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Background: With the growing accessibility of the internet, dietary assessment tools, including food frequency questionnaires (FFQs), are increasingly being adapted for web platforms. A web-based FFQ was developed as a dietary assessment tool for healthy adults in Iran. Objective: This study aimed to develop an online FFQ for dietary data collection among Iranian adults and to compare its performance with the validated Iranian printed FFQ. Methods: Eligible participants were randomly assigned to complete both the printed and web-based FFQs. The type of FFQ alternated for each participant after 10 days. The agreement between the two FFQs was assessed using the Bland-Altman method and correlation analysis. Results: Of the 190 participants, final analyses were conducted on 141 individuals, including 70 females (49.6%) and 71 males (50.4%) who completed both FFQs. Agreement was high for all nutrient intakes (r >.8). Among food groups, "Whole grains" showed the highest correlation (r =.84), while "Potato" had the lowest (r =.25). There were no significant differences in the time taken to complete the questionnaires. Conclusion: The web-based FFQ demonstrated strong agreement with the validated printed FFQ, accurately reflecting nutrient and food group intakes in Iranian adults. [ABSTRACT FROM AUTHOR]

Background: Diet is an important modifiable lifestyle factor for human health, and plant-rich dietary patterns are associated with lower risk of non-communicable diseases in numerous studies. However, objective assessment of plant-rich dietary exposure in nutritional epidemiology remains challenging. Objectives: This study aimed to develop and evaluate metabolic signatures of the most widely used plant-rich dietary patterns using a targeted metabolomics method comprising 108 plant food metabolites. Methods: A total of 218 healthy participants were included, aged 51.5 ± 17.7 years, with 24 h urine samples measured using ultra-high-performance liquid chromatography–mass spectrometry. The validation dataset employed three sample types to test the robustness of the signature, including 24 h urine (n = 88), plasma (n = 195), and spot urine (n = 198). Adherence to the plant-rich diet was assessed using a priori plant-rich dietary patterns calculated using Food Frequency Questionnaires. A combination of metabolites evaluating the adherence to a specific diet was identified as metabolic signature. We applied linear regression analysis to select the metabolites significantly associated with dietary patterns (adjusting energy intake), and ridge regression to estimate penalized weights of each candidate metabolite. The correlation between metabolic signature and the dietary pattern was assessed by Spearman analysis (FDR < 0.05). Results: The metabolic signatures consisting of 42, 22, 35, 15, 33, and 33 predictive metabolites across different subclasses were found to be associated with adherence to Amended Mediterranean Score (A-MED), Original MED (O-MED), Dietary Approaches to Stop Hypertension (DASH), Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND), healthy Plant-based Diet Index (hPDI) and unhealthy PDI (uDPI), respectively. The overlapping and distinct predictive metabolites across six dietary patterns predominantly consisted of phenolic acids (n = 38), including 14 cinnamic acids, 14 hydroxybenzoic acids, seven phenylacetic acids, and three hippuric acids. Six metabolites were included in all signatures, including two lignans: enterolactone-glucuronide, enterolactone-sulfate, and four phenolic acids: cinnamic acid, cinnamic acid-4’-sulfate, 2’-hydroxycinnamic acid, and 4-methoxybenzoic acid-3-sulfate. The established signatures were robustly correlated with dietary patterns in the validation datasets (r = 0.13–0.40, FDR < 0.05). Conclusions: We developed and evaluated a set of metabolic signatures that reflected the adherence to plant-rich dietary patterns, suggesting the potential of these signatures to serve as an objective assessment of free-living eating habits. [ABSTRACT FROM AUTHOR]

Objectives: Food insecurity among college students, combined with limited nutrition knowledge and barriers to healthy eating, significantly impacts diet quality and fruit and vegetable intake. Efforts to address these issues are further complicated by the challenges of accurately and efficiently collecting dietary data in research settings. This study aimed to explore the relationship between nutrition knowledge and fruit/vegetable intake using skin, plasma, and dietary carotenoid levels as biomarkers. Methods: Undergraduate and graduate students aged 18 years and older (n = 166) from a California public university were recruited. The sample was predominately female (n = 133, 80%), with 30 males (18%) and three individuals (2%) identifying as non-binary. Food security was assessed using the USDA's 10-item Adult Food Security Survey Module and nutrition knowledge through a validated questionnaire. Biological data included blood samples and skin carotenoid measurements (Veggie Meter®). Dietary quality (HEI-2015) and carotenoid intake were assessed through Diet ID™, a photo-based assessment tool. Results: The mean nutrition knowledge scores were 36.55 ± 8.83 out of 58 points, and the mean skin carotenoid score was 307.07 ± 110.22. Higher knowledge scores were associated with increased plasma carotenoids, HEI-score, and Diet ID™ total carotenoids. Food security classification did not significantly impact nutrition knowledge but did influence HEI scores and skin carotenoid levels, with very low food security linked to poorer diet quality and lower carotenoid levels. Conclusions: Nutrition knowledge may serve as a significant predictor of fruit and vegetable intake in university students. Despite this correlation, the impact of overall diet quality is potentially hindered by an individual's food security status. Therefore, while knowledge is critical, addressing food insecurity is essential for enhancing diet quality among college students. [ABSTRACT FROM AUTHOR]

Neurogenic bowel dysfunction (NBD) occurs in up to 95% of individuals with spinal cord injury (SCI) and negatively impacts the quality of life. Although diet is an important component in the management of NBD, the relationship between diet quality and NBD is understudied in the SCI population. To assess the diet quality of individuals with chronic SCI and explore possible relationships between diet quality, especially fiber, and symptoms of NBD, and to evaluate whether individuals with SCI themselves recognize relationships between dietary intake and NBD symptoms. Individuals with chronic SCI, recruited via their rehabilitation center, completed web-based questionnaires and 24-hour dietary recalls regarding the quality and intake of their diet and the severity of NBD. Ten individuals participated in interviews to explore their views on potential relationships between their diet and NBD. Twenty-eight participants were recruited, of which ten were interviewed. All participants had symptoms of NBD of varying degrees and a low diet quality, but there was no difference between the NBD groups. The more severe NBD group had a lower intake of vegetables and a higher intake of salt. Almost half of the participants interviewed did not report experiencing an association between dietary intake and their NBD. A low diet quality was observed among individuals with chronic SCI, irrespective of their NBD symptoms. Many participants were unaware of a potential relationship between their diet and NBD. The sample size is insufficient to draw definitive conclusions; however, a potential hypothesis is that those with more severe NBD may consume not enough vegetables and too much salt. Further longitudinal prospective research is required to enhance nutritional guidelines for individuals with SCI and NBD. [ABSTRACT FROM AUTHOR]

