Trends in Health-Risk Behaviors and Psychological Distress among Australian First-Year University Students.

University students are recognized as a high-risk population group who experience greater rates of poor health outcomes and mental ill-health. Commencing university is recognized as a major life transition, where students experience new financial, academic, environmental, and social pressures that can cause changes in their normal behaviors. This study explored trends in health-risk behaviors and psychological distress in commencing university students over four survey years. First-year undergraduate students, aged 17-24, from an Australian university were included. A secondary analysis was performed on data collected via cross-sectional surveys on four occasions (2016, 2017, 2019, 2020). Crude logistic regression models were utilized to investigate the association between meeting guidelines and survey year. Odds ratios for the pairwise comparison between each year are reported. In this analysis, 1300 (2016), 484 (2017), 456 (2019), and 571 (2020) students were included. Analyses showed two clear trends: students' probability of being at high/very high risk of psychological distress (35-55%) and consuming breakfast daily (44-55%) consistently worsened over the four survey years. These findings suggest that the odds of psychological distress and daily breakfast consumption worsened over time, whilst the proportion of students engaging in some health-risk behaviors was high, highlighting the importance of early intervention during the transition to university.

A three-arm randomised controlled trial of a telehealth intervention targeting improvement in addictive eating for Australian adults (the TRACE program).

There is a substantial research base for addictive eating with development of interventions. The current 3-arm RCT aimed to investigate the efficacy of the TRACE (Targeted Research for Addictive and Compulsive Eating) program to decrease addictive eating symptoms and improve mental health. Participants (18-85 yrs) endorsing ≥3 addictive eating symptoms were randomly allocated to 1) active intervention, 2) passive intervention, or 3) control group. Primary outcome was change in addictive eating symptoms 3-months post-baseline measured by the Yale Food Addiction Scale. Depression, anxiety and stress were also assessed. A total of 175 individuals were randomised. Using Linear Mixed Models, from baseline to 3-months, there was significant improvement in symptom scores in all groups with mean decrease of 4.7 (95% CI: -5.8, -3.6; p < 0.001), 3.8 (95% CI: -5.2, -2.4; p < 0.001) and 1.5 (95% CI: -2.6, -0.4; p = 0.01) respectively. Compared with the control group, participants in the active intervention were five times more likely to achieve a clinically significant change in symptom scores. There was a significant reduction in depression scores in the active and passive intervention groups, but not control group [-2.9 (95% CI: -4.5, -1.3); -2.3 (95% CI: -4.3, -0.3); 0.5 (95% CI: -1.1, 2.1), respectively]; a significant reduction in stress scores within the active group, but not passive intervention or control groups [-1.3 (95% CI: -2.2, -0.5); -1.0 (95% CI: -2.1, 0.1); 0.4 (95% CI: -0.5, 1.2), respectively]; and the reduction in anxiety scores over time was similar for all groups. A dietitian-led telehealth intervention for addictive eating in adults was more effective than a passive or control condition in reducing addictive eating scores from baseline to 6 months. Trial registration: Australia New Zealand Clinical Trial Registry ACTRN12621001079831.

Happy Little Vegemites™! An analysis of the contribution of yeast extract spreads and tomato-based sauces to nutrient intake adequacy in Australia.

