Nutrients

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4 pages, 189 KiB

Open AccessEditorial

Advancement in Dietary Assessment and Self-Monitoring Using Technology

by Tracy L. Burrows and Megan E. Rollo

Nutrients 2019, 11(7), 1648; https://doi.org/10.3390/nu11071648 - 19 Jul 2019

Cited by 8 | Viewed by 3480

Abstract

On the surface, some methods to assess and self-monitor dietary intake may be considered similar; however, the intended function of each is quite distinct [...] Full article

(This article belongs to the Special Issue Advancement in Dietary Assessment and Self-Monitoring Using Technology)

Research

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14 pages, 414 KiB

Open AccessArticle

Mobile Phone Text Message Intervention on Diabetes Self-Care Activities, Cardiovascular Disease Risk Awareness, and Food Choices among Type 2 Diabetes Patients

by Martha J. Nepper, Jennifer R. McAtee, Lorey Wheeler and Weiwen Chai

Nutrients 2019, 11(6), 1314; https://doi.org/10.3390/nu11061314 - 11 Jun 2019

Cited by 13 | Viewed by 5420

Abstract

This study examines the effects of educational text messages on diabetes self-care activities, cardiovascular disease (CVD) risk awareness, and home food availabilities related to food choices among patients with type 2 diabetes. Quasi-experimental design was used with 40 patients (58.0 ± 10.6 years) [...] Read more.

This study examines the effects of educational text messages on diabetes self-care activities, cardiovascular disease (CVD) risk awareness, and home food availabilities related to food choices among patients with type 2 diabetes. Quasi-experimental design was used with 40 patients (58.0 ± 10.6 years) in the intervention group and 39 (55.7 ± 12.2 years) in the control group. In addition to the usual care provided for all participants, the intervention group received three educational text messages weekly for 12 weeks. Pre- and post-intervention measures were collected for both groups. Ninety-four percent of the participants receiving text messages indicated the usefulness of this program. The intervention group either maintained the same level or demonstrated small improvements in diabetes self-care activities after the intervention. Significant increases in scores of CVD risk awareness (57% increase; p = 0.04) and availabilities of fresh fruits (320% increase; p = 0.01) and fresh vegetables (250% increase; p = 0.02) in the home and weekly total (16% increase; p = 0.02) and moderate/vigorous (80% increase; p = 0.006) physical activity levels were observed for the intervention group relative to the control group. The pilot results suggest the feasibility and usefulness of the text message program for diabetes education. The study is registered with Clinical Trials.gov (NCT03039569). Full article

(This article belongs to the Special Issue Advancement in Dietary Assessment and Self-Monitoring Using Technology)

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17 pages, 4821 KiB

Open AccessFeature PaperArticle

An End-to-End Image-Based Automatic Food Energy Estimation Technique Based on Learned Energy Distribution Images: Protocol and Methodology

by Shaobo Fang, Zeman Shao, Deborah A. Kerr, Carol J. Boushey and Fengqing Zhu

Nutrients 2019, 11(4), 877; https://doi.org/10.3390/nu11040877 - 18 Apr 2019

Cited by 50 | Viewed by 6160

Abstract

Obtaining accurate food portion estimation automatically is challenging since the processes of food preparation and consumption impose large variations on food shapes and appearances. The aim of this paper was to estimate the food energy numeric value from eating occasion images captured using [...] Read more.

Obtaining accurate food portion estimation automatically is challenging since the processes of food preparation and consumption impose large variations on food shapes and appearances. The aim of this paper was to estimate the food energy numeric value from eating occasion images captured using the mobile food record. To model the characteristics of food energy distribution in an eating scene, a new concept of “food energy distribution” was introduced. The mapping of a food image to its energy distribution was learned using Generative Adversarial Network (GAN) architecture. Food energy was estimated from the image based on the energy distribution image predicted by GAN. The proposed method was validated on a set of food images collected from a 7-day dietary study among 45 community-dwelling men and women between 21–65 years. The ground truth food energy was obtained from pre-weighed foods provided to the participants. The predicted food energy values using our end-to-end energy estimation system was compared to the ground truth food energy values. The average error in the estimated energy was 209 kcal per eating occasion. These results show promise for improving accuracy of image-based dietary assessment. Full article

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12 pages, 1254 KiB

Open AccessArticle

Relative Validity of the Eat and Track (EaT) Smartphone App for Collection of Dietary Intake Data in 18-to-30-Year Olds

by Lyndal Wellard-Cole, Juliana Chen, Alyse Davies, Adele Wong, Sharon Huynh, Anna Rangan and Margaret Allman-Farinelli

Nutrients 2019, 11(3), 621; https://doi.org/10.3390/nu11030621 - 14 Mar 2019

Cited by 32 | Viewed by 5035

Abstract

(1) Background: Smartphone dietary assessment apps can be acceptable and valid data collection methods but have predominantly been validated in highly educated women, and none specifically measured eating-out habits in young adults. (2) Methods: Participants recorded their food and beverage consumption for three [...] Read more.

