Natalie A Strobel1,2,3, Alice Richardson2, Carrington C J Shepherd4,3, Kimberley E McAuley1, Rhonda Marriott3, Karen M Edmond1, Daniel R McAullay1. 1. Medical School, The University of Western Australia, Perth, WA, Australia. 2. National Centre for Epidemiology & Population Health, Research School of Population Health, Australian National University, Canberra, Australia. 3. Ngangk Yira Aboriginal Health and Social Equity Research Centre, Murdoch University, Perth, WA, Australia. 4. Telethon Kids Institute, Crawley, WA, Australia.
Abstract
BACKGROUND: The Australian Early Development Census (AEDC) provides a measure of early child development upon school entry. Understanding which combination of factors influences Aboriginal child neurodevelopment is important to inform policy and practice. OBJECTIVE: The primary objective was to use latent class analysis (LCA) to model AEDC profiles and identify the highest need profiles. The secondary objective was to determine the associations of these high need profiles on the likelihood of a child becoming developmentally vulnerable. METHODS: We designed a prospective population-based birth cohort study (n = 2715) using linked data sets with information on Aboriginal cohort children, and their mothers and siblings in Western Australia. Specific developmental indicators in the 2009 and 2012 AEDC were used to assess developmental vulnerability. LCA methods were used to determine need profiles and their association with developmental vulnerability. RESULTS: 49.3% of Aboriginal children were vulnerable on at least one developmental domain, and 37.5% were vulnerable on two or more domains. LCA found six unique profiles. High needs family, High needs young mother, and Preterm infant comprised 42% of the cohort and were considered to have high need configurations. These groups were at least 1.7 times as likely to have children who had at least one or two developmental vulnerabilities compared with the Healthy family group. CONCLUSION: Many Aboriginal children in Western Australia enter school with at least one developmental vulnerability. This study highlights a range of unique profiles that can be used to empower Aboriginal families for change and develop targeted programmes for improving the early development of young Aboriginal children.
BACKGROUND: The Australian Early Development Census (AEDC) provides a measure of early child development upon school entry. Understanding which combination of factors influences Aboriginal child neurodevelopment is important to inform policy and practice. OBJECTIVE: The primary objective was to use latent class analysis (LCA) to model AEDC profiles and identify the highest need profiles. The secondary objective was to determine the associations of these high need profiles on the likelihood of a child becoming developmentally vulnerable. METHODS: We designed a prospective population-based birth cohort study (n = 2715) using linked data sets with information on Aboriginal cohort children, and their mothers and siblings in Western Australia. Specific developmental indicators in the 2009 and 2012 AEDC were used to assess developmental vulnerability. LCA methods were used to determine need profiles and their association with developmental vulnerability. RESULTS: 49.3% of Aboriginal children were vulnerable on at least one developmental domain, and 37.5% were vulnerable on two or more domains. LCA found six unique profiles. High needs family, High needs young mother, and Preterm infant comprised 42% of the cohort and were considered to have high need configurations. These groups were at least 1.7 times as likely to have children who had at least one or two developmental vulnerabilities compared with the Healthy family group. CONCLUSION: Many Aboriginal children in Western Australia enter school with at least one developmental vulnerability. This study highlights a range of unique profiles that can be used to empower Aboriginal families for change and develop targeted programmes for improving the early development of young Aboriginal children.
Authors: Madeleine Batchelor; Stephanie J Brown; Karen Glover; Deirdre Gartland Journal: Int J Environ Res Public Health Date: 2021-12-01 Impact factor: 3.390