BACKGROUND: Yeast extract spreads and tomato-based sauces (i.e., ketchup) are consumed regularly by the Australian population. Therefore, there is a need to explore the contribution of these condiments to nutrient intakes among Australians. METHODS: The present study comprises a secondary analysis of data from the 2011-2012 Australian National Nutrition and Physical Activity Survey. Dietary intake data were undertaken for 12,153 Australians aged ≥ 2 years, using 24-h recalls. Yeast extract spreads and tomato-based sauces were categorised based on how they were defined in the Australian Food and Nutrient (AUSNUT) 2011-2013 database. Kruskal-Wallis H tests and the post-hoc Dunn's test with Bonferroni correction were applied to test whether a significant difference existed in the percentage contribution of yeast extract spreads and tomato-based sauces to intakes of select nutrients. RESULTS: In total, 19.6% (n = 2384) of the population sample consumed yeast extract spreads and/or tomato-based sauces during the 24-h recall. The percentage contribution of yeast extract spreads to daily intakes of sodium, potassium, thiamine, riboflavin, niacin, folate, magnesium, iron, zinc and iodine were significantly higher in line with a greater quantity of yeast extract spread consumed (p < 0.05). The percentage contribution of tomato-based sauces to daily intakes of sodium, potassium, riboflavin, niacin, folate, beta-carotene, magnesium, iron, zinc and iodine was increased significantly with a greater quantity of tomato-based sauces consumed (p < 0.05). CONCLUSIONS: Consumption of yeast extracts and tomato-based sauces contribute to greater intake of key nutrients, such as B-vitamins and beta-carotene, and may assist in meeting key nutrient reference values. However, consumption of these sauces and condiments also resulted in greater intakes of sodium, contributing to population intakes exceeding recommendations. Reducing sodium content of frequently consumed condiments may potentially assist in lowering population intakes, at the same time as preserving intakes of other important nutrients.

Diet quality and cardiovascular outcomes: A systematic review and meta-analysis of cohort studies.

AIMS: To evaluate relationships between diet quality and cardiovascular outcomes. METHODS: Six databases were searched for studies published between January 2007 and October 2021. Eligible studies included cohort studies that assessed the relationship between a priori diet quality and cardiovascular disease mortality and morbidity in adults. The Academy of Nutrition and Dietetics Checklist was used to assess the risk of bias. Study characteristics and outcomes were extracted from eligible studies using standardised processes. Data were summarised using risk ratios for cardiovascular disease incidence and mortality with difference compared for highest versus lowest diet quality synthesised in meta-analyses using a random effects model. RESULTS: Of the 4780 studies identified, 159 studies (n = 6 272 676 adults) were included. Meta-analyses identified a significantly lower cardiovascular disease incidence (n = 42 studies, relative risk 0.83, 95% CI 0.82-0.84, p < 0.001) and mortality risk (n = 49 studies, relative risk 0.83, 95% CI 0.82-0.84, p < 0.001) among those with highest versus lowest diet quality. In sensitivity analyses of a high number of pooled studies (≥13 studies) the Mediterranean style diet patterns and adherence to the heart healthy diet guidelines were significantly associated with a risk reduction of 15% and 14% for cardiovascular disease incidence and 17% and 20% for cardiovascular disease mortality respectively (p < 0.05). CONCLUSIONS: Higher diet quality is associated with lower incidence and risk of mortality for cardiovascular disease however, significant study heterogeneity was identified for these relationships.

Exploring the design and utility of an integrated web-based chatbot for young adults to support healthy eating: a qualitative study.

BACKGROUND: There is a lack of understanding of the potential utility of a chatbot integrated into a website to support healthy eating among young adults. Therefore, the aim was to interview key informants regarding potential utility and design of a chatbot to: (1) increase young adults' return rates and engagement with a purpose-built healthy eating website and, (2) improve young adults' diet quality. METHODS: Eighteen qualitative, semi-structured interviews were conducted across three stakeholder groups: (i) experts in dietary behaviour change in young adults (n = 6), (ii) young adult users of a healthy eating website (n = 7), and (iii) experts in chatbot design (n = 5). Interview questions were guided by a behaviour change framework and a template analysis was conducted using NVivo. RESULTS: Interviewees identified three potential roles of a chatbot for supporting healthy eating in young adults; R1: improving healthy eating knowledge and facilitating discovery, R2: reducing time barriers related to healthy eating, R3: providing support and social engagement. To support R1, the following features were suggested: F1: chatbot generated recommendations and F2: triage to website information or externally (e.g., another website) to address current user needs. For R2, suggested features included F3: nudge or behavioural prompts at critical moments and F4: assist users to navigate healthy eating websites. Finally, to support R3 interviewees recommended the following features: F5: enhance interactivity, F6: offer useful anonymous support, F7: facilitate user connection with content in meaningful ways and F8: outreach adjuncts to website (e.g., emails). Additional 'general' chatbot features included authenticity, personalisation and effective and strategic development, while the preferred chatbot style and language included tailoring (e.g., age and gender), with a positive and professional tone. Finally, the preferred chatbot message subjects included training (e.g., would you like to see a video to make this recipe?), enablement (e.g., healthy eating doesn't need to be expensive, we've created a budget meal plan, want to see?) and education or informative approaches (e.g., "Did you know bananas are high in potassium which can aid in reducing blood pressure?"). CONCLUSION: Findings can guide chatbot designers and nutrition behaviour change researchers on potential chatbot roles, features, style and language and messaging in order to support healthy eating knowledge and behaviours in young adults.

