Trial of a mobile phone method for recording dietary intake in adults with type 2 diabetes: evaluation and implications for future applications

The association between diet quality and chrononutritional patterns in young adults

PURPOSE

Young adults eat erratically and later in the day which may impact weight and cardiometabolic health. This cross-sectional study examined relationships between chrononutritional patterns and diet quality in two young adult populations: a university and community sample.

METHODS

Three days of dietary data were collected including food images captured using wearable cameras. Chrononutritional variables were extracted: time of first and last eating occasions, caloric midpoint (time at which 50% of daily energy was consumed), number of eating occasions per day, eating window, day-to-day variability of the above metrics, and evening eating (≥20:00h). The Healthy Eating Index for Australian Adults scored diet quality. Statistical analyses controlled for gender, body mass index, and socio-economic status.

RESULTS

No significant associations between chrononutritional patterns and diet quality were found for all participants (n = 95). However, differences in diet quality were found between university (n = 54) and community (n = 41) samples with average diet quality scores of 59.1 (SD 9.7) and 47.3 (SD 14.4), respectively. Of those who extended eating ≥20:00 h, university participants had better diet quality (62.9±SE 2.5 vs. 44.3±SE 2.3, p < 0.001) and discretionary scores (7.9±SE 0.9 vs. 1.6±SE 0.6, p < 0.001) than community participants. University participants consumed predominately healthful dinners and fruit ≥20:00h whereas community participants consumed predominately discretionary foods.

CONCLUSION

For the general young adult population, meal timing needs to be considered. Food choices made by this cohort may be poorer during evenings when the desire for energy-dense nutrient-poor foods is stronger. However, meal timing may be less relevant for young adults who already engage in healthy dietary patterns.

Feasibility of Using an Artificial Intelligence-based Telephone Application for Dietary Assessment and Nudging to Improve the Quality of Food Choices of Female Adolescents in Vietnam: Evidence from a Randomized Pilot Study

Background

Adolescent nutrition has faced a policy neglect, partly owing to the gaps in dietary intake data for this age group. The Food Recognition Assistance and Nudging Insights (FRANI) is a smartphone application validated for dietary assessment and to influence users toward healthy food choices.

Objectives

This study aimed to assess the feasibility (adherence, acceptability, and usability) of FRANI and its effects on food choices and diet quality in female adolescents in Vietnam.

Methods

Adolescents (N = 36) were randomly selected from a public school and allocated into 2 groups. The control group received smartphones with a version of FRANI limited to dietary assessment, whereas the intervention received smartphones with gamified FRANI. After the first 4 wk, both groups used gamified FRANI for further 2 wk. The primary outcome was the feasibility of using FRANI as measured by adherence (the proportion of completed food records), acceptability and usability (the proportion of participants who considered FRANI acceptable and usable according to answers of a Likert questionnaire). Secondary outcomes included the percentage of meals recorded, the Minimum Dietary Diversity for Women (MDDW) and the Eat-Lancet Diet Score (ELDS). Dietary diversity is important for dietary quality, and sustainable healthy diets are important to reduce carbon emissions. Poisson regression models were used to estimate the effect of gamified FRANI on the MDDW and ELDS.

Results

Adherence to the application was 82% and the percentage of meals recorded was 97%. Acceptability and usability were 97%. MDDW in the intervention group was 1.07 points (95% CI: 0.98, 1.18; P = 0.13) greater than that in the control (constant = 4.68); however, the difference was not statistically significant. Moreover, ELDS in the intervention was 1.09 (95% CI: 1.01, 1.18; P = 0.03) points greater than in the control (constant = 3.67).

Conclusions

FRANI was feasible and may be effective to influence users toward healthy food choices. Research is needed for FRANI in different contexts and at scale.The trial was registered at the International Standard Randomized Controlled Trial Number as ISRCTN 10681553.

Use of Digital Tools for the Assessment of Food Consumption in Brazil: A Scoping Review

This is a scoping review on mapping the use of digital tools to assess food consumption in Brazil. Searches were carried out in nine electronic databases (Medline, Lilacs, Scopus, Embase, Web of Science, Science Direct, Ovid, Free Medical Journal and Crossref) to select studies published from October 2020 to December 2023. This review identified forty-eight digital tools in the 94 publications analyzed, the most frequent being web-based technologies (60%) and mobile devices (40%). Among these studies, 55% (n = 52) adopted a population-based approach, while 45% (n = 42) focused on specific regions. The predominant study design observed was cross-sectional (n = 63). A notable trend observed was the increasing frequency of validation studies in recent years. Although the use of digital tools in the assessment of food consumption in Brazil has grown in recent years, studies did not describe the process of creating and validating the tools, which would contribute to the improvement of data quality. Investments that allow the expansion of the use of the internet and mobile devices; the improvement of digital literacy; and the development of open-access tools, especially in the North and Northeast regions, are challenges that require a concerted effort towards providing equal opportunities, fostering encouragement, and delving deeper into the potential of digital tools within studies pertaining to food consumption in Brazil.

Tailored Prompting to Improve Adherence to Image-Based Dietary Assessment: Mixed Methods Study

Background

Accurately assessing an individual's diet is vital in the management of personal nutrition and in the study of the effect of diet on health. Despite its importance, the tools available for dietary assessment remain either too imprecise, expensive, or burdensome for clinical or research use. Image-based methods offer a potential new tool to improve the reliability and accessibility of dietary assessment. Though promising, image-based methods are sensitive to adherence, as images cannot be captured from meals that have already been consumed. Adherence to image-based methods may be improved with appropriately timed prompting via text message.

Objective

This study aimed to quantitatively examine the effect of prompt timing on adherence to an image-based dietary record and qualitatively explore the participant experience of dietary assessment in order to inform the design of a novel image-based dietary assessment tool.

Methods

This study used a randomized crossover design to examine the intraindividual effect of 3 prompt settings on the number of images captured in an image-based dietary record. The prompt settings were control, where no prompts were sent; standard, where prompts were sent at 7:15 AM, 11:15 AM, and 5:15 PM for every participant; and tailored, where prompt timing was tailored to habitual meal times for each participant. Participants completed a text-based dietary record at baseline to determine the timing of tailored prompts. Participants were randomized to 1 of 6 study sequences, each with a unique order of the 3 prompt settings, with each 3-day image-based dietary record separated by a washout period of at least 7 days. The qualitative component comprised semistructured interviews and questionnaires exploring the experience of dietary assessment.

Results

A total of 37 people were recruited, and 30 participants (11 male, 19 female; mean age 30, SD 10.8 years), completed all image-based dietary records. The image rate increased by 0.83 images per day in the standard setting compared to control (P=.23) and increased by 1.78 images per day in the tailored setting compared to control (P≤.001). We found that 13/21 (62%) of participants preferred to use the image-based dietary record versus the text-based dietary record but reported method-specific challenges with each method, particularly the inability to record via an image after a meal had been consumed.

Conclusions

Tailored prompting improves adherence to image-based dietary assessment. Future image-based dietary assessment tools should use tailored prompting and offer both image-based and written input options to improve record completeness.

The Use of Three-Dimensional Images and Food Descriptions from a Smartphone Device Is Feasible and Accurate for Dietary Assessment

Technology-assisted dietary assessment has the potential to improve the accuracy of self-reported dietary intake. This study evaluates MealScan3D (MS3D), a mobile device-based food recording system, which uses three-dimensional images to obtain food volumes and an application to capture algorithm-driven food intake data. Participants (n = 179) were randomly assigned and trained to record three meals using either MS3D or a written food record (WFR). Generous amounts of standardized meals were provided, and participants self-selected portions for each food. The weights of provided and uneaten/leftover foods were used to determine true intake. For total energy intake (three meals combined), validity (Pearson correlation) was significantly higher for MS3D vs. the WFR (p < 0.001); when interpreted as the percentage of variance in energy intake explained, MS3D explained 84.6% of true variance, a 25.3% absolute and 42.6% relative increase over the 59.3% explained by the WFR. For 9 of 15 individual foods, the Pearson correlations between true and reported portion size estimates were significantly larger for MS3D than the WFR. Bias was smaller (intercepts were closer to the means) for 9 of 15 foods and the regression coefficients for 10 of 15 foods were significantly closer to 1.0 in the MS3D arm. MS3D is feasible for dietary assessment and may provide improvements in accuracy compared to WFRs.

