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.

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.

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.

Identifying usual food choices with avocados in a clinical trial cohort of overweight and obese adults in Australia.

BACKGROUND: Consumption of avocados has been suggested to be beneficial for weight control, however, limited research is available about the related food choices. Understanding the food choices associated with avocados at meal occasions may further aid behavioural strategies to lose weight. The present study used a systematic approach to develop an avocado-specific food database, with the aim to explore food choices related to avocados at meal occasions as reported by overweight and obese volunteers in weight loss clinical trials. METHODS: The avocado-specific database was based on AUSNUT 2011-13 food composition database structure and was developed via a systematic approach, which determined the avocado content of Australian foods and beverages. Baseline usual food intake data was retrospectively pooled from four food-based clinical trials (n = 758). The Apriori algorithm of association rules, a two-step descriptive method was used to identify food choices associated with avocados at different meal occasions using a nested hierarchical food group classification system. RESULTS: The avocado database identified 34 avocados and avocado-containing foods and beverages. The proportion of avocado consumers in the pooled cohort was 51.3% (n = 389), with an average avocado intake of 21.57 ± 36.75 grams per day. Avocados were found to be closely related to other food groups at all of the food group levels at main meal occasions. A total of 68 food items containing avocados were identified for avocado consumers at the breakfast, lunch and dinner meals. CONCLUSION: The avocado specific database provides a snapshot of the foods and beverages which contain avocados. Enumerating the full range of food choices in relation to avocado consumption should provide examples of food choices that people might consider in their efforts to increase their avocado consumption.

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.

Consumption of avocado and associations with nutrient, food and anthropometric measures in a representative survey of Australians: a secondary analysis of the 2011-2012 National Nutrition and Physical Activity Survey.

Avocados are a rich source of nutrients including monounsaturated fats, dietary fibre, potassium and Mg, as well as phytochemicals. However, no epidemiological analysis for the associations between avocado consumption and participant anthropometric measures has been conducted in Australia. The present study aimed to perform a secondary analysis of the 2011-2012 National Nutrition and Physical Activity Survey (NNPAS) to quantify avocado consumption in the Australian population and explore the associations between avocado intakes, consumption of nutrients and food groups based on the Australian Dietary Guidelines and anthropometric measurements. Usual avocado consumption in the 2011-2012, NNPAS was determined using the multiple source method regression model. The relationship between avocado consumption and intakes of key nutrients and food groups and participant weight, BMI and waist circumference were examined using linear regression. Mean avocado intake was 2·56 (95 % CI: 2·37, 2·75) grams per day with 15·9 % of Australians considered to be 'avocado consumers' (n 21 526 456 population size; n 12 153 observations). Greater consumption (g) of avocados was associated with significantly higher consumption of monounsaturated fats, polyunsaturated fats, dietary fibre, vitamin E, Mg and potassium, as well as 'whole grains', 'vegetables', 'fruit' and 'meat and alternatives' food groups. Greater consumption (g) of avocados was associated with significantly lower consumption of carbohydrates and discretionary foods. When adjusted for covariates, greater consumption of avocados was significantly associated with a lower body weight (P = 0·034), BMI (P < 0·001) and waist circumference (P < 0·001). Avocados may be incorporated into an eating pattern and may be beneficial in weight management.

Identifying Usual Food Choice Combinations With Walnuts: Analysis of a 2005-2015 Clinical Trial Cohort of Overweight and Obese Adults.

Consumption of nuts has been associated with a range of favorable health outcomes. Evidence is now emerging to suggest that walnuts may also play an important role in supporting the consumption of a healthy dietary pattern. However, limited studies have explored how walnuts are eaten at different meal occasions. The aim of this study was to explore the food choices in relation to walnuts at meal occasions as reported by a sample of overweight and obese adult participants of weight loss clinical trials. Baseline usual food intake data were retrospectively pooled from four food-based clinical trials (n = 758). A nut-specific food composition database was applied to determine walnut consumption within the food intake data. The a priori algorithm of association rules was used to identify food choices associated with walnuts at different meal occasions using a nested hierarchical food group classification system. The proportion of participants who were consuming walnuts was 14.5% (n = 110). The median walnut intake was 5.14 (interquartile range, 1.10-11.45) g/d. A total of 128 food items containing walnuts were identified for walnut consumers. The proportion of participants who reported consuming unsalted raw walnut was 80.5% (n = 103). There were no identified patterns to food choices in relation to walnut at the breakfast, lunch, or dinner meal occasions. A total of 24 clusters of food choices related to walnuts were identified at others (meals). By applying a novel food composition database, the present study was able to map the precise combinations of foods associated with walnuts intakes at mealtimes using data mining. This study offers insights into the role of walnuts for the food choices of overweight adults and may support guidance and dietary behavior change strategies.

