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Aims: A common objective of epidemiological surveys is to providepopulation-level estimates of health indicators. Survey results tend to bebiased under selective non-participation. One approach to bias reduction is tocollect information about non-participants by contacting them again and askingthem to fill in a questionnaire. This information is called re-contact data,and it allows to adjust the estimates for non-participation.  Methods: We analyse data from the FINRISK 2012 survey, where re-contact datawere collected. We assume that the respondents of the re-contact survey aresimilar to the remaining non-participants with respect to the health giventheir available background information. Validity of this assumption isevaluated based on the hospitalization data obtained through record linkage ofsurvey data to the administrative registers. Using this assumption and multipleimputation, we estimate the prevalences of daily smoking and heavy alcoholconsumption and compare them to estimates obtained with a commonly usedassumption that the participants represent the entire target group.  Results: This approach produces higher prevalence estimates than what isestimated from participants only. Among men, smoking prevalence estimate was28.5% (23.2% for participants), heavy alcohol consumption prevalence was 9.4%(6.8% for participants). Among women, smoking prevalence was 19.0% (16.5% forparticipants) and heavy alcohol consumption 4.8% (3.0% for participants).Conclusion: Utilization of re-contact data is a useful method to adjust fornon-participation bias on population estimates in epidemiological surveys.

Adjusting for selective non-participation with re-contact data in the FINRISK 2012 survey