Dalla Lana School of Public Health, University of Toronto, Toronto, Canada.
BMC Public Health. 2012 Apr 18;12:286. doi: 10.1186/1471-2458-12-286.
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.
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.
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.
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.
健康的社会决定因素视角的一个重要贡献是探究人口健康的非医学决定因素。在这些因素中，劳动力市场法规具有至关重要的意义。在这项研究中，我们调查了中低收入国家（LMICs）的劳动力市场法规，并提出了一种劳动力市场分类法，以在全球背景下进一步了解人口健康。
我们使用人均国民生产总值将 113 个国家分为低收入（n=71）或中等收入（n=42）两类。使用三个劳动力市场不平等和贫困标准化指标的主成分分析来构建 2 个因子得分。使用 Cronbach 的 alpha 评估因子得分的可靠性。使用这些得分，我们进行层次聚类分析以生成劳动力市场分类法，进行零阶相关，并创建箱线图以检验它们与成人死亡率、健康预期寿命、婴儿死亡率、孕产妇死亡率、新生儿死亡率、五岁以下儿童死亡率以及因传染病和非传染病导致的生命损失年数的关联。劳动力市场和健康数据来自国际劳工组织的劳动力市场关键指标和世界卫生组织的统计信息系统。
出现了六个劳动力市场集群：残余（n=16）、新兴（n=16）、非正式（n=10）、后共产主义（n=18）、不成功的非正式（n=22）和不稳定（n=31）。主要发现表明：（i）劳动力市场贫困与人口健康在中低收入国家均相关；（ii）劳动力市场不平等与健康指标之间的关联仅在低收入国家具有统计学意义；（iii）新兴（例如东亚和东欧国家）和不稳定（例如撒哈拉以南非洲国家）集群分别是最有利和最不利的，其余集群的人口健康水平与其劳动力市场特征一致。
LMICs 的劳动力市场法规似乎是人口健康的重要社会决定因素。本研究表明，使用探索性分类法方法理解 LMICs 的劳动力市场及其对健康的影响具有启发价值。