(1) Background: Smartphone dietary assessment apps can be acceptable and valid data collection methods but have predominantly been validated in highly educated women, and none specifically measured eating-out habits in young adults. (2) Methods: Participants recorded their food and beverage consumption for three days using the Eat and Track (EaT) app, and intakes were compared with three dietitian-administered 24-h recall interviews matched to the same days as the reference method. Wilcoxon signed-rank or t-tests, correlation coefficients and Bland–Altman plots assessed agreement between the two methods for energy and percentage energy from nutrients (%E). (3) Results: One hundred and eighty nine of 216 participants (54% females, 60% resided in higher socioeconomic areas, 49% university-educated) completed the study. There were significant differences in median energy intake between methods (p < 0.001), but the EaT app had acceptable agreement for most nutrient densities at the group level. Correlation coefficients ranged from r = 0.56 (%E fat) to 0.82 (%E sugars), and between 85% and 94% of participants were cross-classified into the same or adjacent quartiles. Bland–Altman plots showed wide limits of agreement but no obvious biases for nutrient densities except carbohydrate in males. (4) Conclusions: The EaT app can be used to assess group nutrient densities in a general population of 18-to-30-year olds. Full article

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12 pages, 1401 KiB

Open AccessFeature PaperArticle

Validation of Sensor-Based Food Intake Detection by Multicamera Video Observation in an Unconstrained Environment

by Muhammad Farooq, Abul Doulah, Jason Parton, Megan A. McCrory, Janine A. Higgins and Edward Sazonov

Nutrients 2019, 11(3), 609; https://doi.org/10.3390/nu11030609 - 13 Mar 2019

Cited by 35 | Viewed by 4062

Abstract

Video observations have been widely used for providing ground truth for wearable systems for monitoring food intake in controlled laboratory conditions; however, video observation requires participants be confined to a defined space. The purpose of this analysis was to test an alternative approach [...] Read more.

Video observations have been widely used for providing ground truth for wearable systems for monitoring food intake in controlled laboratory conditions; however, video observation requires participants be confined to a defined space. The purpose of this analysis was to test an alternative approach for establishing activity types and food intake bouts in a relatively unconstrained environment. The accuracy of a wearable system for assessing food intake was compared with that from video observation, and inter-rater reliability of annotation was also evaluated. Forty participants were enrolled. Multiple participants were simultaneously monitored in a 4-bedroom apartment using six cameras for three days each. Participants could leave the apartment overnight and for short periods of time during the day, during which time monitoring did not take place. A wearable system (Automatic Ingestion Monitor, AIM) was used to detect and monitor participants’ food intake at a resolution of 30 s using a neural network classifier. Two different food intake detection models were tested, one trained on the data from an earlier study and the other on current study data using leave-one-out cross validation. Three trained human raters annotated the videos for major activities of daily living including eating, drinking, resting, walking, and talking. They further annotated individual bites and chewing bouts for each food intake bout. Results for inter-rater reliability showed that, for activity annotation, the raters achieved an average (±standard deviation (STD)) kappa value of 0.74 (±0.02) and for food intake annotation the average kappa (Light’s kappa) of 0.82 (±0.04). Validity results showed that AIM food intake detection matched human video-annotated food intake with a kappa of 0.77 (±0.10) and 0.78 (±0.12) for activity annotation and for food intake bout annotation, respectively. Results of one-way ANOVA suggest that there are no statistically significant differences among the average eating duration estimated from raters’ annotations and AIM predictions (p-value = 0.19). These results suggest that the AIM provides accuracy comparable to video observation and may be used to reliably detect food intake in multi-day observational studies. Full article

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19 pages, 572 KiB

Open AccessArticle

Validity and Reproducibility of a Self-Administered Food Frequency Questionnaire for the Assessment of Sugar Intake in Middle-Aged Japanese Adults

by Rieko Kanehara, Atsushi Goto, Ayaka Kotemori, Nagisa Mori, Ari Nakamura, Norie Sawada, Junko Ishihara, Ribeka Takachi, Yukari Kawano, Motoki Iwasaki, Shoichiro Tsugane and for the JPHC FFQ Validation Study Group

Nutrients 2019, 11(3), 554; https://doi.org/10.3390/nu11030554 - 5 Mar 2019

Cited by 11 | Viewed by 4078

Abstract

We evaluated the validity and reproducibility of estimated sugar intakes using a food frequency questionnaire (FFQ) among middle-aged Japanese adults in the Japan Public Health Centre-Based Prospective (JPHC) study. In subsamples of the JPHC study (Cohorts I and II in multiple areas), we [...] Read more.

We evaluated the validity and reproducibility of estimated sugar intakes using a food frequency questionnaire (FFQ) among middle-aged Japanese adults in the Japan Public Health Centre-Based Prospective (JPHC) study. In subsamples of the JPHC study (Cohorts I and II in multiple areas), we computed Spearman’s correlations of FFQ results with urine sugar concentrations and dietary records (DR) for validity; we evaluated correlations between two FFQs for reproducibility. During 1994–1998, participants (Cohort I: n = 27 [men], n = 45 [women]) provided two (spring and fall) 24-h urine samples and completed 7-consecutive-day DR per season (I: n = 99, n = 113; II: n = 168, n = 171) and two FFQs (147 food items) at yearly intervals (I: n = 101, n = 108; II: n = 143, n = 146). Sugar intakes from FFQ were correlated with urinary sugar (de-attenuated correlations: 0.40; 95%CI: 0.19, 0.58). After adjustment for sociodemographic and lifestyle variables, correlations between FFQ and DR for men and women were 0.57 (0.42, 0.69) and 0.41 (0.24, 0.55) (I) and 0.56 (0.44, 0.65) and 0.34 (0.20, 0.47) (II), respectively. Correlations between FFQs for men and women were 0.63 (0.49, 0.73) and 0.55 (0.41, 0.67) (I) and 0.66 (0.55, 0.74) and 0.63 (0.52, 0.72) (II). In conclusion, our study showed moderate FFQ validity and reproducibility for sugar intake evaluation. Full article

