Validity of Dietary Assessment Methods When Compared to the Method of Doubly Labeled Water: A Systematic Review in Adults

Comparison of Energy and Nutrient Intake vs. Estimated Needs in Warfighters: an Update

Active members of the military must perform optimally under conditions of thermal stress and/or energy deficiency. Military dietary reference intakes (MDRIs) provide guidelines for energy and nutrient intakes but is based studies largely conducted in Army. Needs may vary by service branch and/or position. New protein recommendations have emerged, which are not reflected in MDRIs. PURPOSE OF REVIEW: Compare reported dietary intake in active duty members to MDRIs and 2016 American College of Sports Medicine (ACSM) sports nutrition guidelines. RECENT FINDINGS: Active duty members are not meeting their energy and carbohydrate needs with low-to-adequate protein intake and adequate-to-high fat intake. Other nutrients of concern are vitamin D, calcium, iron, B-vitamins, and fiber. Thermal stress increases energy needs and suppresses appetite and thus increase risk for energy and nutrition deficiencies. Energy and nutrients needs can vary by branch of armed service, job responsibility, and external stressors.

Dietary Protein Intake Patterns and Inadequate Protein Intake in Older Adults from Four Countries

Recent interest in protein intake per meal is observed in studies that have reported the protein intake patterns in different countries; however, comparisons of these data are lacking. We aimed to compare protein intake patterns and the percentage of inadequate protein intake (IPI) per day and meal in older adults from different countries. We acquired data of protein intake in older adults from four countries (Mexico, United States of America, Germany, and United Kingdom). We compared protein intake (per day and meal), IPI per day and meal, and the number of meals with an adequate protein content among countries. The IPI per day significantly differed among countries for <0.8 and <1.0 (both p < 0.001), but not for <1.2 g/kg/d (p = 0.135). IPI per meal (<30 g/meal) did not differ among countries at breakfast (p = 0.287) and lunch (p = 0.076) but did differ at dinner (p < 0.001). Conversely, IPI per meal (<0.4 g/kg/meal) significantly differed among countries at breakfast, lunch, and dinner (all p < 0.001). The percentage of participants that ate ≥30 g/meal or ≥0.4 g/kg/meal at zero, one, and two or three meals per day significantly differed among countries (all p < 0.05). IPI at breakfast and lunch (<30 g/meal) was a common trait in the analyzed samples and might represent an opportunity for nutritional interventions in older adults in different countries.

Demographic, Behavioural and Anthropometric Correlates of Food Liking: A Cross-sectional Analysis of Young Adults

The degree to which foods are liked or disliked is associated with dietary intake and health behaviours. However, most food liking research has focused on single foods and nutrients and few studies have examined associations with demographics and health behaviours. Thus, this study aimed to investigate the association between food liking and socio-demographics, health behaviours, diet quality and body mass index (BMI) in a sample of young Australian adults. Data from 1728 undergraduate students (21.8 (standard deviation [SD] 6.0) years; 76% female) were used. Food liking scores and a diet quality index (Dietary Guideline Index, DGI) were estimated from a Food Liking Questionnaire and Food Frequency Questionnaire (FFQ), respectively. Multivariate linear regression analyses were used to assess the association between food liking and correlates. Young adults with higher liking for encouraged core foods were older, female, did their own food shopping, consumed less packaged foods and had better diet quality. Higher liking for discretionary foods and beverages was associated with less healthy behaviours, such as smoking, higher BMI and lower diet quality. These results suggest that food liking measures may offer an appropriate methodology for understanding influences on young adults' food choices, adding to the body of literature investigating the potential for food liking scores to assess diet-disease relationships.

Feasibility and Acceptability Findings of an Energy Balance Data Repository of Children, Adolescents, and Young Adults with Cancer

Cancer patients suffer changes in energy balance (EB), the combination of energy intake (nutrition) and energy expenditure (physical activity (PA)), which may influence cancer-related morbidity, mortality, and quality of life. Significant gaps remain in our understanding of the frequency and magnitude of these EB changes. Herein, we report on the feasibility and acceptability of a longitudinal repository of EB outcomes in children, adolescents and young adults (AYA) with cancer along the cancer continuum to fill these gaps. This EB repository includes PA, nutrition, and physical function (PF) parameters. PA data were gathered through activity trackers. Nutritional data were gathered through food diaries and micronutrient labs. PF was assessed with validated objective and patient-reported measures. Feasibility was achieved with >50% enrollment of eligible patients (n = 80, Mage = 18.1 ± 7.5); 26 were children with cancer and 54 were AYAs with cancer. An 88.75% retention rate indicated acceptability. Despite COVID-19 disruptions, >50% of participants provided completed data for PA and micronutrient labs as of April 2020. Food diaries and PF data collection experienced disruptions. Methodological adaptations are in progress to minimize future disruptions. Overall, our findings demonstrate that prospective EB assessments are feasible and acceptable among children and AYAs with cancer.

