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

Rebecca M Leech,Sarah A Mcnaughton,Carol J Boushey

doi:10.1186/s12966-021-01115-w

Abstract

BackgroundThe 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.MethodsDietary 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).ResultsFive 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).ConclusionsWe 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.

Highlights

A poor quality diet is a major modifiable contributor to obesity and its long-term effects, including chronic disease death and disability, globally [1]
The emphasis by dietary guidelines on foods that make up the whole diet, rather than on individual nutrients, reflects the increasing body of evidence that has accrued over recent decades in relation to the health effects of specific food groups and dietary patterns [5, 6]
To understand the potential use of latent variable mixture modelling (LVMM) for assessing meal-specific associations with obesity and health outcomes, we examined the whether the resulting breakfast profiles varied by time of consumption and participant characteristics, including adiposity

Summary

Introduction

A poor quality diet is a major modifiable contributor to obesity and its long-term effects, including chronic disease death and disability, globally [1]. Instead, they select combinations of foods at eating occasions, including meals and snacks. The patterning of food intake at eating occasions, or eating patterns, are an integral, yet poorly understood, intermediary step to achieving a healthy dietary pattern and preventing obesity and its complications [7]. An understanding of eating patterns can inform the development and translation of dietary guidelines by helping to contextualise advice and provide practical guidance on what foods should be consumed more often, in which combinations and at which times [10, 11]. The patterning of food intake at eating occasions is a poorly understood, albeit important, step towards achieving a healthy dietary pattern. We applied a latent variable mixture modelling (LVMM) approach to understand how foods are consumed in relation to each other at breakfast

Methods

Results

Conclusion