Experience Sampling as a dietary assessment method: a scoping review towards implementation

Children are vulnerable to developing iron deficiency anemia, especially in resource-limited settings. Information on habitual dietary intake informs dietary interventions aimed at improving iron deficiency. Dietary assessment in school-aged children is challenging and requires concerted efforts to mitigate the pitfalls of long complex methods. Nested within an intervention trial, we aimed to obtain dietary intake information to assess iron nutrition in 8 to 13-year-old children from resource-limited settings in Cape Town, South Africa. Following careful consideration of the study objective, participant characteristics, research setting, available resources, and features of the different dietary intake assessment methods, we identified an iron quantified food frequency questionnaire (QFFQ) as the best method to obtain the information. The QFFQ reflected the study population’s habitual intake and the nutrients of interest (protein, iron, vitamin A, vitamin C, calcium, zinc, and fiber). In addition, strategies such as interview-administration of the QFFQ, interviewing the child participant and caregiver together, simplifying frequency reporting, a strategic food list order and a variety of interesting portion size estimation aids collectively supported dietary intake assessment in this young study population. Using a methodical, multiphase approach and strategies that promote participant engagement, we developed the QFFQ, achieved interview success, and obtained comparable data.

Different methods of dietary intake assessment are frequently used to assess a population's diet. In this study, we aimed to compare the adherence to Swiss food-based dietary guidelines as depicted in two Swiss population-based surveys using different methods of dietary assessment. Two population-based, cross-sectional surveys were compared. In the Swiss Health Survey (SHS), diet was assessed via a short set of questions on specific food groups, while in menuCH by two non-consecutive 24-h dietary recall interviews. To compare the diet depicted in these surveys, we used the Swiss food-based dietary guidelines on vegetable, fruit, dairy product, meat and meat product, fish and alcohol. The weighted proportion of responders meeting these guidelines was calculated for both surveys and was compared overall and by selected characteristics. Residents of Switzerland, selected from a stratified random sample of the non-institutionalised residents, who agreed to participate in the respective survey. To ensure comparability between the surveys, the age of the study populations was restricted to 18-75 years. In menuCH, approximately 2 % of responders met ≥4 of the selected Swiss food-based dietary guidelines. In the SHS, using a cruder dietary assessment, the corresponding percentage was 20 %. In both surveys, more women and never smokers were meeting ≥4 food-based dietary guidelines compared to men and current or former smokers, respectively. Our study comparing the diet in two population-based, representative surveys detected large variations in guideline adherence depending on the dietary assessment method used.

BackgroundNew methods for assessing diet in research are being developed to address the limitations of traditional dietary assessment methods. Mobile device–assisted ecological momentary diet assessment (mEMDA) is a new dietary assessment method that has not yet been optimized and has the potential to minimize recall biases and participant burden while maximizing ecological validity. There have been limited efforts to characterize the use of mEMDA in behavioral research settings.ObjectiveThe aims of this study were to summarize mEMDA protocols used in research to date, to characterize key aspects of these assessment approaches, and to discuss the advantages and disadvantages of mEMDA compared with the traditional dietary assessment methods as well as implications for future mEMDA research.MethodsStudies that used mobile devices and described mEMDA protocols to assess dietary intake were included. Data were extracted according to Preferred Reporting of Systematic Reviews and Meta-Analyses and Cochrane guidelines and then synthesized narratively.ResultsThe review included 20 studies with unique mEMDA protocols. Of these, 50% (10/20) used participant-initiated reports of intake at eating events (event-contingent mEMDA), and 50% (10/20) used researcher-initiated prompts requesting that participants report recent dietary intake (signal-contingent mEMDA). A majority of the study protocols (60%, 12/20) enabled participants to use mobile phones to report dietary data. Event-contingent mEMDA protocols most commonly assessed diet in real time, used dietary records for data collection (60%, 6/10), and provided estimates of energy and nutrient intake (60%, 6/10). All signal-contingent mEMDA protocols used a near real-time recall approach with unannounced (ie, random) abbreviated diet surveys. Most signal-contingent protocols (70%, 7/10) assessed the frequency with which (targeted) foods or food groups were consumed. Relatively few (30%, 6/20) studies compared mEMDA with the traditional dietary assessment methods.ConclusionsThis review demonstrates that mEMDA has the potential to reduce participant burden and recall bias, thus advancing the field beyond current dietary assessment methods while maximizing ecological validity.