The RODI mHealth app Insight: Machine-Learning-Driven Identification of Digital Indicators for Neurodegenerative Disorder Detection

Neurocognitive Disorders (NCDs) pose a significant global health concern, and early detection is crucial for optimizing therapeutic outcomes. In parallel, mobile health apps (mHealth apps) have emerged as a promising avenue for assisting individuals with cognitive deficits. Under this perspective, we pioneered the development of the RODI mHealth app, a unique method for detecting aligned with the criteria for NCDs using a series of brief tasks. Utilizing the RODI app, we conducted a study from July to October 2022 involving 182 individuals with NCDs and healthy participants. The study aimed to assess performance differences between healthy older adults and NCD patients, identify significant performance disparities during the initial administration of the RODI app, and determine critical features for outcome prediction. Subsequently, the results underwent machine learning processes to unveil underlying patterns associated with NCDs. We prioritize the tasks within RODI based on their alignment with the criteria for NCDs, thus acting as key digital indicators for the disorder. We achieve this by employing an ensemble strategy that leverages the feature importance mechanism from three contemporary classification algorithms. Our analysis revealed that tasks related to visual working memory were the most significant in distinguishing between healthy individuals and those with an NCD. On the other hand, processes involving mental calculations, executive working memory, and recall were less influential in the detection process. Our study serves as a blueprint for future mHealth apps, offering a guide for enhancing the detection of digital indicators for disorders and related conditions.

Using Crowdsourced Food Image Data for Assessing Restaurant Nutrition Environment: A Validation Study

Crowdsourced online food images, when combined with food image recognition technologies, have the potential to offer a cost-effective and scalable solution for the assessment of the restaurant nutrition environment. While previous research has explored this approach and validated the accuracy of food image recognition technologies, much remains unknown about the validity of crowdsourced food images as the primary data source for large-scale assessments. In this paper, we collect data from multiple sources and comprehensively examine the validity of using crowdsourced food images for assessing the restaurant nutrition environment in the Greater Hartford region. Our results indicate that while crowdsourced food images are useful in terms of the initial assessment of restaurant nutrition quality and the identification of popular food items, they are subject to selection bias on multiple levels and do not fully represent the restaurant nutrition quality or customers' dietary behaviors. If employed, the food image data must be supplemented with alternative data sources, such as field surveys, store audits, and commercial data, to offer a more representative assessment of the restaurant nutrition environment.

Continuous Glucose Monitoring and Other Wearable Devices to Assess Hypoglycemia among Older Adult Outpatients with Diabetes Mellitus

BACKGROUND

Hypoglycemia (HG) causes symptoms that can be fatal, and confers risk of dementia. Wearable devices can improve measurement and feedback to patients and clinicians about HG events and risk.

OBJECTIVES

The aim of the study is to determine whether vulnerable older adults could use wearables, and explore HG frequency over 2 weeks.

METHODS

First, 10 participants with diabetes mellitus piloted a continuous glucometer, physical activity monitor, electronic medication bottles, and smartphones facilitating prompts about medications, behaviors, and symptoms. They reviewed graphs of glucose values, and were asked about the monitoring experience. Next, a larger sample (N = 70) wore glucometers and activity monitors, and used the smartphone and bottles, for 2 weeks. Participants provided feedback about the devices. Descriptive statistics summarized demographics, baseline experiences, behaviors, and HG.

RESULTS

In the initial pilot, 10 patients aged 50 to 85 participated. Problems addressed included failure of the glucometer adhesive. Patients sought understanding of graphs, often requiring some assistance with interpretation. Among 70 patients in subsequent testing, 67% were African-American, 59% were women. Nearly one-fourth (23%) indicated that they never check their blood sugars. Previous HG was reported by 67%. In 2 weeks of monitoring, 73% had HG (glucose ≤70 mg/dL), and 42% had serious, clinically significant HG (glucose under 54 mg/dL). Eight patients with HG also had HG by home-based blood glucometry. Nearly a third of daytime prompts were unanswered. In 24% of participants, continuous glucometers became detached.

CONCLUSION

Continuous glucometry occurred for 2 weeks in an older vulnerable population, but devices posed wearability challenges. Most patients experienced HG, often serious in magnitude. This suggests important opportunities to improve wearability and decrease HG frequency among this population.

COVID-19 and Virtual Nutrition: A Pilot Study of Integrating Digital Food Models for Interactive Portion Size Education

Background and aims: Digital food viewing is a vital skill for connecting dieticians to e-health. The aim of this study was to integrate a novel pedagogical framework that combines interactive three- (3-D) and two-dimensional (2-D) food models into a formal dietetic training course. The level of agreement between the digital food models (first semester) and the effectiveness of educational integration of digital food models during the school closure due to coronavirus disease 2019 (COVID-19) (second semester) were evaluated. Method: In total, 65 second-year undergraduate dietetic students were enrolled in a nutritional practicum course at the School of Nutrition and Health Sciences, Taipei Medical University (Taipei, Taiwan). A 3-D food model was created using Agisoft Metashape. Students’ digital food viewing skills and receptiveness towards integrating digital food models were evaluated. Results: In the first semester, no statistical differences were observed between 2-D and 3-D food viewing skills in food identification (2-D: 89% vs. 3-D: 85%) and quantification (within ±10% difference in total calories) (2-D: 19.4% vs. 3-D: 19.3%). A Spearman correlation analysis showed moderate to strong correlations of estimated total calories (0.69~0.93; all p values < 0.05) between the 3-D and 2-D models. Further analysis showed that students who struggled to master both 2-D and 3-D food viewing skills had lower estimation accuracies than those who did not (equal performers: 28% vs. unequal performers:16%, p = 0.041), and interactive 3-D models may help them perform better than 2-D models. In the second semester, the digital food viewing skills significantly improved (food identification: 91.5% and quantification: 42.9%) even for those students who struggled to perform digital food viewing skills equally in the first semester (equal performers: 44% vs. unequal performers: 40%). Conclusion: Although repeated training greatly enhanced students’ digital food viewing skills, a tailored training program may be needed to master 2-D and 3-D digital food viewing skills. Future study is needed to evaluate the effectiveness of digital food models for future “eHealth” care.

Patient-Generated Health Photos and Videos Across Health and Well-being Contexts: Scoping Review

Background

Patient-generated health data are increasingly used to record health and well-being concerns and engage patients in clinical care. Patient-generated photographs and videos are accessible and meaningful to patients, making them especially relevant during the current COVID-19 pandemic. However, a systematic review of photos and videos used by patients across different areas of health and well-being is lacking.

Objective

This review aims to synthesize the existing literature on the health and well-being contexts in which patient-generated photos and videos are used, the value gained by patients and health professionals, and the challenges experienced.

Methods

Guided by a framework for scoping reviews, we searched eight health databases (CINAHL, Cochrane Library, Embase, PsycINFO, PubMed, MEDLINE, Scopus, and Web of Science) and one computing database (ACM), returning a total of 28,567 studies. After removing duplicates and screening based on the predefined inclusion criteria, we identified 110 relevant articles. Data were charted and articles were analyzed following an iterative thematic approach with the assistance of NVivo software (version 12; QSR International).

Results

Patient-generated photos and videos are used across a wide range of health care services (39/110, 35.5% articles), for example, to diagnose skin lesions, assess dietary intake, and reflect on personal experiences during therapy. In addition, patients use them to self-manage health and well-being concerns (33/110, 30%) and to share personal health experiences via social media (36/110, 32.7%). Photos and videos create significant value for health care (59/110, 53.6%), where images support diagnosis, explanation, and treatment (functional value). They also provide value directly to patients through enhanced self-determination (39/110, 35.4%), social (33/110, 30%), and emotional support (21/110, 19.1%). However, several challenges emerge when patients create, share, and examine photos and videos, such as limited accessibility (16/110, 14.5%), incomplete image sets (23/110, 20.9%), and misinformation through photos and videos shared on social media (17/110, 15.5%).

Conclusions

This review shows that photos and videos engage patients in meaningful ways across different health care activities (eg, diagnosis, treatment, and self-care) for various health conditions. Although photos and videos require effort to capture and involve challenges when patients want to use them in health care, they also engage and empower patients, generating unique value. This review highlights areas for future research and strategies for addressing these challenges.

Measurement Properties of Smartphone Approaches to Assess Diet, Alcohol Use, and Tobacco Use: Systematic Review

BACKGROUND

Poor diet, alcohol use, and tobacco smoking have been identified as strong determinants of chronic diseases, such as cardiovascular disease, diabetes, and cancer. Smartphones have the potential to provide a real-time, pervasive, unobtrusive, and cost-effective way to measure these health behaviors and deliver instant feedback to users. Despite this, the validity of using smartphones to measure these behaviors is largely unknown.

OBJECTIVE

The aim of our review is to identify existing smartphone-based approaches to measure these health behaviors and critically appraise the quality of their measurement properties.

METHODS

We conducted a systematic search of the Ovid MEDLINE, Embase (Elsevier), Cochrane Library (Wiley), PsycINFO (EBSCOhost), CINAHL (EBSCOHost), Web of Science (Clarivate), SPORTDiscus (EBSCOhost), and IEEE Xplore Digital Library databases in March 2020. Articles that were written in English; reported measuring diet, alcohol use, or tobacco use via a smartphone; and reported on at least one measurement property (eg, validity, reliability, and responsiveness) were eligible. The methodological quality of the included studies was assessed using the Consensus-Based Standards for the Selection of Health Measurement Instruments Risk of Bias checklist. Outcomes were summarized in a narrative synthesis. This systematic review was registered with PROSPERO, identifier CRD42019122242.

