Dr Maria Gomez Martin

Background/Objectives: Thus far, no studies have examined the relationship between fruit and vegetable (F and V) intake, urinary metabolite quantities, and weight change. Therefore, the aim of the current study was to explore changes in urinary metabolomic profiles during and after a 10-week weight loss intervention where participants were prescribed a high F and V diet (7 servings daily). Methods: Adults with overweight and obesity (n = 34) received medical nutrition therapy counselling to increase their F and V intakes to national targets (7 servings a day). Data collection included weight, dietary intake, and urine samples at baseline at week 2 and week 10. Urinary metabolite profiles were quantified using 1H NMR spectroscopy. Machine learning statistical approaches were employed to identify novel urine-based metabolite biomarkers associated with high F and V diet patterns at weeks 2 and 10. Metabolic changes appearing in urine in response to diet were quantified using Metabolite Set Enrichment Analysis (MSEA). Results: Energy intake was significantly lower (p = 0.02) at week 10 compared with baseline. Total F and V intake was significantly higher at week 2 and week 10 (p < 0.05). In total, 123 urinary metabolites were quantified. At week 10, 21 metabolites showed significant changes relative to baseline. Of these, 11 metabolites also significantly changed at week 2. These overlapping metabolites were acetic acid, dimethylamine, choline, fumaric acid, glutamic acid, L-tyrosine, histidine, succinic acid, uracil, histamine, and 2-hydroxyglutarate. Ridge Classifier and Linear Discriminant Analysis provided best prediction accuracy values of 0.96 when metabolite level of baseline was compared to week 10. Conclusions: Urinary metabolites quantified represent potential candidate biomarkers of high F and V intake, associated with a reduction in energy intake. Further studies are needed to validate these findings in larger population studies.

Objectives: Although xenobiotics derived from food processing may cause modifications in the composition of the gut microbiota (GM) evidence is scarce. The aim of this study is to evaluate the impact of potential dietary carcinogens as heterocyclic amines (HAs), polycyclic aromatic hydrocarbons (PAHs), nitrates, nitrites, nitroso compounds and acrylamide, in combination to fibers (poly)phenols on the GM composition in a group of materially deprived subjects. Study design: Transversal observational study in a sample of 19 subjects recipients of Red Cross food aid. Dietary information was recorded by means of 3 non-consecutive 24 h recalls. Questions focused on the type of cooking and the extent of cooking and roasting were included. Information on potential carcinogens was mainly obtained from the European Prospective Investigation into Cancer and Nutrition (EPIC) and Computerized Heterocyclic Amines Resource for Research in Epidemiology of Disease (CHARRED) Carcinogen Databases. Microbial composition was determined by 16S ribosomal RNA gene sequencing in fecal samples. Results: Higher levels of Lachnospiraceae and Eggerthellaceae families were found in individuals consuming less than 50 ng/day of 2-amino-3,8 dimethylimidazo (4,5,f) quinoxaline (MeIQx) (considered as lower risk dose for colorectal adenoma) while those consuming more than 40 ng/day of 2-amino-1-methyl-6-phenylimidazo (4,5,b) pyridine (PhIP) (higher risk for colorectal adenoma) showed lower relative abundance of Muribaculaceae and greater presence of Streptococcaceae and Eubacterium coprostanoligenes group. Conclusion: The associations identified between diet and processing by-products on GM in this study could be used as potential targets for the designing of dietary interventions tailored to this collective.

Introduction: Overweight and obesity are recognized mortality risk factors in the general population. The aim of the study was to analyse the phenotypic distribution of body mass index (BMI), and to identify the prevalence of malnutrition and clinical and nutritional factors related to BMI in autonomous institutionalized elders. Material and Methods: Cross-sectional and descriptive study in 104 institutionalized aged people (73% female, mean of age 86.4 [±6.2] years and time on institutionalization 25.7 [±21.7] months). Mini-Nutritional Assessment (MNA), anthropometric measures and laboratory parameters were used for nutritional assessment. Bioimpedance analysis (BIA-101; RJL-System) was used for body composition analysis. The sample was classified into BMI tertiles (Tn): T1= < 26.2kg/m2; T2=26.3-29.7kg/m2; and T3==29.8kg/m2. Results: The phenotypic distribution of BMI was: overweight 51% and, prevalence of obesity 29.8%. Mean of BMI: 28.3 (±4.6) kg/m2. Nutritional risk or malnutrition were 60.6% and 11.5%, respectively in the sample. The tertiles of BMI showed significant differences with: mid-arm muscle circumference, triceps-skinfold thickness, total body water (TBW) (all, p < 0.001). Subjects into T1 had significantly higher nutritional risk or malnutrition compared with T2 and T3 counterparts (p=0.015). Waist-circumference, calf-circumference (at least, p < 0.01), and TBW (p < 0.001) were independent predictors of BMI in the linear regression analysis (R2=0.52). Conclusions: Overweight and obesity measured by BMI is not an exclusion criterion of malnutrition in the geriatric population. Nutritional screening by MNA and the conjoint use of clinical-nutritional parameters are useful for identifying at nutritional risk or malnutrition. Further studies are needed to define the potential nutritional risk factors associated with BMI in autonomous institutionalized aged.