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Background: Accurate measurement of dietary intake is vital for providing nutrition interventions and understanding the complex role of diet in health. Traditional dietary assessment methods are very resource intensive and burdensome to participants. Technology may help mitigate these limitations and improve dietary data capture.Objective: Our objective was to evaluate the accuracy of a novel mobile application (PIQNIQ) in capturing dietary intake by self-report. Our secondary objective was to assess whether food capture using PIQNIQ was comparable with an interviewer-assisted 24-h recall (24HR).Methods: This study was a single-center randomized clinical trial enrolling 132 adults aged 18 to 65 y from the general population. Under a provided-food protocol with 3 menus designed to include a variety of foods, participants were randomly assigned to 1 of 3 food capture methods: simultaneous entry using PIQNIQ, photo-assisted recall using PIQNIQ, and 24HR. Primary outcomes were energy and nutrient content (calories, total fat, carbohydrates, protein, added sugars, calcium, dietary fiber, folate, iron, magnesium, potassium, saturated fat, sodium, and vitamins A, C, D, and E) captured by the 3 methods.Results: The majority of nutrients reported were within 30% of consumed intake in all 3 food capture methods (n = 129 completers). Reported intake was highly (>30%) overestimated for added sugars in both PIQNIQ groups and underestimated for calcium in the photo-assisted recall group only (P < 0.001 for all). However, in general, both PIQNIQ methods had similar levels of accuracy and were comparable to the 24HR except in their overestimation (>30%) of added sugars and total fat (P < 0.001 for both).Conclusions: Our results suggest that intuitive, technology-based methods of dietary data capture are well suited to modern users and, with proper execution, can provide data that are comparable to data obtained with traditional methods. This trial was registered at clinicaltrials.gov as NCT03578458. [ABSTRACT FROM AUTHOR]

Background: Better methods are needed for determining vitamin A absorption efficiency in humans to support development of dietary recommendations and to improve the accuracy of predictions of vitamin A status.Objectives: We developed and evaluated a method for estimating vitamin A absorption efficiency based on compartmental modeling of theoretical data on postprandial plasma retinyl ester (RE) kinetics.Methods: We generated data on plasma RE and retinol kinetics (30 min to 8 h or 56 d, respectively) after oral administration of labeled vitamin A for 12 theoretical adults with a range of values assigned for vitamin A absorption (55-90%); we modeled all data to obtain best-fit values for absorption and other parameters using Simulation, Analysis, and Modeling software. We then modeled RE data only (16 or 10 samples), with or without added random error, and compared assigned to predicted absorption values. We also compared assigned values to areas under RE response curves (RE AUCs).Results: We confirmed that a unique value for vitamin A absorption cannot be identified by modeling plasma retinol tracer kinetics. However, when RE data were modeled, predicted vitamin A absorptions were within 1% of assigned values using data without error and within 12% when 5% error was included. When the sample number was reduced, predictions were still within 13% for 10 of the 12 subjects and within 23% overall. Assigned values for absorption were not correlated with RE AUC (P = 0.21).Conclusions: We describe a feasible and accurate method for determining vitamin A absorption efficiency that is based on compartmental modeling of plasma RE kinetic data collected for 8 h after a test meal. This approach can be used in a clinical setting after fasting subjects consume a fat-containing breakfast meal with a known amount of vitamin A or a stable isotope label. [ABSTRACT FROM AUTHOR]

Background: Height is an indicator of nutritional status; linear growth faltering has recognized consequences for cognitive, emotional, and chronic disease risk. Although height is routinely studied in developing countries, less attention is given to height in the United States.Objective: The objective of this study was to identify longitudinal associations between childhood and adolescent beverage intakes, nutrient adequacy, or energy intake and height in a birth cohort.Methods: Data for participants through ages 2-17 y (n = 717; 353 males, 364 females) recruited at birth for the longitudinal Iowa Fluoride Study (IFS) were used in the current cohort analyses. Beverage intakes (n = 708) were collected by beverage-frequency questionnaires at 3- to 6-mo intervals, whereas nutrient data (n = 652) were obtained from 3-d food diaries completed at 3- to 6-mo intervals through age 8.5 y and from Block Kids' food-frequency questionnaires at 2-y intervals after age 8.5 y. Nutrient adequacy ratios were calculated with the use of age- and sex-specific Estimated Average Requirements. Height was measured at clinic visits when the participants were approximately ages 5, 9, 11, 13, 15, and 17 y. Linear mixed models were used to identify longitudinal associations between dietary variables and height. A baseline model that adjusted for changing growth patterns during adolescence was established. Dietary and potential confounding variables were added to this baseline model.Results: Milk intake adjusted for mean adequacy ratio, energy intake, and baseline socioeconomic status was associated with height; for each additional 8 ounces (236 mL) of milk consumed per day throughout childhood and adolescence, height increased, on average, by 0.39 cm (95% CI: 0.18, 0.60 cm; P < 0.001).Conclusions: IFS participants' height increased by 0.39 cm for each additional 8 ounces (236 mL) of milk consumed throughout childhood and adolescence. The clinical implications of the mild linear growth faltering observed in healthy youth are unknown. This trial was registered at www.clinicaltrials.gov as 199112665. [ABSTRACT FROM AUTHOR]

Background: A meal rich in saturated fatty acids induces a postprandial metabolic challenge. The type of dietary protein may modulate postprandial metabolism.Objective: We studied the effect of dietary protein type on postprandial changes in the metabolome after a high-fat meal.Methods: In a 3-period, crossover, postprandial study, 10 healthy overweight men with an elevated waist circumference (>94 cm) ingested high-fat meals made up of cream fat (70% of energy), sucrose (15% energy), and protein (15% energy) from either casein (CAS), whey protein (WHE), or α-lactalbumin-enriched whey protein (LAC). Urine collected immediately before and 2, 4, and 6 h after the meal was analyzed for metabolomics, a secondary outcome of the clinical study. We used mixed-effect models, partial least-square regression, and pathway enrichment analysis.Results: At 4 and 6 h after the meal, the postprandial metabolome was found to be fully discriminated according to protein type. We identified 17 metabolites that significantly explained the effect of protein type on postprandial metabolomic changes (protein-time interaction). Among this signature, acylcarnitines and other acylated metabolites related to fatty acid or amino acid oxidation were the main discriminant features. The difference in metabolic profiles was mainly explained by urinary acylcarnitines and some other acylated products (protein type, Ps < 0.0001), with a dramatically greater increase (100- to 1000-fold) after WHE, and to a lesser extent after LAC, as compared with CAS. Pathway enrichment analysis confirmed that the type of protein had modified fatty acid oxidation (P < 0.05).Conclusion: Taken together, our results indicate that, in healthy overweight men, the type of protein in a high-fat meal interplays with fatty acid oxidation with a differential accumulation of incomplete oxidation products. A high-fat meal containing WHE, but not CAS, resulted in this outpacing of the tricarboxylic acid cycle. This study was registered at clinicaltrials.gov as NCT00931151. [ABSTRACT FROM AUTHOR]