RESULTS

Of 12,261 records, 72 studies describing the measurement properties of smartphone-based approaches to measure diet (48/72, 67%), alcohol use (16/72, 22%), and tobacco use (8/72, 11%) were identified and included in this review. Across the health behaviors, 18 different measurement techniques were used in smartphones. The measurement properties most commonly examined were construct validity, measurement error, and criterion validity. The results varied by behavior and measurement approach, and the methodological quality of the studies varied widely. Most studies investigating the measurement of diet and alcohol received very good or adequate methodological quality ratings, that is, 73% (35/48) and 69% (11/16), respectively, whereas only 13% (1/8) investigating the measurement of tobacco use received a very good or adequate rating.

CONCLUSIONS

This review is the first to provide evidence regarding the different types of smartphone-based approaches currently used to measure key behavioral risk factors for chronic diseases (diet, alcohol use, and tobacco use) and the quality of their measurement properties. A total of 19 measurement techniques were identified, most of which assessed dietary behaviors (48/72, 67%). Some evidence exists to support the reliability and validity of using smartphones to assess these behaviors; however, the results varied by behavior and measurement approach. The methodological quality of the included studies also varied. Overall, more high-quality studies validating smartphone-based approaches against criterion measures are needed. Further research investigating the use of smartphones to assess alcohol and tobacco use and objective measurement approaches is also needed.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-https://doi.org/10.1186/s13643-020-01375-w.

Perspective: Opportunities and Challenges of Technology Tools in Dietary and Activity Assessment: Bridging Stakeholder Viewpoints

The science and tools of measuring energy intake and output in humans have rapidly advanced in the last decade. Engineered devices such as wearables and sensors, software applications, and Web-based tools are now ubiquitous in both research and consumer environments. The assessment of energy expenditure in particular has progressed from reliance on self-report instruments to advanced technologies requiring collaboration across multiple disciplines, from optics to accelerometry. In contrast, assessing energy intake still heavily relies on self-report mechanisms. Although these tools have improved, moving from paper-based to online reporting, considerable room for refinement remains in existing tools, and great opportunities exist for novel, transformational tools, including those using spectroscopy and chemo-sensing. This report reviews the state of the science, and the opportunities and challenges in existing and emerging technologies, from the perspectives of 3 key stakeholders: researchers, users, and developers. Each stakeholder approaches these tools with unique requirements: researchers are concerned with validity, accuracy, data detail and abundance, and ethical use; users with ease of use and privacy; and developers with high adherence and utilization, intellectual property, licensing rights, and monetization. Cross-cutting concerns include frequent updating and integration of the food and nutrient databases on which assessments rely, improving accessibility and reducing disparities in use, and maintaining reliable technical assistance. These contextual challenges are discussed in terms of opportunities and further steps in the direction of personalized health.

A Mixed-Method Study Exploring Experiences and Perceptions of Nutritionists Regarding Use of an Image-Based Dietary Assessment System in Tanzania

Due to global advances in technology, image-based food record methods have emerged as an alternative to traditional assessment methods. The use of image-based food records in low and lower-middle income countries such as Tanzania is limited, with countries still using traditional methods. The current study aimed to determine the feasibility of using a new voice and image-based dietary assessment system (VISIDA) in Dar es Salaam, Tanzania. This mixed-method study recruited 18 nutritionists as participants who collected image-based records of food and drinks they consumed using the VISIDA smartphone app. Participants viewed an online demonstration of the VISIDA web platform and the analysis process for intake data collected using the VISIDA app. Then, participants completed an online survey and were interviewed about the VISIDA app and web platform for food and nutrient intake analysis. The method was reported as being acceptable and was found to be easy to use, although technical challenges were experienced by some participants. Most participants indicated a willingness to use the VISIDA app again for one week or longer and were interested in using the VISIDA system in their current role. Participants acknowledged that the VISIDA web platform would simplify some aspects of their current job. Image-based food records could potentially be used in Tanzania to improve the assessment of dietary intake by nutritionists in urban areas. Participants recommended adding sound-on notifications, using the VISIDA app in both Apple and Android phones, enabling installation from the app store, and improving the quality of the fiducial markers.

Views and needs of people who at high-risk of gestational diabetes mellitus for the development of mobile health applications: A descriptive qualitative research (Preprint)

Background

Early prevention of gestational diabetes mellitus (GDM) can reduce the incidence of not only GDM, but also adverse perinatal pregnancy outcomes. Moreover, it is of great significance to prevent or reduce the occurrence of type 2 diabetes. Mobile health (mHealth) apps can help pregnant women effectively prevent GDM by providing risk prediction, lifestyle support, peer support, professional support, and other functions. Before designing mHealth apps, developers must understand the views and needs of pregnant women, and closely combine users’ needs to develop app functions, in order to better improve user experience and increase the usage rate of these apps in the future.

Objective

The objective of this study was to understand the views of the high-risk population of gestational diabetes mellitus on the development of mobile health apps and the demand for app functions, so as to provide a basis for the development of gestational diabetes mellitus prevention apps.

Methods

Fifteen pregnant women with at least one risk factor for gestational diabetes were recruited from July to September 2021, and were interviewed via a semistructured interview using the purpose sampling method. The transcribed data were analyzed by the traditional content analysis method, and themes were extracted.

Results

Respondents wanted to develop user-friendly and fully functional mobile apps for the prevention of gestational diabetes mellitus. Pregnant women's requirements for app function development include: personalized customization, accurate information support, interactive design, practical tool support, visual presentation, convenient professional support, peer support, reasonable reminder function, appropriate maternal and infant auxiliary function, and differentiated incentive function.These function settings can encourage pregnant women to improve or maintain healthy living habits during their use of the app

Conclusions

This study discusses the functional requirements of target users for gestational diabetes mellitus prevention apps, which can provide reference for the development of future applications.

Use of Natural Spoken Language With Automated Mapping of Self-reported Food Intake to Food Composition Data for Low-Burden Real-time Dietary Assessment: Method Comparison Study

Background

Self-monitoring food intake is a cornerstone of national recommendations for health, but existing apps for this purpose are burdensome for users and researchers, which limits use.

Objective

We developed and pilot tested a new app (COCO Nutritionist) that combines speech understanding technology with technologies for mapping foods to appropriate food composition codes in national databases, for lower-burden and automated nutritional analysis of self-reported dietary intake.

Methods

COCO was compared with the multiple-pass, interviewer-administered 24-hour recall method for assessment of energy intake. COCO was used for 5 consecutive days, and 24-hour dietary recalls were obtained for two of the days. Participants were 35 women and men with a mean age of 28 (range 20-58) years and mean BMI of 24 (range 17-48) kg/m².

Results

There was no significant difference in energy intake between values obtained by COCO and 24-hour recall for days when both methods were used (mean 2092, SD 1044 kcal versus mean 2030, SD 687 kcal, P=.70). There were also no significant differences between the methods for percent of energy from protein, carbohydrate, and fat (P=.27-.89), and no trend in energy intake obtained with COCO over the entire 5-day study period (P=.19).

Conclusions

This first demonstration of a dietary assessment method using natural spoken language to map reported foods to food composition codes demonstrates a promising new approach to automate assessments of dietary intake.

An Exploratory Approach to Deriving Nutrition Information of Restaurant Food from Crowdsourced Food Images: Case of Hartford

Deep learning models can recognize the food item in an image and derive their nutrition information, including calories, macronutrients (carbohydrates, fats, and proteins), and micronutrients (vitamins and minerals). This technology has yet to be implemented for the nutrition assessment of restaurant food. In this paper, we crowdsource 15,908 food images of 470 restaurants in the Greater Hartford region on Tripadvisor and Google Place. These food images are loaded into a proprietary deep learning model (Calorie Mama) for nutrition assessment. We employ manual coding to validate the model accuracy based on the Food and Nutrient Database for Dietary Studies. The derived nutrition information is visualized at both the restaurant level and the census tract level. The deep learning model achieves 75.1% accuracy when compared with manual coding. It has more accurate labels for ethnic foods but cannot identify portion sizes, certain food items (e.g., specialty burgers and salads), and multiple food items in an image. The restaurant nutrition (RN) index is further proposed based on the derived nutrition information. By identifying the nutrition information of restaurant food through crowdsourced food images and a deep learning model, the study provides a pilot approach for large-scale nutrition assessment of the community food environment.