BackgroundThe quest towards more feasible, low-cost yet accurate dietary assessment methods has led to the development of the new Experience Sampling-based Dietary Assessment Method (ESDAM). ESDAM is an app-based quantitative dietary assessment method to assess habitual dietary intake over a period of 2 weeks. ESDAM prompts three 2-hour recalls daily requesting to provide dietary intake on meal and food group level. The ESDAM allows to measure dietary intake near real-time in a rapid, low-cost and feasible manner. Following the user experience evaluation of the ESDAM, the validity of the ESDAM will now be assessed against objective biomarkers.MethodsThis protocol describes the validation of the ESDAM against three 24-hour dietary recalls (24-HDR), doubly labeled water, urinary nitrogen, serum carotenoids, and erythrocyte membrane fatty acids. The primary outcomes include energy intake and protein intake measured by the ESDAM in relation to energy expenditure measured by the doubly labeled water method and protein intake derived from urinary nitrogen analysis respectively. Secondary outcomes include nutrient and food group consumption derived from ESDAM and repeated 24-HDR’s, beta-carotenoids as biomarker of fruit and vegetable consumption and erythrocyte membrane fatty acid composition as biomarker of dietary fatty acid composition. Blinded continuous glucose monitoring will serve as method to assess compliance to ESDAM prompts. A target sample of 115 healthy volunteers will be recruited. Validity will be evaluated by mean differences and spearman correlations between nutrient and biomarker reference values. Bland-Altman plots will be developed to assess agreement. Method of triads will allow quantifying measurement error of the ESDAM, 24-HDR’s and biomarkers in relation to the (unknown) ‘true dietary intake’.DiscussionThis protocol describes an extensive validation study of a newly developed Experience Sampling-based Dietary Assessment Method against both self-reported and objective reference methods. The main strength is the use of the state-of-the-art validation techniques using doubly labeled water, urinary nitrogen, carotenoids and erythrocyte membrane fatty acids as biomarkers for dietary intake. A limitation of the study is that the evaluation of reproducibility of the ESDAM is not included.RegistrationThis study is registered at ClinicalTrials.gov on (NCT06485960, date: 07/02/2024).

The effectiveness of the tailored feedback in digital interventions may be limited by the quality of the dietary assessment (DA) upon which it is based. The present study systematically reviewed studies reporting the protocols for DA methods used to inform tailored feedback in digital weight loss interventions. The search included: PubMed-National Library of Medicine database, MEDLINE, Cochrane Library of Systematic Reviews, Web of Science and ProQuest. Search terms were related to five groups: dietary assessment, weight loss, clinical trials, technology and tailoring. Thirteen articles were eligible for inclusion. The most common DA method was a digital dietary record linked to a food database that provided instant feedback on daily energy intake. Only four studies provided feedback on overall diet quality and intake of fruit, vegetables and fibre. Dietary feedback was provided using text messages, email, mobile applications and online intervention websites. Most digital dietary feedback focused on reducing energy intake without providing feedback to enhance diet quality. This review highlighted the heterogeneity in DA methods used in tailored weight loss interventions, which may account for the range of outcome results reported. Future interventions should publish the protocols describing how dietary data was collected and used to inform dietary feedback.

Chapter 45 - Assessment of Iodine Intake and Iodine Status in Vegans

Understanding the dietary intake of people with kidney disease is fundamental to addressing their treatment or for the prevention or progression of disease. Several recent guidelines on chronic kidney disease (CKD) vary on recommendations for assessing the dietary intake of patients (Table 3.1) [1–8]. Whether the approach to assessing dietary intake is considered warranted is not discussed in these guidelines, so perhaps it is not an issue of the reliability of dietary intake assessment methods but rather one of the origin of the guidelines. For example, the guidelines from the National Kidney Foundation Kidney Disease Outcomes Quality Initiative (NKF KDOQI) on nutrition [1] are written to be multidisciplinary and include guidelines for dietitians. The guidelines for CKD that were produced by the Academy of Nutrition and Dietetics are written specifically for dietitians [4]. However, many of the other guidelines for CKD are physician specific, and obtaining the dietary record is not included in their guidelines, perhaps because physicians do not normally collect this information. In contrast, assessment of dietary intake is a significant practice of dietetics, and they routinely evaluate dietary intake in assessing the nutritional status of patients.

