Prevalence of depression morbidity among Brazilian adults: A systematic review and meta-analysis

Marcus T. Silva, Tais F. Galvao, Silvia S. Martins, Mauricio G. Pereira

Research output: Contribution to journalReview articlepeer-review

59 Scopus citations

Abstract

Objective: To estimate the prevalence of depressive symptoms and major depressive disorder, as assessed in population-based cross-sectional studies of Brazilian adults. Methods: We performed a systematic review of the literature. The major databases were searched up through October 2013. Two researchers selected the studies, extracted the data, and assessed their methodological quality. Meta-analyses were performed using random effects. Results: Of the 2,971 records retrieved, we selected 27 studies that assessed the prevalence of depression morbidity in 464,734 individuals (66% women). Eleven different screening tools were used to assess depression morbidity. The prevalence of depressive symptoms was 14% (95% confidence interval [95%CI] 13-16; I2 = 99.5%), whereas the 1-year prevalence of major depressive disorder was 8% (95%CI 7-10; I2 = 86.7%), and the lifetime prevalence of major depressive disorder was 17% (95%CI 14-19; I2 = 91.6%). All rates were higher in women than in men. No causes of heterogeneity could be identified. Conclusion: Depression morbidity was common among Brazilian adults, and affects more women than men. Inconsistencies across studies highlight the need for standardization of future research. Clinicians should routinely investigate for the presence of depression morbidity in this population.

Original languageEnglish (US)
Pages (from-to)262-270
Number of pages9
JournalRevista Brasileira de Psiquiatria
Volume36
Issue number3
DOIs
StatePublished - 2014

Keywords

  • Adults
  • Brazil
  • Depression
  • Major depressive disorder
  • Prevalence

ASJC Scopus subject areas

  • Psychiatry and Mental health

Fingerprint

Dive into the research topics of 'Prevalence of depression morbidity among Brazilian adults: A systematic review and meta-analysis'. Together they form a unique fingerprint.

Cite this