Implementation of health and wellbeing policies and programs for students: Views of Australian universities.

ISSUE ADDRESSED: Universities are a crucial setting to address and promote optimal mental health of young Australians. However, there is a lack of knowledge of universities' views of current implementation of health and wellbeing initiatives. Therefore, we examined the views of Australian universities on the implementation of health and wellbeing policies and programs within Australian universities. METHODS: An online survey of Australian universities asked respondents to rate their level of agreement with five statements pertaining to the implementation of health and wellbeing policies and programs for students within Australian universities using a 5-point Likert scale (strongly agree to strongly disagree). RESULTS: Eleven universities completed the survey (28.2% response rate). All respondents (n = 11) agreed that universities play a crucial role in supporting the health and wellbeing of their students and report access to sufficient expertise to do this. Approximately three-quarters (8/11) agreed that universities know what policies and programs to implement to support their students' health and wellbeing. There was less agreement that universities have sufficient resources (2/11 agree) or access to sufficient information about the health and wellbeing of their student population (3/11 agree) to support the implementation of health and wellbeing policies and programs. CONCLUSIONS: Australian universities demonstrated strong organisational commitment to supporting the health and wellbeing of their students but highlighted some key barriers to implementation. SO WHAT?: Findings from this preliminary research highlight potential barriers and facilitators to the implementation of health and wellbeing policies and programs in Australian universities, and potential foci for future research.

Examining the efficacy of a telehealth intervention targeting addictive eating in Australian adults (the TRACE Programme): a randomised controlled trial protocol.

INTRODUCTION: Approximately 15%-20% of the adult population self-report symptoms of addictive eating. There are currently limited options for management. Motivational interviewing-based interventions, containing personalised coping skills training, have been found to be effective for behaviour change in addictive disorders (eg, alcohol). This project builds upon foundations of an addictive eating feasibility study previously conducted and co-design process involving consumers. The primary aim of this study is to examine the efficacy of a telehealth intervention targeting addictive eating symptoms in Australian adults compared with passive intervention and control groups. METHODS AND ANALYSIS: This three-arm randomised controlled trial will recruit participants 18-85 years, endorsing ≥3 symptoms on the Yale Food Addiction Scale (YFAS) 2.0, with body mass index >18.5 kg/m2. Addictive eating symptoms are assessed at baseline (pre-intervention), 3 months (post-intervention) and 6 months. Other outcomes include dietary intake and quality, depression, anxiety, stress, quality of life, physical activity and sleep hygiene. Using a multicomponent clinician-led approach, the active intervention consists of five telehealth sessions (15-45 min each) delivered by a dietitian over 3 months. The intervention uses personalised feedback, skill-building exercises, reflective activities and goal setting. Participants are provided with a workbook and website access. The passive intervention group receives the intervention via a self-guided approach with access to the workbook and website (no telehealth). The control group receives personalised written dietary feedback at baseline and participants advised to follow their usual dietary pattern for 6 months. The control group will be offered the passive intervention after 6 months. The primary endpoint is YFAS symptom scores at 3 months. A cost-consequence analysis will determine intervention costs alongside mean change outcomes. ETHICS AND DISSEMINATION: Human Research Ethics Committee of University of Newcastle, Australia provided approval (H-2021-0100). Findings will be disseminated via publication in peer-reviewed journals, conference presentations, community presentations and student theses. TRIAL REGISTRATION NUMBER: Australia New Zealand Clinical Trials Registry (ACTRN12621001079831).