Assessing psychological and nutritional impact of suspected orthorexia nervosa: a cross-sectional pilot study

BACKGROUND

To date, research on the dietary patterns of individuals with potential orthorexic symptoms is lacking. This cross-sectional pilot study aimed to explore the feasibility of assessing dietary patterns with psychological traits and states of individuals with possible orthorexic tendencies.

METHODS

Dietary intakes of 10 individuals (two males and eight females) were assessed using 24-h recall. Mean age of participants was 28.3 years; mean body mass index was 21.2 kg m^-2 . Nutrient intakes were compared with current dietary guidelines and the Eatwell Guide (Public Health England, 2016). Participants completed the ORTO-15, the Eating Attitude Test (EAT-26), the Obsessive-Compulsive Inventory-Revised edition (OCI-R), Paulhus's Spheres of Control (SoC), the Rosenberg's Self-Esteem Scale (RSES) and the Multidimensional Body-Self Relations Questionnaire (MBSRQ).

RESULTS

High levels of disparity across participants' psychometric scores and 24-h recall results were observed. There was no single pattern of self-imposed dietary restrictions among participants. Described dietary practices failed to meet the guidelines for several nutrients.

CONCLUSIONS

The results of this pilot study suggest that an extensive investigation of the diets of individuals with possible orthorexic tendencies in a large-scale study would contribute to the understanding of this condition. In addition, the use of multiple psychometric instruments is recommended for diagnosing orthorexic nervosa.

Impact of obesity on underreporting of energy intake in type 2 diabetic patients: Clinical Evaluation of Energy Requirements in Patients with Diabetes Mellitus (CLEVER-DM) study

BACKGROUND & AIMS

Although accurate assessment of energy intake (EI) is critical in diabetes care, underreporting of EI on dietary records (DR) is often an issue. However, few studies have examined EI with doubly labeled water (DLW) in patients with diabetes mellitus. We aimed to investigate the impact of sex and obesity on the dissociation of DR from total energy expenditure (TEE) evaluated with DLW in patients with type 2 diabetes.

METHODS

Fifty-two patients with type 2 diabetes aged 60-79 years were enrolled for the Clinical Evaluation of Energy Requirements in Patients with Diabetes Mellitus (CLEVER-DM) study at a single university hospital. TEE was measured over 14 days by the DLW method as standard. EI was calculated by assessment of 3-day DR by registered dietitians.

RESULTS

The mean difference between EI and TEE was 238 ± 412 kcal/day (~10% of TEE). Neither EI nor TEE was significantly different between obese (body mass index (BMI) ≥25 kg/m²) and non-obese (BMI <25 kg/m²) patients. There was a negative correlation between EI/TEE ratio and BMI in women (R = -0.437, P = 0.033) but not in men (R = -0.174, P = 0.377). There was a significant difference in EI/TEE ratio between obese and non-obese patients among women (0.85 ± 0.15 vs. 1.01 ± 0.21, P = 0.045) but not men (0.85 ± 0.20 vs. 0.87 ± 0.17, P = 0.79).

CONCLUSIONS

EI calculated by 3-day DR may underestimate habitual intake, which is assumed to be equal to TEE measured by the DLW method except in non-obese women with diabetes.

CLINICAL TRIAL REGISTRATION NUMBER

UMIN000023051.

Traditional Self-Reported Dietary Instruments Are Prone to Inaccuracies and New Approaches Are Needed

Background: Diet is a modifiable behavior that influences an individual's health. Because of this, diet assessment is an important component of public health surveillance, evaluating response to community health interventions, and monitoring individual compliance to medical interventions. Diet assessments are usually performed using one of three basic methods: diet recall, diet diaries, or food frequency questionnaires. Although these three assessment instruments have displayed a strong agreement between themselves, when reported intake is compared with intake measured using quantitative nutrient biomarkers, investigators have identified systematic misreporting errors for all three of these self-reported dietary instruments. Aims: This work aims to summarize the state of knowledge regarding misreporting and why it impedes diet-health research and to introduce advances in the collection and the treatment of dietary data. Methods: This work reviews and summarizes published data on misreporting and the recent efforts to reduce such errors. Results: The evidence demonstrates a strong and consistent systematic underreporting of energy intake (EIn) across adults and children studies. Underreporting of EIn has been found to increase with body mass index (BMI), and the differences between macronutrient reports indicate that not all foods are underreported equally. Protein is least underreported, but which specific foods are commonly underreported are not known. Conclusions: Because energy underreporting varies as a function of BMI, self-reported EIn should not be used for the study of energy balance in the study of obesity. The between-individual variability in the underreporting of self-reported intake of energy and other nutrients attenuates diet-disease relationships. Recent efforts to correct for underreporting have reduced misreporting of diet outcomes, but improvements have been incremental in nature and more research is needed to validate and extend these efforts.

