This study aimed to validate a semiquantitative electronic food frequency questionnaire (eFFQ) in estimating the intake of a comprehensive list of nutrients and bioactive compounds among adults from six regions of Argentina using multiple 24 h dietary recall (24HR) as a reference. A total of 163 adults completed two administrations of the eFFQ and four 24HRs. The paired t-test/Wilcoxon signed-rank test, Spearman/Pearson correlations, cross-classification, weighted kappa statistics, and Bland–Altman plots were employed to determine relative validity. To determine reproducibility, intraclass correlations (ICC), cross-classification, and weighted kappa statistics were calculated. For relative validity, crude correlations ranged from 0.15 to 0.57; energy adjustment and de-attenuation slightly improved most of these correlations. In cross-classification analysis, agreements within one quintile adjacent to exact agreement (EA ± 1) ranged from 52.2% to ~74%; extreme misclassifications were < 7%. For reproducibility, the crude ICC ranged from 0.29 to 0.85, showing moderate to good correlations for most nutrients. Cross-classification analysis showed agreement levels for the EA ± 1 quintile of 70.6% to 87.7%. Weighted kappa values ranged from 0.21 to 0.62. The results show that this eFFQ is relatively valid in ranking adults according to their nutrient intake and has an acceptable reproducibility, yet it slightly overestimates the intake of most nutrients.

Background/Objectives: The association between plasma metabolites derived from dietary substrates and inflammatory processes remains underexplored, despite its potential relevance in the prevention of non-communicable diseases. This systematic review aimed to examine the relationship between blood metabolites and the modulation of inflammatory biomarkers. Methods: A total of 25 randomized controlled trials, published between 2019 and 2024, were included from an initial pool of 111 records. These studies investigated the effects of dietary patterns, specific food groups, or nutritional supplements on the human metabolome and their potential links to inflammation. Results: Metabolomic analyses were predominantly performed using mass spectrometry (MS)-based platforms (17 out of 25), with liquid chromatography–mass spectrometry as the most frequently employed method. Both targeted (n = 14) and untargeted (n = 11) approaches were represented, and samples were drawn from plasma, urine, and feces. Across the interventions, 64 metabolites were modulated, including fatty acyls, glycerolipids, benzenoids, and organic acids, reflecting potential changes in pathways related to oxidative stress, lipid and carbohydrate metabolism, and inflammatory signaling. Several studies also assessed classical inflammatory biomarkers such as C-reactive protein (CRP), tumor necrosis factor alpha (TNFα), interleukin-6 (IL-6), and monocyte chemoattractant protein-1 (MCP-1). Interventions involving healthy traditional dietary patterns, improvements in dietary fat quality, or the use of specific probiotic strains were often associated with favorable immunometabolic outcomes. In contrast, some interventions, such as Mohana Choorna, elicited upregulation of immune-related gene expression in adipose tissue without improvements in glucose or lipid metabolism. Conclusions: While metabolomic responses varied across studies, the evidence highlights the value of dietary interventions in modulating systemic metabolism and inflammation. These findings support the integration of metabolomics into clinical nutrition to define more personalized and effective dietary strategies for inflammation-related chronic disease prevention.

We developed a comprehensive Diet and Lifestyle Quality Index (DLQI) and examined its associations with health status and sociodemographic characteristics in Argentinian adults. The DLQI scores range from 0 to 100 points and comprises 49 indicators across 7 dimensions: diet and eating habits, physical activity, rest and sleeping habits, exposure to sunlight and nature, religiosity, abstinence from tobacco and alcohol, and emotional well-being and relationships. Cross-sectional data from 4215 adults were analyzed to explore links with sociodemographic characteristics and chronic disease prevalence. Participants’ mean age was 35.5±14.6 years and 69% were women. The mean DLQI score was 51.5±10.6. Higher scores were associated with older age, being married, lower financial concern, rural residence, and receipt of social welfare. Elevated DLQI and dimension-specific scores were inversely related to self-reported obesity, diabetes, fatty liver, hypertension, kidney disease, and cancer, while lower scores were positively associated with overweight and obesity. Score distribution and odds ratios supported cut-off points for classifying lifestyle quality. Our evaluation indicates the DLQI is a practical tool for assessing diverse diet and lifestyle factors, with scores reflecting health status in line with existing evidence. Further evaluation in other populations is recommended to confirm its clinical and public health applicability.