AUTHOR=Fang Fang , Qin Defeng , Li Yong , Liu Fang , Wu Jinlin 

TITLE=Effects of curcumin on dyslipidemia and body mass index in metabolic disorders: a systematic review and meta-analysis

JOURNAL=Frontiers in Nutrition

VOLUME=Volume 12 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/nutrition/articles/10.3389/fnut.2025.1655775

DOI=10.3389/fnut.2025.1655775

ISSN=2296-861X

ABSTRACT=ObjectiveThis study aimed to investigate the effects of curcumin on blood lipid levels and body mass index (BMI) in patients with metabolic diseases.MethodsA systematic database search identified 587 records, from which 11 randomized controlled trials (RCTs) involving 662 participants were included. The analysis evaluated changes in triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and BMI. Both fixed-effects models (FEM) and random-effects models (REM) were used for statistical analysis. Funnel plot asymmetry tests (Begg and Egger), Baujat, and Galbraith analyses assessed heterogeneity and potential publication bias. Cochrane RevMan (version 2.0) evaluated the risk of bias.ResultsCurcumin supplementation significantly reduced TG levels [mean difference (MD): −16.76 mg/dL, REM], TC levels (MD: −10.59 mg/dL, FEM), and BMI (MD: −0.94 kg/m2 in both models). However, no significant effect was found for HDL-C and LDL-C under the random-effects model, whereas fixed-effects models showed variable results, highlighting the inconsistency and the need for further investigation. For HDL-C, the random-effects model (REM), which accounts for high heterogeneity (I2 = 83%), showed no significant change (MD: −1.90 mg/dL, p = 0.11), while the fixed-effects model (FEM) indicated a modest increase. Due to substantial between-study variability, the REM results are more reliable and suggest no consistent effect of curcumin on HDL-C levels. For LDL-C, the random-effects model (REM), which accommodates high heterogeneity (I2 = 67%), showed no significant reduction (MD: 5.01 mg/dL, p = 0.12), whereas the fixed-effects model (FEM) suggested a significant effect. Given the heterogeneity, REM is more appropriate, and the results do not support a consistent LDL-lowering effect of curcumin. Subgroup analyses suggested that study quality, regional differences, and outlier studies contributed to high heterogeneity.ConclusionCurcumin effectively reduced levels of TG, TC, and BMI in patients with metabolic diseases. However, its effects on HDL-C and LDL-C were inconsistent and non-significant under random-effects models, indicating limited efficacy for these endpoints. Providing a more detailed context for the variability in lipid outcomes enhances understanding, especially for non-expert audiences.