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What do Australian adults eat for breakfast? A latent variable mixture modelling approach for understanding combinations of foods at eating occasions

Leech, Rebecca M, Boushey, Carol J and McNaughton, Sarah A 2021, What do Australian adults eat for breakfast? A latent variable mixture modelling approach for understanding combinations of foods at eating occasions, International Journal of Behavioral Nutrition and Physical Activity, vol. 18, no. 1, pp. 1-16, doi: 10.1186/s12966-021-01115-w.

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Title What do Australian adults eat for breakfast? A latent variable mixture modelling approach for understanding combinations of foods at eating occasions
Author(s) Leech, Rebecca MORCID iD for Leech, Rebecca M orcid.org/0000-0002-5333-0164
Boushey, Carol J
McNaughton, Sarah AORCID iD for McNaughton, Sarah A orcid.org/0000-0001-5936-9820
Journal name International Journal of Behavioral Nutrition and Physical Activity
Volume number 18
Issue number 1
Article ID 46
Start page 1
End page 16
Total pages 16
Publisher BioMed Central
Place of publication London, Eng.
Publication date 2021
ISSN 1479-5868
1479-5868
Keyword(s) 24-h recall
Breakfast
Dietary patterns
Eating occasions
Eating patterns
Life Sciences & Biomedicine
Nutrition & Dietetics
Physiology
Science & Technology
Summary Background The patterning of food intake at eating occasions is a poorly understood, albeit important, step towards achieving a healthy dietary pattern. However, to capture the many permutations of food combinations at eating occasions, novel analytic approaches are required. We applied a latent variable mixture modelling (LVMM) approach to understand how foods are consumed in relation to each other at breakfast. Methods Dietary intake at breakfast (n = 8145 occasions) was assessed via 24-h recall during the 2011–12 Australian National Nutrition and Physical Activity Survey (n = 3545 men and n = 4127 women, ⩾19 y). LVMM was used to determine breakfast food profiles based on 35 food group variables, reflecting compliance with Australian Dietary Guidelines. F and adjusted-chi2 tests assessed differences in timing of consumption and participant characteristics between the breakfast profiles. Regression models, adjusted for covariates, were used to examine associations between breakfast food profiles and objective adiposity measures (BMI and waist circumference). Results Five distinct profiles were found. Three were similar for men and women. These were labelled: “Wholegrain cereals and milks” (men: 16%, women: 17%), “Protein-foods” (men and women: 11%) and “Mixed cereals and milks” (men: 33%, women: 37%). Two “Breads and spreads” profiles were also found that were differentiated by their accompanying beverages (men) or type of grain (women). Profiles were found to vary by timing of consumption, participant characteristics and adiposity indicators. For example, the “Protein-foods” profile occurred more frequently on weekends and after 9 am. Men with a “Bread and spreads (plus tea/coffee)” profile were older (P < 0.001) and had lower income and education levels (P < 0.05), when compared to the other profiles. Women with a “Protein-foods” profile were younger (P < 0.001) and less likely to be married (P < 0.01). Both men and women with a “Wholegrain cereals and milks” profile had the most favourable adiposity estimates (P < 0.05). Conclusions We identified five breakfast food profiles in adults that varied by timing of consumption, participant characteristics and adiposity indicators. LVMM was a useful approach for capturing the complexity of food combinations at breakfast. Future research could collect contextual information about eating occasions to understand the complex factors that influence food choices.
Language eng
DOI 10.1186/s12966-021-01115-w
Indigenous content off
Field of Research 11 Medical and Health Sciences
13 Education
HERDC Research category C1 Refereed article in a scholarly journal
Grant ID NHMRC 1175250
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30149814

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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.