MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK.
Population Research Unit, Faculty of Social Science, University of Helsinki, Helsinki, Finland.
BMJ Open. 2019 Apr 4;9(4):e026187. doi: 10.1136/bmjopen-2018-026187.
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.
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.
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.
参与健康调查的人数减少，对旨在代表目标人群的估计的有效性构成威胁。如果参与者和非参与者存在系统差异，那么结果可能存在偏差。应用传统的非响应调整方法（如加权）可能无法纠正此类偏差，因为估计通常基于现有的社会人口统计学信息。因此，采用专门的方法推断非参与者，可以通过利用与行政健康记录相关联的调查数据，参考一般人群的数据，来提供改进。我们旨在在基于登记的环境中验证这种方法，在这种环境中，参与者和非参与者的个体层面数据是可用的，以酒精消费估计作为示例重点。
我们利用芬兰进行的健康 2000 调查的选定样本和同期人口的单独基于登记的样本，随访至 2012 年。芬兰拥有全国代表性的行政和健康登记册，可用于对健康 2000 调查的参与者和受邀的非参与者以及人口样本进行个体层面的记录链接。通过将人口样本与参与者进行比较，可以根据所开发的方法生成代表非参与者的合成观测值。我们可以将合成非参与者的分布与来自登记数据的真实分布进行比较。然后，我们使用多重插补根据实际数据和非参与者的合成数据来估计酒精消费，并可以比较这些估计值以评估该方法的性能。
健康 2000 科学顾问委员会、芬兰统计局和国家健康与福利研究所已批准了健康 2000 调查数据和行政及健康登记数据的使用，并获得了访问权限。该研究的成果将包括在公共卫生和统计方法学期刊上发表的两篇论文和会议演讲。
