Archives of Public Health (Jun 2022)
Organizing the health interview survey at the local level: design of a pilot study
Abstract
Abstract Background The local Health Interview Study (LHIS) was developed to gain health information at the level of the municipality in Flanders, the northern part of Belgium. It enables municipalities to make evidence-based decisions in their public health policy. To test the feasibility of implementing the LHIS, a pilot study was conducted in Melle, a small Flemish municipality with 11.736 inhabitants. Methods The target sample size was 1000 (≥ 15 years). A systematic sampling technique was applied with substitutes for non-respondents who were matched in terms of statistical sector, age and sex. Selected persons were contacted by post to complete the questionnaire and in case of non-response, a reminder was sent. Questionnaires were collected using a concurrent mixed-mode design: a paper and pencil, and web option. All questions were selected from the Belgian Health Interview Survey relating to health status and determinants of health. Results One thousand twenty-two questionnaires were obtained after inviting 3137 individuals (response rate = 32.6%). Older adults were more likely to participate than younger adults, and women more than men. The final sample resembled the initial sample in terms of sex and statistical sector, but not in terms of age. Younger adults were underrepresented whereas older adults were overrepresented. Lastly, older adults were more likely to fill in the questionnaire on paper than younger adults, and women more than men. Conclusion The LHIS can be successfully implemented in Flemish municipalities. The method, however, does not guarantee that the composition of the final sample reflects the initial sample. Therefore, weights should be added in the analyses to correct for potential deviations in sample composition. Furthermore, implementing a sequential mixed-mode design with a web option preceding a paper and pencil option in future studies could reduce costs and improve data quality.
Keywords