  Aims: A common objective of epidemiological surveys is to provide
population-level estimates of health indicators. Survey results tend to be
biased under selective non-participation. One approach to bias reduction is to
collect information about non-participants by contacting them again and asking
them 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 data
were collected. We assume that the respondents of the re-contact survey are
similar to the remaining non-participants with respect to the health given
their available background information. Validity of this assumption is
evaluated based on the hospitalization data obtained through record linkage of
survey data to the administrative registers. Using this assumption and multiple
imputation, we estimate the prevalences of daily smoking and heavy alcohol
consumption and compare them to estimates obtained with a commonly used
assumption that the participants represent the entire target group.
  Results: This approach produces higher prevalence estimates than what is
estimated from participants only. Among men, smoking prevalence estimate was
28.5% (23.2% for participants), heavy alcohol consumption prevalence was 9.4%
(6.8% for participants). Among women, smoking prevalence was 19.0% (16.5% for
participants) and heavy alcohol consumption 4.8% (3.0% for participants).
Conclusion: Utilization of re-contact data is a useful method to adjust for
non-participation bias on population estimates in epidemiological surveys.