Harnessing SmartPhones to Personalize Nutrition in a Time of Global Pandemic

The soar in COVID-19 cases around the globe has forced many to adapt to social distancing and self-isolation. In order to reduce contact with healthcare facilities and other patients, the CDC has advocated the use of telemedicine, i.e., electronic information and telecommunication technology. While these changes may disrupt normal behaviors and routines and induce anxiety, resulting in decreased vigilance to healthy diet and physical activity and reluctance to seek medical attention, they may just as well be circumvented using modern technology. Indeed, as the beginning of the pandemic a plethora of alternatives to conventional physical interactions were introduced. In this Perspective, we portray the role of SmartPhone applications (apps) in monitoring healthy nutrition, from their basic functionality as food diaries required for simple decision-making and nutritional interventions, through more advanced purposes, such as multi-dimensional data-mining and development of machine learning algorithms. Finally, we will delineate the emerging field of personalized nutrition and introduce pioneering technologies and concepts yet to be incorporated in SmartPhone-based dietary surveillance.

Impact on Dietary Intake of Two Levels of Technology-Assisted Personalized Nutrition: A Randomized Trial

Advances in web and mobile technologies have created efficiencies relating to collection, analysis and interpretation of dietary intake data. This study compared the impact of two levels of nutrition support: (1) low personalization, comprising a web-based personalized nutrition feedback report generated using the Australian Eating Survey® (AES) food frequency questionnaire data; and (2) high personalization, involving structured video calls with a dietitian using the AES report plus dietary self-monitoring with text message feedback. Intake was measured at baseline and 12 weeks using the AES and diet quality using the Australian Recommended Food Score (ARFS). Fifty participants (aged 39.2 ± 12.5 years; Body Mass Index 26.4 ± 6.0 kg/m2; 86.0% female) completed baseline measures. Significant (p < 0.05) between-group differences in dietary changes favored the high personalization group for total ARFS (5.6 points (95% CI 1.3 to 10.0)) and ARFS sub-scales of meat (0.9 points (0.4 to 1.6)), vegetarian alternatives (0.8 points (0.1 to 1.4)), and dairy (1.3 points (0.3 to 2.3)). Additional significant changes in favor of the high personalization group occurred for proportion of energy intake derived from energy-dense, nutrient-poor foods (-7.2% (-13.8% to -0.5%)) and takeaway foods sub-group (-3.4% (-6.5% to 0.3%). Significant within-group changes were observed for 12 dietary variables in the high personalization group vs one variable for low personalization. A higher level of personalized support combining the AES report with one-on-one dietitian video calls and dietary self-monitoring resulted in greater dietary change compared to the AES report alone. These findings suggest nutrition-related web and mobile technologies in combination with personalized dietitian delivered advice have a greater impact compared to when used alone.

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

BACKGROUND & AIMS

Image-assisted or image-based dietary assessments (IBDAs) refer to the use of food images as the primary dietary record and have emerged as key methods for evaluating habitual dietary intake; however, the validity of image-assisted or IBDAs is still unclear, and no meta-analysis has been conducted. Our aim was to investigate the validity of IBDAs in assessing energy intake (EI) and macronutrients compared to biomarker-based (double-labeled water (DLW)) and traditional methods of 24-h dietary recall (24-HDR) and estimated/weighed food records (WFRs).

METHODS

A systematic review and meta-analysis were performed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines using the PubMed, EMBASE, and Cochrane Central Register of Controlled Trials databases. Of the 4346 papers identified, 13 studies met the inclusion criteria, comprising 606 participants.

RESULTS

The overall weighted mean difference (WMD) in EI showed significant under-reporting (WMD = -179.32 kcal, 95% confidence interval (CI): -269.50 to -89.15 kcal; I² = 89%), with the greatest difference observed between tests and DLW (WMD = -448.04 kcal, 95% CI: -755.52 to -140.56 kcal; I² = 95%). A small non-significant trend towards under-reporting of carbohydrates (CHOs) was observed (WMD = -9.17 g, 95% CI: -20.58 to 2.24 g; I² = 64%), but no differences were found in protein (WMD = -0.08 g, 95% CI: -3.94 to 3.79 g; I² = 68%, p < 0.01) or fat (WMD = -0.57 g, 95% CI: -2.58 to 1.43 g; I² = 12%, p = 0.35). A meta-regression analysis found potential effects of the body-mass index (tests vs. DLW: β = 34.9, p = 0.063) and duration of the assessment (tests vs. WFR: β = -66.5, p = 0.002) on EI; age (tests vs. 24-HDR: β = -2.222, p = 0.019) and duration of the assessment (tests vs. WFR: β = -9.19, p = 0.013) on CHO intake; duration of the assessment on protein intake (tests vs. WFR: β = -3.2250, p = 0.0175); and duration of the assessment on fat intake (tests vs. WFR: β = -1.07, p = 0.040).

CONCLUSIONS

Except for DLW, no statistical difference was found between IBDAs and traditional methods. This suggests that like traditional methods, image-based methods have serious measurement errors, and more studies are needed to determine inherent measurement errors in IBDAs.

A randomized study on the usefulness of an electronic outpatient hypoglycemia risk calculator for clinicians of patients with diabetes in a safety-net institution

Objective: Hypoglycemia (HG) occurs in up to 60% of patients with diabetes mellitus (DM) each year. We assessed a HG alert tool in an electronic health record system, and determined its effect on clinical practice and outcomes.Methods: The tool applied a statistical model, yielding patient-specific information about HG risk. We randomized outpatient primary-care providers (PCPs) to see or not see the alerts. Patients were assigned to study group according to the first PCP seen during four months. We assessed prescriptions, testing, and HG. Variables were compared by multinomial, logistic, or linear model. ClinicalTrials.gov ID: NCT04177147 (registered on 22 November 2019).Results: Patients (N = 3350) visited 123 intervention PCPs; 3395 patients visited 220 control PCPs. Intervention PCPs were shown 18,645 alerts (mean of 152 per PCP). Patients' mean age was 55 years, with 61% female, 49% black, and 49% Medicaid recipients. Mean baseline A1c and body mass index were similar between groups. During follow-up, the number of A1c and glucose tests, and number of new, refilled, changed, or discontinued insulin prescriptions, were highest for patients with highest risk. Per 100 patients on average, the intervention group had fewer sulfonylurea refills (6 vs. 8; p < .05) and outpatient encounters (470 vs. 502; p < .05), though the change in encounters was not significant. Frequency of HG events was unchanged.Conclusions: Informing PCPs about risk of HG led to fewer sulfonylurea refills and visits. Longer-term studies are needed to assess potential for long-term benefits.

mHealth Assessment and Intervention of Depression and Anxiety in Older Adults

Mobile technology is increasingly being used to enhance health and wellness, including in the assessment and treatment of psychiatric disorders. Such applications have been referred to collectively as mHealth, and this article provides a comprehensive review and clinical perspective of research regarding mHealth in late-life mood and anxiety disorders. The novel data collection offered by mHealth has contributed to a broader understanding of psychopathology, to an increased diversity of psychological interventions, and to novel methods of assessment that may ultimately provide individually adaptive mental health care for this population. Older adults face challenges (e.g., transportation, mobility) that limit their ability to receive medical and mental health care services, and mHealth may improve the capacity to reach this population. Although several mobile interventions exist for health-related issues in older adults (e.g., balance, diabetes, medication management), mHealth targeting psychiatric disorders is limited and most often focuses on problems related to dementia, cognitive dysfunction, and memory loss. Given that depression and anxiety are two of the most common mental health concerns among this population, mHealth has strong potential for broad public health interventions that may improve effectiveness of mental health care via individualized assessments and treatments.

Evaluation of New Technology-Based Tools for Dietary Intake Assessment-An ILSI Europe Dietary Intake and Exposure Task Force Evaluation

BACKGROUND

New technology-based dietary assessment tools, including Web-based programs, mobile applications, and wearable devices, may improve accuracy and reduce costs of dietary data collection and processing. The International Life Sciences Institute (ILSI) Europe Dietary Intake and Exposure Task Force launched this project to evaluate new tools in order to recommend general quality standards for future applications.

METHODS

A comprehensive literature search identified technology-based dietary assessment tools, including those published in English from 01/2011 to 09/2017, and providing details on tool features, functions and uses. Each of the 43 tools identified (33 for research and 10 designed for consumer use) was rated on 25 attributes.

RESULTS

Most of the tools identified (79%) relied on self-reported dietary intakes. Most (91%) used text entry and 33% used digital images to help identify foods. Only 65% had integrated databases for estimating energy or nutrients. Fewer than 50% contained any features of customization and about half generated automatic reports. Most tools reported on usability or reported validity compared with another assessment method (77%). A set of Best Practice Guidelines was developed for reporting dietary assessment tools using new technology.

CONCLUSIONS

Dietary assessment methods that utilize technology offer many advantages for research and are often preferable to consumers over more traditional methods. In order to meet general quality standards, new technology tools require detailed publications describing tool development, food identification and quantification, customization, outputs, food composition tables used, and usability/validity testing.

