Food And Nutrient Database For Dietary Studies Research Articles

Intake of dietary flavonoids in relation to overactive bladder among U.S. adults: a nutritional strategy for improving urinary health

BackgroundThe increasing influence of overactive bladder (OAB) on physical as well as mental health of individuals is becoming more pronounced annually, as evidenced by the urge urinary incontinence and nocturia. Symptoms in OAB patients may be influenced by inflammation and oxidative stress. Flavonoids are recognized as significant anti-inflammatory and antioxidant agents, which are commonly available in fruits, tea, vegetables, etc. Previous research has demonstrated the therapeutic potential of flavonoids and their subclasses in treating inflammation, and oxidative stress. Despite this, there remains a paucity of research exploring the potential correlation between flavonoid consumption, specifically within distinct subclasses, and OAB. Thus, our study aims to investigate the relationship between flavonoid intake and OAB to identify possible dietary interventions for OAB management.MethodsWe utilized the survey data from the National Health and Nutrition Examination Survey (NHANES) and the USDA Food and Nutrient Database for Dietary Studies (FNDDS) to investigate the relationship between dietary intake of total and subclass flavonoids and the risk of OAB based on 13,063 qualified American adults. The dietary flavonoid intake was estimated from two 24-h dietary recalls. Weighted multivariate logistic regression model, quantile-based g-computation, restricted cubic spline model, and stratified analysis were used to explore the association between flavonoid intake and OAB, respectively.ResultsThe participants diagnosed with OAB exhibited a higher percentage of being female, older, Non-Hispanic Black, unmarried, former drinkers, having a lower annual household income, lower poverty to income ratio, lower educational attainment, and a higher likelihood of being obese and smokers. Upon adjusting for confounding factors, the weighted logistic regression models revealed that the third quartile of consumption of anthocyanidin and the second quartile of consumption of flavone were significantly associated with the reduced odds of OAB, while total flavonoid consumption did not show a significant correlation with the risk of OAB. The quantile-based g-computation model indicated that flavone, anthocyanidin and flavonol were the primary contributors to the observed negative correlation. Furthermore, the restricted cubic spline models demonstrated a J-shaped non-linear exposure-response association between anthocyanidin intake and the risk of OAB (Pnonlinear = 0.00164). The stratified and interaction analyses revealed that the relationship between anthocyanidin intake and the risk of OAB was significantly influenced by age (Pinteraction = 0.01) and education level (Pinteraction = 0.01), while the relationship between flavone intake and the risk of OAB was found to vary by race (Pinteraction = 0.02) and duration of physical activity (Pinteraction = 0.05).ConclusionOur research suggests that consuming a diet rich in flavonoid subclass anthocyanidin and flavone is associated with a reduced risk of OAB, potentially offering clinical significance in the prevention of OAB development. This underscores the importance of dietary adjustments in the management of OAB symptoms.

Nutrient dataset development via FAO/INFOODS approach for infant nutritional survey in rural Matiari, Pakistan

To accurately evaluate dietary intake, multiple resources are necessary, including serving-size modules, pictures, and questionnaires that are used to gather information during surveys. One critical component is the accessibility of food composition data at the national or regional level, which is required to determine dietary intake. Food Agriculture Organization/International Network of Food Data Systems (FAO/INFOODs) tools are useful for developing high-quality food composition data. We used these tools to create a nutrient dataset for a nutritional survey in Matiari, Sindh, and to collect dietary information through a 24-hour food recall questionnaire. The survey results indicated 540 distinct types of foods, including 291 ready-to-eat items, 84 foods used as ingredients in recipes, and 164 various composite and mixed recipes. Most food items corresponded to the national and regional Food Composition Tables (FCTs) and the Food and Nutrient Database for Dietary Studies (FNDDS) of the USDA, with the exception of recipe food data. We utilized Eurofir-recipe calculation methods to compute the recipe data. The data were homogenized and standardized utilizing EFSA and Langual™. Because of the obsolescence and inadequacy of Pakistan's food composition table in assessing essential nutrients, we had to source data from various other sources. Consequently, to establish the nutrient dataset, we incorporated approximately 25 % of user data from national sources, with recipe data comprising 46 % and less than 20 % extracted from regional, U.S database, and diverse online sources. This study is the first effort in which we gathered data from reliable sources representing local eating patterns, with some exceptions. Future studies will hugely benefit from this database, especially as we face a high prevalence of undernutrition in our part of the world.