Effect of walnut consumption on markers of blood glucose control: a systematic review and meta-analysis.

Type 2 diabetes mellitus is a chronic disease increasing in global prevalence. Although habitual consumption of walnuts is associated with reduced risk of CVD, there is inconsistent evidence for the impact of walnut consumption on markers of glycaemic control. This systematic review and meta-analysis aimed to examine the effect of walnut consumption on markers of blood glucose control. A systematic search of Medline, PubMed, CINAHL and Cochrane databases (to 2 March 2019) was conducted. Inclusion criteria were randomised controlled trials conducted with adults which assessed the effect of walnut consumption on fasting blood glucose and insulin, glycated Hb and homeostatic model assessment of insulin resistance. Random effects meta-analyses were conducted to assess the weighted mean differences (WMD) for each outcome. Risk of bias in studies was assessed using the Cochrane Risk of Bias tool 2.0. Sixteen studies providing eighteen effect sizes were included in the review. Consumption of walnuts did not result in significant changes in fasting blood glucose levels (WMD: 0·331 mg/dl; 95 % CI -0·817, 1·479) or other outcome measures. Studies were determined to have either 'some concerns' or be at 'high risk' of bias. There was no evidence of an effect of walnut consumption on markers of blood glucose control. These findings suggest that the known favourable effects of walnut intake on CVD are not mediated via improvements in glycaemic control. Given the high risk of bias observed in the current evidence base, there is a need for further high-quality randomised controlled trials.

Predictors for misreporting sodium and potassium intakes by overweight and obese participants in a food-based clinical trial: implications for practice.

This study compared self-reported sodium and potassium intakes with urinary biomarkers and identified predictive factors. Secondary analysis of the 3-month intensive phase of the HealthTrack study with control (C), interdisciplinary intervention (I), intervention plus 30 g walnuts/day (IW) arms (n = 149). Dietary data was derived from diet history (DH) interviews and biomarker measures from urine. Urine-derived sodium (all, p = 0.000) and potassium (C: p = 0.011; I: p = 0.000; IW: p = 0.004) measures were significantly greater than self-reported intakes over the three months. Multiple linear regression showed body weight at baseline, body mass index (BMI) at baseline, and combined BMI at baseline and DH interviewer significantly negatively predicted the differences in sodium intake and excretion for C (ß = -21.226, p = 0.016), I (ß = -106.140, p = 0.002) and IW (F (9.530, 2df), p = 0.000), respectively. Where intakes of sodium and potassium are of interest in a trial, both reported intake and urinary biomarker measures are recommended.

Evaluation of the dietary intake data coding process in a clinical setting: Implications for research practice.

BACKGROUND: High quality dietary intake data is required to support evidence of diet-disease relationships exposed in clinical research. Source data verification may be a useful quality assurance method in this setting. The present pilot study aimed to apply source data verification to evaluate the quality of the data coding process for dietary intake in a clinical trial and to explore potential barriers to data quality in this setting. METHODS: Using a sample of 20 cases from a clinical trial, source data verification was conducted between three sets of data derived documents: transcripts of audio-recorded diet history interviews, matched paper-based diet history forms and outputs from nutrition analysis software. The number of cases and rates of discrepancies between documents were calculated. A total of five in-depth interviews with dietitians collecting and coding dietary data were thematically analysed. RESULTS: Some 2024 discrepancies were identified. The highest discrepancy rate was 57.49%, and occurred between diet history interviews and nutrition analysis software outputs. Sources of the discrepancies included both quantities and frequencies of food intake. The highest discrepancy rate was for the food group "vegetable products and dishes". In-depth interviews implicated recall bias of trial participants as a cause of discrepancies, but dietitians also acknowledged a possible subconscious influence of having to code reported foods into nutrition analysis software programs. CONCLUSION: The accuracy of dietary intake data appeared to depend on the level of detailed food data required. More support for participants on reporting consumption, and incorporating supportive tools to guide estimates of food quantities may facilitate a more consistent coding process and improve data quality. This pilot study offers a novel method and an overview of dietary intake data coding measurement errors. These findings may warrant further investigation in a larger sample.

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.

A systematic review of osteoarthritis prevention and management with dietary phytochemicals from foods.

