Background: National Health Interview Surveys are used to produce country-wide results for a substantial number of health indicators. However, if some educational groups are underrepresented in the sample, estimates may be biased. This study investigated the impact of the use of post-stratification weights that adjust for the population distribution by education on estimates from the Belgian Health Interview Survey 2013. Methods: For 25 health-related indicators that match the European Core Health Indicator shortlist, estimates were computed using two different sets of post-stratification weights: one based on age group, gender and province only and the other one including also education. The Census 2011 was used as auxiliary data source. Statistical differences between the two estimates were assessed with the Delta method. Results: If education is not included as post-stratification weighting factor, low educational groups (ISCED 0-2) represent 31.1% of the total study population aged 25 years and older. If education is taken into account this proportion rises to 40.3%. The use of post-stratification weights adjusting for the population distribution by education has an impact on several survey estimates. The most pronounced effect is an increase in the estimated proportion of people with diabetes (+0.73%; 95% CI 0.19-1.27; relative increase +11.6%), asthma (+0.52%; 95% CI, 0.06-0.98; relative increase +12.4%) and difficulties to cover their health expenses (+2.31%; 95% CI, 1.52-3.10; relative increase +9.4%). Conclusions: Including education in the calculation of post-stratification weights reduces bias due to educational differences in survey participation. Auxiliary information used to calculate post-stratification weights for national health surveys should include education.
Background: National Health Interview Surveys are used to produce country-wide results for a substantial number of health indicators. However, if some educational groups are underrepresented in the sample, estimates may be biased. This study investigated the impact of the use of post-stratification weights that adjust for the population distribution by education on estimates from the Belgian Health Interview Survey 2013. Methods: For 25 health-related indicators that match the European Core Health Indicator shortlist, estimates were computed using two different sets of post-stratification weights: one based on age group, gender and province only and the other one including also education. The Census 2011 was used as auxiliary data source. Statistical differences between the two estimates were assessed with the Delta method. Results: If education is not included as post-stratification weighting factor, low educational groups (ISCED 0-2) represent 31.1% of the total study population aged 25 years and older. If education is taken into account this proportion rises to 40.3%. The use of post-stratification weights adjusting for the population distribution by education has an impact on several survey estimates. The most pronounced effect is an increase in the estimated proportion of people with diabetes (+0.73%; 95% CI 0.19-1.27; relative increase +11.6%), asthma (+0.52%; 95% CI, 0.06-0.98; relative increase +12.4%) and difficulties to cover their health expenses (+2.31%; 95% CI, 1.52-3.10; relative increase +9.4%). Conclusions: Including education in the calculation of post-stratification weights reduces bias due to educational differences in survey participation. Auxiliary information used to calculate post-stratification weights for national health surveys should include education.
Authors: Lisa Van Wilder; Rana Charafeddine; Philippe Beutels; Robin Bruyndonckx; Irina Cleemput; Stefaan Demarest; Delphine De Smedt; Niel Hens; Aline Scohy; Niko Speybroeck; Johan Van der Heyden; Renata T C Yokota; Herman Van Oyen; Joke Bilcke; Brecht Devleesschauwer Journal: Qual Life Res Date: 2021-08-18 Impact factor: 4.147