Associations between Essential Amino Acid Intake and Functional Health Outcomes in Older Adults: Analysis of the National Health and Nutrition Examination Survey, 2001–2018

BackgroundThe relationships between habitual essential amino acid (EAA) intake and body composition, muscle strength, and physical function in older US adults are not well defined. ObjectivesThis cross-sectional study evaluated associations between usual EAA intakes and body composition, muscle strength, and physical function in US adults ≥65 y. MethodsThe Food and Nutrient Database for Dietary Studies (FNDDS) 2001–2018 was linked to the US Department of Agriculture Standard Reference database to access existing amino acid composition data for FNDDS ingredients. FNDDS ingredients without existing amino acid composition data were matched to similar ingredient codes with available data. Usual EAA, leucine, lysine, and sulfur-containing amino acid (SAA; methionine + cysteine) intakes (g/d) from National Health and Nutrition Examination Survey 2001–2018 were calculated for individuals ≥65 y (n = 10,843). Dependent variables included muscle strength measured by isometric grip test, body mass index (BMI), waist circumference, dual-energy X-ray absorptiometry-measured appendicular lean mass and whole-body fat mass, and self-reported physical function (that is, tasks of daily living). Regression analyses were used to determine covariate-adjusted relationships between EAA, leucine, lysine, and SAA intake and functional health outcomes. P < 0.0013 was considered significant. ResultsEAA, leucine, lysine, and SAA intakes, covaried with physical activity level and usual protein intake, were not associated with muscle strength or self-reported physical function in males or females or with body composition in males. EAA intakes were positively associated with waist circumference in females (β ± SEM, 2.1 ± 0.6 cm, P = 0.0007). Lysine intakes were positively associated with BMI (3.0 ± 0.7 kg/m2, P < 0.0001) and waist circumference (7.0 ± 1.7 cm, P = 0.0001) in females. ConclusionsHabitual EAA, leucine, lysine, and SAA intakes, covaried with physical activity level and usual protein intake, were not associated with lean mass, muscle strength, or physical function in adults ≥65 y. However, EAA intakes, particularly lysine, were positively associated with measures of adiposity in older females.This trial was registered with the Open Science Framework (https://doi.org/10.17605/OSF.IO/25V63) as osf.io/25v63).

Association between flavonoid intake and rheumatoid arthritis among US adults

Basic research shows that flavonoids have anti-inflammatory effects that influence rheumatoid arthritis (RA) in rats. Investigating potential dietary interventions for RA helps prevent the onset and progression of the disease. Clinical evidence on the association of flavonoid and subclass intake with RA is lacking. Using three survey cycles of 2007–2008, 2009–2010, and 2017–2018 from the National Health and Nutrition Survey and the United States Department of Agriculture's Food and Nutrient Database for Dietary Studies (FNDDS), we analyzed 7,419 American adults (≥20 years old). The values of flavonoid and subclass intake were calculated using FNDDS. The status questions for self-reported RA were from the NHANES codebook. Weighted analyses, revealed that among the 7,419 participants included in this study (mean age of 44.69 years [standard error, 0.40] and 3,584 [48.31%] were female), 408 met the classification criteria for RA. According to the multivariable logistic regression model, compared with the risk of RA in the first quartile (Q1), the risks of RA in the second quartile (Q2), the third quartile (Q3) and the fourth quartile (Q4) were lower (Q2: OR=0.55, 95% CI: 0.38–0.80; Q3: OR=0.66, 95% CI: 0.44–0.97; Q4: OR=0.64, 95% CI: 0.46–0.89; trend: P=.03). The association between total flavonoids and RA remained significant after full consideration of confounding factors. With regard to the subclasses of flavonoids, high flavanones intake was associated with low RA prevalence in Model 3 (Q3: OR= 0.60, 95% CI:0.39–0.92; Q4: OR = 0.56, 95% CI: 0.32–0.99, trend: P=.02), but no such association was found in the other subclasses. Total flavonoids intake protected against RA, and the risk of developing RA decreased significantly with increasing intake of total flavonoids. Total flavonoids and flavanones were significantly associated with reduced RA risk for the American adult population. We highlighted the importance of employing diverse methodologies to assess the health effects of flavonoids.

