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The life course prospective design: an example of benefits and problems associated with study longevity

Author

Listed:
  • Wadsworth, M. E. J.
  • Butterworth, S. L.
  • Hardy, R. J.
  • Kuh, D. J.
  • Richards, M.
  • Langenberg, C.
  • Hilder, W. S.
  • Connor, M.

Abstract

Although the life course prospective study design has many benefits, and information from such studies is in increasing demand for scientific and policy purposes, it has potential inherent design problems associated with its longevity. These are in particular the fixed sample structure and the data collected in early life, which are each determined by the scientific principles of another time and the risk over time of increased sample loss and distortion through loss. The example of a national birth cohort in Britain, studied from birth so far to age 53 years is used to address these questions. Although the response rate is high, avoidable loss, which was low in childhood, increased in adulthood, and was highest in those in adverse socio-economic circumstances and those with low scores on childhood cognitive measures. Recent permanent refusal rate rises may be the result of better tracing and/or a response to increased requests for biological measurement. Nevertheless, the responding sample continues in most respects to be representative of the national population of a similar age. Consistency of response over the study's 20 data collections has been high. The size of the sample responding in adulthood is adequate for the study of the major costly diseases, and for the study of functional ageing and its precursors. This study's continuation has depended not only on scientific value but also policy relevance. Although the problems inherent in the prospective design are unavoidable they are not, in the study described, a barrier to scientific and policy value. That seems also likely in Britain's two later born national birth cohort studies that have continued into adulthood.

Suggested Citation

  • Wadsworth, M. E. J. & Butterworth, S. L. & Hardy, R. J. & Kuh, D. J. & Richards, M. & Langenberg, C. & Hilder, W. S. & Connor, M., 2003. "The life course prospective design: an example of benefits and problems associated with study longevity," Social Science & Medicine, Elsevier, vol. 57(11), pages 2193-2205, December.
  • Handle: RePEc:eee:socmed:v:57:y:2003:i:11:p:2193-2205
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    Citations

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    Cited by:

    1. Hatch, Stephani L. & Jones, Peter B. & Kuh, Diana & Hardy, Rebecca & Wadsworth, Michael E.J. & Richards, Marcus, 2007. "Childhood cognitive ability and adult mental health in the British 1946 birth cohort," Social Science & Medicine, Elsevier, vol. 64(11), pages 2285-2296, June.
    2. Robert Stewart & Rebecca Hardy & Marcus Richards, 2015. "Associations between Skeletal Growth in Childhood and Cognitive Function in Mid-Life in a 53-Year Prospective Birth Cohort Study," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-10, April.
    3. McMunn, Anne & Bartley, Mel & Kuh, Diana, 2006. "Women's health in mid-life: Life course social roles and agency as quality," Social Science & Medicine, Elsevier, vol. 63(6), pages 1561-1572, September.
    4. Collishaw, Stephan & Goodman, Robert & Pickles, Andrew & Maughan, Barbara, 2007. "Modelling the contribution of changes in family life to time trends in adolescent conduct problems," Social Science & Medicine, Elsevier, vol. 65(12), pages 2576-2587, December.
    5. Kuh, Diana & Shah, Imran & Richards, Marcus & Mishra, Gita & Wadsworth, Michael & Hardy, Rebecca, 2009. "Do childhood cognitive ability or smoking behaviour explain the influence of lifetime socio-economic conditions on premature adult mortality in a British post war birth cohort?," Social Science & Medicine, Elsevier, vol. 68(9), pages 1565-1573, May.
    6. Bann, David & Hardy, Rebecca & Cooper, Rachel & Lashen, Hany & Keevil, Brian & Wu, Frederick C.W. & Holly, Jeff M.P. & Ong, Ken K. & Ben-Shlomo, Yoav & Kuh, Diana, 2015. "Socioeconomic conditions across life related to multiple measures of the endocrine system in older adults: Longitudinal findings from a British birth cohort study," Social Science & Medicine, Elsevier, vol. 147(C), pages 190-199.
    7. Rosemary Abbott & George Ploubidis & Felicia Huppert & Diana Kuh & Tim Croudace, 2010. "An Evaluation of the Precision of Measurement of Ryff’s Psychological Well-Being Scales in a Population Sample," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 97(3), pages 357-373, July.
    8. Mishra, Gita & Kuh, Diana, 2006. "Perceived change in quality of life during the menopause," Social Science & Medicine, Elsevier, vol. 62(1), pages 93-102, January.
    9. Tarani Chandola & Paul Clarke & J. N. Morris & David Blane, 2006. "Pathways between education and health: a causal modelling approach," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(2), pages 337-359, March.

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