ArticleInternational journal of environmental research and public health2018
Prediction of Prehypertenison and Hypertension Based on Anthropometry, Blood Parameters, and Spirometry.
Article in International journal of environmental research and public health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Machine Learning for Hypertension Prediction: a Systematic Review.Current hypertension reports · 2022Pooled it
- Caffeine and Exercise in Obesity-Associated Brain Aging and Neurodegeneration: Mechanistic Insights into AMPK/SIRT1/PGC-1α, BDNF/TrkB, and NLRP3 Inflammasome Signaling.Molecular neurobiology · 2026Review
- Machine-Learning-Based Prediction of Hypertension and Its Risk Factors Among Adults in the Northern Region of Bangladesh.Journal of diabetes research · 2026Article
- Explainable machine learning for hypertension prevalence classification: a cross-sectional study in Hainan Province, China.Frontiers in cardiovascular medicine · 2026Article
- Sex differences in hypertension incidence and risk factors: a population-based cohort study in Southern Iran.BMC public health · 2024Article
- Design and Development of IoT and Deep Ensemble Learning Based Model for Disease Monitoring and Prediction.Diagnostics (Basel, Switzerland) · 2023Article
- Intra-person multi-task learning method for chronic-disease prediction.Scientific reports · 2023Article
- Development of a convenient and effective hypertension risk prediction model and exploration of the relationship between Serum Ferritin and Hypertension Risk: a study based on NHANES 2017-March 2020.Frontiers in cardiovascular medicine · 2023Article
- Development and validation of a model to predict the risk of hypertension using anthropometric indicators in the Chinese population: a retrospective cohort study.American journal of translational research · 2023Article
- Machine Learning Approaches for Predicting Hypertension and Its Associated Factors Using Population-Level Data From Three South Asian Countries.Frontiers in cardiovascular medicine · 2022Article
- Determinants of Longitudinal Change of Lung Function in Different Gender in a Large Taiwanese Population Follow-Up Study Categories: Original Investigation.Journal of personalized medicine · 2021Article
- A risk scoring system to predict the risk of new-onset hypertension among patients with type 2 diabetes.Journal of clinical hypertension (Greenwich, Conn.) · 2021Article
- An Application of Machine Learning to Etiological Diagnosis of Secondary Hypertension: Retrospective Study Using Electronic Medical Records.JMIR medical informatics · 2021Article
- Reconstruction error based deep neural networks for coronary heart disease risk prediction.PloS one · 2019Article
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2 authors.
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Abstract
Hypertension and prehypertension are risk factors for cardiovascular diseases. However, the associations of both prehypertension and hypertension with anthropometry, blood parameters, and spirometry have not been investigated. The purpose of this study was to identify the risk factors for prehypertension and hypertension in middle-aged Korean adults and to study prediction models of prehypertension and hypertension combined with anthropometry, blood parameters, and spirometry. Binary logistic regression analysis was performed to assess the statistical significance of prehypertension and hypertension, and prediction models were developed using logistic regression, naïve Bayes, and decision trees. Among all risk factors for prehypertension, body mass index (BMI) was identified as the best indicator in both men [odds ratio (OR) = 1.429, 95% confidence interval (CI) = 1.304⁻1.462)] and women (OR = 1.428, 95% CI = 1.204⁻1.453). In contrast, among all risk factors for hypertension, BMI (OR = 1.993, 95% CI = 1.818⁻2.186) was found to be the best indicator in men, whereas the waist-to-height ratio (OR = 2.071, 95% CI = 1.884⁻2.276) was the best indicator in women. In the prehypertension prediction model, men exhibited an area under the receiver operating characteristic curve (AUC) of 0.635, and women exhibited a predictive power with an AUC of 0.777. In the hypertension prediction model, men exhibited an AUC of 0.700, and women exhibited an AUC of 0.845. This study proposes various risk factors for prehypertension and hypertension, and our findings can be used as a large-scale screening tool for controlling and managing hypertension.
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