Malnutrition is a common and severe problem in patients with cancer that directly increases the incidence of complications and significantly deteriorates quality of life. Nutritional risk screening and dietary assessment are critical because they are the basis for providing personalized nutritional support. No digital smartphone-based self-administered tool for nutritional risk screening and dietary assessment among hospitalized patients with cancer has been developed and evaluated. This study aims to develop a digital smartphone-based self-administered mini program for nutritional risk screening and dietary assessment for hospitalized patients with cancer and to evaluate the validity of the mini program. We have developed the R+ Dietitian mini program, which consists of 3 parts: (1) collection of basic information of patients, (2) nutritional risk screening, and (3) dietary energy and protein assessment. The face-to-face paper-based Nutritional Risk Screening (NRS-2002), the Patient-Generated Subjective Global Assessment Short Form (PG-SGA-SF), and 3 days of 24-hour dietary recall (3d-24HRs) questionnaires were administered according to standard procedure by 2 trained dietitians as the reference methods. Sensitivity, specificity, positive predictive value, negative predictive value, κ value, and correlation coefficients (CCs) of nutritional risk screened in R+ Dietitian against the reference methods, as well as the difference and CCs of estimated dietary energy and protein intakes between R+ Dietitian and 3d-24HRs were calculated to evaluate the validity of R+ Dietitian. A total of 244 hospitalized patients with cancer were recruited to evaluate the validity of R+ Dietitian. The NRS-2002 and PG-SGA-SF tools in R+ Dietitian showed high accuracy, sensitivity, and specificity (77.5%, 81.0%, and 76.7% and 69.3%, 84.5%, and 64.5%, respectively), and fair agreement (κ=0.42 and 0.37, respectively; CC 0.62 and 0.56, respectively) with the NRS-2002 and PG-SGA-SF tools administered by dietitians. The estimated intakes of dietary energy and protein were significantly higher (P<.001 for both) in R+ Dietitian (mean difference of energy intake: 144.2 kcal, SD 454.8; median difference of protein intake: 10.7 g, IQR 9.5-39.8), and showed fair agreement (CC 0.59 and 0.47, respectively), compared with 3d-24HRs performed by dietitians. The identified nutritional risk and assessment of dietary intakes of energy and protein in R+ Dietitian displayed a fair agreement with the screening and assessment conducted by dietitians. R+ Dietitian has the potential to be a tool for nutritional risk screening and dietary intake assessment among hospitalized patients with cancer. Chinese Clinical Trial Registry ChiCTR1900026324; https://www.chictr.org.cn/showprojen.aspx?proj=41528.

Worldwide, in 2014, more than 1.9 billion adults, 18 years and older, were overweight. Of these, over 600 million were obese. Accurately documenting dietary caloric intake is crucial to manage weight loss, but also presents challenges because most of the current methods for dietary assessment must rely on memory to recall foods eaten. The ultimate goal of our research is to develop computer-aided technical solutions to enhance and improve the accuracy of current measurements of dietary intake. Our proposed system in this paper aims to improve the accuracy of dietary assessment by analyzing the food images captured by mobile devices (e.g., smartphone). The key technique innovation in this paper is the deep learning-based food image recognition algorithms. Substantial research has demonstrated that digital imaging accurately estimates dietary intake in many environments and it has many advantages over other methods. However, how to derive the food information (e.g., food type and portion size) from food image effectively and efficiently remains a challenging and open research problem. We propose a new Convolutional Neural Network (CNN)-based food image recognition algorithm to address this problem. We applied our proposed approach to two real-world food image data sets (UEC-256 and Food-101) and achieved impressive results. To the best of our knowledge, these results outperformed all other reported work using these two data sets. Our experiments have demonstrated that the proposed approach is a promising solution for addressing the food image recognition problem. Our future work includes further improving the performance of the algorithms and integrating our system into a real-world mobile and cloud computing-based system to enhance the accuracy of current measurements of dietary intake.

