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Liang Y, Xiao R, Huang F, Lin Q, Guo J, Zeng W, Dong J. AI nutritionist: Intelligent software as the next generation pioneer of precision nutrition. Comput Biol Med 2024; 178:108711. [PMID: 38852397 DOI: 10.1016/j.compbiomed.2024.108711] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Revised: 04/21/2024] [Accepted: 06/03/2024] [Indexed: 06/11/2024]
Abstract
With the rapid development of information technology and artificial intelligence (AI), people have acquired the abilities and are encouraged to develop intelligent tools and software, which begins to shed light on intelligent and precise food nutrition. Despite the rapid development of such software, disparities still exist in terms of methodology, contents, and implementation strategies. Hence, a set of panoramic profiles is urgently needed to elucidate their values and guide their future development. Here a comprehensive review was conducted aiming to summarize and compare the objects, contents, intelligent algorithms, and functions realized by the already released software in current research. Consequently, 177 AI nutritionists in recent years were collected and analyzed. The advantages, limitations, and trends concerning their application scenarios were analyzed. It was found that AI nutritionists have been gradually advancing the production modes and efficiency of food recognition, dietary recording/monitoring, nutritional assessment, and nutrient/recipe recommendation. Most AI nutritionists have a relatively low level of intelligence. However, new trends combining advanced AI algorithms, intelligent sensors and big data are coming with new applications in real-time and precision nutrition. AI models concerning molecular-level behaviors are becoming the new focus to drive AI nutritionists. Multi-center and multi-level studies have also gradually been realized to be necessary.
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Affiliation(s)
- Ying Liang
- National Engineering Research Center of Deep Processing of Rice and Byproducts, College of Food Science and Engineering, Central South University of Forestry and Technology, Changsha, 410004, PR China
| | - Ran Xiao
- National Engineering Research Center of Deep Processing of Rice and Byproducts, College of Food Science and Engineering, Central South University of Forestry and Technology, Changsha, 410004, PR China; SINOCARE Inc., Changsha, 410004, PR China
| | - Fang Huang
- National Engineering Research Center of Deep Processing of Rice and Byproducts, College of Food Science and Engineering, Central South University of Forestry and Technology, Changsha, 410004, PR China
| | - Qinlu Lin
- National Engineering Research Center of Deep Processing of Rice and Byproducts, College of Food Science and Engineering, Central South University of Forestry and Technology, Changsha, 410004, PR China
| | - Jia Guo
- Xiangya Nursing School, Central South University, Changsha, 410004, PR China
| | - Wenbin Zeng
- Xiangya School of Pharmaceutical Sciences, Central South University, Changsha, 410004, PR China
| | - Jie Dong
- Xiangya School of Pharmaceutical Sciences, Central South University, Changsha, 410004, PR China.
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Whitton C, Ramos-García C, Kirkpatrick SI, Healy JD, Dhaliwal SS, Boushey CJ, Collins CE, Rollo ME, Kerr DA. A Systematic Review Examining Contributors to Misestimation of Food and Beverage Intake Based on Short-Term Self-Report Dietary Assessment Instruments Administered to Adults. Adv Nutr 2022; 13:2620-2665. [PMID: 36041186 PMCID: PMC9776649 DOI: 10.1093/advances/nmac085] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 07/15/2022] [Accepted: 08/02/2022] [Indexed: 01/29/2023] Open
Abstract
Error in self-reported food and beverage intake affects the accuracy of dietary intake data. Systematically synthesizing available data on contributors to error within and between food groups has not been conducted but may help inform error mitigation strategies. In this review we aimed to systematically identify, quantify, and compare contributors to error in estimated intake of foods and beverages, based on short-term self-report dietary assessment instruments, such as 24-h dietary recalls and dietary records. Seven research databases were searched for studies including self-reported dietary assessment and a comparator measure of observed intake (e.g., direct observation or controlled feeding studies) in healthy adults up until December 2021. Two reviewers independently screened and extracted data from included studies, recording quantitative data on omissions, intrusions, misclassifications, and/or portion misestimations. Risk of bias was assessed using the QualSyst tool. A narrative synthesis focused on patterns of error within and between food groups. Of 2328 articles identified, 29 met inclusion criteria and were included, corresponding to 2964 participants across 15 countries. Most frequently reported contributors to error were omissions and portion size misestimations of food/beverage items. Although few consistent patterns were seen in omission of consumed items, beverages were omitted less frequently (0-32% of the time), whereas vegetables (2-85%) and condiments (1-80%) were omitted more frequently than other items. Both under- and overestimation of portion size was seen for most single food/beverage items within study samples and most food groups. Studies considered and reported error in different ways, impeding the interpretation of how error contributors interact to impact overall misestimation. We recommend that future studies report 1) all error contributors for each food/beverage item evaluated (i.e., omission, intrusion, misclassification, and portion misestimation), and 2) measures of variation of the error. The protocol of this review was registered in PROSPERO as CRD42020202752 (https://www.crd.york.ac.uk/prospero/).
