MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, 200 Renfield Street, Glasgow, G2 3AX, UK.
Present Address: Amsterdam Institute for Global Health and Development, Paasheuvelweg 25, 1105 BP, Amsterdam, Netherlands.
Int J Equity Health. 2020 Oct 28;19(1):193. doi: 10.1186/s12939-020-01302-4.
Social class is frequently used as a means of ranking the population to expose inequalities in health, but less often as a means of understanding the social processes of causation. We explored how effectively different social class mechanisms could be measured by longitudinal cohort data and whether those measures were able to explain health outcomes.
Using a theoretically informed approach, we sought to map variables within the National Child Development Study (NCDS) to five different social class mechanisms: social background and early life circumstances; habitus and distinction; exploitation and domination; location within market relations; and power relations. Associations between the SF-36 physical, emotional and general health outcomes at age 50 years and the social class measures within NCDS were then assessed through separate multiple linear regression models. R values were used to quantify the proportion of variance in outcomes explained by the independent variables.
We were able to map the NCDS variables to the each of the social class mechanisms except 'Power relations'. However, the success of the mapping varied across mechanisms. Furthermore, although relevant associations between exposures and outcomes were observed, the mapped NCDS variables explained little of the variation in health outcomes: for example, for physical functioning, the R values ranged from 0.04 to 0.10 across the four mechanisms we could map.
This study has demonstrated both the potential and the limitations of available cohort studies in measuring aspects of social class theory. The relatively small amount of variation explained in the outcome variables in this study suggests that these are imperfect measures of the different social class mechanisms. However, the study lays an important foundation for further research to understand the complex interactions, at various life stages, between different aspects of social class and subsequent health outcomes.
社会阶层常被用作一种对人群进行排序的方式，以揭示健康方面的不平等，但较少被用来理解因果关系的社会过程。我们探讨了纵向队列数据能够在多大程度上有效地衡量不同的社会阶层机制，以及这些衡量标准是否能够解释健康结果。
我们采用了一种理论启发式方法，试图将国民儿童发展研究（NCDS）中的变量映射到五个不同的社会阶层机制中：社会背景和早期生活环境；习惯和区别；剥削和统治；在市场关系中的位置；以及权力关系。然后，通过单独的多元线性回归模型，评估 NCDS 中社会阶层措施与 SF-36 身体、情感和总体健康结果在 50 岁时的相关性。R 值用于量化因变量中由独立变量解释的方差比例。
我们能够将 NCDS 变量映射到每个社会阶层机制，除了“权力关系”。然而，映射的成功程度因机制而异。此外，尽管观察到了暴露和结果之间的相关关系，但映射的 NCDS 变量对健康结果的变化解释很少：例如，对于身体机能，在我们能够映射的四个机制中，R 值的范围从 0.04 到 0.10。
这项研究既展示了现有队列研究在衡量社会阶层理论方面的潜力，也展示了其局限性。在本研究中，因变量变化的解释量相对较小，这表明这些变量是衡量不同社会阶层机制的不完美指标。然而，该研究为进一步研究奠定了重要基础，以了解不同社会阶层方面与随后的健康结果在各个生命阶段之间的复杂相互作用。
