Stone Juliet, Netuveli Gopalakrishnan, Blane David
ESRC Centre for Population Change, University of Southampton, Southampton, UK.
ESRC International Centre for Life Course Studies in Society and Health (ICLS), Department of Epidemiology and Public Health, University College London, London, UK.
Eur J Ageing. 2014 Mar 28;11(3):273-284. doi: 10.1007/s10433-014-0307-y. eCollection 2014 Sep.
Research investigating associations between social class over the life-course and later health relies primarily on secondary analysis of existing data, limiting the number and timing of available measurements. This paper aims to examine the impact of these constraints on the measurement of life-course occupational social class and subsequent explanatory analyses predicting health in later life. Participants of the UK Boyd Orr Lifegrid Subsample ( = 294), aged an average of 68 years, provided retrospective information on their life-course occupational social class, coded at 6-month intervals. This was used to simulate two types of life-course data: (1) Theoretical: Life stage (four data-points at key life stages); (2) A-theoretical: Panel data (data-points at regular intervals of varying length). The percentage of life time in disadvantage and the predictive value for limiting longstanding illness (LLI) in later life using the full life-course and simulated data was compared. The presence of 'critical periods' of exposure and the role of trajectories of social class were also investigated. Compared with the full data, the life stage approach estimated a higher percentage of life time in disadvantage and emphasised 'transient' periods in disadvantage (e.g. labour market entry). With varying intervals using the a-theoretical approach, there was no clear pattern. Percentage of life time in manual class was a significant predictor of LLI only when using the four-point life stage approach. Occupational social class at labour market entry was a predictor of LLI in later life, suggesting a 'critical period'. Comparison of trajectories of social class further emphasised the importance of the sequence and timing of exposures to disadvantage in determining later health. We conclude that producing a valid summary of life-course occupational social class does not necessarily require a large number of data-points, particularly if guided by relevant theory, and that such measures can reveal important associations with later health.
关于生命历程中的社会阶层与晚年健康之间关联的研究主要依赖于对现有数据的二次分析，这限制了可用测量的数量和时间。本文旨在研究这些限制对生命历程职业社会阶层测量以及随后预测晚年健康的解释性分析的影响。英国博伊德·奥尔生活网格子样本（n = 294）的参与者，平均年龄为68岁，提供了关于他们生命历程职业社会阶层的回顾性信息，每隔6个月进行编码。这被用于模拟两种类型的生命历程数据：（1）理论型：生命阶段（关键生命阶段的四个数据点）；（2）非理论型：面板数据（不同长度的定期数据点）。比较了使用完整生命历程数据和模拟数据得出的处于劣势的生命时间百分比以及对晚年限制长期疾病（LLI）的预测价值。还研究了暴露的“关键时期”的存在以及社会阶层轨迹的作用。与完整数据相比，生命阶段方法估计处于劣势的生命时间百分比更高，并强调了劣势中的“短暂”时期（例如劳动力市场进入期）。使用非理论方法且间隔不同时，没有明显模式。只有在使用四点生命阶段方法时，体力劳动阶层的生命时间百分比才是LLI的显著预测因素。劳动力市场进入时的职业社会阶层是晚年LLI的预测因素，表明存在一个“关键时期”。社会阶层轨迹的比较进一步强调了暴露于劣势的顺序和时间在决定晚年健康方面的重要性。我们得出结论，要得出生命历程职业社会阶层的有效总结不一定需要大量数据点，特别是如果有相关理论指导，并且这样的测量可以揭示与晚年健康的重要关联。
