Bioelectrical impedance analysis predicts prehypertension and hypertension: A hospital-based cross-sectional study

Abstract

Background Hypertension prediction using anthropometry and bioimpedance offers practical advantages for screening. We aimed to analyze various anthropometric and bioelectrical impedance (BIA) estimates as predictive markers of prehypertension and hypertension. Methods This cross-sectional analysis included 432 adult participants recruited from the medicine outpatient department of a tertiary hospital. Blood pressure measurements; anthropometric measurements of weight, body mass index, waist circumference, and hip circumference; and BIA (Omron HBF 375) were performed for body fat%, resting metabolic rate, visceral fat level, and skeletal muscle percentage. Results Of the 432 participants comprising 220 males and 212 females, 36.8% were normotensive, 42% were prehypertensive, and 21% were hypertensive. Visceral fat (r 0.662, 95% CI: 0.60–0.72, P < 0.001) and resting metabolic rate (r 0.589, 95% CI: 0.52–0.65, P < 0.001) had the highest positive correlation, while skeletal muscle percentage (r -0.551, 95% CI: -0.62 to -0.48, P < 0.001) had a negative correlation with systolic blood pressure according to bivariate analysis. According to the receiver operating characteristic curve analysis for predicting hypertension, visceral fat volume had an area under curve (AUC) of 0.913, and resting metabolic rate had an AUC of 0.968, indicating the best predictive accuracy. Conclusion Multiple BIA estimates, including high visceral fat content, resting metabolic rate, and adipose marker levels combined with low skeletal muscle percentage, were strongly associated with hypertension. Our analysis suggested the superiority of bioimpedance predictors over anthropometry-based prediction modeling alone for screening for hypertension in clinical practice.

Keywords

• bioelectrical impedance analysis
• body composition
• hypertension
• prehypertension
• skeletal muscle mass
• visceral fat