Identification of risk factors for hypertension in overweight and obese people and analysis of risk factor interactions: an R-based analysis

Development and validation of a nomogram model for predicting the risk of MAFLD in the young population

This study aimed to develop and validate a nomogram model that includes clinical and laboratory indicators to predict the risk of metabolic-associated fatty liver disease (MAFLD) in young Chinese individuals. This study retrospectively analyzed a cohort of young population who underwent health examination from November 2018 to December 2021 at The Affiliated Hospital of Southwest Medical University in Luzhou City, Sichuan Province, China. We extracted the clinical and laboratory data of 43,040 subjects and randomized participants into the training and validation groups (7:3). Univariate logistic regression analysis, the least absolute shrinkage and selection operator regression, and multivariate logistic regression models identified significant variables independently associated with MAFLD. The predictive accuracy of the model was analyzed in the training and validation sets using area under the receiver operating characteristic (AUROC), calibration curves, and decision curve analysis. In this study, we identified nine predictors from 31 variables, including age, gender, body mass index, waist-to-hip ratio, alanine aminotransferase, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, uric acid, and smoking. The AUROC for the subjects in the training and validation groups was 0.874 and 0.875, respectively. The calibration curves show excellent accuracy of the nomogram. This nomogram which was based on demographic characteristics, lifestyle habits, anthropometrics, and laboratory data can visually and individually predict the risk of developing MAFLD. This nomogram is a quick and effective screening tool for assessing the risk of MAFLD in younger populations and identifying individuals at high risk of MAFLD, thereby contributing to the improvement of MAFLD management.

Investigating the Prevalence and Predictors of Uncontrolled Hypertension: A Cross-Sectional Study in Gujarat, India

BACKGROUND

Uncontrolled hypertension is a major public health concern that contributes significantly to cardiovascular morbidity and mortality. Treatment of hypertension prevents and reduces cardiovascular morbidity, notably a 40% reduction in risk of stroke and a 15% reduction in risk of myocardial infarction. Understanding the prevalence and predictors of uncontrolled hypertension is crucial for developing targeted interventions.

OBJECTIVE

This study aimed to determine the prevalence of uncontrolled hypertension and identify potential predictors among patients attending the Non-Communicable Disease (NCD) clinic of a tertiary care center in Gujarat, India.

METHODS

A cross-sectional study involving 732 adult patients with hypertension was conducted. Sociodemographic data, lifestyle factors, anthropometric measurements, and comorbidities were assessed. Blood pressure was measured using standardized protocols, and uncontrolled hypertension was defined as a systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg. Univariate and multivariate logistic regression analyses were performed to identify predictors of uncontrolled hypertension.

RESULTS

The prevalence of uncontrolled hypertension was 60.2% (95% CI: 56.7%-63.7%). In the multivariate analysis, increasing age (adjusted OR: 1.21, 95% CI: 1.05-1.39), increased body mass index (adjusted OR: 1.49, 95% CI: 1.27-1.75), diabetes (adjusted OR: 1.68, 95% CI: 1.20-2.35), chronic kidney disease (adjusted OR: 2.11, 95% CI: 1.22-3.65), and current smoking status (adjusted OR: 1.83, 95% CI: 1.14-2.93) were identified as independent predictors of uncontrolled hypertension.

CONCLUSION

This study revealed a high prevalence of uncontrolled hypertension in this tertiary care setting. Age, obesity, diabetes, chronic kidney disease, and smoking were identified as significant predictors. Targeted interventions addressing these modifiable risk factors and comorbidities are crucial for improving blood pressure control and reducing the burden of hypertension-related complications.