Literature showed that soluble fiber has beneficial effects on cardiometabolic risk factors and leptin and adiponectin serum levels. Our aim in this meta-analysis was to determine the effect of soluble fiber supplementation on leptin and adiponectin serum levels. A systematic search was conducted using PubMed, Scopus, and ISI Web of Science for eligible trials up to December 2021. A random-effects model was used to pool calculated effect sizes. Our analysis showed that soluble fiber supplementation did not significantly affect adiponectin (standardized mean difference [SMD], −0.49 Hedges’s, 95% confidence interval [CI], −1.20, 0.21, p value = 0.167; I2 = 95.4, p value < 0.001) and leptin (SMD, −0.8 Hedges’s, 95% CI, −1.70, 0.08, p value = 0.076; I2 = 94.6, p value < 0.001) concentrations in comparison with placebo. However, in the subgroup, soluble fiber supplementation had a significant improvement in leptin concentration in overweight and obese patients (SMD, −0.22 Hedges’s, 95% CI, −0.43, −0.01, p value = 0.048) and a non-significant beneficial effect in adiponectin level in female (SMD, 0.29 Hedges’s, 95% CI, −0.13, 0.71, p value = 0.183) and diabetic patients (SMD, 0.32 Hedges’s, 95% CI, −0.67, 1.32, p value = 0.526). A non-linear association between soluble fiber dosage and adiponectin (pnon-linearity < 0.001) was observed. Soluble fiber supplementation could not change the circulatory leptin and adiponectin levels. However, beneficial effects were seen in overweight and obese leptin, and increases in adiponectin may also be observed in female and diabetic patients. Further studies are needed to confirm this results.
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People with higher genetic predisposition to obesity are more susceptible to cardiovascular diseases (CVDs) and healthy plant-based foods may be associated with reduced risks of obesity and other metabolic markers. We investigated whether healthy plant-foods-rich dietary patterns might have inverse associations with cardiometabolic risk factors in participants at genetically elevated risk of obesity. For this cross-sectional study, 377 obese and overweight women were chosen from health centers in Tehran, Iran. We calculated a healthy plant-based diet index (h-PDI) in which healthy plant foods received positive scores, and unhealthy plant and animal foods received reversed scores. A genetic risk score (GRS) was developed based on 3 polymorphisms. The interaction between GRS and h-PDI on cardiometabolic traits was analyzed using a generalized linear model (GLM). We found significant interactions between GRS and h-PDI on body mass index (BMI) (p = 0.02), body fat mass (p = 0.04), and waist circumference (p = 0.056). There were significant gene-diet interactions for healthful plant-derived diets and BMI-GRS on high-sensitivity C-reactive protein (p = 0.03), aspartate aminotransferase (p = 0.04), alanine transaminase (p = 0.05), insulin (p = 0.04), and plasminogen activator inhibitor 1 (p = 0.002). Adherence to h-PDI was more strongly related to decreased levels of the aforementioned markers among participants in the second or top tertile of GRS than those with low GRS. These results highlight that following a plant-based dietary pattern considering genetics appears to be a protective factor against the risks of cardiometabolic abnormalities.
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This study aimed to investigate if glycated hemoglobin (HgbA1C) as compared to fasting blood glucose is better for reflecting cardiometabolic risk in non-diabetic Korean women. Fasting glucose, HgbA1C and lipid profiles were measured in non-diabetic women without disease (n = 91). The relationships of fasting glucose or HgbA1C with anthropometric parameters, lipid profiles, and liver and kidney functions were analyzed. Both fasting glucose and HgbA1C were negatively correlated with HDL-cholesterol (r = -0.287, p = 0.006; r = -0.261, p = 0.012), and positively correlated with age (r = 0.202, p = 0.008; r = 0.221, p = 0.035), waist circumference (r = 0.296, p = 0.005; r = 0.304, p = 0.004), diastolic blood pressure (DBP) (r = 0.206, p = 0.050; r = 0.225, p = 0.032), aspartate transaminase (AST) (r = 0.237, p = 0.024; r = 0.368, p < 0.0001), alanine transaminase (ALT) (r = 0.296, p = 0.004; r = 0.356, p = 0.001), lipid profiles including triglyceride (r = 0.372, p < 0.001; r = 0.208, p = 0.008), LDL-cholesterol (r = 0.315, p = 0.002; r = 0.373, p < 0.0001) and total cholesterol (r = 0.310, p = 0.003; r = 0.284, p = 0.006). When adjusted for age and body mass index, significant relationships of DBP (r = 0.190, p = 0.049), AST (r = 0.262, p = 0.018), ALT (r = 0.277, p = 0.012), and HDL-cholesterol (r = -0.202, p = 0.049) with HgbA1C were still retained, but those with fasting glucose disappeared. In addition, the adjusted relationships of LDL-cholesterol and total cholesterol with HgbA1C were much greater than those with fasting glucose. These results suggest that glycated hemoglobin may be a better predictor than fasting glucose for cardiometabolic risk in non-diabetic Korean women.
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