Better understanding trajectories of child development: opportunities for data linkage with the Australian Early Development Index (AEDI)
Brinkman, Sally, McDermott, Robyn, and Lynch, John (2010) Better understanding trajectories of child development: opportunities for data linkage with the Australian Early Development Index (AEDI). Public Health Bulletin South Australia, 7 (3). pp. 7-10.
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Abstract
[Extract] Research shows that many challenges in adult society such as obesity, mental health problems, heart disease and other chronic conditions, criminality, and competence in literacy and numeracy may have their roots in early childhood.1,2 Federal and state governments are therefore increasing investment in early childhood with the aim of improving future health and human capability formation. On an international scale, the World Bank’s current portfolio of early child development (ECD) projects totals US$1.7 billion in cumulative lending, the largest amount contributed in the global donor community. The United Nations Children’s Fund (UNICEF) also contributes billions of dollars annually to ECD initiatives in the developing countries.1The global challenge to improve ECD is hampered without an instrument that can be compared overtime and place to evaluate programs and compare their impacts both within and across countries. Acknowledgment of the lack of an internationally comparable indicator for ECD has been highlighted in a series of papers in The Lancet3–5, as well as in the 2010 Education For All Global Monitoring Report by the United Nations Educational, Scientific and Cultural Organization (UNESCO).6 Implications for monitoring child development are also highlighted by the United Nations Convention on the Rights of the Child7—each of the signed countries are responsible for providing children with the opportunities necessary to develop physical, cognitive, social and emotional capacities in early life. In Australia the Federal Government has acknowledged these challenges by investing more than $23 million in the Australian Early Development Index (AEDI)8, and endorsing it as a National Progress Measure.9 Although the instrument was developed in Canada (as the Early Development Instrument (EDI)) in 199810, Australia started using the index in 200211 and was first to implement the instrument across the entire country.8The AEDI is the subject of a companion article in this issue of the Public Health Bulletin. The EDI is gaining attention as an internationally comparable population health and development measure for ECD, with the instrument now being used in 20 countries12 and endorsed by the World Bank and the United Nations.1 Part of its attraction is that the EDI is uniquely administered just like a census, and is a holistic measure covering five key child developmental domains (physical health and wellbeing, social competence, emotional maturity, language and cognitive skills, and communication skills and general knowledge).The AEDI has significant scope as an independent data source used in context with other geographically available social and demographic information together with local community knowledge. Repetitive use of the AEDI in successive cohorts enables monitoring of ECD across populations and time, as well as examination of trends for geographic areas. However, the investigation of risk and protective patterns in child development is generally undertaken using individual-level information—while the AEDI clearly shows a significant socioeconomic gradient in developmental vulnerability, there are still many children in middle-and upper-class Australia that are developmentally vulnerable. Although socioeconomics explains some of the variation in child development, there is still significant variation that requires better understanding of its complexities.8,13Linking various administrative datasets to the AEDI provides a potentially powerful person-specific longitudinal population-based dataset, which significantly increases our ability to investigate the complexities of developmental trajectories. Program and policy evaluation and economic models (such as the effectiveness of preventive interventions, which is traditionally hard to quantify) can also be investigated with such datasets.
Item ID: | 36811 |
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Item Type: | Article (Scholarly Work) |
ISSN: | 1449-485X |
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Date Deposited: | 21 Dec 2017 03:28 |
FoR Codes: | 11 MEDICAL AND HEALTH SCIENCES > 1117 Public Health and Health Services > 111706 Epidemiology @ 100% |
SEO Codes: | 92 HEALTH > 9205 Specific Population Health (excl. Indigenous Health) > 920599 Specific Population Health (excl. Indigenous Health) not elsewhere classified @ 100% |
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