How is online self-reported weight compared with image-captured weight? A comparative study using data from an online longitudinal study of young adults.

BACKGROUND: Accurate anthropometric measurement is important within epidemiological studies and clinical practice. Traditionally, self-reported weight is validated against in-person weight measurement. OBJECTIVES: This study aimed to 1) determine the comparison of online self-reported weight against images of weight captured on scales in a young adult sample, 2) compare this across body mass index (BMI), gender, country, and age groups, and 3) explore demographics of those who did/did not provide a weight image. METHODS: Cross-sectional analysis of baseline data from a 12-mo longitudinal study of young adults in Australia and the UK was conducted. Data were collected by online survey via Prolific research recruitment platform. Self-reported weight and sociodemographics (for example, age, gender) were collected for the whole sample (n = 512), and images of weight for a subset (n = 311). Tests included Wilcoxon signed-rank test to evaluate differences between measures, Pearson correlation to explore the strength of the linear relationship, and Bland-Altman plots to evaluate agreement. RESULTS: Self-reported weight [median (interquartile range), 92.5 kg (76.7-112.0)] and image-captured weight [93.8 kg (78.8-112.8)] were significantly different (z = -6.76, P < 0.001), but strongly correlated (r = 0.983, P < 0.001). In the Bland-Altman plot [mean difference -0.99 kg (-10.83, 8.84)], most values were within limits of agreement (2 standard deviation). Correlations remained high across BMI, gender, country, and age groups (r > 0.870, P < 0.002). Participants with BMI in ranges 30-34.9 and 35-39.9 kg/m2 were less likely to provide an image. CONCLUSIONS: This study demonstrates the method concordance of image-based collection methods with self-reported weight in online research.

Changes in physical activity, diet, sleep, and mental well-being when starting university: A qualitative exploration of Australian student experiences.

Objective: To explore young adult's experiences of how starting university influenced their physical activity, diet, sleep, and mental well-being, and barriers and enablers to health behavior change. Participants: University students aged 18-25 years. Methods: Three focus groups were conducted in November 2019. Inductive thematic approach was utilized to identify themes. Results: Students (female: n = 13, male: n = 2, other gender identity: n = 1, 21.2 (1.6) years) reported mental well-being, physical activity levels, diet quality and sleep health were negatively affected. Stress, study demands, university timetabling, not prioritizing physical activity, cost and availability of healthy foods, and difficulty falling asleep were key barriers. Health behavior change interventions aiming to support mental well-being need to include both information and support features. Conclusions: There is a significant opportunity to improve the transition to university for young adults. Findings highlight areas to target in future interventions to improve physical activity, diet, and sleep of university students.

Are health behaviors associated with mental health among tertiary education students? A systematic review of cohort studies.

OBJECTIVE: To evaluate the association between health behaviors with mental health among tertiary education students. METHODS: Six databases were searched until September 2021 for prospective cohort studies evaluating the association between health behavior(s) (dietary intake, physical activity, sedentary behavior, alcohol intake, sleep, smoking or illicit drug use) and mental health. Two independent reviewers screened records for inclusion, extracted data and completed risk of bias assessments. RESULTS: 33 studies were included (14 assessed sleep, 14 alcohol intake, 13 physical activity, 8 smoking, 6 sedentary behavior, 4 diet, 1 illicit drug use). A consistent association between poor sleep, and physical inactivity with increased risk of poor psychological wellbeing, and between poor sleep and increased mental ill-health related outcomes was demonstrated. CONCLUSION: Findings suggest interventions to address poor sleep and physical inactivity among students may positively impact mental health. Further research of other health behaviors, and their association with mental health, is required.

