Development of a Comprehensive Food Data Citation Standard: A Surprising Gap in the Nutrition Research Literature.

Currently, there is no standard for the citation of food composition data. This leads to the questions: how are food and nutrient data cited in research papers, and are they presented in a way that allows studies to be reproduced? To answer these questions, we performed a review of the literature and quantified the accuracy and completeness of data citations from publications (January to December 2020) in the top 5 nutrition journals as ranked by the Scimago Journal Rankings. We then performed a review of citation guidelines currently in place in other disciplines. Similar to the requirement of completing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist for systematic reviews, we have developed a comprehensive data citation checklist, the Comprehensive Food Data Citation (CFDC) checklist. The CFDC checklist was developed through a benchmarking assessment against established data citation standards. Its purpose is to establish a standardized, best-practice approach for reporting food composition data. The CFDC checklist has been designed to cater to both publishers and authors, ensuring consistency and accuracy in food composition data reporting. The CFDC checklist is also available as an interactive citation generator to facilitate the adoption of consistent and comprehensive citation of food composition data and is available at https://www.nutrientinstitute.org/cfdc. Despite general agreement that accurate data citation is paramount, this is the first citation standard specifically developed to capture food composition data. Because food composition data are the foundation of nutrition research, our proposed guidelines aim to provide the field with a much-needed foundation for acknowledging and sharing data in a way that fosters reproducibility.

Visualizing Data Interoperability for Food Systems Sustainability Research-From Spider Webs to Neural Networks.

Food systems represent all elements and activities needed to feed the growing global population. Research on sustainable food systems is transdisciplinary, relying on the interconnected domains of health, nutrition, economics, society, and environment. The current lack of interoperability across databases poses a challenge to advancing research on food systems transformation. Crosswalks among largely siloed data on climate change, soils, agricultural practices, nutrient composition of foods, food processing, prices, dietary intakes, and population health are not fully developed. Starting with US Department of Agriculture FoodData Central, we assessed the interoperability of databases from multiple disciplines by identifying existing crosswalks and corresponding visualizations. Our visual demonstration serves as proof of concept, identifying databases in need of expansion, integration, and harmonization for use by researchers, policymakers, and the private sector. Interoperability is the key: ontologies and well-defined crosswalks are necessary to connect siloed data, transcend organizational barriers, and draw pathways from agriculture to nutrition and health.

Perspective: Developing a Nutrient-Based Framework for Protein Quality.

The future of precision nutrition requires treating amino acids as essential nutrients. Currently, recognition of essential amino acid requirements is embedded within a generalized measure of protein quality known as the PDCAAS (Protein Digestibility-Corrected Amino Acid Score). Calculating the PDCAAS includes the FAO/WHO/UNU amino acid score, which is based on the limiting amino acid in a food, that is, the single amino acid with the lowest concentration compared to the reference standard. That "limiting" amino acid score is then multiplied by a bioavailability factor to obtain the PDCAAS, which ranks proteins from 0.0 (poor quality) to 1.0 (high quality). However, the PDCAAS has multiple limitations: it only allows for direct protein quality comparison between 2 proteins, and it is not scalable, transparent, or additive. We therefore propose that shifting the protein quality evaluation paradigm from the current generalized perspective to a precision nutrition focus treating amino acids as unique, metabolically active nutrients will be valuable for multiple areas of science and public health. We report the development and validation of the Essential Amino Acid 9 (EAA-9) score, an innovative, nutrient-based protein quality scoring framework. EAA-9 scores can be used to ensure that dietary recommendations for each essential amino acid are met. The EAA-9 scoring framework also offers the advantages of being additive and, perhaps most importantly, allows for personalization of essential amino acid needs based on age or metabolic conditions. Comparisons of the EAA-9 score with PDCAAS demonstrated the validity of the EAA-9 framework, and practical applications demonstrated that the EAA-9 framework is a powerful tool for precision nutrition applications.

Perspective: A Comprehensive Evaluation of Data Quality in Nutrient Databases.