Background: Artificial Intelligence (AI) technologies are now essential as the agenda of nutrition research expands its scope to look at the intricate connection between food and health in both an individual and a community context. AI also helps in tracing and offering solutions in dietary assessment, personalized and clinical nutrition, as well as disease prediction and management, such as cardiovascular diseases, diabetes, cancer, and obesity. This review aims to investigate and assess the different applications and roles of AI in nutrition and research and understand its potential future impact. Methods: We used PubMed, Scopus, Web of Science, Google Scholar, and EBSCO databases for our search. Results: Our findings indicate that AI is reshaping the field of nutrition in ways that were previously unimaginable. By enhancing how we assess diets, customize nutrition plans, and manage complex health conditions, AI has become an essential tool. Technologies like machine learning models, wearable devices, and chatbot applications are revolutionizing the accuracy of dietary tracking, making it easier than ever to provide tailored solutions for individuals and communities. These innovations are proving invaluable in combating diet-related illnesses and encouraging healthier eating habits. One breakthrough has been in dietary assessment, where AI has significantly reduced errors that are common in traditional methods. Tools that use visual recognition, deep learning, and mobile applications have made it possible to analyze the nutrient content of meals with incredible precision. Conclusions: Moving forward, collaboration between tech developers, healthcare professionals, policymakers, and researchers will be essential. By focusing on high-quality data, addressing ethical challenges, and keeping user needs at the forefront, AI can truly revolutionize nutrition science. The potential is enormous. AI is set to make healthcare not only more effective and personalized but also more equitable and accessible for everyone. [ABSTRACT FROM AUTHOR]

Context: Adolescent girls suffer the brunt of malnutrition due to increased nutritional needs to facilitate rapid growth spurt including menstruation and increased physical activity. This vulnerable group has low social power and is subjected to peer and social pressures related to body image and weight. All these factors along with the sociocultural milieu may lead to a spectrum of nutritional problems in them. Aims: To determine factors associated with malnourishment among adolescent females of age 15–19 years in an urban slum of Raipur City. Settings and Design: The study setting was the urban field practice area of the institute in Raipur. The study was an analytical cross-sectional study done from January 2022 to June 2023 among 401 adolescent girls of age 15–19 years. Methods and Material: The sampling was done using the consecutive sampling method. The study tools used were a semi-structured questionnaire on sociodemographic variables and details of the respondents, anthropometric measurements, dietary assessment using the 24-hour food recall method, and food consumption patterns using a food frequency questionnaire. Statistical Analysis Used: The Chi-square test of significance was applied to find the association between malnourishment with the input variables. For calculating the strength of the association, the odds ratio was estimated for those variables with P value < 0.2 in the Chi-square test, and later the odds ratio was adjusted for confounding with the same variables, using multivariable logistic regression. Results: According to BMI-for-age Z scores, 2% were severely thin (< −3 SD), 9.7% were thin (−3 to − 2 SD), 5% were overweight (1 to 2 SD), and 1.5% were obese (>2SD). While measuring the height-for-age Z scores, 5.5% had severe stunting and 21.9% had moderate stunting. Those respondents with educational status of high school or below [AOR 3.5 (1.8–6.8), P < 0.001] and those who did not consume a non-vegetarian diet [AOR 2.1 (1.1–4.1), P = 0.02] had significantly higher adjusted odds of being undernourished (severely thin or thin) as compared to those with educational status above high school and those who consumed a mixed diet, respectively. The respondents who are currently not going to school/college had significantly higher adjusted odds [AOR 2.2 (1.2–3.8), P = 0.007] of being stunted when compared to those who are attending school/college. Conclusions: The significant levels of malnutrition observed in this study among late adolescent girls aged 15–19 years—11.7% undernourishment, 6.5% overnourishment, and 27.4% stunting—highlight the concerning vulnerability of this population. The higher prevalence of stunting throws light onto the chronicity of malnutrition. As seen from the significant associations, proper education, and a mixed diet will help nurture a healthy female adolescent population.

Background: An accurate assessment of food intake is necessary to monitor nutritional status. However, differences in cultures and dietary habits between communities make it necessary to create culturally specific tools to evaluate food intake. This study aimed to develop and validate a short food frequency questionnaire (SH-FFQ) in Iranian adults. Methods: This perspective longitudinal study was conducted during four months. A total of 135 healthy adults over 18 years (both of sex) were included. The 24-hour dietary recalls (24-HDRs) (three times per month: A total of 12 numbers) were collected as reference for validation of SH-FFQ. Participants completed two SH-FFQ, once at the end of the fourth month for validity, and the second one week after the first administration for reliability assessing. Results: Reliability analysis showed that the mean difference between the two SH-FFQs was not statistically significant (P > 0.05). None of the correlation coefficients (rs) were less than 0.4. There was a substantial or perfect correlation (r > 0.6) in 85.1% and a moderate correlation (r = 0.4-0.6) in 14.9% of food items. For validity assessment, the average values of two SH-FFQ1 and SH-FFQ2 (SH-FFQ) were compared with the average values of 24-HDRs. All of the intraclass correlation coefficients (ICCs) of between SH-FFQ and 24-HDRs were equal to or greater than 0.4 (except one item). Moderate correlation (ICC = 0.4-0.6) and substantial or perfect correlation (ICC > 0.6) were observed in 38.3% and 59.6% of food items, respectively. Conclusions: The current study showed that the developed SH-FFQ is reliable and valid in Iranian adults. This developed SH-FFQ can be used in nutritional assessments. [ABSTRACT FROM AUTHOR]

Dietary intake assessment is often complicated by intrinsic bias. This study investigated whether food purchase data could constitute a valid indication of dietary intake, by evaluating the extent to which diet quality as measured by supermarket food purchases is correlated with diet quality as measured by reported dietary intake. We used data from the Supreme Nudge cluster-randomised controlled supermarket trial (n 227). Data were collected at baseline from supermarket purchases (loyalty cards) and a dietary questionnaire (short forty-item FFQ) to compute two scores reflecting diet quality from purchasing data (purchased diet quality) and FFQ (consumed diet quality). Both scores constituted thirteen food groups and could theoretically range from 0 (low diet quality) to 130 (high diet quality). The relationship between purchased diet quality and consumed diet quality was assessed using correlation coefficients and the Bland–Altman limits-of-agreement method. Multiple linear regression was fitted between purchased diet quality and consumed diet quality, adjusted for age, sex, waist circumference, educational level and household size. Consumed and purchased diet qualities were modestly positively correlated (Pearson's ρ = 0·31, 95 % CI 0·18, 0·42). A positive association from linear regression was found after confounding adjustments (βbaseline = 0·22, 95 % CI 0·10, 0·34). The purchased diet quality was systematically lower than the consumed diet quality. This study found that diet quality as measured by supermarket purchases provided a reasonable indication of diet quality as reported by short-FFQ, albeit modest. [ABSTRACT FROM AUTHOR]

