Frontiers in Nutrition最新文献

Objective: Metabolic dysfunction-associated fatty liver disease (MAFLD), a highly prevalent global liver disorder, requires simple and accessible screening approaches. As current diagnostic methods, such as the Controlled Attenuation Parameter (CAP), are limited in their applicability in obese patients and are primarily designed for fibrosis assessment. This study aim to investigate the associations of the serum melanin-concentrating hormone (MCH) and triglyceride-glucose (TyG) indices with MAFLD and to explore the risk factors and disease probability of MAFLD by developing machine learning models.

Methods: In this cross-sectional study of 212 MAFLD patients and 107 healthy controls, and feature selection were identified through the least absolute shrinkage and selection operator (LASSO) regression analysis and Variance Inflation Factor (VIF). Three predictive models-Logistic Regression, Random Forest, Support Vector Machinemodel (SVM)-were constructed using the training set and evaluated in an independent test set. Construction of nomogram using independent risk factors screened by machine learning. Multivariate logistic regression analysis was used to explore further assess independent risk factors. Mediation analysis was conducted to explore potential pathways.

Results: Logistic regression model was found to outperform other classifier models in testing data [area under the curve (AUC) of 92.6, 95% CI: 0.865-0.987] and achieve the lowest Brier Score as well. Decision curve analysis suggested potential clinical utility. Logistic regression analysis indicated that MCH (OR, 2.193; 95% CI, 1.242-3.873; P = 0.007), TyG index (OR, 1.002; 95% CI, 1.001-1.003; P < 0.001), are independent risk factors for MAFLD. Subgroup analysis of the association between MCH and MAFLD stratified by sex, age, and body mass index (BMI) showed no significant effect modification after adjustment. Mediation analysis indicated that the TyG index accounted for a modest proportion of the association between MCH and MAFLD (mediation proportion: 10.89%).

Conclusion: Serum MCH and the TyG index were independently associated with MAFLD. A machine learning-based screening model was developed and internally validated, showing promising performance for identifying individuals at higher risk. However, external validation in larger multicenter prospective cohorts is warranted before broader clinical application.

Undocumented Mexican migrants in the United States navigate everyday life under conditions shaped not only by economic hardship and legal exclusion, but also by the persistent anticipation of surveillance and immigration enforcement. While existing research often frames dietary change in migration as a result of cultural loss or individual choice, less attention has been paid to how legal precarity and anticipatory fear actively govern migrants' food practices, health, and mobility. This study examines how undocumented status becomes embodied through everyday food decisions, contributing to broader processes of health vulnerability and structural inequality. This article draws on ethnographic fieldwork conducted among undocumented Mexican migrants in Los Angeles, California. Data were collected through in-depth semi-structured interviews, participant observation recorded in fieldnotes, and photographic diaries documenting everyday food environments and practices. This qualitative approach enabled an examination of how migrants experience, interpret, and navigate food, health, and fear within their daily routines, capturing both material constraints and subjective meanings. The findings reveal that migrants' dietary practices are shaped not only by limited income and restricted access to nutritious and culturally meaningful foods, but also by what we conceptualize as the anticipatory governance of fear. Even in the absence of direct encounters with immigration authorities, migrants modify their routines to minimize visibility, avoiding certain public spaces, shops, and travel routes. These adaptations often reduce access to healthy foods, contributing to weight gain, fatigue, and chronic health conditions. At the same time, migrants actively preserve traditional foodways, sustain family care through cooking, and create spaces of resilience grounded in memory, cultural continuity, and community ties. These findings demonstrate how undocumented status operates not only as a legal category but as an embodied condition that shapes health outcomes through everyday practices of adaptation, restraint, and survival. By highlighting the anticipatory and lived dimensions of food insecurity, this study challenges individualistic and culturally reductionist explanations of dietary change. Instead, it situates migrant health within broader structures of legal precarity, labor exploitation, and surveillance. This human-centered and ethnographically grounded analysis contributes to critical scholarship on migration, nutrition, and health by revealing how governance, fear, and inequality become inscribed in bodies, diets, and everyday life.

Background: Metabolic Syndrome (MetS), defined by central obesity and disturbances in glucose and lipid metabolism, has not been extensively validated in large national cohorts concerning its association with fatty liver disease (FLD), gastrointestinal tumors (GIT), and prognostic outcomes.

