Associations of erythrocyte membrane fatty acids with blood pressure in children

Background & aims: Different fatty acids may vary in their effect on blood pressure. We tested whether fatty acid classes measured in erythrocytes are associated with blood pressure. Methods: This cross-sectional study included 421 children from Guangzhou, China. Erythrocyte membrane fatty acid concentrations were measured by gas chromatography-mass spectrometry. Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured with an electronic sphygmomanometer. Abnormal blood pressure (ABP) was defined as an elevated SBP and/or DBP. Analysis of covariance (ANCOVA) and multivariable logistic regression models were performed to explore the associations of fatty acid subgroups with the risk of blood pressure status. The joint effect of fatty acid subgroups was evaluated using Probit Bayesian Kernel Machine Regression (BKMR). Results: ANCOVA analysis showed that children in the higher quartiles of odd-chain saturated fatty acids (OSFAs) had significantly lower levels of both SBP (P-trend = 0.020) and DBP (P-trend = 0.008). In contrast, DBP increased significantly across quartiles of monounsaturated fatty acids (MUFAs). In adjusted models of logistic regression analysis, the higher quartiles of MUFAs concentrations were associated with a higher risk of ABP (P-trend = 0.001). BKMR analysis showed that the risk of ABP increased significantly with increasing total MUFAs mixture levels. Similar associations were observed between MUFAs and DBP. Conversely, OSFAs concentrations were negatively correlated with both SBP and DBP. Additionally, children with higher levels of mixture of n-3 polyunsaturated fatty acids (n-3 PUFAs) exhibited lower SBP. Conclusions: Fatty acid subclasses may differ in their relationship with abnormal blood pressure in children. MUFAs exhibit a positive association with blood pressure, whereas OSFAs and n-3 PUFAs demonstrate an inverse association with blood pressure. (c) 2025 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights are reserved, including those for text and data mining, AI training, and similar technologies.