Causalidad en medicina: Modelos que cambian la forma de ver la enfermedad
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https://doi.org/10.29057/estr.v13i25.15880Palabras clave:
Causalidad, multicausalidad, determinantes sociales, sindémica, una sola saludResumen
El proceso salud-enfermedad y su comprensión requiere de modelos causales que exploren otras alternativas distintas al biomédico monocausal. Este ensayo revisa diversos enfoques contemporáneos que actualmente integran la multicausalidad, los determinantes sociales de la salud (DSS), la inferencia causal mediante los diagramas acíclicos dirigidos (DAGs), la perspectiva sindémica y el modelo “una sola salud”. Se expone que estos modelos, lejos de ser aislados, deben integrarse para hacer frente a los desafíos actuales como cambios poblacionales, ambientales y epidemiológicos. La integración de estos a partir del análisis y de la sensibilidad social y ecológica nos facilita explicar riesgos, orientar mejor las políticas equitativas y diseñar intervenciones efectivas.Descargas
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Ali, S., Li, Z., Moqueet, N., Moghadas, S. M., Galvani, A. P., Cooper, L. A., Stranges, S., Haworth-Brockman, M., Pinto, A. D., Asaria, M., Champredon, D., Hamilton, D., Moulin, M., & John-Baptiste, A. A. (2024). Incorporating Social Determinants of Health in Infectious Disease Models: A Systematic Review of Guidelines. Medical decision making : an international journal of the Society for Medical Decision Making, 44(7), 742–755. https://doi.org/10.1177/0272989X241280611
Brown, H.L., Pursley, I.G., Horton, D.L. et al. (2024). One health: a structured review and commentary on trends and themes. One Health Outlook 6, 17 https://doi.org/10.1186/s42522-024-00111-x
Bowie, C.y Friston K. (2025). Dynamic causal models in infectious disease epidemiology (Technical report). Wellcome Open Research. https://doi.org/10.12688/wellcomeopenres.19541.1
Bulled, N., & Singer, M. (2024). Conceptualizing COVID-19 syndemics: A scoping review. Global Advances in Health and Medicine, 13, 1–15. https://doi.org/10.1177/26335565241249835
CDC. (2024). Social Determinants of Health (SDOH). Centers for Disease Control and Prevention. https://www.cdc.gov/about/priorities/why-is-addressing-sdoh-important.html
Didelez, V. (2024). Invited commentary: Where do the causal DAGs come from? American Journal of Epidemiology, 193(8), 1075–1078. https://doi.org/10.1093/aje/kwae067
Fronteira, I., et al. (2021). The SARS-CoV-2 pandemic: A syndemic perspective. One Health, 13, 100283. https://doi.org/10.1016/j.onehlt.2021.100283
Kaufman, J. S., et al. (2024). Causal inference challenges in the relationship between education and health. Chronic Diseases and Injury in Canada, 44(3), 115–123. https://doi.org/10.1016/j.jcjd.2024.08.005
Kouser, H. N., Barnard-Mayers, R., & Murray, E. (2021). Complex systems models for causal inference in social epidemiology. Journal of Epidemiology and Community Health, 75(7), 702–708. https://doi.org/10.1136/jech-2019-
Milazzo, A., Liu, J., Multani, P., Steele, S., Hoon, E., & Chaber, A. L. (2025). One Health implementation: A systematic scoping review using the Quadripartite One Health Joint Plan of Action. One health (Amsterdam, Netherlands), 20, 101008. https://doi.org/10.1016/j.onehlt.2025.101008
Mubareka S., Amuasi J., Banerjee A., Carabin H., Copper J.J., Jardine C., Jaroszewicz B., Keefe G., Kotwa J., Kutz S, McGregor D, Mease A., Nicholson, Nowak K, Pickering B., Reed M.G., Saint-Charles J., Simonienko K, Trevor Smith T., Weese J.S., and Parmley E.J. (2023). Strengthening a One Health approach to emerging zoonoses. FACETS. 8: 1-64. https://doi.org/10.1139/facets-2021-0190
OMS. (2025, May 6). Social determinants of health. World Health Organization. https://www.who.int/news-room/fact-sheets/detail/social-determinants-of-health Organización Mundial de la Salud
OMS-OPS. (2020). Social determinants of health. Pan American Health Organization. https://www.paho.org/en/topics/social-determinants-health Paho
ONU (2025) Objetivos del desarrollo sostenible. Consultado el 15 d septiembre de 2025 desde: https://www.un.org/sustainabledevelopment/es/objetivos-de-desarrollo-sostenible/
Pearl, J. (2009). Causality: Models, reasoning, and inference (2nd ed.). Cambridge University Press.
Pepin, K. M., et al. (2024). Steps towards operationalizing One Health approaches. One Health, 16, 100512. https://doi.org/10.1016/j.onehlt.2024.100512
Pitt, S. J., Gunn A. (2024). The One Health concept. Journal of Infection Prevention, 25(1), 14–24. https://doi.org/10.1177/17571774231220967
Poppe, L., Steen, J., Loh, W. W., Crombez, G., De Block, F., Jacobs, N., Paepe, A. L. D. (2024). How to develop causal directed acyclic graphs for observational health research: a scoping review. Health Psychology Review, 19(1), 45–65. https://doi.org/10.1080/17437199.2024.240289
Tennant, P. W. G., Murray, E. J., Arnold, K. F., Berrie, L., Fox, M. P., Gadd, S. C., ... & Keogh, R. H. (2021). Use of directed acyclic graphs (DAGs) to identify confounders in applied health research. International Journal of Epidemiology, 50(2), 620–632. https://doi.org/10.1093/ije/dyaa213
Van Cauwenberg, J.,De Paepe A., Poppe L. (2023). It’s time to embrace causal thinking using directed acyclic graphs (DAGs). Journal of Epidemiology & Community Health, 77(12), 818–820. https://doi.org/10.1136/jech-2022-219851
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Derechos de autor 2025 Diana V. Sánchez-Martínez, Jesús C. Ruvalcava-Ledezma

Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-SinDerivadas 4.0.