Dietary anthocyanin is associated with a lower prevalence of hyperuricemia independently of metabolic syndrome among females: Results from NHANES 2007-2010 and 2017-2018.

Known for anti-inflammatory and antioxidant properties, flavonoid has phytoestrogenic effects, but it is unclear whether its role in hyperuricemia and metabolic syndrome (MetS) differs by gender. Moreover, given the strong association between hyperuricemia and MetS, we aimed to explore whether flavonoid is a protective factor for hyperuricemia, independently of MetS, in different genders. Data for 2007-2010 and 2017-2018 were obtained from the National Health and Nutrition Examination Survey (NHANES) and the Food and Nutrient Database for Dietary Studies (FNDDS). To assess the association among flavonoid, hyperuricemia, and MetS, multivariate logistic regression and subgroup analyses were conducted. Besides, to investigate whether the association between flavonoid and hyperuricemia was independent of MetS, multivariate logistic regression models were further conducted to explore the association between flavonoid and MetS among females with hyperuricemia and to investigate the association between flavonoid and hyperuricemia among females after excluding MetS. Among 5356 females, anthocyanin intake was inversely associated with the prevalence of hyperuricemia (Q4 vs. Q1: OR 0.49, 95% CI 0.31 to 0.76), and MetS (Q4 vs. Q1: OR 0.68, 95% CI 0.50 to 0.93). Furthermore, subgroup analyses showed the beneficial association between anthocyanin and hyperuricemia among females aged 40 to 59 years and menopausal. However, among 5104 males, no significant association was observed after adjustment for covariates (Q4 vs. Q1: OR 0.81, 95% CI 0.56 to 1.18). While in 372 females with hyperuricemia, no significant association was found between MetS and anthocyanin (Q4 vs. Q1: OR 0.88, 95% CI 0.31 to 2.49). Meanwhile, among 3335 females after excluding MetS, there was still a significant association between anthocyanin and a lower prevalence of hyperuricemia (Q4 vs. Q1: OR 0.38, 95% CI 0.17 to 0.85). Dietary anthocyanin is associated with a lower prevalence of hyperuricemia independently of MetS among females. Foods rich in anthocyanin should be emphasized for females, especially those aged 40 to 59 years and menopausal, which may be of potential significance in the prevention of hyperuricemia.

Identifying Optimally Sustainable Foods: A Four-Dimensional Analysis of Sustainable Foods in the American Diet

A holistic understanding of food sustainability is vital for making socially and environmentally conscious food choices. Sustainable diets have been defined by four dimensions: health, economics, environment, and society. The purpose of this study was to determine how metrics for nutritional quality, monetary cost, environmental impact, and social and cultural acceptability of foods and beverages vary across and within food groups and to identify which foods and beverages are optimally sustainable according to these metrics. Data from the Food and Nutrient Database for Dietary Studies (FNDDS) was linked with frequency of consumption, nutrient density, environmental impact, and cost data from publicly available databases. A sustainability index, based on the four dimensions, was developed to quantify overall sustainability. Nutrient density was correlated negatively with environmental impact and frequency of consumption but positively with cost (p &lt; 0.001). Out of 5964 items, 165 were identified as optimally sustainable. Sustainability index scores varied within each food group. Less than 1% of optimally sustainable items were Dairy products, while 62% were Protein Foods—of which 92% were Plant Proteins. Few foods and beverages met the criteria to be considered optimally sustainable. However, Plant Protein foods may generally strike the best balance among these four indicators of sustainability. A holistic understanding of food sustainability is necessary to facilitate nutritious and environmentally conscious dietary choices that adhere to other needs, personal values, and preferences.

Higher anthocyanin intake is associated with a lower risk of non-alcoholic fatty liver disease in the United States adult population.

