Dr Sasha Fenton

Background: Many young adults report poor diet quality. However, research evaluating whether young adult males and females differ in diet quality is limited. Additionally, although diet quality has a known inverse association with body mass index (BMI), it is unclear whether this association is observed in young adults and whether it varies by gender. The present study aimed to evaluate gender differences in diet quality in young adults, as well as the associations between diet quality and BMI. Methods: Data collected via the Healthy Eating Quiz (HEQ) in respondents aged 18¿35 years between July 2019 and December 2021 were analysed, including demographics, and diet quality calculated using the Australian Recommended Food Score (ARFS). Differences in characteristics were analysed using a two-sample t-test, chi-squared and one-way analysis of covariance. Linear regressions were performed to estimate associations between diet quality and BMI. An interaction term was included in the model to test differences between genders. Results: The respondents (n = 28,969) were predominantly female (70.8%) with a mean ± SD age of 25.9 ± 5.0 years and BMI of 24.6 ± 5.2 kg/m2. The mean ± SD ARFS was significantly different between females and males (33.1 ± 8.6 vs. 31.4 ± 9.3 points out of 70; p < 0.001). Diet quality had a small, significant inverse association with BMI in both genders. The interaction effect between diet quality score and gender in predicting BMI was significant (p < 0.001), suggesting the impact of diet quality on BMI varies by gender, with lower diet quality more strongly associated with higher BMI in females compared to males. Conclusion: Interventions that target young adults are needed to improve diet quality and its potential contribution to BMI status. As a result of the small observed effect sizes, caution should be applied in interpreting these findings.

Background: Massive Open Online Courses (MOOCs) can engage large numbers of learners. Understanding motivations for enrolling and elements that engage learners may help meet learner needs. This study explored motivations, intentions, recruitment methods and course acceptability of learners enrolled in 'The Science of Weight Loss: Dispelling diet myths' (SWL101X) MOOC on EdX. Design and setting: Cross-sectional analysis included 29,666 learners from 180+ countries. Methods: Learners provided demographic data, while 8,454 learners provided optional pre-course data and 987 provided post-course data. The pre-course survey examined learners' motivations and intentions and recruitment method, and the post-course survey examined acceptability of course content. Descriptive statistics were reported as frequencies and percentages or medians (interquartile range)/means (standard deviation). Results: Learners (61% women, 51% aged between 25 and 44 years) enrolled in the MOOCs mainly to increase their nutrition knowledge (46%) and/or lose weight (62%). Most (61%) were recruited through EdX platforms (website, newsletters and blog). Course components were well received by the majority who completed the post-course survey. Conclusion: The SWL101X MOOC successfully delivered nutrition education. Future courses could consider trialling the text, videos and interactive features to further engage learners. Short, informal 'talking head' video content may facilitate engagement. Future courses should also ensure the inclusion of the most recent dietary practices for health, and the management of obesity as a chronic disease, as some of the content used in the course in this study does not represent current and/or best practice. The greater use of social media may enhance learner enrolment.

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.

Background: Recent research has demonstrated an association between dietary intake and sleep health that can influence chronic disease risk factors. A scoping review of research studies investigating dietary intake and sleep was undertaken to determine the extent and scope of research in laboratory-based, free-living and mixed settings. Additionally, this review determines how well subpopulations and geographical locations are represented and the methodologies used to assess outcome measures. Methods: Five online databases were used to identify papers published between 1970 and 2017. Included studies were those conducted in adults and reported both outcomes of interest: (i) sleep health, including sleep restriction and sleep hygiene and (ii) dietary outcomes, including altered nutrients, dietary patterns and supplements. Results: In total, 129 publications were included with the majority¿being dietary interventions investigating sleep outcomes (n¿=¿109) with fewer¿being sleep interventions investigating and reporting dietary outcomes (n¿=¿20). Dietary interventions were most often carried out in free-living environments, in contrast to sleep interventions that were most often carried out in laboratory-based environments. The majority of dietary interventions investigated use of a supplement (n¿=¿66 studies), which was predominantly caffeine (n¿=¿49). Sleep interventions investigated sleep duration only, with the majority (n¿=¿17) investigating the effect of partial sleep restriction under 5.5¿h per night on dietary intake,¿while three studies investigating total sleep deprivation. Conclusions: Investigating broader aspects of dietary such as overall diet quality and dietary patterns and other components of sleep health such as quality, timing and sleep¿hygiene are important aspects for future research.