This study aimed to assess the association of dietary fiber intake with serum uric acid (SUA) levels and risk of hyperuricemia (HUA) among Chinese adults using the latest nationally representative data. A total of 66,427 Chinese adults aged 18 years and over from the China Adult Chronic Disease and Nutrition Surveillance in 2015 were included in this study. Dietary intakes were measured with a 3-day 24 h dietary recall and the household condiment weighing method. Mixed-effect linear and logistic regression models were used to evaluate the associations of dietary fiber intake with SUA levels and risk of HUA, respectively. Compared to the lowest intake group, the coefficient and 95% confidence in the highest intake group of total fiber were −0.06 (−0.08, −0.04) (p-trend < 0.001), −0.18 (−0.2, −0.16) (p-trend < 0.001) for cereal fiber, 0.03 (0.01, 0.04) (p-trend = 0.051) for legume fiber, 0 (−0.01, 0.02) (p-trend = 0.869) for vegetable fiber and 0.01 (−0.001, 0.04) (p-trend = 0.296) for fruit fiber. The odds ratio (OR) and 95% confidence interval (CI) of HUA for the highest vs. lowest intake group of total fiber were 0.88 (0.84, 0.91) (p-trend = 0.001), 0.67 (0.63, 0.71) (p-trend < 0.001) for cereal fiber, 1.05 (1, 1.09) (p-trend = 0.248) for legume fiber, 1.01 (0.97, 1.05) (p-trend = 0.982) for vegetable fiber and 1.06 (1, 1.12) (p-trend = 0.264) for fruit fiber. Our findings suggest that consumption of total fiber and cereal fiber were significantly inversely associated with SUA levels and HUA risk among the Chinese adult population. Developing and implementing effective public education programs are urgently needed to increase the intake of dietary fiber, especially cereal fiber among Chinese adults.

This study aimed to explore the association between dietary BCAAs, blood lipid levels and risk of dyslipidemia. In this case–control study, a total of 9541 subjects with normal blood lipids were included as a control group, and 9792 patients with dyslipidemia were included as a case group. Dietary BCAA intake data were measured using 3-day 24 h meal recalls and household condiment weighing. All samples were from China Nutrition and Health Surveillance (2015). Generalized linear model, logistic regression, and restricted cubic spline (RCS) were used to evaluate the relationship between dietary BCAAs, blood lipids and dyslipidemia. After adjusting for confounding factors, dietary BCAAs were positively correlated with TC and LDL-C (p < 0.05). Higher dietary BCAAs were associated with higher OR for Hypercholesteremia (Q4 vs. Q1, OR = 1.29, 95% CI: 1.05–1.58, p-trend = 0.034). The ORs of Hyper-LDL-cholesterolemia showed inverted U-shaped with increasing dietary BCAAs (Q3 vs. Q1, OR = 1.20, 95% CI: 1.03–1.39; Q2 vs. Q1, OR = 1.05, 95% CI: 1.01–1.31). The relationship between dietary BCAAs and the risk of Hypercholesteremia and Hyper-LDL-cholesterolemia were both nonlinear (p nonlinearity = 0.0059, 0.0198). Our study reveals that dietary BCAAs are associated with specific types of lipids and risk of dyslipidemia, some of which may be non-linear.

The aim of the present study was to examine whether serum Zn concentrations were associated with metabolic risk factors in Chinese children and adolescents. This was a cross-sectional study including 3241 participants, aged 6 to 17 years, from Jiangsu, China. Metabolic risk factors included fasting glucose (FG), total cholesterol (TC), TAG, HDL-cholesterol, LDL-cholesterol, systolic blood pressure and diastolic blood pressure. Data were analysed using multi-variable linear regression and generalised additive models, which were adjusted for age, sex, high-sensitive C-reactive protein, estimated glomerular filtration rate, BMI and region of residence, to assess the associations of serum Zn concentrations with metabolic risk factors. We observed a negative association between serum Zn concentrations and FG (coefficient = −0·532; 95 % CI −0·569, −0·495; P < 0·001). Moreover, TC (coefficient = 0·175; 95 % CI 0·127, 0·222; P < 0·001), HDL-cholesterol (coefficient = 0·137; 95 % CI 0·082, 0·193; P < 0·001) and LDL-cholesterol (coefficient = 0·195; 95 % CI 0·128, 0·263; P < 0·001) were found to be positively associated with Zn levels. A generalised additive model showed that the negative association between serum Zn and FG was weak at lower serum Zn concentrations and was stronger with the increase in serum Zn concentrations. Additionally, a U-shaped association between serum Zn and TAG was observed. Serum Zn concentrations were associated with FG, TC, TAG, HDL-cholesterol and LDL-cholesterol levels in Chinese children and adolescents. Lower levels of serum Zn were more likely related to a poor metabolic status.

