A new category-specific nutrient rich food (NRF9f.3) score adds flavonoids to assess nutrient density of fruit

A novel Nutrient Rich Food (NRFa11.3) score uses flavonoids and carotenoids to identify antioxidant-rich spices, herbs, vegetables, and fruit

Introduction

Nutrient profiling (NP) models designed to evaluate the healthfulness of plant-based foods ought to incorporate bioactive phytochemicals. Herbs and spices are one food group of current interest.

Methods

Two new versions of the well-established Nutrient Rich Food (NRF) index were applied to spices, herbs, vegetables, fruit, and other plant-based foods. Analyses used the US Department of Agriculture (USDA) SR-28 nutrient composition database merged with the USDA Expanded Flavonoid database 3.3. The NRF4.3 model was based on protein, fiber, potassium, and vitamin C. The NRFa11.3 model was based on micronutrients with reported antioxidant activity (vitamin C, vitamin E, selenium, copper, and zinc), carotenoids (alpha and beta carotene, beta-cryptoxanthin, lycopene, lutein/zeaxantin) and flavonoids. Saturated fat, added sugar, and sodium were nutrients to limit. The NRF algorithm was based on sums of percent daily values (%DVs) capped at 100%.

Results

The NRF4.3 model awarded high scores to herbs and spices, cocoa powder, and nuts, but did not discriminate well among vegetables and fruit. The NRFa11.3 model performed better. Green leafy, red orange and cruciferous vegetables had the highest carotenoid content. Highest in flavonoids were cocoa powder, herbs and spices, and berries. Highest combined NRFa11.3 values were observed for herbs and spices, green leafy vegetables, cocoa, nuts, and red-orange and cruciferous vegetables.

Discussion

Fresh and dry herbs and spices, often ignored by NP models, were particularly nutrient-rich and may provide non-negligible amounts of key phytonutrients to the human diet.

Nutrient Density, Added Sugar, and Fiber Content of Commercially Available Fruit Snacks in the United States from 2017 to 2022

Fruit snacks have become a popular and convenient snacking choice and have the potential to contribute to a well-balanced diet. However, the nutritional quality of fruit snack products has not yet been studied. The objective of the present study is to provide a nutritional assessment of the fruit snack product category. This study used the Mintel Global New Product Database to collect data about fruit snack products launched in the United States from 2017 to 2022. Fruit snack products (n = 2405) are divided into nine product categories based on product characteristics. Nutrition composition was assessed using a comprehensive score, Nutrient Rich Food (NRF) model, and by examining individual components (added sugar and fiber). The results show that dried fruit has the highest nutrient density, fiber content, and the lowest added sugar content. Conversely, fruit-flavored snacks have the lowest nutrient density, fiber content, and added sugar content. Currently, fruit puree, canned fruit with juice, and dried fruit are the only fruit snacks that meet the current recommendations set by the USDA Dietary Guidelines. Future directions for the fruit snack category should consider decreasing the added sugar content, increasing the fiber content, and enhancing their sensory profile to improve the overall nutrient density.

An integrative analytical framework to identify healthy, impactful, and equitable foods: a case study on 100% orange juice

To identify healthy, impactful, and equitable foods, we combined health scores from six diverse nutrient profiling systems (NPS) into a meta-framework (meta-NPS) and paired this with dietary guideline adherence assessment via multilevel regression and poststratification. In a case-study format, a commonly debated beverage formulation - 100% orange juice (OJ) - was chosen to showcase the utility and depth of our framework, systematically scoring high across multiple food systems (i.e. a Meta-Score percentile = 93rd and Stability percentile = 75th) and leading to an expected increase of US dietary fruit guideline adherence by ∼10%. Moreover, the increased adherence varies across the 300 sociodemographic strata, with the benefit patterns being sensitive to absolute or relative quantification of the difference of adherence affected by OJ. In sum, the adaptable, integrative framework we established deepens the science of nutrient profiling and dietary guideline adherence assessment while shedding light on the nuances of defining equitable health effects.

