Volume 18, Issue 4 (Vol.18, No.4, Winter 2023)
irje 2023, 18(4): 255-269 |
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Salehnia N, Assari Arani A, Sadeghi Saghdel H, Olyaeemanesh A. Fuzzy Cognitive Map of Macro Determinants of Population Health in Iran. irje 2023; 18 (4) :255-269
URL: http://irje.tums.ac.ir/article-1-7172-en.html
URL: http://irje.tums.ac.ir/article-1-7172-en.html
1- PhD of Health Economics, Department of Economic Development and Planning, Faculty of Management and Economics, Tarbiat Modares University, Tehran, Iran , N.salehnia@modares.ac.ir
2- Associate Professor, Department of Economic Development and Planning, Faculty of Management and Economics, Tarbiat Modares University, Tehran, Iran
3- Professor, National Institute for Health Research & Health Equity Research Centre, Tehran University of Medical Sciences, Tehran, Iran
2- Associate Professor, Department of Economic Development and Planning, Faculty of Management and Economics, Tarbiat Modares University, Tehran, Iran
3- Professor, National Institute for Health Research & Health Equity Research Centre, Tehran University of Medical Sciences, Tehran, Iran
Abstract: (653 Views)
Background and Objectives: Health promotion is a crucial task for policymakers. Therefore, this study aims to identify the key factors that determine population health in Iran and illustrate the causal relationships between these factors.
Methods: The research was conducted using a mixed-method approach in three stages. First, macro social determinants of health were identified by analyzing available resources from 2000 to 2019. Screening of factors was carried out through the fuzzy Delphi method and a survey involving 15 experts. Finally, the causal relationships between the social determinants of health were depicted using a fuzzy cognitive map.
Results: Initially, 96 health determinants were identified at the national and global levels. After the screening, 8 factors that had less significance in population health were excluded. In terms of causal relationships, the economic system emerged as the most important and influential factor, with a centrality degree of 21.06 and an out-degree of 10.91. Following that, governance and policy-making, as well as national policies, were ranked with centrality degrees of 20.25 and 20.19, respectively.
Conclusion: Irrespective of the causal relationships, the health system holds the utmost importance in population health. However, when considering the causal relationships, the economic system takes precedence as the most critical factor, while the health system does not rank among the top three factors. Therefore, the analysis of fuzzy cognitive maps assists policymakers in understanding priorities and the interconnectedness between sectors in developing and implementing health-oriented policies across all sectors, enabling the adoption of the most effective policies.
Methods: The research was conducted using a mixed-method approach in three stages. First, macro social determinants of health were identified by analyzing available resources from 2000 to 2019. Screening of factors was carried out through the fuzzy Delphi method and a survey involving 15 experts. Finally, the causal relationships between the social determinants of health were depicted using a fuzzy cognitive map.
Results: Initially, 96 health determinants were identified at the national and global levels. After the screening, 8 factors that had less significance in population health were excluded. In terms of causal relationships, the economic system emerged as the most important and influential factor, with a centrality degree of 21.06 and an out-degree of 10.91. Following that, governance and policy-making, as well as national policies, were ranked with centrality degrees of 20.25 and 20.19, respectively.
Conclusion: Irrespective of the causal relationships, the health system holds the utmost importance in population health. However, when considering the causal relationships, the economic system takes precedence as the most critical factor, while the health system does not rank among the top three factors. Therefore, the analysis of fuzzy cognitive maps assists policymakers in understanding priorities and the interconnectedness between sectors in developing and implementing health-oriented policies across all sectors, enabling the adoption of the most effective policies.
Keywords: Social determinant of health, Fuzzy cognitive map, Fuzzy Delphi, Qualitative content analysis, Population health
Type of Study: Research |
Subject:
General
Received: 2022/11/15 | Accepted: 2023/03/1 | Published: 2023/03/1
Received: 2022/11/15 | Accepted: 2023/03/1 | Published: 2023/03/1
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