Search Results (18)

Background/Objectives: Accurate dietary assessment is crucial for nutritional epidemiology, but tools like 24 h recalls (24HRs) face challenges with missing or implausible data. The Automated Self-Administered 24 h Dietary Assessment Tool (ASA24) facilitates large-scale data collection, but its lack of interviewer input may lead to implausible dietary recalls (IDRs), affecting data integrity. Multiple imputation (MI) is commonly used to handle missing data, but its effectiveness in high-variability dietary data is uncertain. This study aims to assess MI’s accuracy in estimating nutrient intake under varying levels of missing data. Methods: Data from 24HRs completed by 743 adolescents (ages 13–18) in Ontario, Canada, were used. Implausible recalls were excluded based on nutrient thresholds, creating a cleaned reference dataset. Missing data were simulated at 10%, 20%, and 40% deletion rates. MI via chained equations was applied, incorporating demographic and psychosocial variables as predictors. Imputed values were compared to actual values using Spearman’s correlation and accuracy within ±10% of true values. Results: Spearman’s rho values between the imputed and actual nutrient intakes were weak (mean ρ ≈ 0.24). Accuracy within ±10% was low for most nutrients (typically < 25%), with no clear trend by missingness level. Diet quality scores showed slightly higher accuracy, but values were still under 30%. Conclusions: MI performed poorly in estimating individual nutrient intake in this adolescent sample. While MI may preserve sample characteristics, it is unreliable for accurate nutrient estimates and should be used cautiously. Future studies should focus on improving data quality and exploring better imputation methods. Full article

Trimethylamine N-oxide (TMAO), a gut microbiome metabolite linked to cardiovascular health, can be influenced by dietary factors like choline intake and diet quality. This study compared the effects of mixed tree nuts (MTNs) and pretzels, as part of a 12-week hypocaloric weight loss diet, on TMAO levels and identified dietary predictors. Methods: Plasma samples from 95 overweight individuals consuming either 1.5 oz. of mixed tree nuts (MTNs, n = 56) or isocaloric pretzels (n = 39) daily for 12 weeks were analyzed. Nutritional data were collected at baseline and week 12 through dietary recall using the Automated Self-Administered 24 h Dietary Assessment Tool (ASA24), and the overall diet quality was assessed via the Healthy Eating Index (HEI) score. TMAO levels were determined and analyzed using linear mixed-effect models, adjusting for covariates. Wilcoxon signed-rank tests compared baseline and week 12 TMAO and weight. Multiple linear regression identified baseline predictors of TMAO. Results: Baseline demographics, anthropometric measures, HEI scores, and dietary choline intake were similar between the MTN and pretzel groups. A significant positive association was observed between baseline dietary choline and plasma TMAO levels (p = 0.012). The 12-week hypocaloric diet led to significant weight reduction in both groups (p < 0.01), but the magnitude of weight loss did not differ significantly between the MTN (−3.47 lbs) and pretzel (−4.25 lbs) groups (p = 0.18). Plasma TMAO levels decreased significantly in both groups (p < 0.01), but the between-group difference in reduction was not significant. (MTNs: −0.34 vs. pretzels: −0.37; p = 0.43). HEI scores and dietary choline intake remained unchanged, with no significant time–intervention interaction. Participants with low baseline HEI scores (≤53.72) had a more pronounced reduction in TMAO levels in the MTN group compared to the pretzel group (MTN: −0.54 vs. pretzel: −0.23; p = 0.045) over 12 weeks, despite similar weight loss. This difference was not observed in participants with higher HEI scores. Conclusions: The 12-week hypocaloric diet reduced body weight and plasma TMAO levels similarly in both MTN and pretzel groups. Participants with lower dietary quality saw a greater reduction in TMAO levels in the MTN group, suggesting MTNs may better modulate TMAO levels, especially for those with poorer baseline diets. Full article