Methods: A total of 24,434 adults from the 2003-2018 cycles of The National Health and Nutrition Examination Survey (NHANES) were included as the development cohort, with a validation cohort of 365 adults to verify key associations. MetS was diagnosed per NCEP-ATP III criteria across both cohorts. Weighted multivariate regression models assessed associations between MetS and FLD/GIT incidence, and Cox proportional hazards models evaluated survival risks. Three hierarchical models were constructed: Model 1 (unadjusted), Model 2 (adjusted for demographic confounders), and Model 3 (further adjusted for laboratory parameters).

Results: In the development cohort, MetS patients exhibited a higher FLD prevalence (16.2% vs. 4.6%) and GIT incidence (1.25% vs. 0.57%). After full adjustment in Model 3, MetS remained a strong independent risk factor for FLD (OR = 3.889, 95% CI: 3.529-4.307) and GIT (OR = 2.456, 95% CI: 1.832-3.292). These associations were corroborated in the validation cohort, with adjusted ORs of 4.760 for FLD and 4.395 for GIT. Survival analysis indicated that MetS significantly reduced overall survival in the development cohort, with HRs for all-cause, cancer-specific, and cardiovascular mortality of 2.146, 1.941, and 2.572, respectively. Furthermore, the mortality risk was further elevated in FLD patients with MetS (all-cause mortality HR = 1.823). In the validation cohort, cardiovascular mortality risk was significant (HR = 3.902), while other survival outcomes did not reach statistical significance due to the small sample size. Sensitivity analysis using IDF criteria confirmed the robustness of these findings.

Conclusion: This study confirms that MetS is strongly associated with FLD risk and GIT incidence, supporting early metabolic intervention to interrupt the progression of liver disease and tumors.

Background: Endometriosis is a chronic inflammatory gynecologic disorder associated with pelvic pain and impaired health-related quality of life (HRQoL). Omega-3 polyunsaturated fatty acids (PUFAs) have anti-inflammatory potential and may confer adjunctive benefit when combined with conventional therapy. This study evaluated the association between adjunctive omega-3 PUFA intake and pain, inflammatory biomarkers, and HRQoL in endometriosis.

Methods: This retrospective, time-period-based cohort study included patients with confirmed endometriosis treated at a single center between January 2021 and December 2024. Conventional therapy during 2021-2022 served as the control period, whereas conventional therapy plus omega-3 PUFA supplementation during 2023-2024 constituted the exposure period. Outcomes included pain assessed by the visual analog scale (VAS), inflammatory biomarkers [interleukin-6 (IL-6), tumor necrosis factor alpha (TNF-α), and C-reactive protein (CRP)], and HRQoL measured using the 36-Item Short Form Health Survey (SF-36), including the Physical Component Summary (PCS) and Mental Component Summary (MCS). Multivariable logistic regression and inverse probability of treatment weighting (IPTW) were applied, with pre-specified subgroup and sensitivity analyses.

Results: Among 302 screened patients, 289 were analyzed (control n = 138; omega-3 n = 151), with comparable baseline characteristics. Median exposure to eicosapentaenoic acid (EPA) plus docosahexaenoic acid (DHA) was 900 mg/day (interquartile range [IQR] 600-1,200) for 12 weeks (IQR 10-12). Compared with controls, the omega-3 group experienced greater reductions in overall pain (VAS Δ 3.0 ± 1.0 vs. 1.5 ± 0.9; p < 0.001), larger decreases in IL-6, TNF-α, and CRP (all p < 0.001), and greater improvements in SF-36 PCS (Δ 12.1 ± 5.2 vs. 5.3 ± 4.8) and MCS (Δ 10.3 ± 5.0 vs. 4.8 ± 4.6; both p < 0.001). Omega-3 PUFA intake was independently associated with clinically meaningful improvement, including VAS ≥2-point reduction (odds ratio [OR] 3.06, 95% confidence interval [CI] 1.85-5.06), PCS ≥5-point increase (OR 2.74, 95% CI 1.67-4.50), and MCS ≥5-point increase (OR 2.41, 95% CI 1.50-3.88), with consistent findings across subgroup, sensitivity, and IPTW analyses.

Conclusions: Adjunctive omega-3 PUFA intake was associated with improved pain, reduced inflammatory biomarkers, and better HRQoL in endometriosis, warranting confirmation in future prospective randomized studies.

