4.3 Article

Data to Decisions: Methods to Create Neighbourhood Built Environment Indicators Relevant for Early Childhood Development

Publisher

MDPI
DOI: 10.3390/ijerph19095549

Keywords

built environment; data linkage; early childhood development; neighbourhood; indicators

Funding

  1. Social Research Centre
  2. Australian Institute of Family Studies

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Healthy development in the early years is crucial for children's ongoing development. This study examines the association between neighbourhood-built environment characteristics and health outcomes in children. Using data linkage techniques, a dataset of neighbourhood-built environment measures was created for children in 21 Australian cities. This dataset is the first of its kind worldwide and allows for comparisons between different contexts, providing valuable insights for intervention strategies.
Healthy development in the early years lays the foundations for children's ongoing physical, emotional, and social development. Children develop in multiple contexts, including their local neighbourhood. Neighbourhood-built environment characteristics, such as housing, walkability, traffic exposure, availability of services, facilities, and parks, are associated with a range of health and wellbeing outcomes across the life course, but evidence with early years' outcomes is still emerging. Data linkage techniques were used to assemble a dataset of spatial (objectively-measured) neighbourhood-built environment (BE) measures linked to participant addresses in the 2015 Australian Early Development Census (AEDC) for children living in the 21 most populous urban and regional Australian cities (n = 235,655) to help address this gap. This paper describes the methods used to develop this dataset. This linked dataset (AEDC-BE) is the first of its kind worldwide, enabling opportunities for identifying which features of the built environment are associated with ECD across Australia at scale, allow comparisons between diverse contexts, and the identification of where best to intervene. National data coverage provides statistical power to model real-world complexities, such as differences by city, state/territory, and remoteness. The neighbourhood-built environment can be modified by policy and practice at scale, and has been identified as a way to help reduce inequitable early childhood development outcomes.

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