Popular nutrition-related mobile apps: a feature assessment

Background: A key challenge in human nutrition is the assessment of usual food intake. This is of particular interest given recent proposals of eHealth personalized interventions. The adoption of mobile phones has created an opportunity for assessing and improving nutrient intake as they can be used for digitalizing dietary assessments and providing feedback. In the last few years, hundreds of nutrition-related mobile apps have been launched and installed by millions of users. Objective: This study aims to analyze the main features of the most popular nutrition apps and to compare their strategies and technologies for dietary assessment and user feedback. Methods: Apps were selected from the two largest online stores of the most popular mobile operating systems—the Google Play Store for Android and the iTunes App Store for iOS—based on popularity as measured by the number of installs and reviews. The keywords used in the search were as follows: calorie(s), diet, diet tracker, dietician, dietitian, eating, fit, fitness, food, food diary, food tracker, health, lose weight, nutrition, nutritionist, weight, weight loss, weight management, weight watcher, and ww calculator. The inclusion criteria were as follows: English language, minimum number of installs (1 million for Google Play Store) or reviews (7500 for iTunes App Store), relation to nutrition (ie, diet monitoring or recommendation), and independence from any device (eg, wearable) or subscription. Results: A total of 13 apps were classified as popular for inclusion in the analysis. Nine apps offered prospective recording of food intake using a food diary feature. Food selection was available via text search or barcode scanner technologies. Portion size selection was only textual (ie, without images or icons). All nine of these apps were also capable of collecting physical activity (PA) information using self-report, the global positioning system (GPS), or wearable integrations. Their outputs focused predominantly on energy balance between dietary intake and PA. None of these nine apps offered features directly related to diet plans and motivational coaching. In contrast, the remaining four of the 13 apps focused on these opportunities, but without food diaries. One app—FatSecret—also had an innovative feature for connecting users with health professionals, and another—S Health—provided a nutrient balance score. Conclusions: The high number of installs indicates that there is a clear interest and opportunity for diet monitoring and recommendation using mobile apps. All the apps collecting dietary intake used the same nutrition assessment method (ie, food diary record) and technologies for data input (ie, text search and barcode scanner). Emerging technologies, such as image recognition, natural language processing, and artificial intelligence, were not identified. None of the apps had a decision engine capable of providing personalized diet advice

Strategies for online personalised nutrition advice employed in the development of the eNutri web app

The internet has considerable potential to improve health-related food choice at low-cost. Online solutions in this field can be deployed quickly and at very low cost, especially if they are not dependent on bespoke devices or offline processes such as the provision and analysis of biological samples. One key challenge is the automated delivery of personalised dietary advice in a replicable, scalable and inexpensive way, using valid nutrition assessment methods and effective recommendations. We have developed a web-based personalised nutrition system (eNutri) which assesses dietary intake using a validated graphical FFQ and provides personalised food-based dietary advice automatically. Its effectiveness was evaluated during an online randomised controlled trial dietary intervention (EatWellUK study) in which personalised dietary advice was compared with general population recommendations (control) delivered online. The present paper presents a review of literature relevant to this work, and describes the strategies used during the development of the eNutri app. Its design and source code have been made publicly available under a permissive open source license, so that other researchers and organisations can benefit from this work. In a context where personalised diet advice has great potential for health promotion and disease prevention at-scale and yet is not currently being offered in the most popular mobile apps, the strategies and approaches described in the present paper can help to inform and advance the design and development of technologies for personalised nutrition

Automatic Extraction of Useful Information from Food -Health Articles related to Diabetes, Cardiovascular Disease and Cancer

Food-health articles (FHA) contain invaluable information for health promotion. However, extracting this information manually is a challenging process due to the length and number of articles published yearly. Automatic text summarization efficiently identifies useful information across large bodies of text which in turn speeds up the delivery of useful information from FHA. This research work aims to investigate the performance of statistical based summarization and graphical based unsupervised learning summarization in extracting useful information from FHA related to diabetes, cardiovascular disease and cancer. Various combinations of introduction, result and conclusion sections of three hundred articles were collected, preprocessed and used for evaluating the performance of the two summarization technique types. Generated summaries are compared to the original abstracts using two measures. The first quantifies the similarity of the generated summary to the abstract. The second measure gauges the coverage of the generated summary and the article abstract to the article sections. Overall, this experiment showed the automatically generated summaries are not comparable to the human-made abstracts found in FHA and there is room for improvement since the highest similarity of the generated to the written abstract was 52-57% and the sentence scoring of summarization could be optimized for various domains

The significance of silence. Long gaps attenuate the preference for ‘yes’ responses in conversation.