(This article belongs to the Special Issue Advancement in Dietary Assessment and Self-Monitoring Using Technology)

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16 pages, 446 KiB

Open AccessArticle

Requirements of an Application to Monitor Diet, Physical Activity and Glucose Values in Patients with Type 2 Diabetes: The Diameter

by Niala den Braber, Miriam M. R. Vollenbroek-Hutten, Milou M. Oosterwijk, Christina M. Gant, Ilse J. M. Hagedoorn, Bert-Jan F. van Beijnum, Hermie J. Hermens and Gozewijn D. Laverman

Nutrients 2019, 11(2), 409; https://doi.org/10.3390/nu11020409 - 15 Feb 2019

Cited by 14 | Viewed by 5491

Abstract

Adherence to a healthy diet and regular physical activity are two important factors in sufficient type 2 diabetes mellitus management. It is recognized that the traditional treatment of outpatients does not meet the requirements for sufficient lifestyle management. It is hypothesised that a [...] Read more.

Adherence to a healthy diet and regular physical activity are two important factors in sufficient type 2 diabetes mellitus management. It is recognized that the traditional treatment of outpatients does not meet the requirements for sufficient lifestyle management. It is hypothesised that a personalized diabetes management mHealth application can help. Such an application ideally measures food intake, physical activity, glucose values, and medication use, and then integrates this to provide patients and healthcare professionals insight in these factors, as well as the effect of lifestyle on glucose values in daily life. The lifestyle data can be used to give tailored coaching to improve adherence to lifestyle recommendations and medication use. This study describes the requirements for such an application: the Diameter. An iterative mixed method design approach is used that consists of a cohort study, pilot studies, literature search, and expert meetings. The requirements are defined according to the Function and events, Interactions and usability, Content and structure and Style and aesthetics (FICS) framework. This resulted in 81 requirements for the dietary (n = 37), activity and sedentary (n = 15), glycaemic (n = 12), and general (n = 17) parts. Although many applications are currently available, many of these requirements are not implemented. This stresses the need for the Diameter as a new personalized diabetes application. Full article

(This article belongs to the Special Issue Advancement in Dietary Assessment and Self-Monitoring Using Technology)

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17 pages, 980 KiB

Open AccessArticle

Evaluation of the Recipe Function in Popular Dietary Smartphone Applications, with Emphasize on Features Relevant for Nutrition Assessment in Large-Scale Studies

by Liangzi Zhang, Eline Nawijn, Hendriek Boshuizen and Marga Ocké

Nutrients 2019, 11(1), 200; https://doi.org/10.3390/nu11010200 - 19 Jan 2019

Cited by 7 | Viewed by 6749

Abstract

Nutrient estimations from mixed dishes require detailed information collection and should account for nutrient loss during cooking. This study aims to make an inventory of recipe creating features in popular food diary apps from a research perspective and to evaluate their nutrient calculation. [...] Read more.

Nutrient estimations from mixed dishes require detailed information collection and should account for nutrient loss during cooking. This study aims to make an inventory of recipe creating features in popular food diary apps from a research perspective and to evaluate their nutrient calculation. A total of 12 out of 57 screened popular dietary assessment apps included a recipe function and were scored based on a pre-defined criteria list. Energy and nutrient content of three recipes calculated by the apps were compared with a reference procedure, which takes nutrient retention due to cooking into account. The quality of the recipe function varies across selected apps with a mean score of 3.0 (out of 5). More relevant differences (larger than 5% of the Daily Reference Intake) between apps and the reference were observed in micronutrients (49%) than in energy and macronutrients (20%). The primary source of these differences lies in the variation in food composition databases underlying each app. Applying retention factors decreased the micronutrient contents from 0% for calcium in all recipes to more than 45% for vitamins B6, B12, and folate in one recipe. Overall, recipe features and their ability to capture true nutrient intake are limited in current apps. Full article

(This article belongs to the Special Issue Advancement in Dietary Assessment and Self-Monitoring Using Technology)

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23 pages, 2255 KiB

Open AccessArticle

Assessing the Usability of the Automated Self-Administered Dietary Assessment Tool (ASA24) among Low-Income Adults

by Julia Kupis, Sydney Johnson, Gregory Hallihan and Dana Lee Olstad

Nutrients 2019, 11(1), 132; https://doi.org/10.3390/nu11010132 - 10 Jan 2019

Cited by 36 | Viewed by 7811

Abstract

The Automated Self-Administered Dietary Assessment Tool (ASA24) is a web-based tool that guides participants through completion of a 24-h dietary recall and automatically codes the data. Despite the advantages of automation, eliminating interviewer contact may diminish data quality. Usability testing can assess the [...] Read more.

