Body mass index, body fat percentage, and visceral fat as mediators in the association between health literacy and hypertension among residents living in rural and suburban areas

Nguyen, Tham T.; Nguyen, Minh H.; Nguyen, Yen H.; Nguyen, Thao Thanh; Giap, Manh H.; Tran, Thanh; Pham, Thu Trang; Pham, Khue M.; Nguyen, Kien Trung; Le, Vinh-Tuyen T.; Su, Chien‐Tien; Duong, Tuyen Van

doi:10.3389/fmed.2022.877013

Cited by 4 publications

(3 citation statements)

References 73 publications

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“…This might be as family member share same genetic factors, behaviors, mostly similar lifestyle, and environments related factor that could influence the risk of HTN disease. Additionally, other risk factors such as salt, drinking alcohol, and smoking were found to be an important contributing risk factors of HTN, which is similar with other studies in literature [ 68 , 69 ]. Although this work has many strengths, it also has some limitations, such as the sample only included permanent the residents of the city administration who had lived in the area for more than six months and were older than 30.…”

Section: Discussionsupporting

confidence: 90%

Predicting the risk of hypertension using machine learning algorithms: A cross sectional study in Ethiopia

Islam,

Alam,

Maniruzzaman

et al. 2023

PLoS ONE

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Background and objectives Hypertension (HTN), a major global health concern, is a leading cause of cardiovascular disease, premature death and disability, worldwide. It is important to develop an automated system to diagnose HTN at an early stage. Therefore, this study devised a machine learning (ML) system for predicting patients with the risk of developing HTN in Ethiopia. Materials and methods The HTN data was taken from Ethiopia, which included 612 respondents with 27 factors. We employed Boruta-based feature selection method to identify the important risk factors of HTN. The four well-known models [logistics regression, artificial neural network, random forest, and extreme gradient boosting (XGB)] were developed to predict HTN patients on the training set using the selected risk factors. The performances of the models were evaluated by accuracy, precision, recall, F1-score, and area under the curve (AUC) on the testing set. Additionally, the SHapley Additive exPlanations (SHAP) method is one of the explainable artificial intelligences (XAI) methods, was used to investigate the associated predictive risk factors of HTN. Results The overall prevalence of HTN patients is 21.2%. This study showed that XGB-based model was the most appropriate model for predicting patients with the risk of HTN and achieved the accuracy of 88.81%, precision of 89.62%, recall of 97.04%, F1-score of 93.18%, and AUC of 0. 894. The XBG with SHAP analysis reveal that age, weight, fat, income, body mass index, diabetes mulitas, salt, history of HTN, drinking, and smoking were the associated risk factors of developing HTN. Conclusions The proposed framework provides an effective tool for accurately predicting individuals in Ethiopia who are at risk for developing HTN at an early stage and may help with early prevention and individualized treatment.

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Section: Discussionsupporting

confidence: 90%

Predicting the risk of hypertension using machine learning algorithms: A cross sectional study in Ethiopia

Islam,

Alam,

Maniruzzaman

et al. 2023

PLoS ONE

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“…Overall, the intervention in this study led to significant improvements in all outcome measures, successfully achieving the desired outcomes in hypertension treatment. These findings align with previous research highlighting the relationship between health literacy, BMI control, and hypertension control [38,39]. This serves as evidence for implementing additional community health education activities with non-professional resources which might enhance the outcomes of hypertensives with affordable resources.…”

Section: Discussionsupporting

confidence: 88%

Effectiveness of a Health Education Program in Hypertensive Patients with Dyslipidemia and/or Microalbuminuria: A Quasi-Experimental Study in Vinh Long Province, Vietnam

