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Low health literacy is a hidden epidemic. Identifying individuals with low health literacy is a formidable barrier to eliminating disparities and improving health care quality and health outcomes. However, screening individual patients for low health literacy can be prohibitively expensive, time consuming, and inefficient. Focusing on communities, rather than individuals, provides opportunities for action. Identifying geographic areas with large numbers of individuals with low health literacy can enable stakeholders to focus interventions in areas of greatest need. Creating such a measure also sheds light on health literacy as a community or neighborhood-level resource that contributes to health disparities and can inform health interventions.

We applied regression coefficients from a predictive model of health literacy to US Census data to estimate health literacy scores for census geographic areas in Missouri. We then created maps displaying the variability in health literacy levels. Finally, we compared areas identified by the predictive model to those identified on the basis of educational attainment alone.

Areas identified by the predictive model as having the lowest health literacy were substantially different from those identified using educational attainment alone, suggesting that a multivariate approach using a limited set of widely available predictors is considerably more accurate.

This study demonstrates a cost-effective and feasible method for estimating and mapping community-level health literacy. Predicting and mapping areas of low health literacy is relatively straightforward and inexpensive and makes complex data readily accessible to many stakeholders. Such maps can also identify and prioritize geographic areas for intervention by health care and public health providers. Moreover, this focus on community-level health literacy may help foster stakeholder collaboration, leading to efficient resource use that is targeted effectively and resulting in a positive return on investment for stakeholders.