The aim of this paper is to describe the use of sequence analysis to model trajectories of life‐course economic activity status, within a broader research agenda aimed at improving understanding of the relationship between socioeconomic position and health.
The analysis used data on 288 participants of the Boyd Orr Stratified Sub‐Sample, comprising a combination of prospective and retrospective information on economic activity status, as well as health in early old age. Economic activity was coded as a time‐based sequence of states for each participant based on six‐month periods throughout their lives. Economic activity was classified as: pre‐labour market; full‐time employment; part‐time employment; housewife; made redundant; stopped work due to illness; retired; other unemployed; or not applicable. Optimal matching analysis was carried out to produce a matrix of distances between each sequence, which was then used as the basis for cluster analysis.
The optimal matching analysis resulted in the classification of individuals into five economic activity status trajectories: full‐time workers (transitional exit), part‐time housewives, career breakers, full‐time workers (late entry, early exit), and full‐time housewives.
The paper presents the case for using sequence analysis as a methodological tool to facilitate a more interdisciplinary approach to the measurement of the life‐course socioeconomic position, in particular attempting to integrate the empirical emphasis of epidemiological research with the more theoretical contributions of sociology. This may in turn help generate a framework within which to examine the relationships between life‐course socioeconomic position and outcomes such as health in later life.
Stone, J., Netuveli, G. and Blane, D. (2008), "Modelling socioeconomic trajectories: an optimal matching approach", International Journal of Sociology and Social Policy, Vol. 28 No. 5/6, pp. 217-230. https://doi.org/10.1108/01443330810881268
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