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 e026187. https://doi.org/10.1136/bmjopen-2018-026187

TitleValidation of non-participation bias methodology based on record-linked Finnish register-based health survey data: a protocol paper
TypeJournal article
AuthorsMcMinn, M. A., Martikainen, P., Gorman, E., Rissanen, H., Härkänen, T., Tolonen, H., Leyland, A. H. and Gray, L.
Abstract

Introduction: Decreasing participation levels in health surveys pose a threat to the validity of estimates intended to be representative of their target population. If participants and non-participants differ systematically, the results may be biased. The application of traditional non-response adjustment methods, such as weighting, can fail to correct for such biases, as estimates are typically based on the sociodemographic information available. Therefore, a dedicated methodology to infer on non-participants offers advancement by employing survey data linked to administrative health records, with reference to data on the general population. We aim to validate such a methodology in a register-based setting, where individual-level data on participants and non-participants are available, taking alcohol consumption estimation as the exemplar focus.

Methods and analysis: We made use of the selected sample of the Health 2000 survey conducted in Finland and a separate register-based sample of the contemporaneous population, with follow-up until 2012. Finland has nationally representative administrative and health registers available for individual-level record linkage to the Health 2000 survey participants and invited non-participants, and the population sample. By comparing the population sample and the participants, synthetic observations representing the non-participants may be generated, as per the developed methodology. We can compare the distribution of the synthetic non-participants with the true distribution from the register data. Multiple imputation was then used to estimate alcohol consumption based on both the actual and synthetic data for non-participants, and the estimates can be compared to evaluate the methodology’s performance.

Ethics and dissemination: Ethical approval and access to the Health 2000 survey data and data from administrative and health registers have been given by the Health 2000 Scientific Advisory Board, Statistics Finland and the National Institute for Health and Welfare. The outputs will include two publications in public health and statistical methodology journals and conference presentations.

Article numbere026187
JournalBMJ Open
Journal citation9 (4), p. e026187
ISSN2044-6055
Year2019
PublisherBMJ
Publisher's version
Digital Object Identifier (DOI)https://doi.org/10.1136/bmjopen-2018-026187
Publication dates
Published04 Apr 2019
LicenseCC BY 4.0

Related outputs

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. 2020. Correcting for non-participation bias in health surveys using record-linkage, synthetic observations and pattern mixture modelling. Statistical Methods in Medical Research. 29 (4), pp. 1212-1226. https://doi.org/10.1177/0962280219854482

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. https://doi.org/10.1111/add.13797

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. https://doi.org/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 e002647. https://doi.org/10.1136/bmjopen-2013-002647

Permalink - https://westminsterresearch.westminster.ac.uk/item/qv994/validation-of-non-participation-bias-methodology-based-on-record-linked-finnish-register-based-health-survey-data-a-protocol-paper


Share this
Tweet
Email

Usage statistics

17 total views
12 total downloads
0 views this month
0 downloads this month
These values are for the period from September 2nd 2018, when this repository was created

Export as