Search

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.

Abstract 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

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]

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. [ABSTRACT FROM AUTHOR]

Changes in an individual's digestive system, hormones, senses of smell and taste, and energy requirement accompanying aging could lead to impaired appetite, but older adults may not notice their risk of nutrient deficiency. When assessing the dietary intake of older adults, it was found that they had more difficulties with short-term recall and open-ended recall and would experience greater fatigue and frustration when compared to younger individuals when completing a lengthy questionnaire. There is a need to develop a brief dietary assessment tool to examine the nutritional needs of older adults. In this study, we aimed to assess the diet of Hong Kong older adults using the short FFQ and examine its reproducibility and relative validity as a dietary assessment tool. Dietary data of 198 older adults were collected via FFQs and three-day dietary records. Correlation analyses, cross-tabulation, one-sample t-tests, and linear regression analyses were used to evaluate the relative validity of the short FFQ. In general, the short FFQ was accurate in assessing the intake of phosphorus, water, grains, and wine, as shown by a significant correlation (>0.7) between values reported in the FFQs and dietary records; good agreement (more than 50% of observations belonged to the same quartile) and insignificant differences detected with the one-sample t-tests and linear regression analyses were observed for the above four variables. Additionally, the intake of proteins, carbohydrates, total fat, magnesium, and eggs in terms of the values reported in the FFQs and dietary records showed good agreement. [ABSTRACT FROM AUTHOR]

Changes in an individual’s digestive system, hormones, senses of smell and taste, and energy requirement accompanying aging could lead to impaired appetite, but older adults may not notice their risk of nutrient deficiency. When assessing the dietary intake of older adults, it was found that they had more difficulties with short-term recall and open-ended recall and would experience greater fatigue and frustration when compared to younger individuals when completing a lengthy questionnaire. There is a need to develop a brief dietary assessment tool to examine the nutritional needs of older adults. In this study, we aimed to assess the diet of Hong Kong older adults using the short FFQ and examine its reproducibility and relative validity as a dietary assessment tool. Dietary data of 198 older adults were collected via FFQs and three-day dietary records. Correlation analyses, cross-tabulation, one-sample t-tests, and linear regression analyses were used to evaluate the relative validity of the short FFQ. In general, the short FFQ was accurate in assessing the intake of phosphorus, water, grains, and wine, as shown by a significant correlation (>0.7) between values reported in the FFQs and dietary records; good agreement (more than 50% of observations belonged to the same quartile) and insignificant differences detected with the one-sample t-tests and linear regression analyses were observed for the above four variables. Additionally, the intake of proteins, carbohydrates, total fat, magnesium, and eggs in terms of the values reported in the FFQs and dietary records showed good agreement.

Background: Valid assessment tools are needed when investigating adherence to national dietary and lifestyle guidelines., Objective: The relative validity of the new digital food frequency questionnaire, the DIGIKOST-FFQ, against 7-day weighed food records and activity sensors was investigated., Methods: In total, 77 participants were included in the validation study and completed the DIGIKOST-FFQ and the weighed food record, and of these, 56 (73%) also used the activity sensors. The DIGIKOST-FFQ estimates the intake of foods according to the Norwegian food-based dietary guidelines (FBDGs) in addition to lifestyle factors., Results: At the group level, the DIGIKOST-FFQ showed good validity in estimating intakes according to the Norwegian FBDG. The median differences were small and well below portion sizes for all foods except "water" (median difference 230 g/day). The DIGIKOST-FFQ was able to rank individual intakes for all foods (r=0.2-0.7). However, ranking estimates of vegetable intakes should be interpreted with caution. Between 69% and 88% of the participants were classified into the same or adjacent quartile for foods and between 71% and 82% for different activity intensities. The Bland-Altman plots showed acceptable agreements between DIGIKOST-FFQ and the reference methods. The absolute amount of time in "moderate to vigorous intensity" was underestimated with the DIGIKOST-FFQ. However, estimated time in "moderate to vigorous intensity," "vigorous intensity," and "sedentary time" showed acceptable correlations and good agreement between the methods. The DIGIKOST-FFQ was able to identify adherence to the Norwegian FBDG and physical activity recommendations., Conclusions: The DIGIKOST-FFQ gave valid estimates of dietary intakes and was able to identify individuals with different degrees of adherence to the Norwegian FBDG and physical activity recommendations. Moderate physical activity was underreported, water was overreported, and vegetables showed poor correlation, which are important to consider when interpreting the data. Good agreement was observed between the methods in estimating dietary intakes and time in "moderate to vigorous physical activity," "sedentary time," and "sleep.", (©Hege Berg Henriksen, Markus Dines Knudsen, Anette Hjartåker, Rune Blomhoff, Monica Hauger Carlsen. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 30.04.2024.)

Background: Dietary intake assessment is an integral part of addressing suboptimal dietary intakes. Existing food-based methods are time-consuming and burdensome for users to report the individual foods consumed at each meal. However, ease of use is the most important feature for individuals choosing a nutrition or diet app. Intakes of whole meals can be reported in a manner that is less burdensome than reporting individual foods. No study has developed a method of dietary intake assessment where individuals report their dietary intakes as whole meals rather than individual foods., Objective: This study aims to develop a novel, meal-based method of dietary intake assessment and test its ability to estimate nutrient intakes compared with that of a web-based, 24-hour recall (24HR)., Methods: Participants completed a web-based, generic meal-based recall. This involved, for each meal type (breakfast, light meal, main meal, snack, and beverage), choosing from a selection of meal images those that most represented their intakes during the previous day. Meal images were based on generic meals from a previous study that were representative of the actual meal intakes in Ireland. Participants also completed a web-based 24HR. Both methods were completed on the same day, 3 hours apart. In a crossover design, participants were randomized in terms of which method they completed first. Then, 2 weeks after the first dietary assessments, participants repeated the process in the reverse order. Estimates of mean daily nutrient intakes and the categorization of individuals according to nutrient-based guidelines (eg, low, adequate, and high) were compared between the 2 methods. P values of less than .05 were considered statistically significant., Results: In total, 161 participants completed the study. For the 23 nutrient variables compared, the median percentage difference between the 2 methods was 7.6% (IQR 2.6%-13.2%), with P values ranging from <.001 to .97, and out of 23 variables, effect sizes for the differences were small for 19 (83%) variables, moderate for 2 (9%) variables, and large for 2 (9%) variables. Correlation coefficients were statistically significant (P<.05) for 18 (78%) of the 23 variables. Statistically significant correlations ranged from 0.16 to 0.45, with median correlation of 0.32 (IQR 0.25-0.40). When participants were classified according to nutrient-based guidelines, the proportion of individuals who were classified into the same category ranged from 52.8% (85/161) to 84.5% (136/161)., Conclusions: A generic meal-based method of dietary intake assessment provides estimates of nutrient intake comparable with those provided by a web-based 24HR but with varying levels of agreement among nutrients. Further studies are required to refine and improve the generic recall across a range of nutrients. Future studies will consider user experience including the potential feasibility of incorporating image recognition of whole meals into the generic recall., (©Cathal O'Hara, Eileen R Gibney. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 14.02.2024.)

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., (©Marga Ocké, Ceciel Simone Dinnissen, Coline van den Bogaard, Marja Beukers, José Drijvers, Eline Sanderman-Nawijn, Caroline van Rossum, Ido Toxopeus. Originally published in JMIR mHealth and uHealth (https://mhealth.jmir.org), 09.02.2024.)