Characteristics of smartphone-based dietary assessment tools: a systematic review

NutriDiary, a Smartphone-Based Dietary Record App: Description and Usability Evaluation

Background

Repeated applications of short-term dietary assessment instruments are recommended for estimating usual dietary intake. For this purpose, NutriDiary, a smartphone app for collecting weighed dietary records (WDRs) in the German population, was developed.

Objective

We aim to describe NutriDiary and evaluate its usability and acceptability.

Methods

NutriDiary was developed as a WDR, allowing users to enter food items via text search, barcode scanning, or free text entry. The sample for the evaluation study included 74 participants (n=51, 69% female, aged 18-64 years), including 27 (37.5%) experts and 47 (63.5%) laypersons (including n=22, 30%, nutrition students). Participants completed a 1-day WDR and entered a predefined sample meal (n=17 foods) the following day by using NutriDiary. An evaluation questionnaire was answered from which the system usability scale (SUS) score (0-100) was calculated. A backward selection procedure (PROC REG in SAS; SAS Institute) was used to identify potential predictors for the SUS score (age, sex, status [expert or laypersons], and operating system [iOS or Android]).

Results

The median SUS score of 75 (IQR 63-88) indicated good usability. Age was the only characteristic identified as a potential predictor for a lower SUS score (P<.001). The median completion time for an individual WDR was 35 (IQR 19-52) minutes. Older participants took longer to enter the data than younger ones (18-30 y: median 1.5, IQR 1.1-2.0 min/item vs 45-64 y: median 1.8, IQR 1.3-2.3 min/item). Most participants expressed a preference for NutriDiary over the traditional paper-based method.

Conclusions

Good usability and acceptability make NutriDiary promising for use in epidemiological studies.

Nutrition: A non-negligible factor in the pathogenesis and treatment of Alzheimer's disease

Alzheimer's disease (AD) is a degenerative disease characterized by progressive cognitive dysfunction. The strong link between nutrition and the occurrence and progression of AD pathology has been well documented. Poor nutritional status accelerates AD progress by potentially aggravating amyloid beta (Aβ) and tau deposition, exacerbating oxidative stress response, modulating the microbiota-gut-brain axis, and disrupting blood-brain barrier function. The advanced stage of AD tends to lead to malnutrition due to cognitive impairments, sensory dysfunctions, brain atrophy, and behavioral and psychological symptoms of dementia (BPSD). This, in turn, produces a vicious cycle between malnutrition and AD. This review discusses how nutritional factors and AD deteriorate each other from the early stage of AD to the terminal stages of AD, focusing on the potential of different levels of nutritional factors, ranging from micronutrients to diet patterns. This review provides novel insights into reducing the risk of AD, delaying its progression, and improving prognosis. HIGHLIGHTS: Two-fifths of Alzheimer's disease (AD) cases worldwide have been attributed to potentially modifiable risk factors. Up to ≈26% of community-dwelling patients with AD are malnourished, compared to 7%∼76% of institutionalized patients. Undernutrition effects the onset, progression, and prognosis of AD through multiple mechanisms. Various levels of nutritional supports were confirmed to be protective factors for AD via specific mechanisms.

Data in Personalized Nutrition: Bridging Biomedical, Psycho-behavioral, and Food Environment Approaches for Population-wide Impact

Personalized nutrition (PN) represents an approach aimed at delivering tailored dietary recommendations, products, or services to support both prevention and treatment of nutrition-related conditions and to improve individual health using genetic, phenotypic, medical, nutritional, and other pertinent information. However, current approaches have yielded limited scientific success in improving diets or in mitigating diet-related conditions. In addition, PN currently caters to a specific subgroup of the population rather than having a widespread impact on diet and health at a population level. Addressing these challenges requires integrating traditional biomedical and dietary assessment methods with psycho-behavioral, and novel digital and diagnostic methods for comprehensive data collection, which holds considerable promise in alleviating present PN shortcomings. This comprehensive approach not only allows for deriving personalized goals ("what should be achieved") but also customizing behavioral change processes ("how to bring about change"). We herein outline and discuss the concept of "Adaptive Personalized Nutrition Advice Systems," which blends data from 3 assessment domains: 1) biomedical/health phenotyping; 2) stable and dynamic behavioral signatures; and 3) food environment data. Personalized goals and behavior change processes are envisaged to no longer be based solely on static data but will adapt dynamically in-time and in-situ based on individual-specific data. To successfully integrate biomedical, behavioral, and environmental data for personalized dietary guidance, advanced digital tools (e.g., sensors) and artificial intelligence-based methods will be essential. In conclusion, the integration of both established and novel static and dynamic assessment paradigms holds great potential for transitioning PN from its current focus on elite nutrition to a widely accessible tool that delivers meaningful health benefits to the general population.

