Efficacy of technology-based personalised feedback on diet quality in young Australian adults: results for the advice, ideas and motivation for my eating (Aim4Me) randomised controlled trial.

OBJECTIVE: Web-based dietary interventions could support healthy eating. The Advice, Ideas and Motivation for My Eating (Aim4Me) trial investigated the impact of three levels of personalised web-based dietary feedback on diet quality in young adults. Secondary aims were to investigate participant retention, engagement and satisfaction. DESIGN: Randomised controlled trial. SETTING: Web-based intervention for young adults living in Australia. PARTICIPANTS: 18-24-year-olds recruited across Australia were randomised to Group 1 (control: brief diet quality feedback), Group 2 (comprehensive feedback on nutritional adequacy + website nutrition resources) or Group 3 (30-min dietitian consultation + Group 2 elements). Australian Recommended Food Score (ARFS) was the primary outcome. The ARFS subscales and percentage energy from nutrient-rich foods (secondary outcomes) were analysed at 3, 6 and 12 months using generalised linear mixed models. Engagement was measured with usage statistics and satisfaction with a process evaluation questionnaire. RESULTS: Participants (n 1005, 85 % female, mean age 21·7 ± 2·0 years) were randomised to Group 1 (n 343), Group 2 (n 325) and Group 3 (n 337). Overall, 32 (3 %), 88 (9 %) and 141 (14 %) participants were retained at 3, 6 and 12 months, respectively. Only fifty-two participants (15 % of Group 3) completed the dietitian consultation. No significant group-by-time interactions were observed (P > 0·05). The proportion of participants who visited the thirteen website pages ranged from 0·6 % to 75 %. Half (Group 2 = 53 %, Group 3 = 52 %) of participants who completed the process evaluation (Group 2, n 111; Group 3, n 90) were satisfied with the programme. CONCLUSION: Recruiting and retaining young adults in web-based dietary interventions are challenging. Future research should consider ways to optimise these interventions, including co-design methods.

Do disparities exist between national food group recommendations and the dietary intakes of contemporary young adults?

AIM: The aim of this study was to compare food and nutrient intakes of young Australian adults (18-24 years) to national recommendations as per the Australian Guide to Healthy Eating and Nutrient Reference Values. METHODS: Dietary intake of 18 to 24 year olds (n = 1005) participating in the Advice, Ideas, and Motivation for My Eating (Aim4Me) study was self-reported using the 120-item Australian Eating Survey Food Frequency Questionnaire. Median daily servings of Australian Guide to Healthy Eating food groups, macronutrients and micronutrients were compared to recommendations in the Australian Guide to Healthy Eating and Nutrient Reference Values using t-tests or Kruskal-Wallis tests (P < .05). RESULTS: None of the young adults met all Australian Guide to Healthy Eating recommendations. The highest adherence [% meeting recommendations, median (IQR)] was for meat/alternatives [38%, 2.1(1.8)] and fruit [32%, 1.5(1.6)], with <25% meeting remaining food-group recommendations. The majority (76%) exceeded recommendations for the consumption of discretionary foods [4.0(3.3) vs 0-3 serves] and 81% had excessive saturated fat intakes. Young adults who met all key Nutrient Reference Values (dietary fibre, folate, iodine, iron, calcium and zinc) (18%) consumed a higher number of serves of all food groups, including discretionary foods. CONCLUSIONS: Dietary intakes of contemporary young adults do not align with Australian Guide to Healthy Eating targets, while meeting Nutrient Reference Values is achieved by a higher consumption of all food groups, including discretionary foods. Strategies to increase consumption of nutrient-dense foods in young adults to achieve the Nutrient Reference Values are warranted.

Investigating the Efficacy and Cost-Effectiveness of Technology-Delivered Personalized Feedback on Dietary Patterns in Young Australian Adults in the Advice, Ideas, and Motivation for My Eating (Aim4Me) Study: Protocol for a Randomized Controlled Trial.

BACKGROUND: Web-based health interventions may be easier to access and time efficient relative to face-to-face interventions and therefore may be the most appropriate mode to engage young adults. OBJECTIVE: This study aims to investigate the impact of 3 different levels of personalized web-based dietary feedback and support on changes in diet quality. METHODS: The Advice, Ideas, and Motivation for My Eating (Aim4Me) study is a 12-month assessor-blinded, parallel-group randomized controlled trial evaluating the impact of 3 levels of web-based feedback on diet quality, measured using the Australian Recommended Food Score (ARFS). Participants (N=2570) will primarily be recruited via web-based methods and randomized to 1 of 3 groups. Group 1 (control) will receive the Healthy Eating Quiz, a web-based dietary assessment tool that generates a brief feedback report on diet quality. Individuals randomized to this group can use the brief feedback report to make positive dietary changes. Group 2 will receive the Australian Eating Survey, a web-based dietary assessment tool that generates a comprehensive feedback report on diet quality as well as macro- and micronutrient intake. Group 2 will use the comprehensive feedback report to assist in making positive dietary changes. They will also have access to the Aim4Me website with resources on healthy eating and tools to set goals and self-monitor progress. Group 3 will receive the same intervention as Group 2 (ie, the comprehensive feedback report) in addition to a tailored 30-min video consultation with an accredited practicing dietitian who will use the comprehensive feedback report to assist individuals in making positive dietary changes. The self-determination theory was used as the framework for selecting appropriate website features, including goal setting and self-monitoring. The primary outcome measure is change in diet quality. The completion of questionnaires at baseline and 3, 6, and 12 months will be incentivized with a monetary prize draw. RESULTS: As of December 2019, 1277 participants have been randomized. CONCLUSIONS: The web-based delivery of nutrition interventions has the potential to improve dietary intake of young adults. However, the level of support required to improve intake is unknown. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12618000325202; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=374420. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/15999.

