Dr Lee Ashton

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.

Overweight and obesity has reach pandemic levels, with two-thirds (67%) of adult Australians classified as overweight or obese. As two of the most significant behavioral risk factors for obesity are modifiable (diet and exercise), there exists an opportunity for treatment through workplace health promotion initiatives. As one of Australia's largest industries with its own unique workplace factors, the mining industry has previously reported higher than population levels of overweight and obesity. This represented an opportune setting to test the RESHAPE workplace wellness program. RESHAPE is an eight-step framework (based on the WHO 'Health Workplace Framework and Model') which aims to provide a sustained approach to wellness in the workplace. This paper presents baseline findings from a pilot study that aimed to implement RESHAPE at three mine sites in NSW, Australia, and investigates the issue of overweight and obesity in the coal mining industry. Across three mine sites, 949 coal miners were examined cross-sectionally on a range of workplace, wellness, health, diet, and exercise factors using a paper-based survey. This was a predominantly male sample (90.4%) with the majority (59.2%) of participants aged 25-44 years. Selfreported height and weight measures indicated that less than 20 percent (18.9%) of participants were in a healthy BMI range, while there were effectively equal numbers of overweight (40.9%) and obese (39.1%) participants. Only 3.5% of participants met the daily recommendation for vegetables (5 serves) and shift-workers had greater association with elevated BMI compared to non-shift workers (B = 1.21, 95% CI: 0.23, 2.20, p = 0.016). Poor nutrition is likely to be a key component in elevated levels of overweight and obesity within this industry, with workplace factors compounding challenges workers face in implementing health behavior change. Future studies would benefit from assessing diet and physical activity knowledge in relation to recommendations and serving sizes.

Objective: To describe strategies used to recruit and retain young adults in nutrition, physical activity and/or obesity intervention studies, and quantify the success and efficiency of these strategies. Design: A systematic review was conducted. The search included six electronic databases to identify RCTs published up to 6th December 2019 that evaluated nutrition, physical activity and/or obesity interventions in young adults (17-35 years). Recruitment was considered successful if the pre-determined sample size goal was met. Retention was considered acceptable if =80% retained for =6-month follow-up or =70% for >6-month follow-up. Results: From 21,582 manuscripts identified, 107 RCTs were included. Universities were the most common recruitment setting used in 84 studies (79%). Less than half (46%) the studies provided sufficient information to evaluate whether individual recruitment strategies met sample size goals, with 77% successfully achieving recruitment targets. Reporting for retention was slightly better with 69% of studies providing sufficient information to determine whether individual retention strategies achieved adequate retention rates. Of these, 65% had adequate retention. Conclusions: This review highlights poor reporting of recruitment and retention information across trials. Findings may not be applicable outside a university setting. Guidance on how to improve reporting practices to optimise recruitment and retention strategies within young adults could assist researchers in improving outcomes.

Background & aims: A brief assessment tool on frequency and variety of fruit and vegetable intake could provide a cost-effective and sustainable approach to improving diet. The primary aim was to evaluate the comparative validity of a brief index of Fruit And Vegetable VAriety (FAVVA) relative to food and nutrient intakes derived from a comprehensive food frequency questionnaire (FFQ). The secondary aim was to evaluate the FAVVA index in relation to fasting plasma carotenoid concentrations. Methods: Dietary intakes and fasting plasma carotenoid concentrations of 99 overweight and obese adults (49.5% female; 44.6 ± 9.9 years) were assessed at baseline and 3-months. Food and nutrient intakes were assessed using the Australian Eating Survey (AES) FFQ. The FAVVA index was derived from a sub-set of 35 AES questions related to fruit and vegetable intake frequency and variety. Associations were assessed using Spearman's correlation coefficients and linear regression analysis, and agreement using weighted kappa (K w ). Results: Total FAVVA score demonstrated moderate to strong, significant (all p < 0.01) correlations with total daily intakes of vegetables (r = 0.75), vitamin C (r = 0.71), fruit (r = 0.66), vitamin A (r = 0.49), fibre (r = 0.49), potassium (r = 0.46), magnesium (r = 0.39), iron (r = 0.26), riboflavin (r = 0.24), calcium (r = 0.23), zinc (r = 0.20) and niacin equivalent (r = 0.20). These associations remained significant in the adjusted regression analyses and agreement testing. Total FAVVA was significantly correlated with plasma carotenoid concentrations (µg/dL) of a¿carotene (r = 0.22, p < 0.01), ß¿carotene (r = 0.26, p < 0.001), ß¿cryptoxanthin (r = 0.22, p < 0.01) and total carotenoids (r = 0.18, p < 0.05). The associations with a¿carotene (ß = 0.09, p < 0.001), ß¿carotene (ß = 0.42, p < 0.05) and total plasma carotenoids (ß = 0.85, p < 0.05) remained significant in the adjusted regression analyses and for agreement testing. Conclusions: FAVVA is suitable as a brief tool to rank frequency and variety of fruit and vegetable intake.

