Validity of image-based dietary assessment methods: A systematic review and meta-analysis

Ho, Dang Khanh Ngan; Tseng, Sung Hui; Meng, Wei; Shih, Chun Kuang; Atika, Anif Prameswari; Chen, Yang Ching; Chang, Jung Su

doi:10.1016/j.clnu.2020.08.002

Cited by 25 publications

(19 citation statements)

References 36 publications

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“…Despite the fact that most technology-based dietary assessment studies employed dieticians/nutritionists to perform IBDAs [ 19 ], little research has explored how dieticians develop their “tele-dietetic” knowledge, or how accurate their IBDA skills are. Our study showed that after repeated training, more than half (59%) of junior students were able to estimate calories within ±20%, and most importantly, that the accuracy of those who were the poorest performers improved.…”

Section: Discussionmentioning

confidence: 99%

“…The IBDA method has been employed to measure intake levels of energy and nutrients in children [ 14 , 15 ], adults [ 16 , 17 ], and the elderly [ 18 ]. A recent meta-analysis and systematic review of the validity of IBDAs showed no statistical difference in energy or macronutrient estimates between IBDA and traditional methods (e.g., WFRs and 24-HDRs); however, IBDAs greatly underestimated energy intake (EI) (−448 kcal) when compared to double-labeled water (DLW), a gold standard method for EI assessments [ 19 ]. Those authors concluded that, like traditional methods, image-based methods have serious measurement errors, and more studies are needed to overcome these problems [ 19 ].…”

Section: Introductionmentioning

confidence: 99%

“…Thus, the ability of dieticians and nutrition practitioners to perform IBDAs is important, as inaccurate food image reviewing may increase measurement errors. Although numerous studies have shown that dieticians and trained human analysts with five years of experience were able to perform IBDAs, few studies have reported on the training dieticians use to develop their digital viewing skills [ 19 ]. It is also not known how long it takes to master the necessary skills or how accurate they are.…”

Section: Introductionmentioning

confidence: 99%

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Integration of an Image-Based Dietary Assessment Paradigm into Dietetic Training Improves Food Portion Estimates by Future Dietitians

Chiu

Lee

et al. 2021

Nutrients

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The use of image-based dietary assessments (IBDAs) has rapidly increased; however, there is no formalized training program to enhance the digital viewing skills of dieticians. An IBDA was integrated into a nutritional practicum course in the School of Nutrition and Health Sciences, Taipei Medical University Taiwan. An online IBDA platform was created as an off-campus remedial teaching tool to reinforce the conceptualization of food portion sizes. Dietetic students’ receptiveness and response to the IBDA, and their performance in food identification and quantification, were compared between the IBDA and real food visual estimations (RFVEs). No differences were found between the IBDA and RFVE in terms of food identification (67% vs. 71%) or quantification (±10% of estimated calories: 23% vs. 24%). A Spearman correlation analysis showed a moderate to high correlation for calorie estimates between the IBDA and RFVE (r ≥ 0.33~0.75, all p < 0.0001). Repeated IBDA training significantly improved students’ image-viewing skills [food identification: first semester: 67%; pretest: 77%; second semester: 84%) and quantification [±10%: first semester: 23%; pretest: 28%; second semester: 32%; and ±20%: first semester: 38%; pretest: 48%; second semester: 59%] and reduced absolute estimated errors from 27% (first semester) to 16% (second semester). Training also greatly improved the identification of omitted foods (e.g., condiments, sugar, cooking oil, and batter coatings) and the accuracy of food portion size estimates. The integration of an IBDA into dietetic courses has the potential to help students develop knowledge and skills related to “e-dietetics”.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Integration of an Image-Based Dietary Assessment Paradigm into Dietetic Training Improves Food Portion Estimates by Future Dietitians

