Exploring factors to interpretation of targeted nutrition messages for people living with multiple sclerosis

OBJECTIVES

Current dietary recommendations for MS suggest following national dietary guidelines developed for the general population. The aim of this study was to explore the interpretation of MS-targeted nutrition messages.

METHODS

Using the Elaboration Likelihood Model of persuasion, three nutrition messages were developed targeting the strongest evidence for MS: vitamin D, dietary fat, and dietary diversity. Semi-structured interviews including the cognitive 'thinking-aloud' technique were used to test the messages with adults living with MS. Data were transcribed and coded thematically.

RESULTS

Theoretical saturation was reached by 15 interviews. The data corpus indicated three themes and seven subthemes. The data revealed that people living with MS changed their diet after MS diagnosis. Dietary change was due to uncertainty, fear of disease progression and risk of relapse. The admiration and scepticism of extremist MS diets depended on personal vulnerability and support from health care professionals. The unique MS journey appeared influential to message interpretation; driven by engagement, practicality, and credibility.

CONCLUSION

The interpretation of targeted nutrition messages revealed that dietary changes made after diagnosis are a coping mechanism to improve sense of control and self-management.

PRACTICAL IMPLICATIONS

The potential psychological benefit of dietary change for MS management must be prioritised using person-centred care.

Avocado intake and cardiometabolic risk factors in a representative survey of Australians: a secondary analysis of the 2011-2012 national nutrition and physical activity survey

BACKGROUND

Avocados are a rich source of nutrients including monounsaturated fats, dietary fibre and phytochemicals. Higher dietary quality is reported in studies of consumers with higher avocado intakes. The present study aimed to examine avocado consumption and cardiometabolic risk measures in a representative sample of Australian adults.

METHODS

A cross-sectional analysis was performed using Australian Health Survey 2011-2013 (n = 2,736 observations). Day 1 24-hour recall data was used to examine reported avocado intake (whole avocados and avocado-containing products excluding avocado oil) and cardiometabolic risk measures (LDL, HDL, and total cholesterol, triglycerides, apolipoprotein B, HbA1c, plasma glucose, systolic and diastolic blood pressure). T-tests and chi square analyses were conducted between low (5.21 [95% CI: 4.63, 5.79] grams/day) and high (44.11 [95% CI: 35.89, 52.33] grams/day) consumers of avocado.

RESULTS

14.7% of Australians were 'avocado consumers' (n = 403 observations). Mean avocado intake was 24.63 (95% CI: 20.11, 29.15) grams per day, with a median intake of 10.40 (IQR: 4.49-26.00) grams per day for those considered 'avocado consumers'. Consumers of avocados had a lower BMI and waist circumference (each, p ≤ 0.001), lower plasma glucose level (p = 0.03), and higher HDL cholesterol (p ≤ 0.001) when compared with non-consumers. A trend towards lower plasma glucose, HbA1c (each, p = 0.04) and higher dietary fibre intake (p = 0.05) was found between high and low consumers of avocado.

CONCLUSIONS

Our study suggests favourable outcomes for avocado intake and cardiometabolic characteristics of consumers. Future studies should explore glucose homeostasis using a clinical trial design to understand potential relationships between avocado intake and cardiometabolic risk factors.

A Novel Mobile App for Personalized Dietary Advice Leveraging Persuasive Technology, Computer Vision, and Cloud Computing: Development and Usability Study

BACKGROUND

The Australian Dietary Guidelines (ADG) translate the best available evidence in nutrition into food choice recommendations. However, adherence to the ADG is poor in Australia. Given that following a healthy diet can be a potentially cost-effective strategy for lowering the risk of chronic diseases, there is an urgent need to develop novel technologies for individuals to improve their adherence to the ADG.

OBJECTIVE

This study describes the development process and design of a prototype mobile app for personalized dietary advice based on the ADG for adults in Australia, with the aim of exploring the usability of the prototype. The goal of the prototype was to provide personalized, evidence-based support for self-managing food choices in real time.

