Structural and Social Determinants of Health Factors Associated with County-Level Variation in Non-Adherence to Antihypertensive Medication Treatment

Macarius M. Donneyong, Teng-Jen Chang, John W. Jackson, Michael A. Langston, Paul D. Juarez, Shawnita Sealy-Jefferson, Bo Lu, Wansoo Im, R. Burciaga Valdez, Baldwin M. Way, Cynthia Colen, Michael A. Fischer, Pamela Salsberry, John F.P. Bridges and Darryl B. Hood
Additional contact information
Macarius M. Donneyong: College of Pharmacy, Ohio State University, Columbus, OH 43210, USA
Teng-Jen Chang: College of Pharmacy, Ohio State University, Columbus, OH 43210, USA
John W. Jackson: Departments of Epidemiology and Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
Michael A. Langston: Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN 37996, USA
Paul D. Juarez: Department of Family and Community Medicine, Meharry Medical College, Nashville, TN 37208, USA
Shawnita Sealy-Jefferson: College of Public Health, Ohio State University, Columbus, OH 43210, USA
Bo Lu: College of Public Health, Ohio State University, Columbus, OH 43210, USA
Wansoo Im: Department of Family and Community Medicine, Meharry Medical College, Nashville, TN 37208, USA
R. Burciaga Valdez: Family & Community Medicine, University of New Mexico, Albuquerque, NM 87131, USA
Baldwin M. Way: Department of Psychology, Ohio State University, Columbus, OH 43210, USA
Cynthia Colen: College of Public Health, Ohio State University, Columbus, OH 43210, USA
Michael A. Fischer: Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham & Women’s Hospital, Boston, MA 02115, USA
Pamela Salsberry: College of Public Health, Ohio State University, Columbus, OH 43210, USA
John F.P. Bridges: Department of Biomedical Informatics, Ohio State University, Columbus, OH 43210, USA
Darryl B. Hood: College of Public Health, Ohio State University, Columbus, OH 43210, USA

IJERPH, 2020, vol. 17, issue 18, 1-12

Abstract: Background: Non-adherence to antihypertensive medication treatment (AHM) is a complex health behavior with determinants that extend beyond the individual patient. The structural and social determinants of health (SDH) that predispose populations to ill health and unhealthy behaviors could be potential barriers to long-term adherence to AHM. However, the role of SDH in AHM non-adherence has been understudied. Therefore, we aimed to define and identify the SDH factors associated with non-adherence to AHM and to quantify the variation in county-level non-adherence to AHM explained by these factors. Methods: Two cross-sectional datasets, the Centers for Disease Control and Prevention (CDC) Atlas of Heart Disease and Stroke (2014–2016 cycle) and the 2016 County Health Rankings (CHR), were linked to create an analytic dataset. Contextual SDH variables were extracted from the CDC-CHR linked dataset. County-level prevalence of AHM non-adherence, based on Medicare fee-for-service beneficiaries’ claims data, was extracted from the CDC Atlas dataset. The CDC measured AHM non-adherence as the proportion of days covered (PDC) with AHM during a 365 day period for Medicare Part D beneficiaries and aggregated these measures at the county level. We applied confirmatory factor analysis (CFA) to identify the constructs of social determinants of AHM non-adherence. AHM non-adherence variation and its social determinants were measured with structural equation models. Results: Among 3000 counties in the U.S., the weighted mean prevalence of AHM non-adherence (PDC < 80%) in 2015 was 25.0%, with a standard deviation (SD) of 18.8%. AHM non-adherence was directly associated with poverty/food insecurity (β = 0.31, P -value < 0.001) and weak social supports (β = 0.27, P -value < 0.001), but inversely with healthy built environment (β = −0.10, P -value = 0.02). These three constructs explained one-third ( R 2 = 30.0%) of the variation in county-level AHM non-adherence. Conclusion: AHM non-adherence varies by geographical location, one-third of which is explained by contextual SDH factors including poverty/food insecurity, weak social supports and healthy built environments.

Keywords: adherence; antihypertensive medications; hypertension; social determinants of health; county health rankings; CDC Atlas (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1660-4601/17/18/6684/pdf (application/pdf)
https://www.mdpi.com/1660-4601/17/18/6684/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:17:y:2020:i:18:p:6684-:d:413282

Access Statistics for this article

IJERPH is currently edited by Ms. Jenna Liu

More articles in IJERPH from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().