Recent advances in machine learning technologies and omics methodologies are revolutionizing dietary assessment by integrating phenotypical, clinical, and metabolic biomarkers, which are crucial for personalized precision nutrition. This investigation aims to evaluate the feasibility and efficacy of artificial intelligence tools, particularly machine learning (ML) methods, in analyzing these biomarkers to characterize food and nutrient intake and to predict dietary patterns. Methods: We analyzed data from 138 subjects from the European Dietary Deal project through comprehensive examinations, lifestyle questionnaires, and fasting blood samples. Clustering was based on 72 h dietary recall, considering sex, age, and BMI. Exploratory factor analysis (EFA) assigned nomenclature to clusters based on food consumption patterns and nutritional indices from food frequency questionnaires. Elastic net regression identified biomarkers linked to these patterns, helping construct algorithms. Results: Clustering and EFA identified two dietary patterns linked to biochemical markers, distinguishing pro-Mediterranean (pro-MP) and pro-Western (pro-WP) patterns. Analysis revealed differences between pro-MP and pro-WP clusters, such as vegetables, pulses, cereals, drinks, meats, dairy, fish, and sweets. Markers related to lipid metabolism, liver function, blood coagulation, and metabolic factors were pivotal in discriminating clusters. Three computational algorithms were created to predict the probabilities of being classified into the pro-WP pattern. The first is the main algorithm, followed by a supervised algorithm, which is a simplified version of the main model that focuses on clinically feasible biochemical parameters and practical scientific criteria, demonstrating good predictive capabilities (ROC curve = 0.91, precision–recall curve = 0.80). Lastly, a reduced biochemical-based algorithm is presented, derived from the supervised algorithm. Conclusions: This study highlights the potential of biochemical markers in predicting nutritional patterns and the development of algorithms for classifying dietary clusters, advancing dietary intake assessment technologies. [ABSTRACT FROM AUTHOR]

Background: Dietary habits are crucial for preventing many diseases, particularly in children and adolescents. Accurate assessment of dietary intake is essential for understanding the relationship between diet and health in these age groups. Objective: This study aimed to evaluate the reproducibility and validity of a Spanish version of the European Prospective Investigation into Cancer and Nutrition (EPIC) Food Frequency Questionnaire (FFQ) in 150 Spanish children and adolescents aged 10 to 17 using the average of 9 days of 24-h dietary recall (24H-DR) as a reference. Methods: Intraclass correlation coefficients (ICCs) were calculated to asses reproducibility and Spearman/Pearson correlation coefficients were calculated to assess validity and reproducibility. Results: The average ICCs were 0.41 for crude nutrients, 0.31 for food groups, 0.31 for energy-adjusted nutrients, and 0.4 for energy-adjusted food groups. Spearman/Pearson correlation coefficients averaged 0.39 and 0.41 for crude and energy-adjusted nutrients, respectively, and 0.51 and 0.47 for corresponding food groups. Regarding validity, the average correlation coefficient for crude, energy-adjusted, and de-attenuated nutrients was 0.32, 0.50, and 0.50, respectively. The highest crude coefficient was 0.50 for vitamin C and fiber, while the highest energy-adjusted coefficient was 0.76 for protein and carbohydrates. The highest de-attenuated coefficient was 0.72 for vitamin B6. Conclusions: Overall, these results suggest that the EPIC FFQ is a valid and reliable instrument for assessing dietary intake in Spanish children and adolescents. [ABSTRACT FROM AUTHOR]

Objectives: The correlation between denture usage and nutrition is a subject of ongoing debate, with numerous authors attempting to investigate it using food frequency questionnaires (FFQ). This systematic review aimed to assess the quality of research reporting on the use of FFQ as a tool for evaluating nutrient intake in individuals who wear dentures. Methods: Studies were sourced through online databases, encompassing publications from 1990 to 2024. Four studies employing FFQ to evaluate the nutritional status of denture wearers and meeting the specified inclusion-exclusion criteria were incorporated into this systematic review. Quality assessment of the included studies was independently conducted by two reviewers, utilizing the summary score provided by Dennis et al. Results: All the studies included in the review utilized semi-quantitative FFQ, with most adopting the widely accepted and validated FFQ developed by Willet and Block. The majority of these studies received high-quality scores as per the assessment criteria established by Dennis et al. However, one study under review received a low score due to several shortcomings. This included failure to report the FFQ items utilized in the study, lack of repetition in quality checks, absence of nutrient database utilization for FFQ coding, inadequate portion size estimation, and insufficient information regarding survey completion time. Conclusion: The articles included in the review, along with their quality assessments, provided insights into various aspects of FFQ design that enhance validity. These include the comprehensiveness of items covered, frequency of intake reporting, accuracy of portion size calculations, choice of reference technique, and method of delivery. It was observed that the majority of studies favored the interview administration of FFQ, which was deemed to be more reliable and acceptable during quality analysis. [ABSTRACT FROM AUTHOR]

Background: The increase in serving sizes of energy-dense nutrient-poor discretionary foods over time, with attractively presented large servings and package sizes, has led to portion distortion and a new 'normal' for serving sizes. Little data exists on the variations of portion size norms of discretionary foods across settings. This study aimed to examine the differences in the range of normal portion sizes of commonly consumed foods between home and out-of-home settings (coffee shops, restaurants). Methods: A repeated cross-sectional design was used, with nine selected discretionary foods and beverages included in a validated online image-series questionnaire. Participants completed the questionnaire at two time points to report their normal portion sizes in home and out-of-home settings. Quantile regression models were used to examine differences in the range of normal portion sizes (17th to 83rd percentile, representing the majority of the study population) between settings. Results: A final sample of 295 participants was included in the analysis (51% females, mean age 40 ± 14 years). The ranges of normal portion sizes did not differ by settings for all test foods except for sugar-sweetened beverages (SSB) tested in both containers and glassware. SSB showed smaller normal portion sizes at home compared to fast food restaurants (in a bottle/can and in a glass/cup; p < 0.001). Conclusions: These findings suggest that the portion size norms of many discretionary foods are mostly consistent in home and out-of-home settings. As the typical serving sizes available to consumers in the out-of-home settings are large, it is essential to establish practical serving size guidelines directed at the food industry to increase the availability of smaller size options and empower consumers towards better portion control. [ABSTRACT FROM AUTHOR]

