Gender inequality and depression among medical students: A global meta-regression analysis

J Psychiatr Res. 2019 Apr:111:36-43. doi: 10.1016/j.jpsychires.2019.01.013. Epub 2019 Jan 11.

Abstract

Depression is a serious mental health problem with a high prevalence among medical students. It is unclear whether a gender disparity of depression exists in this population, and whether gender inequality influences depression estimates by gender. We conducted a systematic search for published systematic reviews or meta-analyses in six databases and primary studies were obtained from those records. Studies were included if they contained original data on the prevalence of depression among male and female medical students. The Gender Inequality Index (GII) and the Human Development Index (HDI) were obtained from the United Nations Development Programme website. A random effects meta-analysis of the odds ratio for depression between females and males was conducted. Meta-regression analyses were conducted to assess the association of GII and prevalence of depression. The HDI was later incorporated in a multivariable model. We included a total of 106 studies and 84,119 students from 32 different countries. Female medical students are at higher odds of depression (OR = 1.30, 95% CI 1.17-1.44, p < 0.01). A significant correlation was found between GII and prevalence of depression for female (β = 0.24, p = 0.02) medical students, but not for male medical students. This association remained significant after adjusting for HDI. The female gender was associated with higher prevalence of depression in this population. The gender disparity in depression may be explained by the effect of gender inequality.

Keywords: Depression; Gender; Medical students; Public health; Socio-economic factors.

Publication types

  • Meta-Analysis

MeSH terms

  • Adult
  • Depression / epidemiology*
  • Depressive Disorder / epidemiology*
  • Female
  • Human Development*
  • Humans
  • Male
  • Socioeconomic Factors*
  • Students, Medical / statistics & numerical data*
  • Women*
  • Young Adult