Controversies regarding the putative health effects of dietary sugar, salt, fat, and cholesterol are not driven by legitimate differences in scientific inference from valid evidence, but by a fictional discourse on diet-disease relations driven by decades of deeply flawed and demonstrably misleading epidemiologic research. Over the past 60 years, epidemiologists published tens of thousands of reports asserting that dietary intake was a major contributing factor to chronic non-communicable diseases despite the fact that epidemiologic methods do not measure dietary intake. In lieu of measuring actual dietary intake, epidemiologists collected millions of unverified verbal and textual reports of memories of perceptions of dietary intake. Given that actual dietary intake and reported memories of perceptions of intake are not in the same ontological category, epidemiologists committed the logical fallacy of “Misplaced Concreteness.” This error was exacerbated when the anecdotal (self-reported) data were impermissibly transformed (i.e., pseudo-quantified) into proxy-estimates of nutrient and caloric consumption via the assignment of “reference” values from databases of questionable validity and comprehensiveness. These errors were further compounded when statistical analyses of diet-disease relations were performed using the pseudo-quantified anecdotal data. These fatal measurement, analytic, and inferential flaws were obscured when epidemiologists failed to cite decades of research demonstrating that the proxy-estimates they created were often physiologically implausible (i.e., meaningless) and had no verifiable quantitative relation to the actual nutrient or caloric consumption of participants. In this critical analysis, we present substantial evidence to support our contention that current controversies and public confusion regarding diet-disease relations were generated by tens of thousands of deeply flawed, demonstrably misleading, and pseudoscientific epidemiologic reports. We challenge the field of nutrition to regain lost credibility by acknowledging the empirical and theoretical refutations of their memory-based methods and ensure that rigorous (objective) scientific methods are used to study the role of diet in chronic disease.

Introduction Adequate and safe micronutrient intake is important. Both insufficient and excessive intakes should be prevented as these can be associated with negative health effects. Therefore, the population intake distribution will ideally lay between insufficient and excessive intakes. For the development and evaluation of nutrition and food policy a good estimation of dietary micronutrient intake is of great importance. Aim Three challenges were addressed to improve the estimation of population micronutrient intake distributions: 1) how to estimate current habitual micronutrient intake when (detailed) data are lacking or data from different sources should be combined, 2) how to predict future intakes in order to support policy making, and 3) how to estimate a maximum safe fortification level per food item. The aim of this PhD-thesis is to further develop and apply statistical models which can cope with these challenges. Methods & Results Data from the Dutch National Food Consumption Surveys (DNFCSs) were used to develop and apply statistical models which can cope with the defined challenges. In addition, data from the Dutch food composition database (NEVO) and the Dutch dietary supplement database (NES) were used. Three main methodological improvements have been made. First, the combination of a deterministic approach with probabilistic approaches to be able to take into account uncertainty and variability were needed. This method was applied to estimate habitual iodine and salt intake distributions. From DNFCSs no detailed information was available on the discretionary use of (iodized) salt and no up to date information was available on the use of iodized salt in industrially processed foods. Estimates of the proportion of the population discretionarily using (iodized) salt and the proportion of industrially processed foods applying iodized salt were obtained from other data sources. The model accurately estimates habitual iodine and salt intake distributions when compared with studies measuring urinary iodine and sodium excretion. Additionally a framework was developed to simulate the habitual intake distribution for potential scenarios of future fortification strategies. Within this framework, deterministic and probabilistic approaches were combined when uncertainty or variability had to be taken into account. This framework was illustrated by the estimation of habitual folate-equivalent intake for different scenarios of mandatory or voluntary fortification with folic acid. Further this framework was applied to estimate the habitual iodine intake for several potential changes in the Dutch iodine policy and also for several scenarios of salt reduction strategies. A second methodological improvement was the development of a new statistical model to estimate habitual total micronutrient intake aggregated from food and dietary supplements. Within this 3-part model, habitual intake is estimated separately for a) intake from food for non-users of dietary supplements, b) intake from food for users of dietary supplements, and c) intake from dietary supplements for users only. Habitual total intake for the whole population was obtained by combination of the three separate habitual intake distributions (‘first shrink then add’). This 3-part model was illustrated by vitamin D intake for young children. With a more simple ‘first add then shrink’ approach the estimation of habitual total vitamin D intake distribution may give inconsistent results for the distribution of intake from foods and dietary supplements combined as compared to the intake from food only. In addition, this more simple approach may not be able to cope with multi modal distributions. With the newly developed model this inconsistency problem was solved and the multi-modal shape of the distribution as observed in the ‘raw’ data was preserved. Third, a model calculating the maximum safe fortification level per 100 kcal of a food was developed for the Dutch situation. By considering the tolerable upper intake level and reasonable high micronutrient intakes from food and dietary supplements, the ‘free space’ for voluntary fortification was calculated. This amount was divided over the amount of energy intake that can and may be fortified. The model was applied to derive safe maximum fortification levels for vitamin A, D, and folic acid. Based on these results the risk manager decided to legally allow voluntary fortification with vitamin D and folic acid up to a maximum level of 4.5 and 100 μg/100 kcal respectively. Conclusion The methodological improvements have resulted in higher accuracy for estimations of habitual intake distributions, which are essential for nutritional and food policy making. Furthermore, scenario analyses provide (under specific conditions) quantitative insight into proposed changes or areas such as maximum safe fortification levels. Several results and methods described are currently being used in research to assist Dutch and European food and nutrition policy making, which shows these methodologies are of immediate value to the practice of policy development and support.

