Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/99974
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dc.contributorDepartment of Applied Social Sciences-
dc.creatorWong, RSen_US
dc.creatorTung, KTSen_US
dc.creatorRao, Nen_US
dc.creatorChan, KLen_US
dc.creatorFu, KWen_US
dc.creatorYam, JCen_US
dc.creatorTso, WWYen_US
dc.creatorWong, WHSen_US
dc.creatorLum, TYSen_US
dc.creatorWong, ICKen_US
dc.creatorIp, Pen_US
dc.date.accessioned2023-07-26T05:49:34Z-
dc.date.available2023-07-26T05:49:34Z-
dc.identifier.issn1661-7827en_US
dc.identifier.urihttp://hdl.handle.net/10397/99974-
dc.language.isoenen_US
dc.publisherMDPIen_US
dc.rights© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Wong RS, Tung KTS, Rao N, Chan KL, Fu K-W, Yam JC, Tso WWY, Wong WHS, Lum TYS, Wong ICK, et al. Using Latent Class Analyses to Examine Health Disparities among Young Children in Socially Disadvantaged Families during the COVID-19 Pandemic. International Journal of Environmental Research and Public Health. 2022; 19(13):7893 is available at https://doi.org/10.3390/ijerph19137893.en_US
dc.subjectCOVID-19en_US
dc.subjectPreschooleren_US
dc.subjectHealth disparityen_US
dc.subjectLatent class analysisen_US
dc.subjectFamily hardshipen_US
dc.titleUsing latent class analyses to examine health disparities among young children in socially disadvantaged families during the COVID-19 pandemicen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume19en_US
dc.identifier.issue13en_US
dc.identifier.doi10.3390/ijerph19137893en_US
dcterms.abstractRising income inequality is strongly linked to health disparities, particularly in regions where uneven distribution of wealth and income has long been a concern. Despite emerging evidence of COVID-19-related health inequalities for adults, limited evidence is available for children and their parents. This study aimed to explore subtypes of families of preschoolers living in the disadvantaged neighborhoods of Hong Kong based on patterns of family hardship and to compare their patterns of parenting behavior, lifestyle practices, and wellbeing during the COVID-19 pandemic. Data were collected from 1338 preschoolers and their parents during March to June 2020. Latent class analysis was performed based on 11 socioeconomic and disease indicators. Multivariate logistic regressions were used to examine associations between identified classes and variables of interest during the COVID-19 pandemic. Four classes of family hardship were identified. Class 1 (45.7%) had the lowest disease and financial burden. Class 2 (14.0%) had the highest financial burden. Class 3 (5.9%) had the highest disease burden. Class 4 (34.5%) had low family income but did not receive government welfare assistance. Class 1 (low hardship) had lower risks of child maltreatment and adjustment problems than Class 2 (poverty) and Class 3 (poor health). However, children in Class 1 (low hardship) had higher odds of suffering psychological aggression and poorer physical wellbeing than those in Class 4 (low income), even after adjusting for child age and gender. The findings emphasize the need to adopt flexible intervention strategies in the time of large disease outbreak to address diverse problems and concerns among socially disadvantaged families.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationInternational journal of environmental research and public health, July 2022, v. 19, no. 13, 7893en_US
dcterms.isPartOfInternational journal of environmental research and public healthen_US
dcterms.issued2022-07-
dc.identifier.scopus2-s2.0-85132811548-
dc.identifier.pmid35805550-
dc.identifier.eissn1660-4601en_US
dc.identifier.artn7893en_US
dc.description.validate202307 bcch-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOS-
dc.description.fundingSourceRGCen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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