The Automated Self-Administered Dietary Assessment Tool (ASA24) is a web-based tool that guides participants through completion of a 24-h dietary recall and automatically codes the data. Despite the advantages of automation, eliminating interviewer contact may diminish data quality. Usability testing can assess the extent to which individuals can use the ASA24 to report dietary intake with efficiency, effectiveness, and satisfaction. This mixed-methods study evaluated the usability of the ASA24 to quantify user performance and to examine qualitatively usability issues in a sample of low-income adults (85% female, 48.2 years on average) participating in a nutrition coupon program. Thirty-nine participants completed a 24-h dietary recall using the ASA24. Audio and screen recordings, and survey responses were analyzed to calculate task times, success rates, and usability issue frequency. Qualitative data were analyzed thematically to characterize usability issues. Only one participant was able to complete a dietary recall unassisted. We identified 286 usability issues within 22 general usability categories, including difficulties using the search function, misunderstanding questions, and uncertainty regarding how to proceed to the next step; 71.4% of participants knowingly misentered dietary information at least once. Usability issues may diminish participation rates and compromise the quality of ASA24 dietary intake data. Researchers should provide on-demand technical support and designers should improve the intelligence and flexibility of the ASA24’s search functionality. Full article

(This article belongs to the Special Issue Advancement in Dietary Assessment and Self-Monitoring Using Technology)

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13 pages, 492 KiB

Open AccessArticle

Effectiveness of the Nutritional App “MyNutriCart” on Food Choices Related to Purchase and Dietary Behavior: A Pilot Randomized Controlled Trial

by Cristina Palacios, Michelle Torres, Desiree López, Maria A. Trak-Fellermeier, Catherine Coccia and Cynthia M. Pérez

Nutrients 2018, 10(12), 1967; https://doi.org/10.3390/nu10121967 - 12 Dec 2018

Cited by 23 | Viewed by 5873

Abstract

Objective: To pilot test the effectiveness of “MyNutriCart”, a smartphone application (app) that generates healthy grocery lists, on diet and weight. Methods: A pilot randomized trial was conducted to test the efficacy of using the “MyNutriCart” app compared to one face-to-face counseling session [...] Read more.

Objective: To pilot test the effectiveness of “MyNutriCart”, a smartphone application (app) that generates healthy grocery lists, on diet and weight. Methods: A pilot randomized trial was conducted to test the efficacy of using the “MyNutriCart” app compared to one face-to-face counseling session (Traditional group) in Hispanic overweight and obese adults. Household food purchasing behavior, three 24-h food recalls, Tucker’s semi-quantitative food frequency questionnaire (FFQ), and weight were assessed at baseline and after 8 weeks. Statistical analyses included t tests, a Poisson regression model, and analysis of covariance (ANCOVA) using STATA. Results: 24 participants in the Traditional group and 27 in the App group completed the study. Most participants were women (>88%), with a mean age of 35.3 years, more than a high school education (>80%), a family composition of at least three members, and a mean baseline body mass index (BMI) of 34.5 kg/m². There were significant improvements in household purchasing of vegetables and whole grains, in individual intakes of refined grains, healthy proteins, whole-fat dairies, legumes, 100% fruit juices, and sweets and snacks; and in the individual frequency of intake of fruits and cold cuts/cured meats within the intervention group (p < 0.05). However, no significant differences were found between groups. No changes were detected in weight. Conclusions: “MyNutriCart” app use led to significant improvements in food-related behaviors compared to baseline, with no significant differences when compared to the Traditional group. Cost and resource savings of using the app compared to face-to-face counseling may make it a good option for interventionists. Full article

(This article belongs to the Special Issue Advancement in Dietary Assessment and Self-Monitoring Using Technology)

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11 pages, 790 KiB

Open AccessArticle

Active Image-Assisted Food Records in Comparison to Regular Food Records: A Validation Study against Doubly Labeled Water in 12-Month-Old Infants

by Ulrica Johansson, Michelle Venables, Inger Öhlund and Torbjörn Lind

Nutrients 2018, 10(12), 1904; https://doi.org/10.3390/nu10121904 - 4 Dec 2018

Cited by 7 | Viewed by 3472

Abstract

Overreporting of dietary intake in infants is a problem when using food records (FR), distorting possible relationships between diet and health outcomes. Image-assisted dietary assessment may improve the accuracy, but to date, evaluation in the pediatric setting is limited. The aim of the [...] Read more.

Overreporting of dietary intake in infants is a problem when using food records (FR), distorting possible relationships between diet and health outcomes. Image-assisted dietary assessment may improve the accuracy, but to date, evaluation in the pediatric setting is limited. The aim of the study was to compare macronutrient and energy intake by using an active image-assisted five-day FR against a regular five-day FR, and to validate image-assistance with total energy expenditure (TEE), was measured using doubly labeled water. Participants in this validation study were 22 healthy infants randomly selected from the control group of a larger, randomized intervention trial. The parents reported the infants’ dietary intake, and supplied images of main course meals taken from standardized flat-surfaced plates before and after eating episodes. Energy and nutrient intakes were calculated separately using regular FR and image-assisted FRs. The mean (± standard deviations) energy intake (EI) was 3902 ± 476 kJ/day from the regular FR, and 3905 ± 476 kJ/day from the FR using active image-assistance. The mean EI from main-course meals when image-assistance was used did not differ (1.7 ± 55 kJ, p = 0.89) compared to regular FRs nor did the intake of macronutrients. Compared to TEE, image-assisted FR overestimated EI by 10%. Without validation, commercially available software to aid in the volume estimations, food item identification, and automation of the image processing, image-assisted methods remain a more costly and burdensome alternative to regular FRs in infants. The image-assisted method did, however, identify leftovers better than did regular FR, where such information is usually not readily available. Full article

(This article belongs to the Special Issue Advancement in Dietary Assessment and Self-Monitoring Using Technology)

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7 pages, 631 KiB

Open AccessArticle

Technology-Based Dietary Assessment in Youth with and Without Developmental Disabilities

by Michele Polfuss, Andrea Moosreiner, Carol J. Boushey, Edward J. Delp and Fengqing Zhu

Nutrients 2018, 10(10), 1482; https://doi.org/10.3390/nu10101482 - 11 Oct 2018

Cited by 13 | Viewed by 4196

Abstract

Obesity prevalence is higher in children with developmental disabilities as compared to their typically developing peers. Research on dietary intake assessment methods in this vulnerable population is lacking. The objectives of this study were to assess the feasibility, acceptability, and compare the nutrient [...] Read more.

