American Journal of Clinical Nutrition最新文献

Background: Ultraprocessed foods (UPFs), including plant-based meat substitutes, are marketed as healthy alternatives to whole foods. However, little evidence exists regarding their effects on human milk composition, particularly how dietary UPFs might alter human milk fatty acids.

Objectives: We tested whether replacing beef with an ultraprocessed plant-based beef substitute alters human milk fatty acid profiles.

Methods: In a double-blind, randomized, crossover feeding trial, 17 lactating females whose infants were fed only their milk completed 2 6-d diet phases separated by 6-d washout periods. Participants consumed 339 g (12 oz) daily of beef or plant-based substitute, depending on the diet phase. All meals were prepared in a metabolic kitchen and fully provided. Dietary compliance exceeded 95%. The final human milk samples collected on day 6 of each condition were analyzed for 27 fatty acids. Mean differences in fatty acid percentages were assessed with independent and paired t-tests for intervention food and human milk samples, respectively. Maternal weight, satiety, glucose response, and infant intake were also measured.

Results: Human milk collected during the substitute diet contained higher levels of tropical oil-derived medium-chain saturated fatty acids, such as lauric acid (12:0: 9.32 ± 1.8 compared with 4.47 ± 1.82, P < 0.001) and lower levels of long-chain polyunsaturated fatty acids (LCPUFAs), including arachidonic acid (20:4n-6: 0.35 ± 0.06 compared with 0.41 ± 0.06, P < 0.001) compared with milk form the beef diet. No significant differences were observed in maternal weight, satiety, glucose response, or infant intake.

Conclusions: Replacing beef with plant-based UPF changed human milk fatty acid composition, reducing LCPUFAs and increasing tropical oil-derived saturated fats. These shifts may have implications for infant neurodevelopment and immune function, highlighting the need to distinguish between nutrient-equivalent and biologically equivalent foods in postpartum dietary guidance. This trial was registered at www.

Clinicaltrials: gov as NCT06082921.

Background: The Food and Drug Administration (FDA) recently updated criteria for the "healthy" claim displayed on foods and beverages in the United States. However, it is unknown how updated criteria compare with existing methods for evaluating the healthfulness of foods and beverages.

Objectives: To evaluate correlation between "healthy" criteria and 3 nutrient profiling models used to evaluate food and beverage healthfulness, and with Nova food processing classification. Exploratory analyses compare the nutritional profile of "healthy" items and items not meeting "healthy" criteria.

Methods: In this cross-sectional analysis, we identified individual "healthy" items reported in the 2017-2018 National Health and Nutrition Examination Survey. We used descriptive statistics to characterize "healthy" items across food categories, nutrient profiling models (Food Compass 2.0, Nutri-Score, and Health Star Rating), and Nova. We used point-biserial correlation to evaluate correlation between FDA criteria and nutrient profiling models, and rank point-biserial correlation to evaluate correlation with Nova. We used t-tests to compare nutrient content of "healthy" items and items not meeting "healthy" criteria across food categories and Nova categories.

Results: Overall, 14.9% of items qualified for the "healthy" claim. Although the majority of fruits (60.9%), vegetables (59.6%), and nuts and seeds (68.8%) qualified, few meat, poultry, and eggs (3.0%), grains (4.8%), or savory snacks and desserts (1.3%) met criteria. Criteria were moderately correlated with Food Compass 2.0 (r = 0.56), Nutri-Score (r = 0.46), Health Star Rating (r = 0.41), and Nova (0.49). "Healthy" items were lower in saturated fat and sodium and higher in fiber and vitamin C across nearly all food categories and Nova categories.

Conclusions: Findings suggest few foods met "healthy" criteria. Moderate correlations between "healthy" criteria, Nova, and validated nutrient profiling models provide evidence of convergent validity, yet underscore the challenge of classifying foods by healthfulness, and highlight uncertainty about whether discrepancies reflect real differences in model performance and food healthfulness.

Background: Inverse associations of vegetarian diet with morbidity and mortality have been observed; however, the role of vegetarian diet on exceptional longevity remains unrevealed.

Objectives: This study aims to examine the association between a vegetarian diet and likelihood of becoming a centenarian in adults aged ≥80 y.

Methods: This prospective nested case-control study included 5203 participants aged 80+ y from the Chinese Longitudinal Healthy Longevity Survey, a nationally representative cohort initiated in 1998. Participants were classified as omnivores and vegetarians, and further into vegetarian subgroups (pesco-vegetarians, ovo-lacto-vegetarians, and vegans) based on consumption of animal-derived foods. The primary outcome was living to 100 y old by the end of follow-up (2018). Multivariable unconditional logistic regression models were used to evaluate the association analysis.

