Mortality among sexual and gender minority populations: A systematic review.

Zachry, O''Brien, Clark, Ding, Blosnich. Mortality among sexual and gender minority populations: A systematic review. PLoS ONE. 2025 Feb 3; 20(2):e0307688, DOI: 10.1371/journal.pone.0307688.

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Abstract:

Sexual and gender minority (SGM) populations experience elevated rates of negative health outcomes (e.g., suicidality) and social determinants (e.g., poverty), which have been associated with general population mortality risk. Despite evidence of disparities in threats to well-being, it remains unclear whether SGM individuals have greater risk of mortality. This systematic review synthesized evidence on mortality among studies that included information about SGM. Three independent coders examined 6,255 abstracts, full-text reviewed 107 articles, and determined that 38 met inclusion criteria: 1) contained a sexual orientation or gender identity (SOGI) measure; 2) focused on a mortality outcome; 3) provided SGM vs non-SGM (i.e., exclusively heterosexual and cisgender) or general population comparisons of mortality outcomes; 4) were peer-reviewed; and 5) were available in English. A search of included articles'' references yielded 5 additional studies (total n = 43). The authors used the NIH''s Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies to assess included studies. Mortality outcomes included all-cause (n = 27), suicide/intentional self harm (n = 23), homicide (n = 7), and causes related to drug use (n = 3). Compared to non-SGM people, 14 studies (32.6%) supported higher mortality for SGM, 28 studies (65.1%) provided partial support of higher mortality for SGM (e.g., greater mortality from one cause but not another), one study (2.3%) found no evidence of higher mortality for SGM. There was considerable heterogeneity in operational definitions of SGM populations across studies. Although mixed, findings suggest elevated mortality for SGM versus non-SGM populations. Integrating SOGI measures into mortality surveillance would enhance understanding of disparities by standardizing data collection, thereby reducing heterogeneity and increasing capacity to aggregate results (e.g., meta-analyses).