Dietary Assessment Tools Using Mobile Technology

Hongu, Nobuko; Hingle, Melanie; Merchant, Nirav; Orr, Barron J.; Going, Scott B.; Mosqueda, Martha; Thomson, Cynthia A.

doi:10.1097/tin.0b013e3182379525

Cited by 20 publications

(17 citation statements)

References 39 publications

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“…For example, advances in omics, informatics technologies, and systems biology have been major drivers of new questions and possibilities at the molecular, metabolic, and organismic levels (2)(3)(4), and advances in mobile technologies, telemetry, social networks, and "serious games" have the potential to revolutionize research and behavior change interventions related to diet and physical activity (5)(6)(7)(8)(9). This paper identifies an emergent set of research frontiers at the population end of the nutrition spectrum, with a particular focus on the new research questions, methods, and approaches required to respond effectively to an expanding set of food-and nutrition-related problems and emergent opportunities.…”

Section: Introductionmentioning

confidence: 99%

Expanding the Frontiers of Population Nutrition Research: New Questions, New Methods, and New Approaches

Pelletier

Porter

Aarons

et al. 2013

Advances in Nutrition

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Nutrition research, ranging from molecular to population levels and all points along this spectrum, is exploring new frontiers as new technologies and societal changes create new possibilities and demands. This paper defines a set of frontiers at the population level that are being created by the increased societal recognition of the importance of nutrition; its connection to urgent health, social, and environmental problems; and the need for effective and sustainable solutions at the population level. The frontiers are defined in terms of why, what, who, and how we study at the population level and the disciplinary foundations for that research. The paper provides illustrations of research along some of these frontiers, an overarching framework for population nutrition research, and access to some of the literature from outside of nutrition that can enhance the intellectual coherence, practical utility, and societal benefit of population nutrition research. The frontiers defined in this paper build on earlier forward-looking efforts by the American Society for Nutrition and extend these efforts in significant ways. The American Society for Nutrition and its members can play pivotal roles in advancing these frontiers by addressing a number of well-recognized challenges associated with transdisciplinary and engaged research.

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Section: Introductionmentioning

confidence: 99%

Expanding the Frontiers of Population Nutrition Research: New Questions, New Methods, and New Approaches

Pelletier

Porter

Aarons

et al. 2013

Advances in Nutrition

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“…However, in contrast to our study, users (n=19) entered the WFR into Tap & Track (n=19) and a registered dietitian into the USDA nutrient analysis program [9]. The authors suggested that the observed variability in BlandAltman plots between methods may be associated with the ability of the users to pick appropriate food items and ensure all data is recorded [9], [13], which would not have been an issue in our study as a single researcher entered data into all apps and reference programme. Protein intake was significantly underestimated by FatSecret and Lose It!…”

Section: Discussionmentioning

confidence: 54%

“…Whereas previous studies have compared user with professional entry of the same record [9], or user with professional entry of records taken on separate occasions [17], this study eliminated the biases associated with user entry, (e.g. selection of appropriate food item, estimation of portion size [13]). The strengths of using a WFR, as opposed to a 24-recall is that dietary intake is recorded prospectively (i.e.…”

Section: Strengths and Limitationsmentioning

confidence: 99%

Popular Nutrition-Related Mobile Apps: An Agreement Assessment Against a UK Reference Method (Preprint)