The Use of Mobile Health Applications to Improve Patient Experience: Cross-Sectional Study in Chinese Public Hospitals

Background

The proliferation of mobile health apps has greatly changed the way society accesses the health care industry. However, despite the widespread use of mobile health apps by patients in China, there has been little research that evaluates the effect of mobile health apps on patient experience during hospital visits.

Objective

The purpose of our study was to examine whether the use of mobile health apps improves patient experience and to find out the difference in patient experience between users and nonusers and the characteristics associated with the users of these apps.

Methods

We used the Chinese Outpatient Experience Questionnaire to survey patient experience. A sample of 300 outpatients was randomly selected from 3 comprehensive public hospitals (3 tertiary hospitals) in Hubei province, China. Each hospital randomly selected 50 respondents from mobile health app users and 50 from nonusers. A chi-square test was employed to compare the different categorical characteristics between mobile health app users and nonusers. A t test was used to test the significance in continuous variables between user scores and nonuser scores. Multiple linear regression was conducted to determine whether the use of mobile health apps during hospital visits was associated with patient experience.

Results

The users and nonusers differed in age (χ²₂=12.2, P=.002), education (χ²₃=9.3, P=.03), living place (χ²₁=7.7, P=.006), and the need for specialists (χ²₄=11.0, P=.03). Compared with nonusers, mobile health app users in China were younger, better educated, living in urban areas, and had higher demands for specialists. In addition, mobile health app users gave significantly higher scores than nonusers in total patient experience scores (t₂₉₈=3.919, P<.001), the 18 items and the 5 dimensions of physician-patient communication (t₂₉₈=2.93, P=.004), health information (t₂₉₈=3.556, P<.001), medical service fees (t₂₉₈=3.991, P<.001), short-term outcome (t₂₉₈=4.533, P<.001), and general satisfaction (t₂₉₈=4.304, P<.001). Multiple linear regression results showed that the use of mobile health apps during hospital visits influenced patient experience (t₂₈₉=3.143, P=.002). After controlling for other factors, it was shown that the use of mobile health apps increased the outpatient experience scores by 17.7%. Additional results from the study found that the self-rated health status (t₂₈₉=3.746, P<.001) and monthly income of patients (t₂₈₉=2.416, P=.02) influenced the patient experience as well.

Conclusions

The use of mobile health apps could improve patient experience, especially with regard to accessing health information, making physician-patient communication more convenient, ensuring transparency in medical charge, and ameliorating short-term outcomes. All of these may contribute to positive health outcomes. Therefore, we should encourage the adoption of mobile health apps in health care settings so as to improve patient experience.

A Comparison of Food Portion Size Estimation by Older Adults, Young Adults and Nutritionists

OBJECTIVES

To investigate the ability of older adults, younger adults and nutritionists to assess portion size using traditional methods versus a computer-based method. This was to inform the development of a novel dietary assessment method for older adults "The NANA system".

DESIGN

Older and younger adults assessed the portion size of self-served portions of foods from a buffet style set up using traditional and computerised portion size assessment aids. Nutritionists assessed the portion size of foods from digital photographs using computerised portion size aids. These estimates were compared to known weights of foods using univariate analyses of covariance (ANCOVA).

SETTING

The University of Sheffield, United Kingdom.

SUBJECTS

Forty older adults (aged 65 years and over), 41 younger adults (aged between 18 and 40 years) and 25 nutritionists.

RESULTS

There was little difference in the abilities of older and younger adults to assess portion size using both assessment aids with the exception of small pieces morphology. Even though the methods were not directly comparable among the test groups, there was less variability in portion size estimates made by the nutritionists.

CONCLUSION

Older adults and younger adults are similar in their ability to assess food portion size and demonstrate wide variability of estimation compared to the ability of nutritionists to estimate portion size from photographs. The results suggest that the use of photographs of meals consumed for portion size assessment by a nutritionist may improve the accuracy of dietary assessment. Improved portion size assessment aids are required for all age groups.

Adherence to self-monitoring healthy lifestyle behaviours through mobile phone-based ecological momentary assessments and photographic food records over 6 months in mostly ethnic minority mothers

OBJECTIVE

Mobile phones can replace traditional self-monitoring tools through cell phone-based ecological momentary assessment (CEMA) of lifestyle behaviours and camera phone-based images of meals, i.e. photographic food records (PFR). Adherence to mobile self-monitoring needs to be evaluated in real-world treatment settings. Towards this goal, we examine CEMA and PFR adherence to the use of a mobile app designed to help mothers self-monitor lifestyle behaviours and stress. Design/Setting In 2012, forty-two mothers recorded CEMA of diet quality, exercise, sleep, stress and mood four times daily and PFR during meals over 6 months in Los Angeles, California, USA.

SUBJECTS

A purposive sample of mothers from mixed ethnicities.

RESULTS

Adherence to recording CEMA at least once daily was higher compared with recording PFR at least once daily over the study period (74 v. 11 %); adherence to both types of reports decreased over time. Participants who recorded PFR for more than a day (n 31) were more likely to be obese v. normal- to overweight and to have higher blood pressure, on average (all P<0·05). Based on random-effects regression, CEMA and PFR adherence was highest during weekdays (both P<0·01). Additionally, PFR adherence was associated with older age (P=0·04). CEMA adherence was highest in the morning (P<0·01). PFR recordings occurred throughout the day.

CONCLUSIONS

Variations in population and temporal characteristics should be considered for mobile assessment schedules. Neither CEMA nor PFR alone is ideal over extended periods.

Scaling up Dietary Data for Decision-Making in Low-Income Countries: New Technological Frontiers

Dietary surveys in low-income countries (LICs) are hindered by low investment in the necessary research infrastructure, including a lack of basic technology for data collection, links to food composition information, and data processing. The result has been a dearth of dietary data in many LICs because of the high cost and time burden associated with dietary surveys, which are typically carried out by interviewers using pencil and paper. This study reviewed innovative dietary assessment technologies and gauged their suitability to improve the quality and time required to collect dietary data in LICs. Predefined search terms were used to identify technologies from peer-reviewed and gray literature. A total of 78 technologies were identified and grouped into 6 categories: 1) computer- and tablet-based, 2) mobile-based, 3) camera-enabled, 4) scale-based, 5) wearable, and 6) handheld spectrometers. For each technology, information was extracted on a number of overarching factors, including the primary purpose, mode of administration, and data processing capabilities. Each technology was then assessed against predetermined criteria, including requirements for respondent literacy, battery life, requirements for connectivity, ability to measure macro- and micronutrients, and overall appropriateness for use in LICs. Few technologies reviewed met all the criteria, exhibiting both practical constraints and a lack of demonstrated feasibility for use in LICs, particularly for large-scale, population-based surveys. To increase collection of dietary data in LICs, development of a contextually adaptable, interviewer-administered dietary assessment platform is recommended. Additional investments in the research infrastructure are equally important to ensure time and cost savings for the user.

Do Image-Assisted Mobile Applications Improve Dietary Habits, Knowledge, and Behaviours in Elite Athletes? A Pilot Study

To date, there has been a paucity of research on optimal ways to educate and promote dietary behavioural change within athletes. Optimising athlete nutrition is fundamental to reaching peak performance and maintaining athlete wellbeing. MealLogger^® is a smartphone application that incorporates the use of an image-based food record and social-media functionality to provide in-application personalised feedback to individuals or groups, peer-support, and a platform to deliver nutrition education material. This study measured the feasibility of MealLogger^® within New Zealand elite male field hockey players (n = 17) aged 18–20 to increase athlete knowledge and nutrition promoting behaviours. During a six-week intervention, participants were instructed to log images of their meals three days per week and they received individualised dietetic feedback on logged meals. Weekly nutrition-education fact-sheets and videos were delivered through the application. Nutrition knowledge increased moderately from baseline (%Pre 54.7 ± 14.3; %Post 61.1 ± 11.45, p = 0.01). Participants report a highly positive experience of application use (8/10) with 82.3% attempting to make positive changes in dietary behaviours based on in-app education. All participants preferred this method to traditional methods of dietary analysis. Using image-based applications such as MealLogger^® is an effective approach to monitor dietary intake and deliver education to optimise the nutritional behaviours of elite athletes.

The patient perspective on the use of information and communication technologies and e-health in rehabilitation

INTRODUCTION

Success of e-health relies on the extent to which the related technology, such as the electronic device, is accepted by its users. However, there has been limited research on the patients' perspective on use of e-health-related technology in rehabilitation care.

OBJECTIVE

To explore the usage of common electronic devices among rehabilitation patients with access to email and investigate their preferences regarding their usage in rehabilitation.

METHODS

Adult patients who were admitted for inpatient and/or outpatient rehabilitation and were registered with an email address were invited to complete an electronic questionnaire regarding current and preferred use of information and communication technologies in rehabilitation care.