ABSTRACT: Context: Adolescent girls suffer the brunt of malnutrition due to increased nutritional needs to facilitate rapid growth spurt including menstruation and increased physical activity. This vulnerable group has low social power and is subjected to peer and social pressures related to body image and weight. All these factors along with the sociocultural milieu may lead to a spectrum of nutritional problems in them. Aims: To determine factors associated with malnourishment among adolescent females of age 15–19 years in an urban slum of Raipur City. Settings and Design: The study setting was the urban field practice area of the institute in Raipur. The study was an analytical cross-sectional study done from January 2022 to June 2023 among 401 adolescent girls of age 15–19 years. Methods and Material: The sampling was done using the consecutive sampling method. The study tools used were a semi-structured questionnaire on sociodemographic variables and details of the respondents, anthropometric measurements, dietary assessment using the 24-hour food recall method, and food consumption patterns using a food frequency questionnaire. Statistical Analysis Used: The Chi-square test of significance was applied to find the association between malnourishment with the input variables. For calculating the strength of the association, the odds ratio was estimated for those variables with P value < 0.2 in the Chi-square test, and later the odds ratio was adjusted for confounding with the same variables, using multivariable logistic regression. Results: According to BMI-for-age Z scores, 2% were severely thin (< −3 SD), 9.7% were thin (−3 to − 2 SD), 5% were overweight (1 to 2 SD), and 1.5% were obese (>2SD). While measuring the height-for-age Z scores, 5.5% had severe stunting and 21.9% had moderate stunting. Those respondents with educational status of high school or below [AOR 3.5 (1.8–6.8), P < 0.001] and those who did not consume a non-vegetarian diet [AOR 2.1 (1.1–4.1), P = 0.02] had significantly higher adjusted odds of being undernourished (severely thin or thin) as compared to those with educational status above high school and those who consumed a mixed diet, respectively. The respondents who are currently not going to school/college had significantly higher adjusted odds [AOR 2.2 (1.2–3.8), P = 0.007] of being stunted when compared to those who are attending school/college. Conclusions: The significant levels of malnutrition observed in this study among late adolescent girls aged 15–19 years—11.7% undernourishment, 6.5% overnourishment, and 27.4% stunting—highlight the concerning vulnerability of this population. The higher prevalence of stunting throws light onto the chronicity of malnutrition. As seen from the significant associations, proper education, and a mixed diet will help nurture a healthy female adolescent population. [ABSTRACT FROM AUTHOR]

Purpose: Whether youth who follow plant-based diets in Nordic countries meet their dietary needs for micronutrients remains unclear. This study aims to evaluate micronutrient intake and status in Norwegian youth following vegan, lacto-ovo-vegetarian, pescatarian, flexitarian and omnivore diets. Methods: Cross-sectional design, with healthy 16-to-24-year-olds (n = 165). Participants were asked to complete a questionnaire and four 24-hour dietary recalls. Dried blood spots (DBS) and spot-urine samples were collected for analysis of methyl malonic acid (MMA) (n = 65), haemoglobin (Hb) (n = 164) and urinary iodine concentration (UIC) (n = 163). Results: Vegans reported highest habitual supplement usage of multivitamin (58%), B12 (90%) and macroalgae consumption (32%), while flexitarians reported highest habitual usage of omega-3 supplements (56%). For daily supplement usage, vegans reported highest use of multivitamins (42%), B12 (79%), iodine (37%) and iron (63%). Increased risk of inadequate intake (energy-adjusted) were found for vitamin D (60% within lacto-ovo-vegetarians), selenium (70% within lacto-ovo-vegetarians, 65% within omnivores), and iodine (63% within vegans). Median MMA levels suggest low risk of insufficient B12 status across all groups (MMA 0.04‒0.37µmol/l) and 2% had MMA levels indicating possible B12 deficiency and 8% had elevated levels. Median Hb levels indicated low risk of anemia across all groups (≥ 12.0 females, ≥ 13.0 g/dl males), though 7% had Hb values indicating risk of mild anemia and 4% risk of moderate anemia. The median UIC indicates mild iodine deficiency in all groups (UIC < 100 µg/l), except vegans, who were moderately iodine deficient (UIC < 50 µg/l). Conclusions: Our study indicated that the participating youth had low risk of inadequate intake of most micronutrients, partly due to high supplement usage. However, for iodine, vitamin D, and selenium higher risk of inadequate intake was found. UIC corroborated the low iodine intake among vegans. Thus, we suggest iodine status of youth in Norway should be monitored, especially among young fertile women who omits dietary iodine sources, until a mandatory iodine fortification program is implemented. Furthermore, we suggest that food education on how to secure sufficient nutrients from food in general should be provided to the Norwegian youth population, especially how to secure adequate intake of vitamin D, selenium and iodine. [ABSTRACT FROM AUTHOR]

Photo-based dietary assessment is becoming more feasible as artificial intelligence methods improve. However, advancement of these methods for dietary assessment in research settings has been hindered by the lack of an appropriate dataset against which to benchmark algorithm performance. We conducted the Surveying Nutrient Assessment with Photographs of Meals (SNAPMe) study (ClinicalTrials ID: NCT05008653) to pair meal photographs with traditional food records. Participants were recruited nationally, and 110 enrollment meetings were completed via web-based video conferencing. Participants uploaded and annotated their meal photos using a mobile phone app called Bitesnap and completed food records using the Automated Self-Administered 24-h Dietary Assessment Tool (ASA24®) version 2020. Participants included photos before and after eating non-packaged and multi-serving packaged meals, as well as photos of the front and ingredient labels for single-serving packaged foods. The SNAPMe Database (DB) contains 3311 unique food photos linked with 275 ASA24 food records from 95 participants who photographed all foods consumed and recorded food records in parallel for up to 3 study days each. The use of the SNAPMe DB to evaluate ingredient prediction demonstrated that the publicly available algorithms FB Inverse Cooking and Im2Recipe performed poorly, especially for single-ingredient foods and beverages. Correlations between nutrient estimates common to the Bitesnap and ASA24 dietary assessment tools indicated a range in predictive capacity across nutrients (cholesterol, adjusted R2 = 0.85, p < 0.0001; food folate, adjusted R2 = 0.21, p < 0.05). SNAPMe DB is a publicly available benchmark for photo-based dietary assessment in nutrition research. Its demonstrated utility suggested areas of needed improvement, especially the prediction of single-ingredient foods and beverages.