Polyphenolic profiles of a variety of wild berries from the Pacific Northwest region of North America

Polyphenols have been extensively profiled and quantified in commercially grown berries, but similar information is sparsely available for wild berries. Because polyphenolic contents are inherently associated with berries health benefits, determining phenolic profiles is an important step for strategizing potential uses by the industry and for health and nutrition outcomes. Here, we profiled phenolic compounds in wild berries commonly encountered and harvested in the Pacific Northwest region of North America. Huckleberries (Vaccinium membranaceum) of varying phenotypes were found to be comparable to related blueberries in terms of general phenolic classes composition. However, all huckleberries exhibited markedly high levels of cyanidins, and delphinidins or peonidins were also higher in specific phenotypes. Wild black elderberries (Sambucus nigra spp. Canadensis) were found to have remarkably high phenolic, especially anthocyanins, in line with reports from cultivated elderberries. Saskatoon serviceberries (Amelanchier alnifolia) were found to exhibit high polyphenol content, but with a less diverse profile dominated by quercetin. The most intriguing berry may be the Oregon grape (Mahonia Aquifolium) being the only one exhibiting more than one g of polyphenols per 100 g; as well as a remarkably even distribution of the different anthocyanin classes. All colored wild berries were found to have at minimum comparable total phenolic contents when compared to cultivated and other wild berries, suggesting they should exhibit comparable human health benefits such as antioxidant and metabolic syndrome preventative potential described for these other berries. Overall, our data represents a valuable resource to explore the potential to valorize wild berry species for their specific phenolic profiles and predicted nutritional and health properties. With repeated phenolic profiling to better understand the impact of the environment, the wild berries described here hold promises both as food ingredient applications as well as valuable complement for healthy dietary patterns.

Identification of a secondary Q-marker in high-quality ecotypes of Carthamus tinctorius L. and exploration of the target preference

Safflower (Carthamus tinctorius) has the efficacy for promoting blood circulation and preventing cardiovascular and Alzheimer's diseases and is thus a valuable medicinal and functional food plant. However, how to evaluate high-quality safflower is still a problem. To differentiate intraspecies ecotypes and illustrate the mechanisms of differential metabolites of C. tinctorius from different regions, this study combined the widely targeted metabolome, weighted network pharmacology, and molecular docking to filter bioactive compounds and predict the target preference. The results indicated that kaempferol is suitable as a secondary Q-marker to differentiate intraspecies ecotypes. In secondary metabolites, the average content of kaempferol and its derivates in C. tinctorius from Sichuan is three times that of other areas, which have the potential for the targeted medicine of CA2 and TNF. In volatile metabolites, isoaromadendrene epoxide has the potential as a specifically targeted medicine of RXRA. The change of the target preference could be the reason for the difference in drug efficacy among different varieties of C. tinctorius. It is reasonable that Sichuan was recognized as a high-quality ecotype producing region of C. tinctorius in China, which promotes blood circulation and removes blood stasis. This study provides an innovative method to differentiate intraspecies ecotypes and explore their target preference.

Mixed nuts with high nutrient density improve insulin resistance in mice by gut microbiota remodeling

The consumption of mixed nuts is a healthy dietary strategy to reduce the risk of cardiovascular disease and has a prebiotic effect on the gut microbiota. However, there is a lack of basic research based on mixed nut formulation. This study established a new method for optimizing mixed nut formulations using the Nutrient Rich Food (NRF) index model. Nutrient indices were adjusted by combining 10 and 8 encouraging nutrients and 3 limiting nutrients of nuts and dried fruits, respectively. The optimized mixed nut formulation had the highest total NRF and the lowest energy, which was achieved by applying linear programming. The effect of an optimized mixed nut formulation on insulin resistance and gut microbiota was investigated in an animal model of metabolic disorders caused by a high-fat diet. Male C57BL/6J mice (n = 12 per group) were fed a low-fat diet, a high-fat diet (HFD), HFD with a supplemented classical randomized controlled trial mixed nut formula (MN1), a commercially available mixed nut formula (MN2), a high-nutrient density mixed nut formula (MN3), or ellagic acid (positive control). MN3 treatment decreased total plasma cholesterol, homeostasis model assessment-insulin resistance index, high sensitivity C-reactive protein, and zonulin levels, strengthened the intestinal barrier, and significantly altered the β-diversity of the intestinal microbiota as compared to the HFD group. These effects of MN3 were superior to MN1 and MN2. In conclusion, MN3 had the highest nutrient density and improved insulin resistance in low-grade inflammation via gut microbiota remodeling.