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Affiliation(s)
- Clare Whitton
- Curtin School of Population Health, Curtin University, Perth, WA, Australia
- Curtin Health Innovation Research Institute, Curtin University, Perth, WA, Australia
| | - César Ramos-García
- Curtin School of Population Health, Curtin University, Perth, WA, Australia
- Division of Health Sciences, Tonalá University Center, University of Guadalajara, Guadalajara, Mexico
| | | | - Janelle D Healy
- Curtin School of Population Health, Curtin University, Perth, WA, Australia
- Curtin Health Innovation Research Institute, Curtin University, Perth, WA, Australia
| | - Satvinder S Dhaliwal
- Curtin Health Innovation Research Institute, Curtin University, Perth, WA, Australia
- Duke-NUS Medical School, National University of Singapore, Singapore
- Institute for Research in Molecular Medicine (INFORMM), Universiti Sains Malaysia, Pulau Pinang, Malaysia
- Singapore University of Social Sciences, Singapore
| | - Carol J Boushey
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Clare E Collins
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW, Australia
- Food and Nutrition Research Program, Hunter Medical Research Institute, New Lambton, NSW, Australia
| | - Megan E Rollo
- Curtin School of Population Health, Curtin University, Perth, WA, Australia
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Development of a Digital Photographic Food Atlas as a Portion Size Estimation Aid in Japan. Nutrients 2022; 14:nu14112218. [PMID: 35684017 PMCID: PMC9182677 DOI: 10.3390/nu14112218] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2022] [Revised: 05/18/2022] [Accepted: 05/23/2022] [Indexed: 11/22/2022] Open
Abstract
This study aimed to develop a digital photographic food atlas as a portion size estimation aid. Commonly consumed foods were identified from the 5512-day weighed dietary records of 644 Japanese adults. Portion sizes were determined based on the market research and distribution of food consumption in the dietary records. Each food item was classified into one of two photo types: a series of photographs showing gradually increasing portion sizes or guide photographs representing a range of portion sizes and food varieties in one photograph. Photographs of the food were taken at an angle of 42°, along with appropriate reference objects such as chopsticks. In total, 209 food and dish items were included in the food atlas. Series of photographs were taken for 105 items that are not usually served in predetermined amounts (e.g., rice and pasta), whereas guide photographs were taken for 104 items usually served in predetermined amounts (e.g., bananas and cookies). Moreover, photographs were taken for 12 kinds of household measurement items, such as cups and glasses. The food atlas could be a valuable tool for estimating the portion size in dietary surveys. Evaluating the validity of this food atlas for portion size estimation is warranted.
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Zuppinger C, Taffé P, Burger G, Badran-Amstutz W, Niemi T, Cornuz C, Belle FN, Chatelan A, Paclet Lafaille M, Bochud M, Gonseth Nusslé S. Performance of the Digital Dietary Assessment Tool MyFoodRepo. Nutrients 2022; 14:635. [PMID: 35276994 PMCID: PMC8838173 DOI: 10.3390/nu14030635] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 01/26/2022] [Accepted: 01/27/2022] [Indexed: 12/10/2022] Open
Abstract
Digital dietary assessment devices could help overcome the limitations of traditional tools to assess dietary intake in clinical and/or epidemiological studies. We evaluated the accuracy of the automated dietary app MyFoodRepo (MFR) against controlled reference values from weighted food diaries (WFD). MFR's capability to identify, classify and analyze the content of 189 different records was assessed using Cohen and uniform kappa coefficients and linear regressions. MFR identified 98.0% ± 1.5 of all edible components and was not affected by increasing numbers of ingredients. Linear regression analysis showed wide limits of agreement between MFR and WFD methods to estimate energy, carbohydrates, fat, proteins, fiber and alcohol contents of all records and a constant overestimation of proteins, likely reflecting the overestimation of portion sizes for meat, fish and seafood. The MFR mean portion size error was 9.2% ± 48.1 with individual errors ranging between -88.5% and +242.5% compared to true values. Beverages were impacted by the app's difficulty in correctly identifying the nature of liquids (41.9% ± 17.7 of composed beverages correctly classified). Fair estimations of portion size by MFR, along with its strong segmentation and classification capabilities, resulted in a generally good agreement between MFR and WFD which would be suited for the identification of dietary patterns, eating habits and regime types.