In conversation, negative responses to invitations, requests, offers and the like more often occur with a delay – conversation analysts talk of them as dispreferred. Here we examine the contrastive cognitive load ‘yes’ and ‘no’ responses make, either when given relatively fast (300 ms) or delayed (1000 ms). Participants heard minidialogues, with turns extracted from a spoken corpus, while having their EEG recorded. We find that a fast ‘no’ evokes an N400-effect relative to a fast ‘yes’, however this contrast is not present for delayed responses. This shows that an immediate response is expected to be positive – but this expectation disappears as the response time lengthens because now in ordinary conversation the probability of a ‘no’ has increased. Additionally, however, 'No' responses elicit a late frontal positivity both when they are fast and when they are delayed. Thus, regardless of the latency of response, a ‘no’ response is associated with a late positivity, since a negative response is always dispreferred and may require an account. Together these results show that negative responses to social actions exact a higher cognitive load, but especially when least expected, as an immediate response

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.ope

Considerations for Dietary Assessment in the Canadian Partnership for Tomorrow Project

Dietary factors are leading contributors to chronic disease and mortality globally and in Canada (1–3), and have been recognized as modifiable risk factors for certain cancers (4). However, much remains to be learned about how dietary factors interact with other modifiable and nonmodifiable exposures and physiologic variables to influence disease risk in humans (5,6). Information collected from large prospective cohorts plays an important role in furthering our understanding of diet-disease relationships (7,8). To advance knowledge on how to promote health and prevent disease, it is critically important to use robust tools for collecting dietary information from participants in such cohorts (9). This guide is intended to be utilized by researchers designing nutritional epidemiological research and in particular, to guide the implementation of dietary assessment tools within the CPTP cohorts. The aim is to provide guidance on method selection, data collection, and analyses of dietary data, as well as stimulate discussions of harmonization of methods across cohorts to advance the evidence base. Because objective measures such as biomarkers of diet are currently few, burdensome, costly, and limited in the information they provide about the types of foods and beverages people consume (5,6), researchers typically rely upon self-report tools. However, it has long been recognized that self-reported dietary data are affected by error, including systematic error or bias (9,10), leading some commentators to suggest that research should no longer rely on selfreport approaches (11,12). However, much work has been conducted to better understand and address error in self-report dietary intake data (9,10). Such work has informed the development of novel technology-enabled tools to allow collection of the least-biased data possible, as well as the development of rigorous statistical approaches to mitigate the effects of error (13–16). Based on what is known about sources and types of error in data captured using different types of tools, it has been recommended that a combination of tools may be the optimal way forward for cohort studies. Specifically, multiple 24-hour recalls (24HRs), administered in combination with a food frequency questionnaire (FFQ), may allow researchers to leverage the strengths of each instrument (10,14,17). Data from 24HRs provide comprehensive detail on intake and measure consumption with less bias than FFQs. On the other hand, FFQs measure intake over a longer period (e.g. past month or year) (18–20), meaning they are better able to capture intake of foods and beverages that may be consumed more episodically (e.g., whole grains, dark-green vegetables) but that may be important to diet-disease relationships. The availability of weband mobile device-based dietary assessment tools for use in Canada and emerging statistical techniques to analyze the resulting data makes this multiple-tool scenario a realistic consideration for Alberta’s Tomorrow Project (21), other cohorts within the Canadian Partnership for Tomorrow Project (CPTP) (22), and other health-related studies. With comprehensive and standardized measurement of dietary exposures across cohorts, the identification of promising strategies to reduce diet-related disease risk among Canadians can be furthered (9)

Making the best use of new technologies in the National Diet and Nutrition Survey: a review

