Gabriela R Oates1, Lucia D Juarez2, Barbara Hansen3, Catarina I Kiefe4, James M Shikany5. 1. Assistant Professor of Pediatrics, Division of Pulmonary and Sleep Medicine, University of Alabama at Birmingham, Birmingham, AL., Email: goates@uab.edu. 2. Scientist III, Division of Preventive Medicine, University of Alabama at Birmingham, Birmingham, AL. 3. Scientist I, Division of Preventive Medicine, University of Alabama at Birmingham, Birmingham, AL. 4. Professor and Chair, Population and Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA. 5. Professor of Medicine, Division of Preventive Medicine, University of Alabama at Birmingham, Birmingham, AL.
Abstract
Objectives: Nonadherence to medications has been documented, but the combined effect of social risk factors on medication nonadherence has not been investigated. Methods: We conducted a cross-sectional analysis of data from the Coronary Artery Risk Development in Young Adults (CARDIA) study, a population-based prospective cohort. The sample (N = 1506) included subjects who at Year 20 (2005-06) were taking prescription medications and completed a 4-item Medication Adherence Scale. Social risk factors were education of high school or less, annual household income <$25,000, high financial strain, high chronic stress, low social support, and high social strain. Results: In a fully adjusted logistic regression model, income <$25,000 (OR = 2.37 [95% CI 1.12-4.98], p < .05) and high chronic stress (OR = 2.07 [95% CI 1.09-3.94], p < .05) were significantly associated with medication nonadherence. Individuals with ≥3 social risk factors had >3 times higher odds of nonadherence than counterparts with no social risk factors (OR = 3.26 [95% CI 1.72-6.19], p < .001). Conclusion: Low income and chronic stress are associated with medication nonadherence, and the odds of nonadherence increase with the accumulation of social risk factors. Findings may be used to develop risk prediction tools to identify individuals who can benefit from adherence-promoting interventions.
Objectives: Nonadherence to medications has been documented, but the combined effect of social risk factors on medication nonadherence has not been investigated. Methods: We conducted a cross-sectional analysis of data from the Coronary Artery Risk Development in Young Adults (CARDIA) study, a population-based prospective cohort. The sample (N = 1506) included subjects who at Year 20 (2005-06) were taking prescription medications and completed a 4-item Medication Adherence Scale. Social risk factors were education of high school or less, annual household income <$25,000, high financial strain, high chronic stress, low social support, and high social strain. Results: In a fully adjusted logistic regression model, income <$25,000 (OR = 2.37 [95% CI 1.12-4.98], p < .05) and high chronic stress (OR = 2.07 [95% CI 1.09-3.94], p < .05) were significantly associated with medication nonadherence. Individuals with ≥3 social risk factors had >3 times higher odds of nonadherence than counterparts with no social risk factors (OR = 3.26 [95% CI 1.72-6.19], p < .001). Conclusion: Low income and chronic stress are associated with medication nonadherence, and the odds of nonadherence increase with the accumulation of social risk factors. Findings may be used to develop risk prediction tools to identify individuals who can benefit from adherence-promoting interventions.
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