Life-course occupational social class and health in later life: The importance of frequency and timing of measures StoneJuliet NetuveliGopalakrishnan BlaneDavid 2018 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 (n = 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. © 2014 Springer-Verlag Berlin Heidelberg.