Background: To study the relationship between serum vitamin A (VA) level and blood lipid profiles in children and adolescents aged 6–18 years, as well as the effect of VA on dyslipidemia. Methods: The project adopted a multistage stratified cluster sampling method. The Food Frequency Questionnaire (FFQ) was used to obtain dietary factors data. Blood samples of subjects were taken via venipuncture. Generalized linear models were used to explore the correlation be-tween VA and biochemical indicators, as well as stratified and inter-actions analysis to explore the influence of confounders on these relationships. Generalized linear models were constructed to explore the association between VA and blood lipids. Restricted cubic splines were used to characterize dose–response associations between serum VA and dyslipidemia based on logistic regression. Results: Serum VA was positively correlated with TC, TG and HDL-C (p < 0.05), but these associations were influenced by age (p < 0.05). The adjusted odds ratio (OR) values of VA for hypercho lesterolemia, hypertriglyceridemia, mixed hyperlipidemia and low high-density lipoprotein cholesterolemia were 3.283, 3.239, 5.219 and 0.346, respectively (p < 0.01). Meanwhile, significant age interactions affected the relationship between VA and TC, as well as TG and LDL-C (p < 0.01). Conclusion: Serum VA was positively correlated with blood lipids, but these associations were influenced by age. VA was a risk factor for dyslipidemias, such as hypercholesterolemia, hypertriglyceridemia and mixed hyperlipidemia, but was a protective factor for low high-density lipoprotein cholesterolemia.

Background: Evidence remains limited on the effects of dietary betaine intake and dyslipidemia. We aim to investigate the association between dietary betaine intake and dyslipidemia in Chinese children and adolescents and illustrate the differences in these associations stratified by different food sources. Methods: Based on a national cross-sectional study from the China National Nutrition and Health Surveillance of Children and Lactating Mothers, 11,452 individuals aged 6–17 years were enrolled between October 2016 and December 2018. Participants were divided into quartiles according to residual energy-adjusted dietary betaine intake. The associations of dietary betaine with dyslipidemia and lipid profiles were estimated using restricted cubic spline regression and logistic regression analysis. Results: Among the 11,452 participants, 2577 (22.5%) individuals were found to have dyslipidemia. The median (IQR) intake of dietary betaine was 56.35 (25.77, 207.66) mg/day. Negative dose-dependent associations were found between residual energy-adjusted dietary betaine intake and dyslipidemia. Compared with participants in the lowest quartile (Q1) of residual energy-adjusted betaine intake, participants in the fourth quartile (Q4) had lower odds of high total cholesterol (TC), high low-density lipoprotein cholesterol (LDL-C), high non-high-density lipoprotein cholesterol (non-HDL-C), high remnant cholesterol (RC), and dyslipidemia, with odds ratios (OR) and 95% confidence intervals (95% CI) of 0.56 (0.45, 0.70), 0.65 (0.48, 0.87), 0.53 (0.41, 0.68), 0.42 (0.28, 0.61), and 0.79 (0.69, 0.91), respectively. Furthermore, reduced odds of high TC, high LDL-C, high non-HDL-C, high RC, and dyslipidemia were observed in dietary betaine from plant-source foods but not in animal-source foods. Conclusions: High intake of dietary betaine (56.35–207.66 mg/day) was associated with reduced odds of dyslipidemia, including elevated TC, LDL-C, non-HDL-C, and RC, and dietary betaine from plant-source foods revealed significant benefits for dyslipidemia in Chinese children and adolescents.

Background High-sensitivity C-reactive protein (hs-CRP) is a protein that indicates inflammation and the risk of cardiovascular diseases. The intake of dietary amino acids can influence immune and inflammatory reactions. However, studies on the relationship between dietary amino acids and hs-CRP, especially in children, remain scarce. Methods This cross-sectional study analyzed data from the Nutrition and China Children and Lactating Women Nutrition and Health Survey (2016–2019), focusing on 3514 children (724 with elevated hs-CRP ≥ 3 mg/L and 2790 with normal levels). Dietary information was gathered via a food frequency questionnaire, and hs-CRP levels were obtained from blood samples. Boruta algorithm and propensity scores were used to select and match dietary factors and sample sizes. Machine learning (ML) algorithms and logistic regression models assessed the link between amino acid intake and elevated hs-CRP risk, adjusting for age, sex, BMI, and lifestyle factors. Results The odds ratios (ORs) for elevated hs-CRP were significant for several amino acids, including Ile, Leu, Lys, Ser, Cys, Tyr, His, Pro, SAA, and AAA, with values ranging from 1.10 to 2.07. The LightGBM algorithm was the most effective in predicting elevated hs-CRP risk, achieving an AUC of 0.927. Tyrosine, methionine, cysteine, and proline were identified as important features by SHAP analysis and logistic regression. The intake of Ser, Cys, Tyr, and Pro showed a linear increase in the risk of elevated hs-CRP, especially in individuals with low protein intake and normal weight (p < 0.1). Conclusions Intake of amino acids like Ser, Cys, Tyr, and Pro significantly impacts hs-CRP levels in children, indicating that regulating these could help prevent inflammation-related diseases. This study supports future dietary and health management strategies. This is first large-scale ML study linking amino acids to pediatric inflammation in China. The main limitations are the cross-section design and the use of self-reported dietary data.