Evidence map›Paper›PMID 37200385›Full record

ArticlePloS one2023

A latent class analysis of the socio-demographic factors and associations with mental and behavioral disorders among Australian children and adolescents.

Nahida Afroz, Enamul Kabir, Khorshed Alam

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Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

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9citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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9 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Nahida AfrozDepartment of Statistics, Faculty of Science, Comilla University, Cumilla, Bangladesh.ORCID 0000-0003-0323-3523
Enamul KabirSchool of Mathematics, Physics, and Computing, Faculty of Health, Engineering and Sciences, University of Southern Queensland, Toowoomba, Queensland, Australia.
Khorshed AlamSchool of Business, Faculty of Business, Education, Law & Arts, and Centre for Health Research, University of Southern Queensland, Toowoomba, Queensland, Australia.ORCID 0000-0003-2232-0745

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPrevious studies have shown a relationship between socio-demographic variables and the mental health of children and adolescents. However, no research has been found on a model-based cluster analysis of socio-demographic characteristics with mental health. This study aimed 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 (LCA) and examining the associations with their mental health.

methodsChildren and adolescents aged 11-17 years (n = 3152) were considered from the 2013-2014 Young Minds Matter: The Second Australian Child and Adolescent Survey of Mental Health and Wellbeing. LCA was performed based on relevant socio-demographic factors from three levels. Due to the high prevalence of mental and behavioral disorders, the generalized linear model with log-link binomial family (log-binomial regression model) was used to examine the associations between identified classes, and the mental and behavioral disorders of children and adolescents.

resultsThis study identified five classes based on various model selection criteria. Classes 1 and 4 presented the vulnerable class carrying the characteristics of "lowest socio-economic status and non-intact family structure" and "good socio-economic status and non-intact family structure" respectively. By contrast, class 5 indicated the most privileged class carrying the characteristics of "highest socio-economic status and intact family structure". Results from the log-binomial regression model (unadjusted and adjusted models) showed that children and adolescents belonging to classes 1 and 4 were about 1.60 and 1.35 times more prevalent to be suffering from mental and behavioral disorders compared to their class 5 counterparts (95% CI of PR [prevalence ratio]: 1.41-1.82 for class 1; 95% CI of PR [prevalence ratio]: 1.16-1.57 for class 4). Although children and adolescents from class 4 belong to a socio-economically advantaged group and shared the lowest class membership (only 12.7%), the class had a greater prevalence (44.1%) of mental and behavioral disorders than did class 2 ("worst education and occupational attainment and intact family structure") (35.2%) and class 3 ("average socio-economic status and intact family structure") (32.9%).

conclusionsAmong the five latent classes, children and adolescents from classes 1 and 4 have a higher risk of developing mental and behavioral disorders. The findings suggest that health promotion and prevention as well as combating poverty are needed to improve mental health in particular among children and adolescents living in non-intact families and in families with a low socio-economic status.

Indexed as

Neurodevelopmental DisordersSocial ClassAdolescentAustralasian PeopleAustraliaChildHumansLatent Class AnalysisPrevalenceSociodemographic Factors

Identifiers

PMID37200385
PMCPMC10194994

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.