Opportunities to design better computer vison-assisted food diaries to support individuals and experts in dietary assessment: An observation and interview study with nutrition experts

Automatic visual recognition for photo-based food diaries is increasingly prevalent. However, existing tools in food recognition often focus on food classification and calorie counting, which may not be sufficient to support the variety of food and healthy eating goals people have. To understand how to better design computer-vision-based food diaries to support healthy eating, we began to examine how nutrition experts, such as dietitians, use the visual features of food photos to evaluate diet quality. We conducted an observation and interview study with 18 dietitians, during which we asked the dietitians to review a seven-day photo-based food diary and fill out an evaluation form about their observations, recommendations, and questions. We then conducted follow-up interviews to understand their strategies, needs, and challenges of photo diary review. Our findings show that dietitians used the photo features to understand long-term eating patterns, diet variety, eating contexts, and food portions. Dietitians also adopted various strategies to achieve these understandings, such as grouping photos to find patterns, using color to estimate food variety, and identifying background objects to infer eating contexts. These findings suggest design opportunities for future compute-vision-based food diaries to account for dietary patterns over time, incorporate contextual information in dietary analysis, and support collaborations between nutrition experts, clients, and computer vision systems in dietary review and provide individualized recommendations.

Development and User Experience Evaluation of an Experience Sampling-Based Dietary Assessment Method

Background

Most technology-based dietary assessment methods use the same methodology as traditional dietary assessment methods resulting in similar limitations and biases. Experience sampling methodology (ESM) is a real-life real-time data-capturing method that is explored as an alternative methodology for dietary assessment to improve feasibility and data accuracy.

Objectives

This research aimed to develop and evaluate an experience sampling-based dietary assessment method (ESDAM) measuring habitual dietary intake.

Methods

Starting from a food frequency questionnaire, experience sampling principles were implemented resulting in a pilot ESDAM. Second, the pilot ESDAM was evaluated for feasibility and convergent validity compared with a 3-d food record. Mean intake with standard deviations was compared between the pilot ESDAM, food record (FR), and food frequency questionnaire (FFQ), and Spearman correlation coefficients (SCCs) were calculated. Third, following a literature review and expert opinion, the questions and design of the pilot ESDAM were further adapted to ESM and implemented in an experience sampling survey application. The resulting prototype ESDAM underwent 2 rounds of user experience (UX) evaluation in which 10 persons tested ESDAM for 1 wk followed by a structured evaluation interview.

Results

The pilot ESDAM, FR, and FFQ were completed by 27 participants and the evaluation questionnaire by 78 participants. Mean energy intake by the FFQ, pilot ESDAM, and FR was 1272.2 ± 308.9 kcal/d, 1592.3 ± 358.9 kcal/d, and 1664.6 ± 257.8 kcal, respectively. The evaluation revealed the limited time window (19:00-23:00) to respond was inconvenient, good acceptability, and ease of use of the pilot ESDAM. The UX evaluation study revealed overall good acceptability, ease of use, and low burden of the different prototypes of ESDAM.

Conclusions

ESM could advance the field beyond traditional methodologies and improve feasibility. ESDAM is unique in assessing dietary intake quantitatively through ESM. Additional assessment of validity might shed light on the data accuracy of ESDAM.