A Guide to Diet-Microbiome Study Design

Intense recent interest in understanding how the human gut microbiome influences health has kindled a concomitant interest in linking dietary choices to microbiome variation. Diet is known to be a driver of microbiome variation, and yet the precise mechanisms by which certain dietary components modulate the microbiome, and by which the microbiome produces byproducts and secondary metabolites from dietary components, are not well-understood. Interestingly, despite the influence of diet on the gut microbiome, the majority of microbiome studies published to date contain little or no analysis of dietary intake. Although an increasing number of microbiome studies are now collecting some form of dietary data or even performing diet interventions, there are no clear standards in the microbiome field for how to collect diet data or how to design a diet-microbiome study. In this article, we review the current practices in diet-microbiome analysis and study design and make several recommendations for best practices to provoke broader discussion in the field. We recommend that microbiome studies include multiple consecutive microbiome samples per study timepoint or phase and multiple days of dietary history prior to each microbiome sample whenever feasible. We find evidence that direct effects of diet on the microbiome are likely to be observable within days, while the length of an intervention required for observing microbiome-mediated effects on the host phenotype or host biomarkers, depending on the outcome, may be much longer, on the order of weeks or months. Finally, recent studies demonstrating that diet-microbiome interactions are personalized suggest that diet-microbiome studies should either include longitudinal sampling within individuals to identify personalized responses, or should include an adequate number of participants spanning a range of microbiome types to identify generalized responses.

Diet, nutrients and the microbiome

Although there is associative evidence linking fecal microbiome profile to health and disease, many studies have not considered the confounding effects of dietary intake. Consuming food provides fermentable substrate which sustains the microbial ecosystem that resides with most abundance in the colon. Western, Mediterranean and vegetarian dietary patterns have a role in modulating the gut microbiota, as do trending restrictive diets such the paleolithic and ketogenic. Altering the amount or ratio of carbohydrate, protein and fat, particularly at the extremes of intake, impacts the microbiome. Diets high in fermentable carbohydrates support the relative abundance of Bifidobacterium, Prevotella, Ruminococcus, Dorea and Roseburia, among others, capable of degrading polysaccharides, oligosaccharides and sugars. Conversely, very high fat diets increase bile-resistant organisms such as Bilophila and Bacteroides. Food form, whole foods vs. ultra-processed, alters the provision of macronutrient substrate to the colon due to differing digestibility, and thereby may impact the microbiota and its metabolic activity. In addition, phytochemicals in plant-based foods have specific and possibly prebiotic effects on the microbiome. Further, food ingredients such as certain low-calorie sweeteners enhance Bifidobacterium spp. The weight of evidence to date suggests a high level of interindividual variability in the human microbiome vs. clearly defined, dietary-induced profiles. Healthful dietary patterns, emphasizing plant foods high in microbial-available carbohydrate, support favorable microbiome profiles active in saccharolytic fermentation. Future research into diet and microbiome should consider the balance of gut microbial-generated metabolites, an important link between microbiome profile and human health.

Current Developments in Digital Quantitative Volume Estimation for the Optimisation of Dietary Assessment

Obesity is a global health problem with wide-reaching economic and social implications. Nutrition surveillance systems are essential to understanding and addressing poor dietary practices. However, diets are incredibly diverse across populations and an accurate diagnosis of individualized nutritional issues is challenging. Current tools used in dietary assessment are cumbersome for users, and are only able to provide approximations of dietary information. Given the need for technological innovation, this paper reviews various novel digital methods for food volume estimation and explores the potential for adopting such technology in the Southeast Asian context. We discuss the current approaches to dietary assessment, as well as the potential opportunities that digital health can offer to the field. Recent advances in optics, computer vision and deep learning show promise in advancing the field of quantitative dietary assessment. The ease of access to the internet and the availability of smartphones with integrated cameras have expanded the toolsets available, and there is potential for automated food volume estimation to be developed and integrated as part of a digital dietary assessment tool. Such a tool may enable public health institutions to be able to gather an effective nutritional insight and combat the rising rates of obesity in the region.