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Objective: To examine how socio-demographic characteristics and diet quality vary with consumption of ultra-processed foods (UPF) in a cross-sectional nationally representative survey of Australian adults.Design: Using a 24-h 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 UPF.Setting: Australian Health Survey 2011-2013.Participants: Australian adults aged ≥ 19 years (n 8209).Results: Consumption of UPF was higher among younger adults (aged 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 UPF 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 UPF are detrimental to diet quality. The findings can be used to inform interventions to reduce UPF consumption and improve diet quality. [ABSTRACT FROM AUTHOR]

Objective: To investigate the association between plant-based diets (PBD) and overweight/obesity compared to regular meat eaters in older women.Design: Cross-sectional analysis.Setting: 1946-1951 birth cohort of the Australian Longitudinal Study on Women's Health (ALSWH). PBD were categorised as vegan, lacto-ovo vegetarian, pesco-vegetarian, semi-vegetarian and regular meat eaters. Outcomes included body weight (BW), BMI and waist circumference (WC).Participants: Women who completed Survey 7 (n 9102) with complete FFQ data.Results: Compared to regular meat eaters, BW, BMI and WC were significantly lower in pesco-vegetarians (-10·2 kg (95 % CI -5·1, -15·2); -3·8 kg/m2 (95 % CI -2·0, -5·6); -8·4 cm (95 % CI -3·9, -12·9)) and BW and BMI lower in lacto-ovo vegetarians (-7·4 kg (95 % CI -1·2, -13·6); -2·9 kg/m2 (95 % CI -0·6, -5·1)). In regular meat eaters, individuals consuming meat daily or multiple times/d had significantly higher BW, BMI and WC compared to those consuming meat >2 times/week but 1 but ≤2 times/week (6·8 kg (95 % CI 1·8, 11·8); 2·1 kg/m2 (95 % CI 0·3, 4·0) and 6·0 cm (95 % CI 1·7, 10·4)). This association was dose-dependent such that for every increase in category of weekly meat intake (i.e. >1 time/week but ≤2 times/week; >2 times/week but less than daily, and daily or multiple times/d), an associated 2·6 kg (95 % CI 1·8, 3·4) increase in BW, 0·9 kg/m2 (95 % CI 0·6, 1·2) increase in BMI and 2·3 cm (95 % CI 1·6, 3·0) increase in WC was reported.Conclusions: BW, BMI and WC are lower in women following PBD and positively associated with increasing meat consumption. Results were robust to adjustment for confounders including physical activity levels, smoking status, habitual alcohol intake, use of supplements, and hormone replacement therapy. [ABSTRACT FROM AUTHOR]

Objective: To investigate the psychometric properties, validity and reliability of a newly developed measure of food insecurity, the Household Food and Nutrition Security Survey (HFNSS), among an Australian population.Design: Cross-sectional study.Setting: Metropolitan areas of Melbourne, Australia, identified as very high, high or medium vulnerability in the 2008 Vulnerability Assessment for Mortgage, Petrol and Inflation Risks and Expenditure index.Subjects: A convenience sample of 134 adults (117 females and fifteen males, aged over 18 years).Results: Rasch modelling and factor analysis identified four items for exclusion. The remaining items yielded excellent reliability among the current sample and assessed three underlying components: the adult experience of food insecurity (component one), initial/periodic changes to children's food intakes (component two) and progressive/persistent decreases in children's food intakes (component three). Compared with the widely used US Department of Agriculture Food Security Survey Module, the HFNSS identified a significantly higher proportion of food insecurity; this is likely due to the HFNSS's identification of food insecurity due to reasons other than (and including) limited financial access.Conclusions: The HFNSS may be a valid and reliable tool for the assessment of food insecurity among the Australian population and provides a means of assessing multiple barriers to food security beyond poor financial access (which has been identified as a limitation of other existing tools). Future research should explore the validity and reliability of the tool among a more representative sample, as well as specifically among vulnerable population subgroups. [ABSTRACT FROM AUTHOR]

Identifying toddlers at dietary risk is crucial for determining who requires intervention to improve dietary patterns and reduce health consequences. The objectives of the present study were to develop a simple tool that assesses toddlers' dietary risk and investigate its reliability and validity. The nineteen-item Toddler Dietary Questionnaire (TDQ) is informed by dietary patterns observed in Australian children aged 14 (n 552) and 24 (n 493) months and the Australian dietary guidelines. It assesses the intake of ‘core’ food groups (e.g. fruit, vegetables and dairy products) and ‘non-core’ food groups (e.g. high-fat, high-sugar and/or high-salt foods and sweetened beverages) over the previous 7 d, which is then scored against a dietary risk criterion (0–100; higher score = higher risk). Parents of toddlers aged 12–36 months (Socio-Economic Index for Areas decile range 5–9) were asked to complete the TDQ for their child (n 111) on two occasions, 3·2 (sd 1·8) weeks apart, to assess test–retest reliability. They were also asked to complete a validated FFQ from which the risk score was calculated and compared with the TDQ-derived risk score (relative validity). Mean scores were highly correlated and not significantly different for reliability (intra-class correlation = 0·90, TDQ1 30·2 (sd 8·6) v. TDQ2 30·9 (sd 8·9); P= 0·14) and validity (r 0·83, average TDQ ((TDQ1+TDQ2)/2) 30·5 (sd 8·4) v. FFQ 31·4 (sd 8·1); P= 0·05). All the participants were classified into the same (reliability 75 %; validity 79 %) or adjacent (reliability 25 %; validity 21 %) risk category (low (0–24), moderate (25–49), high (50–74) and very high (75–100)). Overall, the TDQ is a valid and reliable screening tool for identifying at-risk toddlers in relatively advantaged samples. [ABSTRACT FROM PUBLISHER]

The aim of the present study was to investigate and benchmark the level of general nutrition knowledge in elite Australian athletes (EA) against a similar aged community (CM) and criterion sample with dietetic training (DT). EA (n 175), CM (n 116) and DT (n 53) completed the General Nutrition Knowledge Questionnaire (GNKQ), which assesses four domains (sections A–D) of general nutrition knowledge (section A: dietary guidelines; section B: sources of nutrients; section C: choosing everyday foods; section D: diet–disease relationships). Age, sex and education level were collected in all groups, and athletic calibre and sport type (team or individual) in EA. Dietitians and nutrition scientists (n 53) re-examined the GNKQ for content validity, resulting in instrument revision (R-GNKQ; ninety-six items). Psychometric assessment (internal consistency: Cronbach-α; test–retest: Spearman rank correlation) was performed in a sub-sample (n 28). Independent t tests, ANOVA and ANCOVA (χ2 for categorical variables) were used to assess between-group differences. DT scored higher than EA and CM in all sub-sections and overall (P < 0·005). EA scored lower than CM in GNKQ for section B (P < 0·005) and overall (P < 0·005), and in R-GNKQ for section B (P < 0·005), section C (P < 0·005), section D (P = 0·006) and overall (P < 0·005). Overall score was influenced by age (P = 0·036 for GNKQ: P = 0·053 for R-GNKQ), sex (P = 0·016 for GNKQ: P = 0·003 for R-GNKQ) and athletic calibre (P = 0·029 for R-GNKQ only), but not level of education, living situation or ethnicity. EA and CM performed best on section A and worst on D. EA had lower overall general knowledge scores than CM. This was significantly influenced by age and sex. [ABSTRACT FROM PUBLISHER]