METHODS

The guidelines of the design science paradigm were applied to guide the design, development, and evaluation of a progressive web app using Amazon Web Services Elastic Compute Cloud services via iterations. The food layer of the Nutrition Care Process, the strategies of cognitive behavioral theory, and the ADG were translated into prototype features guided by the Persuasive Systems Design model. A gain-framed approach was adopted to promote positive behavior changes. A cross-modal image-to-recipe retrieval model under an Apache 2.0 license was deployed for dietary assessment. A survey using the Mobile Application Rating Scale and semistructured in-depth interviews were conducted to explore the usability of the prototype through convenience sampling (N=15).

RESULTS

The prominent features of the prototype included the use of image-based dietary assessment, food choice tracking with immediate feedback leveraging gamification principles, personal goal setting for food choices, and the provision of recipe ideas and information on the ADG. The overall prototype quality score was "acceptable," with a median of 3.46 (IQR 2.78-3.81) out of 5 points. The median score of the perceived impact of the prototype on healthy eating based on the ADG was 3.83 (IQR 2.75-4.08) out of 5 points. In-depth interviews identified the use of gamification for tracking food choices and innovation in the image-based dietary assessment as the main drivers of the positive user experience of using the prototype.

CONCLUSIONS

A novel evidence-based prototype mobile app was successfully developed by leveraging a cross-disciplinary collaboration. A detailed description of the development process and design of the prototype enhances its transparency and provides detailed insights into its creation. This study provides a valuable example of the development of a novel, evidence-based app for personalized dietary advice on food choices using recent advancements in computer vision. A revised version of this prototype is currently under development.

Mobile apps used for people living with multiple sclerosis: A scoping review

BACKGROUND

Multiple Sclerosis (MS) is a chronic neurodegenerative disorder. People living with MS (plwMS) require long-term, multidisciplinary care in both clinical and community settings. MS-specific mHealth interventions have advanced in the form of clinical treatments, rehabilitation, disease monitoring and self-management of disease. However, mHealth interventions for plwMS appear to have limited proof of clinical efficacy. As native mobile apps target specific mobile operating systems, they tend to have better interactive designs leveraging platform-specific guidelines. Thus, to improve such efficacy, it is pivotal to explore the design characteristics of native mobile apps used for plwMS.

OBJECTIVES

This study aimed to explore the design characteristics of native mobile apps used for adults living with MS in academic settings.

METHODS

A scoping review of studies was conducted. A literature search was performed through PubMed, CINAHL, MEDLINE and Cochrane Library. Per native mobile apps, characteristics, persuasive technology elements and evaluations were summarized.

RESULTS

A total of 14 native mobile apps were identified and 43% of the identified apps were used for data collection (n=6). Approximately 70% of the included apps involved users (plwMS) whilst developing (n=10). A total of three apps utilized embedded sensors. Videos or photos were used for physical activity interventions (n=2) and gamification principles were applied for cognitive and/or motor rehabilitation interventions (n=3). Behavior change theories were integrated into the design of the apps for fatigue management and physical activity. Regarding persuasive technology, the design principles of primary support were applied across all identified apps. The elements of dialogue support and social support were the least applied. The methods for evaluating the identified apps were varied.

CONCLUSION

The findings suggest that the identified apps were in the early stages of development and had a user-centered design. By applying the persuasive systems design model, interaction design qualities and features of the identified mobile apps in academic settings were systematically evaluated at a deeper level. Identifying the digital functionality and interface design of mobile apps for plwMS will help researchers to better understand interactive design and how to incorporate these concepts in mHealth interventions for improvement of clinical efficacy.