Nutrient dataset development via FAO/INFOODS approach for infant nutritional survey in rural Matiari, Pakistan

To accurately evaluate dietary intake, multiple resources are necessary, including serving-size modules, pictures, and questionnaires that are used to gather information during surveys. One critical component is the accessibility of food composition data at the national or regional level, which is required to determine dietary intake. Food Agriculture Organization/International Network of Food Data Systems (FAO/INFOODs) tools are useful for developing high-quality food composition data. We used these tools to create a nutrient dataset for a nutritional survey in Matiari, Sindh, and to collect dietary information through a 24-hour food recall questionnaire. The survey results indicated 540 distinct types of foods, including 291 ready-to-eat items, 84 foods used as ingredients in recipes, and 164 various composite and mixed recipes. Most food items corresponded to the national and regional Food Composition Tables (FCTs) and the Food and Nutrient Database for Dietary Studies (FNDDS) of the USDA, with the exception of recipe food data. We utilized Eurofir-recipe calculation methods to compute the recipe data. The data were homogenized and standardized utilizing EFSA and Langual™. Because of the obsolescence and inadequacy of Pakistan's food composition table in assessing essential nutrients, we had to source data from various other sources. Consequently, to establish the nutrient dataset, we incorporated approximately 25 % of user data from national sources, with recipe data comprising 46 % and less than 20 % extracted from regional, U.S database, and diverse online sources. This study is the first effort in which we gathered data from reliable sources representing local eating patterns, with some exceptions. Future studies will hugely benefit from this database, especially as we face a high prevalence of undernutrition in our part of the world.

Investigation of Ukrainian refugees' eating behavior, food intake, and psychological distress: Study protocol and baseline data

Since the start of the war in Ukraine, almost 8 million people left the country; more than 1 million of them relocated to Germany. It is to be expected that the war puts considerable strain on refugees, which will impact the public health system in host countries. This paper presents baseline data and protocol of longitudinal online experimental study of 619 Ukrainian refugees in Germany started in autumn 2022, focusing on participants' self-reports of appetite, food intake, and levels of stress, anxiety, and depressive symptoms to examine their associations. Results indicate that levels of stress, anxiety, and depressive symptoms in refugees significantly exceed the indicators of relevant parameters as reported by independent large-scale surveys conducted in Ukraine before the war as well as strong correlations between these deviations (.59 ≤ r ≤ .69, p = .005). Changes in appetite were related to more severe psycho-emotional deviations (.15 ≤ r ≤ .19, p = .003) and somewhat unhealthier food intake (r = -.08, p < .001). The study underlines the need of psychological care for refugees to improve their mental health and counteract potential negative consequences for physical health via changes in food intake, for which suitable interventions need to be developed.

The PICOTS-ComTeC Framework for Defining Digital Health Interventions: An ISPOR Special Interest Group Report

OBJECTIVES

Digital health definitions are abundant, but often lack clarity and precision. We aimed to develop a minimum information framework to define patient-facing digital health interventions (DHIs) for outcomes research.

METHODS

Definitions of digital-health-related terms (DHTs) were systematically reviewed, followed by a content analysis using frameworks, including PICOTS (population, intervention, comparator, outcome, timing, and setting), Shannon-Weaver Model of Communication, Agency for Healthcare Research and Quality Measures, and the World Health Organization's Classification of Digital Health Interventions. Subsequently, we conducted an online Delphi study to establish a minimum information framework, which was pilot tested by 5 experts using hypothetical examples.

RESULTS

After screening 2610 records and 545 full-text articles, we identified 101 unique definitions of 67 secondary DHTs in 76 articles, resulting in 95 different patterns of concepts among the definitions. World Health Organization system (84.5%), message (75.7%), intervention (58.3%), and technology (52.4%) were the most frequently covered concepts. For the Delphi survey, we invited 47 members of the ISPOR Digital Health Special Interest Group, 18 of whom became the Delphi panel. The first, second, and third survey rounds were completed by 18, 11, and 10 respondents, respectively. After consolidating results, the PICOTS-ComTeC acronym emerged, involving 9 domains (population, intervention, comparator, outcome, timing, setting, communication, technology, and context) and 32 optional subcategories.

