Dietary Intake, Cost, and Affordability by Socioeconomic Group in Australia

Few Australians consume diets consistent with the Australian Dietary Guidelines. A major problem is high intake of discretionary food and drinks (those not needed for health and high in saturated fat, added sugar, salt and/or alcohol). Low socioeconomic groups (SEGs) suffer particularly poor diet-related health. Surprisingly, detailed quantitative dietary data across SEGs was lacking. Analysis of the most recent national nutrition survey data produced habitual intakes of a reference household (two adults and two children) in SEG quintiles of household income. Cost and affordability of habitual and recommended diets for the reference household were determined using methods based on the Healthy Diets Australian Standardised Affordability and Pricing protocol. Low SEGs reported significantly lower intakes of healthy food and drinks yet similarly high intakes of discretionary choices to high SEGs (435 serves/fortnight). Total habitual diets of low SEGs cost significantly less than those of high SEGs (AU$751/fortnight to AU$853/fortnight). Results confirmed low SEGs cannot afford a healthy diet. Lower intakes of healthy choices in low SEGs may help explain their higher rates of diet-related disease compared to higher SEGs. The findings can inform potential policy actions to improve affordability of healthy foods and help drive healthier diets for all Australians.

Diet Quality of Australian Children and Adolescents on Weekdays versus Weekend Days: A Secondary Analysis of the National Nutrition and Physical Activity Survey 2011–2012

Daily routines may influence children and adolescents’ eating patterns, however the influence of days of the week on dietary intake has rarely been explored. This study aimed to examine discretionary choices intake in the context of diet quality on weekdays versus weekends. A secondary analysis was conducted using the Australian National Nutrition and Physical Activity Survey 2011–2012. Differences in discretionary choices intake and diet quality on weekdays versus weekends, were examined using ANCOVA analyses. Associations between child and parent-proxy characteristics and weekday/weekend discretionary choices intake were examined using multivariable regression models. Primary analyses included 2584 Australian 2–17-year-olds. There were small differences in discretionary choices intake and diet quality between weekdays and weekends in all age subgroups. Compared to weekdays, intakes on weekends were characterized by a higher intake of discretionary choices, and lower total Dietary Guidelines Index for Children and Adolescents (DGI-CA) scores across the age subgroups (all p < 0.01). Parent-proxy discretionary choices intake and child age were predictors of weekday and weekend discretionary choices intake. Parent-proxy obesity weight status compared with healthy weight status was a predictor of weekend intake, while parent-proxy education level was a predictor of weekday discretionary choices intake. Future intervention strategies should target discretionary choices intake on both weekdays and weekends.

The food and nutrient intake of 5- to 12-year-old Australian children during school hours: a secondary analysis of the 2011–2012 National Nutrition and Physical Activity Survey

Objective: School food intake of Australian children is not comprehensively described in literature, with limited temporal, nationally representative data. Greater understanding of intake at school can inform school-based nutrition promotion. This study aimed to describe the dietary intake of primary-aged children during school hours and its contribution to daily intake. Design: This secondary analysis used nationally representative, cross-sectional data from the 2011 to 2012 National Nutrition and Physical Activity Survey. Dietary intake was assessed using validated 24-h dietary recalls on school days. Descriptive statistics were undertaken to determine energy, nutrients, food groups and food products consumed during school hours, as well as their contributions to total daily intake. Associations between school food intake and socio-demographic characteristics were explored. Setting: Australia. Participants: Seven hundred and ninety-five children aged 5–12 years. Results: Children consumed 37 % of their daily energy and 31–43 % of select nutrient intake during school hours, with discretionary choices contributing 44 % of school energy intake. Most children consumed less than one serve of vegetables, meat and alternatives or milk and alternatives during school hours. Commonly consumed products were discretionary choices (34 %, including biscuits, processed meat), bread (17 %) and fruit (12 %). There were limited associations with socio-economic position variables, apart from child age. Conclusions: Children’s diets were not aligned with national recommendations, with school food characterised by high intake of discretionary choices. These findings are consistent with previous Australian evidence and support transformation of the Australian school food system to better align school food consumption with recommendations.