Background: Malnutrition and sodium water retention are some of the most common complications of chronic heart failure (CHF). To date, several parameters or risk stratification tools have been established to predict one's volume or nutritional status. Unfortunately, there is no biomarker that may reflect both conditions, thus, in this study, we established a novel biomarker known as total body water (TBW) to lean body mass ratio (LBM) ratio (TLR). Accordingly, we also assessed the prognostic value of TLR in CHF patients.

Methods: A total of 401 consecutive patients with CHF from August 2019 to October 2021 were prospectively enrolled. TBW and LBM were obtained by InBody S10. The primary endpoint was long-term all-cause and cardiovascular mortality. The cut-off and prognostic value of TLR was determined by receiver operating characteristic curves and Cox regression analysis. Patients were then divided into two groups according to the cut-off value of TLR.

Results: During a median follow-up of 1,200 days, the high-TLR group (TLR ≥ 0.783) was presented with a higher all-cause mortality (41.27% vs. 18.40%, p < 0.001) and cardiovascular mortality (28.57% vs. 13.68%, p < 0.001) compared to the low-TLR group (TLR < 0.783). Furthermore, patients in the high-TLR group tended to be older, presented with atrial fibrillation, had higher NYHA class, had a history of chronic kidney disease, had a higher level of N-terminal prohormone of brain natriuretic peptide, worse nutritional status, and a lower level of albumin (all p < 0.05). The Kaplan-Meier curves of the two group patients revealed that the cumulative all-cause and cardiovascular mortality were lower in patients with lower TLR (all log-rank p < 0.001). In the multivariate Cox proportional hazard analysis, TLR ≥ 0.783 was an independent predictor for both all-cause mortality (HR = 2.108, 95%CI 1.400, 3.173, p < 0.001) and cardiovascular mortality (HR = 2.044, 95%CI 1.264, 3.305, p = 0.004).

Conclusion: The TLR may serve as a novel composite biomarker that reflects both volume and nutritional status in CHF patients and is associated with long-term prognosis. Its prognostic performance appears comparable to several established biomarkers, though further validation is warranted.

Background: The neutrophil percentage-to-albumin ratio (NPAR) is a novel inflammatory marker. This study explores its association with cognitive impairment (CI) in peritoneal dialysis (PD) patients.

Methods: In this cross-sectional study, 152 PD patients were categorized into CI (Montreal Cognitive Assessment (MoCA) score <26) or non-CI (MoCA ≥26) groups.

Results: CI was present in 66.45% of PD patients. Patients in the CI group had older age (63.01 ± 10.88 vs. 49.75 ± 12.74 years, p < 0.001), a high proportion of female individuals (43.56% vs. 23.53%, p = 0.016), and a higher NPAR (1.94 ± 0.24 vs. 1.80 ± 0.24, p = 0.001). In addition, patients in the CI group had lower levels of education (8.24 ± 2.97 vs. 11.55 ± 3.45 years, p < 0.001), serum albumin (36.29 ± 3.56 vs. 37.75 ± 2.60 g/L, p = 0.010), potassium (4.30 ± 0.71 vs. 4.51 ± 0.53 mmol/L, p = 0.039), creatinine (865.79 ± 274.38 vs. 1099.92 ± 293.86 umol/L, p < 0.001), and phosphorus (1.43 ± 0.41 vs. 1.68 ± 0.44 mmol/L, p = 0.001). Multivariate logistic regression analysis revealed that NPAR, age, serum phosphorus levels, and education were significant independent determinants of CI. The area under the curve (AUC) for NPAR in predicting CI was 0.657, with a sensitivity of 0.496 and a specificity of 0.745 (p = 0.002). When age, NPAR, blood phosphorus levels, and education were combined, the AUC increased to 0.861, with a sensitivity of 0.822 and specificity of 0.745 (p < 0.001).

Conclusion: CI in PD patients was found to be independently associated with elevated NPAR. The NPAR may serve as a potential biological indicator for identifying prevalent cases of CI, providing a basis for further exploration of early intervention strategies for CI.

Objective: To mitigate current research limitations, this cross-sectional study aimed to systematically evaluate the associations between dietary amino acids and overweight/obesity and to identify critical biomarkers among Chinese children and adolescents. This was achieved by integrating multiple machine learning algorithms with traditional statistical models.

