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Adjustment for survey non-representativeness using record-linkage: refined estimates of alcohol consumption by deprivation in Scotland.
- Source :
-
Addiction . Jul2017, Vol. 112 Issue 7, p1270-1280. 11p. 5 Charts. - Publication Year :
- 2017
-
Abstract
- Background and aims Analytical approaches to addressing survey non-participation bias typically use only demographic information to improve estimates. We applied a novel methodology which uses health information from data linkage to adjust for non-representativeness. We illustrate the method by presenting adjusted alcohol consumption estimates for Scotland. Design Data on consenting respondents to the Scottish Health Surveys (SHeSs) 1995-2010 were linked confidentially to routinely collected hospital admission and mortality records. Synthetic observations representing non-respondents were created using general population data. Multiple imputation was performed to compute adjusted alcohol estimates given a range of assumptions about the missing data. Adjusted estimates of mean weekly consumption were additionally calibrated to per-capita alcohol sales data. Setting Scotland. Participants 13 936 male and 18 021 female respondents to the SHeSs 1995-2010, aged 20-64 years. Measurements Weekly alcohol consumption, non-, binge- and problem-drinking. Findings Initial adjustment for non-response resulted in estimates of mean weekly consumption that were elevated by up to 17.8% [26.5 units (18.6-34.4)] compared with corrections based solely on socio-demographic data [22.5 (17.7-27.3)]; other drinking behaviour estimates were little changed. Under more extreme assumptions the overall difference was up to 53%, and calibrating to sales estimates resulted in up to 88% difference. Increases were especially pronounced among males in deprived areas. Conclusions The use of routinely collected health data to reduce bias arising from survey non-response resulted in higher alcohol consumption estimates among working-age males in Scotland, with less impact for females. This new method of bias reduction can be generalized to other surveys to improve estimates of alternative harmful behaviours. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09652140
- Volume :
- 112
- Issue :
- 7
- Database :
- Academic Search Index
- Journal :
- Addiction
- Publication Type :
- Academic Journal
- Accession number :
- 123438996
- Full Text :
- https://doi.org/10.1111/add.13797