Results: The study identified 1459 centenarians and matched them with 3744 noncentenarians (who had deceased before reaching 100 y). Relative to omnivores, vegetarians had a lower likelihood of becoming centenarians [odds ratio (OR): 0.81, 95% confidence interval (CI): 0.69, 0.96], and similar patterns were observed for vegans (OR: 0.71, 95% CI: 0.54, 0.98), but not for pesco-vegetarians (OR: 0.84, 95% CI: 0.64, 1.09) and ovo-lacto-vegetarians (OR: 0.86, 95% CI: 0.67, 1.09). The significant association was seen in individuals with BMI <18.5 kg/m² (OR: 0.72, 95% CI: 0.57, 0.91), but not for those with BMI ≥18.5 kg/m² (OR: 0.92, 95% CI: 0.73, 1.17) (P-interaction = 0.08).

Conclusions: Targeting individuals of advanced age (80+ y) in China, we found that individuals following a vegetarian diet had a lower likelihood of becoming centenarians relative to omnivores, underscoring the importance of a balanced, high-quality diet with animal- and plant-derived food composition for exceptional longevity, especially in the underweight oldest-old.

Background: Bone mineral density (BMD) explains fractures incompletely; studies relating lifestyle to bone quality are lacking.

Objectives: This study aims to examine associations of diet quality with bone measures [bone material strength index (BMSi), trabecular bone score (TBS), BMD], evaluate moderation by inflammation, identify gut microbiome features linked to diet quality, and quantify diet-microbiome-bone relationships.

Methods: This cross-sectional study included participants from the Boston Puerto Rican Osteoporosis Study. Diet was assessed with a culturally tailored food frequency questionnairew, and diet quality with the Dietary Approaches to Stop Hypertension (DASH) score. BMSi was measured using microindentation; BMD by dual-energy X-ray absorptiometry (DXA); TBS derived from DXA. Inflammation was assessed with a biomarker score (BMS) and tested as a moderator of diet-bone associations via interaction terms in linear regression. Gut microbiome composition (shotgun metagenomics) was analyzed with microbiome multivariate association with linear models regression to assess diet associations. A machine learning algorithm determined dietary, microbial, and bone-related predictors of bone health; sample sizes varied by outcome: BMSi (n = 86); TBS (n = 204); BMD femoral neck (n = 220), total hip (n = 221), lumbar spine (n = 207).

Results: DASH score was not associated with BMSi [β = -0.10; 95% confidence interval (CI): -0.46, 0.27; P = 0.60], TBS (β = 0.002; 95% CI: -0.002, 0.005, P = 0.36), BMD at the femoral neck (β = 0.002; 95% CI: -0.002, 0.005; P = 0.30), or lumbar spine (β = 0.002; 95% CI: -0.003, 0.006, P = 0.52) but was at total hip (β = 0.004; 95% CI: 0.003, 0.008; P = 0.03). The association was not moderated by inflammation (β = -0.0001, P = 0.89). Lachnospira eligens was 1 of 4 taxa positively associated with DASH score and BMD. No microbial pathways were associated with the DASH score.

Conclusions: DASH score was associated with hip BMD, but not with BMSi or TBS. Select diet-related gut microbes and an inflammation score were associated with BMD. Future studies should examine dietary inflammation in relation to bone quality.

Background: Proteomics has facilitated the identification of key pathways linking diet to diseases. However, a key challenge in high-throughput proteomics is identifying functional units of proteins that act together in biological processes.

Objectives: We aimed to identify protein networks associated with diet quality and cardiovascular disease (CVD) risk factors.

Methods: We analyzed 740 Framingham Heart Study participants (mean age 52 y; 46% female). Weighted gene coexpression network analysis was applied to construct protein networks (i.e. modules) using 2651 plasma proteins. We assessed cross-sectional associations of modules with the Dietary Approach to Stop Hypertension (DASH) diet score, and body mass index (BMI). We examined the prospective association of the diet- and BMI-associated modules with incident fatty liver and type 2 diabetes (T2D). Furthermore, we conducted Mendelian randomization (MR) analysis to investigate protein-protein relationships.