Effectiveness and reporting of nutrition interventions in cardiac rehabilitation programmes: a systematic review.

AIMS: Dietary modification is essential for the secondary prevention of cardiovascular disease. However, there are limited published evidence syntheses to guide practice in the cardiac rehabilitation (CR) setting. This systematic review's objective was to assess effectiveness and reporting of nutrition interventions to optimize dietary intake in adults attending CR. METHODS AND RESULTS: Randomized controlled trials (RCTs) of nutrition interventions within CR were eligible for inclusion and had to have measured change in dietary intake. MEDLINE, Embase, Emcare, PsycINFO, CINAHL, Scopus, and The Cochrane Library were searched from 2000 to June 2020, limited to publications in English. Evidence from included RCTs was synthesized descriptively. The risk of bias was assessed using the Cochrane Risk of Bias 2 tool. This review is registered on PROSPERO; CRD42020188723. Of 13 048 unique articles identified, 11 were eligible. Randomized controlled trials were conducted in 10 different countries, included 1542 participants, and evaluated 29 distinct dietary intake outcomes. Five studies reported statistically significant changes in diet across 13 outcomes. Most nutrition interventions were not reported in a manner that allowed replication in clinical practice or future research. CONCLUSION: There is a gap in research testing high-quality nutrition interventions in CR settings. Findings should be interpreted in the light of limitations, given the overall body of evidence was heterogenous across outcomes and study quality; 6 of 11 studies were conducted more than 10 years old. Future research should investigate strategies to optimize and maintain nutrition improvements for patients attending CR. REGISTRATION: PROSPERO; CRD42020188723.

Do sauces, condiments and seasonings contribute important amounts of nutrients to Australian dietary intakes?

BACKGROUND: Dietary assessment commonly focuses on particular foods/food groups as indicators of overall dietary intake. Accompaniments such as sauces are not often a focus. The present study describes daily intakes of sauces, condiments and seasonings (SCS) using the most recent Australian National Nutrition and Physical Activity Survey (NNPAS), as well as the contribution to total energy and selected nutrient intakes. METHODS: NNPAS dietary data were collected by one 24-h recall for 12,153 individuals aged ≥ 2 years (53% female, 29% aged 31-50 years). SCS (i.e., any food items not normally consumed as a food itself, consumed as an addition to a dish after cooking/preparation to enhance flavour) were identified/coded within the dietary data and reported in terms of how they were consumed, primary composition, and contribution to total daily energy and selected macro- and micronutrient intakes. RESULTS: Most participants (85.1%) reported consuming at least one SCS on the day of the recall (median [interquartile range], 2 [1-4]). SCS were predominantly consumed within main meals (breakfast, lunch, dinner) (73.9%), and were predominantly sugar/sugar products (e.g., white sugar) (35.0%), or fats and oils (e.g., butter) (25.9%). SCS contributed a median (interquartile range) of 3.8% (1.1-7.9) of total energy, 5.3% (0.0-15.5) of fat, 2.3% (0.1-6.6) of carbohydrate and 0.2% (0.01-1.2) of protein intake. SCS made the largest contribution towards vitamin E (females median 3.6%; males median 3.4%) and sodium intakes (females median 3.0%; males median 2.9%). CONCLUSIONS: Although SCS contribute a small proportion of total energy and nutrient intakes in the Australian population, the contribution is more substantial for some nutrients and population groups.

How Can We Support Healthy Eating in Young Adults with Low Diet Quality? A Survey of Users of the 'No Money No Time' Healthy Eating Website.