Flavonoids are a class of plant chemicals known to have health-promoting properties, including six subclasses. Anthocyanin is one of the subclasses that have anti-inflammatory and antioxidant activities. However, the relationship between flavonoid subclass intake and the risk of non-alcoholic fatty liver disease (NAFLD) and liver fibrosis has not been verified in representative samples of the United States. This is a cross-sectional study based on the data from the National Health and Nutrition Examination Survey (NHANES) and the Food and Nutrient Database for Dietary Studies (FNDDS) in 2017-2018. The intake of flavonoid subclasses of the participants was obtained from two 24 h dietary recalls. The NAFLD and liver fibrosis were defined based on the international consensus criteria. The relationship between flavonoid subclass intake and NAFLD and liver fibrosis was evaluated using a multivariate logistic regression model corrected for multiple confounding factors. Subgroup analysis, trend tests, interaction tests and restricted cubic spline were carried out to further explore this relationship. In addition, we also explored the relationship between anthocyanin and liver serum biomarkers, dietary total energy intake and healthy eating index (HEI)-2015 scores. A total of 2,288 participants were included in the analysis. The intake of anthocyanin was significantly negatively associated with the risk of NAFLD, but not other flavonoid subclasses. A higher anthocyanin intake was significantly associated with a lower risk of NAFLD (quartile 4, OR 0.470, 95% CI 0.275-0.803). The results of subgroup analysis showed that the protective effect of dietary anthocyanin intake on NAFLD was more pronounced in participants of non-Hispanic whites, with hypertension and without diabetes (P for interaction <0.05). Alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), dietary total energy intake was significantly negatively correlated with dietary anthocyanin intake. We did not find any protective effect of flavonoid subclass intake on liver fibrosis. Anthocyanin, but not other flavonoid subclasses, can significantly reduce the risk of NAFLD. The protective effect was more pronounced in non-Hispanic whites, participants without diabetes and those with hypertension. Our study provides new evidence that anthocyanin intake has a reverse significant association with the risk for NAFLD.

Selecting foods from FNDDS when calculating food intake: Does the reference matter?

To estimate food intake, the nutrient content of food must be known or inferred by matching it to a nutrient database. This study evaluated how different procedures for matching foods to the Food and Nutrient Database for Dietary Studies (FNDDS) affect food intake estimates. Adult participants estimated a meal with the PortionSize app, which contains a subset of FNDDS codes (PortionSize FNDDS). Meals were covertly weighed (weigh back), and intake was estimated by referencing the FNDDS dataset. Combination foods were evaluated by 1) a composite generated by summing the nutrient values (from FNDDS) from single food items and 2) using the single composite food code from FNDDS. Raters analyzed food images from the PortionSize app to estimate intake with the digital photography of foods (DPF) method. Raters estimated intake from: 1) PortionSize FNDDS and 2) full FNDDS. Using PortionSize’s FNDDS database, participants’ energy intake estimates were equivalent to rater estimated energy intake. Raters estimated almost identical energy intake when they used PortionSize vs. full FNDDS. Using the full FNDDS, the DPF’s energy estimates were similar to weigh back. Estimation of energy intake with a single FNDDS code was not equivalent to estimation from summing the nutrient values for combination foods.

Validity of an Artificial Intelligence-Based Application to Identify Foods and Estimate Energy Intake Among Adults: A Pilot Study

BackgroundThe commercial application Openfit allows for automatic identification and quantification of food intake through short video capture without a physical reference marker. There are no known peer-reviewed publications on the validity of this Nutrition Artificial Intelligence (AI). ObjectivesTo test the validity of Openfit to identify food automatically and semiautomatically (with user correction), test the validity of Openfit at quantifying energy intake (kcal) automatically and semiautomatically, and assess satisfaction and usability of Openfit. MethodsDuring a laboratory-based visit, adults (7 male and 17 female), used Openfit to automatically and semiautomatically record provided meals, which were covertly weighed. Foods logged were identified as an “exact match,” “far match,” or an “intrusion” using Food and Nutrient Database for Dietary Studies (FNDDS) codes. Descriptive data were stratified by meal, food item, and FNDDS group, and presented with or without beverages. Bland–Altman analyses assessed errors over levels of energy intake. Participants completed a User Satisfaction Survey (USS) and the Computer Systems Usability Questionnaire (CSUQ). Open-ended questions were assessed with qualitative methods. ResultsExact matches, far matches, and intrusions were 46%, 41%, and 13% for automated identification, and 87%, 23%, and 0% for semiautomated identification, respectively. Error for automated and semiautomated energy estimates were 43% and 33% with beverages, and 16% and 42% without beverages. Bland–Altman analyses indicated larger error for higher energy meals. Overall mean scores were 2.4 for the CSUQ and subscale means scores ranged from 4.1 to 5.5. for the USS. Participants recommended improvements to Openfit’s Nutrition AI, manual estimation, and overall app. ConclusionOpenfit worked relatively well for automatically and semiautomatically identifying foods. Error in automated energy estimates was relatively high; however, after excluding beverages, error was relatively low (16%). For semiautomated energy estimates, error was comparable to previous studies. Improvements to the Nutrition AI, manual estimation and overall application may increase Openfit’s usability and validity.This trial was registered at clinicaltrials.gov as NCT05343585.

