Clustering of socio-demographic factors and their association with the mental health of Australian children and adolescents: A latent class analysis
Authors: Afroz Nahida , Kabir Enamul , Alam Khorshed 
Published: July 2022

Abstract
Background: Previous studies have shown a relationship between socioeconomic and demographic variables with the mental health of children and adolescents. However, while utilizing a nationally representative sample, no study has yet been conducted on a cluster-based connection or model-based cluster analysis of socio-economic and demographic characteristics with mental health. This study aims to identify the cluster of the items representing the socio-demographic characteristics of Australian children and adolescents aged 11-17 years by using latent class analysis and examining the associations with their mental health.Methods: This study involved children and adolescents aged 11–17 (n = 3152) from the Young Minds Matter (YMM): The Second Australian Child and Adolescent Survey of Mental Health and Wellbeing. The YMM is a nationwide cross-sectional study in which data was obtained from children and adolescents, as well as from their parents/carers. Latent class analysis was performed based on nine socio-demographic factors related to Individual level (age, sex), Household level (regions, family blending, and parents living status in the household), and Socio-economic level (primary carer education, income, occupation, Index of relative socio-economic advantage and disadvantage [IRSAD]) variables. Bivariate logistic regressions were used to examine associations between identified classes and mental disorders.Results: Based on various model selection criteria, this study identified five classes. Class 1 (working/poor class), 2 (lower middle class), 3 (mobile middle class), 4 (growing wealthy class) and 5 (wealthy class) represents 18.7%, 16.7%, 27.7%, 13.5% and 23.4% of the total sample respectively. Most of the households of class 1 and class 5 were from the underprivileged and most privileged groups respectively. Results of binary logistic regression model showed that, in unadjusted latent classes, children and adolescents from the wealthy class (OR: 0.2938, 95% CI: 0.2187–0.3947) were 71 percent less likely to suffer from mental illness than their working-class counterparts. Lower middle class (OR: 0.4455, 95% CI: 0.3170–0.6260), mobile middle class (OR: 0.3227, 95% CI: 0.2405–0.4329) and growing wealthy class (OR: 0.5079, 95% CI: 0.3520–0.7329) also had lower odds of mental disorder than working class. The majority of the members of the ‘growing wealthy class’ were from the socio-economically advantaged group than the lower and mobile middle class, but their family functioning (interactions and relationships within the family) was very poor. As a result, mental disorders of children and adolescents of that growing wealthy class were respectively 1.14 and 1.57 times higher compared to that of lower and mobile middle class.Conclusions: Among five latent classes, adolescents with lower socio-economic status and poor family functioning were exposed to a higher risk of developing mental health problems. The findings suggest that the reduction of socioeconomic inequalities and improving family interactions might help to reduce the mental health problems of children and adolescents’.