Higher scores obtained using diet quality and variety indices are indicators of more optimal food and nutrient intakes and lower chronic disease risk. The aim of this paper is to describe the overall diet quality and variety in a sample of Australian adults who completed an online diet quality self-assessment tool, the Healthy Eating Quiz. The Healthy Eating Quiz takes approximately five minutes to complete online and computes user responses into a total diet quality score (out of a maximum of 73 points) and then categorizes them into the following groups: ‘needs work’ (<33), ‘getting there’ (33–38), ‘excellent’ (39–46), or ’outstanding’ (47+). There was a total of 93,252 first-time respondents, of which 76% were female. Over 80% of respondents were between 16–44 years of age. The mean total score was 34.1 ± 9.7 points. Females had a higher total score than males (p < 0.001) and vegetarians had higher total scores than non-vegetarians (p < 0.001). Healthy eating quiz scores were higher in those aged 45–75 years compared to 16–44 years (p < 0.001). When comparing Socioeconomic Indices for Areas deciles, those most disadvantaged had a lower total score than those least disadvantaged (p < 0.001). Repeat measures showed that those who scored lowest (needs work) in their first completion increased their total score by 3.2 ± 7.4 at their second completion (p < 0.001). While the Healthy Eating Quiz data indicates that individuals receiving feedback on how to improve their score can improve their diet quality, there is a need for further nutrition promotion interventions in Australian adults.

Background: Changing people’s behaviour by giving advice and instruction, as traditionally provided in healthcare consultations, is usually ineffective. Healthy Conversation Skills (HCS) training enhances health professionals’ communication skills and ability to empower and motivate people in health behaviour change. Guided by the Theoretical Domains Framework (TDF), this study examined the impact of HCS training on health professional barriers to conducting behaviour change conversations in both clinical and non-clinical settings. Secondary aims were to i) identify health professionals’ barriers to having behaviour change conversations, and explore the ii) effect of HCS training on health professionals’ competence and attitudes to adopting HCS, iii) feasibility, acceptability and appropriateness of using HCS in their clinical and non-clinical roles, and iv) acceptability and quality of HCS training.Methods: HCS training was conducted in October-November 2019 and February 2020. Pre-training (T1), post-training (T2) and follow-up (T3; 6-10 weeks post-training) surveys collected data on demographics and changes in competence, confidence, importance and usefulness (10-point Likert scale, where 10 = highest score) of conducting behaviour change conversations. Validated items assessing barriers to having these conversations were based on eight TDF domains. Post-training acceptability and quality of training was assessed. Data were summarised using descriptive statistics, and differences between TDF domain scores at the specific time points were analysed using Wilcoxon matched-pairs signed-rank tests.Results: Sixty-four participants consented to complete surveys (97% women; 16% identified as Aboriginal), with 37 employed in clinical settings and 27 in non-clinical settings. The training improved scores for the TDF domains of skills (T1: median (interquartile range) = 4.7(3.3-5.3); T3 = 5.7(5.3-6.0),p < 0.01), belief about capabilities (T1 = 4.7(3.3-6.0); T3 = 5.7(5.0-6.0),p < 0.01), and goals (T1 = 4.3(3.7-5.0); T3 = 4.7(4.3-5.3), p < 0.01) at follow-up. Competence in using ‘open discovery questions’ increased post-training (T1 = 25% of responses; T2 = 96% of responses; T3 = 87% of responses,p < 0.001), as did participants’ confidence for having behaviour change conversations (T1 = 6.0(4.7-7.6); T2 = 8.1(7.1-8.8),p < 0.001), including an increased confidence in having behaviour change conversations with Aboriginal clients (T1 = 5.0(2.7-6.3); T2 = 7.6(6.4-8.3),p < 0.001).Conclusions: Provision of additional support strategies to address intentions; memory, attention and decision processes; and behavioural regulation may enhance adoption and maintenance of HCS in routine practice. Wider implementation of HCS training could be an effective strategy to building capacity and support health professionals to use a person-centred, opportunistic approach to health behaviour change.