Nutrient databases are a critical component of nutrition science and the basis of exciting new research in precision nutrition (PN). To identify the most critical components needed for improvement of nutrient databases, food composition data were analyzed for quality, with completeness being the most important measure, and for FAIRness, how well the data conformed with the data science criteria of findable, accessible, interoperable, and reusable (FAIR). Databases were judged complete if they provided data for all 15 nutrition fact panel (NFP) nutrient measures and all 40 National Academies of Sciences, Engineering, and Medicine (NASEM) essential nutrient measures for each food listed. Using the gold standard the USDA standard reference (SR) Legacy database as surrogate, it was found that SR Legacy data were not complete for either NFP or NASEM nutrient measures. In addition, phytonutrient measures in the 4 USDA Special Interest Databases were incomplete. To evaluate data FAIRness, a set of 175 food and nutrient data sources were collected from worldwide. Many opportunities were identified for improving data FAIRness, including creating persistent URLs, prioritizing usable data storage formats, providing Globally Unique Identifiers for all foods and nutrients, and implementing citation standards. This review demonstrates that despite important contributions from the USDA and others, food and nutrient databases in their current forms do not yet provide truly comprehensive food composition data. We propose that to enhance the quality and usage of food and nutrient composition data for research scientists and those fashioning various PN tools, the field of nutrition science must step out of its historical comfort zone and improve the foundational nutrient databases used in research by incorporating data science principles, the most central being data quality and data FAIRness.

Establishing a Common Nutritional Vocabulary - From Food Production to Diet.

Informed policy and decision-making for food systems, nutritional security, and global health would benefit from standardization and comparison of food composition data, spanning production to consumption. To address this challenge, we present a formal controlled vocabulary of terms, definitions, and relationships within the Compositional Dietary Nutrition Ontology (CDNO, www.cdno.info) that enables description of nutritional attributes for material entities contributing to the human diet. We demonstrate how ongoing community development of CDNO classes can harmonize trans-disciplinary approaches for describing nutritional components from food production to diet.

A Clear Difference Emerges in Hormone Patterns Following a Standard Midday Meal in Young Women Who Regularly Eat or Skip Breakfast.

BACKGROUND: Multiple hormones are involved in the regulation of food intake and glucose metabolism. Past intervention studies showed a benefit of eating breakfast on satiety, but this was possibly confounded by the disruption of habitual meal patterns. OBJECTIVE: The objective of this study was to compare hormonal responses, including insulin, leptin, glucagon-like peptide-1, ghrelin, peptide YY (PYY3-36), and cholecystokinin (CCK), between habitual breakfast eaters (Br-Es) and habitual skippers (Br-Ss) to a standard midday meal. METHODS: Thirty-two women [mean ± SD age: 22.6 ± 3.3 y; body mass index (in kg/m2): 21.8 ± 2.0] participated in a cross-sectional study that consisted of a 3-h test protocol that included a standard test meal served at 1230 with pre- and postmeal blood sampling. The protocol required that Br-Es eat a typical breakfast between 0700 and 1000, whereas Br-Ss had no breakfast meal and had fasted for 12 h. Blood was drawn 35 and 5 min prelunch and 5, 20, 35, 50, and 110 min postlunch. RESULTS: Repeated-measures ANOVA revealed a group difference for PYY3-36 (P = 0.001), with the Br-E group exhibiting 50-90% higher concentrations throughout the test period. Leptin tended to be different (P = 0.08) between groups, with higher mean ± SD values for the Br-S group (27.6 ± 29.6 ng/mL) compared with the Br-E group (11.5 ± 9.8 ng/mL). Partial least squares regression analysis confirmed that these 2 hormones were important contributors to the patterns of the hormones, anthropometric, clinical, and behavioral variables that differed between groups; insulin and CCK were important as well. CONCLUSION: We found differences between the Br-E and Br-S groups in circulating gut and adipose-derived hormones measured midday, indicating that the breakfast habit is associated with the hormonal milieu before and after a midday meal. The different patterns may be short-lived or may impact metabolism later in the day. This report is a secondary analysis of a trial registered at clinicaltrials.gov as NCT01427556.

Chronic Stress Is Associated with Indicators of Diet Quality in Habitual Breakfast Skippers.