Methods: This study utilized data from the 2016-2019 China Children and Lactating Women Nutrition and Health Surveillance, a nationally representative survey. Participants included children and adolescents aged 6-18 years. Dietary intake was assessed using a validated food frequency questionnaire, and amino acid intakes were calculated. Four machine learning algorithms were applied to build prediction models. Model performance was evaluated via the area under the receiver operating characteristic curve (AUC). The SHapley Additive exPlanations (SHAP) method was used to interpret the optimal model and identify important features. Multivariable logistic regression models were additionally used to examine the relationship between amino acids and overweight/obesity risk.

Results: A total of 8,664 participants were included. The LightGBM model showed the best predictive effect (AUC = 0.805). Both SHAP analysis and logistic regression results consistently identified leucine (OR 1.13; 95% CI 1.01 ~ 1.27), threonine (OR 1.41; 95% CI 1.22 ~ 1.63), methionine (OR 1.30; 95% CI 1.07 ~ 1.57), and cysteine (OR 0.71; 95% CI 0.59 ~ 0.84) as key amino acids associated with overweight/obesity risk. After multivariable adjustment, the intake of leucine, threonine, and methionine was positively related to the risk of overweight/obesity, whereas cysteine intake was inversely related to the risk. Restricted cubic spline analyses suggested linear relationships for these associations.

Conclusion: Higher dietary intakes of leucine, threonine, and methionine are potential risk factors, while cysteine is a potential protective factor against overweight/obesity in Chinese children and adolescents.

[This corrects the article DOI: 10.3389/fnut.2026.1774865.].

Introduction: Sedentary behavior is associated with gut microbiota dysbiosis and low-grade systemic inflammation, both of which contribute to increased cardiometabolic risk. However, the combined effects of functional dietary fiber supplementation and home-based exercise on these outcomes remain unclear. This study aimed to investigate whether a combined intervention could improve gut microbiota diversity and reduce systemic inflammation in urban sedentary adults.

Methods: In this 24-week parallel-group randomized controlled trial, 140 sedentary adults were randomly assigned to an intervention group (functional dietary fiber supplementation providing 15-20 g/day of resistant starch, inulin, and beta-glucan combined with home-based moderate-intensity exercise, five sessions per week) or a control group maintaining their usual lifestyle. Gut microbiota diversity was assessed using 16S rRNA gene sequencing, and inflammatory markers (hs-CRP, IL-6, TNF-α, IL-10) were measured using immunoassays.

Results: The intervention significantly increased gut microbiota alpha diversity, with Shannon index rising from 3.82 ± 0.48 to 4.31 ± 0.49 (p < 0.001), while minimal changes were observed in controls. Significant reductions were observed in hs-CRP (-42.1%), IL-6 (-35.4%), and TNF-α (-28.6%), alongside an increase in IL-10 (+31.8%) (all p < 0.001). Butyrate levels increased by 50%, and changes in Shannon diversity were negatively correlated with reductions in hs-CRP (r = -0.52, p < 0.001).

Conclusion: Combined functional dietary fiber supplementation and home-based exercise significantly improved gut microbiota diversity and reduced low-grade inflammation in sedentary adults. These findings support integrated lifestyle interventions as effective strategies for reducing cardiometabolic risk.

Sleep is vital to human health, and poor sleep health has been associated with numerous chronic conditions, including cardiovascular disease, obesity, depression, and type 2 diabetes. Recently, an emerging area of research has focused on the relationship between dietary polyphenols and sleep health. This connection may be mediated by the gut microbiota and polyphenol-derived microbial metabolites, which also exert biologically relevant effects. One such metabolite, urolithin A, has been shown to improve mitochondrial function, muscle strength, and inflammation in humans. However, its potential effect on sleep remains unexplored. Thus, this mini review aimed to summarize the current evidence on the effect of urolithin A on sleep-relevant pathways and to explore the possible mechanisms underlying this effect. Although no study directly investigating the effect of urolithin A on sleep outcomes was identified, our search found four preclinical studies that included outcomes relevant to sleep. These studies provide mechanistic plausibility for the relationship between urolithin A and sleep health through direct and indirect mechanisms such as modulation of the central clock, protection against neuroinflammation caused by sleep deprivation, and modulation of the gut microbiota. However, to elucidate the direct effect of urolithin A on sleep, studies with specific sleep measures such as electroencephalogram, actigraphy, and/or polysomnography are still required. Taken together, this represents a novel direction in polyphenol-derived microbial metabolite research with many opportunities for future research.