Journal of Nutrition最新文献

Background: Healthy eating patterns are associated with reduced overall and select cause-specific mortality. Whether dietary quality and mortality risk differ by census-level neighborhood socioeconomic deprivation has not been well studied.

Objective: To investigate whether dietary quality, measured by the Healthy Eating Index (HEI)-2020, is associated with all-cause and 12 cause-specific mortality, and if the association is modified by a neighborhood socioeconomic deprivation index (NSDI).

Methods: Prospective analysis of 544,837 American participants (321,756 men and 223,081 women), aged 50-71 years from the National Institutes of Health (NIH)-AARP Diet and Health Study from baseline (1995/1996 through December 31, 2019). HEI-2020 was calculated using dietary data from self-reported responses to a 124-item baseline food frequency questionnaire. NSDI was estimated based on census variables and developed using principal component analysis. Multivariable-adjusted Cox proportional hazards models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI).

Results: During follow-up to 24.2 years, 282,073 deaths occurred. HEI-2020 quintile (Q5), compared to the Q1 was associated with reduced all-cause mortality (HR: 0.86; 95% CI: 0.85-0.87) and death from 11 causes (HRs: 0.61-0.90), including cancer, cardiovascular, respiratory, stroke, infections, diabetes, kidney, liver, and autoimmune diseases, external, and other causes, but not neurological disease. Stronger reductions were observed among those in less deprived neighborhoods (NSDI Q1) than more deprived (Q5) for respiratory [HEI-2020 HR (95% CI) 0.67 (0.60-0.76) vs. 0.78 (0.71-0.85), P-interaction=.0001] and neurological disease mortality [0.90 (0.81-0.99) vs. 1.06 (0.98-1.16), P-interaction=.002], after correction for multiple comparisons (Bonferroni threshold P<.004) CONCLUSIONS: Dietary quality was protective for all-cause and most cause-specific mortality in middle-aged and older people, but less protective for respiratory and neurological disease among those living in more deprived neighborhoods.

Background: Age-related decline in digestive function increases malnutrition risk. Supplementing meals with digestive enzymes may improve macronutrient digestion and bioavailability in adults reaching older ages.

Objective: To assess postprandial plasma nutrient concentrations after co-ingestion of a mixed meal and a mixture of six enzyme preparations (ENZ), including proteases, lipase, amylase, and glucoamylase.

Design: Thirty middle-aged and older adults (56 ± 11 y; 18 females, 12 males) ingested chicken, peas, potatoes, and butter (435 kcal, 34 g PRO, 51 g CHO, 11 g FAT) with either ENZ or placebo (PLA) in a randomized crossover fashion. Blood samples were collected at baseline and throughout a 0-5 h postprandial period for measurement of plasma amino acid, insulin, glucose, and non-esterified fatty acid (NEFA) concentrations. Clustering of postprandial amino acid responses was conducted in MFuzz, and logistic regression for response groups was conducted in JMP 18.2.0.

Results: Plasma amino acid concentrations were not statistically different between treatments (PLA vs. ENZ) over the postprandial period (all, P > 0.05). Leucine time to maximum concentration (T_max) was significantly faster (P = 0.047) with ENZ (121.2 ± 55.9 min) compared to PLA (141.0 ± 49.2 min). Postprandial plasma glucose concentrations (P = 0.04) and total NEFA (P = 0.001) were higher with ENZ compared to PLA. Three distinct response patterns (clusters) were detected within and across all postprandial amino acid categories. Differences in habitual macronutrient intake and interactions between sex, lean mass, and BMI distinguished participants with an earlier time to maximum postprandial leucine concentration when consuming ENZ vs. PLA from those with stable responses.

Conclusion: Multi-enzyme supplementation improved macronutrient digestion of a mixed meal in middle-aged and older adults. For plasma amino acids, this benefit was most pronounced in adults with lower BMI and higher lean mass, and the effect was sex-dependent. The study was registered at ClinicalTrials.gov (NCT05211440).

Background: B vitamin inadequacies are common in the United States, particularly among African Americans. B vitamins play a key role in 1-carbon metabolism, and poor status may influence cardiovascular health. We investigated associations of dietary intake of vitamins B-6, B-12, and folate, as well as plasma concentrations of vitamin B-12 and folate, with incident coronary artery disease (CAD).