CONCLUSIONS

Patient-facing DHIs can be specified using PICOTS-ComTeC that facilitates identification of appropriate interventions and comparators for a given decision. PICOTS-ComTeC is a flexible and versatile tool, intended to assist authors in designing and reporting primary studies and evidence syntheses, yielding actionable results for clinicians and other decision makers.

A Smartphone Food Record App Developed for the Dutch National Food Consumption Survey: Relative Validity Study

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.

Assessing daily energy intake in adult women: validity of a food-recognition mobile application compared to doubly labelled water

Accurate dietary assessment is crucial for nutrition and health research. Traditional methods, such as food records, food frequency questionnaires, and 24-hour dietary recalls (24HR), have limitations, such as the need for trained interviewers, time-consuming procedures, and inaccuracies in estimations. Novel technologies, such as image-based dietary assessment apps, have been developed to overcome these limitations. SNAQ is a novel image-based food-recognition app which, based on computer vision, assesses food type and volume, and provides nutritional information about dietary intake. This cross-sectional observational study aimed to investigate the validity of SNAQ as a dietary assessment tool for measuring energy and macronutrient intake in adult women with normal body weight (n = 30), compared to doubly labeled water (DLW), a reference method for total daily energy expenditure (TDEE). Energy intake was also estimated using a one-day 24HR for direct comparison. Bland-Altman plots, paired difference tests, and Pearson's correlation coefficient were used to assess agreement and relationships between the methods. SNAQ showed a slightly higher agreement (bias = -329.6 kcal/day) with DLW for total daily energy intake (TDEI) compared to 24HR (bias = -543.0 kcal/day). While both SNAQ and 24HR tended to underestimate TDEI, only 24HR significantly differed from DLW in this regard (p < 0.001). There was no significant relationship between estimated TDEI and TDEE using SNAQ (R2 = 27%, p = 0.50) or 24HR (R2 = 34%, p = 0.20) and there were no significant differences in energy and macronutrient intake estimates between SNAQ and 24HR (Δ = 213.4 kcal/day). In conclusion, these results indicate that SNAQ provides a closer representation of energy intake in adult women with normal body weight than 24HR when compared to DLW, but no relationship was found between the energy estimates of DLW and of the two dietary assessment tools. Further research is needed to determine the clinical relevance and support the implementation of SNAQ in research and clinical settings. Clinical trial registration: This study is registered on ClinicalTrials.gov with the unique identifier NCT04600596 (https://clinicaltrials.gov/ct2/show/NCT04600596).

Do nutrition knowledge, food preferences, and habit strength moderate the association between preference for intuition and deliberation in eating decision-making and dietary intake?

An intuitive style in eating decision-making, for example, basing decisions on one's gut feeling, has been related to a less healthy diet, whereas deliberately deciding what to eat, such as making plans about eating behavior, has been related to a healthier diet. The present study investigated whether nutrition knowledge, food preferences, and habit strength for healthy and unhealthy eating moderate these relationships. In total, 1245 participants took part in a preregistered cross-sectional online survey. Results revealed that neither nutrition knowledge, nor liking of healthy or unhealthy foods, nor habit strength for healthy or unhealthy eating interacted with the preference for intuition or deliberation in eating decision-making in affecting dietary intake (βs ≤ |.06|; ts ≤ |2.11|; ps ≥ .035). Instead, including the potential moderating variables in analyses rendered the effect of a preference for intuition largely non-significant. In contrast, the positive effect of a preference for deliberation was largely stable even when including the potential moderating variables. Thus, the present study confirms the general health-promoting effect of a preference for deliberation in eating decision-making. In contrast, results speak in favor of a generally minor role of a preference for intuition for healthy or unhealthy eating.

Are commonly used lab-based measures of food value and choice predictive of self-reported real-world snacking? An ecological momentary assessment study

OBJECTIVES

While the assessment of actual food intake is essential in the evaluation of behaviour change interventions for weight-loss, it may not always be feasible to collect this information within traditional experimental paradigms. For this reason, measures of food preference (such as measures of food value and choice) are often used as more accessible alternatives. However, the predictive validity of these measures (in relation to subsequent food consumption) has not yet been studied. Our aim was to investigate the extent to which three commonly used measures of preference for snack foods (explicit food value, unhealthy food choice and implicit preference) predicted self-reported real-world snacking occasions.