RESULTS

190 out of 714 invited patients completed the questionnaire, 94 (49%) female, mean age 49 years (SD 16). 149 patients (78%) used one or more devices every day, with the most frequently used devices were: PC/laptop (93%), smartphone (57%) and tablet (47%). Patients mostly preferred to use technology for contact with health professionals (mean 3.15, SD 0.79), followed by access to their personal record (mean 3.09, SD 0.78) and scheduling appointments with health professionals (mean 3.07, SD 0.85).

CONCLUSION

Most patients in rehabilitation used one or more devices almost every day and wish to use these devices in rehabilitation. Implications for Rehabilitation In a sample of 190 patients in rehabilitation with access to email, almost all patients used one or more electronic devices almost every day of the week, with the most frequently used devices were: a PC/laptop, smartphone and tablet. Most of the patients wish to incorporate electronic devices in their rehabilitation process and prefer to use those devices to have insight in their health record, communication with peers and scheduling appointments with health professionals. To better assist patients with e-health in rehabilitation care in the future, preferences could be implemented in rehabilitation care by using the most commonly used devices.

Novel Online or Mobile Methods to Assess Eating Patterns

Purpose of Review

Recent developments in technology-based dietary assessment allow real-time data collection of eating occasions, yet their application to assessing eating pattern constructs has not been evaluated. The purpose of this review was to examine existing electronic and mobile food diary methods in relation to their ability to assess eating patterns constructs (e.g. patterning, format and context of eating occasions).

Recent Findings

A systematic search of electronic databases identified 18 dietary assessment methods. Multiple methods with diverse technological capabilities have been developed, yet few studies report on their ability to assess all eating pattern constructs, particularly eating occasion context. Validity of the methods to assess overall dietary intake was found to be similar to traditional dietary assessment methods.

Summary

A diverse range of methods are available for examining the patterning and format/content, but not context, of eating occasions. Further consideration of eating pattern constructs is required when developing dietary assessment methods.

Evaluation of a smartphone food diary application using objectively measured energy expenditure

BACKGROUND

Dietary assessment methods are limited in their ability to adequately measure food and beverage consumption. Smartphone applications may provide a novel method of dietary assessment to capture real-time food intake and the contextual factors surrounding eating occasions. The aim of this study is to evaluate the capability of a Smartphone meal diary app ("FoodNow") to measure food intake using a validated objective method for assessing energy expenditure among young adults.

METHODS

Participants (18-30 years) used FoodNow over four non-consecutive days recording all eating occasions through a combination of written text, and/or optional images and voice recordings. A series of contextual questions were also completed. Participants wore the validated SenseWear Armband (BodyMedia Inc, USA) during the same period to measure free-living energy expenditure. Intra-class correlation coefficients (ICC) estimated the reliability of FoodNow to measure estimated energy intake compared to measured energy expenditure.

RESULTS

Ninety participants (71 female, 19 male; mean age = 24.9 ± 4.1 years) were recruited to use the FoodNow app to record their eating occasions. Thirteen were excluded as they did not meet minimum requirements for number of reporting days (n = 3) or SenseWear Armband wear time (5 days of 11 h), while 21 participants were excluded after being identified as mis-reporters (Huang method). Among the remaining sample (n = 56), reliability between estimated energy intake and measured energy expenditure was high (ICC, 95% CI: 0.75, 0.61-0.84).

CONCLUSIONS

FoodNow is a suitable method for capturing estimated energy intake data from young adults. Despite wide levels of agreement at the individual level (-3709 kJ to 2056 kJ), at the group level, FoodNow appears to have potential as a dietary assessment tool. This new dietary assessment method will offer an alternative and novel method of dietary assessment which is capable of collecting both estimated energy intake and contextual factors surrounding eating occasions. Information collected may be used to inform future public health messages or research interventions.

Validation of a Smartphone Image-Based Dietary Assessment Method for Pregnant Women

Image-based dietary records could lower participant burden associated with traditional prospective methods of dietary assessment. They have been used in children, adolescents and adults, but have not been evaluated in pregnant women. The current study evaluated relative validity of the DietBytes image-based dietary assessment method for assessing energy and nutrient intakes. Pregnant women collected image-based dietary records (via a smartphone application) of all food, drinks and supplements consumed over three non-consecutive days. Intakes from the image-based method were compared to intakes collected from three 24-h recalls, taken on random days; once per week, in the weeks following the image-based record. Data were analyzed using nutrient analysis software. Agreement between methods was ascertained using Pearson correlations and Bland-Altman plots. Twenty-five women (27 recruited, one withdrew, one incomplete), median age 29 years, 15 primiparas, eight Aboriginal Australians, completed image-based records for analysis. Significant correlations between the two methods were observed for energy, macronutrients and fiber (r = 0.58–0.84, all p < 0.05), and for micronutrients both including (r = 0.47–0.94, all p < 0.05) and excluding (r = 0.40–0.85, all p < 0.05) supplements in the analysis. Bland-Altman plots confirmed acceptable agreement with no systematic bias. The DietBytes method demonstrated acceptable relative validity for assessment of nutrient intakes of pregnant women.

Unobtrusive and Wearable Systems for Automatic Dietary Monitoring

The threat of obesity, diabetes, anorexia, and bulimia in our society today has motivated extensive research on dietary monitoring. Standard self-report methods such as 24-h recall and food frequency questionnaires are expensive, burdensome, and unreliable to handle the growing health crisis. Long-term activity monitoring in daily living is a promising approach to provide individuals with quantitative feedback that can encourage healthier habits. Although several studies have attempted automating dietary monitoring using wearable, handheld, smart-object, and environmental systems, it remains an open research problem. This paper aims to provide a comprehensive review of wearable and hand-held approaches from 2004 to 2016. Emphasis is placed on sensor types used, signal analysis and machine learning methods, as well as a benchmark of state-of-the art work in this field. Key issues, challenges, and gaps are highlighted to motivate future work toward development of effective, reliable, and robust dietary monitoring systems.

A Brief Tool to Assess Image-Based Dietary Records and Guide Nutrition Counselling Among Pregnant Women: An Evaluation

Background

Dietitians ideally should provide personally tailored nutrition advice to pregnant women. Provision is hampered by a lack of appropriate tools for nutrition assessment and counselling in practice settings. Smartphone technology, through the use of image-based dietary records, can address limitations of traditional methods of recording dietary intake. Feedback on these records can then be provided by the dietitian via smartphone. Efficacy and validity of these methods requires examination.

Objective

The aims of the Australian Diet Bytes and Baby Bumps study, which used image-based dietary records and a purpose-built brief Selected Nutrient and Diet Quality (SNaQ) tool to provide tailored nutrition advice to pregnant women, were to assess relative validity of the SNaQ tool for analyzing dietary intake compared with nutrient analysis software, to describe the nutritional intake adequacy of pregnant participants, and to assess acceptability of dietary feedback via smartphone.

Methods

Eligible women used a smartphone app to record everything they consumed over 3 nonconsecutive days. Records consisted of an image of the food or drink item placed next to a fiducial marker, with a voice or text description, or both, providing additional detail. We used the SNaQ tool to analyze participants’ intake of daily food group servings and selected key micronutrients for pregnancy relative to Australian guideline recommendations. A visual reference guide consisting of images of foods and drinks in standard serving sizes assisted the dietitian with quantification. Feedback on participants’ diets was provided via 2 methods: (1) a short video summary sent to participants’ smartphones, and (2) a follow-up telephone consultation with a dietitian. Agreement between dietary intake assessment using the SNaQ tool and nutrient analysis software was evaluated using Spearman rank correlation and Cohen kappa.

Results

We enrolled 27 women (median age 28.8 years, 8 Indigenous Australians, 15 primiparas), of whom 25 completed the image-based dietary record. Median intakes of grains, vegetables, fruit, meat, and dairy were below recommendations. Median (interquartile range) intake of energy-dense, nutrient-poor foods was 3.5 (2.4-3.9) servings/day and exceeded recommendations (0-2.5 servings/day). Positive correlations between the SNaQ tool and nutrient analysis software were observed for energy (ρ=.898, P<.001) and all selected micronutrients (iron, calcium, zinc, folate, and iodine, ρ range .510-.955, all P<.05), both with and without vitamin and mineral supplements included in the analysis. Cohen kappa showed moderate to substantial agreement for selected micronutrients when supplements were included (kappa range .488-.803, all P ≤.001) and for calcium, iodine, and zinc when excluded (kappa range .554-.632, all P<.001). A total of 17 women reported changing their diet as a result of the personalized nutrition advice.

Conclusions

The SNaQ tool demonstrated acceptable validity for assessing adequacy of key pregnancy nutrient intakes and preliminary evidence of utility to support dietitians in providing women with personalized advice to optimize nutrition during pregnancy.

Analysis of energy metabolism in humans: A review of methodologies

Background

Obesity is a consequence of chronic energy imbalance. We need accurate and precise measurements of energy intake and expenditure, as well as the related behaviors, to fully understand how energy homeostasis is regulated in order to develop interventions and evaluate their effectiveness to combat the global obesity epidemic.

