Risk Assessment Score and χ2 Automatic Interaction Detection Algorithm for Hypertension Among Africans: Models From the SIREN Study
Document Type
Article
Department
Internal Medicine (East Africa)
Abstract
Background:
This study aimed to develop a risk-scoring model for hypertension among Africans. Methods:
In this study, 4413 stroke-free controls were used to develop the risk-scoring model for hypertension. Logistic regression models were applied to 13 vascular risk factors. We randomly split the data set into training and testing data at a ratio of 80:20. Constant and standardized weights were assigned to factors significantly associated with hypertension in the regression model to develop a probability risk score on a scale of 0% to 100% using a logistic regression model. The model accuracy was assessed to estimate the cutoff score for discriminating between hypertensives.
Results:
Mean age was 59.9±13.3, 56.0% were hypertensives, and 7 factors, including diabetes, age in years, waist circumference, body mass index, highest education completed, family history of cardiovascular diseases, and current alcohol use, were associated with hypertension. Cohen κ was maximal at ≥0.28, and a total probability risk score of ≥0.60 was adopted for both statistical weighting for risk quantification of hypertension in both data sets. The probability risk score presented a good performance—receiver operating characteristic: 64% (95% CI, 61.0–68.0), a sensitivity of 55.1%, specificity of 71.5%, positive predicted value of 70.9%, and negative predicted value of 55.8%, in the test data set. Similarly, decision tree had a predictive accuracy of 67.7% (95% CI, 66.1–69.3) for the training set and 64.6% (95% CI, 61.0–68.0) for the testing data set.
Conclusions:
The novel risk assessment model discriminated hypertensives with good accuracy and will be helpful in the early identification of community-based Africans vulnerable to hypertension for its primary prevention.
Publication (Name of Journal)
Hypertension
DOI
10.1161/HYPERTENSIONAHA.122.20572
Recommended Citation
Asowata, O.,
Okekunle, A.,
Akpa, O.,
Akinyemi, J.,
Fakunle, A.,
Komolafe, M.,
Sarfo, F.,
Akpalu, A.,
Obiako, R.,
Adebayo, P.
(2023). Risk Assessment Score and χ2 Automatic Interaction Detection Algorithm for Hypertension Among Africans: Models From the SIREN Study. Hypertension.
Available at:
https://ecommons.aku.edu/eastafrica_fhs_mc_intern_med/354