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Treffer: Descriptive social epidemiology: putting the question before the methods.

Title:
Descriptive social epidemiology: putting the question before the methods.
Authors:
Dashti SG; Clinical Epidemiology and Biostatistics Unit, Murdoch Children's Research Institute, Melbourne, VIC, Australia.; Department of Pediatrics, University of Melbourne, Melbourne, VIC, Australia., Moreno-Betancur M; Clinical Epidemiology and Biostatistics Unit, Murdoch Children's Research Institute, Melbourne, VIC, Australia.; Department of Pediatrics, University of Melbourne, Melbourne, VIC, Australia.
Source:
American journal of epidemiology [Am J Epidemiol] 2025 Aug 05; Vol. 194 (8), pp. 2150-2153.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Oxford University Press Country of Publication: United States NLM ID: 7910653 Publication Model: Print Cited Medium: Internet ISSN: 1476-6256 (Electronic) Linking ISSN: 00029262 NLM ISO Abbreviation: Am J Epidemiol Subsets: MEDLINE
Imprint Name(s):
Publication: Cary, NC : Oxford University Press
Original Publication: Baltimore, School of Hygiene and Public Health of Johns Hopkins Univ.
Grant Information:
ID 2009572 National Health and Medical Research Council (NHMRC) Investigator Grants; ID 2027171 National Health and Medical Research Council (NHMRC) Investigator Grants
Contributed Indexing:
Keywords: competing risks; descriptive epidemiology; health disparities; health inequities; mortality; social epidemiology
Entry Date(s):
Date Created: 20250430 Date Completed: 20250826 Latest Revision: 20250826
Update Code:
20250827
DOI:
10.1093/aje/kwaf090
PMID:
40302109
Database:
MEDLINE

Weitere Informationen

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.
(© The Author(s) 2025. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)