Brief interventions are effective in improving health behaviours including alcohol intake, however the effectiveness of brief interventions targeting nutrition outcomes has not been determined. The aim of this systematic review was to determine the effectiveness of brief nutrition interventions in adults. Seven databases were searched for RCT/pseudo RCT studies published in English to April 2016, and evaluating brief interventions (i.e. single point of contact) designed to promote change in eating behaviours in healthy adults (=18 years). Of 4849 articles identified, 45 studies met inclusion criteria. Most studies targeted fruit and/or vegetable intake (n = 21) or fat intake (n = 10), and few targeted diet quality (n = 2). Median follow-up was 3.5 months, with few studies (n = 4) measuring longer-term outcomes (=12 months). Studies aimed to determine whether a brief intervention was more effective than another brief intervention (n = 30), and/or more effective than no intervention (n = 20), with 17 and 11 studies, respectively, reporting findings to that effect. Interventions providing education plus tailored or instructional components (e.g. feedback) were more effective than education alone or non-tailored advice. This review suggests that brief interventions, which are tailored and instructional, can improve short-term dietary behaviours, however evidence for longer-term behaviour change maintenance is limited.

Young adult men are under-represented in health research, and little is known about how to reach and engage them in lifestyle interventions. This mixed-methods study aimed to explore young males¿ preferences for recruitment strategies, content, format (delivery mode and program duration and frequency), and facilitator characteristics for future physical activity and nutrition interventions. Ten focus groups involving 61 men (aged 18¿25 years) in the Hunter region, New South Wales, Australia and an online survey distributed within Australia were completed by 282 males (aged 18¿25 years). Key focus group themes included a preference for recruitment via multiple sources, ensuring images and recruiters were relatable; intervention facilitators to be engaging and refrain from discussing negative consequences of being unhealthy. Key program content preferences included skill development and individualized goals and feedback. Focus groups and the survey confirmed a preference for multiple delivery modes, including; face-to-face (group and individual), with support using eHealth technologies. Survey results confirmed the most favored program content as: ¿healthy eating on a budget,¿ ¿quick and easy meals,¿ and ¿resistance training.¿ Focus group responses suggested a program duration of =6 months, with 2¿3 combined face-to-face and supportive eHealth sessions per week. Survey intervention duration preference was 3 months with 4 face-to-face sessions per month. Findings can guide the design, conduct, and evaluation of relevant contemporary physical activity and or nutrition interventions for young men. There is a need to identify the most effective ways to address young men¿s individual preferences in intervention research.

Many Australian young men (18-25 years) fail to meet recommendations in national dietary or physical activity (PA) guidelines. However, there is a lack of understanding of their perspectives on PA and diet to inform intervention design. This study examined young men¿s motivators and barriers to healthy eating and PA, along with differences by demographic and behavioral factors. A cross-sectional online survey was completed by 282 men aged 18 to 25 years in Australia. Results identified the most common motivators for healthy eating included improving health (63.5%), body image (52.3%), and increasing energy (32.1%). Motivators for PA included improving body image (44.6%), fitness (44.2%), and health (41.0%). Common barriers to healthy eating were access to unhealthy foods (61.1%), time to cook/prepare healthy foods (55.0%), and motivation to cook healthy foods (50.7%). Barriers for PA included motivation (66.3%), time (57.8%), and cost of equipment/facilities (33.3%). Significant differences (p <.01) in motivators to healthy eating and/or PA were identified for BMI category, marital status, PA level, alcohol intake, and stress levels. Significant differences were identified for barriers to healthy eating and/or PA by BMI, PA level, stress, and fruit and vegetable intake, assessed using Pearson¿s chi-square test. Findings suggest that promotion of benefits related to health, appearance/body image, increased energy and fitness, and addressing key barriers including motivation, time, financial restraints, and accessibility of unhealthy foods, could engage young men in improving lifestyle behaviors. Differences by demographic and behavioral factors suggest development of tailored programs to address diversity among young men may be required.

