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Social Risk Factors for Medication Nonadherence: Findings from the CARDIA Study

Gabriela R Oates1, Lucia D Juarez2, Barbara Hansen3

  • 1Assistant Professor of Pediatrics, Division of Pulmonary and Sleep Medicine, University of Alabama at Birmingham, Birmingham, AL.,

American Journal of Health Behavior
|February 6, 2020
PubMed

Insights

Medication nonadherence is linked to low income and chronic stress. The risk of not taking medications increases with more social risk factors, highlighting a need for targeted interventions.

Area of Science:

  • Public Health
  • Social Epidemiology
  • Health Disparities

Background:

  • Medication nonadherence is a significant public health issue.
  • The cumulative impact of social risk factors on medication adherence remains understudied.

Purpose of the Study:

  • To investigate the association between multiple social risk factors and medication nonadherence.
  • To identify specific social determinants influencing adherence to prescription medications.

Main Methods:

  • Cross-sectional analysis of 1506 participants from the Coronary Artery Risk Development in Young Adults (CARDIA) study.
  • Utilized a 4-item Medication Adherence Scale and assessed social risk factors including income, education, financial strain, stress, and social support.
  • Employed logistic regression to analyze the relationship between social risk factors and medication nonadherence.

Main Results:

  • Low household income (<$25,000) and high chronic stress were significantly associated with medication nonadherence.
  • Individuals with three or more social risk factors exhibited over three times higher odds of nonadherence compared to those with none.
  • A dose-response relationship was observed, where increased social risk factors correlated with higher odds of nonadherence.

Conclusions:

  • Low income and chronic stress are key social determinants of medication nonadherence.
  • The accumulation of social risk factors significantly elevates the likelihood of medication nonadherence.
  • Findings support the development of risk prediction tools to guide adherence-promoting interventions for vulnerable populations.

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