Osteoarthritis is the most prevalent chronic inflammatory joint disease affecting mobility in humans, as well as in companion and captive animals. Understanding the effect of dietary phytochemical intake from foods on osteoarthritis and its long-term outcomes may inform public health strategies for osteoarthritis prevention and management, reducing healthcare costs globally. The aim of this systematic review was to examine the effects of dietary phytochemical intake from foods on osteoarthritis in adult populations. A literature search was performed using Scopus, Web of Science, MEDLINE, PubMed and the Cochrane Library for human studies to identify randomised controlled trials (RCTs) and observational studies focused on osteoarthritis up to May 2018. From 5879 articles, five RCTs and four cross-sectional studies were identified. Dietary carotenoids were examined in the observational studies, while dietary intakes of polyphenols from foods were assessed in the RCTs. Dietary polyphenol intake from foods (e.g., freeze-dried strawberries and tart cherry juice) may slow the progression of osteoarthritis via decreased inflammation and reduced cartilage degradation. However, there were relatively few studies and a lack of uniformity in the biomarkers used and the measurements of pain, quality of life and physical activity relating to osteoarthritis. The heterogeneity among the studies suggests that there is insufficient evidence related to phytochemical intake from foods. High-quality epidemiological studies and controlled trials are therefore required. Nevertheless, exploring dietary phytochemical intake from foods may complement current dietary strategies for the management of osteoarthritis and help in the formulation of more economical and manageable strategies for osteoarthritis.

Identifying usual food choices at meals in overweight and obese study volunteers: implications for dietary advice.

Understanding food choices made for meals in overweight and obese individuals may aid strategies for weight loss tailored to their eating habits. However, limited studies have explored food choices at meal occasions. The aim of this study was to identify the usual food choices for meals of overweight and obese volunteers for a weight-loss trial. A cross-sectional analysis was performed using screening diet history data from a 12-month weight-loss trial (the HealthTrack study). A descriptive data mining tool, the Apriori algorithm of association rules, was applied to identify food choices at meal occasions using a nested hierarchical food group classification system. Overall, 432 breakfasts, 428 lunches, 432 dinners and 433 others (meals) were identified from the intake data (n 433 participants). A total of 142 items of closely related food clusters were identified at three food group levels. At the first sub-food group level, bread emerged as central to food combinations at lunch, but unprocessed meat appeared for this at dinner. The dinner meal was characterised by more varieties of vegetables and of foods in general. The definitions of food groups played a pivotal role in identifying food choice patterns at main meals. Given the large number of foods available, having an understanding of eating patterns in which key foods drive overall meal content can help translate and develop novel dietary strategies for weight loss at the individual level.

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.

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.

Dietary phytochemical intake from foods and health outcomes: a systematic review protocol and preliminary scoping.

INTRODUCTION: Dietary phytochemicals are found in plant-based foods such as fruits, vegetables and grains and may be categorised in a nested hierarchical manner with many hundred individual phytochemicals identified to date. To associate phytochemical intakes with positive health outcomes, a fundamental step is to accurately estimate the dietary phytochemical intake from foods reported. The purpose of this systematic review protocol is to describe the process to be undertaken to summarise the evidence for food-based dietary phytochemical intakes and health outcomes for adults. METHODS AND ANALYSIS: The review will be undertaken following the PRISMA guidelines and the Cochrane Handbook for Systematic Reviews of Interventions using the Review Manager software. Phytochemical subclasses (phenolic acids, flavanols, etc) will be used to search for relevant studies using the Web of Science and Scopus scientific databases. The retrieved studies will be screened based on inclusion of natural whole food items and health outcomes. Phytochemical studies related to cardiovascular disease, cancer, overweight, glucose tolerance, digestive, reproductive, macular and bone health and mental disorders, fatigue and immunity will be examined based on prior scoping. The evidence will be aggregated by the food types and health outcomes. Comparison of differences in the outcomes for randomised controlled trials and observational studies will be undertaken. The strength of the review lies in its focus on whole food items and health conditions rather than one type of phytochemical related to one single health condition. Subgroup and sensitivity analyses will be conducted where an adequate number of publications are found per phytochemical subclass. DISSEMINATION: By comparing the outcomes from experimental and observational studies, the review will determine whether the overall conclusions related to the phytochemical subclasses are the same between study types for the identified health conditions. This is useful to public health policymakers and health professionals alike. TRIAL REGISTRATION NUMBER: #CRD42014015610.

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.