Year: 2025
Type: article
Abstract: In studies describing socioeconomic inequities in health outcomes, the choice of estimand and the planned analytic approach are central to the interpretability and policy relevance of findings. In this commentary, we aimed to highlight this by revisiting some of the choices made in the article by Eisenberg-Guyot and Renson (Am J Epidemiol. 2025;194(8):2440-2444) and presenting a discussion on how these choices impact the meaning of the inequity estimates obtained, in particular what they tell us about the world. These choices concern (1) the estimand in the presence of competing events (ie, the measure of inequity to be estimated), (2) the timescale with time-to-event outcomes, and (3) covariate adjustment. When describing inequities in health outcomes in the presence of competing events, it is indispensable to start with a clear research question and choosing the most relevant estimand to address it. This should then be followed by a study design and data analytic approaches that appropriately target that estimand. Following these steps will help avoid findings with obscure or misleading interpretation. This article is part of a Special Collection on Methods in Social Epidemiology.
Source: American Journal of Epidemiology
DOI: 10.1093/aje/kwaf090
Language: English
Subfield: Health
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $4,856
OpenAlex ID: W4409979581