This study investigated associations between diet quality measures and quality of life two years later. Adults 55-65 years participating in the Wellbeing, Eating and Exercise for a Long Life (WELL) study in Victoria, Australia (n = 1150 men and n = 1307 women) completed a postal survey including a 111-item food frequency questionnaire in 2010. Diet quality in 2010 was assessed via the dietary guideline index (DGI), recommended food score (RFS) and Mediterranean diet score (MDS). The RAND 36-item survey assessed health-related quality of life in 2012. Associations were assessed using logistic regression adjusted for covariates. In men, DGI and RFS were associated with better reported energy (OR = 1.79, CI: 1.25, 2.55 and OR = 1.56, CI: 1.11, 2.19 respectively), and DGI was additionally associated with better general health (OR = 1.54, 95% CI: 1.08, 2.20), and overall mental component summary scale (OR = 1.51, CI: 1.07, 2.15) in the fully adjusted model. In women, associations between two indices of diet quality (DGI, RFS) physical function (OR = 1.66, CI: 1.19, 2.31 and OR = 1.70, CI: 1.21, 2.37 respectively) and general health (OR = 1.83, CI: 1.32, 2.54 and OR = 1.54, CI: 1.11, 2.14 respectively) were observed. DGI was also associated with overall physical component summary score (OR = 1.56, CI: 1.12, 2.17). Additional associations between emotional wellbeing and DGI (OR = 1.40, CI: 1.01, 1.93) and RFS (OR = 1.44, CI: 1.04, 1.99), and MDS and energy (OR = 1.53, CI: 1.11, 2.10) were observed in the fully adjusted model, in women only. Older adults with better quality diets report better health-related quality of life, with additional associations with emotional wellbeing observed in women.

Despite increased use of dietary pattern methods in nutritional epidemiology, there have been few direct comparisons of methods. Older adults are a particularly understudied population in the dietary pattern literature. This study aimed to compare dietary patterns derived by principal component analysis (PCA) and cluster analysis (CA) in older adults and to examine their associations with socio-demographic and health behaviours. Men (n = 1888) and women (n = 2071) aged 55–65 years completed a 111-item food frequency questionnaire in 2010. Food items were collapsed into 52 food groups and dietary patterns were determined by PCA and CA. Associations between dietary patterns and participant characteristics were examined using Chi-square analysis. The standardised PCA-derived dietary patterns were compared across the clusters using one-way ANOVA. PCA identified four dietary patterns in men and two dietary patterns in women. CA identified three dietary patterns in both men and women. Men in cluster 1 (fruit, vegetables, wholegrains, fish and poultry) scored higher on PCA factor 1 (vegetable dishes, fruit, fish and poultry) and factor 4 (vegetables) compared to factor 2 (spreads, biscuits, cakes and confectionery) and factor 3 (red meat, processed meat, white-bread and hot chips) (mean, 95 % CI; 0.92, 0.82–1.02 vs. 0.74, 0.63–0.84 vs. −0.43, −0.50– −0.35 vs. 0.60 0.46–0.74, respectively). Women in cluster 1 (fruit, vegetables and fish) scored highest on PCA factor 1 (fruit, vegetables and fish) compared to factor 2 (processed meat, hot chips cakes and confectionery) (1.05, 0.97–1.14 vs. −0.14, −0.21– −0.07, respectively). Cluster 3 (small eaters) in both men and women had negative factor scores for all the identified PCA dietary patterns. Those with dietary patterns characterised by higher consumption of red and processed meat and refined grains were more likely to be Australian-born, have a lower level of education, a higher BMI, smoke and did not meet physical activity recommendations (all P < 0.05). PCA and CA identified comparable dietary patterns within older Australians. However, PCA may provide some advantages compared to CA with respect to interpretability of the resulting dietary patterns. Older adults with poor dietary patterns also displayed other negative lifestyle behaviours. Food-based dietary pattern methods may inform dietary advice that is understood by the community.

Objective: To determine the diet quality of a group of young adults and explore its associations with two food-related behaviours (involvement in meal preparation and consumption of commercially prepared meals).Design: Cross-sectional study of young adults. Sample characteristics, food-related behaviours and dietary intake were assessed using a self-administered questionnaire including an FFQ. Diet quality was measured using the fifteen-item Dietary Guideline Index (DGI) designed to assess adherence to Australian dietary guidelines. One-way ANOVA, t tests and multiple linear regression analyses were used to explore the relationships between DGI scores, sample characteristics and food-related behaviours.Setting: University students enrolled in an undergraduate nutrition class, Melbourne, Australia.Subjects: Students (n 309) aged 18–36 years.Results: The DGI score was normally distributed, with a mean score of 93·4 (sd 17·1) points (range 51·9–127·4 points), out of a possible score of 150 points. In multivariate analyses adjusted for age, sex, nationality, BMI and maternal education, cooking meals for oneself was positively associated with DGI score (β = 0·15; 95 % CI 1·15, 10·03; P = 0·01); frequency of takeaway and frequency of convenience meal consumption were inversely associated with DGI score (β = −0·21; 95 % CI −9·96, −2·32; P = 0·002 and β = −0·16; 95 % CI −7·40, −0·97; P < 0·01, respectively).Conclusions: Cooking meals for oneself was linked to higher diet quality among young adults, while consumption of commercially prepared meals was associated with poorer diet quality. Maintaining education programmes that promote cooking skills within young adults has the potential to improve DGI scores.

The Dietary Guideline Index, a measure of diet quality, was updated to reflect the 2013 Australian Dietary Guidelines. This paper describes the revision of the index (DGI-2013) and examines its use in older adults. The DGI-2013 consists of 13 components reflecting food-based daily intake recommendations of the Australian Dietary Guidelines. In this cross-sectional study, the DGI-2013 score was calculated using dietary data collected via an 111-item food frequency questionnaire and additional food-related behaviour questions. The DGI-2013 score was examined in Australian adults (aged 55–65 years; n = 1667 men; 1801 women) according to sociodemographics, health-related behaviours and BMI. Women scored higher than men on the total DGI-2013 and all components except for dairy. Those who were from a rural area (men only), working full-time (men only), with lower education, smoked, did not meet physical activity guidelines, and who had a higher BMI, scored lower on the DGI-2013, highlighting a group of older adults at risk of poor health. The DGI-2013 is a tool for assessing compliance with the Australian Dietary Guidelines. We demonstrated associations between diet quality and a range of participant characteristics, consistent with previous literature. This suggests that the DGI-2013 continues to demonstrate convergent validity, consistent with the original Dietary Guideline Index.

Many national and international public health organisations recommend achieving nutrient adequacy through consumption of a wide variety of nutritious foods. Despite this, dietary supplement sales continue to increase. Understanding the characteristics of micronutrient supplement users and the relationship with diet quality can help develop effective public health interventions to reduce unnecessary consumption of vitamin and mineral supplements. Participants (n = 1306) were a convenience sample of students studying first year food and nutrition. Data was collected via a Food and Diet Questionnaire (FDQ) and a Food Frequency Questionnaire (FFQ). Supplement users were defined as participants who indicated consuming any listed supplement as frequently as once a month or more. Diet quality was assessed using a Dietary Guideline Index (DGI) score. Prevalence of supplement use was high in this study population with 56% of participants reporting supplement use; the most popular supplements consumed were multivitamins (28%) and vitamin C (28%). A higher DGI score was significantly associated with an increased likelihood of supplement use (mean: 105 ± 18 vs. 109 ± 17, p = 0.001). Micronutrient supplement use was associated with a higher DGI score, suggesting that supplements are more likely to be used by those who are less likely to require them.