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

dc.contributor.author

Trivedi, Ranak B

dc.contributor.author

Ayotte, Brian J

dc.contributor.author

Thorpe, Carolyn T

dc.contributor.author

Edelman, David

dc.contributor.author

Bosworth, Hayden B

dc.date.accessioned

2024-02-01T20:21:32Z

dc.date.available

2024-02-01T20:21:32Z

dc.date.issued

2010-07

dc.description.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.

dc.identifier.issn

1177-889X

dc.identifier.issn

1177-889X

dc.identifier.uri

https://hdl.handle.net/10161/30107

dc.language

eng

dc.publisher

Informa UK Limited

dc.relation.ispartof

Patient preference and adherence

dc.relation.isversionof

10.2147/ppa.s11335

dc.rights.uri

https://creativecommons.org/licenses/by-nc/4.0

dc.subject

adherence

dc.subject

hypertension

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latent class analysis

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self-management

dc.title

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

dc.type

Journal article

duke.contributor.orcid

Edelman, David|0000-0001-7112-6151

duke.contributor.orcid

Bosworth, Hayden B|0000-0001-6188-9825

pubs.begin-page

255

pubs.end-page

262

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Duke

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School of Medicine

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Basic Science Departments

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Clinical Science Departments

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Institutes and Centers

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Medicine

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Psychiatry & Behavioral Sciences

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Medicine, General Internal Medicine

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Duke Cancer Institute

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Duke Clinical Research Institute

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Institutes and Provost's Academic Units

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Center for the Study of Aging and Human Development

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Initiatives

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Duke Science & Society

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Population Health Sciences

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Duke Innovation & Entrepreneurship

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Psychiatry & Behavioral Sciences, Behavioral Medicine & Neurosciences

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Duke - Margolis Center For Health Policy

pubs.publication-status

Published

pubs.volume

4

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