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Herbal or Dietary Supplement Use and Hypertensive Medications: Does the Combination Relate to Medication Adherence and Blood Pressure Control?

ABSTRACT: Introduction: Medication nonadherence contributes to poor blood pressure control and increases cardiovascular disease risk in patients with hypertension. Identifying modifiable risk factors for low or nonadherence to antihypertensive medication is needed. Studies that have examined the relationship between herbal or dietary supplement (HDS) use and antihypertensive medication nonadherence provide inconsistent findings. Data from the National Health and Nutrition Examination Survey were used to examine the association between HDS use, current use of prescribed antihypertensive medication, and blood pressure status. Methods: The study sample included hypertensive adults (n = 5,478) who have been told by a health professional to take prescribed medication for their health condition. Respondents were classified as either HDS users or HDS nonusers. Depending on the kind of supplement used, HDS users were further divided into three mutually exclusive groups: hypertension HDS users, nonhypertension HDS users, and those who used both kinds of supplements. Supplements groupings were based on reports in the literature. Blood pressure status definition was based on Eighth Joint National Committee (JNC 8) recommendations. Adjusted odds ratios (aORs) and 95% confidence intervals (95% CIs) were obtained from logistic models. Results: Overall HDS use prevalence was 62%. Current medication use did not significantly differ between patients reporting no HDS use and those reporting HDS use (aOR: 1.45; 95% CI: 0.78-2.69). No observable differences were found in current medication use between patients reporting no HDS use and those taking nonhypertension HDS or both kinds of supplements. Use of hypertension HDS was associated with improved blood pressure (aOR: 1.90; 95% CI: 1.07-3.36) compared with no HDS use. Conclusion: In a nationally representative U.S. sample, HDS use did not compromise current use of prescribed medication and was associated with improved blood pressure control. More research is needed to better understand why HDS use is associated with better blood pressure control.

SUBMITTER: Nagawa CS

PROVIDER: S-EPMC8020560 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThis study assesses the feasibility of using machine learning methods such as Random Forests (RF), Artificial Neural Networks (ANN), Support Vector Regression (SVR) and Self-Organizing Feature Maps (SOM) to identify and determine factors associated with hypertensive patients' adherence levels. Hypertension is the medical term for systolic and diastolic blood pressure higher than 140/90 mmHg. A conventional medication adherence scale was used to identify patients' adherence to their prescribed medication. Using machine learning applications to predict precise numeric adherence scores in hypertensive patients has not yet been reported in the literature.MethodsData from 160 hypertensive patients from a tertiary hospital in Kuala Lumpur, Malaysia, were used in this study. Variables were ranked based on their significance to adherence levels using the RF variable importance method. The backward elimination method was then performed using RF to obtain the variables significantly associated with the patients' adherence levels. RF, SVR and ANN models were developed to predict adherence using the identified significant variables. Visualizations of the relationships between hypertensive patients' adherence levels and variables were generated using SOM.ResultMachine learning models constructed using the selected variables reported RMSE values of 1.42 for ANN, 1.53 for RF, and 1.55 for SVR. The accuracy of the dichotomised scores, calculated based on a percentage of correctly identified adherence values, was used as an additional model performance measure, resulting in accuracies of 65% (ANN), 78% (RF) and 79% (SVR), respectively. The Wilcoxon signed ranked test reported that there was no significant difference between the predictions of the machine learning models and the actual scores. The significant variables identified from the RF variable importance method were educational level, marital status, General Overuse, monthly income, and Specific Concern.ConclusionThis study suggests an effective alternative to conventional methods in identifying the key variables to understand hypertensive patients' adherence levels. This can be used as a tool to educate patients on the importance of medication in managing hypertension.

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Herbal or Dietary Supplement Use and Hypertensive Medications: Does the Combination Relate to Medication Adherence and Blood Pressure Control?

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