Which behaviour change techniques within interventions to prevent weight gain and/or initiate weight loss improve adiposity outcomes in young adults? A systematic review and meta-analysis of randomized controlled trials.

Young adulthood is associated with the highest rate of weight gain compared with any other adult age group. This review evaluates the effectiveness of interventions with adiposity outcomes among young adults and identifies which behaviour change techniques (BCTs) are most effective. BCT utilization was assessed using Michie's 93-item BCT Taxonomy v1. Six electronic databases were searched for randomized controlled trials assessing change in adiposity in young adults (17-35 years) until December 2019; identifying 21,582 articles. Fifty-one studies were included. Meta-analyses for weight (n=19 studies), body mass index (BMI) (n=20 studies), and waist circumference (n=10 studies) demonstrated no significant between-group differences at ≤3 or >3 months. There were no differences between interventions focusing on weight loss or weight-gain prevention. Narrative synthesis showed significant between-group differences in weight change, favouring the intervention in 14/43 (33%) studies. In studies assessing BMI and waist circumference, this was 31% (11/36) and 25% (4/16). Two BCTs had a percentage effectiveness ratio >50% in weight loss interventions; social support (unspecified) and self-monitoring behaviour, and one in weight-gain prevention interventions; and goal-setting (outcome). Findings demonstrate initial potential for these types of BCTs and can help build cumulative evidence towards delivering effective, cost-efficient, and replicable interventions.

Determinants of eating behaviours in Australian university students: A cross-sectional analysis.

AIM: This study aimed to explore clustering among individual eating behaviours in a sample of Australian university students, and explore associations between clustered eating behaviours and demographic characteristics. METHODS: A cross-sectional analysis of data from the University of Newcastle (UON) Student Healthy Lifestyle Survey 2017 was conducted. Measures included eating behaviours (eg, vegetables, energy-dense nutrient poor [EDNP] food intakes) assessed using short diet questions, and demographic characteristics (eg, age, undergraduate/postgraduate student). Factor analysis was used to explore clustering of individual eating behaviours (ie, identify factors). Linear regression models were used to explore associations between eating behaviour factors identified and demographic characteristics. RESULTS: A total of 3062 students (70% female; 56% aged 17-24 years) were included in the analysis. The six eating behaviour factors identified (characterised by higher consumption of the named foods/drinks) were; EDNP snack foods, meat and takeaway foods, fruit and vegetables, sugary drinks, breakfast, and breads and cereals. A higher fruit and vegetable factor score was associated with being female (P < .001), and a higher meat and takeaway foods factor score was associated with being male (P < .001) and of younger age (P < .001). CONCLUSIONS: Nutrient-rich foods clustered together and EDNP foods clustered together, that is, the identified factors represent either nutrient-rich or EDNP foods. Interventions in the university setting should target students with the poorest eating behaviours, including males and younger students.

Predictors of Food Insecurity among Australian University Students: A Cross-Sectional Study.

Food insecurity is much higher among university students than the general population, and is linked with poorer mental health, diet and academic achievement. The aim of this study was to explore the level of food insecurity among a sample of Australian university students and determine which socio-demographic and student characteristics predict food insecurity. An online cross-sectional survey with students from the University of Newcastle, Australia was conducted in 2017-2018. Food insecurity was assessed using the 6-item US Department of Agriculture Food Security Survey Module, and socio-demographic (e.g., age, living situation) and student characteristics (e.g., undergraduate/postgraduate student) were captured. Multivariate logistic regression was used to determine the odds of food insecurity for each of the socio-demographic and student characteristics, and included characteristics of significance in bivariate analyses as potential confounders. Data for 366 students were analysed (mean age 27.3 ± 10.4 years, 27.3% male). Forty-eight percent of participants were food insecure. The odds of food insecurity were higher among students living in rental accommodation compared with their parents' home (OR = 2.39, 95% CI 1.41, 4.06), and undergraduate compared with postgraduate students (OR = 3.50, 95% CI 1.83, 6.69). Commencing university and moving away from parents may be key times for intervention. Strategies that can provide longstanding benefit are needed to address the high level of food insecurity among university students.

