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Social determinants of health inequalities: towards a theoretical perspective using systems science

A systems approach offers a novel conceptualization to natural and social systems. In recent years, this has led to perceiving population health outcomes as an emergent property of a dynamic and open, complex adaptive system. The current paper explores these themes further and applies the principles...

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Autor principal: Jayasinghe, Saroj
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4549102/
https://www.ncbi.nlm.nih.gov/pubmed/26303914
http://dx.doi.org/10.1186/s12939-015-0205-8
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author Jayasinghe, Saroj
author_facet Jayasinghe, Saroj
author_sort Jayasinghe, Saroj
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description A systems approach offers a novel conceptualization to natural and social systems. In recent years, this has led to perceiving population health outcomes as an emergent property of a dynamic and open, complex adaptive system. The current paper explores these themes further and applies the principles of systems approach and complexity science (i.e. systems science) to conceptualize social determinants of health inequalities. The conceptualization can be done in two steps: viewing health inequalities from a systems approach and extending it to include complexity science. Systems approach views health inequalities as patterns within the larger rubric of other facets of the human condition, such as educational outcomes and economic development. This anlysis requires more sophisticated models such as systems dynamic models. An extension of the approach is to view systems as complex adaptive systems, i.e. systems that are 'open' and adapt to the environment. They consist of dynamic adapting subsystems that exhibit non-linear interactions, while being 'open' to a similarly dynamic environment of interconnected systems. They exhibit emergent properties that cannot be estimated with precision by using the known interactions among its components (such as economic development, political freedom, health system, culture etc.). Different combinations of the same bundle of factors or determinants give rise to similar patterns or outcomes (i.e. property of convergence), and minor variations in the initial condition could give rise to widely divergent outcomes. Novel approaches using computer simulation models (e.g. agent-based models) would shed light on possible mechanisms as to how factors or determinants interact and lead to emergent patterns of health inequalities of populations.
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spelling pubmed-45491022015-08-26 Social determinants of health inequalities: towards a theoretical perspective using systems science Jayasinghe, Saroj Int J Equity Health Commentary A systems approach offers a novel conceptualization to natural and social systems. In recent years, this has led to perceiving population health outcomes as an emergent property of a dynamic and open, complex adaptive system. The current paper explores these themes further and applies the principles of systems approach and complexity science (i.e. systems science) to conceptualize social determinants of health inequalities. The conceptualization can be done in two steps: viewing health inequalities from a systems approach and extending it to include complexity science. Systems approach views health inequalities as patterns within the larger rubric of other facets of the human condition, such as educational outcomes and economic development. This anlysis requires more sophisticated models such as systems dynamic models. An extension of the approach is to view systems as complex adaptive systems, i.e. systems that are 'open' and adapt to the environment. They consist of dynamic adapting subsystems that exhibit non-linear interactions, while being 'open' to a similarly dynamic environment of interconnected systems. They exhibit emergent properties that cannot be estimated with precision by using the known interactions among its components (such as economic development, political freedom, health system, culture etc.). Different combinations of the same bundle of factors or determinants give rise to similar patterns or outcomes (i.e. property of convergence), and minor variations in the initial condition could give rise to widely divergent outcomes. Novel approaches using computer simulation models (e.g. agent-based models) would shed light on possible mechanisms as to how factors or determinants interact and lead to emergent patterns of health inequalities of populations. BioMed Central 2015-08-25 /pmc/articles/PMC4549102/ /pubmed/26303914 http://dx.doi.org/10.1186/s12939-015-0205-8 Text en © Jayasinghe. 2015 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Commentary
Jayasinghe, Saroj
Social determinants of health inequalities: towards a theoretical perspective using systems science
title Social determinants of health inequalities: towards a theoretical perspective using systems science
title_full Social determinants of health inequalities: towards a theoretical perspective using systems science
title_fullStr Social determinants of health inequalities: towards a theoretical perspective using systems science
title_full_unstemmed Social determinants of health inequalities: towards a theoretical perspective using systems science
title_short Social determinants of health inequalities: towards a theoretical perspective using systems science
title_sort social determinants of health inequalities: towards a theoretical perspective using systems science
topic Commentary
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4549102/
https://www.ncbi.nlm.nih.gov/pubmed/26303914
http://dx.doi.org/10.1186/s12939-015-0205-8
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