Obesity prevalence is higher in children with developmental disabilities as compared to their typically developing peers. Research on dietary intake assessment methods in this vulnerable population is lacking. The objectives of this study were to assess the feasibility, acceptability, and compare the nutrient intakes of two technology-based dietary assessment methods in children with-and-without developmental disabilities. This cross-sectional feasibility study was an added aim to a larger pilot study. Children (n = 12; 8–18 years) diagnosed with spina bifida, Down syndrome, or without disability were recruited from the larger study sample, stratified by diagnosis. Participants were asked to complete six days of a mobile food record (mFR™), a 24-h dietary recall via FaceTime^® (24 HR-FT), and a post-study survey. Analysis included descriptive statistics for survey results and a paired samples t-test for nutrient intakes. All participants successfully completed six days of dietary assessment using both methods and acceptability was high. Energy (kcal) and protein (g) intake was significantly higher for the mFR™ as compared to the 24 HR-FT (p = 0.041; p = 0.014, respectively). Each method had strengths and weaknesses. The two technology-based dietary assessment tools were well accepted and when combined could increase accuracy of self-reported dietary assessment in children with-and-without disability. Full article

(This article belongs to the Special Issue Advancement in Dietary Assessment and Self-Monitoring Using Technology)

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11 pages, 475 KiB

Open AccessArticle

A Qualitative Evaluation of the eaTracker^® Mobile App

by Jessica R. L. Lieffers, Renata F. Valaitis, Tessy George, Mark Wilson, Janice Macdonald and Rhona M. Hanning

Nutrients 2018, 10(10), 1462; https://doi.org/10.3390/nu10101462 - 9 Oct 2018

Cited by 10 | Viewed by 4689

Abstract

Background: eaTracker^® is Dietitians of Canada’s online nutrition/activity self-monitoring tool accessible via website and mobile app. The purpose of this research was to evaluate the eaTracker^® mobile app based on user perspectives. Methods: One-on-one semi-structured interviews were conducted with adult eaTracker [...] Read more.

Background: eaTracker^® is Dietitians of Canada’s online nutrition/activity self-monitoring tool accessible via website and mobile app. The purpose of this research was to evaluate the eaTracker^® mobile app based on user perspectives. Methods: One-on-one semi-structured interviews were conducted with adult eaTracker^® mobile app users who had used the app for ≥ 1 week within the past 90 days. Participants (n = 26; 89% female, 73% 18–50 years) were recruited via email. Interview transcripts were coded using first level coding and pattern coding, where first level codes were grouped according to common themes. Results: Participants mentioned several positive aspects of the mobile app which included: (a) Dashboard displays; (b) backed by dietitians; (c) convenience and ease of use; (d) portion size entry; (e) inclusion of food and physical activity recording; and (f) ability to access more comprehensive information via the eaTracker^® website. Challenges with the mobile app included: (a) Search feature; (b) limited food database; (c) differences in mobile app versus website; and (d) inability to customize dashboard displayed information. Suggestions were provided to enhance the app. Conclusion: This evaluation provides useful information to improve the eaTracker^® mobile app and also for those looking to develop apps to facilitate positive nutrition/physical activity behavior change. Full article

(This article belongs to the Special Issue Advancement in Dietary Assessment and Self-Monitoring Using Technology)

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11 pages, 843 KiB

Open AccessArticle

Comparing Interviewer-Administered and Web-Based Food Frequency Questionnaires to Predict Energy Requirements in Adults

by Didier Brassard, Simone Lemieux, Amélie Charest, Annie Lapointe, Patrick Couture, Marie-Ève Labonté and Benoît Lamarche

Nutrients 2018, 10(9), 1292; https://doi.org/10.3390/nu10091292 - 12 Sep 2018

Cited by 14 | Viewed by 3859

Abstract

Traditional food frequency questionnaires (FFQs) are influenced by systematic error, but web-based FFQ (WEB-FFQs) may mitigate this source of error. The objective of this study was to compare the accuracy of interview-based and web-based FFQs to assess energy requirements (mERs). The mER was [...] Read more.

Traditional food frequency questionnaires (FFQs) are influenced by systematic error, but web-based FFQ (WEB-FFQs) may mitigate this source of error. The objective of this study was to compare the accuracy of interview-based and web-based FFQs to assess energy requirements (mERs). The mER was measured in a series of controlled feeding trials in which participants daily received all foods and caloric drinks to maintain stable body weight over 4 to 6 weeks. FFQs assessing dietary intakes and hence mean energy intake were either interviewer-administered by a registered dietitian (IA-FFQ, n = 127; control method) or self-administered using a web-based platform (WEB-FFQ, n = 200; test method), on a single occasion. Comparison between self-reported energy intake and mER revealed significant under-reporting with the IA-FFQ (−9.5%; 95% CI, −12.7 to −6.1) and with the WEB-FFQ (−11.0%; 95% CI, −15.4 to −6.4), but to a similar extent between FFQs (p = 0.62). However, a greater proportion of individuals were considered as accurate reporters of energy intake using the IA-FFQ compared with the WEB-FFQ (67.7% vs. 48.0%, respectively), while the prevalence of over-reporting was lower with the IA-FFQ than with the WEB-FFQ (6.3% vs. 17.5%, respectively). These results suggest less accurate prediction of true energy intake by a self-administered WEB-FFQ than with an IA-FFQ. Full article

