Medication, Healthcare Follow-up, and Lifestyle Nonadherence: Do They Share the Same Risk Factors?. Issue 1 (13th December 2021)

• Record Type: Journal Article
• Authors: Ng, Yue-Harn; Litvinovich, Igor; Leyva, Yuridia; Ford, C. Graham; Zhu, Yiliang; Kendall, Kellee; Croswell, Emilee; Puttarajappa, Chethan M.; Dew, Mary Amanda; Shapiro, Ron; Unruh, Mark L.; Myaskovsky, Larissa
• Is Part Of: Transplantation direct. Volume 8:Issue 1(2022)
• Page Start: e1256
• Publication Date: 2021-12-13
• Subjects: Transplantation of organs, tissues, etc -- Periodicals; Transplantation -- Periodicals; 362.19795
• DOI: 10.1097/TXD.0000000000001256
• Languages: English
• ISSNs: 2373-8731

Abstract

Abstract : Background: Barriers to medication adherence may differ from barriers in other domains of adherence. In this study, we assessed the association between pre–kidney transplantation (KT) factors with nonadherent behaviors in 3 different domains post-KT. Methods: We conducted a prospective cohort study with patient interviews at initial KT evaluation (baseline—nonadherence predictors in sociodemographic, condition-related, health system, and patient-related psychosocial factors) and at ≈6 mo post-KT (adherence outcomes: medications, healthcare follow-up, and lifestyle behavior). All patients who underwent KT at our institution and had ≈6-mo follow-up interview were included in the study. We assessed nonadherence in 3 different domains using continuous composite measures derived from the Health Habit Survey. We built multiple linear and logistic regression models, adjusting for baseline characteristics, to predict adherence outcomes. Results: We included 173 participants. Black race (mean difference in adherence score: −0.72; 95% confidence interval [CI], −1.12 to −0.32) and higher income (mean difference: −0.34; 95% CI, −0.67 to −0.02) predicted lower medication adherence. Experience of racial discrimination predicted lower adherence (odds ratio, 0.31; 95% CI, 0.12–0.76) and having internal locus of control predicted better adherence (odds ratio, 1.46; 95% CI, 1.06–2.03) to healthcare follow-up. In the lifestyle domain, higher education (mean difference: 0.75; 95% CI, 0.21–1.29) and lower body mass index (mean difference: −0.08; 95% CI, −0.13 to −0.03) predicted better adherence to dietary recommendations, but no risk factors predicted exercise adherence. Conclusions: Different nonadherence behaviors may stem from different motivation and risk factors (eg, clinic nonattendance due to experiencing racial discrimination). Thus adherence intervention should be individualized to target at-risk population (eg, bias reduction training for medical staff to improve patient adherence to clinic visit).