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Affiliation(s)
- Claire Zuppinger
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, 1010 Lausanne, Switzerland; (P.T.); (G.B.); (W.B.-A.); (T.N.); (C.C.); (F.N.B.); (M.B.); (S.G.N.)
| | - Patrick Taffé
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, 1010 Lausanne, Switzerland; (P.T.); (G.B.); (W.B.-A.); (T.N.); (C.C.); (F.N.B.); (M.B.); (S.G.N.)
| | - Gerrit Burger
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, 1010 Lausanne, Switzerland; (P.T.); (G.B.); (W.B.-A.); (T.N.); (C.C.); (F.N.B.); (M.B.); (S.G.N.)
| | - Wafa Badran-Amstutz
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, 1010 Lausanne, Switzerland; (P.T.); (G.B.); (W.B.-A.); (T.N.); (C.C.); (F.N.B.); (M.B.); (S.G.N.)
| | - Tapio Niemi
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, 1010 Lausanne, Switzerland; (P.T.); (G.B.); (W.B.-A.); (T.N.); (C.C.); (F.N.B.); (M.B.); (S.G.N.)
| | - Clémence Cornuz
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, 1010 Lausanne, Switzerland; (P.T.); (G.B.); (W.B.-A.); (T.N.); (C.C.); (F.N.B.); (M.B.); (S.G.N.)
| | - Fabiën N. Belle
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, 1010 Lausanne, Switzerland; (P.T.); (G.B.); (W.B.-A.); (T.N.); (C.C.); (F.N.B.); (M.B.); (S.G.N.)
- Institute of Social and Preventive Medicine (ISPM), University of Bern, 3012 Bern, Switzerland;
| | - Angeline Chatelan
- Institute of Social and Preventive Medicine (ISPM), University of Bern, 3012 Bern, Switzerland;
- Department of Nutrition and Dietetics, School of Health Sciences (HEdS-GE), University of Applied Sciences and Arts Western Switzerland (HES-SO), 1227 Carouge, Switzerland
| | - Muriel Paclet Lafaille
- Department of Endocrinology, Diabetology and Metabolism, Lausanne University Hospital (CHUV), 1011 Lausanne, Switzerland;
| | - Murielle Bochud
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, 1010 Lausanne, Switzerland; (P.T.); (G.B.); (W.B.-A.); (T.N.); (C.C.); (F.N.B.); (M.B.); (S.G.N.)
| | - Semira Gonseth Nusslé
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, 1010 Lausanne, Switzerland; (P.T.); (G.B.); (W.B.-A.); (T.N.); (C.C.); (F.N.B.); (M.B.); (S.G.N.)
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Accuracy of estimates of serving size using digitally displayed food photographs among Japanese adults. J Nutr Sci 2022; 11:e105. [PMID: 36452397 PMCID: PMC9705702 DOI: 10.1017/jns.2022.102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Accepted: 10/17/2022] [Indexed: 11/25/2022] Open
Abstract
We evaluated the accuracy of the estimated serving size using digital photographs in a newly developed food atlas. From 209 food items in the food atlas, we selected 14 items with various appearances for evaluation. At the study site, fifty-four participants aged 18-33 years were served fourteen foods in the amount they usually ate. After they left, each food item was weighed by a researcher. The following day, the participants estimated the quantity of each food they served based on food photographs using a web-based questionnaire. We compared the weights of the foods the participants served (true serving sizes) and those determined based on the photographs (estimated serving sizes). For ten of the fourteen food items, significant differences were observed between the estimated and true serving sizes, ranging from a 29⋅8 % underestimation (curry sauce) to a 34⋅0 % overestimation (margarine). On average, the relative difference was 8⋅8 %. Overall, 51⋅6 % of the participants were within ±25 % of the true serving size, 81⋅9 % were within ±50 % and 93⋅4 % were within ±75 %. Bland-Altman plots showed wide limits of agreement and increased variances with larger serving sizes for most food items. Overall, no association was found between estimation errors and participant characteristics. The food atlas has shown potential for assessment of portion size estimation. Further development, refinement and testing are needed to improve the usefulness of the digital food photographic atlas as a portion size estimation aid.
