Serum Folate in Relation to Lipid Abnormalities in Community-Dwelling Adults: A Population-Based Cross-Sectional Study in Zhejiang Province, China.
X, C., J, L., L, C., W, Y., J, Z., & M, L. (2026). Serum Folate in Relation to Lipid Abnormalities in Community-Dwelling Adults: A Population-Based Cross-Sectional Study in Zhejiang Province, China.. Nutrients. https://doi.org/10.3390/nu18122024
X C, J L, L C, W Y, J Z, M L. Serum Folate in Relation to Lipid Abnormalities in Community-Dwelling Adults: A Population-Based Cross-Sectional Study in Zhejiang Province, China.. Nutrients. 2026; doi: 10.3390/nu18122024
X C, J L, L C, et al. Serum Folate in Relation to Lipid Abnormalities in Community-Dwelling Adults: A Population-Based Cross-Sectional Study in Zhejiang Province, China.[J]. Nutrients. 2026. DOI: 10.3390/nu18122024.
@article{x2026,
author = {Chen X and Lin J and Chen L and Yao W and Zhong J and Liang M},
title = {Serum Folate in Relation to Lipid Abnormalities in Community-Dwelling Adults: A Population-Based Cross-Sectional Study in Zhejiang Province, China.},
journal = {Nutrients},
year = {2026},
doi = {10.3390/nu18122024},
note = {PMID: 42356410},
}
TY - JOUR AU - Chen X AU - Lin J AU - Chen L AU - Yao W AU - Zhong J AU - Liang M TI - Serum Folate in Relation to Lipid Abnormalities in Community-Dwelling Adults: A Population-Based Cross-Sectional Study in Zhejiang Province, China. T2 - Nutrients PY - 2026 DO - 10.3390/nu18122024 AN - PMID:42356410 ER -
Objectives: This study aimed to examine the cross-sectional associations between serum folate concentrations and four lipid abnormality subtypes among community-dwelling adults in Zhejiang Province, China. Methods: This population-based cross-sectional study included 3254 adults from Zhejiang Province, China. Serum folate concentrations were analyzed both as quartiles and per 1-standard deviation (SD) increments. Multivariable logistic regression models were used to evaluate the associations of serum folate with hypercholesterolemia, hypertriglyceridemia, high low-density lipoprotein cholesterol (LDL-C), and low high-density lipoprotein cholesterol (HDL-C). Restricted cubic spline (RCS) regression models were further applied to assess dose-response patterns. Additional RCS analyses using continuous lipid parameters were also performed. False discovery rate (FDR) correction, exploratory subgroup analyses, and sensitivity analyses were additionally conducted. Results: The prevalences of hypercholesterolemia, hypertriglyceridemia, high LDL-C, and low HDL-C were 7.87%, 17.12%, 4.30%, and 4.46%, respectively. In the fully adjusted model, each 1-SD increment in serum folate was associated with lower odds of hypertriglyceridemia (OR = 0.82, 95% CI: 0.73-0.92) and low HDL-C (OR = 0.63, 95% CI: 0.49-0.81). Compared with the lowest quartile, participants in the highest serum folate quartile had lower odds of hypertriglyceridemia (OR = 0.62, 95% CI: 0.46-0.82) and low HDL-C (OR = 0.38, 95% CI: 0.22-0.64), with significant trends across quartiles (both p for trend < 0.001). No significant associations were observed for hypercholesterolemia or high LDL-C. These findings remained significant after FDR correction. RCS analyses suggested an overall inverse association between serum folate and hypertriglyceridemia, with no evidence of nonlinearity (p for overall = 0.001; p for nonlinearity = 0.212), whereas the association with low HDL-C showed evidence of nonlinearity (p for overall < 0.001; p for nonlinearity = 0.009). Additional RCS analyses using continuous lipid parameters showed broadly consistent findings for TG and HDL-C. Exploratory subgroup and sensitivity analyses showed generally similar results. Conclusions: Higher serum folate concentrations were cross-sectionally associated with lower odds of hypertriglyceridemia and low HDL-C among community-dwelling adults in Zhejiang Province, China, whereas no significant associations were observed for hypercholesterolemia or high LDL-C. Further prospective cohort studies are warranted to verify these cross-sectional findings and to explore underlying mechanisms.