JOURNAL ARTICLE
Embodiment and Erasure: Understanding Health Inequity for Queer and Trans Communities through a Queer Ecosocial Lens.
Published In: Health & Social Work, 2026, v. 51, n. 1. P. 31 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Hillier, Amy; McDonald, Kari; Shelton, Jama 3 of 3
Abstract
This article examines health disparities affecting queer and transgender (trans) communities through the lenses of ecosocial and queer theories, emphasizing the concepts of embodiment—how individuals incorporate social and environmental factors into their physical and mental health—and erasure, which refers to the invisibility imposed by healthcare systems and societal structures. It identifies key pathways contributing to health inequities, including cisnormativity and heteronormativity, institutional discrimination and structural violence, interpersonal violence and rejection, and internalized oppression, with particular focus on the role of healthcare services, training, and research. The article calls for systemic changes involving educators, researchers, funders, and clinicians to disrupt oppressive norms and practices, advocating for inclusive education, ethical research, equitable funding, and culturally competent healthcare to promote health equity for queer and trans people. It concludes by urging a radical reimagining of social institutions through queer theory’s praxis-oriented approach to foster accountability and justice in health and social systems.
Additional Information
- Source:Health & Social Work. 2026/02, Vol. 51, Issue 1, p31
- Document Type:Article
- Subject Area:Social Sciences and Humanities
- Publication Date:2026
- ISSN:0360-7283
- DOI:10.1093/hsw/hlaf049
- Accession Number:191655936
- Copyright Statement:Copyright of Health & Social Work is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.