Using Online 24-h Dietary Methodology to Validate the Psychometric Properties of a Dietary Scoring Tool with an International Sample of Adults Living with Multiple Sclerosis

Understanding the dietary characteristics of people living with multiple sclerosis (plwMS) may assist in the planning of nutrition interventions for multiple sclerosis; yet dietary assessment methods in existing studies are not well established. The aim of this study was to validate the psychometric properties (construct validity and internal consistency) of the Dietary Habits Questionnaire (DHQ) against repeated online 24-h recall dietary assessments. The DHQ is a 24-item tool that is scored using ten dietary sub-scores. Total DHQ scores can range from 20−100 and are considered indicative of the quality of dietary intake with higher scores reflecting increased quality. People living with a relapsing-remitting MS phenotype who had completed a modified DHQ were recruited from the international Health Outcomes and Lifestyle In a Sample of people with Multiple sclerosis (HOLISM) cohort. Repeated 24-h recall via the online Automated Self-administered Assessment-24 (ASA-24) tool were modelled to reflect usual dietary intakes using the Multiple Source Method. DHQ scores of eight sub-scores: three key nutrients, three food groups and two food preparation practices, were calculated and statistically compared with ASA-24 usual intake data. Principal component analysis of the ASA-24 data was undertaken to understand dietary patterns of the sample. Of the 105 participants, valid 24-h recall data were available for 96 plwMS (n = 66 1 day, n = 30 ≥ 2 day). The median total DHQ score was 84.50 (IQR: 77.04, 91.83) points. The highest absolute correlations were between the DHQ scores and ASA-24 data for cereal (r = 0.395, p < 0.001), fruit and vegetables (r = 0.436, p < 0.001), and total dietary fiber (r = 0.482, p < 0.001). Five dietary patterns emerged from the data explaining 42.12% variance and reflecting exposure of plwMS to the influence of ‘MS diets’. The DHQ appears to be appropriate for screening participants with relapsing-remitting MS. Evidence-based dietary models focusing on food are required to monitor the quality of an overall dietary pattern and set priorities for the planning nutrition interventions for plwMS.

Patient self-management and empowerment for multiple sclerosis: The implications of dietary lifestyle management for primary care

BACKGROUND

Multiple sclerosis (MS) is a chronic neurological condition of increasing prevalence. Many people living with MS will trial various alternative therapies, including changed patterns of eating, to try to gain control over their condition. New clinical guidelines advise reducing the time between first clinical symptoms and treatment. It is the support of the healthcare team that can empower the person in their healthcare journey.

OBJECTIVE

The aim of this article is to provide insights into the role of diet as an element of lifestyle management of MS and describe the implications of diet as a first-line treatment for MS.

DISCUSSION

Many 'MS diets' have been promoted to persons diagnosed with MS, yet evidence-based advice is necessitated by an expressed need. Although health risks of short-term exploration of specific diets are not likely to cause concern, lifestyle management should be included in communication plans, with referrals to other healthcare professionals as appropriate.

Development of a Choline Database to Estimate Australian Population Intakes

The AUSNUT 2011-13 food composition database was expanded to include Australian choline values. The development began with a systematic literature review of published studies. Analytical data from the food studies were extracted and aligned with their equivalent AUSNUT food identification code. Global food composition databases containing choline values were matched to the remaining AUSNUT food codes, following the FAO INFOODS food matching guidelines, including adjustments for moisture and protein composition. Composite foods, and not further-specified foods, were developed using the Food Standards Australia New Zealand (FSANZ) recipe files. The completed choline database was then employed to analyse the Australian National Nutrition and Physical Activity Survey 2011-12, with population and sampling weightings applied. Survey respondents were classified into categories based on their level of choline intake and compared with the Australian Adequate Intake levels. Food sources of intake were also explored. Multiple linear regression models were developed for food group contributors to choline intake. Mean choline intakes varied from 151.50 mg for pregnant 14-18 years old, to 310.54 mg for 19-64 year old males. Less than 10% of the population by age and gender were achieving the Adequate Intake for choline. Eggs and their contributing food groups were the top ranked food sources of choline for the population.

The effect of nut consumption on markers of inflammation and endothelial function: a systematic review and meta-analysis of randomised controlled trials

OBJECTIVES

To examine the effect of nut consumption on inflammatory biomarkers and endothelial function.

