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OBJECTIVE: To compare the differences in estimated food, energy, and nutrient intakes between the consecutive 3 days 24-hour dietary recall(24HR)(referred to as the 3-day method) and consecutive 2 days 24HR(referred to as the 2-day method) to provide a basis for the use of consecutive 2 days 24HR in China nutrition surveillance. METHODS: Using objective sampling to select participants in northern and southern provinces, dietary data were obtained through consecutive 3 days 24HR, and the average intakes of food, energy and nutrients were calculated for three days from Thursday to Saturday and two days on Friday and Saturday, respectively. The 3-day method was considered as the reference standard method to evaluate the performance of the 2-day method for estimating food, energy and nutrient intakes. RESULTS: Among 778 participants aged 18-60 years in urban and rural areas of two provinces, the errors of the mean and median of 2-day method for estimating the intake of four major food categories less than 6% compared with the 3-day method, and there were significant equivalencies(P<0.025) and no significant differences in four major food categories group(P>0.05). Of the 24 food groups estimated by the 2-day method, 17 had mean errors within 5%, the largest error was in animal offal(13.45%) and the smallest in fruit(0.15%), and there were significant equivalencies(P<0.025) and no significant differences in seven food groups(P>0.05). For energy and nutrients, the mean and median errors of energy were less than 0.5% and there were significant equivalencies(P<0.025) and no significant differences for energy(P>0.05). Among the 25 nutrients, except sodium, iodine and vitamin E, the mean and median errors of the other 22 nutrients were less than 5%, and there were significant equivalencies(P<0.025) and no significant differences in 16 nutrients(P>0.05). CONCLUSION: There was little difference between the two survey method in assessing the intake of high consumption frequency foods, energy and most nutrients at group level, the 2-day method can be used as an alternative to the 3-day method to collect dietary intake data with high consumption rates in the population.

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Dairy, especially cheese, is associated with high levels of greenhouse gas emissions. Accurate estimates of dairy consumption are therefore important for monitoring dietary transition targets. Previous studies found that disaggregating the meat out of composite foods significantly impacts estimates of meat consumption. Our objective was to determine whether disaggregating the dairy out of composite foods impacts estimates of dairy consumption in Scotland. Approximately 32% of foods in the UK Nutrient Databank contain some dairy. In the 2021 Scottish Health Survey, mean daily intakes of dairy with and without disaggregation of composite foods were 238.6 and 218.4 g, respectively. This translates into an 8% underestimation of dairy consumption when not accounting for dairy in composite foods. In particular, milk was underestimated by 7% and cheese and butter by 50%, whereas yogurt was overestimated by 15% and cream by 79%. Failing to disaggregate dairy from composite foods may underestimate dairy consumption.

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BACKGROUND: Previous studies have shown that Japanese dietary patterns are associated with high nutrient density. However, these studies were limited to the Japanese population. We examined this association in the US population. METHODS: A cross-sectional analysis was conducted using data from the National Health and Nutrition Examination Survey (NHANES) 2017-2018. We included 3138 people aged 20-79 years. Food and nutrient intake data were based on the 24 h recall method. Three Japanese diet indices were used: (1) Japanese Diet Index (JDI, based on 9 food items), (2) modified JDI (mJDI, based on 12 food items), and (3) weighted JDI (wJDI, selected and weighted from mJDI food items). The nutrient density (ND) score was calculated based on the Nutrient-Rich Food Index 9.3. Spearman's rank correlation coefficients were calculated. RESULTS: The correlation coefficients with the ND score were 0.24 (p < 0.001) for the JDI and 0.38 (p < 0.001) for the mJDI. The correlation coefficient between the wJDI and ND score was 0.48 (p < 0.001). The three Japanese diet indices were correlated with the ND score in all racial groups (p < 0.001). CONCLUSIONS: Even among the US population, higher degrees of Japanese diet defined by the JDI or mJDI were associated with higher nutrient density.

