Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

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


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.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.


  • Australian Bureau of Statistics. 1995 National Health Survey: Users' Guide Catalogue no. 4363.0 Canberra: Australian Bureau of Statistics

  • Australian Bureau of Statistics. 1998 National Nutrition Survey: User's Guide, 1995 Catalogue no. 4801.0 Canberra: Australian Bureau of Statistics

  • Baghurst K, Baghurst P . 1981 The measurement of usual dietary intakes in individuals and groups Trans. Menzies Found. 3: 139–160

    Google Scholar 

  • Baghurst K, Record S, Syrette J, Crawford D, Baghurst P . 1989 Intakes and sources of a range of dietary sugars in various Australian populations Med. J. Aust. 151: 512–518

    CAS  PubMed  Google Scholar 

  • Baghurst K, Record S, Baghurst P, Syrette J, Crawford D, Worsley A . 1990 Socioeconomic determinants in Australia of the intake of food and nutrients implicated in cancer aetiology Med. J. Aust. 153: 444–452

    CAS  PubMed  Google Scholar 

  • Bartley M, Fitzpatric R, Firth D, Marmot M . 2000 Social distribution of cardiovascular disease risk factors: change among men in England 1984–1993 J Epidemiol. Community Health 54: 806–814

    Article  CAS  Google Scholar 

  • Gex-Fabry M, Raymond L, Jeanneret O . 1988 Multivariate analysis of dietary patterns in 939 Swiss adults: sociodemographic parameters and alcohol consumption profiles Int. J. Epidemiol. 17: 548–555

    Article  CAS  Google Scholar 

  • Hair JF Jr, Anderson RE, Tatham RL, Black WC . 1997 Multivariate Data Analysis with Readings 4th edn New Jersey: Prentice Hall

    Google Scholar 

  • Hu FB, Rimm E, Smith-Warner SA, Feskanich D, Stampfer MJ, Ascherio A, Sampson L, Willett WC . 1999 Reproducibility and validity of dietary patterns assessed with a food-frequency questionnaire Am. J. Clin. Nutr. 69: 243–249

    Article  CAS  Google Scholar 

  • Huijbregts P, Feskens E, Rasanen L, Fidanza F, Nissinen A, Menotti A, Kromhout D . 1997 Dietary pattern and 20 y mortality in elderly men in Finland, Italy, and the Netherlands: longitudinal cohort study Br. Med. J. 314: 13–18

    Article  Google Scholar 

  • Iizumi H, Amemiya T . 1986 Eleven-year follow-up of changes in individuals' food consumption patterns Int. J. Vit. Nutr. Res. 56: 399–409

    CAS  Google Scholar 

  • Irala-Estevez J, Groth M, Johansson L, Oltersdorf U, Prattala R, Martinez-Gonzalez M . 2000 A systemic review of socio-economic differences in food habits in Europe: consumption of fruit and vegetables Eur. J. Clin. Nutr. 54: 706–714

    Article  CAS  Google Scholar 

  • Kant AK . 1996 Indexes of overall diet quality: a review J. Am. Diet. Assoc. 96: 785–792

    Article  CAS  Google Scholar 

  • Kim J . 1975 Factor analysis In Statistical Package for the Social Sciences ed. NH Nie, CH Hull, JG Jenkins, K Steinbrenner & DH Bent New York: McGraw-Hill

    Google Scholar 

  • Kumagai S, Shibata H, Watanabe S, Suzuki T, Haga H . 1999 Effect of food intake pattern on all-cause mortality in the community elderly: a 7-year longitudinal study J. Nutr. Health Aging 3: 29–33

    CAS  PubMed  Google Scholar 

  • Lissner L, Heitmann BL, Bengtsson C . 2000 Population studies of diet and obesity Br. J. Nutr. 83: S21–S24

    Article  CAS  Google Scholar 

  • Milligan R, Burke V, Beilin L, Dunbar D . 1998 Influence of gender and socio-economic status on dietary patterns and nutrient intakes in 18 y old Australians Aust. NZJ. Public Health 22: 485–493

    Article  CAS  Google Scholar 

  • Mishra GD, Ball K, Dobson AJ, Byles JE, Warner-Smith P . 2001 The measurement of socioeconomic status: investigation of gender- and age-specific indicators in Australia National Health Survey '95. Social Indicators Research 56: 73–89