Fallaize¹,

Franco²,

Pasang³

et al. 2018

Preprint

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Background: Nutrition-related apps are commonly used to provide information about the users' dietary intake, but limited research has been performed on the evaluation of their reliability. Objective: To evaluate the relative reliability of popular nutrition-related apps for the assessment of energy and available macro-and micronutrients against a standard method. Methods: Dietary analysis of 24-hour weighed food records (n = 20) were compared between five nutrition-related apps: S Health, MyFitnessPal, FatSecret, Noom Coach and Lose It!, and DietPlan6 (reference method). Estimates of energy, macronutrients (carbohydrate, protein, fat, saturated fat and fibre) and micronutrients (sodium, calcium, iron, vitamin A and vitamin C) were compared using t-tests and Wilcoxon signed-rank tests, correlation coefficients and Bland-Altman plots. 24-hour weighed food records from 20 participants (female/male, 15/5; mean age, 36.3 years; mean body mass index, 22.9 kg/m 2 ) recruited from previous controlled studies conducted at the Hugh Sinclair Unit of Human Nutrition, University of Reading, UK. Results: No significant difference in estimation of energy and saturated fat intake between DietPlan6 and the diet apps was observed. Estimates of protein and sodium intake were significantly lower using Lose It! and FatSecret than DietPlan6. Lose It! also gave significantly lower estimates for other reported outputs: carbohydrate, fat, fibre and sodium, compared with DietPlan6. For S Health and MyFitnessPal, calcium, iron and vitamin C were all significantly under-estimated compared with DietPlan6, although there was no significant difference for vitamin A. No other significant differences were observed between DietPlan6 and the apps. Correlation coefficients ranged from -0.12 for iron (S Health vs. DietPlan6) to 0.91 for protein (FatSecret vs DietPlan6). Noom Coach was limited to energy output but it had a high correlation with DietPlan6 (r=0.91) and S Health had the greatest variation of correlation, with energy at 0.79. Bland-Altman analysis revealed potential proportional bias for vitamin A. Conclusions: The findings suggest that the apps provide comparable estimates of energy and saturated fat intake compared with DietPlan6. With the exception of Lose It!, the apps also provided comparable estimates of carbohydrate, total fat and fibre. Two apps displayed a tendency to underestimate protein and sodium (FatSecret and Lose It!). Apart from vitamin A, the estimates of micronutrient intake (calcium, iron and vitamin C) by the two apps (S Health and MyFitnessPal) were inconsistent and less reliable. Lose It! was the less comparable app in relation to DietPlan6. As the use and availability of apps grows, this study helps clinicians and researchers to make betterinformed decisions about using these apps in research and practice.

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“…With the rise in computer and smartphone use, web-based DATs are becoming more popular in nutritional research compared with the traditional pen and paper approach (Carter et al 2015). New technology can reduce participant and researcher burden, increase adherence, improve data analysis, and reduce the time and cost required for data entry and data coding (Thompson et al 2010;Hongu et al 2011; Shriver, Roman-Shriver, and Long 2010); however, paper- (Livingstone, Robson, and Wallace 2004). Due to the difficulty of measuring absolute validity of dietary intake, studies typically measure relative validity, which includes errors associated with the reference method.…”

Section: Discussionmentioning

confidence: 99%

A systematic review of reviews identifying UK validated dietary assessment tools for inclusion on an interactive guided website for researchers: www.nutritools.org

Hooson

Hutchinson

Warthon-Medina

et al. 2019

Critical Reviews in Food Science and Nutrition

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behalf of the DIET@NET consortium (2020) A systematic review of reviews identifying UK validated dietary assessment tools for inclusion on an interactive guided website for researchers: www.nutritools.org, Critical Reviews in ABSTRACT Background: Health researchers may struggle to choose suitable validated dietary assessment tools (DATs) for their target population. The aim of this review was to identify and collate information on validated UK DATs and validation studies for inclusion on a website to support researchers to choose appropriate DATs. Design: A systematic review of reviews of DATs was undertaken. DATs validated in UK populations were extracted from the studies identified. A searchable website was designed to display these data. Additionally, mean differences and limits of agreement between test and comparison methods were summarized by a method, weighting by sample size. Results: Over 900 validation results covering 5 life stages, 18 nutrients, 6 dietary assessment methods, and 9 validation method types were extracted from 63 validated DATs which were identified from 68 reviews. These were incorporated into www.nutritools.org. Limits of agreement were determined for about half of validations. Thirty four DATs were FFQs. Only 17 DATs were validated against biomarkers, and only 19 DATs were validated in infant/children/adolescents. Conclusions: The interactive www.nutritools.org website holds extensive validation data identified from this review and can be used to guide researchers to critically compare and choose a suitable DAT for their research question, leading to improvement of nutritional epidemiology research.

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Dietary Assessment Tools Using Mobile Technology

Cited by 20 publications

References 39 publications

Expanding the Frontiers of Population Nutrition Research: New Questions, New Methods, and New Approaches

Expanding the Frontiers of Population Nutrition Research: New Questions, New Methods, and New Approaches

Popular Nutrition-Related Mobile Apps: An Agreement Assessment Against a UK Reference Method (Preprint)

A systematic review of reviews identifying UK validated dietary assessment tools for inclusion on an interactive guided website for researchers: www.nutritools.org

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