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There is robust evidence linking diet and physical activity to major public health concerns such as cardiovascular diseases, type 2 diabetes, and osteoporosis. Dietary habits of children and adolescents are frequently discussed in health policy debates due to their modifiability, making them viable targets for prevention and health promotion initiatives. This study aimed to assess the dietary habits of 14-15-year-old Faroese adolescents using an online 24 h recall tool, examining their intake relative to public recommendations and exploring associations with health behaviour and wellbeing. A total of 78 participants (45 girls, 33 boys), with a mean age of 14.3 years, recorded their food intake and completed a questionnaire. Results indicated a higher intake of saturated fats and sugar and a lower intake of dietary fibre, n-3 fatty acids, fruits, and vegetables compared to recommendations. Healthier food intake was associated with better health behaviour and wellbeing. This very first study of Faroese adolescents' overall diet underscores the need for health-promoting interventions, and suggests the feasibility of using an online 24 h recall tool for dietary assessment in this age group, albeit with necessary adjustments for Faroese language and traditional foods.

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This report explores the 24-hour dietary recall (24HDR) form used for the Expanded Food and Nutrition Education Program (EFNEP). Dietary supplement use, amount of money spent on food, time being physically active, portion size consumed, foods reported by meals, and preparation of the meal were common components collected among 61 EFNEP programs. Components not included were instructions for the peer educator, use of food models/measuring cups, examples of foods/beverages, time food/beverages were consumed, color coding, and a prompt to review what was written. A standardized 24-hour dietary recall form with training protocols is recommended to uphold the integrity of data collection.

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Validated carotenoid assessment methods are needed to study infant carotenoid nutrition. This is a secondary analysis of repeated diet assessments of healthy participants collected at 4- (n = 21), 6- (n = 12), and 8- (n = 9) months of age in Houston, TX between April 2019 and June 2020. Intake was assessed with 3 assessment tools, analyzed with 3 nutrient databases, and underwent 3 adjustments to account for milk composition variability. We hypothesized that manual adjustment of milk carotenoid intake based on laboratory measurements would improve the validity of all assessment approaches and that using a database with greater coverage of infant food carotenoid compositions would improve accuracy. Generalized linear mixed models assessed associations between tool, nutrient database, age, and milk carotenoid adjustment variables with carotenoid, energy, fruit, and vegetable intakes. The effect of the number of food diary days on intake estimate precision was evaluated by testing the correlation between intake estimates derived from 1, 3, or 5, vs. 7 days. Visit age influenced energy intake estimates (p = .029), along with assessment tool (p = .020). Estimates of vegetable intake were influenced by tool (p = .009). Combined fruit and vegetable intake differed by nutrient database (p = .007). Carotenoid intake differed by age (p =<.0001), tool (p = .002), and nutrient database (p = .004). A minimum of 3 food diary days strongly correlated (rho = 0.79-1) with reference estimates across ages. Milk carotenoid adjustment was most influential in estimating 4-month olds' carotenoid intake, while nutrient database and tool were important for 6- and 8-month-olds', highlighting the dynamic nature of infant diet assessment validity across feeding stages.

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BACKGROUND: Healthy eating habits at a young age are crucial to support growth and development and good general health. In this context, monitoring youth dietary intakes adequately with valid tools is important to develop efficient interventions and identify groups that are more at risk of inadequate intakes. This study aimed to assess the relative validity of the self-administered web-based 24-h dietary recall (R24W) for evaluating energy and nutrient intakes among active adolescents. METHODS: Participants were invited to complete one interviewer-administered 24-h dietary dietary recall and the R24W on up to three occasions within one month. A total of 272 French-speaking active adolescents aged 12 to 17 years from the province of Québec were invited to complete three R24W and one interview-administered 24-h recall. Student's t-test and correlations were conducted on sex-adjusted data. Percent differences, cross-classification (percentage of agreement), weighted Kappa and Bland-Altman plots were calculated. RESULTS: Mean (SD) energy intake from the R24W was 8.8% higher than from the interview-administered 24-h dietary recall (2558 kcal ± 1128 vs. 2444 kcal ± 998, p < 0.05). Significant differences in mean nutrient intake between the R24W and the interview-administered 24-h dietary recall ranged from 6.5% for % E from fat (p < 0.05) to 25.2% for saturated fat (p < 0.001), i.e., higher values with R24W. Sex-adjusted correlations were significant for all nutrients except for % E from proteins and thiamin (range: 0.24 to 0.52, p < 0.01). Cross-classification demonstrated that 36.6% of the participants were classified in the same fourth with both methods, 39.6% in the adjacent fourth, and 5.7% misclassified. Bland-Atman plots revealed proportional bias between the two methods for 7/25 nutrients. Completing at least two recalls with the R24W increased the precision of intake estimates. CONCLUSION: These data suggest that the R24W presents an acceptable relative validity compared to a standard interview-administered 24-h recall for estimating energy and most nutrients in a cohort of French-speaking adolescents from the province of Québec.

