SynthesisInternational journal for equity in health2023
Utilising quantitative methods to study the intersectionality of multiple social disadvantages in women with common mental disorders: a systematic review.
Synthesis in International journal for equity in health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 5 citations in OpenAlex.
- Beyond the Individual: The Weight of Social and Structural Determinants of Depression Among Transgender Women Living with HIV in France (ANRS-Trans&HIV).AIDS and behavior · 2026Observational
- Connecting the Dots: Exploring the Association between Perceived Discrimination and Physical and Psychological Well-Being Among Doctoral Trainees and Postdoctoral Fellows in Biomedical Fields.Journal of diversity in higher education · 2026Article
- Assessing intersectional disparities in obesity among Brazilian adults: a MAIHDA approach.Cadernos de saude publica · 2026Article
- The Association Between Social Determinants of Health (SDoH) and Mental Health Status in the US.European journal of investigation in health, psychology and education · 2025Article
- Moderation of financial stress and cardiovascular disease risk in black catholics: A social-ecological pathway utilizing latent class and structural equation analyses.PLOS mental health · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Women are at greater risk of common mental disorders. The intersectionality concept provides a framework to examine the effects of multiple social disadvantages on women's mental health. We conducted a systematic review to collect and analyse information to identify the quantitative methodologies and study designs used in intersectional research to examine women's mental health and multiple social disadvantages. Included studies used accepted statistical methods to explore the intersectional effects of gender and one or more types of social disadvantage from the PROGRESS-Plus inequity framework: a place of residence, race/ethnicity, occupation, gender/ sex, religion, education, socioeconomic status, social capital (O'Neill et al. J Clin Epidemiol 67:56-64, 2014). The scope of this systematic review was limited to studies that analysed common mental disorders in women and men comparatively. Studies focusing on only one gender were excluded, ensuring a comprehensive comparative analysis of the intersection of social disadvantages in mental health.Twelve papers were included in the narrative synthesis (Table 1). Eight of the included papers (67%) reported an intersectional effect of gender and one or more additional types of social disadvantage. The multiplicative effect of gender and socioeconomic status on the risk of common mental disorders was the most commonly reported interaction. This systematic review shows that multiplicative and simultaneous interactions of multiple social disadvantage increase the risk of common mental disorders experienced by women. Moreover, it underlines the potential for quantitative research methods to complement qualitative intersectionality research on gender and mental health. The findings of this systematic review highlight the importance of multiple social disadvantage in understanding the increased risk of mental health experienced by women.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.