Methods: We analyzed data from the Jackson Heart Study (2000-2016), including 4863 participants in the dietary analytic sample (309 CAD cases) and 4906 in the plasma analytic sample (311 CAD cases). Dietary intake of B vitamins was energy-adjusted using the residual method. Cox proportional hazards regression with multiple imputation was used to estimate hazard ratios (HRs) for incident CAD over a median of 13.8 y of follow-up (60,660 and 61,180 person-years in the dietary and plasma samples, respectively). Linearity of associations was evaluated using restricted cubic splines.

Results: In multivariable-adjusted models (per 1 SD), higher energy-adjusted dietary intake of vitamin B-6 [HR = 1.07; 95% confidence interval (CI): 0.93, 1.25], vitamin B-12 (HR = 0.99; 95% CI: 0.87, 1.12), or folate (HR = 0.97; 95% CI: 0.82, 1.15) was not significantly associated with CAD risk. Similarly, plasma vitamin B-12 (HR = 0.99; 95% CI: 0.84, 1.18) and folate (HR = 0.97; 95% CI: 0.80, 1.17) showed no statistically significant associations. Tests for nonlinearity revealed no evidence of threshold or U-shaped relationships.

Conclusions: In this cohort of African-American adults, neither dietary intake nor plasma concentrations of B vitamins were significantly associated with CAD risk. These findings do not support a strong association between B vitamin status and CAD risk in this cohort.

Background: Growing evidence shows that obesity influences iron status during pregnancy; however, it is unknown whether maternal obesity is associated with epigenetic changes in transferrin receptor 2 (TfR2) and hemojuvelin (HJV).

Objectives: This study aimed to explore the association between adiposity and DNA methylation in TfR2 and HJV in early pregnancy and the mediating effect of inflammation on this association.

Methods: This cross-sectional study used data from a double-blind randomized controlled trial in singleton pregnant women with normal weight (BMI: 18.5-24.9 kg/m²) and obesity (BMI: ≥30.0 kg/m²). Maternal BMI, fat mass, visceral fat, iron/inflammatory markers and DNA methylation of TfR2 and HJV were measured at 12 gestational weeks. Two primer sets were designed [TfR2 zone 1 and 2 (TfR2z1, TfR2z2); HJV zone 1 and 2 (HJVz1, HJVz2)]. An inflammation score was calculated using proinflammatory cytokines.

Results: A total of 65 pregnant females were included, 34 with normal weight, and 31 with obesity. Compared with those of normal-weight women, those with obesity showed: lower percentage of DNA methylation in TfR2z1 cytosine-phosphate-guanine (CpG) sites 5, 6, 8-10 and the average in this zone (average CpG methylation 5.80% compared with 6.92%, P = 0.004); lower percentage of DNA methylation in TfR2z2 CpG sites 5 and 6 (12.5% compared with 14.7%, P = 0.035; 17.8% compared with 20.1%, P = 0.031); higher percentage methylation of DNA in HJVz1 CpG site 3 (HJVz1 CpG 3 45.3% compared with 43.4%, P = 0.010) and HJVz2 CpG site 2 and the average (HJVz2 CpG 2 43.2% compared with 37.9%, P < 0.001, average 65.9% compared with 61.6%, P < 0.001). Adjusting for covariates, TfR2z1 was negatively and HJVz2 positively associated with all adiposity measures (TfR2z1, BMI β = -0.288, P = 0.030; HJVz2 β = 0.459, P < 0.001). Inflammation showed a mediating effect on the association between all adiposity measures and DNA methylation of HJVz1 (P = 0.019).

Conclusions: Maternal adiposity is associated with epigenetic changes in the iron metabolism genes TfR2 and HJV in early pregnancy, part of which are inflammation-mediated changes in HJV.

Background: Gut dysbiosis is associated with malnutrition and inflammation in chronic kidney disease (CKD); however, the causality remains unclear.

Objectives: This study aimed to determine whether fecal microbiota from patients with stage 5 CKD can directly induce nutritional impairment and inflammatory responses in recipient rats.

Methods: Fecal microbiota from patients with stage 5 CKD and healthy controls were transplanted into rats treated with antibiotics. After 2 weeks, we assessed nutritional parameters, inflammatory markers, and microbial composition.

