Madina Agénor is a social epidemiologist based in the USA specialising in sexual and reproductive health. Using secondary quantitative data from a large national survey, Agénor and her colleagues (2015: 728-730) observed lower uptake of cervical cancer screening among black lesbian, bisexual and queer (LBQ) women relative to black heterosexual women.

Her work offers an excellent example of how research findings can inform recommendations for action to reduce social inequalities in health. These included:

During the clinical encounter

Providers should take the time to build a relationship with black LBQ women by getting to know them as individuals and asking non-judgmental questions about their lives, and should avoid making heteronormative assumptions about women’s sexual orientation and take the initiative to ask non-heterosexist questions about their sexual activity, female and male sexual partners (both past and current), and sexual behavior (both past and current).

Education and continued professional development

General practitioners and ob/gyns alike should receive training in LBQ women’s sexuality and sexual health during medical or nursing school, residency, and continuing education. Health care education programs should train clinicians in the area of anti-sexist, anti-racist, and anti-classist, patient-centered communication that reflects an understanding of and respect for women, people of color, and low-income individuals and fosters comfort, safety, and trust among patients from marginalized groups.

Expanding the diversity of the workforce

Given many black LBQ women’s preference for black and/or LBQ female providers, health care institutions should focus on increasing the supply of women of color and LBQ clinicians in the U.S. by facilitating access to medical and nursing education among populations who are marginalized as a result of their gender, race/ethnicity, sexual orientation, and/or social class.

This work also illustrates the importance of integrating intersecting dimensions of inequalities in research questions and shows options for exploring structural drivers of unequal experiences when relevant data are not available in secondary data sources (HIAT section 4).