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Distribution of nursing workforce in the world using Gini coefficient

INTRODUCTION: Unequal Access to human resources for health, reduces access to healthcare services, worsens the quality of services and reduces health outcomes. This study aims to investigate the distribution of the nursing workforce around the world. METHODS: This is a descriptive-analytical study,...

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Autores principales: Kharazmi, Erfan, Bordbar, Najmeh, Bordbar, Shima
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10161512/
https://www.ncbi.nlm.nih.gov/pubmed/37147626
http://dx.doi.org/10.1186/s12912-023-01313-w
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author Kharazmi, Erfan
Bordbar, Najmeh
Bordbar, Shima
author_facet Kharazmi, Erfan
Bordbar, Najmeh
Bordbar, Shima
author_sort Kharazmi, Erfan
collection PubMed
description INTRODUCTION: Unequal Access to human resources for health, reduces access to healthcare services, worsens the quality of services and reduces health outcomes. This study aims to investigate the distribution of the nursing workforce around the world. METHODS: This is a descriptive-analytical study, which was conducted in 2021. The number of nurses and world populations was gathered from World Health Organization (WHO) and The United Nations (UN) databases. The UN has divided world countries based on the Human Development Index (HDI) into four categories of very high, high, medium and low HDI. To investigate the distribution of the nurses around the world, we used the nurse population ratio (per 10,000 population), Gini coefficient, Lorenz curve and Pareto curve. FINDINGS: On average, there were 38.6 nurses for every 10,000 people in the world. Nations with the very high HDI, had the highest nurse/population ratio (95/10,000), while the low HDI nations had the lowest nurse/population ratio (7/10,000). Most nurses around the world were females (76.91%) who were in the age group of 35–44 (29.1%). The Gini coefficient of nations in the each four HDI categories varied from 0.217 to 0.283. The Gini coefficient of the nations between the four HDI categories was 0.467, and the Gini coefficient of the whole world was 0.667. CONCLUSION: There were inequalities between countries all over the world. Policymakers should focus on the equitable distribution of the nursing workforce across all local, national and regional levels.
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spelling pubmed-101615122023-05-06 Distribution of nursing workforce in the world using Gini coefficient Kharazmi, Erfan Bordbar, Najmeh Bordbar, Shima BMC Nurs Research INTRODUCTION: Unequal Access to human resources for health, reduces access to healthcare services, worsens the quality of services and reduces health outcomes. This study aims to investigate the distribution of the nursing workforce around the world. METHODS: This is a descriptive-analytical study, which was conducted in 2021. The number of nurses and world populations was gathered from World Health Organization (WHO) and The United Nations (UN) databases. The UN has divided world countries based on the Human Development Index (HDI) into four categories of very high, high, medium and low HDI. To investigate the distribution of the nurses around the world, we used the nurse population ratio (per 10,000 population), Gini coefficient, Lorenz curve and Pareto curve. FINDINGS: On average, there were 38.6 nurses for every 10,000 people in the world. Nations with the very high HDI, had the highest nurse/population ratio (95/10,000), while the low HDI nations had the lowest nurse/population ratio (7/10,000). Most nurses around the world were females (76.91%) who were in the age group of 35–44 (29.1%). The Gini coefficient of nations in the each four HDI categories varied from 0.217 to 0.283. The Gini coefficient of the nations between the four HDI categories was 0.467, and the Gini coefficient of the whole world was 0.667. CONCLUSION: There were inequalities between countries all over the world. Policymakers should focus on the equitable distribution of the nursing workforce across all local, national and regional levels. BioMed Central 2023-05-05 /pmc/articles/PMC10161512/ /pubmed/37147626 http://dx.doi.org/10.1186/s12912-023-01313-w Text en © The Author(s) 2023 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
Kharazmi, Erfan
Bordbar, Najmeh
Bordbar, Shima
Distribution of nursing workforce in the world using Gini coefficient
title Distribution of nursing workforce in the world using Gini coefficient
title_full Distribution of nursing workforce in the world using Gini coefficient
title_fullStr Distribution of nursing workforce in the world using Gini coefficient
title_full_unstemmed Distribution of nursing workforce in the world using Gini coefficient
title_short Distribution of nursing workforce in the world using Gini coefficient
title_sort distribution of nursing workforce in the world using gini coefficient
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10161512/
https://www.ncbi.nlm.nih.gov/pubmed/37147626
http://dx.doi.org/10.1186/s12912-023-01313-w
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