Diet is considered a key research priority for juvenile idiopathic arthritis (JIA), garnering considerable interest from affected families. Despite this, research studies focusing on dietary interventions remain scarce. The specific carbohydrate diet (SCD) has shown potential, however, its nutritional consequences and risks are not well understood. This study aims to describe and evaluate food and nutrient intakes in children with JIA adhering to the SCD and contextualize the results relative to recommendations and intakes in the general population. In a secondary analysis, food and nutrient intakes from three-day dietary records of ten children, following a four-week SCD intervention, were evaluated against the Nordic Nutrition Recommendations 2023 and Riksmaten Adolescents data (RMA) (n = 1282). All children following the SCD met the recommended minimum intake of fruit and vegetables of 500g/day, a stark contrast to the 6% in RMA. Median dietary fibre intake for the SCD was 26g/d, (IQR 21-33), compared to 16g/d (IQR 12-22) in RMA. Elevated saturated fatty acid (SFA) intake was observed in both groups, with the SCD group also consuming high amounts of red meat. Calcium was the sole nutrient for which the standard diet surpassed the SCD, as 9 out of 10 participants had inadequate intake. While children on the SCD showed a lower likelihood of nutrient inadequacy compared to the general population, inadequate calcium intake and elevated SFA and red meat consumption are concerning given known comorbidities in JIA. These results highlight the importance of disease-specific dietary guidance to ensure optimal support for patients and parents.

IntroductionAccurate measurement of dietary intake without interfering in natural eating habits is a long-standing problem in nutritional epidemiology. We explored the applicability of hyperspectral imaging and machine learning for dietary assessment of home-prepared meals, by building a proof-of-concept, which automatically detects food ingredients inside closed sandwiches.MethodsIndividual spectra were selected from 24 hyperspectral images of assembled closed sandwiches, measured in a spectral range of 1116.14 nm to 1670.62 nm over 108 bands, pre-processed with Standard Normal Variate filtering, derivatives, and subsampling, and fed into multiple algorithms, among which PLS-DA, multiple classifiers, and a simple neural network.ResultsThe resulting best performing models had an accuracy score of ~80% for predicting type of bread, ~60% for butter, and ~ 28% for filling type. We see that the main struggle in predicting the fillings lies with the spreadable fillings, meaning the model may be focusing on structural aspects and not nutritional composition.DiscussionFurther analysis on non-homogeneous mixed food items, using computer vision techniques, will contribute toward a generalizable system. While there are still significant technical challenges to overcome before such a system can be routinely implemented in studies of free-living subjects, we believe it holds promise as a future tool for nutrition research and population intake monitoring.

PurposeThe Healthy Eating Index-Canada 2015 (HEI-C 2015), Diet Quality Index-International (DQI-I), and Healthy Eating Food Index 2019 (HEFI-2019) are commonly used to summarize the quality of Canadian diets. This paper sought to compare these three diet quality indices with respect to their ability to capture diets of different quality in Canadian children and to discriminate between population subgroups.MethodsData were collected in school-based surveys from grade 4–6 students (9–12 years old) in western Canada through 24-h dietary recall in 2016 (n = 336), 2018 (n = 454), and 2020/2021 (n = 909). Diet quality was assessed using HEI-C 2015, DQI-I and HEFI-2019. Agreement between the three indices was assessed using weighted Cohen’s kappa. Univariate and multivariable linear regression models assessed diet quality according to student’s sex, grade level, school material/social deprivation, and geographic region.ResultsHEFI-2019 scores had the widest range, while DQI-I had the smallest. Agreement was 0.55 between HEI-C 2015 and DQI-I, 0.38 between HEI-C 2015 and HEFI-2019, and 0.29 between DQI-I and HEFI-2019. Boys and students from materially deprived areas reported diets of lower quality, irrespective of the index. There were no differences in diet quality across grade levels and geographic region. Energy consumption was associated positively with DQI-I and negatively HEFI-2019 scores.ConclusionThe three indices demonstrated fair to moderate agreement and varying ability to discriminate diet quality between different population subgroups of Canadian children. This study shows that the choice of a diet quality index affects the interpretation of results and practical considerations, yielding different conclusions with respect to the determinants of children’s diet quality. Seeking consensus on which diet quality index to use for research, policy and/or practice would help support dietary research and policy development, and promote dietary guidelines implementation.

Objective: A study was undertaken to explore the portion size estimation accuracy of bean bags as low-cost volumetric portion size estimation aids for amorphous foods.Designs: Three observational, cross-sectional and three experimental/quasi-experimental developmental evaluation sub-studies were carried out.Settings: Observational, cross-sectional: one retirement village and four schools. Experimental/quasi-experimental: one South African university.Participants: Observational, cross-sectional: elderly persons, adult women (school educators), schoolchildren. Experimental/quasi-experimental: university students. In total N = 541; > 3 800 observations.Variables measured: Using a standardised set of bean bags (test object; volume range: 60–625 ml), volumes of different amorphous foods (reference objects: actual foods or representations) in varying portion sizes had to be estimated. Accuracy (outcome measure) was perfect if volumes of test and reference object were identical. Acceptable estimation accuracy allowed for misestimation by one bean bag size. Test–retest reproducibility was also assessed.Analysis: Descriptive statistics (proportions perfect and acceptable accuracy).Results: Across the sub-studies, perfect accuracy ranged from 22–65% depending on participants, reference food and portion size. Irrespective thereof, acceptable accuracy was noted in > 70% of observations. Reproducibility varied (range: 28–67% agreement).Conclusions and implications: Perfect portion size estimation of amorphous foods remains challenging. When misestimation by 60–125 ml still serves the purpose of a dietary assessment, bean bags show promise for cost-effective food volume quantification, especially on group level in resource-limited settings.

Background: Vitamin B12 deficiency is widely prevalent in all age groups which is of major concern. However, there is no valid Food Frequency Questionnaire (FFQ) for dietary vitamin B12 estimation. Hence, we aimed to develop and validate an FFQ for the estimation of dietary intake of Vitamin B12. Materials and Methods: Commonly consumed B12-rich food items were selected from literature and filtered using a market survey. For concordant and discriminant validation, B12 and homocysteine levels were estimated. To establish convergent validity, the Cobalamin Intake in North Indians by Food Frequency Questionnaire (COIN-FFQ) and 72-hour dietary recall (72HrDR) were both administered to the same subjects. The COIN-FFQ was readministered after initial administration for test–retest reliability. Internal consistency of the FFQ was then tested using Cronbach’s alpha. Results: We enrolled 115 adults with a mean age and weight of 31.9 ± 8.7 years and 66.0 ± 11.8 kg, respectively. In total, 19.1% were vegetarian. The dietary B12 using COIN-FFQ (n = 60; mean = 4.3 ± 1.8 µg/d) was significantly correlated (r = 0.255; P = 0.049) with serum levels (mean = 120.1 ± 62.6 pmol/L) establishing concordant validity. A significant difference was noted between the dietary, serum B12, and homocysteine levels of vegetarians versus nonvegetarians establishing discriminant validity (mean diff 1.4 (0.5–2.4), P = 0.004; Z-statistic −2.182, P value 0.029, and Z-statistic −2.438; P value 0.015), respectively. FFQ was strongly correlated with 72HrDR and test–retest FFQ (n = 27; r = 0.814, P < 0.001 and r = 0.869, P < 0.001, respectively) establishing convergent validity and test–retest reliability. The internal consistency with Cronbach’s alpha was in the acceptable range, 0.631 (n = 115). Conclusion: The newly developed COIN-FFQ is valid and reliable in estimating dietary B12 intake.

