy ranged from 1% to 6% in patients with depression. In population-based settings, the pooled period prevalence of depression in patients with epilepsy was 27% (95% CI, 23-31) and 34% in clinical settings (95% CI, 30-39). Twenty studies reported that seizure frequency, low income, unemployment of the patients, perception of stigma, anxiety, being female, unmarried status, disease course, worse quality of life, higher disability scores, and focal-impaired awareness seizures were risk factors for depression.

Conclusion: Our study found that epilepsy was associated with an increased risk of depression. Depression was associated with the severity of epilepsy.

Publication types

  • Meta-Analysis
  • Systematic Review
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Depression / complications
  • Depression / epidemiology
  • Epilepsies, Partial*
  • Epilepsy* / complications
  • Epilepsy* / epidemiology
  • Female
  • Humans
  • Male
  • Quality of Life
  • Seizures / complications

Grants and funding

1. The S&T Program of Hebei (grant no. 20567625H) provided computer and related software for this work, and Lin Pei is the recipient of the funding awards. 2. Pei Lin National Famous and Old Chinese Medicine Expert Inheritance Studio provided databases search costs, and Lin Pei is the recipient of the funding awards. 3. Postgraduate Innovation Funding Project of Hebei University of Chinese Medicine (grant no. XCXZZBS2022011) provided training funding for the meta-analysis, and Shao-kun Qin is the recipient of the funding awards.