    Article  Google Scholar 

  • Nicklas TA, Webber LS, Thompson B, Berenson GS . 1989 A multivariate model for assessing eating patterns and their relationship to cardiovascular risk factors: the Bogalusa Heart Study Am. J. Clin. Nutr. 49: 1320–1327

    Article  CAS  Google Scholar 

  • Randall E, Marshall JR, Graham S, Brasure J . 1990 Patterns in food use and their associations with nutrient intakes Am. J. Clin. Nutr. 52: 739–745

    Article  CAS  Google Scholar 

  • SAS Institute Inc.. 1989 SAS/STAT User's Guide (Version 6, 4th edn, Vol 2) Cary, NC: SAS Institute Inc.

  • Schwerin HS, Stanton JL, Riley AM Jr, Schaefer AE, Leveille GA, Elliott JG, Warwick KM, Brett BE . 1981 Food eating patterns and health: a reexamination of the Ten-State and HANES 1 surveys Am. J. Clin. Nutr. 34: 568–555

    Article  CAS  Google Scholar 

  • Schwerin HS, Stanton JL, Smith JL, Riley AM, Brett BE . 1982 Food, eating habits, and health: a further examination of the relationship between food eating patterns and nutritional health Am. J. Clin. Nutr. 35: 1319–1325

    Article  CAS  Google Scholar 

  • Shimakawa T, Sorlie P, Carpenter M, Dennis B, Tell G, Watson R, Williams O . 1994 Dietary intake patterns and sociodemographic factors in the atherosclerosis risk in communities study. ARIC study investigators Prev. Med. 23: 769–780

    Article  CAS  Google Scholar 

  • Smith A, Owen N . 1992 Associations of social status and health-related beliefs with dietary fat and fiber densities Prev. Med. 21: 735–745

    Article  CAS  Google Scholar 

  • Steele P, Dobson A, Alexander H, Russell A . 1991 Who eats what? A comparison of dietary patterns among men and women in different occupational groups Aust. J. Public Health 14: 286–295

    Google Scholar 

  • Thompson R, Margetts B, Speller V, McVey D . 1999 The health education authority's health and lifestyle survey 1993: who are the low fruit and vegetable consumers? J. Epidemiol. Community Health 53: 294–299

    Article  CAS  Google Scholar 

  • Wallstrom P, Wirfalt E, Janzon L, Mattisson I, Elmstahl S, Johansson U, Berglund G . 2000 Fruit and vegetable consumption in relation to risk factors for cancer: a report from the Malmo Diet and Cancer study Public Health Nutr. 3: 263–271

    Article  CAS  Google Scholar 

  • Wamala S, Mittleman M, Schenck-Gustafsson K, Orth-Gomer K . 1999 Potential explanations for the educational gradient in coronary heart disease: a population-based case-control study of Swedish women Am. J. Public Health 89: 315–321

    Article  CAS  Google Scholar 

  • Webb K, Schofield W, Lazarus R, Smith W, Mitchell P, Leeder S . 1999 Prevalence and socio-demographic predictors of dietary goal attainment in an older population Aust. N.Z. J. Public Health 23: 578–584

    Article  CAS  Google Scholar 

  • Wirfalt E, Mattisson I, Gullberg B, Berglund G . 2000 Food patterns defined by cluster analysis and their utility as dietary exposure variables: a report from the Malmo Diet and Cancer Study Public Health Nutr. 3: 159–173

    Article  CAS  Google Scholar 

  • Wolff CB, Wolff HK . 1995 Maternal eating patterns and birth weight of Mexican American infants Nutr. Health 10: 121–134

    Article  CAS  Google Scholar 

  • Wynn A . 1987 Inequalities in nutrition Nutr. Health 5: 79–94

    Article  CAS  Google Scholar 

Download references


Dr Kylie Ball is supported by a Public Health Research Fellowship from the National Health and Medical Research Council (ID 136925). Dr David Crawford is supported by a Nutrition Research Fellowship from the National Heart Foundation of Australia.

Author information

Authors and Affiliations


Corresponding author

Correspondence to K Ball.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Mishra, G., Ball, K., Arbuckle, J. et al. Dietary patterns of Australian adults and their association with socioeconomic status: results from the 1995 National Nutrition Survey. Eur J Clin Nutr 56, 687–693 (2002).

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:


  • dietary patterns
  • socioeconomic status
  • factor analysis
  • population study

This article is cited by


Quick links