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BACKGROUND: Technology-assisted 24-h dietary recalls (24HRs) have been widely adopted in population nutrition surveillance. Evaluations of 24HRs inform improvements, but direct comparisons of 24HR methods for accuracy in reference to a measure of true intake are rarely undertaken in a single study population. OBJECTIVES: To compare the accuracy of energy and nutrient intake estimation of 4 technology-assisted dietary assessment methods relative to true intake across breakfast, lunch, and dinner. METHODS: In a controlled feeding study with a crossover design, 152 participants [55% women; mean age 32 y, standard deviation (SD) 11; mean body mass index 26 kg/m2, SD 5] were randomized to 1 of 3 separate feeding days to consume breakfast, lunch, and dinner, with unobtrusive weighing of foods and beverages consumed. Participants undertook a 24HR the following day [Automated Self-Administered Dietary Assessment Tool-Australia (ASA24); Intake24-Australia; mobile Food Record-Trained Analyst (mFR-TA); or Image-Assisted Interviewer-Administered 24-hour recall (IA-24HR)]. When assigned to IA-24HR, participants referred to images captured of their meals using the mobile Food Record (mFR) app. True and estimated energy and nutrient intakes were compared, and differences among methods were assessed using linear mixed models. RESULTS: The mean difference between true and estimated energy intake as a percentage of true intake was 5.4% (95% CI: 0.6, 10.2%) using ASA24, 1.7% (95% CI: -2.9, 6.3%) using Intake24, 1.3% (95% CI: -1.1, 3.8%) using mFR-TA, and 15.0% (95% CI: 11.6, 18.3%) using IA-24HR. The variances of estimated and true energy intakes were statistically significantly different for all methods (P < 0.01) except Intake24 (P = 0.1). Differential accuracy in nutrient estimation was present among the methods. CONCLUSIONS: Under controlled conditions, Intake24, ASA24, and mFR-TA estimated average energy and nutrient intakes with reasonable validity, but intake distributions were estimated accurately by Intake24 only (energy and protein). This study may inform considerations regarding instruments of choice in future population surveillance. This trial was registered at Australian New Zealand Clinical Trials Registry as ACTRN12621000209897.

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This cross-sectional study evaluated the validity of three alternative methods compared to the gold standard 24-h urine collection for estimating dietary sodium intake, a modifiable risk factor for hypertension, among middle-aged and older adults with elevated blood pressure. These included spot urine collection (using Kawasaki, Tanaka, and INTERSALT equations), 24-h dietary recall, and food frequency questionnaire responses, compared to 24-h urine collection in a subset of 65 participants (aged 50-75 years, 58.5% women, 61.6% hypertensive) from the DePEC-Nutrition trial. The validity of the methods was assessed using bias, the Spearman correlation coefficient (SCC), the intraclass correlation coefficient (ICC), and Bland-Altman analysis. Among the alternative methods, spot urine collection using the Kawasaki equation showed the strongest correlation (SCC 0.238; ICC 0.119, 95% CI -0.079 to 0.323), but it exhibited a significant bias (1414 mg/day, p-value < 0.001) relative to 24-h urine collection. Conversely, dietary surveys had a smaller bias but wider limits of agreement. These findings underscore the complexities of accurately estimating dietary sodium intake using spot urine collection or dietary surveys in this specific population, suggesting that a combination or the refinement of existing methodologies might improve accuracy. Further research with larger samples is necessary to develop more reliable methods for assessing sodium intake in this high-risk group.

