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Socioeconomic disparities are main determinants of health outcomes inequalities in children. In turn, the prevalence of chronic diseases among children and adolescents is increasing in the world. Previous studies have investigated that how socioeconomic status, socio-demographic factors, and children characteristics related to chronic diseases, including using data from Australian studies. However, the multifaced relationship between SES, other factors and healthcare utilization has not been clearly explored through using advanced models with mediational and intersectional approaches and spatial analysis. So, the aim of thesis is to explore the impact of socioeconomic disparities on healthcare utilization and long-term Health Trajectories in Australian Children. Especially, this study aims to explore how these factors have impact on childhood chronic diseases like allergic diseases, hay fever, eczema, and asthma mental illness, ranging from ages 0 to 18. Data from the Longitudinal Study of Australian Children (LSAC) will be used to perform this research which will be taken from different cohorts (waves 1 to wave 9). This study will have a new insight on the multifaced r/ship b/n socioeconomic status, health care utilization and children's chronic diseases. This study will help to identify the most vulnerable groups concerning childhood chronic diseases. This study will explore the main factors for long-term health outcomes in Australian children and adolescents. Moreover, this study will have a result in actionable recommendations for policymakers on how to structure childhood and adolescents' health programs guidelines to reduce the risk of chronic disease among children and adolescents. 

Keywords: Children, adolescents; Latent class analysis; Childhood chronic diseases, Structural Equation Modelling, Latent class analysis, machine learning

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