Skip to main content
SpringerLink
Log in

The impact of handling missing data on alcohol consumption estimates in the UK women cohort study

  • METHODS
  • Published:
European Journal of Epidemiology Aims and scope Submit manuscript

Abstract

We discuss methods for dealing with incomplete-data in the United Kingdom Women’s Cohort Study. We demonstrate by example how important it is to address the issues related to missing data with statistical integrity, illustrate the deficiencies of a data-reduction and a single-imputation method, and discuss how the method of multiple imputation overcomes them. Although the method entails some complexity, the computational activities can be organized in such a way that efficient analyses can be conducted by analysts who are not acquainted with all the details of the imputation method and who wish to rely on software they use and regard as standard.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Abbreviations

UKWCS:

UK women cohort study

FFQ:

Food frequency questionnaire

WCRF:

World cancer research fund

MAR:

Missing at random

References

  1. Gronbaek M, et al. Type of alcohol consumed and mortality from all causes, coronary heart disease, and cancer. Ann Intern Med. 2000;133:411–9.

    PubMed  CAS  Google Scholar 

  2. IARC. IARC monographs on the evaluation of carcinogenic risks to humans; alcoholic beverage consumption and ethyl carbamate (Urethane). Lyon: IARCPress; 2007. p. 149–156.

  3. Boffetta P, Hashibe M. Alcohol and cancer. Lancet Oncol. 2006;7:149–56.

    Article  PubMed  CAS  Google Scholar 

  4. Paton A. ABC of alcohol. BMJ Publishing Group; 1994.

  5. Wood AM, et al. Comparison of imputation and modelling methods in the analysis of a physical activity trial with missing outcomes. Int J Epidemiol. 2005;34:89–99.

    Article  PubMed  Google Scholar 

  6. Nur U, et al. Dealing with incomplete data in questionnaires of food and alcohol consumption. Stat Transit. 2005;7:111–34.

    Google Scholar 

  7. Cade J, et al. Costs of a healthy diet: analysis from the UK Women’s cohort study. Public Health Nutr. 1999;2:505–12.

    Article  PubMed  CAS  Google Scholar 

  8. Pollard J, et al. Lifestyle factors affecting fruit and vegetable consumption in the UK Women’s cohort study. Appetite. 2001;37:71–9.

    Article  PubMed  CAS  Google Scholar 

  9. Greenwood DC, et al. Seven unique food consumption patterns identified among women in the UK Women’s cohort study. Eur J Clin Nutr. 2000;54:314–20.

    Article  PubMed  CAS  Google Scholar 

  10. Holland B, et al. McCance and Widdowson’s the composition of foods. London: The Royal Society of Chemistry and MAFF; 1991.

    Google Scholar 

  11. Rubin DB. Multiple imputation for nonresponse in surveys. New York: Wiley; 1987.

    Book  Google Scholar 

  12. Clark TG, Altman DG. Developing a prognostic model in the presence of missing data: an ovarian cancer case study. J Clin Epidemiol. 2003;56:28–37.

    Article  PubMed  Google Scholar 

  13. Van Buuren S, Boshuizen HC, Knook DL. Multiple imputation of missing blood pressure covariates in survival analysis. Stat Med. 1999;18:681–94.

    Article  PubMed  Google Scholar 

  14. Royston P. Multiple imputation of missing values: update. Stata J. 2005;5:188–201.

    Google Scholar 

  15. Carlin JB, Galati JC, Royston P. A new framework for managing and analyzing multiply imputed data in Stata. Stata J. 2008;8:49–67.

    Google Scholar 

  16. Rubin DB. Multiple imputation after 18+ years. J Am Stat Assoc. 1996;91:473–89.

    Article  Google Scholar 

  17. Statacorp. STATA statistical software. [8.0]. 2004. College Station, TX: Stata Corporation; 2009.

Download references

Author information

Authors and Affiliations

  1. Cancer Research UK Cancer Survival Group, Non-Communicable Disease Epidemiology Unit, London School of Hygiene and Tropical Medicine, Keppel St, London, WC1E 7HT, UK

    U. Nur

  2. Departament d’Economia i Empresa, Universitat Pompeu Fabra, Ramon Trias Fargas 25–27, 08005, Barcelona, Spain

    N. T. Longford

  3. Centre for Epidemiology and Biostatistics, University of Leeds, Leeds, LS2 9LN, UK

    J. E. Cade & D. C. Greenwood

Authors
  1. U. Nur
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. N. T. Longford
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. J. E. Cade
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. D. C. Greenwood
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to U. Nur.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Nur, U., Longford, N.T., Cade, J.E. et al. The impact of handling missing data on alcohol consumption estimates in the UK women cohort study. Eur J Epidemiol 24, 589–595 (2009). https://doi.org/10.1007/s10654-009-9384-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10654-009-9384-1

Keywords

Search

Navigation