Adjusting for selective non-participation with re-contact data in the FINRISK 2012 survey
| Autor: | Juho Kopra, Pekka Jousilahti, Juha Karvanen, Hanna Tolonen, Tommi Härkänen, Kari Kuulasmaa, Jaakko Reinikainen |
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| Rok vydání: | 2017 |
| Předmět: |
Male
FOS: Computer and information sciences 01 natural sciences 010104 statistics & probability missing data 0302 clinical medicine Epidemiology Prevalence 030212 general & internal medicine bias (epidemiology) Finland media_common juomatavat General Medicine ta3142 Middle Aged valikoitumisharha data Female alkoholinkäyttö Psychology Alcohol consumption survey-tutkimus Adult medicine.medical_specialty Alcohol Drinking media_common.quotation_subject alcohol consumption Survey result Statistics - Applications smoking 03 medical and health sciences Non participation tupakointi Environmental health medicine Humans selection bias Applications (stat.AP) 0101 mathematics Aged Selection bias ta112 Public Health Environmental and Occupational Health epidemiologiset harhat Missing data Health Surveys Health indicator terveystutkimus Patient Participation |
| DOI: | 10.48550/arxiv.1711.06070 |
| Popis: | 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. Comment: 16 pages, 4 tables, 0 figures |
| Databáze: | OpenAIRE |
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