Nutrient Profiling of Japanese Dishes: The Development of a Novel Ajinomoto Group Nutrient Profiling System

Government agencies and private companies have supported the development of nutrient profiling (NP) systems to facilitate the selection of nutrient-dense foods by consumers, promote nutritious food development, and limit excessive advertising of products with low nutritional value. While most NP models were developed to assess individual foods, the Ajinomoto Group Nutrient Profiling System (ANPS) was developed to assess the overall nutritional value of cooked dishes that are culturally specific to Japan. Based on the national dietary recommendations and nutritional surveys, target values were created for 13 dish categories, while considering the combinations of meal units. For the ANPS, the four evaluating elements were protein and vegetables, which should be encouraged, and sodium and saturated fatty acids, which should be limited. The ANPS algorithm for dishes was the sum of the scores of individual elements, with a maximum of 10 points per serving. The sum of scores was then multiplied by 2.5 to convert to the 100-point scale. Convergent validity was tested using the nutrient-rich food index (NRF) score of 6.3. In total, 1,089 popular Japanese dishes were evaluated using the ANPS, and the median score of ANPS was 70.0 points (interquartile range, 55–78.8), and the average score was 67.7 (standard deviation, 16.5) points. Since salt intake is a major health risk in Japan, this tool was designed to evaluate sodium content with high sensitivity, and low-salt dishes significantly improved sodium and ANPS scores compared with regular dishes. The Pearson’s correlation coefficient between the total score of NRF 6.3 and ANPS in 1,089 dishes was r = 0.452 (p < 0.0001). This newly developed ANPS could be used to evaluate culture-specific cooked dishes per serving size. It can determine the nutritional values of dishes, with a high sensitivity to sodium content, a major Japanese nutritional issue. Further research is needed to determine the accuracy and usefulness of the ANPS as a system that would lead to changes in eating behavior nationwide.

A New Carbohydrate Food Quality Scoring System to Reflect Dietary Guidelines: An Expert Panel Report

Existing metrics of carbohydrate food quality have been based, for the most part, on favorable fiber- and free sugar-to-carbohydrate ratios. In these metrics, higher nutritional quality carbohydrate foods are defined as those with >10% fiber and <10% free sugar per 100 g carbohydrate. Although fiber- and sugar-based metrics may help to differentiate the nutritional quality of various types of grain products, they may not aptly capture the nutritional quality of other healthy carbohydrate foods, including beans, legumes, vegetables, and fruits. Carbohydrate food quality metrics need to be applicable across these diverse food groups. This report introduces a new carbohydrate food scoring system known as a Carbohydrate Food Quality Score (CFQS), which supplements the fiber and free sugar components of previous metrics with additional dietary components of public health concern (e.g., sodium, potassium, and whole grains) as identified by the Dietary Guidelines for Americans. Two CFQS models are developed and tested in this study: one that includes four dietary components (CFQS-4: fiber, free sugars, sodium, potassium) and one that considers five dietary components (CFQS-5: fiber, free sugars, sodium, potassium, and whole grains). These models are applied to 2596 carbohydrate foods in the Food and Nutrient Database for Dietary Studies (FNDDS) 2017−2018. Consistent with past studies, the new carbohydrate food scoring system places large percentages of beans, vegetables, and fruits among the top scoring carbohydrate foods. The whole grain component, which only applies to grain foods (N = 1561), identifies ready-to-eat cereals, oatmeal, other cooked cereals, and selected whole grain breads and crackers as higher-quality carbohydrate foods. The new carbohydrate food scoring system shows a high correlation with the Nutrient Rich Food (NRF9.3) index and the Nutri-Score. Metrics of carbohydrate food quality that incorporate whole grains, potassium, and sodium, in addition to sugar and fiber, are strategically aligned with multiple 2020−2025 dietary recommendations and may therefore help with the implementation of present and future dietary guidelines.