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The health risks associated with the consumption of staples cultivated in the subsistence food gardens along the Watut River were investigated in Papua New Guinea. Twenty soil samples and twenty-nine samples of staple foods (including banana, taro, sweet potato, and Singapore taro) were collected from the food gardens following a three-day dietary recall survey. The concentration of metals (Cr, Cu, Pb, and Ni) was analyzed in the soil and food samples using Inductively Coupled Plasma Optical Emission Spectrophotometer. The descending order of mean metal concentration in the food garden soils is as follows: Cr > Cu > Ni > Pb. The concentration of Pb in all samples and Cr in 97% of staple foods exceeded the FAO/WHO permissible limits. Approximately 87% of adult consumers of bananas (Musa sp) were found to have estimated Cr and Pb ingestion levels exceeding the permissible daily tolerable intake of metals (0.2 and 0.21 mg day-1, respectively). Hazard index values from the staples analysis indicate that the consumption of bananas (9.40) poses the highest risk of non-carcinogenic effects on adults, followed by taro (7.32), sweet potato (6.13), and Singapore taro (4.30). The consumption of taro is dangerous due to cancer risk associated with the intake of excessive Ni (2.88E-02) and Cr (8.82E-03) in adults and children compared to banana, sweet potato, and Singapore taro. Non-carcinogenic hazards of metal ingestion were found to be pronounced in the younger population, while carcinogenic effects were more serious in adults. Urgent measures must be implemented to protect communities, especially children, from the dangerous effects of heavy metal ingestion through staples in the lower Watut region.

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Importance: Various studies have widely explored the association between index of dietary inflammation (DII) and occurrence of diseases. Accumulating evidence have revealed that a lower DII seems to be protective against a variety of diseases. Nevertheless, the association between DII and age-related cataract remains unclear. Objective: To investigate the correlation between DII and age-related cataract in a representative sample of the American population. Design setting and participants: This cross-sectional population-based study comprised 6,395 participants from the National Health and Nutrition Examination Survey (NHANES) conducted in cycles from 2005 to 2008. DII was calculated using dietary recall information, with higher scores indicating greater inflammatory potential of the diet. Age-related cataract was evaluated using cataract surgery as a surrogate measure. Covariates included sociodemographic factors, lifestyle factors, physical measures, and comorbidities. Logistic regression models were employed to assess the association between DII and cataract. The presence of a non-linear relationship was examined using restricted cubic spline analysis. Subgroup analysis was conducted to explore potential interaction effects. Data analysis was performed from September 1 to December 30, 2022. Main outcomes and measures: Age-related cataract assessed through cataract surgery information obtained from a self-reported questionnaire. Results: A total of 6,395 participants were included, with a mean (standard deviation, SD) age of 48.7 (15.3) years. Of these, 3,115 (48.7%) were male, 3,333 (52.1%) were non-Hispanic white, and 683 (10.7%) had cataract. The mean (SD) DII was -4.78 (1.74). After adjusting for all included covariates, DII showed a positive association with cataract, both as a continuous variable (odds ratio (OR): 1.054, 95% confidence interval (CI): 1.007-1.103, p = 0.023) and in quartiles, with the highest quartile compared to the lowest (OR: 1.555, 95% CI: 1.233-1.967, p < 0.001). Restricted cubic spline analysis revealed no evidence of a non-linear relationship (p for non-linearity 0.085). Subgroup analysis indicated no interaction effects among the studied covariates. Conclusions and relevance: These findings suggest that a pro-inflammatory diet serves as a risk factor for the occurrence of cataracts.