Background: Micronutrient deficiency, including iron, vitamin A, B-12 and folic acid, can cause anemia and harm adolescent health. Accurate dietary assessment methods is crucial to detect micronutrient deficiencies, but existing methods, have limitations, necessitating a review to identify the accurate methods for assessing micronutrient intake in adolescents. Objectives: To determine the accuracy of dietary assessment methods as suitable option for measuring micronutrient intake in adolescents. Methods: This study utilized the Preferred Reporting Items for Systematic Review and Meta-Analysis extension for Scoping Review (PRISMA-ScR) flowchart approach. Article were identified from ScienceDirect, PubMed, Scopus, Google Scholar. Articles were included if participants aged 10-19 years, published between 2014-2024, written in English/Indonesian, original research articles and studies related to validation of dietary assessment methods for micronutrient intake. The keywords were "micronutrient intake" OR "dietary intake" AND "dietary assessment" OR "validity" AND "adolescent". Discussions: 1157 articles were identified, 7 met the eligibility criteria, including 50 to 1081 adolescent. The Semi-Quantitative Food Frequency Questionnaire (SQ-FFQ) method was valid for sodium, niacin, folate, thiamine, calcium, phosphorus and reproducible for vitamin A, vitamin C, thiamine, riboflavin, niacin, iron, calcium, phosphorus, potassium, β-carotene. The Food Frequency Questionnaire (FFQ) method was valid for riboflavin, vitamin C, calcium, serum iron biomarkers, and reproducible for retinol, thiamine, riboflavin, vitamin C, vitamin D, iron, calcium. The 24-hour Dietary Recall (24hDR) method showed acceptable validity for serum iron biomarkers. Conclusions: The SQ-FFQ, completed by adolescents with instruction of nutritionist, using a shorter food list and time intervals, has higher relative validity and reproducibility.

Background: Accurate estimation of dietary intake is challenging. However, whilst some progress has been made in high-income countries, low- and middle-income countries (LMICs) remain behind, contributing to critical nutritional data gaps. This study aimed to validate an objective, passive image-based dietary intake assessment method against weighed food records in London, UK, for onward deployment to LMICs. Methods: Wearable camera devices were used to capture food intake on eating occasions in 18 adults and 17 children of Ghanaian and Kenyan origin living in London. Participants were provided pre-weighed meals of Ghanaian and Kenyan cuisine and camera devices to automatically capture images of the eating occasions. Food images were assessed for portion size, energy, nutrient intake, and the relative validity of the method compared to the weighed food records. Results: The Pearson and Intraclass correlation coefficients of estimates of intakes of food, energy, and 19 nutrients ranged from 0.60 to 0.95 and 0.67 to 0.90, respectively. Bland–Altman analysis showed good agreement between the image-based method and the weighed food record. Under-estimation of dietary intake by the image-based method ranged from 4 to 23%. Conclusions: Passive food image capture and analysis provides an objective assessment of dietary intake comparable to weighed food records.

Novel strategies for improving dietary exposure assessment: Multiple-data fusion is a more accurate measure than the traditional single-biomarker approach

The aim of the present paper is to summarise current and future applications of dietary assessment technologies in nutrition surveys in developed countries. It includes the discussion of key points and highlights of subsequent developments from a panel discussion to address strengths and weaknesses of traditional dietary assessment methods (food records, FFQ, 24h recalls, diet history with interviewer-assisted data collection) v. new technology-based dietary assessment methods (web-based and mobile device applications). The panel discussion 'Traditional methods v. new technologies: dilemmas for dietary assessment in population surveys', was held at the 9th International Conference on Diet and Activity Methods (ICDAM9), Brisbane, September 2015. Despite respondent and researcher burden, traditional methods have been most commonly used in nutrition surveys. However, dietary assessment technologies offer potential advantages including faster data processing and better data quality. This is a fast-moving field and there is evidence of increasing demand for the use of new technologies amongst the general public and researchers. There is a need for research and investment to support efforts being made to facilitate the inclusion of new technologies for rapid, accurate and representative data.