(This article belongs to the Special Issue Advancement in Dietary Assessment and Self-Monitoring Using Technology)

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13 pages, 209 KiB

Open AccessArticle

Comparison of Nutrient Estimates Based on Food Volume versus Weight: Implications for Dietary Assessment Methods

by Emma K. Partridge, Marian L. Neuhouser, Kara Breymeyer and Jeannette M. Schenk

Nutrients 2018, 10(8), 973; https://doi.org/10.3390/nu10080973 - 27 Jul 2018

Cited by 7 | Viewed by 4025

Abstract

Novel technology-based dietary assessment methods use volume estimates of foods to assess dietary intake. However, the nutrient content of standard databases is based on food weight. The goal of this study is to evaluate the accuracy of the United States Department of Agriculture [...] Read more.

Novel technology-based dietary assessment methods use volume estimates of foods to assess dietary intake. However, the nutrient content of standard databases is based on food weight. The goal of this study is to evaluate the accuracy of the United States Department of Agriculture National Nutrient Database for Standard Reference (USDA-SR) estimates of volume and the corresponding macronutrient content of the foods. The weights of 35 individual food volumes were measured (on trial) and compared to the USDA-SR-determined weight for the food volume. Macronutrient content corresponding to the trial weight and the USDA-SR weight for the food volume (USDA) were determined using the USDA-SR, and the differences were calculated. There were statistically significant differences between the USDA and trial weights for 80% of foods measured. Calorie estimates by USDA weight were significantly lower than that of trial weight for 54% of foods but were significantly greater for 26% of foods. Differences in macronutrient estimates by trial and USDA weight varied by food type. These findings suggest that nutrient databases based on food weight may not provide accurate estimates of dietary intake when assessed using food volumes. Further development of image-assisted dietary assessment methods which measure food volumes will necessitate evaluation of the accuracy of the processes used to convert weight to volume in nutrient databases. Full article

(This article belongs to the Special Issue Advancement in Dietary Assessment and Self-Monitoring Using Technology)

15 pages, 1212 KiB

Open AccessArticle

Accuracy of Automatic Carbohydrate, Protein, Fat and Calorie Counting Based on Voice Descriptions of Meals in People with Type 1 Diabetes

by Piotr Ladyzynski, Janusz Krzymien, Piotr Foltynski, Monika Rachuta and Barbara Bonalska

Nutrients 2018, 10(4), 518; https://doi.org/10.3390/nu10040518 - 21 Apr 2018

Cited by 15 | Viewed by 6719

Abstract

The aim of this work was to assess the accuracy of automatic macronutrient and calorie counting based on voice descriptions of meals provided by people with unstable type 1 diabetes using the developed expert system (VoiceDiab) in comparison with reference counting made by [...] Read more.

The aim of this work was to assess the accuracy of automatic macronutrient and calorie counting based on voice descriptions of meals provided by people with unstable type 1 diabetes using the developed expert system (VoiceDiab) in comparison with reference counting made by a dietitian, and to evaluate the impact of insulin doses recommended by a physician on glycemic control in the study’s participants. We also compared insulin doses calculated using the algorithm implemented in the VoiceDiab system. Meal descriptions were provided by 30 hospitalized patients (mean hemoglobin A1c of 8.4%, i.e., 68 mmol/mol). In 16 subjects, the physician determined insulin boluses based on the data provided by the system, and in 14 subjects, by data provided by the dietitian. On one hand, differences introduced by patients who subjectively described their meals compared to those introduced by the system that used the average characteristics of food products, although statistically significant, were low enough not to have a significant impact on insulin doses automatically calculated by the system. On the other hand, the glycemic control of patients was comparable regardless of whether the physician was using the system-estimated or the reference content of meals to determine insulin doses. Full article

(This article belongs to the Special Issue Advancement in Dietary Assessment and Self-Monitoring Using Technology)

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8 pages, 192 KiB

Open AccessArticle

Pilot Testing a Photo-Based Food Diary in Nine- to Twelve- Year Old- Children from Dunedin, New Zealand

by Brittany K. Davison, Robin Quigg and Paula M. L. Skidmore

Nutrients 2018, 10(2), 240; https://doi.org/10.3390/nu10020240 - 20 Feb 2018

Cited by 8 | Viewed by 4669

Abstract

The purpose of the study was to investigate if an Evernote app-based electronic food diary is an acceptable method to measure nutrient intake in children aged 9–12 years. A convenience sample of 16 nine- to twelve-year-olds from Dunedin, New Zealand, completed a paper-based [...] Read more.