Scope of review

We provide an in-depth review of the methodologies currently used to measure energy intake and expenditure in humans, including their principles, advantages, and limitations in the clinical research setting. The aim is to provide researchers with a comprehensive guide to conduct obesity research of the highest possible quality.

Major conclusions

An array of methodologies is available to measure various aspects of energy metabolism and none is perfect under all circumstances. The choice of methods should be specific to particular research questions with practicality and quality of data the priorities for consideration. A combination of complementary measurements may be preferable. There is an imperative need to develop new methodologies to improve the accuracy and precision of energy intake assessments.

•

Image-based technology is a significant step to improve energy intake measurement.

•

Physical activity informs patterns but not absolute energy expenditure.

•

Combining complementary measurements overcomes shortfalls of individual methods.

Using Personal Mobile Phones to Assess Dietary Intake in Free-Living Adolescents: Comparison of Face-to-Face Versus Telephone Training

Background

Traditional paper-based methods to assess food intake can be cumbersome for adolescents; use of mobile phones to track and photograph what they eat may be a more convenient, reliable, and compelling way to collect data.

Objective

Our aims were to determine (1) the feasibility of using personal mobile phones to send food records with digital images (FRDIs) among free-living adolescents and (2) whether the quality of food records differed between a high-level intervention group (ie, face-to-face training plus real-time support) and a low-level intervention group (ie, telephone training plus next-day follow-up).

Methods

Adolescents (N=42, 11 males and 31 females) aged 12-18 years who had a mobile phone with camera enrolled in the study via consecutive sampling. The first group (n=21) received face-to-face training while the second group (n=21) was trained via telephone. Participants received a fiducial marker (FM) and completed a 1-day FRDI using their mobile phones. At every eating occasion, participants were to (1) take clear images of their meals/food with a correctly placed fiducial marker before eating, (2) send the image immediately to a designated email address, (3) right after completing a meal, send a text message listing the time and name of the meal, foods eaten, and amounts eaten, and (4) before sleep, send an “end” text message to indicate completion of food recording. Those who received face-to-face training received real-time support during reporting; those trained by telephone received next-day follow-up. Descriptive statistics and comparison tests were used to determine performance of the groups.

Results

All participants (N=42) who underwent training completed their 1-day FRDI. A significantly greater proportion of the low-level intervention group compared to the high-level intervention group placed their FM correctly in the image (95% vs 43%, P<.001), had complete information for each meal in their food record (95% vs 71%, P=.04), and had a higher overall score in meeting the criteria for food recording (4.3 vs 3.4 out of 5 points). Both groups had energy intake values that moderately correlated with their estimated energy requirements: low-intervention r=.55; high-intervention r=.51.

Conclusions

Using personal mobile phones to report dietary intake via texting and digital images is feasible among free-living adolescents. Real-time support or high-level intervention does not guarantee better food recording quality among adolescents.

Designing, Implementing, and Evaluating Mobile Health Technologies for Managing Chronic Conditions in Older Adults: A Scoping Review

Background

The current landscape of a rapidly aging population accompanied by multiple chronic conditions presents numerous challenges to optimally support the complex needs of this group. Mobile health (mHealth) technologies have shown promise in supporting older persons to manage chronic conditions; however, there remains a dearth of evidence-informed guidance to develop such innovations.

Objectives

The purpose of this study was to conduct a scoping review of current practices and recommendations for designing, implementing, and evaluating mHealth technologies to support the management of chronic conditions in community-dwelling older adults.

Methods

A 5-stage scoping review methodology was used to map the relevant literature published between January 2005 and March 2015 as follows: (1) identified the research question, (2) identified relevant studies, (3) selected relevant studies for review, (4) charted data from selected literature, and (5) summarized and reported results. Electronic searches were conducted in 5 databases. In addition, hand searches of reference lists and a key journal were completed. Inclusion criteria were research and nonresearch papers focused on mHealth technologies designed for use by community-living older adults with at least one chronic condition, or health care providers or informal caregivers providing care in the home and community setting. Two reviewers independently identified articles for review and extracted data.

Results

We identified 42 articles that met the inclusion criteria. Of these, described innovations focused on older adults with specific chronic conditions (n=17), chronic conditions in general (n=6), or older adults in general or those receiving homecare services (n=18). Most of the mHealth solutions described were designed for use by both patients and health care providers or health care providers only. Thematic categories identified included the following: (1) practices and considerations when designing mHealth technologies; (2) factors that support/hinder feasibility, acceptability, and usability of mHealth technologies; and (3) approaches or methods for evaluating mHealth technologies.

Conclusions

There is limited yet increasing use of mHealth technologies in home health care for older adults. A user-centered, collaborative, interdisciplinary approach to enhance feasibility, acceptability, and usability of mHealth innovations is imperative. Creating teams with the required pools of expertise and insight regarding needs is critical. The cyclical, iterative process of developing mHealth innovations needs to be viewed as a whole with supportive theoretical frameworks. Many barriers to implementation and sustainability have limited the number of successful, evidence-based mHealth solutions beyond the pilot or feasibility stage. The science of implementation of mHealth technologies in home-based care for older adults and self-management of chronic conditions are important areas for further research. Additionally, changing needs as cohorts and technologies advance are important considerations. Lessons learned from the data and important implications for practice, policy, and research are discussed to inform the future development of innovations.

The development of a mobile u-Health program and evaluation for self-diet management for diabetic patients

BACKGROUND/OBJECTIVES

This study aims to develop a mobile nutritional management program for integration into the already developed web-based program, Diabetes Mellitus Dietary Management Guide (DMDMG) for diabetic patients. Further, we aim to evaluate the amended DMDMG program.

SUBJECTS/METHODS

The mobile application based on an Android operating system includes three parts: 1) record of diet intake, which allows users to take pictures of the meal and save to later add diet records into DMDMG; 2) an alarm system that rings at each meal time, which reminds users to input the data; 3) displays the diet record and the results of nutrient intake, which can be also viewed through the web program. All three parts are linked to the web-based program. A survey was conducted to evaluate the program in terms of nutrition knowledge, dietary attitude, eating behavior and diet intake by non-equivalent control group design among diabetic patients with 14 DMDMG users and 12 non-user controls after a one-month trial of DMDMG.

RESULTS

Non-users did not use the program, but participated in the weekly off-line nutrition classes for one month. The program users showed increased healthful dietary behavior (P < 0.01) and dietary attitude scores (P < 0.05). More DMDMG users had higher nutrition knowledge scores after one-month trial than non-users. However, dietary intake significantly increased in non-user group for calcium and sodium (P < 0.05) while the user group did not show significant changes.

CONCLUSIONS

The program has created positive changes in patients' dietary life. All the users were satisfied with the program, although some expressed minor difficulties with an unfamiliar mobile app.

eHealth technologies to support nutrition and physical activity behaviors in diabetes self-management

Diabetes is a chronic, complex condition requiring sound knowledge and self-management skills to optimize glycemic control and health outcomes. Dietary intake and physical activity are key diabetes self-management (DSM) behaviors that require tailored education and support. Electronic health (eHealth) technologies have a demonstrated potential for assisting individuals with DSM behaviors. This review provides examples of technologies used to support nutrition and physical activity behaviors in the context of DSM. Technologies covered include those widely used for DSM, such as web-based programs and mobile phone and smartphone applications. In addition, examples of novel tools such as virtual and augmented reality, video games, computer vision for dietary carbohydrate monitoring, and wearable devices are provided. The challenges to, and facilitators for, the use of eHealth technologies in DSM are discussed. Strategies to support the implementation of eHealth technologies within practice and suggestions for future research to enhance nutrition and physical activity behaviors as a part of broader DSM are provided.

A pilot study to determine whether using a lightweight, wearable micro-camera improves dietary assessment accuracy and offers information on macronutrients and eating rate

A major limitation in nutritional science is the lack of understanding of the nutritional intake of free-living people. There is an inverse relationship between accuracy of reporting of energy intake by all current nutritional methodologies and body weight. In this pilot study we aim to explore whether using a novel lightweight, wearable micro-camera improves the accuracy of dietary intake assessment. Doubly labelled water (DLW) was used to estimate energy expenditure and intake over a 14-d period, over which time participants (n 6) completed a food diary and wore a micro-camera on 2 of the days. Comparisons were made between the estimated energy intake from the reported food diary alone and together with the images from the micro-camera recordings. There was an average daily deficit of 3912 kJ using food diaries to estimate energy intake compared with estimated energy expenditure from DLW (P=0·0118), representing an under-reporting rate of 34 %. Analysis of food diaries alone showed a significant deficit in estimated daily energy intake compared with estimated intake from food diary analysis with images from the micro-camera recordings (405 kJ). Use of the micro-camera images in conjunction with food diaries improves the accuracy of dietary assessment and provides valuable information on macronutrient intake and eating rate. There is a need to develop this recording technique to remove user and assessor bias.