An Alternative Nutrient Rich Food Index (NRF-ai) Incorporating Prevalence of Inadequate and Excessive Nutrient Intake

Most nutrient profiling models give equal weight to nutrients irrespective of their ubiquity in the food system. There is also a degree of arbitrariness about which nutrients are included. In this study, an alternative Nutrient Rich Food index was developed (NRF-ai, where ai denotes adequate intake) incorporating prevalence of inadequate and excessive nutrient intake among Australian adults. Weighting factors for individual nutrients were based on a distance-to-target method using data from the Australian Health Survey describing the proportion of the population with usual intake less than the Estimated Average Requirement defined by the Nutrient Reference Values for Australia and New Zealand. All nutrients for which data were available were included, avoiding judgements about which nutrients to include, although some nutrients received little weight. Separate models were developed for females and males and for selected age groups, reflecting differences in nutrient requirements and usual intake. Application of the new nutrient profiling models is demonstrated for selected dairy products and alternatives, protein-rich foods, and discretionary foods. This approach emphasises the need to identify foods that are rich in those specific nutrients for which intake is below recommended levels and can be used to address specific nutrient gaps in subgroups such as older adults. In addition, the new nutrient profiling model is used to explore other sustainability aspects, including affordability (NRF-ai per AUD) and ecoefficiency (NRF-ai/environmental impact score).

Watermelon and L-Citrulline in Cardio-Metabolic Health: Review of the Evidence 2000-2020

PURPOSE OF REVIEW

Watermelon (Citrullus lanatus) distinctively contains L-citrulline and L-arginine, precursors of nitric oxide (NO), along with polyphenols and carotenoids suggesting a role in cardio-metabolic health. The goal of this paper is to review the preclinical and clinical trial evidence published from 2000 to 2020 to assess watermelon intake and L-citrulline, as a signature compound of watermelon, on cardiovascular and metabolic outcomes, and to identify future directions important for establishing dietary guidance and therapeutic recommendations actionable by health care professionals, patients, and the general public.

RECENT FINDINGS

Watermelon and L-citrulline supplementation reduced blood pressure in human trials. Evidence for benefits in lipids/lipoprotein metabolism is emerging based on human literature and consistently reported in animal models. A role for watermelon intake in body weight control, possibly through satiety mechanisms, warrants further research. Likewise, improved glucose homeostasis in chemically and diet-induced animal models of diabetes is apparent, though limited data are available in humans. Emerging areas include brain and gut health indicated by NO bioavailability in all tissues, and evidence suggesting improvements in gut barrier function and altered microbial composition after watermelon intake that may influence metabolite pools and physiological function. Watermelon fruit contains unique vaso- and metabolically-active compounds. Accumulating evidence supports regular intake for cardio-metabolic health. Future research to determine the amount and frequency of watermelon/citrulline intake for desired outcomes in different populations requires attention to advance preventative and therapeutic strategies for optimal health and disease risk reduction.

Adjusting for protein quality by food source may affect nutrient density metrics

Methods to assess nutrient density of foods, commonly known as nutrient profiling (NP), typically include protein as a component. In this study, the goal was to apply a correction for protein quality by food source to selected NP algorithms. Analyses of 378 component foods of the Fred Hutch food frequency questionnaire showed that animal-source foods (ie, meat, eggs, and dairy) along with some soy products and nuts were the only foods that provided > 20% of the daily value (DV) of protein per 100 g or per 100 kcal. Most beans, pulses, legumes, grains, and vegetables provided <10% DV of protein per 100 g or per 100 kcal. Adjusting for protein quality using a simplified Protein Digestibility Corrected Amino Acid Score (PDCAAS) had consequences for point-based NP models (namely, Nutri-Score) and for continuous nutrient density scores (namely, Nutrient Rich Foods). Quantitative methods that use protein content to capture nutrient density may require a protein-quality adjustment, especially when adapted for use in low- and middle-income countries where protein quality is an issue of public health concern.