The purpose of the study was to investigate if an Evernote app-based electronic food diary is an acceptable method to measure nutrient intake in children aged 9–12 years. A convenience sample of 16 nine- to twelve-year-olds from Dunedin, New Zealand, completed a paper-based food dairy on four days, followed by four more days using a photo-based diary on an iPod. This photo-based diary used a combination of photographs and short written descriptions of foods consumed. The photo-based diaries produced similar results to written diaries for all macronutrients and major micronutrients (e.g., calcium, fibre, vitamin C). Spearman correlation coefficients between the two methods for all nutrients, except sugars, were above 0.3. However, burden on researchers and participants was reduced for the photo-based diary, primarily due to the additional information obtained from photographs. Participating children needed less help from parents with completing the electronic diaries and preferred them to the paper version. This electronic diary is likely to be suitable, after additional formal validity testing, for use in measuring nutrient intake in children. Full article

(This article belongs to the Special Issue Advancement in Dietary Assessment and Self-Monitoring Using Technology)

Review

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25 pages, 771 KiB

Open AccessReview

Assessing Eating Behaviour Using Upper Limb Mounted Motion Sensors: A Systematic Review

by Hamid Heydarian, Marc Adam, Tracy Burrows, Clare Collins and Megan E. Rollo

Nutrients 2019, 11(5), 1168; https://doi.org/10.3390/nu11051168 - 24 May 2019

Cited by 31 | Viewed by 6330

Abstract

Wearable motion tracking sensors are now widely used to monitor physical activity, and have recently gained more attention in dietary monitoring research. The aim of this review is to synthesise research to date that utilises upper limb motion tracking sensors, either individually or [...] Read more.

Wearable motion tracking sensors are now widely used to monitor physical activity, and have recently gained more attention in dietary monitoring research. The aim of this review is to synthesise research to date that utilises upper limb motion tracking sensors, either individually or in combination with other technologies (e.g., cameras, microphones), to objectively assess eating behaviour. Eleven electronic databases were searched in January 2019, and 653 distinct records were obtained. Including 10 studies found in backward and forward searches, a total of 69 studies met the inclusion criteria, with 28 published since 2017. Fifty studies were conducted exclusively in laboratory settings, 13 exclusively in free-living settings, and three in both settings. The most commonly used motion sensor was an accelerometer (64) worn on the wrist (60) or lower arm (5), while in most studies (45), accelerometers were used in combination with gyroscopes. Twenty-six studies used commercial-grade smartwatches or fitness bands, 11 used professional grade devices, and 32 used standalone sensor chipsets. The most used machine learning approaches were Support Vector Machine (SVM, n = 21), Random Forest (n = 19), Decision Tree (n = 16), Hidden Markov Model (HMM, n = 10) algorithms, and from 2017 Deep Learning (n = 5). While comparisons of the detection models are not valid due to the use of different datasets, the models that consider the sequential context of data across time, such as HMM and Deep Learning, show promising results for eating activity detection. We discuss opportunities for future research and emerging applications in the context of dietary assessment and monitoring. Full article

(This article belongs to the Special Issue Advancement in Dietary Assessment and Self-Monitoring Using Technology)

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14 pages, 252 KiB

Open AccessReview

Dietary Assessment of Shared Plate Eating: A Missing Link

by Tracy Burrows, Clare Collins, Marc Adam, Kerith Duncanson and Megan Rollo

Nutrients 2019, 11(4), 789; https://doi.org/10.3390/nu11040789 - 5 Apr 2019

Cited by 25 | Viewed by 4907

Abstract

Shared plate eating is a defining feature of the way food is consumed in some countries and cultures. Food may be portioned to another serving vessel or directly consumed into the mouth from a centralised dish rather than served individually onto a discrete [...] Read more.

Shared plate eating is a defining feature of the way food is consumed in some countries and cultures. Food may be portioned to another serving vessel or directly consumed into the mouth from a centralised dish rather than served individually onto a discrete plate for each person. Shared plate eating is common in some low- and lower-middle income countries (LLMIC). The aim of this narrative review was to synthesise research that has reported on the assessment of dietary intake from shared plate eating, investigate specific aspects such as individual portion size or consumption from shared plates and use of technology in order to guide future development work in this area. Variations of shared plate eating that were identified in this review included foods consumed directly from a central dish or shared plate food, served onto additional plates shared by two or more people. In some settings, a hierarchical sharing structure was reported whereby different family members eat in turn from the shared plate. A range of dietary assessment methods have been used in studies assessing shared plate eating with the most common being 24-h recalls. The tools reported as being used to assist in the quantification of food intake from shared plate eating included food photographs, portion size images, line drawings, and the carrying capacity of bread, which is often used rather than utensils. Overall few studies were identified that have assessed and reported on methods to assess shared plate eating, highlighting the identified gap in an area of research that is important in improving understanding of, and redressing dietary inadequacies in LLMIC. Full article

(This article belongs to the Special Issue Advancement in Dietary Assessment and Self-Monitoring Using Technology)

16 pages, 439 KiB

Open AccessReview

Potential Use of Mobile Phone Applications for Self-Monitoring and Increasing Daily Fruit and Vegetable Consumption: A Systematized Review

by Floriana Mandracchia, Elisabet Llauradó, Lucia Tarro, Josep Maria del Bas, Rosa Maria Valls, Anna Pedret, Petia Radeva, Lluís Arola, Rosa Solà and Noemi Boqué

Nutrients 2019, 11(3), 686; https://doi.org/10.3390/nu11030686 - 22 Mar 2019

Cited by 28 | Viewed by 8064

Abstract

A wide range of chronic diseases could be prevented through healthy lifestyle choices, such as consuming five portions of fruits and vegetables daily, although the majority of the adult population does not meet this recommendation. The use of mobile phone applications for health [...] Read more.