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BACKGROUND: Dietary choices can affect human health through alterations in gut microbial metabolism, and gut microbial metabolites could serve as biomarkers for disease risk conferred by dietary intake. However, self-reported dietary intake may not reflect true intake. OBJECTIVES: We identified circulating metabolites, including gut microbiome-related metabolites, associated with adherence to a healthy diet in the ChooseWell 365 study. In this randomized clinical trial, the dietary choices of hospital employees were assessed over 24 mo using not only 24-h dietary recalls but also electronic records of hospital cafeteria purchases. METHODS: Plasma metabolites were profiled from 470 participants. Two targeted metabolomics methods were developed and implemented to expand detection coverage for metabolites related to gut microbial activity. Linear regression models were used to associate metabolites with Healthy Purchasing Scores (HPSs) derived from cafeteria purchases and Healthy Eating Index-2015 (HEI-15) scores derived from dietary recalls. RESULTS: Fourteen metabolites were concordantly associated with the HPS and HEI-15 scores in multivariable models adjusted for age, gender, and race, including the gut microbiome-related metabolites indole-3-propionic acid (HPS, ß: 0.16, 95% CI: 0.07, 0.26, P = 7.32 × 10-4; HEI-15, ß: 0.16, 95% CI: 0.07, 0.25, P = 6.79 × 10-4), hippuric acid (HPS, ß: 0.11, 95% CI: 0.02, 0.21, P = 1.97 × 10-2; HEI-15, ß: 0.10, 95% CI: 0.01, 0.19, P = 3.14 × 10-2), and indoxyl sulfate (HPS, ß = -0.13, 95% CI: -0.23, -0.03, P = 8.21 × 10-3; HEI-15, ß: -0.12, 95% CI: -0.22, -0.03, P = 8.50 × 10-3). These gut microbial metabolites were associated with the intake of specific food groups, such as whole fruits. These metabolites were also associated with clinical variables, including blood pressure, diabetes or prediabetes, and body mass index. CONCLUSIONS: In a secondary analysis of the ChooseWell 365 study, associations between circulating gut microbiome-related metabolites and a healthy diet were confirmed using both objective and subjective measures of consumption. Accurate identification of diet-associated metabolites may help guide dietary or microbiome-based interventions aimed at disease prevention.

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BACKGROUND: Atypical Anorexia Nervosa (AAN) is a Feeding and Eating Disorder characterized by fear of gaining weight and body image disturbance, in the absence of significantly low body weight. AAN may present specific clinical and psychopathological features. Nonetheless, the literature lacks data concerning the nutritional characteristics and body composition of children and adolescents with AAN and their variation over time. METHODS: Case series, including 17 children and adolescents with AAN. All the patients were assessed at the first evaluation (T0) with a standardized dietary assessment (24 h Dietary Recall, 24 hDR). Nutritional data were compared with European dietary reference values (DRVs). Body composition parameters (weight, fat mass, fat-free mass) and their changes over time at two (T1) and six (T2) months were collected as well, using a Bioelectrical impedance analysis (Wunder WBA300 with four poles and foot contact; impedance frequency 50 kHz 500 µA; impedance measurement range 200~1000 Ω/0.1 Ω). RESULTS: The included individuals presented eating behaviors oriented towards significantly low daily energy intake (p < 0.001) compared with DRVs set by the European Food Safety Authority (EFSA) (with low carbohydrates and fats), and increased proteins (p < 0.001). A longer latency before observation (illness duration before observation) correlated with a negative change in weight. Body composition parameters were described, with no significant changes across the six-month outpatient assessment. DISCUSSION: This is the first research to systematically assess the body composition and nutritional features of a group of individuals with AAN in the developmental age. Further research should assess the effect of targeted treatment interventions on body composition and nutritional features.

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The purpose of this article is to describe the impact of the research program entitled "Adherence to healthy eating recommendations: identification of measures, determinants and interventions". Beyond the main results described in this article, this program had a major impact on the training of graduate students. It was also a unique opportunity to develop and validate measurement tools relevant to nutrition research, and to make them available to the scientific community. Lastly, this program was a catalyst for establishing new collaborations and setting up larger-scale studies.