.Background Dietary assessment is of paramount importance for public health monitoring. Currently in the UK, the population’s diets are examined by the National Diet and Nutrition Survey Rolling Programme (NDNS RP). In the survey, diet is assessed by a four-day paper-based dietary diary, with accompanying interviews, anthropometric measurements and blood and urine sampling. However, there is growing interest worldwide in the potential for new technologies to assist in data collection for assessment of dietary intake. Published literature reviews have identified the potential of new technologies to improve accuracy, reduce costs, and reduce respondent and researcher burden by automating data capture and the nutritional coding process. However, this is a fast-moving field of research, with technologies developing at a rapid pace, and an updated review of the potential application of new technologies in dietary assessment is warranted. This review was commissioned to identify the new technologies employed in dietary assessment and critically appraise their strengths and limitations in order to recommend which technologies, if any, might be suitable to develop for use in the NDNS RP and other UK population surveys. Objectives The overall aim of the project was to inform the Department of Health of the range of new technologies currently available and in development internationally that have potential to improve, complement or replace the methods used in the NDNS RP. The specific aims were: to generate an itinerary of new and emerging technologies that may be suitable; to systematically review the literature and critically appraise new technologies; and to recommend which of these new technologies, if any, would be appropriate for future use in the NDNS RP. To meet these aims, the project comprised two main facets, a literature review and qualitative research. Literature review data sources The literature review incorporated an extensive search of peer-reviewed and grey literature. The following sources were searched: Cochrane Database of Systematic Reviews (CDSR), Database of Abstracts of Reviews of Effectiveness (DARE), Web of Science Core Collection, Ovid MEDLINE, Ovid MEDLINE In-Process, Embase, NHS EED (Economic Evaluation Database), National Cancer Institute (NCI) Dietary Assessment Calibration/Validation Register, OpenGrey, EPPI Centre (TRoPHI), conference proceedings (ICDAM 2012, ISBNPA 2013, IEEE Xplore, Nutrition Society Irish Section and Summer Meetings 2014), recent issues of journals (Journal of Medical Internet Research, International Journal of Medical Informatics), grants registries (ClinicalTrials.gov, BBSRC, report), national surveys, and mobile phone application stores. In addition, hand-searching of relevant citations was performed. The search also included solicitation of key authors in the field to enquire about Making the best use of new technologies in the NDNS: a review 4 as-yet unpublished articles or reports, and a Bristol Online Survey publicised via social media, society newsletters and meetings. Literature review eligibility criteria Records were screened for eligibility using a three-stage process. Firstly, keyword searches identified obviously irrelevant titles. Secondly, titles and abstracts were screened against the eligibility criteria, following which full-text copies of papers were obtained and, in the third stage of screening, examined against the criteria. Two independent reviewers screened each record at each stage, with discrepancies referred to a third reviewer. Eligibility criteria were pre-specified and agreed by the project Steering Group (Section 1.6). Eligible records included: studies involving technologies, new to the NDNS RP, which can be used to automate or assist the collection of food consumption data and the coding of foods and portion sizes, currently available or beta versions, public domain or commercial; studies that address the development, features, or evaluation of new technology; technologies appropriate for the requirements of the NDNS RP in terms of nutritional analysis, with capacity to collect quantifiable consumption data at the food level; primary sources of information on a particular technology; and journal articles published since the year 2000 or grey literature available from 2011 onwards. The literature search was not limited to Englishlanguage publications, which are included in the itinerary, although data were not extracted from non-English studies. Literature synthesis and appraisal New technologies were categorised into eleven types of technology, and an itinerary was generated of tools falling under each category type. Due to the volume of eligible studies identified by the literature searches, data extraction was limited to the literature focussing on selected exemplar tools of five technology categories (web-based diet diary, web-based 24- hour recall, handheld devices (personal digital assistants and mobile phones), nonautomated cameras to complement traditional methods, and non-automated cameras to replace traditional methods). For each category, at least two exemplars were chosen, and all studies involving the exemplar were included in data extraction and synthesis. Exemplars were selected on the basis of breadth of evidence available, using pre-specified criteria agreed by the Steering Group. Data were extracted by a single reviewer and an evidence summary collated for each exemplar. A quality appraisal checklist was developed to assess the quality of validation studies. The checklist was piloted and applied by two independent reviewers. Studies were not excluded on the basis of quality, but study quality was taken into account when judging the strength of evidence. Due to the heterogeneity of the literature, meta-analyses were not performed. References were managed and screened using the EPPI Reviewer 4 systematic review software. EPPI Reviewer was also used to extract data

Exploring racial disparity in stillbirth rates through structural racism and methylation of stress-related genes: From systemic to epigenetic