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Ding Y, Yang Y, Li F, Shao Y, Sun Z, Zhong C, Fan P, Li Z, Zhang M, Li X, Jiang T, Song C, Chen D, Peng X, Yin L, She Y, Wang Z. Development and validation of a photographic atlas of food portions for accurate quantification of dietary intakes in China. J Hum Nutr Diet 2021; 34:604-615. [PMID: 33406287 PMCID: PMC8246756 DOI: 10.1111/jhn.12844] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Revised: 10/28/2020] [Accepted: 11/03/2020] [Indexed: 01/26/2023]
Abstract
BACKGROUND Accurate estimation of food portion sizes remains an important challenge in dietary data collection. The present study aimed to develop a food atlas with adequate visual reference to improve the accuracy of dietary surveys in China. METHODS A food atlas for dietary surveys in China was developed using three visual reference systems, namely, regularly placed food portions, the two-dimensional background coordinates and common objects known in daily life. The atlas was validated by estimating a meal before and after using the food atlas, and differences in weight estimation were compared using a paired t-test. In total, 50 college students participated in the study. RESULTS After determination of food varieties; design of the food display; purchase, processing, cooking and weighing of food; photographing food; post-image processing and data processing, a total of 799 pictures of 303 types of food and two types of tableware were produced. The mean value of food weight estimated with the atlas was closer to the actual weight, and the variation range of these values was smaller and more stable than that estimated without the atlas. The differences estimated before and after using the atlas for all foods were significant (P < 0.05). Comparing the differences in weight before using the atlas, the error ranges of food samples were reduced. CONCLUSIONS A food atlas has been developed for a retrospective dietary survey in China, which can be used to enable a better understanding of nutritional adequacy in the Chinese population.
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Affiliation(s)
- Ye Ding
- Department of Maternal, Child and Adolescent HealthSchool of Public HealthNanjing Medical UniversityNanjingChina
| | - Yue Yang
- Department of Maternal, Child and Adolescent HealthSchool of Public HealthNanjing Medical UniversityNanjingChina
| | - Fang Li
- Department of Maternal, Child and Adolescent HealthSchool of Public HealthNanjing Medical UniversityNanjingChina
| | | | - Zhongqing Sun
- Qingdao Municipal Center for Disease Control & PreventionQingdaoChina
| | - Chunmei Zhong
- Department of NutritionThe Affiliated Hospital of Qingdao UniversityQingdaoChina
| | - Ping Fan
- Changzhou Center for Disease Control and PreventionChangzhouChina
| | - Zuwen Li
- Kun Shan Market Regulatory AdministrationSuzhouChina
| | - Man Zhang
- Department of Nutrition and Food HygieneSchool of Public HealthPeking UniversityBeijingChina
| | - Xiaocheng Li
- Nanjing Municipal Center for Disease Control and PreventionNanjingChina
| | | | - Chenglin Song
- The Second People's Hospital of LianyungangLianyungangChina
| | - Dandan Chen
- Huai'an Maternal and Child Health CenterHuai'anChina
| | - Xiaoju Peng
- Suzhou Maternal and Child Health Care & Family Planning Service CenterSuzhouChina
| | - Lu Yin
- Nanjing Brain HospitalNanjingChina
| | - Yuanhong She
- Department of Maternal, Child and Adolescent HealthSchool of Public HealthNanjing Medical UniversityNanjingChina
| | - Zhixu Wang
- Department of Maternal, Child and Adolescent HealthSchool of Public HealthNanjing Medical UniversityNanjingChina
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Faerber EC, Stein AD, Webb Girard A. Portion size and consistency as indicators of complementary food energy intake. MATERNAL AND CHILD NUTRITION 2021; 17:e13121. [PMID: 33533154 PMCID: PMC7988842 DOI: 10.1111/mcn.13121] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Revised: 11/14/2020] [Accepted: 11/19/2020] [Indexed: 01/03/2023]
Abstract
We evaluated whether novel portion size and consistency indicators can identify children with low complementary food energy intake in southern Ethiopia. We conducted 24-h dietary recalls with caregivers of 548 children aged 6-13 months; additionally, caregivers estimated their child's usual portion size using uncooked rice and selected which of five photographs of porridges of varying consistencies most closely matched the food their child usually ate. Complementary food energy and density from the 24-h recall were used as reference values. We computed correlation coefficients and areas under receiver operating characteristic curves (AUC) and conducted sensitivity and specificity analyses to classify children with low complementary food energy intake. The median complementary food energy intakes for children 6-8, 9-11 and 12-13 months were 312, 322 and 375 kcal; median estimated portion sizes were 50, 58 and 64 ml, respectively. Estimated portion size correlated with total complementary food energy intake and with average energy and quantity consumed per feeding (r = 0.42, 0.46 and 0.45, respectively, all p < 0.001). Reported food consistency was weakly correlated with total complementary food energy intake (r = 0.18) and density (r = 0.10), and energy density of porridge only (r = 0.24, all p < 0.05). Predicted energy intake combining feeding frequency and portion size predicted inadequate energy intake better than did feeding frequency alone in infants 6-8 months [∆AUC = 0.16, 95% confidence interval (CI) 0.04, 0.28] and 9-11 months (∆AUC = 0.09, 95% CI 0.04, 0.14). Caregiver estimates of portion size can improve identification of infants with low complementary food energy intake when more robust dietary assessment is not feasible.
