Diet affects the human gastrointestinal microbiota. Blood and urine samples have been used to determine nutritional biomarkers. However, there is a dearth of knowledge on the utility of fecal biomarkers, including microbes, as biomarkers of food intake. This study aimed to identify a compact set of fecal microbial biomarkers of food intake with high predictive accuracy. Data were aggregated from 5 controlled feeding studies in metabolically healthy adults (n = 285; 21–75 y; BMI 19–59 kg/m²; 340 data observations) that studied the impact of specific foods (almonds, avocados, broccoli, walnuts, and whole-grain barley and whole-grain oats) on the human gastrointestinal microbiota. Fecal DNA was sequenced using 16S ribosomal RNA gene sequencing. Marginal screening was performed on all species-level taxa to examine the differences between the 6 foods and their respective controls. The top 20 species were selected and pooled together to predict study food consumption using a random forest model and out-of-bag estimation. The number of taxa was further decreased based on variable importance scores to determine the most compact, yet accurate feature set. Using the change in relative abundance of the 22 taxa remaining after feature selection, the overall model classification accuracy of all 6 foods was 70%. Collapsing barley and oats into 1 grains category increased the model accuracy to 77% with 23 unique taxa. Overall model accuracy was 85% using 15 unique taxa when classifying almonds (76% accurate), avocados (88% accurate), walnuts (72% accurate), and whole grains (96% accurate). Additional statistical validation was conducted to confirm that the model was predictive of specific food intake and not the studies themselves. Food consumption by healthy adults can be predicted using fecal bacteria as biomarkers. The fecal microbiota may provide useful fidelity measures to ascertain nutrition study compliance.

The gut microbiota consists of a set of microorganisms that colonizes the intestine and ferment fibers, among other nutrients, from the host’s diet. A healthy gut microbiota, colonized mainly by beneficial microorganisms, has a positive effect on digestion and plays a role in disease prevention. However, dysregulation of the gut microbiota can contribute to various diseases. The nutrition of the host plays an important role in determining the composition of the gut microbiota. A healthy diet, rich in fiber, can beneficially modulate the gut microbiota. In this sense, oats are a source of both soluble and insoluble fiber. Oats are considered a functional ingredient with prebiotic potential and contain plant proteins, unsaturated fats, and antioxidant compounds. The impact of oat consumption on the gut microbiota is still emerging. Associations between oat consumption and the abundance of Akkermansia muciniphila, Roseburia, Lactobacillus, Bifidobacterium, and Faecalibacterium prausnitzii have already been observed. Therefore, this integrative review summarizes the findings from studies on the relationship between oat consumption, the gut microbiota, and the metabolites, mainly short-chain fatty acids, it produces.

The fecal metabolome is impacted by diet and includes metabolites generated by human and microbial metabolism. Advances in -omics technologies and analytic approaches have allowed researchers to identify metabolites and better utilize large datasets to generate usable information. One promising aspect of these advancements is the ability to determine objective biomarkers of food intake. We aimed to utilize a multivariate, machine learning approach to identify metabolite biomarkers that accurately predict food intake. Data were aggregated from five controlled feeding studies in adults that tested the impact of specific foods (almonds, avocados, broccoli, walnuts, barley, and oats) on the gastrointestinal microbiota. Fecal samples underwent gas chromatography–mass spectrometry (GC-MS) metabolomic analysis; 307 metabolites were detected. Changes in metabolite relative concentration (treatment post-intervention minus pre-intervention) were utilized in random forest models to 1) examine the relationship between food consumption and fecal metabolome changes and 2) rank the fecal metabolites by their predictive power (i.e., feature importance score). Using the change in relative concentration of fecal metabolites, six single-food random forest models for almond, avocado, broccoli, walnuts, whole-grain barley, and whole-grain oats revealed prediction accuracies between 47% and 89%. When comparing foods to one another, almond intake was differentiated from walnut intake with 91% classification accuracy. Our findings reveal promise in utilizing fecal metabolites as objective complements to certain self-reported food intake estimates. Future research on other foods at different doses and dietary patterns is needed to identify biomarkers that can be applied in feeding study compliance and clinical settings.

The aims of this study are (1) to assess changes in infant WHO growth indicators (weight-for-age, weight-for-length, and head circumference z-scores) from birth to 12 months of age as a function of feeding practices (FP) and (2) to describe the proportion of infants experiencing rapid weight gain (RWG; defined as change in weight-for-age z-score of ≥0.67 between birth and six months) among different FP. The modified Infant Feeding Practices Study II questionnaire was administered to 149 diverse caretakers/mothers of infants who were less than six months of age in a pediatric outpatient clinic. Growth as a function of FP was assessed using repeated measures ANOVA, while logistic regression was used to describe the correlates of RWG. The largest proportion of caretakers was African American (37%), 46% completed college, and 48% were enrolled in the Women, Infants, and Children (WIC) program. Regarding FP, 32% of infants were formula fed, and 18% were breastfed, with the remaining being either mixed fed or complementary fed, with nearly 40% of infants demonstrating RWG. While changes in weight-for-age z-scores differed among FP across time (p<0.05), observed patterns for head-circumference-for-age and weight-for-length z-scores did not. Various demographic correlates (caretaker race-ethnicity, education, and WIC enrollment) were associated with FP. Only the patterns of change in weight-for-age z-scores at 9 and 12 months differed among FP (with breastfeeding being the lowest at both time points). Further study is needed to adequately characterize the correlates of infant growth performance and growth patterns among different FP in such diverse samples. Continued research will allow for the development of an easy-to-use, succinct questionnaire that will allow healthcare providers to individualize feeding recommendations for caretakers of infants.

There is a lack of tools and training to assist in salary and benefit (S&B) negotiations within the nutrition profession. This study is the first to analyze thoughts, feelings, and experiences with S&B negotiations among nutrition and dietetics professionals. The 32-item, web-based, cross-sectional survey study was completed by English-speaking individuals of any gender who identified as a “nutrition and dietetics professional,” were 18 years of age or older in the United States or US Territory. Participant demographics, experience, confidence, and success with negotiation of S&B, value of negotiation, and interest in learning more were the primary outcome measures determined before data collection. Means, standard deviations, and ranges were calculated for ordinal data with frequencies on nominal data. ANOVAs were conducted to evaluate relationships between demographics and negotiation. Participants (N = 1239) were mostly white (90.2%), female (94.5%), registered dietitian (RD) (96.8%) members of the Academy of Nutrition and Dietetics (96.1%). Clinical practitioners accounted for the largest practice area (38.5%). Non-RD professionals had a significantly higher mean for experience with negotiation than RD’s, DTR’s and participants eligible for the RD exam (P = 0.008) and had higher confidence (P = 0.001). Clinical dietitians had significantly lower satisfaction with current salary (P < 0.001) and experience (P < 0.001), confidence (P < 0.001), and success (P < 0.001) with negotiation but had significantly higher interest in advancing negotiation skills (P = 0.017) than all other practice areas. Early education, exposure, and empowerment are key factors in improving the negotiation experience that begins in the undergraduate experience and continues well into professional practice.