Dietary patterns of Australian adults and their association with socioeconomic status: results from the 1995 National Nutrition Survey

Eur J Clin Nutr. 2002 Jul;56(7):687-93. doi: 10.1038/sj.ejcn.1601391.

Abstract

Objective: To describe dietary patterns among men and women in the Australian population, and to explore how these varied according to socioeconomic status (SES).

Design: A cross-sectional self-report population survey, the 1995 Australian National Nutrition Survey (NNS), was used.

Setting: Private dwelling sample, covering urban and rural areas across Australia.

Subjects: Data provided by 6680 adults aged 18-64 who participated in the NNS were used in the analyses.

Methods: Factor analyses were used to analyse data from a Food Frequency Questionnaire (FFQ) completed by participants. Associations between SES and dietary pattens were assessed using ANOVA.

Results: Separate factor analyses of the FFQ data for men and women revealed 15 factors, accounting for approximately 50% of the variance in both men's and women's dietary patterns. Several gender and SES differences in food patterns were observed. Lower SES males more frequently consumed 'tropical fruits', 'protein foods', and 'offal and canned fish', while high SES males more often ate 'breakfast cereals' and 'wholemeal bread'. Lower SES females more often ate 'traditional vegetables', 'meat dishes' and 'pasta, rice and other mixed foods', while high SES females more frequently ate 'ethnic vegetables' and 'breakfast cereal/muesli'.

Conclusions: These findings contribute to a better understanding of the dietary patterns that underscore gender-specific SES differences in nutrient intakes. Analyses of the type employed in this study will facilitate the development of interventions aimed at modifying overall eating patterns, rather than specific components of the diet.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Australia
  • Cohort Studies
  • Cross-Sectional Studies
  • Diet / statistics & numerical data*
  • Factor Analysis, Statistical
  • Feeding Behavior*
  • Female
  • Humans
  • Male
  • Middle Aged
  • Nutrition Surveys
  • Rural Population
  • Sex Factors
  • Social Class*
  • Surveys and Questionnaires
  • Urban Population