Kristine Pezdirc

Distilling the complexity of overall diet into a simple measure or summative score by data reduction methods has become a common practice in nutritional epidemiology. Recent reviews on diet quality indices (DQI) have highlighted the importance of sound construction criteria and validation. The aim of this current review was to identify and critically appraise all DQI used within Australian and New Zealand adult populations. Twenty-five existing DQI were identified by electronic searching in Medline and hand searching of reference lists. DQI were constructed based on the respective national dietary guidelines and condition-specific recommendations. For preferable features of DQI, six captured the dimensions of adequacy, moderation and balance; five had a nested structure; 12 consisted of foods, food groups and nutrients; 11 used metric scoring systems and most of those with metric scales used normative cutoff points. Food frequency questionnaires, either alone or with other methods, were the most common dietary assessment method used in 20 DQI. For evaluation of DQI, construct validity and relative validity are reported. Based on our critical appraisal, Dietary Guideline Index (DGI), Dietary Guideline Index-2013 (DGI-2013), Total Diet Score (TDS), Healthy Eating Index for Australian Adults-2013 (HEIFA-2013), and Aussie-Diet Quality Index (Aussie-DQI) were the preferred DQI used in Australian adults according to dimension, indicator selection, scoring criteria and evaluation. Further work is needed to enhance the construction of all Australian and New Zealand DQI, especially in terms of dimension and structure, for alignment with recommended construction criteria.

The current study examines associations between the dietary intakes of nutrient-dense foods, measured using brief indices and skin coloration, measured using reflectance spectroscopy in young adults. This is a cross-sectional analysis of 148 young Australian males and females (55% female) aged 18 to 25 years. Dietary intake was assessed using a validated food frequency questionnaire, with responses used to calculate two dietary indices: (i) the Australian Recommended Food Score (ARFS); and (ii) the Fruit And Vegetable VAriety Score (FAVVA). Skin yellowness was measured at three body locations using reflectance spectroscopy. Associations were assessed using Spearman’s correlation coefficients, regression analysis, and agreement using weighted kappa (K_w). Significant, moderate correlations were found between skin yellowness and diet index scores for the ARFS (ρ = 0.30, p < 0.001) and FAVVA score (ρ = 0.39, p < 0.001). These remained significant after adjustment for confounders (total fat intake, sex, skin lightness) and for agreement based on categorical rankings. Results suggest that measurement of skin coloration by reflectance spectroscopy can be used as an indicator of overall dietary quality and variety in young adults. Further exploration in diverse populations is required.

Diet quality indices can predict nutritional adequacy of usual intake, but validity should be determined. The aim was to assess the validity of total and sub-scale score within the Australian Recommended Food Score (ARFS), in relation to fasting plasma carotenoid concentrations. Diet quality and fasting plasma carotenoid concentrations were assessed in 99 overweight and obese adults (49.5% female, aged 44.6 ± 9.9 years) at baseline and after three months (198 paired observations). Associations were assessed using Spearman’s correlation coefficients and regression analysis, and agreement using weighted kappa (K_w). Small, significantly positive correlations were found between total ARFS and plasma concentrations of total carotenoids (r = 0.17, p < 0.05), β-cryptoxanthin (r = 0.18, p < 0.05), β-carotene (r = 0.20, p < 0.01), and α-carotene (r = 0.19, p < 0.01). Significant agreement between ARFS categories and plasma carotenoid concentrations was found for total carotenoids (K_w 0.12, p = 0.02), β-carotene (K_w 0.14, p < 0.01), and α-carotene (K_w 0.13, p < 0.01). In fully-adjusted regression models the only signification association with ARFS total score was for α-carotene (β = 0.19, p < 0.01), while ARFS meat and fruit sub-scales demonstrated significant relationships with α-carotene, β-carotene, and total carotenoids (p < 0.05). The weak associations highlight the issues with self-reporting dietary intakes in overweight and obese populations. Further research is required to evaluate the use of the ARFS in more diverse populations.