Suicide rates among physicians: a quantitative and gender assessment (meta-analysis)

Am J Psychiatry. 2004 Dec;161(12):2295-302. doi: 10.1176/appi.ajp.161.12.2295.

Abstract

Objective: Physicians' suicide rates have repeatedly been reported to be higher than those of the general population or other academics, but uncertainty remains. In this study, physicians' suicide rate ratios were estimated with a meta-analysis and systematic quality assessment of recent studies.

Method: Studies of physicians' suicide rates were located in MEDLINE, PsycINFO, AARP Ageline, and the EBM Reviews: Cochrane Database of Systematic Reviews with the terms "physicians," "doctors," "suicide," and "mortality." Studies were included if they were published in or after 1960 and gave estimates of age-standardized suicide rates of physicians and their reference population or reported extractable data on physicians' suicide; 25 studies met the criteria. Reviewers extracted data and scored each study for quality. The studies were tested for heterogeneity and publication bias and were stratified by publication year, follow-up, and study quality. Effect sizes were pooled by using fixed-effects (women) and random-effects (men) models.

Results: The aggregate suicide rate ratio for male physicians, compared to the general population, was 1.41, with a 95% confidence interval (CI) of 1.21-1.65. For female physicians the ratio was 2.27 (95% CI=1.90-2.73). Visual inspection of funnel plots from tests of publication bias revealed randomness for men but some indication of bias for women, with a relative, nonsignificant lack of studies in the lower right quadrant.

Conclusions: Studies on physicians' suicide collectively show modestly (men) to highly (women) elevated suicide rate ratios. Larger studies should help clarify whether female physicians' suicide rate is truly elevated or can be explained by publication bias.

Publication types

  • Comparative Study
  • Meta-Analysis

MeSH terms

  • Cause of Death
  • Cross-Cultural Comparison
  • Data Collection / methods
  • Female
  • Humans
  • Male
  • Physicians / statistics & numerical data*
  • Physicians, Women / statistics & numerical data*
  • Publication Bias
  • Registries / statistics & numerical data
  • Sex Distribution
  • Sex Factors
  • Suicide / statistics & numerical data*