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Personalized nutrition (PN) approaches have been shown to help drive behavior change and positively influence health outcomes. This has led to an increase in the development of commercially available PN programs, which utilize various forms of individual-level information to provide services and products for consumers. The lack of a well-accepted definition of PN or an established set of guiding principles for the implementation of PN creates barriers for establishing credibility and efficacy. To address these points, the North American Branch of the International Life Sciences Institute convened a multidisciplinary panel. In this article, a definition for PN is proposed: "Personalized nutrition uses individual-specific information, founded in evidence-based science, to promote dietary behavior change that may result in measurable health benefits." In addition, 10 guiding principles for PN approaches are proposed: 1) define potential users and beneficiaries; 2) use validated diagnostic methods and measures; 3) maintain data quality and relevance; 4) derive data-driven recommendations from validated models and algorithms; 5) design PN studies around validated individual health or function needs and outcomes; 6) provide rigorous scientific evidence for an effect on health or function; 7) deliver user-friendly tools; 8) for healthy individuals, align with population-based recommendations; 9) communicate transparently about potential effects; and 10) protect individual data privacy and act responsibly. These principles are intended to establish a basis for responsible approaches to the evidence-based research and practice of PN and serve as an invitation for further public dialog. Several challenges were identified for PN to continue gaining acceptance, including defining the health-disease continuum, identification of biomarkers, changing regulatory landscapes, accessibility, and measuring success. Although PN approaches hold promise for public health in the future, further research is needed on the accuracy of dietary intake measurement, utilization and standardization of systems approaches, and application and communication of evidence.

Objective: The U.S. Army uses sex‐specific circumference‐based prediction equations to estimate percent body fat (%BF) to evaluate adherence to body composition standards. The equations are periodically evaluated to ensure that they continue to accurately assess %BF in a diverse population. The objective of this study was to develop and validate alternative field expedient equations that may improve upon the current Army Regulation (AR) body fat (%BF) equations. Methods: Body size and composition were evaluated in a representatively sampled cohort of 1904 active‐duty Soldiers (1261 Males, 643 Females), using dual‐energy X‐ray absorptiometry (%BFDXA), and circumferences obtained with 3D imaging and manual measurements. Sex stratified linear prediction equations for %BF were constructed using internal cross validation with %BFDXA as the criterion measure. Prediction equations were evaluated for accuracy and precision using root mean squared error, bias, and intraclass correlations. Equations were externally validated in a convenient sample of 1073 Soldiers. Results: Three new equations were developed using one to three circumference sites. The predictive values of waist, abdomen, hip circumference, weight and height were evaluated. Changing from a 3‐site model to a 1‐site model had minimal impact on measurements of model accuracy and performance. Male‐specific equations demonstrated larger gains in accuracy, whereas female‐specific equations resulted in minor improvements in accuracy compared to existing AR equations. Equations performed similarly in the second external validation cohort. Conclusions: The equations developed improved upon the current AR equation while demonstrating robust and consistent results within an external population. The 1‐site waist circumference‐based equation utilized the abdominal measurement, which aligns with associated obesity related health outcomes. This could be used to identify individuals at risk for negative health outcomes for earlier intervention. [ABSTRACT FROM AUTHOR]

More than 75 women have successfully graduated from the U.S. Army Ranger Course since the integration of women into elite military combat training. This study sought to identify the psychological characteristics and sociological variables that contributed to their motivation and success. A guided interview and demographic and psychological questionnaires were used to assess characteristics of 13 women who successfully completed elite military combat training. Collectively, these women were college graduates and had well educated fathers, possessed high levels of grit and resiliency, and described themselves as self-competitive challenge seekers. These women all had a strong male influence in their lives. The characteristics of these pioneer women may be unique from subsequent cohorts as female participation in elite military combat training becomes the norm and as attitudes and experiences change for graduates of female combat training over time. [ABSTRACT FROM AUTHOR]

Background Food processing alters diet digestibility and composition, thereby influencing interactions between host biology, diet, and the gut microbiota. The fecal metabolome offers insight into those relations by providing a readout of diet–microbiota interactions impacting host health. Objectives The aims were to determine the effects of consuming a processed diet on the fecal metabolome and to explore relations between changes in the fecal metabolome with fecal microbiota composition and gastrointestinal health markers. Methods This was a secondary analysis of a randomized controlled trial wherein healthy adults [94% male; 18–61 y; BMI (kg/m2): 26 ± 3] consumed their usual diet [control (CON), n  = 27] or a Meal, Ready-to-EatTM (Ameriqual Packaging) military ration diet composed of processed, shelf-stable, ready-to-eat items for 21 d (MRE; n  = 27). Fecal metabolite profiles, fecal microbiota composition, biomarkers of intestinal barrier function, and gastrointestinal symptoms were measured before and after the intervention. Between-group differences and associations were assessed using nonparametric t tests, partial least-squares discriminant analysis, correlation, and redundancy analysis. Results Fecal concentrations of multiple dipeptides [Mann-Whitney effect size (ES) = 0.27–0.50] and long-chain SFAs (ES = 0.35–0.58) increased, whereas plant-derived compounds (ES = 0.31–0.60) decreased in MRE versus CON (P  < 0.05; q  < 0.20). Changes in dipeptides correlated positively with changes in fecal concentrations of Maillard-reaction products (ρ = 0.29–0.70; P  < 0.05) and inversely with changes in serum prealbumin (ρ = −0.30 to −0.48; P  ≤ 0.03). Multiple bile acids, coffee and caffeine metabolites, and plant-derived compounds were associated with both fecal microbiota composition and gastrointestinal health markers, with changes in fecal microbiota composition explaining 26% of the variability within changes in gastrointestinal health–associated fecal metabolites (P  = 0.001). Conclusions Changes in the fecal metabolomes of adults consuming a Meal, Ready-to-EatTM diet implicate interactions between diet composition, diet digestibility, and the gut microbiota as contributing to variability within gastrointestinal responses to the diet. Findings underscore the need to consider both food processing and nutrient composition when investigating the impact of diet–gut microbiota interactions on health outcomes. This trial was registered at www.clinicaltrials.gov as NCT02423551. [ABSTRACT FROM AUTHOR]