Chiu

Lee

et al. 2021

Nutrients

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“…Thereafter, the image data are analyzed to specify the foods, to estimate portion sizes, and to count the dietary intake. Recent studies suggested that image-based methods could provide more accurate dietary data compared with traditional methods [15]; however, their superiority has not been demonstrated [16]. Image-based dietary records have been found to be feasible and valid dietary assessment methods and comparable to the traditional methods in adults [16][17][18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Agreement between an Image-Based Dietary Assessment Method and a Written Food Diary among Adolescents with Type 1 Diabetes

et al. 2021

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Valid and useful dietary assessment methods for adolescents with type 1 diabetes (T1D) are needed. In this study, we compared an image-based method with a written food diary for dietary intake estimation among adolescents with T1D and evaluated the adolescents’ experiences of the methods. Adolescents with T1D aged 13 to 18 years (n = 13) photographed their meals (n = 264) with a mobile phone camera and simultaneously kept a written food diary for four consecutive days. The participants filled out electronic background and feedback questionnaires. The agreement between the methods was evaluated using intraclass correlation coefficients (ICCs) and Bland–Altman plot analyses. The agreement between the methods was moderate to excellent for the energy intake (ICC = 0.91, 95% confidence interval (CI): 0.66 to 0.97, p < 0.001) and good to excellent for total carbohydrate intake (ICC = 0.95, 95% CI: 0.84 to 0.99, p < 0.001). The adolescents considered photographing easier and faster than keeping a food diary. In conclusion, the image-based method appeared comparable to the food diary for dietary intake estimation among adolescents with T1D. The photographing of meals may become a useful dietary assessment tool for adolescents with T1D, but must be further developed and validated.

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“…Traditional methods, such as self-reported 24-hour dietary recall, have significantly underreported energy intake when compared with 7-day food weigh records [ 34 ]. A systematic review and meta-analysis study found that image-based dietary assessments underestimated energy intake by 20% (range 0%-37%) when compared with the doubly labeled water method; however, the study showed no significant difference in energy intakes estimated via traditional methods (such as 24-hour dietary recall) and the RFPM [ 35 ]. We observed in this pilot study that the CI for the mean difference in energy intake estimations between the two methods—the PortionSize app and weigh back—crossed 0 (Table S2 in Multimedia Appendix 1 ).…”

Section: Discussionmentioning

confidence: 99%

Assessing the Initial Validity of the PortionSize App to Estimate Dietary Intake Among Adults: Pilot and Feasibility App Validation Study

Saha¹,

Panizza²,

Broyles³

et al. 2022

JMIR Form Res

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Background Accurately assessing dietary intake can promote improved nutrition. The PortionSize app (Pennington Biomedical Research Center) was designed to quantify and provide real-time feedback on the intake of energy, food groups, saturated fat, and added sugar. Objective This study aimed to assess the preliminary feasibility and validity of estimating food intake via the PortionSize app among adults. Methods A total of 15 adults (aged 18-65 years) were recruited and trained to quantify the food intake from a simulated meal by using PortionSize. Trained personnel prepared 15 simulated meals and covertly weighed (weigh back) the amount of food provided to participants as well as food waste. Equivalence tests (±25% bounds) were performed to compare PortionSize to the weigh back method. Results Participants were aged a mean of 28 (SD 12) years, and 11 were female. The mean energy intake estimated with PortionSize was 742.9 (SD 328.2) kcal, and that estimated via weigh back was 659.3 (SD 190.7) kcal (energy intake difference: mean 83.5, SD 287.5 kcal). The methods were not equivalent in estimating energy intake (P=.18), and PortionSize overestimated energy intake by 83.5 kcal (12.7%) at the meal level. Estimates of portion sizes (gram weight; P=.01), total sugar (P=.049), fruit servings (P=.01), and dairy servings (P=.047) from PortionSize were equivalent to those estimated via weigh back. PortionSize was not equivalent to weigh back with regard to estimates for carbohydrate (P=.10), fat (P=.32), vegetable (P=.37), grain (P=.31), and protein servings (P=.87). Conclusions Due to power limitations, the equivalence tests had large equivalence bounds. Though preliminary, the results of this small pilot study warrant the further adaptation, development, and validation of PortionSize as a means to estimate energy intake and provide users with real-time and actionable dietary feedback.

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Validity of image-based dietary assessment methods: A systematic review and meta-analysis

Cited by 25 publications

References 36 publications

Integration of an Image-Based Dietary Assessment Paradigm into Dietetic Training Improves Food Portion Estimates by Future Dietitians

Integration of an Image-Based Dietary Assessment Paradigm into Dietetic Training Improves Food Portion Estimates by Future Dietitians

Agreement between an Image-Based Dietary Assessment Method and a Written Food Diary among Adolescents with Type 1 Diabetes

Assessing the Initial Validity of the PortionSize App to Estimate Dietary Intake Among Adults: Pilot and Feasibility App Validation Study

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