Discontinued food codes resource for Food and Nutrient Database for Dietary Studies 2019–2020

The Food and Nutrient Database for Dietary Studies (FNDDS) is USDA’s application database used for analysis of dietary intake from What We Eat in America (WWEIA), the dietary interview component of the National Health and Nutrition Examination Survey (NHANES). Food codes are added and discontinued with each two-year release of FNDDS. A discontinued codes resource was first developed in 2012 to archive the food codes no longer used, provide the rationale for discontinuation and, where applicable, a link to a different FNDDS code. This research details the Discontinued Food Codes between FNDDS 2017–2018 and FNDDS 2019–2020, the fifth discontinued codes resource release. More than 1800 discontinued codes are included, which is comparable to the FNDDS 2017–2018 and double the FNDDS 2015–2016 releases. More than 75 % of these codes are consolidated into similar FNDDS food codes. This highlights the continued focus on incorporating generic food codes in FNDDS that reflect the foods Americans consume. A few highly reported food codes representing more than one product were expanded. This resource is beneficial to those who use FNDDS and researchers who conduct trend analysis using WWEIA, NHANES. The discontinued codes resource can be downloaded from the Food Surveys Research Group website at www.ars.usda.gov/nea/bhnrc/fsrg.

Food and Nutrient Database for Dietary Studies 2019–2020: An application database for national dietary surveillance

The USDA Food and Nutrient Database for Dietary Studies (FNDDS) is an application database created for analyzing dietary intakes from What We Eat in America (WWEIA), National Health and Nutrition Examination Survey (NHANES). FNDDS 2019–2020, the 10th version released contains 5624 food codes and their descriptions. Values for 65 nutrients are included for each item, as well as weights for common portions. Most nutrient values are derived from USDA’s FoodData Central and newer analytical data from Foundation Foods are incorporated. Changes to the recipe calculation process generate nutrient profiles that represent a variety of items. Several categories were reviewed and updated including beef, pork, seafood, candy and cakes/pies. Both the baby-toddler foods and ready-to-eat cereals categories were updated to have generic food codes and recipe calculations, which represent a variety of commercial products versus prior FNDDS versions which contained food codes for specific products matched to the same Standard Reference codes. The FNDDS is available in both SAS® and Access® formats for download. FNDDS At A Glance provides quick viewing in Microsoft Excel® file format. All are publicly available at www.ars.usda.gov/nea/bhnrc/fsrg.

Association between dietary anthocyanidins intake and depression among US adults: a cross-sectional study (NHANES, 2007–2010 and 2017–2018)

BackgroundAnthocyanidins encompass a diverse array of compounds that possess notable anti-inflammatory and antioxidant properties with pharmacological activity. However, the correlation between the consumption of anthocyanidins through diet and its impact on depression has yet to be investigated.MethodsThis study utilized the Food and Nutrient Database for Dietary Studies (FNDDS) expanded flavonoid intake database, as well as data from the National Health and Nutrition Examination Survey (NHANES) from the years 2007 to 2010 and 2017 to 2018. The analysis of the collected data was conducted in R, following the guidelines outlined in the official NHANES user guide “Stratified Multi-stage Probability Sampling”. Three different models were developed using logistic regression to assess the protective effects of T3 (representing the highest intake of anthocyanidins) against depression. Additionally, the study aimed to investigate whether there existed a non-linear relationship between the dietary intake of anthocyanidins and the prevalence of depression by employing restricted cubic spline (RCS) analysis.ResultsA total of 6,845 eligible participants were included in this cross-sectional study, with their data appropriately weighted to represent a population of 89.8 million people in the United States of America. The results demonstrated that individuals diagnosed with depression had a significantly lower dietary intake of anthocyanidins compared to those without depression (P < 0.0001). Moreover, significant differences were observed among different participant groups regarding socioeconomic status and the presence of chronic physical illnesses (such as hypertension, glucose status, and chronic kidney disease risk, etc.) (P < 0.05). After adjustment for covariates, participants with the highest intake of anthocyanins (T3) demonstrated a significantly reduced risk of depression [ORT3 = 0.67, 95%CI: (0.48–0.95), (Ptrend= 0.02]. Furthermore, the RCS analysis revealed a significant linear relationship between dietary anthocyanidin intake and depression (P for non-linear = 0.5876).ConclusionOur findings reveal a negative association between dietary anthocyanidin intake and depression.

