Association between diet quality, dietary patterns and cardiometabolic health in Australian adults: a cross-sectional study

Background: Diet quality indices score dietary intakes against recommendations, whereas dietary patterns consider the pattern and combination of dietary intakes. Studies evaluating both methodologies in relation to cardiometabolic health in a nationally representative sample are limited. The aim of the present study was to investigate the relationship between diet quality, dietary patterns and markers of cardiometabolic health in Australian adults. Methods: Dietary data, using two 24-h dietary recalls, were collected from adults in the cross-sectional Australian Health Survey 2011-2013 (n = 2121; 46.4 (SE 0.48) years). Diet quality was estimated using the Dietary Guideline Index (DGI). Dietary patterns (DPs), derived using reduced rank regression, were estimated using fiber density, SFA:PUFA and total sugars intake as intermediate markers. Multi-variable adjusted linear regression analyses were used to examine associations between diet quality and DPs and blood biomarkers, body mass index, waist circumference, diastolic and systolic blood pressure and an overall cardiometabolic risk score. Results: DGI was associated with lower glucose (coef - 0.009, SE 0.004; P-trend = 0.033), body mass index (coef - 0.017, SE 0.007; P-trend = 0.019) and waist circumference (coef - 0.014, SE 0.005; P-trend = 0.008). Two dietary patterns were derived: dietary pattern-1 was characterized by higher intakes of pome fruit and wholegrain bread, while dietary pattern-2 was characterized by higher intakes of added sugars and tropical fruit. Dietary pattern-1 was associated with lower body mass index (coef - 0.028, SE 0.007; P-trend< 0.001) and waist circumference (coef - 0.017, SE 0.005; P-trend = 0.001). There was a trend towards lower cardiometabolic risk score. Dietary pattern-2 was associated with lower HDL-cholesterol (coef - 0.026, SE 0.012; P-trend = 0.028). There was a trend towards lower diastolic blood pressure. No associations with other markers were observed. Conclusions: Better diet quality and healthier dietary patterns were primarily associated with favorable anthropometric markers of cardiometabolic health. Findings support the need for comparison of whole-diet based methodologies that take into consideration the interactions between foods and nutrients. Longitudinal studies are warranted to better understand causal relationships between diet and cardiometabolic health.