Problem to be addressed: Stillbirth is a major public health problem. The stillbirth burden is on a par with newborn deaths. The stillbirth rate measures not only a substantial portion of the global and national burden of mortality, but also equity and quality of care for women’s and children’s health. Reducing the numbers of these deaths requires an understanding of why they occur, yet approximately one-third of stillbirths are unexplained, even in settings with high-quality autopsy and placental examination, while deaths considered to be explained are usually ascribed to single, proximal causes. An important limiting factor for efforts to reduce the large and inequitable stillbirth burden has been insufficient research into conditions that could inform prevention strategies and reduce inequity.1 2 Substantial evidence exists for associations between structural racism, maternal stress, and adverse pregnancy outcomes, yet research focusing on stillbirth is sparse, particularly at the ends of the causal spectrum—macro-level structural conditions and mechanisms. Several studies have called for research on possible biological mechanisms by which racism, racism-related stress, and stillbirth may be associated, including epigenetic mechanisms.3-6 The most recent review of causes of racial disparities in stillbirth rates in the U.S. recommended that researchers take a multi-domain approach, considering not just individual-level risk factors, which have been relatively well-studied, but also upstream factors such as institutional racism, and biological mechanisms such as epigenetic modification. The objective of this dissertation was to explore evidence that could help to explain persistent racial disparities in stillbirth. The specific aims were: 1. To review the literature on racial disparity in stillbirth rates; 2. To assess whether structural racism can help to explain racial disparity in stillbirth rates in New York City; and 3. To assess whether maternal stress is associated with stillbirth, whether stress is associated with methylation of stress-related genes, whether methylation is associated with stillbirth, and whether there is evidence that methylation of stress-related genes mediates associations between stress and stillbirth. Materials and methods used: For Aim 1, we carried out a scoping review of the literature in five databases (PubMed, Scopus, Cinahl, Embase, PsycInfo) to identify all reports including stillbirth rates stratified by race in the U.S., mapping exposures and effect modifiers (“domains of analysis”) and authors’ comments on racial disparity in stillbirths (“domains of explanation”) into one of eight domains (race, genetic, fetal, maternal, family, community, healthcare system, and structural). We defined Stillbirth Disparity Ratios (SDRs) as the ratio of the stillbirth rate in a racial/ethnic minority group to the stillbirth rate in white individuals. Selected SDRs were extracted from each report, as were all SDRs for Black/white comparisons. For Aim 2, we modelled associations between four measures of structural racism and stillbirth in all non-Hispanic (NH) Black and white singleton births in New York City between 2009 and 2018. Exposures were four Public Use Microdata Area (PUMA)-level measures of structural racism (Indices of Dissimilarity, Isolation, and Concentration at the Extremes (ICE), and an Educational Inequity Ratio) constructed from U.S. Census American Community Survey data. Using multilevel logistic regression, we first tested for interaction between race and structural racism in relation to stillbirth. For structural racism measures that interacted with race, we estimated odds ratios for stillbirth separately in 221,925 NH Black and 325,058 NH white births. Race-specific models were further stratified by maternal age. For Aim 3, we assessed associations between maternal stressors and stillbirth in 183 non-anomalous full-term singleton births (63 stillbirths and 120 livebirths) from the U.S. Stillbirth Collaborative Research Network. Measuring maternal stress with two hypothesized stressors, an Index of Significant Life Events and an Index of Disadvantage, we assessed associations between maternal stressors and stillbirth in our sample, and then whether maternal stressors and stillbirth were associated with differential methylation of 1,191 CpGs on five stress-related genes (BDNF, FKBP5, HSD11B2, IGF2, and NR3C1). Finally, we assessed whether methylation mediates associations between stressors and stillbirth. Conclusions reached: For Aim 1, we found 95 reports presenting stillbirth rates stratified by race/ethnicity in the U.S. We found evidence of increased risk of stillbirth in Black as compared to white births in the majority of the 83 reports with the necessary data. Among the 1143 Black-white SDRs that we extracted, the median SDR was 1.67, with 74% of SDRs showing evidence of disparity. Family and community factors, healthcare system factors, and structural factors were commonly used as domains of explanation (20-38% of reports), but rarely (family/community, structural, 4-5%) or never (healthcare system) used in analysis. The most commonly used domains of analysis—fetal and maternal factors including gestational age, maternal age, education, and prenatal care—do not appear able to explain the observed racial disparities. Gaps in the literature include a paucity of studies examining the possible role of health system, community, and structural factors in Black-white disparity in stillbirth rates, and limited data on other types of racial disparities in stillbirth rates, including Hispanic and Native American births. For Aim 2, we found that structural racism as measured by ICE and Isolation was associated with stillbirth in NH Black but not NH white mothers. This would seem consistent with our hypothesis that structural racism may help to explain racial disparity in stillbirth rates; however, the associations we observed were not in the expected direction. Specifically, NH Black mothers living in PUMAs with a high concentration of privilege had 90% greater odds of stillbirth in comparison to those living in PUMAs with a high concentration of disadvantage (ICE quintile 5 vs 1), and NH Black mothers living in PUMAs that were the most isolated had 40% lower odds of stillbirth in comparison to those living in PUMAs that were the least isolated (Isolation tertile 3 vs 1). We suggest that while the measures we used (ICE and Isolation) do help to explain the Black-white disparity in stillbirth rates, our results raise questions about the way these measures operationalize structural racism, meriting further investigation. For Aim 3, we found that having two or more vs no items in the Index of Disadvantage (“Disadvantage”) was associated with more than fourfold greater odds of stillbirth (95% CI 1.58, 12.93). We found no association between the Index of Significant Life Events and stillbirth. We found that 32 out of 1,191 CpGs on five stress-related genes were differentially methylated with respect to stillbirth, and six CpGs were differentially methylated with respect to Disadvantage. Methylation at two CpGs on IGF2 and one on HSD11B2 (cg02097792, cg12283393, and cg19413291, respectively) mediated the association between Disadvantage and stillbirth. Research on causes is a critical component of stillbirth prevention and reducing the inequitable distribution of this public health burden. Limited understanding of causes at both “ends of the spectrum”, from upstream distal factors to mechanisms, has likely contributed to slow progress on prevention.7 8 This dissertation contributes to science and public health by providing researchers with data to support new lines of inquiry, e.g., into associations between structural racism and stillbirth, and for methylation as a mechanism of effect, that should help to improve our understanding of causes. Our research may also support health policy makers who now have additional data to illustrate the adverse health outcomes of structural racism in the U.S. Finally, it may help the parents and other family members of stillborn babies who continually seek to understand “why”

