Adjustment for survey non-representativeness using record-linkage: refined estimates of alcohol consumption by deprivation in Scotland

Gorman, E., Leyland, A. H. , McCartney, G., Katikireddi, S. V. , Rutherford, L., Graham, L., Robinson, M. and Gray, L. (2017) Adjustment for survey non-representativeness using record-linkage: refined estimates of alcohol consumption by deprivation in Scotland. Addiction, 112(7), pp. 1270-1280. (doi: 10.1111/add.13797) (PMID:28276110) (PMCID:PMC5467727)

[img]
Preview
Text
136732.pdf - Published Version
Available under License Creative Commons Attribution.

245kB

Abstract

Background and aims: Analytical approaches to addressing survey non-participation bias typically only use 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 confidentially linked 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: 30,718 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 overall mean weekly consumption that were elevated by up to 15.1% [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 87% difference. Increases were especially pronounced among males in deprived areas. Conclusions: 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 generalised to other surveys to improve estimates of alternative harmful behaviours.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Katikireddi, Professor Vittal and Gray, Dr Linsay and Leyland, Professor Alastair and Graham, Dr Lesley and Gorman, Ms Emma
Authors: Gorman, E., Leyland, A. H., McCartney, G., Katikireddi, S. V., Rutherford, L., Graham, L., Robinson, M., and Gray, L.
College/School:College of Medical Veterinary and Life Sciences > School of Cardiovascular & Metabolic Health
College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > MRC/CSO SPHSU
Journal Name:Addiction
Publisher:Wiley
ISSN:0965-2140
ISSN (Online):1360-0443
Published Online:25 April 2017
Copyright Holders:Copyright © 2017 The Authors
First Published:First published in Addiction 112(7):1270-1280
Publisher Policy:Reproduced under a Creative Commons License

University Staff: Request a correction | Enlighten Editors: Update this record

Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
652821Addressing non-response in health survey data to refine alcohol consumption estimates in ScotlandLinsay GrayMedical Research Council (MRC)MC_EX_UU_MR/J013498/1IHW - MRC/CSO SPHU
727651Measuring and Analysing Socioeconomic Inequalities in HealthAlastair LeylandMedical Research Council (MRC)MC_UU_12017/13HW - MRC/CSO Social and Public Health Sciences Unit
727671Informing Healthy Public PolicyPeter CraigMedical Research Council (MRC)MC_UU_12017/15HW - MRC/CSO Social and Public Health Sciences Unit
699162Understanding the impacts of welfare policy on health: A novel data linkage studySrinivasa KatikireddiOffice of the Chief Scientist (CSO)SCAF/15/02IHW - MRC/CSO SPHU