Abstract Background Dietary assessment methods have limitations in capturing real-time eating behaviour accurately. Equipped with automated dietary-data-collection capabilities, the “intelligent ordering system” (IOS) has potential applicability in obtaining long-term consecutive, relatively detailed on-campus dietary records among university students with little resource consumption. We investigated (1) the relative validity of IOS-derived nutrient/food intakes compared to those from the 7-day food diary (7DFD); (2) whether including a supplemental food frequency questionnaire (SFFQ) improves IOS accuracy; and (3) sex differences in IOS dietary intake estimation. Methods Medical students (n = 221; age = 22.2 ± 2.4 years; 38.5% male and 61.5% female) completed the 7DFD and SFFQ. During the consecutive 7-day survey period, students weighed and photographed each meal before and after consumption. Then, students reviewed their 3-month diet and completed the SFFQ, which includes eight underprovided school-canteen food items (e.g., dairy, fruits, nuts). Meanwhile, 9385 IOS dietary data entries were collected. We used Spearman coefficients and linear regression models to estimate the associations among the different dietary intake assessment methods. Individual- and group-level agreement was assessed using the Wilcoxon signed-rank test, cross-classification, and Bland‒Altman analysis. Results IOS mean daily energy, protein, fat, and carbohydrate intake estimations were significantly lower (-15-20%) than those of the 7DFD. The correlation coefficients varied from 0.52 (for added sugar) to 0.88 (for soybeans and nuts), with fruits (0.37) and dairy products (0.29) showing weaker correlations. Sixty-two (milk and dairy products) to 97% (soybeans and nuts) of participants were classified into the same or adjacent dietary intake distribution quartile using both methods. The energy and macronutrient intake differences between the IOS + SFFQ and 7DFD groups decreased substantially. The separate fruit intake measurements from each assessment method did not significantly differ from each other (p > 0.05). IOS and IOS + SFFQ regression models generally yielded higher R2 values for males than for females. Conclusion Despite estimation differences, the IOS can be reliable for medical student dietary habit assessment. The SFFQ is useful for measuring consumption of foods that are typically unavailable in school cafeterias, improving the overall dietary evaluation accuracy. The IOS assessment was more accurate for males than for females.

Objective: We studied the presence of psychological stress in patients with type 2 diabetes (T2D) and if could be attributed to the consumption of a pro-inflammatory diet. We evaluated the inflammatory potential of the habitual Mexican diet, addressed by tools with an approach to collecting information on e-Health. Methods: In this cross-sectional analytic study of 238 Mexican adults with T2D, the profile of the inflammatory diet was obtained by the Dietary Inflammatory Index (DII), and the presence of psychological stress by the Diabetes Distress Scale-17 (DSS) was assessed. Multivariable logistic regression analysis was performed to estimate the association between diabetes stress and DII score. Sensitivity analysis was performed by Energy–Density Dietary Inflammatory Index (E-DII). Results: We demonstrated that there is an association between a profile of stress and high-inflammatory values of the DII score after adjustment for potential confounders (OR 2.40, 95% CI 1.2, 4.6). Conclusion: Using e-Health through web-based tools to collect information showed benefits of the application as a method of dietary assessment. We provide evidence showing that better values of the DII score and physical activity may play a protective role against the presence of psychological stress; DII and E-DII scores qualify and label habitual diet into pro and anti-inflammatory and are associated with psychological stress in T2D. [ABSTRACT FROM AUTHOR]

Objective: A study was undertaken to explore the portion size estimation accuracy of bean bags as low-cost volumetric portion size estimation aids for amorphous foods. Designs: Three observational, cross-sectional and three experimental/quasi-experimental developmental evaluation sub-studies were carried out. Settings: Observational, cross-sectional: one retirement village and four schools. Experimental/quasi-experimental: one South African university. Participants: Observational, cross-sectional: elderly persons, adult women (school educators), schoolchildren. Experimental/quasi-experimental: university students. In total N = 541; > 3 800 observations. Variables measured: Using a standardised set of bean bags (test object; volume range: 60–625 ml), volumes of different amorphous foods (reference objects: actual foods or representations) in varying portion sizes had to be estimated. Accuracy (outcome measure) was perfect if volumes of test and reference object were identical. Acceptable estimation accuracy allowed for misestimation by one bean bag size. Test–retest reproducibility was also assessed. Analysis: Descriptive statistics (proportions perfect and acceptable accuracy). Results: Across the sub-studies, perfect accuracy ranged from 22–65% depending on participants, reference food and portion size. Irrespective thereof, acceptable accuracy was noted in > 70% of observations. Reproducibility varied (range: 28–67% agreement). Conclusions and implications: Perfect portion size estimation of amorphous foods remains challenging. When misestimation by 60–125 ml still serves the purpose of a dietary assessment, bean bags show promise for cost-effective food volume quantification, especially on group level in resource-limited settings. [ABSTRACT FROM AUTHOR]

Purpose: of review Accurate assessment of dietary intake, especially energy and protein intake, is crucial for optimizing nutritional care and outcomes in patients with cancer. Validation of dietary assessment methods is necessary to ensure accuracy, but the validity of these methods in patients with cancer, and especially in those with cancer cachexia, is uncertain. Validating nutritional intake is complex because of the variety of dietary methods, lack of a gold standard method, and diverse validation measures. Here, we review the literature on validations of dietary intake methods in patients with cancer, including those with cachexia, and highlight the gap between current validation efforts and the need for accurate dietary assessment methods in this population. Recent findings: We analyzed eight studies involving 1479 patients with cancer to evaluate the accuracy and reliability of 24-hour recalls, food records, and food frequency questionnaires in estimating energy and protein intake. We discuss validation methods, including comparison with biomarkers, indirect calorimetry, and relative validation of dietary intake methods. Summary: Few have validated dietary intake methods against objective markers in patients with cancer. While food records and 24-hour recalls show potential accuracy for energy and protein intake, this may be compromised in hypermetabolic patients. Additionally, under- and overreporting of intake may be less frequent, and the reliability of urinary nitrogen as a protein intake marker in patients with cachexia needs further investigation. Accurate dietary assessment is important for enhancing nutritional care outcomes in cachexia trials, requiring validation at multiple time points throughout the cancer trajectory. [ABSTRACT FROM AUTHOR]