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BACKGROUND: In the Dutch National Food Consumption Survey, dietary intake has been assessed since 2003 through 24-hour dietary recalls using the GloboDiet software. A new self-administered smartphone food record app called DitEetIk! was developed for potential use in future surveys. OBJECTIVE: This study aims to evaluate the data collected using the DitEetIk! app and its relative validity for food group, energy, and nutrient intake compared with the previous dietary assessment method (GloboDiet 24-hour dietary recalls). METHODS: A total of 300 participants aged 18 to 79 years were recruited from a consumer panel. Participants were asked to keep a record of their consumption using the DitEetIk! app on 3 nonconsecutive days. Trained dietitians conducted a 24-hour dietary recall interview by telephone using the GloboDiet software (International Agency for Research on Cancer) regarding 1 of 3 DitEetIk! recording days. Nutrient intake was calculated using the NEVO database (version 2021/7.0). Relative validity was studied by comparing data from GloboDiet 24-hour dietary recalls and the DitEetIk app for the same day. Participants with implausible records, defined as days with energy intake of <0.6 or >3.0 basal metabolic rate, were excluded from the analyses. For 19 food groups and 29 nutrients, differences in median intake were assessed using the Wilcoxon signed rank test, and Spearman correlation coefficients were calculated. Bland-Altman plots with mean differences and 95% limits of agreement were created for energy intake and the contribution to energy intake from fat, carbohydrates, and protein. RESULTS: A total of 227 participants completed a combination of a DitEetIk! app recording day and a 24-hour dietary recall interview for the same day. Of this group, 211 participants (n=104, 49.3% men and n=107, 50.7% women) had plausible recording days. Of all recorded food items, 12.8% (114/894) were entered via food barcode scanning, and 18.9% (169/894) were searched at the brand level. For 31% (5/16) of the food groups, the median intake assessed using the DitEetIk! app was >10% lower than that assessed using 24-hour dietary recalls; this was the case for fruit (P=.005), added fats (P=.001), milk and milk products (P=.02), cereal products (P=.01), and sauces (P<.001). This was also the case for 14% (4/29) of the nutrients (all P<.001). Regarding mean intake, differences were generally smaller. Regarding energy intake, the mean difference and 95% limits of agreement were 14 kcal (-1096 to 1124). Spearman correlation coefficients between intake assessed using the DitEetIk! app and 24-hour dietary recalls ranged from 0.48 to 0.88 (median 0.78) for food groups and from 0.58 to 0.90 (median 0.72) for nutrients. CONCLUSIONS: Compared with GloboDiet 24-hour dietary recalls, the DitEetIk! app assessed similar mean energy intake levels but somewhat lower median intake levels for several food groups and nutrients.

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BACKGROUND: Studies regarding the validity of the food frequency questionnaire (FFQ) and the food composition table (FCT) are limited in Asian countries. We aimed to evaluate the validity of a 64-item FFQ and different methods of constructing the FFQ FCTs for assessing dietary intakes of foods and nutrients among adults in eastern China. METHODS: A total of 2325 participants (aged 56.2 ± 14.9 years, 51.6% female) from nine cities in Zhejiang province who completed a 64-item FFQ and 3-day 24-hour dietary recalls (24HRs) in 2015 were included. Eight FFQ FCTs were generated covering food items and specific weights estimated using professional knowledge, representative 24HRs data, or the Chinese FCT (CFCT). Energy-adjusted intakes of foods and nutrients were estimated by residual and energy density methods. Spearman correlation coefficients (SCCs) of intakes of 14 food groups and 17 nutrients between FFQ and 24HRs were calculated to evaluate the overall validity of FFQ. RESULTS: The average intakes of most food groups and nutrients assessed with FFQ were higher than those assessed using the 24HRs. For the food groups, the averaged energy-adjusted (residual method) SCC between FFQ and 24HRs was 0.27, ranging from 0.14 (starch-rich beans) to 0.49 (aquatic products). For nutrient assessment, the weighted FCT (WFCT) performs the best, and the averaged energy-adjusted (residual method) SCC was 0.26, ranging from 0.16 (iron) to 0.37 (potassium). Similar correlations with 24HRs were observed when using other FFQ FCT in the calculation of nutrient intakes. CONCLUSION: The 64-item Chinese FFQ and the WFCT were reasonably valid to assess the dietary intakes of certain foods and nutrients among adults in eastern China.