A systematic review of randomized control trials (RCT) was undertaken to evaluate the effectiveness of eHealth behavioral interventions aiming to improve smoking rates, nutrition behaviors, alcohol intake, physical activity levels and/or obesity (SNAPO) in young adults. Seven electronic databases were searched for RCTs published in English from 2000 to April 2015 and evaluating eHealth interventions aiming to change one or multiple SNAPO outcomes, and including young adult (18¿35¿years) participants. Of 2,159 articles identified, 45 studies met the inclusion criteria. Most interventions targeted alcohol (n¿=¿26), followed by smoking (n¿=¿7), physical activity (n¿=¿4), obesity (n¿=¿4) and nutrition (n¿=¿1). Three interventions targeted multiple behaviors. The eHealth interventions were most often delivered via websites (79.5%). Most studies (n¿=¿32) compared eHealth interventions to a control group (e.g. waiting list control, minimal intervention), with the majority (n¿=¿23) showing a positive effect on a SNAPO outcome at follow-up. Meta-analysis demonstrated a significantly lower mean number of drinks consumed/week in brief web or computer-based interventions compared to controls (Mean Difference -¿2.43 [-¿3.54, -¿1.32], P¿<¿0.0001, n¿=¿10). Sixteen studies compared eHealth delivery modes, with inconsistent results across target behaviors and technology types. Nine studies compared eHealth to other modes of delivery (e.g. in person) with all finding no difference in SNAPO outcomes between groups at follow-up. This review provides some evidence for the efficacy of eHealth SNAPO interventions for young adults, particularly in the short-term and for alcohol interventions. But there is insufficient evidence for their efficacy in the longer-term, as well as which mode of delivery is most effective.

Objectives: To investigate the effectiveness of Smoking, Nutrition, Alcohol, Physical activity and Obesity (SNAPO) interventions in young men exclusively. The secondary aim was to evaluate the recruitment, retention and engagement strategies. Methods: A search with no date restrictions was conducted across seven databases. Randomized controlled trials recruiting young men only (aged 18-35. years) into interventions targeting any SNAPO risk factors were included. Results: Ten studies were included (two nutrition, six alcohol use, two targeting multiple SNAPO risk factors). Six studies (two nutrition, three alcohol use and one targeting multiple SNAPO risk factors) demonstrated significant positive short-term intervention effects, but impact was either not assessed beyond the intervention (n = 3), had short-term follow-up (= 6 months) (n = 2) or not sustained beyond six months (n = 1). Overall, a high risk of bias was identified across studies. Only one study undertook a power calculation and recruited the required sample size. Adequate retention was achieved in three studies. Effectiveness of engagement strategies was not reported in any studies. Conclusions: Despite preliminary evidence of short-term effectiveness of SNAPO interventions in young men, few studies characterized by a high risk of bias were identified. High quality SNAPO interventions for young men are warranted.

Background: Existing systematic reviews aimed at comparing effectiveness of childhood obesity treatment interventions are limited by a lack of quality in the conduct and reporting of trials in this area. This study aimed to identify the number and types of primary and secondary outcomes used within trials of childhood obesity treatments and to determine the degree to which these trials correctly report their use of outcome measures. A systematic literature review was conducted to identify phase II (i.e. pilot and feasibility studies) and phase III (e.g. determining effectiveness) trials of childhood obesity treatments across 11 databases. Data were extracted from eligible manuscripts pertaining to the number and type of outcome measures used, in addition to details of citations provided for these measures. Results: 145 different outcome measures were reported to be used within 200 identified eligible trial manuscripts. Citations were provided to indicate the provenance for 417 measures, but only 13% of these were correctly linked to papers describing the development and/or evaluation of measures. Conclusions: This study identified inconsistencies and inaccuracies in the use and reporting of outcome measures used by eligible trials. Researchers in this area are urged to consider guidelines such as CONSORT and the National Obesity Observatory Standard Evaluation Framework in the design and reporting of future trials.