Diet quality indices can predict nutritional adequacy of usual intake, but validity should be determined. The aim was to assess the validity of total and sub-scale score within the Australian Recommended Food Score (ARFS), in relation to fasting plasma carotenoid concentrations. Diet quality and fasting plasma carotenoid concentrations were assessed in 99 overweight and obese adults (49.5% female, aged 44.6 ± 9.9 years) at baseline and after three months (198 paired observations). Associations were assessed using Spearman’s correlation coefficients and regression analysis, and agreement using weighted kappa (K_w). Small, significantly positive correlations were found between total ARFS and plasma concentrations of total carotenoids (r = 0.17, p < 0.05), β-cryptoxanthin (r = 0.18, p < 0.05), β-carotene (r = 0.20, p < 0.01), and α-carotene (r = 0.19, p < 0.01). Significant agreement between ARFS categories and plasma carotenoid concentrations was found for total carotenoids (K_w 0.12, p = 0.02), β-carotene (K_w 0.14, p < 0.01), and α-carotene (K_w 0.13, p < 0.01). In fully-adjusted regression models the only signification association with ARFS total score was for α-carotene (β = 0.19, p < 0.01), while ARFS meat and fruit sub-scales demonstrated significant relationships with α-carotene, β-carotene, and total carotenoids (p < 0.05). The weak associations highlight the issues with self-reporting dietary intakes in overweight and obese populations. Further research is required to evaluate the use of the ARFS in more diverse populations.

The maternal diet influences the long-term health status of both mother and offspring. The current study aimed to compare dietary intakes of pregnant women compared to food and nutrient recommendations in the Australian Guide to Healthy Eating (AGHE) and Nutrient Reference Values (NRVs). Usual dietary intake was assessed in a sample of women in their 3rd trimester of pregnancy attending antenatal outpatient clinics at John Hunter Hospital, Newcastle, New South Wales (NSW). Dietary intake was measured using the Australian Eating Survey, a validated, semi-quantitative 120-item food frequency questionnaire. Daily food group servings and nutrient intakes were compared to AGHE and NRV targets. Of 534 women participating, none met the AGHE recommendations for all food groups. Highest adherence was for fruit serves (38%), and lowest for breads and cereals (0.6%). Only four women met the pregnancy NRVs for folate, iron, calcium, zinc and fibre from food alone. Current dietary intakes of Australian women during pregnancy do not align with national nutrition guidelines. This highlights the importance of routine vitamin and mineral supplementation during pregnancy, as intakes from diet alone may commonly be inadequate. Future revisions of dietary guidelines and pregnancy nutrition recommendations should consider current dietary patterns. Pregnant women currently need more support to optimise food and nutrient intakes.

Aims: Secondary prevention reduces coronary heart disease (CHD) progression. Traditional prevention programs including cardiac rehabilitation are under-accessed, which smartphone apps may overcome. To evaluate the effect of a game-based mobile app intervention (MyHeartMate) to improve cardiovascular risk factors and lifestyle behaviours. Methods and results: Single-blind randomized trial of CHD patients in Sydney, 2017–2021. Intervention group were provided the MyHeartMate app for 6 months. Co-designed features included an avatar of the patient’s heart and tokens earned by risk factor work (tracking, challenges, and quizzes). The control group received usual care. Primary outcome was self-reported physical activity [metabolic equivalents (METs), Global Physical Activity Questionnaire] and secondary outcomes included lipid levels, blood pressure (BP), body mass index, and smoking. Pre-specified sample size was achieved (n = 390), age 61.2 ± 11.5 years; 82.5% men and 9.2% current smokers. At 6 months, adjusted for baseline levels, the intervention group achieved more physical activity than control (median difference 329 MET mins/wk), which was not statistically significant (95% CI −37.4, 696; P = 0.064). No differences occurred between groups on secondary outcomes except for lower triglyceride levels in the intervention [mean difference −0.3 (95% CI −0.5, −0.1 mmoL/L, P = 0.004)]. Acceptability was high: 94.8% of intervention participants engaged by tracking exercise or BP and completing missions; 26.8% continued to engage for ≥30 days. Participants (n = 14) reported the app supported tracking behaviours and risk factors, reinforcing and improving self-care confidence, and decreasing anxiety. Conclusion: A game-based app proved highly acceptable for patients with CHD but did not improve risk factors or lifestyle behaviours other than triglyceride levels.