Literature DB >> 30012352

Dietary patterns of Australian children at three and five years of age and their changes over time: A latent class and latent transition analysis.

Erin Pitt1, Cate M Cameron2, Lukar Thornton3, Danielle Gallegos4, Ania Filus5, Shu-Kay Ng6, Tracy Comans7.   

Abstract

Consuming a healthy diet characterised by a variety of nutritious foods is essential for promoting and maintaining health and wellbeing, yet the diets of Australian children continue to fall well short of national healthy eating recommendations. This research endeavours to identify patterns of dietary intake in Australian children at three and five years of age and investigate associations between early childhood dietary patterns and socio-economic and demographic indicators and Body Mass Index (BMI), as well as identify changes in children's dietary patterns over time. Cross-sectional dietary patterns were derived for 1565 and 631 children aged three and five years, respectively using Latent Class Analysis (LCA), with changes over time analysed with Latent Transition Analysis (LTA). Demographic variables of interest included child sex, parental age, family status, and use of childcare services and socio-economic variables included education, income and employment status. Three patterns of dietary intake were identified at three years (Highly Unhealthy, Healthier and Moderately Unhealthy) and two patterns at five years (Unhealthy and Healthier). Children with younger mothers, working mothers, fathers with a higher BMI and living in a two-carer household were more likely to have unhealthy eating patterns at three years, and children with working mothers and living in a two-carer household were more likely to have unhealthy patterns of dietary intake at five years. Approximately one eighth of the sample transitioned from the healthier to unhealthy pattern of dietary intake from three to five years. The quality of Australian children's diets appears to be declining through the early childhood years, continuing to highlight the importance of nutrition policies and interventions targeted towards the early years of life.
Copyright © 2018. Published by Elsevier Ltd.

Entities:  

Keywords:  Australia; Dietary patterns children; Latent class analysis; Latent transition analysis; Socio-economic status

Mesh:

Year:  2018        PMID: 30012352     DOI: 10.1016/j.appet.2018.07.008

Source DB:  PubMed          Journal:  Appetite        ISSN: 0195-6663            Impact factor:   3.868


  5 in total

1.  Child Nutrition Patterns Are Associated with Primary Dentition Dental Caries.

Authors:  Erin E Tilton; Martha Ann Keels; Miguel A Simancas-Pallares; Rocío B Quiñonez; Michael W Roberts; Andrea G Ferreira Zandona; Kimon Divaris
Journal:  Pediatr Dent       Date:  2021-05-15       Impact factor: 1.874

2.  Association between Sociodemographic Factors and Dietary Patterns in Children Under 24 Months of Age: A Systematic Review.

Authors:  Claudia Gutiérrez-Camacho; Lucia Méndez-Sánchez; Miguel Klünder-Klünder; Patricia Clark; Edgar Denova-Gutiérrez
Journal:  Nutrients       Date:  2019-08-26       Impact factor: 5.717

3.  Exploring the Provider-Level Socio-Demographic Determinants of Diet Quality of Preschool-Aged Children Attending Family Childcare Homes.

Authors:  Alison Tovar; Patricia Markham Risica; Andrea Ramirez; Noereem Mena; Ingrid E Lofgren; Kristen Cooksey Stowers; Kim M Gans
Journal:  Nutrients       Date:  2020-05-11       Impact factor: 5.717

Review 4.  Conceptualizing and Measuring Appetite Self-Regulation Phenotypes and Trajectories in Childhood: A Review of Person-Centered Strategies.

Authors:  Alan Russell; Rebecca M Leech; Catherine G Russell
Journal:  Front Nutr       Date:  2021-12-22

5.  Study Protocol for the Evaluation of "SuperFIT", a Multicomponent Nutrition and Physical Activity Intervention Approach for Preschools and Families.

Authors:  Ilona van de Kolk; Sanne M P L Gerards; Lisa S E Harms; Stef P J Kremers; Angela M H S van Dinther-Erkens; Monique Snellings; Jessica S Gubbels
Journal:  Int J Environ Res Public Health       Date:  2020-01-17       Impact factor: 3.390

  5 in total

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