Objective: To examine how socio-demographic characteristics and diet quality vary with consumption of ultra-processed foods (UPFs) in a cross-sectional nationally representative survey of Australian adults. Design: Using a 24-hour recall, this cross-sectional analysis of dietary and socio-demographic data classified food items using the NOVA system, estimated the percentage of total energy contributed by UPFs and assessed diet quality using the Dietary Guideline Index (DGI – 2013 total and components). Linear regression models examined associations between socio-demographic characteristics and diet quality with percentage of energy from UPFs. Setting: Australian Health Survey 2011-13 Participants: Australian Adults aged ≥ 19 years (n=8,209) Results: Consumption of UPFs was higher among younger adults (19-30 years), adults born in Australia, those experiencing greatest area level disadvantage, lower levels of education, and the second lowest household income quintile. No significant association was found for sex or rurality. A higher percentage of energy from UPFs was inversely associated with diet quality and with lower DGI scores related to the variety of nutritious foods, fruits, vegetables, total cereals, meat and poultry, fish, eggs, nuts and seeds, legumes/beans, water and limits on discretionary foods, saturated fat and added sugar. Conclusions: This research adds to the evidence on dietary inequalities across Australia and how UPFs are detrimental to diet quality. The findings can be used to inform interventions to reduce UPF consumption and improve diet quality.

Dietary patterns examine the combinations, types and quantities of foods consumed in the diet. Compared to individual nutrients, dietary patterns may be better associated with cancer-related malnutrition, low muscle mass and sarcopenia. This scoping review identified associations between dietary patterns, assessed using data-driven methods (i.e., statistical methods used to derive existing dietary patterns) and hypothesis-orientated methods (i.e., adherence to diet quality indices), and malnutrition, low muscle (lean) mass and sarcopenia. MEDLINE, Embase and CINAHL databases were searched up to September 2021. Of the 3341 studies identified, seven studies were eligible for review. Study designs included experimental (n = 5) and observational (n = 2), and people with prostate, ovarian and endometrial, bladder, breast, and gastrointestinal cancers. One study used data-driven methods to derive dietary patterns, finding adherence to a ‘fat and fish’ diet was associated with lower odds of low muscle mass. Two studies examined adherence to hypothesis-orientated methods including the Mediterranean Diet Adherence Screener and Healthy Eating Index 2010 and four studies used ‘non-traditional’ approaches to analyse dietary patterns. Hypothesis-orientated dietary patterns, developed to improve general health and prevent chronic disease, and ‘non-traditional’ dietary patterns demonstrated inconsistent effects on muscle (lean) mass. All studies investigated muscle (lean) mass, omitting malnutrition and sarcopenia as cancer-related outcomes. This scoping review highlights the limited research examining the effect of dietary patterns on cancer-related outcomes.

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The effect of dietary fat on type 2 diabetes (T2D) risk is unclear. A posteriori dietary pattern methods have been increasingly used to investigate how dietary fats impact T2D risk. However, the diverse nutrients, foods and dietary patterns reported in these studies requires examination to better understand the role of dietary fats. This scoping review aimed to systematically search and synthesize the literature regarding the association between dietary patterns characterized by dietary fats and T2D risk using reduced rank regression. Medline and Embase were searched for cross-sectional, cohort or case-control studies published in English. Of the included studies (n = 8), five high-fat dietary patterns, mostly high in SFA, were associated with higher T2D risk or fasting glucose, insulin and Homeostasis Model Assessment (HOMA) levels. These were mostly low-fiber (n = 5) and high energy-density (n = 3) dietary patterns characterized by low fruit and vegetables intake, reduced fat dairy products and higher processed meats and butter intake. Findings from this review suggest that a posteriori dietary patterns high in SFA that increase T2D risk are often accompanied by lower fruits, vegetables and other fiber-rich foods intake. Therefore, healthy dietary fats consumption for T2D prevention should be encouraged as part of a healthful dietary pattern.

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