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Jurisdictional, socioeconomic and gender inequalities in child health and development:

Early child development may have important consequences for inequalities in health and well-being. This paper explores population level patterns of child...

Authors:
Brinkman, S. A.; Gialamas, A.; Rahman, A.; Mittinty, M. N.; Gregory, T. A.; Silburn, S.; Goldfeld, S.; Zubrick, S. R.; et al.

Authors notes:
BMJ Open. 2012;2(5):e001075.1-14 

Keywords:
child development, inequalities, health, well-being, Australian jurisdictions, socioeconomic, demographic

Abstract
Early child development may have important consequences for inequalities in health and well-being. This paper explores population level patterns of child development across Australian jurisdictions, considering socioeconomic and demographic characteristics.

Census of child development across Australia. Setting and participants: Teachers complete a developmental checklist, the Australian Early Development Index (AEDI), for all children in their first year of full-time schooling. Between May and July 2009, the AEDI was collected by 14 628 teachers in primary schools (government and non-government) across Australia, providing information on 261 147 children (approximately 97.5% of the estimated 5-year-old population).

Level of developmental vulnerability in Australian children for five developmental domains: physical well-being, social competence, emotional maturity, language and cognitive skills and communication skills and general knowledge.

The results show demographic and socioeconomic inequalities in child development as well as within and between jurisdiction inequalities. The magnitude of the overall level of inequality in child development and the impact of covariates varies considerably both between and within jurisdiction by sex.

For example, the difference in overall developmental vulnerability between the best-performing and worst-performing jurisdiction is 12.5% for males and 7.1% for females. Levels of absolute social inequality within jurisdictions range from 8.2% for females to 12.7% for males.

The different mix of universal and targeted services provided within jurisdictions from pregnancy to age 5 may contribute to inequality across the country. These results illustrate the potential utility of a developmental census to shed light on the impact of differences in universal and targeted services to support child development by school entry