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

TitleAdjustment for survey non‐representativeness using record‐linkage: refined estimates of alcohol consumption by deprivation in Scotland
TypeJournal article
AuthorsGorman, E., Leyland, A. H., McCartney, G., Katikireddi, S. V., Rutherford, L., Graham, L., Robinson, M. and Gray, L.
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.

JournalAddiction
Journal citation112 (7), pp. 1270-1280
ISSN0965-2140
Year2017
PublisherWiley
Publisher's versionGorman_et_al-2017-Addiction.pdf
Digital Object Identifier (DOI)doi:10.1111/add.13797
Publication dates
Published09 Mar 2017
LicenseCC BY 4.0

Related outputs

Validation of non-participation bias methodology based on record-linked Finnish register-based health survey data: a protocol paper
McMinn, M. A., Martikainen, P., Gorman, E., Rissanen, H., Härkänen, T., Tolonen, H., Leyland, A. H. and Gray, L. 2019. Validation of non-participation bias methodology based on record-linked Finnish register-based health survey data: a protocol paper. BMJ Open. 9 (4), p. e026187. doi:10.1136/bmjopen-2018-026187

Correcting for non-participation bias in health surveys using record-linkage, synthetic observations and pattern mixture modelling
Gray, L., Gorman, E., White, I. R., Katikireddi, S. V., McCartney, G., Rutherford, L. and Leyland, A. H. 2019. Correcting for non-participation bias in health surveys using record-linkage, synthetic observations and pattern mixture modelling. Statistical Methods in Medical Research. Advanced online publication. doi:10.1177/0962280219854482

Assessing the Representativeness of Population-Sampled Health Surveys Through Linkage to Administrative Data on Alcohol-Related Outcomes
Gorman, E., Leyland, A. H., McCartney, G., White, I. R., Katikireddi, S. V., Rutherford, L., Graham, L. and Gray, L. 2014. Assessing the Representativeness of Population-Sampled Health Surveys Through Linkage to Administrative Data on Alcohol-Related Outcomes. American Journal of Epidemiology. 180 (9), pp. 941-948. doi:10.1093/aje/kwu207

Use of record-linkage to handle non-response and improve alcohol consumption estimates in health survey data: a study protocol
Gray, L., McCartney, G., White, I. R., Katikireddi, S. V., Rutherford, L., Gorman, E. and Leyland, A. H. 2013. Use of record-linkage to handle non-response and improve alcohol consumption estimates in health survey data: a study protocol . BMJ Open. 3 (3), p. BMJ Open 2013;3:e002647. doi:10.1136/bmjopen-2013-002647

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