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Is there a nonadherent subtype of hypertensive patient? A latent class analysis approach

Authors Trivedi R, Ayotte BJ, Thorpe CT, Edelman D, Bosworth HB

Published 16 July 2010 Volume 2010:4 Pages 255—262

DOI https://doi.org/10.2147/PPA.S11335

Review by Single-blind

Peer reviewer comments 2

Ranak B Trivedi1, Brian J Ayotte2, Carolyn T Thorpe3, David Edelman4, Hayden B Bosworth5

1Northwest Health Services Research and Development Service Center of Excellence, VA Puget Sound Health Care System, Seattle, Washington; 2Boston VA Health Care System, Boston, Massachusetts; 3Department of Population Health Sciences, University of Wisconsin, Madison, Wisconsin; 4Department of Medicine, Duke University Medical Center, Durham, North Carolina; 5Research Professor, Department of Medicine, Duke University Medical Center, Durham, North Carolina, USA

Abstract: To determine subtypes of adherence, 636 hypertensive patients (48% White, 34% male) reported adherence to medications, diet, exercise, smoking, and home blood pressure monitoring. A latent class analysis approach was used to identify subgroups that adhere to these five self-management behaviors. Fit statistics suggested two latent classes. The first class (labeled “more adherent”) included patients with greater probability of adhering to ­recommendations compared with the second class (labeled “less adherent”) with regard to nonsmoking (97.7% versus 76.3%), medications (75.5% versus 49.5%), diet (70.7% versus 46.9%), exercise (63.4% versus 27.2%), and blood pressure monitoring (32% versus 3.4%). Logistic regression analyses used to characterize the two classes showed that “more adherent” participants were more likely to report full-time employment, adequate income, and better emotional and physical well-being. Results suggest the presence of a less adherent subtype of hypertensive patients. Behavioral interventions designed to improve adherence might best target these at-risk patients for greater treatment efficiency.

Keywords: adherence, hypertension, latent class analysis, self-management

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