DESIGN: Scoping review.
SETTING: Systematic search using PubMed and Web of Science.
RESULTS: We identified twelve tools from seventy-four eligible publications. They were developed for Koreans (n 4), Bangladeshis (n 2), Iranians (n 1), Indians/Malays/Chinese (n 1), Japanese (n 3) and Chinese Americans (n 1). Most tools (10/12) were composed of a dish-based FFQ. Although the development process of a dish list varied among the tools, six studies classified mixed dishes based on the similarity of their characteristics such as food ingredients and cooking methods. Tools were validated against self-reported dietary information (n 9) and concentration biomarkers (n 1). In the eight studies assessing the differences between the tool and a reference, the mean (or median) intake of energy significantly differed in five studies, and 26-83 % of nutrients significantly differed in eight studies. Correlation coefficients for energy ranged from 0·15 to 0·87 across the thirteen studies, and the median correlation coefficients for nutrients ranged from 0·12 to 0·77. Dish-based dietary assessment tools were used in fifty-nine studies mainly to assess diet-disease relationships in target populations.
CONCLUSIONS: Dish-based dietary assessment tools have exclusively been developed and used for Asian-origin populations. Further validation studies, particularly biomarker-based studies, are needed to assess the applicability of tools.
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.
METHODS: A total of 392 children participated in the FFQ development and 112 children aged 9-12 years participated in the validation phase; with a subsample of 50 children participating in the reproducibility phase. Three-day diet record (3DR) as the reference method in validation phase. Spearman correlations, mean difference, Bland-Altman plot and cross-classification analyses were used to assess validity. The reproducibility was tested through a repeat administration of the FFQ, with 1 month time interval. Reproducibility analyses involved intra-class correlation coefficient (ICC), Cronbach's alpha and cross-classification analyses.
RESULTS: The FFQ consisted of 156 whole grain food items from six food groups. Mean intake of whole grain in FFQ1 and 3DR were correlated well (r = 0.732), demonstrated good acceptance of the FFQ. Bland Altman plots showed relatively good agreement for both the dietary methods. Cross-classification of whole grain intake between the two methods showed that
METHODS: This cross-sectional study was conducted among 411 students aged 18-29 years, purposive sampled from a selected private university in Klang Valley, Malaysia. Anthropometric profiles were measured. Nutrient intakes were assessed by 3-day 24-hour diet recalls.
RESULTS: Respondents on average had adequate macronutrient intakes, however, total consumption of dietary fiber and micronutrients were fell short of recommended levels. Significant negative associations were found between body mass index (BMI) and all the macronutrients, calcium, thiamine, riboflavin and niacin. Body fat percentage was significantly associated with all the macronutrients, calcium, zinc, thiamine and niacin. Significant inverse associations were also found between waist circumference and carbohydrate, fiber, thiamine, riboflavin and niacin. Visceral fat showed significant inverse associations with carbohydrate, fat, fiber, thiamine, riboflavin and niacin. Further, after adjusting for sex, gender and race, BMI was associated with niacin (β=-0.161, p=0.027). Body fat percentage was also found significantly associated with niacin (β=-0.180, p=0.002) and riboflavin (β=-0.132, p=0.014).
CONCLUSION: Micronutrients, especially B vitamins, are important in weight management among the young adults.
METHODS AND STUDY DESIGN: This study comprised development and validation phases. In the development phase, 129 young adults from a public university in Klang Valley completed a 3-day food record (3DFR), and the data were used to create a food list for the FFQ. Two weeks later, in the validation phase, another 100 participants recruited from the same university completed the 3DFR and a newly developed FFQ for assessing consumption of 38 food items. Finally, the data obtained from the FFQ and 3DFR were used to analyze the nutrient intake of each participant, and the developed FFQ was validated using Spearman correla-tion coefficients (r) and Bland-Altman methods.
RESULTS: For the development phase, 38 food items were determined to contribute to 90% of the participants' total energy and macronutrient intake, and these items were included on the FFQ. For the validation phase, the average Spearman correlation coefficient for energy and all nutrients was 0.43, which indicated good agreement between the 3DFR and FFQ. Cross-classification analysis of the 3DFR and FFQ results revealed that 79% of the young adults were classified into similar or neighboring quartiles when each set of results was used. The Bland-Altman plots revealed that the results obtained using the two methods were parallel.
CONCLUSIONS: The FFQ is a simple and validated tool that can be self-administered to young adults to assess their energy and nutrient consumption.