Le,

Nguyen,

Pham

et al. 2023

Healthcare

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Introduction: Hypertension, a major health concern, is associated with significant mortality and disease burden worldwide, including Vietnam. Comprehensive interventions targeting medication, lifestyle modifications, dyslipidemia (DLP), and microalbuminuria (MAU) are vital for effective hypertension management and reducing the risk of cardiovascular disease complications (CDV). While medication interventions have proven efficacy, the evidence regarding the effectiveness of community-based health education interventions in managing DLP and MAU is limited. Therefore, this study aims to evaluate the effectiveness of community health education interventions in reducing hypertension risk factors and achieving hypertension management objectives, as well as managing DLP and MAU among hypertension patients. Methods: A quasi-experimental study was conducted on 330 hypertensive patients with dyslipidemia (DLP) and/or microalbuminuria (MAU) who were divided into a control group (n = 164) and an intervention group (n = 166). The control group received standard national hypertension management, while the intervention group received additional intensive health education provided by trained volunteers. The effectiveness of the intervention was assessed by comparing outcomes such as lifestyle factors, BMI control, treatment adherence, hypertension control, and DLP and MAU status between the two groups before and after a two-year intervention period. Results: The health education intervention resulted in significant reductions in dietary risk factors, specifically in fruit and vegetable consumption (p < 0.001). There was a lower prevalence of high salt intake in the intervention group compared to the control group (p = 0.002), while no significant differences were observed in other dietary factors. Smoking habits and low physical activity significantly decreased in the intervention group, with a notable disparity in physical activity proportions (p < 0.001). Both groups showed significant improvements in achieving hypertension management targets, with the intervention group demonstrating superior outcomes. The intervention was effective in reducing the prevalence of risk factors, particularly treatment non-adherence, blood pressure control, and low physical activity. Additionally, the intervention group had a higher likelihood of achieving DLP and MAU control compared to the control group. Conclusions: This study underscored the additional positive impact of incorporating health education by non-professional educators in achieving favorable outcomes, including better control of BMI, blood pressure, medication adherence, and management of dyslipidemia (DLP) and microalbuminuria (MAU). Further research is warranted to fully explore the potential of health education in primary healthcare settings and maximize its effectiveness.

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“…In addition, in the higher quartiles of the TyG-BMI index, VFA, PBF and abdominal obesity were signi cantly higher than in the lower quartiles. Previous studies have also shown a positive relationship between VFA, WC, Visceral adiposity index (VAI) and body fat mass with hypertension [17,30,31]. These results indicate the importance of obesity (abdominal, general and increased fat) in the development of hypertension.…”

Section: Discussionsupporting

confidence: 59%

Triglyceride glucose-body mass index and hypertension risk in Iranian adults; a population-based study

Nikbakht

Najafi

Shakiba

et al. 2023

Preprint

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Background Insulin resistance (IR) and obesity are risk factors for hypertension; triglyceride-glucose (TyG) is known as a surrogate for IR. The present study investigated the association between the triglyceride-glucose body mass index (TyG-BMI) index and the risk of hypertension in Iranian adults. Methods This study was conducted on a sample of 8,610 participants from the baseline phase of the Ravansar non- communicable diseases (RaNCD) in Iran. A logistic regression model was used to evaluate the relationship between TyG-BMI and hypertension. Receiver operating characteristic (ROC) curve analysis was conducted to estimate the predictive power of TyG-BMI for hypertension. Results A total of 4176 men and 4434 women with an average age of 46.74 years were examined. The anthropometric indices were significantly higher in hypertensive than normotensive subjects (P < 0.001). The level of physical activity was significantly higher in the bottom quartiles (P < 0.001). The odds of hypertension in the highest quartile and 3.10 (95% CI: 2.28, 4.16) times significantly higher than the bottom quartile of the TyG-BMI index. The discriminating ability of TyG-BMI to predict blood pressure was 61% (AUC: 0.61; 95% CI: 0.57, 0.63), and higher than BMI and TyG. Conclusion The TyG-BMI index is associated with an increase in the odds of hypertension. Therefore, the TyG-BMI index can be a new clinical index for early diagnosis of hypertension. Lifestyle modifications such as weight control through physical activity and a healthy diet can help improve IR and prevent hypertension.

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Body mass index, body fat percentage, and visceral fat as mediators in the association between health literacy and hypertension among residents living in rural and suburban areas

Cited by 4 publications

References 73 publications

Predicting the risk of hypertension using machine learning algorithms: A cross sectional study in Ethiopia

Predicting the risk of hypertension using machine learning algorithms: A cross sectional study in Ethiopia

Effectiveness of a Health Education Program in Hypertensive Patients with Dyslipidemia and/or Microalbuminuria: A Quasi-Experimental Study in Vinh Long Province, Vietnam

Triglyceride glucose-body mass index and hypertension risk in Iranian adults; a population-based study

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