Background/Objectives: Persons with multiple sclerosis (MS) are interested in diet as a second-line approach for disease management. This study examined potential variables that correlate with inaccuracy of self-reported energy intake (EI) in adults with MS. Methods: Twenty-eight participants completed two assessment appointments within a 14-day period that included a standard doubly labeled water (DLW) protocol for estimating total energy expenditure (TEE). The participants reported their EI using the Automated Self-Administered 24 h (ASA24) Dietary Assessment Tool. The primary variables of interest for explaining the discrepancy between TEE and ASA24 EI (i.e., inaccuracy) included cognition (processing speed, visuospatial memory, and verbal memory), hydration status (total body water), and device-measured physical activity. Pearson’s correlations assessed the association between absolute and percent inaccuracy in reporting of EI with outcomes of interest, followed by linear regression analyses for identifying independent correlates. Results: California Verbal Learning Test—Second Edition (CVLT-II) z-scores and light physical activity (LPA) were significantly associated with mean absolute difference in EI (r = –0.53 and r = 0.46, respectively). CVLT-II z-scores and LPA were the only variables significantly associated with mean percent difference in EI (r = –0.48 and r = 0.42, respectively). The regression analyses indicated that both CVLT-II and LPA significantly explained variance in mean absolute difference in EI, and only CVLT-II explained variance for percent difference in EI. Conclusions: The results from this study indicate that verbal learning and memory and LPA are associated with inaccuracy of self-reported EI in adults with MS. This may guide timely research identifying appropriate protocols for assessment of diet in MS. Full article

Tools to briefly assess diet among US Spanish-speaking adults are needed to identify individuals at risk for cardiometabolic disease (CMD) related to diet. Two registered dietitian nutritionists (RDNs) recruited bilingual medical students to translate the validated Diet Risk Score (DRS) into Spanish (DRS-S). Participants were recruited from a federally qualified health center. Students administered the DRS-S and one 24-h recall (Automated Self-Administered 24-Hour (ASA24^®) Dietary Assessment Tool) on one day; a second recall was administered within 1 week. Recalls were scored using the Healthy Eating Index (HEI)-2015, a measure of adherence to the Dietary Guidelines for Americans. Spearman correlations, weighted kappa, and ANOVA were conducted using SAS 9.4 to assess the relative validity of the DRS-S. Thirty-one Spanish-speaking adults (female: n = 17, 53%; mean age: 58 (42–69)) completed assessments. The mean DRS-S was 9 (SD = 4.2) (max: 27; higher score = higher risk) and the mean HEI-2015 score was 65.7 (SD = 9.7) (max: 100; higher score = lower risk), with significant agreement between measures (r: −0.45 (p = 0.01)), weighted kappa: −0.3 (p = 0.03). The DRS-S can be used in resource-constrained settings to assess diet for intervention and referral to RDNs. The DRS-S should be tested in clinical care to assess the impact of dietary changes to reduce CMD risk. Full article

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. Full article

Understanding the dietary characteristics of people living with multiple sclerosis (plwMS) may assist in the planning of nutrition interventions for multiple sclerosis; yet dietary assessment methods in existing studies are not well established. The aim of this study was to validate the psychometric properties (construct validity and internal consistency) of the Dietary Habits Questionnaire (DHQ) against repeated online 24-h recall dietary assessments. The DHQ is a 24-item tool that is scored using ten dietary sub-scores. Total DHQ scores can range from 20–100 and are considered indicative of the quality of dietary intake with higher scores reflecting increased quality. People living with a relapsing-remitting MS phenotype who had completed a modified DHQ were recruited from the international Health Outcomes and Lifestyle In a Sample of people with Multiple sclerosis (HOLISM) cohort. Repeated 24-h recall via the online Automated Self-administered Assessment-24 (ASA-24) tool were modelled to reflect usual dietary intakes using the Multiple Source Method. DHQ scores of eight sub-scores: three key nutrients, three food groups and two food preparation practices, were calculated and statistically compared with ASA-24 usual intake data. Principal component analysis of the ASA-24 data was undertaken to understand dietary patterns of the sample. Of the 105 participants, valid 24-h recall data were available for 96 plwMS (n = 66 1 day, n = 30 ≥ 2 day). The median total DHQ score was 84.50 (IQR: 77.04, 91.83) points. The highest absolute correlations were between the DHQ scores and ASA-24 data for cereal (r = 0.395, p < 0.001), fruit and vegetables (r = 0.436, p < 0.001), and total dietary fiber (r = 0.482, p < 0.001). Five dietary patterns emerged from the data explaining 42.12% variance and reflecting exposure of plwMS to the influence of ‘MS diets’. The DHQ appears to be appropriate for screening participants with relapsing-remitting MS. Evidence-based dietary models focusing on food are required to monitor the quality of an overall dietary pattern and set priorities for the planning nutrition interventions for plwMS. Full article

