Identifying At-Risk Subpopulations of Canadians with Limited Health Literacy

Abstract

Background: Health literacy, the set of skills for locating, understanding, and using health-related information, is associated with various health outcomes through health behaviors and health care service use. While health literacy has great potential for addressing health disparities stemming from the differing educational attainment in diverse populations, knowledge about subpopulations that share the same risk factors is useful. Objective: This study employed a logistic regression tree algorithm to identify subpopulations at risk of limited health literacy in Canadian adults. Design: The nationally representative data were derived from the International Adult Literacy and Skills Survey (n = 20,059). The logistic regression tree algorithm splits the samples into subgroups and fits logistic regressions. Results: Results showed that the subpopulation comprised of individuals 56 years and older, with household income less than $50,000, no participation in adult education programs, and lack of reading activities (i.e., newspaper, books) was at the greatest risk (82%) of limited health literacy. Other identified subgroups were displayed in an easily interpreted tree diagram. Conclusions: Identified subpopulations organized in tree diagrams according to the risk of limited health literacy inform not only intervention programs targeting unique subpopulations but also future health literacy research.