Association between hematocrit levels and arterial hypertension

Abstract

Background: Arterial hypertension (AH) is a major cardiovascular risk factor worldwide, with a prevalence of 33.1% in Mongolia according to the 2019 STEPS survey. Hematocrit (HCT) is the primary determinant of blood viscosity and has been associated with hypertension in international studies; however, this association has not been sufÏciently investigated in the Mongolian population, providing the rationale for the present study. Aim: To investigate the association between hematocrit levels and arterial hypertension in the Mongolian population. Material and Methods: From 57,108 records of the 2022–2023 national early detection program organized by the Government of Mongolia, 32,626 participants were selected using proportional stratified random sampling by region. AH was defined per Mongolia’s 2018 Clinical Guidelines for Arterial Hypertension in Adults, with blood pressure measured using an automated sphygmomanometer, as SBP ≥130 mmHg or DBP ≥80 mmHg. Statistical analysis included Mann-Whitney U test, Pearson and Spearman correlation, univariate and multivariate logistic regression, and ROC curve analysis. Results: AH was identified in 58.2% of participants (n=18,988). The median HCT in the AH group (43.60%) was significantly higher than in the normotensive group (42.40%, p<0.001). The correlation between HCT and SBP was r=0.152 (p<0.001), with the strongest association observed in the 18–40 age group (r=0.203). ROC curve analysis identified optimal cut-off values of 47.2% for males and 41.8% for females. Conclusions: 1. Hematocrit levels were significantly higher in the hypertensive group compared to the normotensive group and showed a weak positive correlation with both systolic and diastolic blood pressure. 2. Although hematocrit was significantly associated with AH in univariate logistic regression, its independent effect was attenuated in multivariate analysis due to collinearity with hemoglobin. In a separate model with HCT alone adjusted for age, sex, and BMI, the independent association remained statistically significant (aOR=1.260, p<0.001). 3. ROC curve analysis identified sex-specific optimal cut-off values of 47.2% for males and 41.8% for females, highlighting the need to consider sex differences in the Mongolian population. These cut-off values should be regarded as supplementary indicators to be used alongside other cardiovascular risk factors.