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

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 (? = 0.31, P-value < 0.001) and weak social supports (? = 0.27, P-value < 0.001), but inversely with healthy built environment (? = -0.10, P-value = 0.02). These three constructs explained one-third (R2 = 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.

SUBMITTER: Donneyong MM

PROVIDER: S-EPMC7557537 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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

Donneyong Macarius M MM Chang Teng-Jen TJ Jackson John W JW Langston Michael A MA Juarez Paul D PD Sealy-Jefferson Shawnita S Lu Bo B Im Wansoo W Valdez R Burciaga RB Way Baldwin M BM Colen Cynthia C Fischer Michael A MA Salsberry Pamela P Bridges John F P JFP Hood Darryl B DB

International journal of environmental research and public health 20200914 18

<h4>Background</h4>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-ad ...[more]

PMID: 32937852

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Project description:BackgroundCommunity pharmacy represents an important setting to identify patients who may benefit from an adherence intervention, however it remains unclear whether it would be feasible to monitor antihypertensive adherence within the workflow of community pharmacy. The aim of this study was to identify facilitators and barriers to monitoring antihypertensive medication adherence of older adults at the point of repeat dispensing.MethodsWe undertook a factorial survey of Irish community pharmacists, guided by a conceptual model adapted from the Theory of Planned Behaviour (TPB). Respondents completed four sections, 1) five factorial vignettes (clinical scenario of repeat dispensing), 2) a medication monitoring attitude measure, 3) subjective norms and self-efficacy questions, and 4) demographic and workplace questions. Barriers and facilitators to adherence monitoring behaviour were identified in factorial vignette analysis using multivariate multilevel linear modelling, testing the effect of both contextual factors embedded within the vignettes (section 1), and respondent-level factors (sections 2-4) on likelihood to perform three adherence monitoring behaviours in response to the vignettes.ResultsSurvey invites (n = 1543) were sent via email and 258 completed online survey responses were received; two-thirds of respondents were women, and one-third were qualified pharmacists for at least 15 years. In factorial vignette analysis, pharmacists were more inclined to monitor antihypertensive medication adherence by examining refill-patterns from pharmacy records than asking patients questions about their adherence or medication beliefs. Pharmacists with more positive attitudes towards medication monitoring and normative beliefs that other pharmacists monitored adherence, were more likely to monitor adherence. Contextual factors also influenced pharmacists' likelihood to perform the three adherence monitoring behaviours, including time-pressures and the number of days late the patient collected their repeat prescription. Pharmacists' normative beliefs and the number of days late the patient collected their repeat prescription had the largest quantitative influence on responses.ConclusionsThis survey identified that positive pharmacist attitudes and normative beliefs can facilitate adherence monitoring within the current workflow; however contextual time-barriers may prevent adherence monitoring. Future research should consider these findings when designing a pharmacist-led adherence intervention to be integrated within current pharmacy workflow.

Project description:BackgroundCommunities with more Black or Hispanic residents have higher coronavirus rates than communities with more White residents, but relevant community characteristics are underexplored. The purpose of this study was to investigate poverty-, race- and ethnic-based disparities and associated economic, housing, transit, population health and health care characteristics.MethodsSix-month cumulative coronavirus incidence and mortality were examined using adjusted negative binomial models among all U.S. counties (n = 3142). County-level independent variables included percentages in poverty and within racial/ethnic groups (Black, Hispanic, Native American, Asian), and rates of unemployment, lacking a high school diploma, housing cost burden, single parent households, limited English proficiency, diabetes, obesity, smoking, uninsured, preventable hospitalizations, primary care physicians, hospitals, ICU beds and households that were crowded, in multi-unit buildings or without a vehicle.ResultsCounties with higher percentages of Black (IRR = 1.03, 95% CI: 1.02-1.03) or Hispanic (IRR = 1.02, 95% CI: 1.01-1.03) residents had more coronavirus cases. Counties with higher percentages of Black (IRR = 1.02, 95% CI: 1.02-1.03) or Native American (IRR = 1.02, 95% CI: 1.01-1.04) residents had more deaths. Higher rates of lacking a high school diploma was associated with higher counts of cases (IRR = 1.03, 95% CI: 1.01-1.05) and deaths (IRR = 1.04, 95% CI: 1.01-1.07). Higher percentages of multi-unit households were associated with higher (IRR = 1.02, 95% CI: 1.01-1.04) and unemployment with lower (IRR = 0.96, 95% CI: 0.94-0.98) incidence. Higher percentages of individuals with limited English proficiency (IRR = 1.09, 95% CI: 1.04-1.14) and households without a vehicle (IRR = 1.04, 95% CI: 1.01-1.07) were associated with more deaths.ConclusionsThese results document differential pandemic impact in counties with more residents who are Black, Hispanic or Native American, highlighting the roles of residential racial segregation and other forms of discrimination. Factors including economic opportunities, occupational risk, public transit and housing conditions should be addressed in pandemic-related public health strategies to mitigate disparities across counties for the current pandemic and future population health events.

