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  • Confirmation of Candidature - The Interplay Between Maternal and Child Factors in Childhood and Adolescent Obesity: A Longitudinal Analysis from Australia

Confirmation of Candidature - The Interplay Between Maternal and Child Factors in Childhood and Adolescent Obesity: A Longitudinal Analysis from Australia

Candidate : Nasrin Begum
When
20 SEP 2024
8.00 AM - 9.30 AM
Where
Online via Zoom

Obesity is a major public issue that affects both children and adolescents, with its prevalence increasing globally. Previous studies have examined the relationship between lifestyle, socio- demographic and health-related behaviours in Australian children and their association with child obesity. As per our knowledge, no studies have applied cluster analysis to examine maternal characteristics (health, lifestyle, diet and socio-demographics factors) during pregnancy and childhood characteristics (birth weight, growth patterns, diet, and physical activity) and their association with childhood obesity. This study aims to identify the clusters based on maternal characteristics during pregnancy and childhood characteristics and assess their association with childhood obesity. Furthermore, this study also examines the influence of theses clusters on childhood obesity by sex across different stages of childhood, ranging from ages 2 to 15. The Longitudinal 精东传媒app of Australian Children (LSAC) data will be used to perform this research which will be taken from different cohorts (waves 1 to wave 8). Latent class analysis (LCA) will be employed to identify the cluster patterns based on maternal characteristics during pregnancy and childhood characteristics. Various model selection criteria (Akaike Information Criterion, Bayesian Information Criterion, adjusted Bayesian Information Criterion, and Likelihood Ratio) will be used to determine optimal clusters. Chi-square analysis will be conducted to examine the associations between the identified clusters and childhoods obesity at different ages (2 to 15) and gender. Moreover, multinomial logistics regression model will be employed to examine the impact of these clusters on obesity over different waves. The findings of this study will offer a novel perspective on LCA by utilizing various maternal and child characteristics. This approach helps to identify the most influential groups concerning childhood obesity. Furthermore, emphasizing the importance of maternal health and promoting targeted campaigns for improving maternal lifestyle and dietary habits can be crucial in addressing and preventing childhood obesity.

For more information, please email the Graduate Research School or phone 0746 311088.