Nutrition interventions to support young adults are needed due to low diet quality. The aims were to explore the (1) circumstances and (2) barriers regarding dietary habits of the young adult users of the No Money No Time (NMNT) healthy eating website with the lowest diet quality scores. An online cross-sectional survey was conducted from August-September 2022 with a sample of NMNT users aged 18-35 years with low diet quality (defined as Healthy Eating Quiz score 0-38/73). The survey included demographics (e.g., gender), circumstances (6-item US Food Security Survey, Cooking and Food Skills Confidence Measures), and challenges and resources used in relation to healthy eating (open-responses). Theoretical thematic analysis was used to analyse open-response questions and derive main themes. The study sample (n = 108; 71.3% female, median age 28; 28.7% food insecure) had a mean (standard deviation) Cooking Skills score 70.2 (17.5)/98, and median (interquartile range) Food Skills score 96.0 (83.5-107.5)/133. The main challenges regarding healthy eating were (1) time and (2) cost, and the main resources to support healthy eating were (1) online resources (e.g., websites, Google) and (2) recipes. Findings identify possible targets for future interventions to support healthy eating in this vulnerable group (e.g., supporting cooking and food skills).

Health behavior interventions for university students measuring mental health outcomes: A scoping review.

Introduction: Many university students have poor mental health, and co-occurring health risk behaviors. Targeting health behavior change in this population may improve mental health outcomes. This scoping review describes the extent and range of randomized controlled trials (RCT) evaluating interventions targeting health risk behaviors and measuring a mental health outcome, among university students. Methods: Six electronic databases were searched for RCTs published until the 18th May 2021. Eligible RCTs included university students, evaluated interventions that promoted health behavior change (i.e., dietary intake, physical activity, sedentary behavior, alcohol and drug use, smoking, and sleep), and measured a mental health-related outcome. Results: Fifty-nine RCTs met the inclusion criteria that were published from 2000 to 2021, and over half (n = 33) were conducted in the United States. Interventions evaluated within the RCTs (n = 92) predominantly targeted changes to dietary intake (n = 41 interventions), physical activity (n = 39), or alcohol intake (n = 35). Most interventions targeted one (n = 51) or two (n = 27) health behaviors only. Included RCTs considered mental ill health outcomes (n = 24), psychological wellbeing outcomes (n = 20), or both (n = 15). Discussion: This scoping review identified a moderate volume of experimental research investigating the impact of health behavior interventions on university students' mental health. There is scope for further research examining health behavior interventions targeting university students, particularly interventions taking a multi-behavioral approach.

Diet Quality of Adolescents and Adults Who Completed the Australian Healthy Eating Quiz: An Analysis of Data over Six Years (2016-2022).

Diet quality is influenced by demographics and can change over time. This study aimed to (1) compare diet quality among adolescents/adults who completed the online Healthy Eating Quiz (HEQ) by demographic characteristics, and (2) to evaluate change in score over time for repeat completers. HEQ data collected between July 2016 and May 2022 were analysed, including demographics (age, gender, vegetarian status, socio-economic status, number of people main meals are shared with, country), and diet quality calculated using the Australian Recommended Food Score (ARFS) (range 0−73) for respondents aged ≥ 16 years. Differences in ARFS by demographic characteristics and change in score over time, adjusted for age, gender and vegetarian status, were tested by linear regression. The participants (n = 176,075) were predominantly female (70.4%), Australian (62.8%), and aged 18−24 years (27.7%), with 4.0% (n = 7087) repeat completers. Mean ± SD ARFS was 33.9 ± 9.4/73. Results indicate that ARFS was significantly lower among males and significantly higher with increasing age group, higher socio-economic status, in vegetarians, those who shared main meals with others, and those living in Australia (p-values < 0.001). Mean change in ARFS over time (2.3 ± 6.9) was significantly higher for those with lower baseline scores (p < 0.001). Publicly available, brief dietary assessment tools have the potential to improve diet quality at the population level.