Integration of USDA Food Classification System and Food Composition Database for Image-Based Dietary Assessment among Individuals Using Insulin.

New imaging technologies to identify food can reduce the reporting burden of participants but heavily rely on the quality of the food image databases to which they are linked to accurately identify food images. The objective of this study was to develop methods to create a food image database based on the most commonly consumed U.S. foods and those contributing the most to energy. The objective included using a systematic classification structure for foods based on the standardized United States Department of Agriculture (USDA) What We Eat in America (WWEIA) food classification system that can ultimately be used to link food images to a nutrition composition database, the USDA Food and Nutrient Database for Dietary Studies (FNDDS). The food image database was built using images mined from the web that were fitted with bounding boxes, identified, annotated, and then organized according to classifications aligning with USDA WWEIA. The images were classified by food category and subcategory and then assigned a corresponding USDA food code within the USDA's FNDDS in order to systematically organize the food images and facilitate a linkage to nutrient composition. The resulting food image database can be used in food identification and dietary assessment.

The association between dietary intake of flavonoids and its subclasses and the risk of metabolic syndrome.

The healthiest way to prevent metabolic syndrome (MetS) is through behavioral and nutritional adjustments. We examined the relationship between total flavonoids intake, flavonoid subclasses, and clinically manifest MetS. A cross-sectional analysis was conducted among 28,719 individuals from the National Health and Nutrition Examination Survey (NHANES) and Food and Nutrient Database for Dietary Studies (FNDDS) 2007-2011 and 2017-2018. Two 24-h reviews were conducted to determine flavonoids intake and subclasses. The link between flavonoids intake and MetS was investigated using a multivariate logistic regression model. Q2 and Q3 of total flavonoids intake were associated with 20 and 19% lower risk of incident MetS after adjusting age and sex. Anthocyanidins and flavanones intake in Q2 and Q3 substantially reduced the MetS risk compared to Q1. MetS risk decreased steadily as the total intake of flavonoids increased to 237.67 mg/d. Flavanones and anthocyanidins also displayed V-shaped relationship curves (34.37 and 23.13 mg/d). MetS was adversely linked with total flavonoids intake, flavanones, and anthocyanidins. Moreover, the most effective doses of total flavonoids, flavanones, and anthocyanidins were 237.67, 34.37, and 23.13 mg/d, respectively, potentially preventing MetS.

P06-010-23 Determination of the Prebiotic Content of Foods in the 2015–2016 Food and Nutrient Database for Dietary Studies (FNDDS)

P06-010-23 Determination of the Prebiotic Content of Foods in the 2015–2016 Food and Nutrient Database for Dietary Studies (FNDDS)