Background: Vitamin B12 deficiency is widely prevalent in all age groups which is of major concern. However, there is no valid Food Frequency Questionnaire (FFQ) for dietary vitamin B12 estimation. Hence, we aimed to develop and validate an FFQ for the estimation of dietary intake of Vitamin B12. Materials and Methods: Commonly consumed B12-rich food items were selected from literature and filtered using a market survey. For concordant and discriminant validation, B12 and homocysteine levels were estimated. To establish convergent validity, the Cobalamin Intake in North Indians by Food Frequency Questionnaire (COIN-FFQ) and 72-hour dietary recall (72HrDR) were both administered to the same subjects. The COIN-FFQ was readministered after initial administration for test-retest reliability. Internal consistency of the FFQ was then tested using Cronbach's alpha. Results: We enrolled 115 adults with a mean age and weight of 31.9 ± 8.7 years and 66.0 ± 11.8 kg, respectively. In total, 19.1% were vegetarian. The dietary B12 using COIN-FFQ (n = 60; mean = 4.3 ± 1.8 µg/d) was significantly correlated (r = 0.255; P = 0.049) with serum levels (mean = 120.1 ± 62.6 pmol/L) establishing concordant validity. A significant difference was noted between the dietary, serum B12, and homocysteine levels of vegetarians versus nonvegetarians establishing discriminant validity (mean diff 1.4 (0.5-2.4), P = 0.004; Z-statistic -2.182, P value 0.029, and Z-statistic -2.438; P value 0.015), respectively. FFQ was strongly correlated with 72HrDR and test--retest FFQ (n = 27; r = 0.814, P < 0.001 and r = 0.869, P < 0.001, respectively) establishing convergent validity and test--retest reliability. The internal consistency with Cronbach's alpha was in the acceptable range, 0.631 (n = 115). Conclusion: The newly developed COIN-FFQ is valid and reliable in estimating dietary B12 intake. [ABSTRACT FROM AUTHOR]

The evidence on the impact of fruits and vegetable types on cardiovascular risk factors remains limited. Specifically, the utilisation of biomarkers to objectively measure dietary compliance and metabolic responses is emerging. This protocol and baseline characteristics of a pilot randomised controlled, crossover, dietary intervention study aimed to examine the effects of citrus fruits, cruciferous vegetables, or common fruits and vegetables on cardiovascular risk factors. A total of 39 volunteers with untreated prehypertension was recruited and consumed a standardised, provided diet with eight daily portions of citrus fruits and cruciferous vegetables, common fruits and vegetables, or a low fruit and vegetable diet (two portions/d, control diet) in a random order for 2 weeks each, separated by a wash-out week. A targeted cohort-based recruitment strategy was utilised and resulted in 74% of participants recruited by re-contacting preselected individuals from two cohort studies with a 15% average enrolment rate. Participants had an average age of 54.4 years (±6.1 years), BMI of 27.9 kg/m2, and BP of 135/81 mmHg and were mainly male (67%). The primary outcome was office blood pressure; secondary outcomes included arterial stiffness, lipid profiles, inflammation, cognitive function, and subjective mood. Biofluids, i.e., 24 h urine, stool, and blood samples, were collected for biomarker measurements with multiple metabolomic platforms and the gut microbial composition, together with traditional dietary biomarkers. [ABSTRACT FROM AUTHOR]

Background: Insights into (poly)phenol exposure represent a modifiable factor that may modulate inflammation in chronic pancreatitis (CP), yet intake is poorly characterized and methods for assessment are underdeveloped. Aims: The aims are to develop and test a method for estimating (poly)phenol intake from a 90-day food frequency questionnaire (FFQ) using the Phenol-Explorer database and determine associations with dietary patterns in CP patients versus controls via analysis of previously collected cross-sectional data. Methods: Fifty-two CP patients and 48 controls were recruited from an ambulatory clinic at a large, academic institution. To assess the feasibility of the proposed methodology for estimating dietary (poly)phenol exposure, a retrospective analysis of FFQ data was completed. Mann–Whitney U tests were used to compare (poly)phenol intake by group; Spearman correlations and multivariable-adjusted log-linear associations were used to compare (poly)phenol intakes with dietary scores within the sample. Results: Estimation of (poly)phenol intake from FFQs was feasible and produced estimates within a range of intake previously reported. Total (poly)phenol intake was significantly lower in CP vs controls (463 vs. 567mg/1000kcal; p = 0.041). In adjusted analyses, higher total (poly)phenol intake was associated with higher HEI-2015 (r = 0.34, p < 0.001), aMED (r = 0.22, p = 0.007), EDIH (r = 0.29, p < 0.001), and EDIP scores (r = 0.35, p < 0.001), representing higher overall diet quality and lower insulinemic and anti-inflammatory dietary potentials, respectively. Conclusions: Using enhanced methods to derive total (poly)phenol intake from an FFQ is feasible. Those with CP have lower total (poly)phenol intake and less favorable dietary pattern indices, thus supporting future tailored dietary intervention studies in this population. [ABSTRACT FROM AUTHOR]

For artificial intelligence (AI) to support nutrition care, high quality and accuracy of its features within smartphone applications (apps) are essential. This study evaluated popular apps' features, quality, behaviour change potential, and comparative validity of dietary assessment via manual logging and AI. The top 200 free and paid nutrition-related apps from Australia's Apple App and Google Play stores were screened (n = 800). Apps were assessed using MARS (quality) and ABACUS (behaviour change potential). Nutritional outputs from manual food logging and AI-enabled food-image recognition apps were compared with food records for Western, Asian, and Recommended diets. Among 18 apps, Noom scored highest on MARS (mean = 4.44) and ABACUS (21/21). From 16 manual food-logging apps, energy was overestimated for Western (mean: 1040 kJ) but underestimated for Asian (mean: −1520 kJ) diets. MyFitnessPal and Fastic had the highest accuracy (97% and 92%, respectively) out of seven AI-enabled food image recognition apps. Apps with more AI integration demonstrated better functionality, but automatic energy estimations from AI-enabled food image recognition were inaccurate. To enhance the integration of apps into nutrition care, collaborating with dietitians is essential for improving their credibility and comparative validity by expanding food databases. Moreover, training AI models are needed to improve AI-enabled food recognition, especially for mixed dishes and culturally diverse foods. [ABSTRACT FROM AUTHOR]