Understanding eating behaviours, mental health and weight change in young adults: protocol paper for an international longitudinal study.

INTRODUCTION: Understanding the complexities of change in eating behaviours, mental health, well-being and weight is crucial to inform healthcare and service provision, particularly in light of the exacerbating effects of the COVID-19 pandemic. This study aims to address the need for more comprehensive cross-sectional and longitudinal evidence, by tracking eating behaviours, mental health, health related behaviours and weight over a 12-month period, in a sample of young adults (18-35 years) in the UK and Australia. METHODS AND ANALYSIS: Online surveys administered via the Prolific online research platform will be used for data collection at baseline, 6 months and 12 months. The survey (approximately 45 min) measures demographics, the impact of COVID-19, body mass index (BMI), weight management and health service usage, eating behaviours, personality, mental health, and health-related behaviours. An optional substudy component at each time point aims to validate self-reported weight in the main survey through images. Study inclusion criteria are; aged 18-34 years at baseline, BMI ≥20 kg/m2, and residing in the UK or Australia. A target of 500 participants at baseline was set, recruited through Prolific, and with recruitment stratified by BMI, sex and country. The proposed analyses include creating static predictive models using baseline data (eg, using latent class analysis, factor analysis or similar), and mapping changes longitudinally (eg, using multivariate regressions). These analyses will enable changes in the study measures to be identified, as well as predictors and outcomes of change. ETHICS AND DISSEMINATION: Ethical approval was granted by Leeds Beckett University, UK (reference number 86004) and the University of Newcastle, Australia (reference number H-2022-0110). Study findings will be disseminated through scientific journals, conferences, institute websites and social media, and briefings tailored to policy, practice and the public, with the intention to help inform the future development of health and well-being care and support for young adults across Australia and the UK.

Ultra-processed food intakes associated with 'food addiction' in young adults.

Exploring potentially addictive foods and food components is a recent research focus. Few studies have evaluated this based on level of food processing using the NOVA classification system. This study compared intakes of ultra-processed foods in young adults with and without food addiction. Secondary analysis of online cross-sectional survey data was conducted. The sample included 735 young Australian adults (18-35 years). Dietary intake was assessed by food frequency questionnaire and coded using NOVA to determine percentage energy (%E) from each of the four NOVA categories (unprocessed; processed culinary ingredients; processed; ultra-processed). Food addiction was assessed using the Yale Food Addiction Scale (YFAS). Linear regression models, adjusted for age, gender and body mass index (BMI), were developed to examine the association between %E from NOVA categories with food addiction status and number of symptoms. Sample mean age was 24.7 ± 4.2 years, 85% were female, 67% within healthy weight BMI range, and 20% classified as food addicted. Participants consumed 34.3 ± 13.4 %E from ultra-processed foods. Young adults classified as food addicted consumed a higher %E from ultra-processed foods (ß = 3.954, p = 0.002) and a lower %E from unprocessed foods (ß = -2.743, p = 0.010) than those classified as not food addicted. For each additional food addiction symptom reported, the %E from ultra-processed foods was higher (ß = 1.693, p < 0.001) and %E from unprocessed foods was lower (ß = -1.238, p < 0.001). Results demonstrate an association between YFAS assessed food addiction and higher intakes of ultra-processed foods, providing an important new perspective on the relationship between self-reported diet and food addiction in young adults. Future research should evaluate the relationship between food addiction, ultra-processed food intakes and health in longitudinal studies in order to inform potential treatment approaches.

Effectiveness of dietary interventions in mental health treatment: A rapid review of reviews.