Predicting Unreported Micronutrients From Food Labels: Machine Learning Approach

Micronutrient deficiencies represent a major global health issue, with over 2 billion individuals experiencing deficiencies in essential vitamins and minerals. Food labels provide consumers with information regarding the nutritional content of food items and have been identified as a potential tool for improving diets. However, due to governmental regulations and the physical limitations of the labels, food labels often lack comprehensive information about the vitamins and minerals present in foods. As a result, information about most of the micronutrients is absent from existing food labels. This paper aims to examine the possibility of using machine learning algorithms to predict unreported micronutrients such as vitamin A (retinol), vitamin C, vitamin B1 (thiamin), vitamin B2 (riboflavin), vitamin B3 (niacin), vitamin B6, vitamin B12, vitamin E (alpha-tocopherol), vitamin K, and minerals such as magnesium, zinc, phosphorus, selenium, manganese, and copper from nutrition information provided on existing food labels. If unreported micronutrients can be predicted with acceptable accuracies from existing food labels using machine learning predictive models, such models can be integrated into mobile apps to provide consumers with additional micronutrient information about foods and help them make more informed diet decisions. Data from the Food and Nutrient Database for Dietary Studies (FNDDS) data set, representing a total of 5624 foods, were used to train a diverse set of machine learning classification and regression algorithms to predict unreported vitamins and minerals from existing food label data. For each model, hyperparameters were adjusted, and the models were evaluated using repeated cross-validation to ensure that the reported results were not subject to overfitting. According to the results, while predicting the exact quantity of vitamins and minerals is shown to be challenging, with regression R2 varying in a wide range from 0.28 (for magnesium) to 0.92 (for manganese), the classification models can accurately predict the category ("low," "medium," or "high") level of all minerals and vitamins with accuracies exceeding 0.80. The highest classification accuracies for specific micronutrients are achieved for vitamin B12 (0.94) and phosphorus (0.94), while the lowest are for vitamin E (0.81) and selenium (0.83). This study demonstrates the feasibility of predicting unreported micronutrients from existing food labels using machine learning algorithms. The results show that the approach has the potential to significantly improve consumer knowledge about the micronutrient content of the foods they consume. Integrating these predictive models into mobile apps can enhance their accessibility and engagement with consumers. The implications of this research for public health are noteworthy, underscoring the potential of technology to augment consumers' understanding of the micronutrient content of their diets while also facilitating the tracking of food intake and providing personalized recommendations based on the micronutrient content and individual preferences.

Associations between dietary flavonoid intake with hepatic steatosis and fibrosis quantified by VCTE: Evidence from NHANES and FNDDS

Background and aimFlavonoids are natural products of plant origin and have been shown to be beneficial for nonalcoholic fatty liver disease (NAFLD) in animal studies. However, relevant epidemiological evidence is still lacking, and the relationship between flavonoid and subclass intake with quantified hepatic steatosis and fibrosis has not been investigated. Methods and resultsThis study was based on the Food and Nutrient Database for Dietary Studies (FNDDS) expanded flavonoid intake database and the National Health and Nutrition Examination Survey (NHANES) 2017–2018 and included a total of 4113 participants with vibration-controlled transient elastography (VCTE) data. Multiple logistic regression was used to assess linear relationships between flavonoids and hepatic steatosis and fibrosis. Smoothed curve fit and a generalized additive model were used to investigate the non-linear relationship, and a two-tailed linear regression model was used to find potential inflection points. Of the 4113 participants, 1045 (25.41%) were diagnosed with NAFLD. After adjusting for energy and major non-dietary covariates, significant linear negative correlations were observed between total flavonoids and CAP [-1.53 (−2.59, −0.47)] and LSM [-0.17 (−0.27, −0.07)]. After adjusting for all covariates, flavones had the strongest and most significant negative association with hepatic steatosis [-1.98 (−3.79, −0.17)]. The results of smooth curve fitting and subgroup analysis demonstrated gender differences, and threshold effect analysis further identified a U-shaped relationship and inflection point between flavonoid intake and hepatic steatosis (infection point: 287.25 mg/d). ConclusionsOur findings suggest negative associations between flavonoid and subclass intake with hepatic steatosis and fibrosis.

Association between daidzein intake and metabolic associated fatty liver disease: A cross-sectional study from NHANES 2017-2018.

Metabolic associated fatty liver disease (MAFLD) has become the most common liver disease globally, yet no new drugs have been approved for clinical treatment. Therefore, we investigated the relationship between dietary intake of soy-derived daidzein and MAFLD, to find potentially effective treatments. We conducted a cross-sectional study using data from 1,476 participants in National Health and Nutrition Examination Survey (NHANES) from 2017 to 2018 and their associated daidzein intake from the flavonoid database in the USDA Food and Nutrient Database for Dietary Studies (FNDDS). We investigated the relationship between MAFLD status, controlled attenuation parameter (CAP), AST/Platelet Ratio Index (APRI), Fibrosis-4 Index (FIB-4), liver stiffness measurement (LSM), nonalcoholic fatty liver disease (NAFLD) fibrosis score (NFS), hepatic steatosis index (HSI), fatty liver index (FLI), and daidzein intake by adjusting for confounding variables using binary logistic regression models and linear regression models. In the multivariable-adjusted model II, there was a negative association between daidzein intake and the incidence of MAFLD (OR for Q4 versus Q1 was 0.65, 95% confidence interval [CI] = 0.46-0.91, p = 0.0114, p for trend was 0.0190). CAP was also negatively associated with daidzein intake, β = -0.37, 95% CI: -0.63 to -0.12, p = 0.0046 in model II after adjusting for age, sex, race, marital status, education level, family income-to-poverty ratio (PIR), smoking, and alcohol consumption. Stratified by quartiles of daidzein intake, trend analysis of the relationship between daidzein intake and CAP remained significant (p for trend = 0.0054). In addition, we also found that HSI, FLI, and NFS were negatively correlated with daidzein intake. LSM was negatively related to daidzein intake but had no statistical significance. The correlation between APRI, FIB-4, and daidzein intake was not strong (although p < 0.05, β values were all 0). We found that MAFLD prevalence, CAP, HSI, and FLI, all decreased with increased daidzein intake, suggesting that daidzein intake may improve hepatic steatosis. Therefore, dietary patterns of soy food or supplement consumption may be a valuable strategy to reduce the disease burden and the prevalence of MAFLD.