BACKGROUND: Previous studies suggest skipping breakfast is associated with lower diet quality, but possible reasons underlying this relationship are not clear. OBJECTIVE: Our aim was to determine the relationship between chronic stress and variations in diet quality in the context of breakfast eating or breakfast skipping. DESIGN: Based on morning eating habits, 40 breakfast eaters and 35 breakfast skippers participated in a cross-sectional study. Diet assessment was based on unannounced 24-hour recalls. PARTICIPANTS/SETTING: Women, ages 18 to 45 years, with a body mass index (calculated as kg/m2) <40 were recruited in the greater Sacramento, CA, area between 2009 and 2013. Only women who consistently ate or skipped breakfast were enrolled. MAIN OUTCOME MEASURES: Compliance with the 2010 Dietary Guidelines for Americans was measured using the Healthy Eating Index 2010 (HEI-2010). Stress and executive function were evaluated with validated questionnaires and a computer-based task, respectively. STATISTICAL ANALYSES PERFORMED: Diet characteristics of breakfast eating and breakfast skipping were evaluated as nutrient densities (amounts per 1,000 kcal) and compared using a one-way analysis of covariance, with body mass index as covariate. Diet and stress variable associations were assessed using Pearson correlations. RESULTS: Despite no observed differences in daily energy intake between breakfast skipping and breakfast eating, overall diet quality (P=0.001), whole grains (P=0.002), fruit (P=0.002), empty calories (P=0.050), fiber (P=0.001), calcium (P=0.001), potassium (P=0.033), and folate (P=0.013) intakes were higher in breakfast eating. In the evening, breakfast skipping consumed more added sugars (P=0.012) and saturated fat (P=0.006). In breakfast skipping, reported stress was associated with empty calories (r=-0.39; P=0.027) and evening intake of added sugars (r=0.501; P=0.005). These relationships were not observed in breakfast eating. CONCLUSIONS: Breakfast skippers were less likely to meet the Dietary Guidelines for Americans and consumed more empty calories at night. Chronic stress was related to evening eating choices and overall empty calories in the diet of breakfast skippers, whereas breakfast eaters' dietary intake did not appear to be affected by chronic stress.

Female breakfast skippers display a disrupted cortisol rhythm and elevated blood pressure.

Chronic stress and over-activity in the hypothalamic-pituitary-adrenal (HPA) axis may link breakfast skipping and poor cardiometabolic health. Missing the first major meal of the day in rodents prolongs elevated circulating corticosterone at a time when it's normally decreasing. To extend these findings to humans, we hypothesized that habitual breakfast skippers would display a similar pattern of circulating cortisol and alterations in meal and stress-induced cortisol reactions. Normal weight to obese women aged 18-45 years old who were strictly defined as either breakfast skippers (n=30) or breakfast eaters (n=35) were invited to participate in our study. Normal breakfast habits were maintained for the entire study period and each participant attended 4 lab visits. Over the first 2 lab visits, body composition, fasting clinical chemistries, and self-reports of chronic stress were assessed. On each of 2 additional days (lab visits 3 and 4), salivary free cortisol was measured at home upon waking and at bedtime, and in the lab in response to a standard lunch, ad libitum afternoon snack buffet, and stress and control (relaxation) tasks. The order of the control and stress test visits was randomized. While body weight, body composition, HOMA-IR, total and HDL cholesterol did not statistically differ (p>0.05), both diastolic and systolic blood pressure was elevated (p<0.01) and LDL cholesterol was lower (p=0.04) in the breakfast skipper group. Compared to the breakfast eaters and on the control task visit only, breakfast skippers had higher circulating cortisol from arrival to midafternoon (p<0.01) and during the snack buffet (p<0.05). Furthermore, the lunch-induced cortisol reaction was larger in the 'skippers' (p=0.03). On both stress and control visit days, the diurnal cortisol amplitude was significantly (p=0.02) blunted in breakfast skippers. Self-reports of chronic stress did not differ between the groups. These data indicate that habitually skipping breakfast is associated with stress-independent over-activity in the HPA axis which, if prolonged, may increase risk (e.g., hypertension) for cardiometabolic disease in some people.

Vegetable variety is a key to improved diet quality in low-income women in California.

Primary prevention education interventions, including those sponsored by the US Department of Agriculture for low-income families, encourage and support increases in vegetable intake. Promoting vegetable variety as a focal point for behavior change may be a useful strategy to increase vegetable consumption. A simple vegetable variety evaluation tool might be useful to replace the time-intensive 24-hour dietary recall. The purpose of our study was to determine whether vegetable variety is associated with vegetable consumption and diet quality among US Department of Agriculture program participants. Variety of vegetable intake and measures of total vegetable intake, diet quality, and diet cost were evaluated. Low-income, female participants (N=112) aged 20 to 55 years with body mass index 17.7 to 68.5 who were the primary food purchasers/preparers for their households were recruited from four California counties representing rural, urban, and suburban areas. Energy density and Healthy Eating Index-2005 were used to assess diet quality. Vegetable variety was based on number of different vegetables consumed per week using a food frequency questionnaire, and three groups were identified as: low variety, ≤5 different vegetables per week; moderate variety, 6 to 9 vegetables per week; and high variety, ≥10 vegetables per week. Compared with the low-variety group, participants in the high-variety group ate a greater quantity of vegetables per day (P<0.001); their diets had a higher Healthy Eating Index score (P<0.001) and lower energy density (P<0.001); and costs of their daily diet and vegetable use were higher (P<0.001). Thus, greater vegetable variety was related to better overall diet quality, a larger quantity of vegetables consumed, and increased diet cost.