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Establishment of an indicator framework for global One Health Intrinsic Drivers index based on the grounded theory and fuzzy analytical hierarchy-entropy weight method

BACKGROUND: One Health has become a global consensus to deal with complex health problems. However, the progress of One Health implementation in many countries is still relatively slow, and there is a lack of systematic evaluation index. The purpose of this study was to establish an indicator framew...

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Autores principales: Feng, Jiaxin, Guo, Zhaoyu, Ai, Lin, Liu, Jingshu, Zhang, Xiaoxi, Cao, Chunli, Xu, Jing, Xia, Shang, Zhou, Xiao-Nong, Chen, Jin, Li, Shizhu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9733012/
https://www.ncbi.nlm.nih.gov/pubmed/36482389
http://dx.doi.org/10.1186/s40249-022-01042-3
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author Feng, Jiaxin
Guo, Zhaoyu
Ai, Lin
Liu, Jingshu
Zhang, Xiaoxi
Cao, Chunli
Xu, Jing
Xia, Shang
Zhou, Xiao-Nong
Chen, Jin
Li, Shizhu
author_facet Feng, Jiaxin
Guo, Zhaoyu
Ai, Lin
Liu, Jingshu
Zhang, Xiaoxi
Cao, Chunli
Xu, Jing
Xia, Shang
Zhou, Xiao-Nong
Chen, Jin
Li, Shizhu
author_sort Feng, Jiaxin
collection PubMed
description BACKGROUND: One Health has become a global consensus to deal with complex health problems. However, the progress of One Health implementation in many countries is still relatively slow, and there is a lack of systematic evaluation index. The purpose of this study was to establish an indicator framework for global One Health Intrinsic Drivers index (GOH-IDI) to evaluate human, animal and environmental health development process globally. METHOD: First, 82 studies were deeply analyzed by a grounded theory (GT) method, including open coding, axial coding, and selective coding, to establish a three-level indicator framework, which was composed of three selective codes, 19 axial codes, and 79 open codes. Then, through semi-structured interviews with 28 health-related experts, the indicators were further integrated and simplified according to the inclusion criteria of the indicators. Finally, the fuzzy analytical hierarchy process combined with the entropy weight method was used to assign weights to the indicators, thus, forming the evaluation indicator framework of human, animal and environmental health development process. RESULTS: An indicator framework for GOH-IDI was formed consisting of three selective codes, 15 axial codes and 61 open codes. There were six axial codes for “Human Health”, of which “Infectious Diseases” had the highest weight (19.76%) and “Injuries and Violence” had the lowest weight (11.72%). There were four axial codes for “Animal Health”, of which “Animal Epidemic Disease” had the highest weight (39.28%) and “Animal Nutritional Status” had the lowest weight (11.59%). Five axial codes were set under “Environmental Health”, among which, “Air Quality and Climate Change” had the highest weight (22.63%) and “Hazardous Chemicals” had the lowest weight (17.82%). CONCLUSIONS: An indicator framework for GOH-IDI was established in this study. The framework were universal, balanced, and scientific, which hopefully to be a tool for evaluation of the joint development of human, animal and environmental health in different regions globally. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40249-022-01042-3.
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spelling pubmed-97330122022-12-10 Establishment of an indicator framework for global One Health Intrinsic Drivers index based on the grounded theory and fuzzy analytical hierarchy-entropy weight method Feng, Jiaxin Guo, Zhaoyu Ai, Lin Liu, Jingshu Zhang, Xiaoxi Cao, Chunli Xu, Jing Xia, Shang Zhou, Xiao-Nong Chen, Jin Li, Shizhu Infect Dis Poverty Research Article BACKGROUND: One Health has become a global consensus to deal with complex health problems. However, the progress of One Health implementation in many countries is still relatively slow, and there is a lack of systematic evaluation index. The purpose of this study was to establish an indicator framework for global One Health Intrinsic Drivers index (GOH-IDI) to evaluate human, animal and environmental health development process globally. METHOD: First, 82 studies were deeply analyzed by a grounded theory (GT) method, including open coding, axial coding, and selective coding, to establish a three-level indicator framework, which was composed of three selective codes, 19 axial codes, and 79 open codes. Then, through semi-structured interviews with 28 health-related experts, the indicators were further integrated and simplified according to the inclusion criteria of the indicators. Finally, the fuzzy analytical hierarchy process combined with the entropy weight method was used to assign weights to the indicators, thus, forming the evaluation indicator framework of human, animal and environmental health development process. RESULTS: An indicator framework for GOH-IDI was formed consisting of three selective codes, 15 axial codes and 61 open codes. There were six axial codes for “Human Health”, of which “Infectious Diseases” had the highest weight (19.76%) and “Injuries and Violence” had the lowest weight (11.72%). There were four axial codes for “Animal Health”, of which “Animal Epidemic Disease” had the highest weight (39.28%) and “Animal Nutritional Status” had the lowest weight (11.59%). Five axial codes were set under “Environmental Health”, among which, “Air Quality and Climate Change” had the highest weight (22.63%) and “Hazardous Chemicals” had the lowest weight (17.82%). CONCLUSIONS: An indicator framework for GOH-IDI was established in this study. The framework were universal, balanced, and scientific, which hopefully to be a tool for evaluation of the joint development of human, animal and environmental health in different regions globally. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40249-022-01042-3. BioMed Central 2022-12-08 /pmc/articles/PMC9733012/ /pubmed/36482389 http://dx.doi.org/10.1186/s40249-022-01042-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Feng, Jiaxin
Guo, Zhaoyu
Ai, Lin
Liu, Jingshu
Zhang, Xiaoxi
Cao, Chunli
Xu, Jing
Xia, Shang
Zhou, Xiao-Nong
Chen, Jin
Li, Shizhu
Establishment of an indicator framework for global One Health Intrinsic Drivers index based on the grounded theory and fuzzy analytical hierarchy-entropy weight method
title Establishment of an indicator framework for global One Health Intrinsic Drivers index based on the grounded theory and fuzzy analytical hierarchy-entropy weight method
title_full Establishment of an indicator framework for global One Health Intrinsic Drivers index based on the grounded theory and fuzzy analytical hierarchy-entropy weight method
title_fullStr Establishment of an indicator framework for global One Health Intrinsic Drivers index based on the grounded theory and fuzzy analytical hierarchy-entropy weight method
title_full_unstemmed Establishment of an indicator framework for global One Health Intrinsic Drivers index based on the grounded theory and fuzzy analytical hierarchy-entropy weight method
title_short Establishment of an indicator framework for global One Health Intrinsic Drivers index based on the grounded theory and fuzzy analytical hierarchy-entropy weight method
title_sort establishment of an indicator framework for global one health intrinsic drivers index based on the grounded theory and fuzzy analytical hierarchy-entropy weight method
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9733012/
https://www.ncbi.nlm.nih.gov/pubmed/36482389
http://dx.doi.org/10.1186/s40249-022-01042-3
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