The Relationship between Dietary Patterns and Metabolic Health in a Representative Sample of Adult Australians

Nutrients. 2015 Aug 5;7(8):6491-505. doi: 10.3390/nu7085295.

Abstract

Studies assessing dietary intake and its relationship to metabolic phenotype are emerging, but limited. The aims of the study are to identify dietary patterns in Australian adults, and to determine whether these dietary patterns are associated with metabolic phenotype and obesity. Cross-sectional data from the Australian Bureau of Statistics 2011 Australian Health Survey was analysed. Subjects included adults aged 45 years and over (n = 2415). Metabolic phenotype was determined according to criteria used to define metabolic syndrome (0-2 abnormalities vs. 3-7 abnormalities), and additionally categorized for obesity (body mass index (BMI) ≥30 kg/m2 vs. BMI <30 kg/m2). Dietary patterns were derived using factor analysis. Multivariable models were used to assess the relationship between dietary patterns and metabolic phenotype, with adjustment for age, sex, smoking status, socio-economic indexes for areas, physical activity and daily energy intake. Twenty percent of the population was metabolically unhealthy and obese. In the fully adjusted model, for every one standard deviation increase in the Healthy dietary pattern, the odds of having a more metabolically healthy profile increased by 16% (odds ratio (OR) 1.16; 95% confidence interval (CI): 1.04, 1.29). Poor metabolic profile and obesity are prevalent in Australian adults and a healthier dietary pattern plays a role in a metabolic and BMI phenotypes. Nutritional strategies addressing metabolic syndrome criteria and targeting obesity are recommended in order to improve metabolic phenotype and potential disease burden.

Keywords: Australia, national survey; adults; body mass index; dietary patterns; metabolic health; obesity.

MeSH terms

  • Aged
  • Australia
  • Blood Glucose / metabolism
  • Body Mass Index*
  • Cholesterol, HDL / blood
  • Cholesterol, LDL / blood
  • Cross-Sectional Studies
  • Diet*
  • Energy Intake
  • Female
  • Fruit
  • Health Surveys
  • Humans
  • Logistic Models
  • Male
  • Metabolic Syndrome / epidemiology*
  • Middle Aged
  • Motor Activity
  • Obesity / epidemiology*
  • Prevalence
  • Red Meat
  • Socioeconomic Factors
  • Triglycerides / blood
  • Vegetables

Substances

  • Blood Glucose
  • Cholesterol, HDL
  • Cholesterol, LDL
  • Triglycerides