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Multiple-domain Versus Single-domain Measurements of Socioeconomic Status (SES) for Predicting Nonadherence to Statin Medications: An Observational Population-based Cohort Study

Alsabbagh, Mhd. Wasem PhD*; Lix, Lisa M. PhD; Eurich, Dean PhD; Wilson, Thomas W. MD§; Blackburn, David F. PharmD

doi: 10.1097/MLR.0000000000000468
Original Articles

Introduction: Low socioeconomic status (SES) should be a robust predictor of medication nonadherence because it shares key features with the theoretical origins of this phenomenon. However, population-based studies have demonstrated weak associations overall, possibly because SES is inadequately represented. We compared the performance of multiple versus single-domain measures of SES as predictors of statin adherence.

Methods: This retrospective cohort study used population-based administrative data mapped to area-level census information of individuals who received a statin medication following a hospitalization for coronary heart disease. One-year adherence was calculated by dividing the sum of all tablets dispensed by the total number of days in the observation period (365 d following the first statin dispensation). Logistic regression models were constructed and the relative impact of each SES measure was assessed by its adjusted odds ratio (OR) and improvement over the predictive accuracy of a reference model that included non-SES factors only.

Results: More than two thirds (ie, 68.8%; 6517/9478) of eligible individuals exhibited optimal adherence (ie, ≥80%). The estimated impact of SES on optimal adherence differed depending on the SES measure tested. The highest performing single-domain measure, household income (OR=0.75; 95% confidence interval, 0.63–0.90; model c-statistic improvement 0.5%, P=0.04) generated a similar result to the multiple-domain measure (adjusted OR=0.74; 95% confidence interval, 0.62–0.88; model c-statistic improvement 0.7%, P=0.01).

Conclusion: Multidomain measurements of SES using administrative databases mapped to census data are not associated with better performance in predicting statin medication adherence compared with single-domain measures such as household income.

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*School of Pharmacy, Faculty of Science, University of Waterloo, Waterloo, ON

Department of Community Health Sciences, Faculty of Medicine, University of Manitoba, Winnipeg, MB

Department of Public Health Sciences, School of Public Health, University of Alberta, Li Ka Shing Center for Health Research Innovation, Edmonton, AB

§Department of Medicine, Royal University Hospital, Saskatoon Health Region

College of Pharmacy and Nutrition, University of Saskatchewan, Saskatoon, SK, Canada

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Funding for this study was solely provided from the Chair in Patient Adherence to Drug Therapy within the College of Pharmacy and Nutrition, University of Saskatchewan. D.F.B. is the Chair in Patient Adherence within the College of Pharmacy and Nutrition, University of Saskatchewan. This position was created through unrestricted financial support from AstraZeneca Canada, Merck Frosst Canada, Pfizer Canada, and the Province of Saskatchewan’s Ministry of Health. D.E. receives salary support though a population health investigator award from the Alberta Heritage Foundation for Medical Research and is a Canadian Institutes of Health Research New Investigator. L.M.L. is supported by a Manitoba Research Chair. As a graduate student, M.H.D.W.A. also receives a scholarship through the Research Chair fund.

This study is based in part on deidentified data provided by the Saskatchewan Ministry of Health. The interpretation and conclusions contained herein do not necessarily represent those of the Government of Saskatchewan or the Saskatchewan Ministry of Health.

The authors declare no conflict of interest.

Reprints: MHD Wasem Alsabbagh, PhD, School of Pharmacy, Faculty of Science, University of Waterloo, 10A Victoria Street S., Kitchener, ON, Canada N2G 1C5. E-mail: wasem.alsabbagh@uwaterloo.ca.

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