Results: There were 39 protein modules identified, and each was assigned an arbitrary color name. Four protein modules were associated with both diet and BMI. For example, a 10-unit higher DASH score was associated with 0.27 SD lower darkgrey module eigenvalues (95% confidence interval [CI]; 0.12, 0.42; P = 0.0008), and per 0.27 SD lower darkgrey module was associated with 1.17 kg/m² lower BMI (95% CI: 1.07, 1.27; P = 2.4e-88). Furthermore, we found that the darkgrey module was associated with both incident fatty liver and T2D, and the association with incident fatty liver remained after BMI adjustment (odds ratio 3.22 per SD increase), (95% CI: 1.68, 6.19; P = 0.0005). The darkgrey module comprises 39 proteins, including 8 proteins such as fatty acid-binding protein, adipocyte 4, leptin, and interleukin-1 receptor antagonist protein that may drive with the association with diet and BMI. MR analysis revealed 3 putative causal protein pairs from the darkgrey module.

Conclusions: Our findings highlight proteomic networks potentially linking diet and CVD risk and demonstrate the usefulness of proteomics for identifying high-risk individuals for future interventions.

Background: Diets have become increasingly monotonous and high in ultraprocessed foods (UPFs), contributing to poor health outcomes and environmental degradation. Although sustainable diets, food biodiversity, and food processing levels have each been linked to nutritional and environmental outcomes, their combined impact has not been assessed.

Objectives: This study aims to examine whether food biodiversity, intakes of UPFs, and adherence to the EAT-Lancet diet can simultaneously optimize nutrient adequacy while reducing environmental impacts.

Methods: Using data from 368,733 adults in the European Prospective Investigation into Cancer and Nutrition, we assessed associations and interactions between dietary species richness (DSR) (disaggregated into DSR_Plant and DSR_Animal), food processing levels (Nova categories; % g/d), and adherence to EAT-Lancet recommendations [healthy reference diet (HRD) score; 0-140 points] with the Probability of Adequate Nutrient Intake Diet (PANDiet) score, dietary greenhouse gas emissions (GHGe; kg CO₂-eq/d), and land use (m²/d). Regression models subsequently informed multiobjective optimization to identify optimal dietary patterns balancing nutritional and environmental outcomes.

Results: Compared with observed diets, optimal diets showed a mean HRD score increase of 13.91 (95% confidence interval: 13.89, 13.93) points; DSR_Plant increased by mean of 1.36 (1.35, 1.37) species, and a mean substitution of 12.44 (12.40, 12.49) percentage points of UPFs with unprocessed or minimally processed foods. Correspondingly, the mean PANDiet score increased by 4.12 (4.10, 4.14) percentage points, whereas GHGe and land use reduced by 1.07 (1.05, 1.09) kg CO₂-eq/d and 1.43 (1.41, 1.45) m²/d, respectively.

Conclusions: Diets that adhere to the EAT-Lancet diet, are more biodiverse, and prioritize unprocessed and minimally processed foods over UPFs, have the potential to synergistically enhance nutrient adequacy while minimizing environmental impacts. These findings suggest that moderate improvements across multiple dietary dimensions simultaneously can achieve meaningful gains in both nutritional adequacy and environmental sustainability.

Background: Weight retention postpartum can increase long-term risk of maternal overweight and obesity. In theory, breastfeeding may facilitate postpartum weight loss, but its association with maternal weight change, especially long-term, remains uncertain.

Objectives: The aim of this study was to investigate the association between breastfeeding duration and maternal weight change through adulthood emphasizing possible variations based on early adulthood BMI and the time of childbirth during the 1940s through the 1990s.

Methods: Women (n = 172,472) in the Norwegian Women and Health Study, born 1927 to 1965, completed ≤3 questionnaires (Q1-Q3) between 1991 and 2014. A linear mixed model was applied to assess the association between BMI change from age 18 y in relation to mean breastfeeding duration per child (0, >0 to <3, 3 to <6, 6 to <9, 9 to <12, 12 to <15, ≥15 mo), including a 3-way interaction with categories of BMI at age 18 y and time period of first birth.

Results: We found a significant interaction between breastfeeding duration per child, BMI at age 18 y, and year of first birth in relation to BMI change from age 18 y. Longer breastfeeding duration per child was associated with a lower increase in BMI among both mothers who either had overweight or obesity or had normal weight at age 18 y (P-trend < 0.001), irrespective of time of first birth. Among mothers with overweight or obesity at age 18 y who had their first child ≥1980, breastfeeding for ≥3 mo per child was significantly associated with lower increase in BMI from age 18 y, ranging from -1.26 kg/m² [95% confidence interval (CI): -2.19, -0.32] to -2.11 kg/m² (95% CI: -2.93, -1.30), compared with >0 to <3 mo.

Conclusions: We found a significant association between longer breastfeeding duration per child and lower maternal weight gain through adulthood, which was particularly pronounced among mothers with overweight or obesity at age 18 y and among mothers who had their first child ≥1980.