AIM: This rapid review of reviews aimed to determine the extent of research undertaken on the effectiveness of dietary interventions for individuals with a mental disorder. METHODS: Three databases (MEDLINE, Embase, Cochrane Reviews and Cochrane Trials) were searched to February 2021 for systematic reviews including experimental studies assessing the effectiveness of dietary interventions with physical or mental health related outcomes in adults or children with one or more of: severe mental illness, depression or anxiety, eating disorders, or substance use disorder. Results are presented descriptively. RESULTS: The number of included reviews was 46 (67% in severe mental illness, 20% in depression and anxiety, 7% in eating disorders, and 7% in substance use disorders). Most reviews were published since 2016 (59%), and included studies conducted in adults (63%). Interventions in the eating disorders and severe mental illness reviews were predominantly education and behaviour change, whereas interventions in the substance use disorders, and depression and anxiety reviews were predominantly supplementation (e.g. omega-3). Twenty-eight and twelve of the reviews respectively reported mental health and dietary outcomes for one or more included studies. Most reviews in severe mental illness, and depression and anxiety reported conclusions supporting the positive effects of dietary intervention, including positive effects on weight-related or mental health outcomes, and on mental health outcomes, respectively. CONCLUSIONS: A larger number of systematic reviews were identified which evaluated dietary interventions in individuals with severe mental illness, and depression and anxiety, compared with substance use disorders, and eating disorders. Dietary intervention is an important component of the treatment that should be available to individuals living with mental disorders, to support their physical and mental health.

Designing an online intervention for adults with addictive eating: a qualitative integrated knowledge translation approach.

INTRODUCTION: Codesign is a meaningful end-user engagement in research design. The integrated knowledge translation (IKT) framework involves adopting a collaborative research approach to produce and apply knowledge to address real-world needs, resulting in useful and useable recommendations that will more likely be applied in policy and practice. In the field of food addiction (FA), there are limited treatment options that have been reported to show improvements in FA symptoms. OBJECTIVES: The primary aim of this paper is to describe the step-by-step codesign and refinement of a complex intervention delivered via telehealth for adults with FA using an IKT approach. The secondary aim is to describe our intervention in detail according to the TIDieR checklist. DESIGN: This study applies the IKT process and describes the codesign and refinement of an intervention through a series of online meetings, workshops and interviews. PARTICIPANTS: This study included researchers, clinicians, consumers and health professionals. PRIMARY OUTCOME MEASURE: The primary outcome was a refined intervention for use in adults with symptoms of FA for a research trial. RESULTS: A total of six female health professionals and five consumers (n=4 female) with lived overeating experience participated in two interviews lasting 60 min each. This process resulted in the identification of eight barriers and three facilitators to providing and receiving treatment for FA, eight components needed or missing from current treatments, telehealth as a feasible delivery platform, and refinement of key elements to ensure the intervention met the needs of both health professionals and possible patients. CONCLUSION: Using an IKT approach allowed for a range of viewpoints and enabled multiple professions and disciplines to engage in a semiformalised way to bring expertise to formulate a possible intervention for FA. Mapping the intervention plan to the TIDieR checklist for complex interventions, allowed for detailed description of the intervention and the identification of a number of areas that needed to be refined before development of the finalised intervention protocol.

Are health behaviors associated with academic performance among tertiary education students? A systematic review of cohort studies.

OBJECTIVE: To evaluate the association between health behaviors with academic performance among tertiary education students. METHODS: Six databases were searched until July 2020 for prospective cohort studies evaluating the association between health behavior(s) (dietary intake, physical activity, sedentary behavior, alcohol intake, sleep, smoking or illicit drug use) and academic performance. RESULTS: Thirty-four studies were included (18 assessed sleep, 16 alcohol intake, 12 illicit drug use, 10 physical activity, 8 diet, 4 smoking, 2 sedentary behavior). A consistent negative association with academic performance was demonstrated for sleep (12/18 studies), alcohol intake (13/16) and illicit drug use (9/12). Most (7/10) studies found no association between physical activity and academic performance. CONCLUSION: Findings suggest interventions to mitigate the influence of poor sleep, high alcohol intake, and illicit drug use on academic performance may be needed. Further research of other health behaviors, along with their co-occurrence, with academic performance, is required.