Online personalised nutrition advice

The Internet has considerable potential to improve health-related food choice at lowcost. In order to provide online personalised nutrition advice, a valid and user-friendly method for recording dietary intake is key. Yet, the author’s review of popular nutritionrelated mobile apps revealed that none of these apps were capable of providing personalised diet advice This work presents a web app (eNutri), which is able to assess dietary intake using a validated food frequency questionnaire (FFQ) and provide personalised food-based diet advice. The initial version of this app presented the food items in a list and its usability was evaluated in Kuwait. In response to user feedback, the design was modified to present a single food item at a time. This app was deployed in an online study to assess usability with 324 participants in the UK, using different devices. The median System Usability Scale (SUS) score (n=322) was 77.5 (IQR 15.0) out of 100, illustrating high acceptance by users. Potential users were consulted during the design process, but assessing whether nutrition professionals (n=32) agree with the automated advice and collecting their insights were important in maximising the success and wider utility of this app. The mean scores for the appropriateness, relevance and suitability of the eNutri diet messages by nutritional professionals were 3.5, 3.3 and 3.3 respectively (maximum 5). Its effectiveness was evaluated during a 12-week online randomly controlled parallel blinded dietary intervention (n=210) (EatWellUK study) in which personalised dietary advice was compared with general population recommendation (control). A significant improvement in the modified Alternative Healthy Eating Index (m-AHEI) score, against which the participants’ diets were compared, of 3.06 (CI 95% 0.91 to 5.21, p=0.005), was reported following personalised compared to population advice. This work indicates the benefit of personalised dietary advice delivered online to motivate dietary change. The eNutri app’s design and source code were made publicly available under a permissive open source license, so that other researchers and organizations can benefit from this work

THE CONTRIBUTION OF THE MONTESSORI APPROACH TO MULTISENSORY APPROACHES TO EARLY LEARNING DISABILITIES

Faculty of Humanities School of Education 9805090w [email protected] disabilities have become of increasing concern for educators. More and more children are having difficulty learning to read and write. This dissertation investigates what constitutes a learning disability, its etiology and whether or not it is possible to identify these disabilities in early childhood. The investigation further aims to discover if these learning disabilities are comprised of sub-disabilities and if these can be identified as such. To this end the research aims to determine the most appropriate remedial intervention strategies used for learning disabilities. Multisensory intervention is therefore explored. On the basis of this the Montessori Method is examined to ascertain whether or not the method can contribute to multisensory intervention at the preschool level. It is argued that the Montessori Method is admirably suited to making such a contribution. Further empirical research for these claims is indicated