Results: Compared with the healthy-FMT group, rats receiving CKD-derived microbiota exhibited a significant reduction in body weight (466.70 ± 12.60 g vs. 433.90 ± 20.10 g) and serum albumin concentrations (22.87 ± 5.43 g/L vs. 20.36 ± 7.51 g/L). In contrast, serum inflammatory markers were significantly elevated in the CKD-FMT group, including C-reactive protein (12.10 ± 3.10 vs. 15.40 ± 5.00 mg/L) and interleukin-6 (14.30 ± 1.80 vs. 18.80 ± 2.10 pg/L) (all p < 0.01). Microbial analysis revealed enrichment of Enterobacteriaceae and depletion of beneficial genera such as Lactobacillus and Ruminococcaceae.

Conclusions: Our results provide direct evidence that gut microbiota from patients with uremia can impair nutritional status and aggravate systemic inflammation in recipient rats, underscoring a pathogenic role of dysbiosis in CKD complications.

Background: Consuming ≥20% of daily energy from pecans improves blood lipids and reduces dyslipidemia but exceeds dietary recommendations. The benefits of lower doses remain unclear.

Objectives: This study aimed to examine the effects of pecan consumption at doses of 6%, 13%, and 20% of total energy needs on fasting and postprandial blood lipids in adults with excess body weight and/or dyslipidemia, compared with the control (CON). We hypothesized a dose-response relationship, with the 20% group showing the greatest lipid improvements, followed by 13% and 6%, and all would be better than the CON.

Methods: This single-blind, randomized, controlled superiority trial enrolled 102 adults with excess body weight (BMI ≥28 kg/m²) or dyslipidemia. Participants were randomly assigned to 6% (n = 26), 13% (n = 26), or 20% (n = 25) pecan-intake groups, or to a CON (n = 25) that maintained a habitual, nut-free diet. Participants completed preintervention and postintervention visits, which included fasting lipid assessments and a high-fat meal challenge (17% of total energy), followed by 4-h postprandial blood draws.

Results: Change in total cholesterol (TC), low-density lipoprotein cholesterol, apolipoprotein B, non-HDL cholesterol, and TC/HDL cholesterol ratio all decreased from preintervention to postintervention in MID (-13.3 ± 3.4, -12.7 ± 3.3, -9.2 ± 2.3, -13.9 ± 3.2, and -0.3 ± 0.1 mg/dL, respectively; P < 0.05 for all) and HIGH (-12.7 ± 3.6, -11.9 ± 3.4, -7.8 ± 1.9, -13.8 ± 3.6, and -0.3 ± 0.1 mg/dL, respectively; P < 0.05 for all) compared with no change in LOW or CON. Change from baseline postprandial nonesterified fatty acids (NEFAs) decreased from preintervention to postintervention in MID (P = 0.01) compared with no changes in CON, HIGH, or LOW (P > 0.05 for all). Fasting triglycerides (TGs), fasting NEFAs, and postprandial TGs did not differ between groups (P > 0.05 for all).

Conclusions: Pecan intake providing 20% and 13%, but not 6%, of daily energy improved fasting blood lipid profiles compared with the control, with postprandial NEFA reductions observed only at 13%. These findings offer the first evidence that moderate doses of daily pecan consumption confer cardioprotective benefits. This trial was registered at clinicaltrials.gov as NCT05949879 and available from: https://clinicaltrials.gov/study/NCT05949879. The date of initial trial registration was 18 July, 2023.

Computational approaches are transforming nutrition science by integrating data from wearables, digital health platforms, and multiomics technologies to unravel complex diet-health interactions. Traditional statistical models cannot adequately capture the temporal, nonlinear, and individual variability inherent in such data. Computational nutrition, integrating data science, machine learning, and systems modeling, has therefore emerged as a distinct and rapidly developing field. Landmark studies have demonstrated its potential to improve dietary assessment, predict metabolic responses, and design personalized interventions. From an early-career perspective, however, the rise of computational nutrition also exposes structural and educational gaps. Early-career researchers often encounter fragmented training, limited mentorship, and restricted access to interoperable data and computational infrastructure. Empowering early-career researchers through integrated curricula, equitable data access, and recognition of interdisciplinary contributions will be essential for ensuring that computational nutrition evolves into a transparent, reproducible, and inclusive discipline capable of advancing both personalized and population-level nutrition.