Skip to main content
    • Aa
    • Aa

Classification of main meal patterns – a latent class approach

  • Wei C. Wang (a1), Anthony Worsley (a1) and Victoria Hodgson (a2)

Relatively little examination of the meals that are prepared in households has been conducted, despite their well-defined properties and widespread community interest in their preparation. The purpose of the present study was to identify the patterns of main meal preparation among Australian adult household meal preparers aged 44 years and younger and 45 years and over, and the relationships between these patterns and likely socio-demographic and psychological predictors. An online cross-sectional survey was conducted by Meat and Livestock Australia among a representative sample of people aged 18–65 years in Australia in 2011. A total of 1076 usable questionnaires were obtained, which included categorical information about the main meal dishes that participants had prepared during the previous 6 months along with demographic information, the presence or absence of children at home, confidence in seasonal food knowledge and personal values. Latent class analysis was applied and four types of usage patterns of thirty-three popular dishes were identified for both age groups, namely, high variety, moderate variety, high protein but low beef and low variety. The meal patterns were associated differentially with the covariates between the age groups. For example, younger women were more likely to prepare a high or moderate variety of meals than younger men, while younger people who had higher levels of education were more likely to prepare high-protein but low-beef meals. Moreover, young respondents with higher BMI were less likely to prepare meals with high protein but low beef content. Among the older age group, married people were more likely to prepare a high or moderate variety of meals than people without partners. Older people who held strong universalist values were more likely to prepare a wide variety of meals with high protein but low beef content. For both age groups, people who had children living at home and those with better seasonal food knowledge were more likely to prepare a high variety of dishes. The identification of classes of meal users would enable health communication to be tailored to improve meal patterns. Moreover, the concept of meals may be useful for health promotion, because people may find it easier to change their consumption of meals rather than individual foods.

  • View HTML
    • Send article to Kindle

      To send this article to your Kindle, first ensure is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle.

      Note you can select to send to either the or variations. ‘’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

      Find out more about the Kindle Personal Document Service.

      Classification of main meal patterns – a latent class approach
      Available formats
      Send article to Dropbox

      To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your Dropbox account. Find out more about sending content to Dropbox.

      Classification of main meal patterns – a latent class approach
      Available formats
      Send article to Google Drive

      To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your Google Drive account. Find out more about sending content to Google Drive.

      Classification of main meal patterns – a latent class approach
      Available formats
Corresponding author
*Corresponding author: W. C. Wang, fax +61 3 9244 6017, email
Linked references
Hide All

This list contains references from the content that can be linked to their source. For a full set of references and notes please see the PDF or HTML where available.

1 SM Moeller , J Reedy , AE Millen , et al. (2007) Dietary patterns: challenges and opportunities in dietary patterns research: an Experimental Biology Workshop, April 1, 2006. J Am Diet Assoc 107, 12331239.

4 RL Bailey , MD Gutschall , DC Mitchell , et al. (2006) Comparative strategies for using cluster analysis to assess dietary patterns. J Am Diet Assoc 106, 11941200.

5 PM Guenther , J Reedy , SM Krebs-Smith , et al. (2008) Evaluation of the Healthy Eating Index-2005. J Am Diet Assoc 108, 18541864.

7 SS Padmadas , JG Dias & FJ Willekens (2006) Disentangling women's responses on complex dietary intake patterns from an Indian cross-sectional survey: a latent class analysis. Public Health Nutr 9, 204211.

9 M Slattery & J Potter (2002) Physical activity and colon cancer: confounding or interaction? Med Sci Sports Exerc 34, 913919.

10 H Berteus Forslund , AK Lindroos , L Sjostrom , et al. (2002) Meal patterns and obesity in Swedish women – a simple instrument describing usual meal types, frequency and temporal distribution. Eur J Clin Nutr 56, 740747.

13 Á Skrabski , M Kopp & I Kawachi (2003) Social capital in a changing society: cross sectional associations with middle aged female and male mortality rates. J Epidemiol Commun Health 57, 114119.

14 C Higgins , L Duxbury & C Lee (1994) Impact of life-cycle stage and gender on the ability to balance work and family responsibilities. Fam Relat 43, 144150.

15 SG Leveille , CC Wee & LI Iezzoni (2005) Trends in obesity and arthritis among baby boomers and their predecessors, 1971–2002. Am J Public Health. 95, 16071613.

16 A Trichopoulou , T Costacou , C Bamia , et al. (2003) Adherence to a Mediterranean diet and survival in a Greek population. New Engl J Med 348, 25992608.

17 A Beardsworth , A Bryman , T Keil , et al. (2002) Women, men and food: the significance of gender for nutritional attitudes and choices. Br Food J 104, 470491.

19 S Thiele , GBM Mensink & R Beitz (2004) Determinants of diet quality. Public Health Nutr 7, 2937.

20 RB Schafer , E Schafer , M Dunbar , et al. (1999) Marital food interaction and dietary behavior. Soc Sci Med 48, 787796.

21 D Umberson (1992) Gender, marital status and the social control of health behavior. Soc Sci Med 34, 907917.

22 G Turrell , B Hewitt , C Patterson , et al. (2002) Socioeconomic differences in food purchasing behaviour and suggested implications for diet-related health promotion. J Hum Nutr Diet 15, 355364.

23 A Worsley , R Blasche , K Ball , et al. (2004) The relationship between education and food consumption in the 1995 Australian National Nutrition Survey. Public Health Nutr 7, 649663.

24 A Worsley , R Blasche , K Ball , et al. (2003) Income differences in food consumption in the 1995 Australian National Nutrition Survey. Eur J Clin Nutr 57, 11981211.

25 A Worsley & V Scott (2000) Consumers' concerns about food and health in Australia and New Zealand. Asia Pac J Clin Nutr 9, 2432.

