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Evaluation of Medication Adherence Among Prevalent Users in Hypertension, Dyslipidemia, and Diabetes Using Health

Minako Matsumoto1, Sei Harada1, Harufumi Ikuta2

  • 1Department of Preventive Medicine, Public Health, Keio University School of Medicine, Tokyo, Japan.

Pharmacoepidemiology and Drug Safety
|August 15, 2024
PubMed

Insights

Medication adherence for hypertension, dyslipidemia, and diabetes was evaluated. While overall adherence was high, lifestyle factors like skipping breakfast and poor sleep quality predicted non-adherence in specific patient groups.

Area of Science:

  • Cardiovascular disease research
  • Pharmacoepidemiology
  • Metabolomics

Background:

  • Hypertension (HT), dyslipidemia (DL), and diabetes mellitus (DM) are significant risk factors for cardiovascular diseases.
  • Despite available medications, medication adherence remains a challenge in managing these conditions.

Purpose of the Study:

  • To evaluate medication adherence among prevalent users of HT, DL, and DM medications using claims data.
  • To identify factors associated with non-adherence in these patient populations.

Main Methods:

  • Analysis of 3693 prevalent medication users from the Tsuruoka Metabolomics Cohort Study.
  • Medication adherence assessed using Proportion of Days Covered (PDC), with PDC ≥0.8 defined as adherent.
  • Multivariable logistic regression used to determine predictors of non-adherence, with lifestyle data collected via questionnaire.

Main Results:

  • Adherence rates varied by condition: HT-only (90.2%), DM-only (81.2%), and DL-only (80.8%) among those without comorbidities.
  • Predictors of non-adherence included skipping breakfast and poor medication understanding (HT); female sex, comorbidities, heart disease history, and drinking habits (DL).
  • Good sleep quality and skipping breakfast were associated with non-adherence for DM medications.

Conclusions:

  • Participants generally exhibited high medication adherence, but significant differences were noted across medication groups.
  • Identified predictors of non-adherence can inform targeted interventions to improve medication adherence and reduce cardiovascular risk.
Abstract

Keywords:
adherencecohort‐studyhealth insurance claims datapharmacoepidemiology

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