DESIGN

A systematic review and meta-analysis.

DATA SOURCES

MEDLINE, PubMed, Cumulative Index to Nursing and Allied Health Literature and Cochrane Central Register of Controlled Trials (all years to 13 January 2017).

ELIGIBILITY CRITERIA

Randomised controlled trials (with a duration of 3 weeks or more) or prospective cohort designs conducted in adults; studies assessing the effect of consumption of tree nuts or peanuts on C-reactive protein (CRP), adiponectin, tumour necrosis factor alpha, interleukin-6, intercellular adhesion molecule 1, vascular cell adhesion protein 1 and flow-mediated dilation (FMD).

DATA EXTRACTION AND ANALYSIS

Relevant data were extracted for summary tables and analyses by two independent researchers. Random effects meta-analyses were conducted to explore weighted mean differences (WMD) in change or final mean values for each outcome.

RESULTS

A total of 32 studies (all randomised controlled trials) were included in the review. The effect of nut consumption on FMD was explored in nine strata from eight studies (involving 652 participants), with consumption of nuts resulting in significant improvements in FMD (WMD: 0.79%(95% CI 0.35 to 1.23)). Nut consumption resulted in small, non-significant differences in CRP (WMD: -0.01 mg/L (95% CI -0.06 to 0.03)) (26 strata from 25 studies), although sensitivity analyses suggest results for CRP may have been influenced by two individual studies. Small, non-significant differences were also found for other biomarkers of inflammation.

CONCLUSIONS

This systematic review and meta-analysis of the effects of nut consumption on inflammation and endothelial function found evidence for favourable effects on FMD, a measure of endothelial function. Non-significant changes in other biomarkers indicate a lack of consistent evidence for effects of nut consumption on inflammation. The findings of this analysis suggest a need for more research in this area, with a particular focus on randomised controlled trials.

PROSPERO REGISTRATION NUMBER

CRD42016045424.

A systematic review of food composition tools used for determining dietary polyphenol intake in estimated intake studies

Translating food intake data into phytochemical outcomes is a crucial step in investigating potential health benefits. The aim of this review was to examine the tools for determining dietary-derived polyphenol intakes for estimated intake studies. Published studies from 2004 to 2014 reporting polyphenol food composition information were sourced with 157 studies included. Six polyphenol subclasses were identified. One quarter of studies (n=39) reported total flavonoids intake with 27% reporting individual flavonoid compounds. Assessing multiple compounds was common with approximately 10% of studies assessing seven (n=13), six (n=12) and five (n=14) subclasses of polyphenol. There was no pattern between reported flavonoids compounds and subclass studied. Approximately 60% of studies relied on publicly accessible food composition data to estimate dietary polyphenols intake with 33% using two or more tools. This review highlights the importance of publicly accessible composition databases for estimating polyphenol intake and provides a reference for tools available globally.

Development of an At-Risk Assessment Approach to Dietary Data Quality in a Food-Based Clinical Trial

Accurate and valid dietary data is the basis to investigate diet-disease relationships. Potential data discrepancies may be introduced when collecting and analysing data, despite rigorous quality assurance protocols. The aim of this study was to identify at-risk areas of dietary data in a food-based clinical trial. Source data verification was performed on a 10% random sample (n=38) of paper-based baseline diet history interview records in a registered clinical trial. All items listed in the source data underwent 100% manual verification based on the food input data from FoodWorks nutrient analysis software. Food item discrepancies were explored using food categories and summarised based on meals. The differences in identified discrepancies for energy and macronutrient output generated from FoodWorks software between previously entered data and re-entered data were compared. An overall discrepancy rate of 4.88% was identified. It was found that dinner intake data were more prone to discrepancy incidences than breakfast, lunch and snacks. Furthermore, assessing intake based on reported quantity and frequency may be more effective to correct discrepancies for quality improvement. Therefore, the dinner meal appeared to be an at risk area of dietary data. The method implemented in this study offers a systematic approach to evaluating dietary data in a research setting.