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Hierarchical cluster analysis of labour market regulations and population health: a taxonomy of low- and middle-income countries
BACKGROUND: An important contribution of the social determinants of health perspective has been to inquire about non-medical determinants of population health. Among these, labour market regulations are of vital significance. In this study, we investigate the labour market regulations among low- and...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3349504/ https://www.ncbi.nlm.nih.gov/pubmed/22512892 http://dx.doi.org/10.1186/1471-2458-12-286 |
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author | Muntaner, Carles Chung, Haejoo Benach, Joan Ng, Edwin |
author_facet | Muntaner, Carles Chung, Haejoo Benach, Joan Ng, Edwin |
author_sort | Muntaner, Carles |
collection | PubMed |
description | BACKGROUND: An important contribution of the social determinants of health perspective has been to inquire about non-medical determinants of population health. Among these, labour market regulations are of vital significance. In this study, we investigate the labour market regulations among low- and middle-income countries (LMICs) and propose a labour market taxonomy to further understand population health in a global context. METHODS: Using Gross National Product per capita, we classify 113 countries into either low-income (n = 71) or middle-income (n = 42) strata. Principal component analysis of three standardized indicators of labour market inequality and poverty is used to construct 2 factor scores. Factor score reliability is evaluated with Cronbach's alpha. Using these scores, we conduct a hierarchical cluster analysis to produce a labour market taxonomy, conduct zero-order correlations, and create box plots to test their associations with adult mortality, healthy life expectancy, infant mortality, maternal mortality, neonatal mortality, under-5 mortality, and years of life lost to communicable and non-communicable diseases. Labour market and health data are retrieved from the International Labour Organization's Key Indicators of Labour Markets and World Health Organization's Statistical Information System. RESULTS: Six labour market clusters emerged: Residual (n = 16), Emerging (n = 16), Informal (n = 10), Post-Communist (n = 18), Less Successful Informal (n = 22), and Insecure (n = 31). Primary findings indicate: (i) labour market poverty and population health is correlated in both LMICs; (ii) association between labour market inequality and health indicators is significant only in low-income countries; (iii) Emerging (e.g., East Asian and Eastern European countries) and Insecure (e.g., sub-Saharan African nations) clusters are the most advantaged and disadvantaged, respectively, with the remaining clusters experiencing levels of population health consistent with their labour market characteristics. CONCLUSIONS: The labour market regulations of LMICs appear to be important social determinant of population health. This study demonstrates the heuristic value of understanding the labour markets of LMICs and their health effects using exploratory taxonomy approaches. |
format | Online Article Text |
id | pubmed-3349504 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-33495042012-05-11 Hierarchical cluster analysis of labour market regulations and population health: a taxonomy of low- and middle-income countries Muntaner, Carles Chung, Haejoo Benach, Joan Ng, Edwin BMC Public Health Research Article BACKGROUND: An important contribution of the social determinants of health perspective has been to inquire about non-medical determinants of population health. Among these, labour market regulations are of vital significance. In this study, we investigate the labour market regulations among low- and middle-income countries (LMICs) and propose a labour market taxonomy to further understand population health in a global context. METHODS: Using Gross National Product per capita, we classify 113 countries into either low-income (n = 71) or middle-income (n = 42) strata. Principal component analysis of three standardized indicators of labour market inequality and poverty is used to construct 2 factor scores. Factor score reliability is evaluated with Cronbach's alpha. Using these scores, we conduct a hierarchical cluster analysis to produce a labour market taxonomy, conduct zero-order correlations, and create box plots to test their associations with adult mortality, healthy life expectancy, infant mortality, maternal mortality, neonatal mortality, under-5 mortality, and years of life lost to communicable and non-communicable diseases. Labour market and health data are retrieved from the International Labour Organization's Key Indicators of Labour Markets and World Health Organization's Statistical Information System. RESULTS: Six labour market clusters emerged: Residual (n = 16), Emerging (n = 16), Informal (n = 10), Post-Communist (n = 18), Less Successful Informal (n = 22), and Insecure (n = 31). Primary findings indicate: (i) labour market poverty and population health is correlated in both LMICs; (ii) association between labour market inequality and health indicators is significant only in low-income countries; (iii) Emerging (e.g., East Asian and Eastern European countries) and Insecure (e.g., sub-Saharan African nations) clusters are the most advantaged and disadvantaged, respectively, with the remaining clusters experiencing levels of population health consistent with their labour market characteristics. CONCLUSIONS: The labour market regulations of LMICs appear to be important social determinant of population health. This study demonstrates the heuristic value of understanding the labour markets of LMICs and their health effects using exploratory taxonomy approaches. BioMed Central 2012-04-18 /pmc/articles/PMC3349504/ /pubmed/22512892 http://dx.doi.org/10.1186/1471-2458-12-286 Text en Copyright ©2011 Muntaner et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Muntaner, Carles Chung, Haejoo Benach, Joan Ng, Edwin Hierarchical cluster analysis of labour market regulations and population health: a taxonomy of low- and middle-income countries |
title | Hierarchical cluster analysis of labour market regulations and population health: a taxonomy of low- and middle-income countries |
title_full | Hierarchical cluster analysis of labour market regulations and population health: a taxonomy of low- and middle-income countries |
title_fullStr | Hierarchical cluster analysis of labour market regulations and population health: a taxonomy of low- and middle-income countries |
title_full_unstemmed | Hierarchical cluster analysis of labour market regulations and population health: a taxonomy of low- and middle-income countries |
title_short | Hierarchical cluster analysis of labour market regulations and population health: a taxonomy of low- and middle-income countries |
title_sort | hierarchical cluster analysis of labour market regulations and population health: a taxonomy of low- and middle-income countries |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3349504/ https://www.ncbi.nlm.nih.gov/pubmed/22512892 http://dx.doi.org/10.1186/1471-2458-12-286 |
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