Predicting small-area health-related behaviour: a comparison of smoking and drinking indicators

L Twigg*, G Moon, Kelvyn Jones

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

79 Citations (Scopus)

Abstract

Health-related behaviours are of central importance to health promotion and to the promotion of enhanced population health. In the UK, localised knowledge of the quantitative dimensions of health-related behaviours is traditionally attained by conducting a costly sample survey, Such surveys seldom generate reliable data at scales more local than that of the health authority, they also need to be repeated regularly. This paper outlines an alternative framework for generating statistics on small-area health related behaviours using routinely available data from the annual Health Survey for England (N = 17,000) and the decennial Population Census. Using a multilevel modelling approach nesting individuals within postcode sectors within health authorities, and focusing on the prevalence of smoking and 'problem' drinking, the paper comprises four sections: a consideration of the modelling strategy, a comparison of the smoking and drinking models, an outline of the estimation strategy, and the presentation and discussion of ward-level estimates of smoking and drinking behaviour for England. The paper concludes that the method is better at estimating smoking than drinking but that it offers a feasible, cheap and more informative alternative to the survey approach to the generation of information on smoking and drinking behaviour.

Original languageEnglish
Pages (from-to)1109-1120
Number of pages12
JournalSocial Science and Medicine
Volume50
Issue number7-8
Publication statusPublished - Apr 2000
Event8th International Symposium on Medical Geography - BALTIMORE, United Kingdom
Duration: 1 Jan 1998 → …

Keywords

  • multilevel models
  • Health Survey for England
  • smoking
  • drinking
  • MULTILEVEL ANALYSIS
  • PREVALENCE
  • CONTEXT
  • PLACES
  • GENDER
  • MODELS
  • LOGIC
  • AGE

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