Electronic Dietary Intake Assessment (e-DIA): Comparison of a Mobile Phone Digital Entry App for Dietary Data Collection With 24-Hour Dietary Recalls

Background

The electronic Dietary Intake Assessment (e-DIA), a digital entry food record mobile phone app, was developed to measure energy and nutrient intake prospectively. This can be used in monitoring population intakes or intervention studies in young adults.

Objective

The objective was to assess the relative validity of e-DIA as a dietary assessment tool for energy and nutrient intakes using the 24-hour dietary recall as a reference method.

Methods

University students aged 19 to 24 years recorded their food and drink intake on the e-DIA for five days consecutively and completed 24-hour dietary recalls on three random days during this 5-day study period. Mean differences in energy, macro-, and micronutrient intakes were evaluated between the methods using paired t tests or Wilcoxon signed-rank tests, and correlation coefficients were calculated on unadjusted, energy-adjusted, and deattenuated values. Bland-Altman plots and cross-classification into quartiles were used to assess agreement between the two methods.

Results

Eighty participants completed the study (38% male). No significant differences were found between the two methods for mean intakes of energy or nutrients. Deattenuated correlation coefficients ranged from 0.55 to 0.79 (mean 0.68). Bland-Altman plots showed wide limits of agreement between the methods but without obvious bias. Cross-classification into same or adjacent quartiles ranged from 75% to 93% (mean 85%).

Conclusions

The e-DIA shows potential as a dietary intake assessment tool at a group level with good ranking agreement for energy and all nutrients.

Dietary Assessment on a Mobile Phone Using Image Processing and Pattern Recognition Techniques: Algorithm Design and System Prototyping

Dietary assessment, while traditionally based on pen-and-paper, is rapidly moving towards automatic approaches. This study describes an Australian automatic food record method and its prototype for dietary assessment via the use of a mobile phone and techniques of image processing and pattern recognition. Common visual features including scale invariant feature transformation (SIFT), local binary patterns (LBP), and colour are used for describing food images. The popular bag-of-words (BoW) model is employed for recognizing the images taken by a mobile phone for dietary assessment. Technical details are provided together with discussions on the issues and future work.

Evaluation of a Mobile Phone Image-Based Dietary Assessment Method in Adults with Type 2 Diabetes

Image-based dietary records have limited evidence evaluating their performance and use among adults with a chronic disease. This study evaluated the performance of a 3-day mobile phone image-based dietary record, the Nutricam Dietary Assessment Method (NuDAM), in adults with type 2 diabetes mellitus (T2DM). Criterion validity was determined by comparing energy intake (EI) with total energy expenditure (TEE) measured by the doubly-labelled water technique. Relative validity was established by comparison to a weighed food record (WFR). Inter-rater reliability was assessed by comparing estimates of intake from three dietitians. Ten adults (6 males, age: 61.2 ± 6.9 years old, BMI: 31.0 ± 4.5 kg/m²) participated. Compared to TEE, mean EI (MJ/day) was significantly under-reported using both methods, with a mean ratio of EI:TEE 0.76 ± 0.20 for the NuDAM and 0.76 ± 0.17 for the WFR. Correlations between the NuDAM and WFR were mostly moderate for energy (r = 0.57), carbohydrate (g/day) (r = 0.63, p < 0.05), protein (g/day) (r = 0.78, p < 0.01) and alcohol (g/day) (r_s = 0.85, p < 0.01), with a weaker relationship for fat (g/day) (r = 0.24). Agreement between dietitians for nutrient intake for the 3-day NuDAM (Intra-class Correlation Coefficient (ICC) = 0.77–0.99) was lower when compared with the 3-day WFR (ICC = 0.82–0.99). These findings demonstrate the performance and feasibility of the NuDAM to assess energy and macronutrient intake in a small sample. Some modifications to the NuDAM could improve efficiency and an evaluation in a larger group of adults with T2DM is required.

Development and validity of a 3-day smartphone assisted 24-hour recall to assess beverage consumption in a Chinese population: a randomized cross-over study

This paper addresses the need for diet assessment methods that capture the rapidly changing beverage consumption patterns in China. The objective of this study was to develop a 3-day smartphone-assisted 24-hour recall to improve the quantification of beverage intake amongst young Chinese adults (n=110) and validate, in a small subset (n=34), the extent to which the written record and smartphone-assisted recalls adequately estimated total fluid intake, using 24-hour urine samples. The smartphone-assisted method showed improved validity compared with the written record-assisted method, when comparing reported total fluid intake to total urine volume. However, participants reported consuming fewer beverages on the smartphone-assisted method compared with the written record-assisted method, primarily due to decreased consumption of traditional zero-energy beverages (i.e. water, tea) in the smartphone-assisted method. It is unclear why participants reported fewer beverages in the smartphone-assisted method than the written record -assisted method. One possibility is that participants found the smartphone method too cumbersome, and responded by decreasing beverage intake. These results suggest that smartphone-assisted 24-hour recalls perform comparably but do not appear to substantially improve beverage quantification compared with the current written record-based approach. In addition, we piloted a beverage screener to identify consumers of episodically consumed SSBs. As expected, a substantially higher proportion of consumers reported consuming SSBs on the beverage screener compared with either recall type, suggesting that a beverage screener may be useful in characterizing consumption of episodically consumed beverages in China's dynamic food and beverage landscape.

Usability of a smartphone food picture app for assisting 24-hour dietary recall: a pilot study

BACKGROUND/OBJECTIVES

The Recaller app was developed to help individuals record their food intakes. This pilot study evaluated the usability of this new food picture application (app), which operates on a smartphone with an embedded camera and Internet capability.

SUBJECTS/METHODS

Adults aged 19 to 28 years (23 males and 22 females) were assigned to use the Recaller app on six designated, nonconsecutive days in order to capture an image of each meal and snack before and after eating. The images were automatically time-stamped and uploaded by the app to the Recaller website. A trained nutritionist administered a 24-hour dietary recall interview 1 day after food images were taken. Participants' opinions of the Recaller app and its usability were determined by a follow-up survey. As an evaluation indicator of usability, the number of images taken was analyzed and multivariate Poisson regression used to model the factors determining the number of images sent.

RESULTS

A total of 3,315 food images were uploaded throughout the study period. The median number of images taken per day was nine for males and 13 for females. The survey showed that the Recaller app was easy to use, and 50% of the participants would consider using the app daily. Predictors of a higher number of images were as follows: greater interval (hours) between the first and last food images sent, weekend, and female.

CONCLUSIONS

The results of this pilot study provide valuable information for understanding the usability of the Recaller smartphone food picture app as well as other similarly designed apps. This study provides a model for assisting nutrition educators in their collection of food intake information by using tools available on smartphones. This innovative approach has the potential to improve recall of foods eaten and monitoring of dietary intake in nutritional studies.

Image-assisted dietary assessment: a systematic review of the evidence

Images captured during eating episodes provide objective information to assist in the assessment of dietary intake. Images are captured using handheld devices or wearable cameras, and can support traditional self-report or provide the primary record of dietary intake. A diverse range of image-assisted methods have been developed and evaluated but have not been previously examined together. Therefore, a review was undertaken to examine all studies that have evaluated or validated image-assisted methods of dietary assessment for assessing dietary energy intake. Identified image-assisted methods that employ similar methodologies were grouped for comparison. English-language full-text research articles published between January 1998 and November 2013 were searched using five electronic databases. A search of reference lists and associated websites was also conducted. Thirteen studies that evaluated 10 unique image-assisted methods among adults aged 18 to 70 years were included. Ten studies used handheld devices and three studies used wearable cameras. Eight studies evaluated image-based food records, two studies explored the use of images to enhance written food records, and three studies evaluated image-assisted 24-hour dietary recalls. Results indicate images enhance self-report by revealing unreported foods and identify misreporting errors not captured by traditional methods alone. Moreover, when used as the primary record of dietary intake, images can provide valid estimates of energy intake. However, image-assisted methods that rely on image analysis can be prone to underestimation if users do not capture images of satisfactory quality before all foods are consumed. Further validation studies using criterion measures are warranted. The validity among children, adolescents, and elderly persons as well as the feasibility of using image-assisted methods in large samples needs to be examined. Additional research is also needed to better understand the potential applications and pitfalls of wearable cameras.

Dietary assessment methods in epidemiologic studies

Diet is a major lifestyle-related risk factor of various chronic diseases. Dietary intake can be assessed by subjective report and objective observation. Subjective assessment is possible using open-ended surveys such as dietary recalls or records, or using closed-ended surveys including food frequency questionnaires. Each method has inherent strengths and limitations. Continued efforts to improve the accuracy of dietary intake assessment and enhance its feasibility in epidemiological studies have been made. This article reviews common dietary assessment methods and their feasibility in epidemiological studies.