Automated, self-administered, Web-based 24-h dietary recall tools are increasingly available for nutrition research in different settings, particularly in epidemiological studies and national surveys because of their practicality and efficiency. However, the usability of different 24-h dietary recall tools must be assessed and compared for use in specific populations as it is a major driver of the response rate and retention of participants. The primary aim of this study was to compare the usability of two validated, self-administered, web-based 24-h dietary recall tools available for the Canadian population: the R24W and the 2018 Canadian version of the ASA24. The R24W was developed in French for primary use in the province of Québec, Canada while the ASA24 was developed in English for primary use in the USA and recently adapted and translated for use in French-speaking Canadian adults. Whether the R24W and the ASA24-Canada-2018 yield similar nutritional data was also tested. In this randomized crossover study, 48 women and 20 men (mean age of 35 ± 14 years; range: 19–79 years) recruited in the province of Quebec completed the R24W and the ASA24-Canada-2018 in French twice on each occasion. Participants also completed the System Usability Scale (SUS), a reliable and valid scale giving a global view of subjective assessments of usability. Mean SUS score as well as mean dietary intakes of energy, nutrients and food groups generated by each tool were compared using mixed model analyses for repeated measures. On a scale of 0 to 100, the mean SUS scores (±SD) for the R24W and the ASA24-Canada-2018 were 81 ± 2 and 58 ± 2, respectively (p < 0.0001). 84% of participants stated that they would prefer to use the R24W if they were invited to complete additional 24-h dietary recalls. No significant difference was found between the R24W and the ASA24-Canada-2018 for the intake of energy, proteins, lipids, saturated fatty acids, carbohydrates, fibers, sodium and vegetables and fruits. In sum, while the R24W and the ASA24-Canada-2018 generate comparable self-reported dietary intake data, the R24W showed a better usability than the ASA24-Canada-2018 in a sample of French-speaking adults from the province of Quebec. Full article

Demographic and psychosocial factors concerning dietary assessment error have been explored, but few studies have investigated the perceived problems experienced when completing dietary recalls. The aim of this research was to (i) compare the perceived problems encountered in two commonly used self-administered 24-hour dietary recall (24HR) programs (INTAKE24© and ASA24^®) and (ii) explore whether mindful and habitual eating are associated with perceived problems during dietary recall. A randomised quantitative crossover design and think-aloud methodology were employed. Undergraduate university students (N = 55, M_age = 25.5, SD = 8.2, 75% female) completed a food habits and mindfulness questions pre-program, one 24HR (whilst thinking aloud), and a systems usability scale post-program. A week later, they completed the other 24HR (whilst thinking aloud). During a pilot, a coding frame of perceived problems was devised to quantify participants’ perceived problems. INTAKE24© generated significantly fewer perceived problems across all categories compared to ASA24^® (17.2 vs. 33.1, p < 0.001). Of the participants, 68% reported a preference for INTAKE24© over ASA24^®. Hierarchical multiple regression showed that habits and systems usability were significant predictors of perceived problems for INTAKE24© only. No significant predictors were found for ASA24^®. The results provide insight into perceived problems people may encounter when using 24HR tools. Full article