Association between flavonoid and subclasses intake and metabolic associated fatty liver disease in U.S. adults: Results from National Health and Nutrition Examination Survey 2017-2018.

Metabolic associated fatty liver disease (MAFLD) formerly known as non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease. Flavonoid is considered a promising candidate for metabolic disease prevention although few studies have explored the relationship between flavonoid intake and MAFLD. To assess the relationship between flavonoid intake and MAFLD prevalence in the U.S. adult population. The data of this cross-sectional study was obtained from National Health and Nutrition Examination Survey (NHANES) and Food and Nutrient Database for Dietary Studies (FNDDS) 2017-2018. Flavonoid and subclasses intake was assessed by two 24h recalls. MAFLD was diagnosed according to the consensus definitions. Multivariate logistic regression model was performed to examine the association between flavonoid intake and MAFLD with adjustments for confounders. A total of 4,431 participants were included in this cross-sectional analysis. MAFLD had a weighted prevalence of 41.93% and was not associated with total flavonoid intake. A higher anthocyanin and isoflavone intake, on the other hand, was associated with a lower prevalence of MAFLD. The protective effect of higher anthocyanin intake was significant among male, Non-Hispanic White, and Non-Hispanic Asia participants. Higher isoflavone intake was associated with a lower risk of MAFLD in participants of younger (age < 50), Non-Hispanic Black, Non-Hispanic Asia, and higher HEI-2015 scores compared with the lowest quartile of isoflavone intake. Stratified analysis showed that compared with the lowest quartile of anthocyanin intake, the effect of anthocyanin intake on MAFLD varied by racial groups (P interaction = 0.02). A positive correlation existed between HDL and anthocyanidin intake (P = 0.03), whereas a negative correlation existed between FPG and isoflavone intake (P = 0.02). MAFLD was adversely linked with flavonoid subclasses, anthocyanin and isoflavone. This modifiable lifestyle provides a potential opportunity to prevent MAFLD. These findings promote future research into the links and mechanisms between anthocyanin and isoflavone intake and MAFLD.

Effect of increasing plant protein intake on protein quality and nutrient intake of US adults.

Three cycles of NHANES (2013-2018) were used to assess protein intake, protein quality (PDCAAS), protein cost, and nutrient intakes across quartiles of plant protein intake (Q1: <28.2%; Q2: 28.2%-<32.1%; Q3: 32.1-<36.2%; Q4: ≥36.2%) over a 24 hr period (≥ 19 years, n=14,888). Grains represented the primary source of plant protein across quartiles and increased from 5.01% (Q1) to 13.5% (Q4). Across all the USDA's Food and Nutrient Database for Dietary Studies (FNDDS) food groups, grains were the most economical source of protein (24.3-26 g protein/$1). Legumes were the most economical plant-based protein (28-37.7 g protein/$1) within the "Protein Foods" FNDDS group. Absolute protein intake (96.6 g/day) and PDCAAS (0.91) of diets were progressively lower from Q1 to 72.0 g/day and 0.8 in Q4, respectively. Modelling the replacement of 50% of amino acids from grains in the diet with amino acids from legumes increased the PDCAAS by 10% in Q4. Intake levels of fibre, folate, iron, and zinc, were higher in Q2-4 compared to Q1, but had lower intakes of vitamin B12 and vitamin D. Amino acid complementation is required to effectively integrate higher levels plant protein into US diets.