26 HH Laroche , TP Hofer & MM Davis (2007) Adult fat intake associated with the presence of children in households: findings from NHANES III. J Am Board Fam Med 20, 915.

27 V Burke , LJ Beilin , D Dunbar , et al. (2004) Changes in health-related behaviours and cardiovascular risk factors in young adults: associations with living with a partner. Prev Med 39, 722730.

28 A Drewnowski (2004) Obesity and the food environment: dietary energy density and diet costs. Am J Prev Med 27, 3 Suppl. 1, 154162.

29 DA Booth , AJ Blair , VJ Lewis , et al. (2004) Patterns of eating and movement that best maintain reduction in overweight. Appetite 43, 277283.

30 WL Wrieden , AS Anderson , PJ Longbottom , et al. (2007) The impact of a community-based food skills intervention on cooking confidence, food preparation methods and dietary choices – an exploratory trial. Public Health Nutr 10, 203211.

31 M Stead , M Caraher & A Anderson (2004) Confident, fearful and hopeless cooks: findings from the development of a food-skills initiative. Br Food J 106, 274287.

32 JF Guthrie , B-H Lin & E Frazao (2002) Role of food prepared away from home in the American diet, 1977–78 versus 1994–96: changes and consequences. J Nutr Educ Behav 34, 140150.

33 SH Schwartz , G Melech , A Lehmann , et al. (2001) Extending the cross-cultural validity of the theory of basic human values with a different method of measurement. J Cross Cult Psychol 32, 519542.

34 A Worsley (2006) Lay people's views of school food policy options: associations with confidence, personal values and demographics. Health Educ Res 21, 848861.

36 A Worsley , ML Wahlqvist , FS Dalais , et al. (2002) Characteristics of soy bread users and their beliefs about soy products. Asia Pac J Clin Nutr 11, 5155.

37 M Lindeman & M Verkasalo (2005) Measuring values with the Short Schwartz's Value Survey. J Personal Assess 85, 170178.

40 ST Lanza , LM Collins , DR Lemmon , et al. (2007) PROC LCA: a SAS procedure for latent class analysis. Struct Eq Model 14, 671694.

41 LA Goodman (1974) Exploratory latent structure analysis using both identifiable and unidentifiable models. Biometrika 61, 215231.

43 H Akaike (1987) Factor analysis and AIC. Psychometrika 52, 317332.

44 G Schwarz (1978) Estimating the dimension of a model. Ann Stat 6, 461464.

45 S Sclove (1987) Application of model-selection criteria to some problems in multivariate analysis. Psychometrika 52, 333343.

47 G McLachlan & D Peel (2000) Finite Mixture Models. New York: Wiley.

48 KL Nylund , T Asparouhov & BO Muthén (2007) Deciding on the number of classes in latent class analysis and growth mixture modeling: a Monte Carlo simulation study. Struct Eq Model 14, 535569.

49 V Ramaswamy , WS Desarbo , DJ Reibstein , et al. (1993) An empirical pooling approach for estimating marketing mix elasticities with PIMS data. Market Sci 12, 103124.

50 G-H Huang & K Bandeen-Roche (2004) Building an identifiable latent class model with covariate effects on underlying and measured variables. Psychometrika 69, 532.

51 E Lea & A Worsley (2003) Benefits and barriers to the consumption of a vegetarian diet in Australia. Public Health Nutr 6, 505511.

52 EJ Lea , D Crawford & A Worsley (2006) Public views of the benefits and barriers to the consumption of a plant-based diet. Eur J Clin Nutr 60, 828837.

53 GS Savige (2002) Can food variety add years to your life? Asia Pac J Clin Nutr 11, Suppl. 3, S637S641.

54 S Brownie (2006) Why are elderly individuals at risk of nutritional deficiency? Int J Nurs Pract 12, 110118.

55 SB Roberts , CL Hajduk , NC Howarth , et al. (2005) Dietary variety predicts low body mass index and inadequate macronutrient and micronutrient intakes in community-dwelling older adults. J Gerontol A: Biol Sci Med Sci 60, 613621.

56 KB Michels & A Wolk (2002) A prospective study of variety of healthy foods and mortality in women. Int J Epidemiol 31, 847854.

61 M Caraher , P Dixon , T Lang , et al. (1999) The state of cooking in England: the relationship of cooking skills to food choice. Br Food J 101, 590609.

62 S Fordyce-Voorham (2010) Identification of essential food skills for skill-based healthful eating programs in secondary schools. J Nutr Educ Behav 43, 116122.

63 G Hughes , KM Bennett & MM Hetherington (2004) Old and alone: barriers to healthy eating in older men living on their own. Appetite 43, 269276.

64 A Worsley , WC Wang & W Hunter (2010) Baby boomers' food shopping habits. Relationships with demographics and personal values. Appetite 55, 466472.

65 A Pan , Q Sun , AM Bernstein , et al. (2011) Red meat consumption and risk of type 2 diabetes: 3 cohorts of US adults and an updated meta-analysis. Am J Clin Nutr 94, 10881096.

69 LC Wilson , A Alexander & M Lumbers (2004) Food access and dietary variety among older people. Int J Ret Distrib Manage 32, 109122.

Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

British Journal of Nutrition
  • ISSN: 0007-1145
  • EISSN: 1475-2662
  • URL: /core/journals/british-journal-of-nutrition
Please enter your name
Please enter a valid email address
Who would you like to send this to? *



Full text views

Total number of HTML views: 4
Total number of PDF views: 49 *
Loading metrics...

Abstract views

Total abstract views: 146 *
Loading metrics...

* Views captured on Cambridge Core between September 2016 - 24th June 2017. This data will be updated every 24 hours.