Background: Diet quality has not been distinctively examined in wheelchair users with multiple sclerosis (MS). Methods: This cross-sectional study examined the Diet History Questionnaire (DHQ) III and the Automated Self-Administered 24-h (ASA24) Dietary Assessment Tool in 128 wheelchair users with MS. Participants were prompted to complete the DHQ-III and 3 ASA24 recalls during a seven-day data collection period. Healthy Eating Index (HEI)-2015 scores were calculated for DHQ-III and ASA24, and scores were compared with normative values. Spearman’s correlation analyses (r_s) estimated the associations between DHQ-III and ASA24 HEI-2015 total and component scores with supportive paired sample t-tests. Results: HEI-2015 scores for DHQ-III and ASA24 were significantly higher than normative values for total score, total protein foods, and added sugar. Correlations between HEI-2015 scores generated using ASA24 and DHQ-III were all statistically significant (range r_s = 0.23–0.69); however, significant differences between ASA24 and DHQ-III values were noted for HEI-2015 total score, total fruits, whole fruit, total vegetable, greens and beans, whole grains, seafood and plant protein, refined grains, and saturated fats. Conclusion: This study provided a novel description of diet quality in wheelchair users with MS for guiding future research promoting healthy eating in this population. Full article

Background: Increasing evidence points to the esophageal microbiome as an important co-factor in esophageal neoplasia. Esophageal microbiome composition is strongly influenced by the oral microbiome. Salivary microbiome assessment has emerged as a potential non-invasive tool to identify patients at risk for esophageal cancer, but key host and environmental factors that may affect the salivary microbiome have not been well-defined. This study aimed to evaluate the impact of short-term dietary intake on salivary microbiome composition. Methods: Saliva samples were collected from 69 subjects prior to upper endoscopy who completed the Automated Self-Administered 24-Hour (ASA24) Dietary Assessment. Salivary microbiome composition was determined using 16S rRNA amplicon sequencing. Results: There was no significant correlation between alpha diversity and primary measures of short-term dietary intake (total daily calories, fat, fiber, fruit/vegetables, red meat intake, and fasting time). There was no evidence of clustering on beta diversity analyses. Very few taxonomic alterations were found for short-term dietary intake; an increased relative abundance of Neisseria oralis and Lautropia sp. was associated with high fruit and vegetable intake, and an increased relative abundance of a taxon in the family Gemellaceae was associated with increased red meat intake. Conclusions: Short-term dietary intake was associated with only minimal salivary microbiome alterations and does not appear to have a major impact on the potential use of the salivary microbiome as a biomarker for esophageal neoplasia. Full article

Background: Diet is a modifiable behavior of interest in multiple sclerosis (MS); however, measures of diet in persons with MS have not been vetted for feasibility, acceptability, and validity. Methods: This cross-sectional study examined the Automated Self-Administered 24-H (ASA24) Dietary Assessment Tool in 30 persons with MS and 15 healthy control (HC) participants. Participants were prompted to complete six ASA24 recalls and undergo a standard doubly labeled water (DLW) protocol. Acceptability of ASA24 was assessed using an online questionnaire. Total energy expenditure (TEE) from DLW was compared with ASA24-reported energy intake for assessing validity. Results: All participants completed four or more ASA24 recalls, indicating feasibility of ASA24. Regarding acceptability, the hardest part of completing the ASA24 was remembering everything eaten the previous day. Pearson correlation coefficients between DLW TEE and ASA24 kcal/day were not significant among HC (r = 0.40; p = 0.14) or MS (r = 0.26; p = 0.16) participants. The absolute mean error between DLW TEE and ASA24 among HC participants was 694.96 ± 506.25 mean kcal/day and among MS participants was 585.37 ± 529.02 mean kcal/day; this represents a mean difference of 30 and 25%, respectively. Conclusion: This study established the feasibility and acceptability of ASA24 in persons with MS and provides a foundation regarding the need for further validation research examining appropriate outcomes for supporting dietary interventions. Full article

The Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA24) is a free dietary recall system that outputs fewer nutrients than the Nutrition Data System for Research (NDSR). NDSR uses the Nutrition Coordinating Center (NCC) Food and Nutrient Database, both of which require a license. Manual lookup of ASA24 foods into NDSR is time-consuming but currently the only way to acquire NCC-exclusive nutrients. Using lactose as an example, we evaluated machine learning and database matching methods to estimate this NCC-exclusive nutrient from ASA24 reports. ASA24-reported foods were manually looked up into NDSR to obtain lactose estimates and split into training (n = 378) and test (n = 189) datasets. Nine machine learning models were developed to predict lactose from the nutrients common between ASA24 and the NCC database. Database matching algorithms were developed to match NCC foods to an ASA24 food using only nutrients (“Nutrient-Only”) or the nutrient and food descriptions (“Nutrient + Text”). For both methods, the lactose values were compared to the manual curation. Among machine learning models, the XGB-Regressor model performed best on held-out test data (R² = 0.33). For the database matching method, Nutrient + Text matching yielded the best lactose estimates (R² = 0.76), a vast improvement over the status quo of no estimate. These results suggest that computational methods can successfully estimate an NCC-exclusive nutrient for foods reported in ASA24. Full article