A wide range of chronic diseases could be prevented through healthy lifestyle choices, such as consuming five portions of fruits and vegetables daily, although the majority of the adult population does not meet this recommendation. The use of mobile phone applications for health purposes has greatly increased; these applications guide users in real time through various phases of behavioural change. This review aimed to assess the potential of self-monitoring mobile phone health (mHealth) applications to increase fruit and vegetable intake. PubMed and Web of Science were used to conduct this systematized review, and the inclusion criteria were: randomized controlled trials evaluating mobile phone applications focused on increasing fruit and/or vegetable intake as a primary or secondary outcome performed from 2008 to 2018. Eight studies were included in the final assessment. The interventions described in six of these studies were effective in increasing fruit and/or vegetable intake. Targeting stratified populations and using long-lasting interventions were identified as key aspects that could influence the effectiveness of these interventions. In conclusion, evidence shows the effectiveness of mHealth application interventions to increase fruit and vegetable consumption. Further research is needed to design effective interventions and to determine their efficacy over the long term. Full article

(This article belongs to the Special Issue Advancement in Dietary Assessment and Self-Monitoring Using Technology)

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25 pages, 1749 KiB

Open AccessReview

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

by Alison L. Eldridge, Carmen Piernas, Anne-Kathrin Illner, Michael J. Gibney, Mirjana A. Gurinović, Jeanne H.M. De Vries and Janet E. Cade

Nutrients 2019, 11(1), 55; https://doi.org/10.3390/nu11010055 - 28 Dec 2018

Cited by 146 | Viewed by 13157

Abstract

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 [...] Read more.

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. Full article

(This article belongs to the Special Issue Advancement in Dietary Assessment and Self-Monitoring Using Technology)

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19 pages, 378 KiB

Open AccessReview

Narrative Review of New Methods for Assessing Food and Energy Intake

by M. Carolina Archundia Herrera and Catherine B. Chan

Nutrients 2018, 10(8), 1064; https://doi.org/10.3390/nu10081064 - 10 Aug 2018

Cited by 42 | Viewed by 9775

Abstract

Dietary self-report instruments are essential to nutritional analysis in dietetics practice and their use in research settings has facilitated numerous important discoveries related to nutrition, health and chronic diseases. An important example is obesity, for which measuring changes in energy intake is critical [...] Read more.

Dietary self-report instruments are essential to nutritional analysis in dietetics practice and their use in research settings has facilitated numerous important discoveries related to nutrition, health and chronic diseases. An important example is obesity, for which measuring changes in energy intake is critical for assessing efficacy of dietary interventions. However, current methods, including counting calories, estimating portion size and using food labels to estimate human energy intake have considerable constraints; consequently, research on new methodologies/technologies has been encouraged to mitigate the present weaknesses. The use of technologies has prompted innovation in dietary analysis. In this review, the strengths and limitations of new approaches have been analyzed based on ease of use, practical limitations, and statistical evaluation of reliability and validity. Their utility is discussed through the lens of the 4Ms of Obesity Assessment and Management, which has been used to evaluate root causes of obesity and help select treatment options. Full article

(This article belongs to the Special Issue Advancement in Dietary Assessment and Self-Monitoring Using Technology)

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11 pages, 646 KiB

Open AccessBrief Report

Dietary Intake Reporting Accuracy of the Bridge2U Mobile Application Food Log Compared to Control Meal and Dietary Recall Methods

by Jennifer L. Lemacks, Kristen Adams and Ashley Lovetere

Nutrients 2019, 11(1), 199; https://doi.org/10.3390/nu11010199 - 19 Jan 2019

Cited by 18 | Viewed by 5991

Abstract

Mobile technology introduces opportunity for new methods of dietary assessment. The purpose of this study was to compare the reporting accuracy of a mobile food log application and 24 h recall method to a controlled meal among a convenience sample of adults (18 [...] Read more.

Mobile technology introduces opportunity for new methods of dietary assessment. The purpose of this study was to compare the reporting accuracy of a mobile food log application and 24 h recall method to a controlled meal among a convenience sample of adults (18 years of age or older). Participants were recruited from a community/university convenience sample. Participants consumed a pre-portioned control meal, completed mobile food log entry (mfood log), and participated in a dietary recall administered by a registered dietitian (24R). Height, weight, and application use survey data were collected. Sign test, Pearson’s correlation, and descriptive analyses were conducted to examine differences in total and macronutrient energy intake and describe survey responses. Bland Altman plots were examined for agreement between energy intake from control and 24R and mfood log. The 14 included in the analyses were 78.6% female, 85.7% overweight/obese, and 64.3% African American. Mean total energy, protein, and fat intakes reported via the mfood log were significantly (p < 0.05) lower compared to the control, by 268.31kcals, 20.37 g, and 19.51 g, respectively. Only 24R mean fat intake was significantly (p < 0.01) lower than the control, by 6.43 g. Significant associations (r = 0.57–0.60, p < 0.05) were observed between control and mfood log mean energy, carbohydrate, and protein intakes, as well as between control and 24R mean energy (r = 0.64, p = 0.01) and carbohydrate (r = 0.81, p < 0.001) intakes. Bland Altman plots showed wide limits of agreement, which were not statistically significant but may have practical limitations for individual dietary assessment. Responses indicated the ease of and likelihood of daily mfood log use. This study demonstrates that the Bridge2U mfood log is valid for the assessment of group level data, but data may vary too widely for individual assessment. Further investigation is warranted for nutrition intervention research. Full article

(This article belongs to the Special Issue Advancement in Dietary Assessment and Self-Monitoring Using Technology)

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