Testing the Effect of a Brief, Online and Tailored Intervention on Dietary Behaviors of Australian Adults: A Randomized Controlled Trial

Objectives Using technology, nutrition messages can be tailored to individuals, which may enhance the effectiveness of online dietary behavior interventions. The study objective was to test whether a brief, online intervention using tailored nutrition messaging, supported by behavior change techniques, is more effective than a brief, online intervention using generic messages, in reducing discretionary choices (energy dense, nutrient poor foods and beverages) intake in a sample of Australian adults. Methods A two armed randomized controlled trial was conducted from September to December 2019. The intervention group received two e-mails containing tailored nutrition messages, supported by behavior change techniques, over a 28 day period. The control group received similar e-mails using generic messages. Sociodemographic and dietary data were collected using a validated Short Food Survey at baseline and at follow-up. Statistical analysis used ANCOVA. Results Final analysis included 1441 Australian adults, of which 77.3% were female, with a mean age of 50.8 (SD = 16.0) and Body Mass Index of 28.2 (SD = 6.3). There was no significant difference between delivering tailored or generic messages via e-mail, on discretionary choice intake at follow-up, after controlling for baseline discretionary choice intake (P = .49). Regardless of intervention group allocation, there was a decrease in mean intake of discretionary choices from baseline to follow-up (M = 4.2, SD = 3.9 vs. M = 3.1, SD = 4.0, respectively, P &lt; .001), with a small to medium effect (Cohen's d = .28). Conclusions The primary outcome of the study was discretionary choice intake after a 28 day brief, online intervention using tailored or generic messaging. The intervention was able to significantly reduce discretionary choice intake, however, the impact was not significantly enhanced by tailoring the intervention message. Other forms of tailoring or the inclusion of additional intervention features should be investigated to further enhance intervention effectiveness in future research. Funding Sources The presented work had financial support from Flinders University through a research scholarship, and from CSIRO, Healthy Development Adelaide and the Commonwealth Scholarships Program through top-up scholarships.

Minimal changes in telomere length after a 12-week dietary intervention with almonds in mid-age to older, overweight, and obese Australians: Results of a randomised clinical trial

Diet is a modifiable risk factor for chronic disease and a potential modulator of telomere length (TL). The study aim was to investigate associations between diet quality and TL in Australian adults after a 12-week dietary intervention with an almond-enriched diet. Participants (overweight/obese, 50-80 years) were randomised to an almond-enriched diet (AED, N=62) or iso-caloric nut-free diet (NFD, N=62) for 12 weeks. Diet quality was assessed using a Dietary Guideline Index (DGI), applied to weighed food records, that consists of 10 components reflecting adequacy, variety and quality of core food components and discretionary choices within the diet. Telomere length was measured by quantitative polymerase chain reaction in samples of lymphocytes, neutrophils, and whole blood. There were no significant associations between DGI scores and TL at baseline. Diet quality improved with AED and decreased with NFD after 12 weeks (change from baseline AED +9.8%, NFD −14.3%; P<0.001). Telomere length increased in neutrophils (+ 9.6 base pairs, P=0.009) and decreased in whole blood, to a trivial extent (−12.1 base pairs, P=0.001), and was unchanged in lymphocytes. Changes did not differ between intervention groups. There were no significant relationships between changes in diet quality scores and changes in lymphocyte, neutrophil or whole blood TL. The inclusion of almonds in the diet improved diet quality scores but had no impact on TL mid-age to older Australian adults. Future studies should investigate the impact of more substantial dietary changes over longer periods of time.

Algorithmic justice and groundtruthing the remote mapping of informal settlements: The example of Ho Chi Minh City’s periphery

The significant advances made in interpreting satellite imagery to monitor urban expansion and informal settlements has made important contributions to urban studies and planning. This paper focuses on the under-examined dimensions of how improvements to classifications of urban areas are not only a technical challenge but lie at the society/technology nexus. We examine why three different research groups produced different urban land use classifications of Ho Chi Minh City, Vietnam from remote sensing images. We trace how a confluence of factors including how the technology intersects with field conditions, researcher assumptions and discretionary choices, and institutional norms and agendas shaped the differences in their results. The different spatial facts they produced raises the issue of adapting algorithms for not only technical accuracy but appropriate social use. In the case of detecting informal settlements, our study finds that groundtruthing through fieldwork or collaborative partnerships is needed to not systematically overlook vulnerable populations and misinform urban planning decisions.

Hunger for Home Delivery: Cross-Sectional Analysis of the Nutritional Quality of Complete Menus on an Online Food Delivery Platform in Australia

Online food delivery (OFD) platforms have changed how consumers purchase food prepared outside of home by capitalising on convenience and smartphone technology. Independent food outlets encompass a substantial proportion of partnering outlets, but their offerings’ nutritional quality is understudied. Little is also known as to how OFD platforms influence consumer choice. This study evaluated the nutritional quality and marketing attributes of offerings from independent takeaway outlets available on Sydney’s market-leading OFD platform (UberEats®). Complete menus and marketing attributes from 202 popular outlets were collected using web scraping. All 13841 menu items were classified into 38 food and beverage categories based on the Australian Dietary Guidelines. Of complete menus, 80.5% (11,139/13,841) were discretionary and 42.3% (5849/13,841) were discretionary cereal-based mixed meals, the largest of the 38 categories. Discretionary menu items were more likely to be categorised as most popular (OR: 2.5, 95% CI 1.9–3.2), accompanied by an image (OR: 1.3, 95% CI 1.2–1.5) and offered as a value bundle (OR: 6.5, 95% CI 4.8–8.9). Two of the three discretionary food categories were more expensive than their healthier Five Food Group counterparts (p < 0.02). The ubiquity of discretionary choices offered by independent takeaways and the marketing attributes employed by OFD platforms has implications for public health policy. Further research on the contribution of discretionary choices and marketing attributes to nutritional intakes is warranted.