The production of food is associated with significant environmental impact. In this paper, we describe the first assessment of the environmental impact of food consumption in the United States using individually reported dietary intake data from a nationally representative sample. Using individual-level dietary intake data from the National Health and Nutrition Examination Survey (NHANES) and applying median environmental impact factors compiled by Poore and Nemecek (2018), we estimate that the daily diet that a non-institutionalized U.S. civilian reports results in a mean of 3.92 m² (95% CI: 3.51–4.34) of land used, 2.26 kg (95% CI: 2.09–2.42)of CO₂e emitted, and 159 L (95% CI: 150–168) of freshwater withdrawn. The scope of all impacts is agricultural; transportation, storage, and preparation were not included. These results suggest that the calculator is ready for further development. This calculator can be used to estimate the environmental impact of individual diets in the 5100 studies (as of November 2018) registered with the Automated Self-Administered 24-h Dietary Assessment Tool, in addition to the last two decades of the nationally representative NHANES research. Full article

The Automated Self-Administered Dietary Assessment Tool (ASA24) is a web-based tool that guides participants through completion of a 24-h dietary recall and automatically codes the data. Despite the advantages of automation, eliminating interviewer contact may diminish data quality. Usability testing can assess the extent to which individuals can use the ASA24 to report dietary intake with efficiency, effectiveness, and satisfaction. This mixed-methods study evaluated the usability of the ASA24 to quantify user performance and to examine qualitatively usability issues in a sample of low-income adults (85% female, 48.2 years on average) participating in a nutrition coupon program. Thirty-nine participants completed a 24-h dietary recall using the ASA24. Audio and screen recordings, and survey responses were analyzed to calculate task times, success rates, and usability issue frequency. Qualitative data were analyzed thematically to characterize usability issues. Only one participant was able to complete a dietary recall unassisted. We identified 286 usability issues within 22 general usability categories, including difficulties using the search function, misunderstanding questions, and uncertainty regarding how to proceed to the next step; 71.4% of participants knowingly misentered dietary information at least once. Usability issues may diminish participation rates and compromise the quality of ASA24 dietary intake data. Researchers should provide on-demand technical support and designers should improve the intelligence and flexibility of the ASA24’s search functionality. Full article

This study assessed test-retest reliability and relative validity of the Short Diet Questionnaire (SDQ) and usability of an online 24 h recall among 232 participants (62 years ± 9.1; 49.6% female) from the Canadian Longitudinal Study on Aging (CLSA). Participants were asked to complete four 24 h dietary recalls (24HRs) using the Automated Self-Administered 24-h Dietary Assessment Tool (ASA24-Canada-2014), two SDQ administrations (prior to recalls one and four), and the System Usability Scale (SUS) for ASA24. For the SDQ administrations, Intraclass Correlation Coefficients ranged from 0.49 to 0.57 for nutrients and 0.35 to 0.72 for food groups. Mean intakes estimated from the SDQ were lower compared than those from the 24HRs. For nutrients, correlation coefficients were highest for fiber, calcium, and vitamin D (45–64 years: 0.59, 0.50, 0.51; >65 years: 0.29, 0.38, 0.49, p < 0.01); Kappas ranged from 0.14 to 0.37 in those 45–64 years and 0.17 to 0.32 in participants >65 years. Among the 70% who completed all recalls independently, the SUS indicated poor usability, though the majority reported feeling confident using ASA24. Overall, the SDQ captures intake with varying test-retest reliability and accuracy by nutrient and age. Further research is needed to inform use of a more comprehensive dietary measure in the CLSA. Full article