Project description:Adherence to antihypertensive medications is a key component to control blood pressure levels. Poor adherence to these medications leads to the development of hypertensive complications and increase risk of cardiovascular events which in turn reduces the ultimate clinical outcome. The purpose of this study was to assess antihypertensive medication adherence and associated factors among adult hypertensive patients. A hospital-based cross-sectional study among adult hypertensive patients was conducted at hypertensive follow-up clinic of Jimma University Specialized Hospital from March 4, 2015 to April 3, 2015. A simple random sampling technique was used to select the study participants from the study population. The study patients were interviewed and their medical charts were reviewed using a pretested structured questionnaire. Adherence was assessed using Morisky Medication Adherence Scale-8 (MMAS-8) and MMAS-8 score less than 6 was considered as non-adherent and MMAS-8 score was ? 6 was declared as adherence. Factors associated with adherence were identified using binary and multivariate logistic regression analysis. Crude odds ratio, adjusted odds ratio (AOR) and 95% confidence interval of the odds ratio were calculated using SPSS version 21. Variables with p-value less than 0.05 were assumed as statistically significant factors.Among 280 hypertensive patients, 61.8% of the study participants were found to be adherent. More than half (53.2%) of the participants were males and the mean age of the participants was 55.0 ± 12.7 years. Co-morbidity (AOR = 0.083, 95% CI = 0.033-0.207, p < 0.001), alcohol intake (AOR = 0.011, 95% CI = 0.002-0.079, p < 0.001), getting medications freely (AOR = 0.020, 95% CI = 0.003-0.117, p < 0.001), and combination of antihypertensive medications (AOR = 0.32, 95% CI = 0.144-0.712, p < 0.005) were inversely associated with antihypertensive medication adherence.The adherence level to the prescribed antihypertensive medications was found to be sub-optimal according to the MMAS-8, and influenced by co morbidity, alcohol intake, self-purchasing of the medications and combination of antihypertensive medications.

Project description:To determine the associations between medical, demographic, socioeconomic, and ocular factors and adherence to topical glaucoma ocular hypotensive therapy.One hundred sixteen patients with ocular hypertension or open-angle glaucoma from 2 tertiary glaucoma services participated in this prospective study. Adherence to ocular hypotensive therapy was measured using an electronic dose monitor (Travatan Dosing Aid, Alcon Laboratories Inc., Fort Worth, TX) and collected data at 3 months after enrollment. We used 3 different definitions of adherence: 1) Definition 1: the proportion of days taking the prescribed number of drops within 3 hours of the prescribed dosing time; 2) Definition 2: the proportion of days taking any drops within 3 hours of the prescribed dosing time; and 3) Definition 3: the proportion of days taking any drops within 6 hours of the prescribed dosing time. Univariate and multivariate models were used to determine the association between the 3 adherence definitions, medical, demographic, socioeconomic, and ocular factors at 3-month follow-up. The main outcome measures for this study were risk factors for poor objective medication adherence.Adherence, using Definition 1, Definition 2, and Definition 3, was 64%, 75%, and 80%, respectively. Age, total number of other eye diseases, and race were significantly associated with full treatment adherence (Definition 1), with race alone significantly predicting 11% of full treatment adherence. For Definition 2, age, income, level of education, and total number of eye diseases were significantly associated with partial adherence (3 h), again race alone significantly predicted 15% of partial adherence (any drops within 3 h). For Definition 3, race, income, level of education, and total number of other eye diseases significantly predicted partial adherence (any drops within 6 h), both race and income predicted 19% of partial treatment adherence. Significant differences for adherence rates between patients of European descent and those of African descent were found for all 3 definitions with those who were less adherent more likely to be of African descent.Electronic dose monitors provide important information regarding adherence to topical ocular hypotensive medications in glaucoma patients. Electronic dose monitors show low adherence in a significant number of participants. Future studies are needed to determine the reasons for these differences in health behaviors related to glaucoma treatment, which should guide treatment of poor adherence with glaucoma therapy.

Project description:Adherence to medication has been repeatedly proposed to represent a major cause of treatment-resistant hypertension (TRH); however, treatment decisions such as treating TRH with renal denervation depend on accurate judgment of adherence. We carefully analyzed adherence rates to medication before and after renal denervation and its effect on blood pressure (BP) control. Eighty patients with TRH were included in 2 prospective observational studies that assessed the difference of potential antihypertensive and nephroprotective effects of renal denervation. To compare prescribed with actual medication intake (representing a measure of adherence), we analyzed urine samples collected at baseline and at 6 months after renal denervation for antihypertensive compounds or metabolites (by liquid chromatography-mass spectrometry). In addition to office BP, 24-hour ambulatory BP and central hemodynamics (central systolic pressure, central pulse pressure) were assessed. Informed consent for analyses of urine metabolites was obtained from 79 of 80 patients. Actual intake of all antihypertensive drugs was detected at baseline and at 6 months after renal denervation in 44 (56%) and 52 (66%) patients, respectively; 1 drug was missing in 22 (28%) and 17 (22%) patients, respectively, and ≥2 drugs were missing in 13 (16%) and 10 (13%) patients, respectively. At baseline, 24-hour ambulatory BP (P=0.049) and central systolic BP (P=0.012) were higher in nonadherent patients. Adherence did not significantly change overall (McNemar-Bowker test, P=0.362). An increase in adherence was observed in 21 patients, and a decrease was observed in 11 patients. The decrease in 24-hour ambulatory BP was not different in those with stable adherence 6 months after renal denervation (n=41, -7±13 mm Hg) compared with those with increased adherence (n=21, -10±13 mm Hg) and decreased adherence (n=11, -7±14 mm Hg) (P>0.20). Our study is limited by the relatively small sample size and potentially by the specific health environment of our university center (Northern Bavaria, Germany). Nonadherence to medication among patients with TRH was relatively low: ≈1 of 6 patients with TRH did not take ≥2 of the prescribed drugs. Adherence pattern did not change significantly after renal denervation and had no impact on the overall observed BP changes, supporting the concept that renal denervation is an effective treatment in patients with TRH. URL: https://www.clinicaltrials.gov. Unique identifiers: NCT00888433, NCT01442883 and NCT01687725.

Dataset Information

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

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

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