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Dietary assessments are important clinical tools used by Registered Dietitians (RDs). Current methods pose barriers to accurately assess the nutritional intake of older adults due to age-related increases in risk for cognitive decline and more complex health histories. Our qualitative study explored whether implementing Voice assistant systems (VAS) could improve current dietary recall from the perspective of 20 RDs. RDs believed the implementing VAS in dietary assessments of older adults could potentially improve patient accuracy in reporting food intake, recalling portion sizes, and increasing patient-provider efficiency during clinic visits. RDs reported that low technology literacy in older adults could be a barrier to implementation. Our study provides a better understanding of how VAS can better meet the needs of both older adults and RDs in managing and assessing dietary intake.

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Background: Food frequency questionnaire (FFQ) is the most frequently used dietary assessment method in estimating dietary intakes in epidemiological studies. Aim: This study aimed to assess the relative validity of a semiquantitative FFQ in evaluating dietary intake among pregnant women in the United Arab Emirates. Methods: Within the Mutaba'ah study, a subsample of 111 pregnant women completed a semiquantitative FFQ and a single 24-hour dietary recall (24-HDR) regarded as the reference method. Absolute and energy-adjusted nutrient and food intakes between the FFQ and 24-HDR were compared using the Wilcoxon signed ranks test, correlations, Bland-Altman analysis, cross-classification, and weighted kappa analysis. Results: There were no significant differences in reported absolute intakes between the FFQ and 24-HDR for carbohydrates, whole grains, white meat, beta-carotene, vitamin K, sodium, and selenium. Spearman's correlation coefficients between the FFQ and 24-HDR ranged from 0.09 (trans fatty acids) to 0.5 (potassium) for absolute intakes. Correlation decreased after energy adjustment. Bland-Altman analysis showed that the FFQ overestimated intakes compared with 24-HDR and that the limits of agreement were wide. The average percentage of pregnant women classified into the same or adjacent quartile of intake by both methods was 73%. Weighted kappa values ranged from -0.02 (white meat) to 0.33 (magnesium). Conclusion: Our findings showed that the semi-quantitative FFQ is a useful tool in ranking pregnant women from the Emirati population according to their dietary intake. However, the validity of some estimated intakes was poor; hence, certain intakes should be interpreted with caution.

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OBJECTIVE: The aim of this study was to compare self-reported total energy intake (TEI) collected using an online multiple-pass 24-h dietary recall tool (Intake24) with total energy expenditure (TEE) estimated from Fitbit Charge 2-improved algorithms in adults from the NoHoW trial (12-mo weight maintenance after free-living weight loss). METHODS: Bland-Altman plots were used to assess the level of agreement between TEI and TEE at baseline and after 12 mo. The ratio of TEI to TEE was also calculated. RESULTS: Data from 1323 participants (71% female) was included in the analysis (mean ± SD: age 45 ± 12 y, body mass index 29.7 ± 5.4 kg/m2, initial weight loss 11.5 ± 6.5 kg). The TEI was lower than TEE on average by 33%, with limits of agreement ranging from -91% to +25%. Men, younger individuals, those with higher body mass index, those with the greater weight loss before enrollment, and those who gained weight during the study underestimated to a greater extent. CONCLUSIONS: These findings contribute to the ongoing research examining the validity of technology-based dietary assessment tools.

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In nutritional epidemiological studies, it is imperative to collect high-quality data to ensure accurate dietary assessment. However, dietary data collection using traditional paper forms has several limitations that may compromise data quality. The aim of this study was to propose novel methods to design and develop software applications (Apps) for dietary data collection to assess the nutritional status of pregnant women and infants. This study is part of the M-SAKHI (Mobile-Solutions for Aiding Knowledge for Health Improvement) cluster randomised controlled trial (cRCT) implemented in central India. Three tablet-based software Apps were developed in this study: the ACEC (Automated Coding and Energy Calculation) App to establish a generic cooked food recipe database, the FFQ (Food Frequency Questionnaire), and the IDR (24 h Infant Dietary Recall) Apps to collect dietary data from pregnant women and their infants from rural area of Bhandara and Nagpur districts. Regional food lists, recipes, and portion resource kits were developed to support the data collection using the Apps. In conclusion, the Apps were user-friendly, required minimal prior training, had built-in validation checks for erroneous data entry and provided automated calculations. The Apps were successfully deployed in low-resource rural settings to accurately collect high-quality regional cooked food data and individual-level dietary data of pregnant women and their infants.

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