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The harmonisation of longitudinal data: a case study using data from cohort studies in The Netherlands and the United Kingdom

Published online by Cambridge University Press:  29 September 2010

PETER A. BATH ,
DORLY DEEG  and
JAN POPPELAARS
PETER A. BATH*
Affiliation:
Information Centre, University of Sheffield, Sheffield, UK.
DORLY DEEG
Affiliation:
Institute for Health and Care Research, VU University Medical Centre, Amsterdam.
JAN POPPELAARS
Affiliation:
Institute for Health and Care Research, VU University Medical Centre, Amsterdam.
*
Address for correspondence: Peter Bath, Centre for Health Information Management Research, University of Sheffield, Regent Court, 211 Portobello Street, Sheffield S1 4DP, UK E-mail: [email protected]
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Abstract

This paper presents a case study of the challenges and requirements associated with harmonising data from two independently-conceived datasets from The Netherlands and the United Kingdom: the Longitudinal Aging Study Amsterdam (LASA) and the Nottingham Longitudinal Study of Activity and Ageing (NLSAA). The objectives were to create equivalent samples and variables, and to identify the methodological differences that affect the comparability of the samples. Data are available from the two studies' 1992–93 surveys for respondents born during 1908–20, and the common data set had 1,768 records and enabled the creation of 26 harmonised variables in the following domains: demographic composition and personal finances, physical health, mental health and loneliness, contacts with health services, physical activity, religious attendance and pet ownership. The ways in which the methodological differences between the two studies and their different selective attrition might lead to sample differences were carefully considered. It was concluded that the challenges of conducting cross-national comparative research using independent datasets include differences in sampling, study design, measurement instruments, response rates and selective attrition. To reach conclusions from any comparative study about substantive socio-cultural differences, these challenges must first be identified and addressed.

Keywords

data harmonisationolder peoplecross-national comparisonsample attrition
Type
Research Article
Information
Ageing & Society , Volume 30 , Issue 8 , November 2010 , pp. 1419 - 1437
Copyright
Copyright © Cambridge University Press 2010

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References

Bedford, A., Foulds, G. A. and Sheffield, B. F. 1976. A new personal disturbance scale: DSSI/SAD. British Journal of Social and Clinical Psychology, 15, 4, 387–94.Google Scholar
Casado-Díaz, M. A., Kaiser, C. and Warnes, A. M. 2004. Northern European retired residents in eight southern European areas: characteristics, motivations and adjustment. Ageing & Society, 24, 3, 353–81.CrossRefGoogle Scholar
Curran, P. J. 2009. The seemingly quixotic pursuit of a cumulative psychological science: introduction to a special issue. Psychological Methods, 14, 2, 77–80.Google Scholar
Curran, P. J. and Husong, A. M. 2009. Integrative data analysis: the simultaneous analysis of multiple data sets. Psychological Methods, 14, 2, 81–100.Google Scholar
Deeg, D. J. H. 2002. Attrition in longitudinal population studies: does it affect the generalizability of the findings? An introduction to the series. Journal of Clinical Epidemiology, 55, 3, 213–5.Google Scholar
Deeg, D. J. H., Knipscheer, C. P. M. and van Tilburg, W. (eds)1993. Autonomy and Well-being in the Aging Population: Concepts and Design of the Longitudinal Aging Study Amsterdam. Netherlands Institute of Gerontology, Bunnik, The Netherlands.Google Scholar
Deeg, D. J. H., van Tilburg, T. G., Smit, J. H. and de Leeuw, E. D. 2002. Attrition in the Longitudinal Aging Study Amsterdam: the effect of differential inclusion in side studies. Journal of Clinical Epidemiology, 55, 4, 319–28.Google Scholar
Fleishman, R. and Shmueli, A. 1984. Patterns of informal social support of the elderly: an international comparison. The Gerontologist, 24, 3, 303–12.Google Scholar
Folstein, M., Folstein, S. and McHugh, P. R. 1975. Mini-Mental State: a practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12, 3, 189–98.Google Scholar
Hofer, S. M. and Piccinin, A. M. 2009. Integrative data analysis through coordination of measurement and analysis protocol across independent longitudinal studies. Psychological Methods, 14, 2, 150–64.CrossRefGoogle ScholarPubMed
Jackendoff, R. 2009. Language, Consciousness, Culture: Essays on Mental Structure. MIT Press, Cambridge, Massachusetts.Google Scholar
Knipscheer, C. P. M., de Jong Gierveld, J., van Tilburg, T. G. and Dykstra, P. A. (eds)1995. Living Arrangements and Social Networks of Older Adults. VU University Press, Amsterdam.Google Scholar
Minicuci, N., Noale, M., Bardage, C., Blumstein, T., Deeg, D. J. H., Gindin, J., Jylha, M., Nikula, S., Otero, A., Pedersen, N. L., Pluijm, S. M. F., Zunzunegui, M. V. and Maggi, S. 2003. Cross-national determinants of quality of life from six longitudinal studies on aging: the CLESA Project. Aging Clinical and Experimental Research, 15, 3, 187–202.CrossRefGoogle ScholarPubMed
Morgan, K. 1998. The Nottingham Longitudinal Study of Activity and Ageing: a methodological overview. Age and Ageing, 27, Supplement 3, 5–11.Google Scholar
Morgan, K., Dallosso, H. M., Arie, T., Byrne, E. J., Jones, R. and Waite, J. 1987. Mental health and psychological well-being among the old and very old living at home. British Journal of Psychiatry, 150, 6, 801–7.Google Scholar
Nikula, S., Jylha, M., Bardage, C., Deeg, D. J. H., Gindin, J., Minicuci, N., Pluijm, S. M. F. and Rodriguez-Laso, A. 2003. Are IADLs comparable across countries? Sociodemographic associates of harmonized IADL measures. Aging Clinical and Experimental Research, 15, 6, 451–9.Google Scholar
Pattie, A. H. and Gilleard, C. J. 1979. Manual of the Clifton Assessment Procedures for the Elderly (CAPE). Hodder and Stoughton, Sevenoaks, UK.Google Scholar
Radloff, L. S. 1977. The CES-D scale: a self-report depression scale for research in the general population. Applied Psychological Measurement, 1, 3, 385–401.Google Scholar
Shanas, E. 1968. Health and incapacity in later life. In Shanas, E., Townsend, P., Wedderburn, D., Friis, H., Milhoj, P. and Stehouwer, J. (eds), Old People in Three Industrial Societies. Routledge and Kegan Paul, London, 18–48.Google Scholar
Shanas, E., Townsend, P., Wedderburn, D., Friis, H., Milhoj, P. and Stehouwer, J. 1968. Old People in Three Industrial Societies. Routledge and Kegan Paul, London.Google Scholar
Walker, A. (ed.)2005. Growing Older in Europe. Open University Press, Maidenhead, UK.Google Scholar
Zigmund, A. S. and Snaith, R. P. 1983. The Hospital Anxiety and Depression Scale. Acta Psychiatrica Scandinavica 67, 6, 361–70.Google Scholar