Sociodemographic, health and lifestyle characteristics reported by discrete groups of adult dietary supplement users in Alberta, Canada: findings from The Tomorrow Project

Abstract

AbstractObjectiveTo determine the extent to which differences in sociodemographic, dietary and lifestyle characteristics exist between users of different types of dietary supplements and supplement non-users.DesignWe analysed cross-sectional data obtained from self-administered questionnaires completed at baseline by participants in The Tomorrow Project; a prospective cohort study in Alberta, Canada. Participants who used at least one type of dietary supplement at least weekly in the year prior to questionnaire completion were defined as supplement users, while the remainder were classified as non-users. Seven discrete user categories were created: multivitamins (+/− minerals) only, specific nutritional supplements only, herbal/other supplements only, and all possible combinations. Differences in sociodemographic, dietary and lifestyle characteristics between different groups of supplement users and non-users were analysed using Rao–Scottχ2tests and multinomial logistic regression.Subjects and settingSubjects were 5067 men and 7439 women, aged 35–69 years, recruited by random digit dialling throughout Alberta.ResultsSupplement use was extensive in this study population (69·8 %). Users of herbal/other supplements only, and women who used multivitamins only, tended to report dietary and lifestyle characteristics that were not significantly different from non-users. In contrast, those who reported using a combination of multivitamins, specific nutritional and herbal/other supplements were more likely than non-users to report behaviours and characteristics consistent with current health guidelines.ConclusionsDichotomizing participants as supplement users or non-users is likely to mask further differences in sociodemographic, dietary and lifestyle characteristics among users of different types of supplements. This may have implications for analysis and interpretation of observational studies.