The 2020–2025 Dietary Guidelines for Americans recommend limiting intakes of saturated fat and added sugars (SF/AS) to <10% total energy. Data-driven approaches to identify sources of SF/AS are needed to meet these goals. We propose using a population-based approach to identify the leading food and beverage sources of SF/AS consumed by US adults. Foods and beverages reported as consumed were assessed from two, 24 h dietary recalls (24HRDR) from 36,378 adults aged 19 years and older from the 2005–2018 National Health and Nutrition Examination Survey. Intakes of SF/AS were aggregated across both 24HRDR to identify What We Eat in America food categories accounting for ≥90% of SF/AS, respectively, by the total population and within population subgroups. Data were weighted to estimate a nationally representative sample. Ninety-five discrete food categories accounted for ≥90% of the total SF/AS intakes for >88% of the representative sample of U.S. adults. The top sources of SF were cheese, pizza, ice cream, and eggs. The leading sources of AS were soft drinks, tea, fruit drinks, and cakes and pies. This analysis reflects a parsimonious approach to reliably identify foods and beverages that contribute to SF/AS intakes in U.S. adults. [ABSTRACT FROM AUTHOR]

Implementing dietary screening tools into clinical practice has been challenging, including in Nigeria. This study evaluated the impact of the Nigerian dietary screening tool (NiDST) on patient–clinician communication and barriers to and facilitators of implementation. A mixed methods approach was used to collect data from patients (n = 151) and clinicians (n = 20) from outpatient clinics in Nigeria. Patients completed the validated 25-item NiDST prior to outpatient consultations. Both patients and clinicians completed the Measurement Instrument for Determinants of Innovations (MIDI) questionnaire to assess implementation determinants post-consultation. Semi-structured interviews were conducted for in-depth feedback. The fidelity of implementation was 92% for NiDST-reported dietary discussion, with a mean completion time of <6 min and an accepted marginal increase in consultation time (<10 min). For clinicians, 25% reported time constraints and their additional nutritional knowledge as barriers, while facilitators of NiDST implementation were the clarity and completeness of the NiDST, clinical relevance and improved patient–clinician communication, as reported by all the clinicians. Over 96% of patients reported the NiDST as quick to complete, with 90.7% reporting self-reflection on dietary intake. This study demonstrated the NiDST's potential to enhance patient–clinician communication and highlighted major facilitators of implementation in clinical practice to improve dietary discussion in Nigeria. [ABSTRACT FROM AUTHOR]

Background: Dietary assessment methods have limitations in capturing real-time eating behaviour accurately. Equipped with automated dietary-data-collection capabilities, the "intelligent ordering system" (IOS) has potential applicability in obtaining long-term consecutive, relatively detailed on-campus dietary records among university students with little resource consumption. We investigated (1) the relative validity of IOS-derived nutrient/food intakes compared to those from the 7-day food diary (7DFD); (2) whether including a supplemental food frequency questionnaire (SFFQ) improves IOS accuracy; and (3) sex differences in IOS dietary intake estimation. Methods: Medical students (n = 221; age = 22.2 ± 2.4 years; 38.5% male and 61.5% female) completed the 7DFD and SFFQ. During the consecutive 7-day survey period, students weighed and photographed each meal before and after consumption. Then, students reviewed their 3-month diet and completed the SFFQ, which includes eight underprovided school-canteen food items (e.g., dairy, fruits, nuts). Meanwhile, 9385 IOS dietary data entries were collected. We used Spearman coefficients and linear regression models to estimate the associations among the different dietary intake assessment methods. Individual- and group-level agreement was assessed using the Wilcoxon signed-rank test, cross-classification, and Bland‒Altman analysis. Results: IOS mean daily energy, protein, fat, and carbohydrate intake estimations were significantly lower (-15-20%) than those of the 7DFD. The correlation coefficients varied from 0.52 (for added sugar) to 0.88 (for soybeans and nuts), with fruits (0.37) and dairy products (0.29) showing weaker correlations. Sixty-two (milk and dairy products) to 97% (soybeans and nuts) of participants were classified into the same or adjacent dietary intake distribution quartile using both methods. The energy and macronutrient intake differences between the IOS + SFFQ and 7DFD groups decreased substantially. The separate fruit intake measurements from each assessment method did not significantly differ from each other (p > 0.05). IOS and IOS + SFFQ regression models generally yielded higher R2 values for males than for females. Conclusion: Despite estimation differences, the IOS can be reliable for medical student dietary habit assessment. The SFFQ is useful for measuring consumption of foods that are typically unavailable in school cafeterias, improving the overall dietary evaluation accuracy. The IOS assessment was more accurate for males than for females. [ABSTRACT FROM AUTHOR]

ABSTRACTInteractions between diet and gastrointestinal microbiota influence health status and outcomes. Evaluating these relationships requires accurate quantification of dietary variables relevant to microbial metabolism, however current dietary assessment methods focus on dietary components relevant to human digestion only. The aim of this study was to synthesize research on foods and nutrients that influence human gut microbiota and thereby identify knowledge gaps to inform dietary assessment advancements toward better understanding of diet–microbiota interactions. Thirty-eight systematic reviews and 106 primary studies reported on human diet-microbiota associations. Dietary factors altering colonic microbiota included dietary patterns, macronutrients, micronutrients, bioactive compounds, and food additives. Reported diet-microbiota associations were dominated by routinely analyzed nutrients, which are absorbed from the small intestine but analyzed for correlation to stool microbiota. Dietary derived microbiota-relevant nutrients are more challenging to quantify and underrepresented in included studies. This evidence synthesis highlights advancements needed, including opportunities for expansion of food composition databases to include microbiota-relevant data, particularly for human intervention studies. These advances in dietary assessment methodology will facilitate translation of microbiota-specific nutrition therapy to practice.

BackgroundNutrition Data is a web-based program for nutrition analysis and registration of diet and exercise. It may aid dietary assessment and carbohydrate counting in people with type 1 diabetes (T1D) but requires validation.ObjectivesTo assess relative validity of Nutrition Data in measuring energy, carbohydrate and other macronutrient intake and evaluate the program’s user acceptability, in adults with T1D.MethodsIn this validation study, we analyzed data from 42 participants (median age 46.5 years, 45% women) from the DANCE study, a randomized controlled trial comprising of individuals with T1D in Sweden. Mean intakes of energy, carbohydrates, fat, protein, alcohol, fiber, sugars and saturated fat from 2 days registered in Nutrition Data were compared against the respective intakes acquired by unannounced 24-h-recalls of the same days. Paired sample t-tests and Wilcoxon matched-pairs signed rank tests were used to compare mean intakes between the two methods, and Spearman’s rank correlation and Bland Altman plots were used to assess agreement between the methods. Usability and user acceptability of Nutrition Data were assessed with a questionnaire.ResultsThere were no significant differences in mean dietary intakes between the two methods. Spearman’s correlation coefficients ranged from r = 0.79 for energy intake to r = 0.94 for carbohydrate intake (% total energy intake) (p