Image-Based Dietary Assessment and Tailored Feedback Using Mobile Technology: Mediating Behavior Change in Young Adults.

Assessing the implementation of nutrition interventions is important to identify characteristics and dietary patterns of individuals who benefit most. The aim was to report on young adults' experiences of receiving dietary feedback text messaging intervention. Diet was captured using an image-based 4-day mobile food recordTM application (mFRTM) and assessed to formulate two tailored feedback text messages on fruit and vegetables and energy-dense nutrient-poor (EDNP) foods and beverages. At 6-months 143 participants completed a second mFRTM and a questionnaire evaluating the dietary feedback. Participants who agreed the text messages made them think about how much vegetables they ate were more likely to increase their intake by at least half a serve than those who disagreed [odds ratio (OR) = 4.28, 95% Confidence Interval (CI): 1.76 to 10.39]. Those who agreed the text messages made them think about how much EDNP foods they ate, were twice as likely to decrease their intake by over half a serve (OR = 2.39, 95%CI: 1.12 to 5.25) than those who disagreed. Undertaking detailed dietary assessment ensured the tailored feedback was constructive and relevant. Personal contemplation about vegetable and EDNP food intake appears to be a mediator of dietary change in young adults.

Cost evaluation of providing evidence-based dietetic services for weight management in adults: In-person versus eHealth delivery.

AIM: To compare the theoretical costs of best-practice weight management delivered by dietitians in a traditional, in-person setting compared to remote consultations delivered using eHealth technologies. METHODS: Using national guidelines, a framework was developed outlining dietitian-delivered weight management for in-person and eHealth delivery modes. This framework mapped one-on-one patient-dietitian consultations for an adult requiring active management (BMI ≥ 30 kg/m2 ) over a one-year period using both delivery modes. Resources required for both the dietitian and patient to implement each treatment mode were identified, with costs attributed for material, fixed, travel and personnel components. The resource costs were categorised as either establishment or recurring costs associated with the treatment of one patient. RESULTS: Establishment costs were higher for eHealth compared to in-person costs ($1394.21 vs $90.05). Excluding establishment costs, the total (combined dietitian and patient) cost for one patient receiving best-practice weight management for 12 months was $560.59 for in-person delivery, compared to $389.78 for eHealth delivery. Compared to the eHealth mode, a higher proportion of the overall recurring delivery costs was attributed to the patient for the in-person mode (46.4% and 33.9%, respectively). CONCLUSIONS: Although it is initially more expensive to establish an eHealth service mode, the overall reoccurring costs per patient for delivery of best-practice weight management were lower compared to the in-person mode. This theoretical cost evaluation establishes preliminary evidence to support alternative obesity management service models using eHealth technologies. Further research is required to determine the feasibility, efficacy and cost-effectiveness of these models within dietetic practice.

Public, official, and industry submissions on a Bill to increase the alcohol minimum purchasing age: A critical analysis.

BACKGROUND: In 2005 a Bill was introduced to the New Zealand parliament to increase the alcohol minimum purchasing age (MPA) from 18 to 20 years and submissions were invited from interested parties. We sought to characterise and critique the arguments tendered for and against the proposal. METHODS: We used template analysis to study written submissions on the Bill from 178 people and organisations in New Zealand. Independent raters coded submissions according to the source, whether for or opposed, and the arguments employed. RESULTS: The most common sources of submissions were members of the public (28%), the alcohol industry (20%), and NGOs (20%). Overall, 40% opposed increasing the MPA, 40% were in favour, 4% supported a split MPA (18 years for on-premise, 20 years for off-premise), 7% were equivocal, and 8% offered no comment. The most common proponents of increasing the MPA were NGOs (36%) and members of the public (30%) and their arguments concerned the expected positive effects on public health (36%) and public disorder/property damage (16%), while 24% argued that other strategies should be used as well. The most common sources of opposition to increasing the MPA were the alcohol industry (50%) and the public (20%). It was commonly claimed that the proposed law change would be ineffective in reducing harm (22%), that other strategies should be used instead (16%), that it would infringe adult rights (15%), and that licensed premises are safe environments for young people (14%). There were noteworthy examples of NGOs and government agencies opposing the law change. The alcohol industry maximised its impact via multiple submissions appealing to individual rights while neglecting to report or accurately characterise the scientific evidence. Several health and welfare agencies presented confused logic and/or were selective in their use of scientific evidence. CONCLUSION: In contrast to the fragmented and inconsistent response from government and NGOs, the alcohol industry was organised and united, with multiple submissions from the sector with most at stake, namely the hospitality industry, and supporting submissions from the manufacturing, import, and wholesale sectors. Systematic reviews of research evidence should be routinely undertaken to guide the legislature and submissions should be categorised on the basis of pecuniary interest.