DESIGN

Ecological Momentary Assessment (EMA) design.

METHOD

Over a seven-day study period, participants (N = 49) completed three daily assessments where they reported their healthy and unhealthy snack food consumption and completed the three measures of preference (explicit food value, unhealthy food choice and implicit preference).

RESULTS

Our findings demonstrated some weak evidence that unhealthy Visual Analogue Scale scores predicted between-subject increases in unhealthy snacking frequency (OR = 1.018 [1.006, 1.030], p = .002). No other preference measures significantly predicted self-reported healthy or unhealthy snacking occasions (ps > .05).

CONCLUSIONS

These findings raise questions in relation to the association between measures of preference and self-reported real-world snack food consumption. Future research should further evaluate the predictive and construct validity of these measures in relation to food behaviours and explore the development of alternative assessment methods within eating behaviour research.

Development of eHealth-Based Behavior Change Support for Young Adults Using the Nine Principles Framework

Implementing behavior strategies into nutrition research requires consideration. The Nine Principles framework was used to develop an eHealth behavior change support (BCS) program to enhance young adults' adherence to (1) eating healthily and (2) recording dietary intake when participating in a randomized control trial. The Theory of Planned Behavior and qualitative focus group data informed a 10-week pilot of the BCS delivered on Facebook and texts. The BCS appeared to support optimal dietary recording and maintained dietary behaviors, suggesting using a framework underpinned by theory and user-centered design may be a promising avenue to enhance adherence in randomized control trials.

Wearable Cameras Reveal Large Intra-Individual Variability in Timing of Eating among Young Adults

Studies have shown that young adults follow less structured eating patterns compared with older cohorts. This may have implications for dietary assessment methods which rely on memory and structured meal patterns. Our aim was to describe the intra-individual variation of eating times in young adults aged 18−30 years. Participants (n = 41) wore an Autographer camera that captured first-person perspective images every 30 s for three consecutive days. All images were timestamped and those showing food consumption were used to extract data such as the timing of the first and last eating occasions (EOs), number of EOs per day, and length of eating window. Intra-individual variability was calculated from these data using composite phase deviation (CPD) and coefficient of variation (CV). The number of individuals with high or very high variability was 28 and 18 for timing of first and last EOs, respectively (CPD > 1.70), and 27 and 17 for number of EOs and eating window, respectively (CV > 20%). In this sample of young adults, the lack of regularity in eating patterns should be considered when selecting a dietary assessment method.

A theory-based video intervention to enhance communication and engagement in online health communities: two experiments

Background

Online communities and social networking sites have great potential for supporting health behavior change. However, interventions vary greatly in participants’ engagement rates and, consequently, their effectiveness. Theory-based interventions in real-world contexts are needed to further increase engagement and effectiveness.

Methods

We experimentally tested whether a video intervention teaching Self-Determination-Theory-based communication strategies increases need-supportive communication strategy use over one week (Study 1, N = 76) and perceived need support, engagement, and goal attainment in a behavior change intervention supported by a forum-based online community (Study 2, N = 537). In Study 2, participants chose a goal (increasing either fruit or vegetable consumption or increasing moderate or vigorous physical activity) and joined an online community for 2 weeks. Data from both experiments were analyzed with mixed models and follow-up tests.

Results

In Study 1, participants in the intervention but not in the control group showed an increase in the number of need-supportive communication strategies used both immediately and one week after the intervention (condition × time interaction, partial η² = 0.31). In Study 2, participants who watched the intervention video had a higher number of postings and reported a higher subjective forum use frequency (but not a higher number of logins) compared to participants who watched the control video. However, the effect on the subjective forum visit frequency was not robust. There were no intervention effects on perceived need support, goal attainment, or secondary outcomes. The results might be explained by low application of need-supportive communication strategies.

Conclusion

A brief video intervention may be a suitable, low-cost intervention to promote need-supportive communication strategy use, benefitting both engagement and behavior change. Future studies should incorporate additional means to further improve communication strategy uptake and engagement in online communities.