An empirical study on the GEOtop hydrological model optimal estimation and uncertainty reduction using supercomputers

&lt;p&gt;Proper characterization of uncertainty remains a major research and operational challenge in Earth and Environmental Systems Models (EESMs). In fact, model calibration is often more an art than a science: one must make several discretionary choices, guided more by his own experience and intuition than by the scientific method. In practice, this means that the result of calibration (CA) could be suboptimal. One of the challenges of CA is the large number of parameters involved in EESM, which hence are usually selected with the help of a preliminary sensitivity analysis (SA). Finally, the computational burden of EESMs models and the large volume of the search space make SA and CA very time-consuming processes.&lt;/p&gt;&lt;p&gt;This work applies a modern HPC approach to optimize a complex, over parameterized hydrological model, improving the computational efficiency of SA/CA. We apply the derivative-free optimization algorithms implemented in the Facebook Nevergrad Python library (Rapin and Teytaud, 2018) on a HPC cluster, thanks to the Dask framework (Dask Development Team, 2016).&lt;/p&gt;&lt;p&gt;The approach has been applied to the GEOtop hydrological model (Rigon et al., 2006; Endrizzi et al., 2014) to predict the time evolution of variables as soil water content and evapotranspiration for several mountain agricultural sites in South Tyrol with different elevation, land cover (pasture, meadow, orchard), soil types.&lt;/p&gt;&lt;p&gt;We performed simulations on one-dimensional domains, where the model solves the energy and water budget equations in a column of soil and neglects the lateral water fluxes.&amp;#160; Even neglecting the distribution of parameters across layers of soil, considering a homogeneous column, one has tens of parameters, controlling soil and vegetation properties, where only a few of them are experimentally available.&amp;#160;&lt;/p&gt;&lt;p&gt;Because the interpretation of global SA could be difficult or misleading and the number of model evaluations needed by SA is comparable with CA, we employed the following strategy. We performed CA using a full set of continuous parameters and SA after CA, using the samples collected during CA, to interpret the results. However, given the above-mentioned computational challenges, this strategy is possible only using HPC resources. For this reason, we focused on the computational aspects of calibration from an HPC perspective and examined the scaling of these algorithms and their implementation up to 1024 cores on a cluster. Other issues that we had to address were the complex shape of the search space and robustness of CA and SA against model convergence failure.&lt;/p&gt;&lt;p&gt;HPC &amp;#160;techniques allow to calibrate models with a high number of parameters within a reasonable computing time and &amp;#160;exploring the parameters space properly. This is particularly important with noisy, multimodal objective functions. In our case, HPC was essential to determine the &amp;#160;parameters controlling the water retention curve, which is highly not linear.&amp;#160; The developed &amp;#160;framework, which is published and freely available on GitHub, shows also how libraries and tools used within the machine learning community could be useful and easily adapted to EESMs CA.&lt;/p&gt;

Understanding the Variation within a Dietary Guideline Index Score to Identify the Priority Food Group Targets for Improving Diet Quality across Population Subgroups

Globally, population dietary intakes fall below the guideline recommendations and large-scale interventions have had modest success in improving diet quality. To inform the development of more targeted approaches, this study analysed the variations in self-reported data from an online survey of Australian adults collected between 2015 and 2020, to identify common combinations of low scoring components within a dietary guideline index. A low score was defined as meeting less than half the guideline recommendations (a score <50 out of 100). Among 230,575 adults, a single component analysis showed that 79.5% had a low score for discretionary choices, 72.2% for healthy fats and 70.8% for dairy. The combinations approach showed 83.0% of individuals had two to five low scoring components, with men, younger adults aged 18–30 years and individuals with obesity (BMI ≥ 30) more likely to have five or more. The most common dietary pattern combination included low scores for discretionary choices, dairy and healthy fats. There was a considerable but systematic variation in the low scoring components within the dietary patterns, suggesting that interventions with the flexibility to address particular combinations of key food groups across subgroups could be an effective and resource efficient way to improve diet quality in the population.