Opinion Review
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World J Methodol. Mar 20, 2025; 15(1): 95796
Published online Mar 20, 2025. doi: 10.5662/wjm.v15.i1.95796
Reevaluating health metrics: Unraveling the limitations of disability-adjusted life years as an indicator in disease burden assessment
Ariel Beresniak, Dominique Bremond-Gignac, Danielle Dupont, Gerard Duru
Ariel Beresniak, Gerard Duru, Data Mining International, Geneva 1216, Switzerland
Dominique Bremond-Gignac, Department of Ophtalmology, Necker-Enfants Malades University Hospital, AP-HP, Paris-Cité University, INSERM, UMRS1138, Team 17, From Physiopathology of Ocular Diseases to Clinical Development, Sorbonne Paris Cité University, Centre de Recherche des Cordeliers, Paris 75015, France
Danielle Dupont, Data Mining America, Montreal H2Y, Canada
Author contributions: Beresniak A and Duru G conceived the methodological analyses; Duru G developed the theoretical framework; Bremond-Gignac D and Dupont D aided in the analysis and the interpretation; Beresniak A supervised the project and took the lead in writing the manuscript; All authors discussed the results and contributed to the final manuscript.
Conflict-of-interest statement: All authors have no conflicts of interest to disclose.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Ariel Beresniak, MD, PhD, CEO, Senior Researcher, Data Mining International, Data Mining International, Geneva 1216, Switzerland. aberesniak@datamining-international.com
Received: April 18, 2024
Revised: September 12, 2024
Accepted: September 23, 2024
Published online: March 20, 2025
Processing time: 163 Days and 15.6 Hours
Abstract

In 1993, the World Bank released a global report on the efficacy of health promotion, introducing the disability-adjusted life years (DALY) as a novel indicator. The DALY, a composite metric incorporating temporal and qualitative data, is grounded in preferences regarding disability status. This review delineates the algorithm used to calculate the value of the proposed DALY synthetic indicator and elucidates key methodological challenges associated with its application. In contrast to the quality-adjusted life years approach, derived from multi-attribute utility theory, the DALY stands as an independent synthetic indicator that adopts the assumptions of the Time Trade Off utility technique to define Disability Weights. Claiming to rely on no mathematical or economic theory, DALY users appear to have exempted themselves from verifying whether this indicator meets the classical properties required of all indicators, notably content validity, reliability, specificity, and sensitivity. The DALY concept emerged primarily to facilitate comparisons of the health impacts of various diseases globally within the framework of the Global Burden of Disease initiative, leading to numerous publications in international literature. Despite widespread adoption, the DALY synthetic indicator has prompted significant methodological concerns since its inception, manifesting in inconsistent and non-reproducible results. Given the substantial diffusion of the DALY indicator and its critical role in health impact assessments, a reassessment is warranted. This reconsideration is imperative for enhancing the robustness and reliability of public health decision-making processes.

Keywords: Disability adjusted life years; Cost-utility analyses; Outcome research; Public health; Burden of disease

Core Tip: Despite its adoption for conducting burden of disease studies, the disability-adjusted life years synthetic indicator has raised substantial methodological concerns since its introduction, leading to inconsistent and non-reproducible outcomes, and consequently, flawed results and public health rankings.