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Affiliation(s)
- Emily C Faerber
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
| | - Aryeh D Stein
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
| | - Amy Webb Girard
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
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Validation of a life-logging wearable camera method and the 24-h diet recall method for assessing maternal and child dietary diversity. Br J Nutr 2020; 125:1299-1309. [PMID: 32912365 DOI: 10.1017/s0007114520003530] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Accurate and timely data are essential for identifying populations at risk for undernutrition due to poor-quality diets, for implementing appropriate interventions and for evaluating change. Life-logging wearable cameras (LLWC) have been used to prospectively capture food/beverage consumed by adults in high-income countries. This study aimed to evaluate the concurrent criterion validity, for assessing maternal and child dietary diversity scores (DDS), of a LLWC-based image-assisted recall (IAR) and 24-h recall (24HR). Direct observation was the criterion method. Food/beverage consumption of rural Eastern Ugandan mothers and their 12-23-month-old child (n 211) was assessed, for the same day for each method, and the IAR and 24HR DDS were compared with the weighed food record DDS using the Bland-Altman limits of agreement (LOA) method of analysis and Cohen's κ. The relative bias was low for the 24HR (-0·1801 for mothers; -0·1358 for children) and the IAR (0·1227 for mothers; 0·1104 for children), but the LOA were wide (-1·6615 to 1·3012 and -1·6883 to 1·4167 for mothers and children via 24HR, respectively; -2·1322 to 1·8868 and -1·7130 to 1·4921 for mothers and children via IAR, respectively). Cohen's κ, for DDS via 24HR and IAR, was 0·68 and 0·59, respectively, for mothers, and 0·60 and 0·59, respectively, for children. Both the 24HR and IAR provide an accurate estimate of median dietary diversity, for mothers and their young child, but non-differential measurement error would attenuate associations between DDS and outcomes, thereby under-estimating the true associations between DDS - where estimated via 24HR or IAR - and outcomes measured.
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Abstract
OBJECTIVE To investigate preferences for and ease-of-use perceptions of different aspects of printed and digitally displayed photographic portion-size estimation aids (PSEA) in a low-resource setting and to document accuracy of portion-size selections using PSEA with different visual characteristics. DESIGN A convergent mixed-methods design and stepwise approach were used to assess characteristics of interest in isolation. Participants served themselves food and water, which were weighed before and after consumption to measure leftovers and quantity consumed. Thirty minutes later, data collectors administered a meal recall using a PSEA and then a semi-structured interview. SETTING Blantyre and Chikwawa Districts in the southern region of Malawi. PARTICIPANTS Ninety-six women, aged 18-45 years. RESULTS Preferences and ease-of-use perceptions favoured photographs rather than drawings of shapes, three and five portion-size options rather than three with four virtual portion-size options, a 45° rather than a 90° photograph angle, and simultaneous rather than sequential presentation of portion-size options. Approximately half to three-quarters of participants found the portion-size options represented appropriate amounts of foods or water consumed. Photographs with three portion sizes resulted in more accurate portion-size selections (closest to measured consumption) than other format and number of portion-size option combinations. A 45° angle and simultaneous presentation were more accurate than a 90° angle and sequential presentation of images. CONCLUSIONS Results from testing PSEA visual characteristics separately can be used to generate optimal PSEA, which can improve participants' experiences during meal recalls.
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