Children’s early development plays a vital role for maintaining healthy lives and influences future outcomes. It is also heavily affected by community factors which vary geographically. Direct methods do not provide a comprehensive picture of this variation, especially for areas with sparse populations and low data coverage. In the context of Australia, the Australian Early Development Census (AEDC) provides a measure of early child development upon school entry. There are two primary aims of this study: (i) provide improved prevalence estimates of children who are considered as developmentally vulnerable in regions across Australia; (ii) ascertain how social-economic disadvantage partly explains the spatial variation. We used Bayesian spatial hierarchical models with the Socio-economic Indexes for Areas (SEIFA) as a covariate to provide improved estimates of all 335 SA3 regions in Australia. The study included 308,953 children involved in the 2018 AEDC where 21.7% of them were considered to be developmentally vulnerable in at least one domain. There are five domains of developmental vulnerability—physical health and wellbeing; social competence; emotional maturity; language and cognitive skills; and communication and general knowledge. There are significant improvements in estimation of the prevalence of developmental vulnerability through incorporating the socio-economic disadvantage in an area. These improvements persist in all five domains—the largest improvements occurred in the Language and Cognitive Skills domain. In addition, our results reveal that there is an important geographical dimension to developmental vulnerability in Australia. Sparsely populated areas in sample surveys lead to unreliable direct estimates of the relatively small prevalence of child vulnerability. Bayesian spatial modelling can account for the spatial patterns in childhood vulnerability while including the impact of socio-economic disadvantage on geographic variation. Further investigation, using a broader range of covariates, could shed more light on explaining this spatial variation.

中文翻译：

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澳大利亚地区幼儿发展的贝叶斯空间模型

儿童的早期发育对于维持健康的生活并影响未来的结果起着至关重要的作用。它还受地域不同的社区因素的严重影响。直接方法无法提供这种变化的全面描述，尤其是对于人口稀少和数据覆盖率较低的地区。在澳大利亚的背景下，澳大利亚早期发展普查（AEDC）提供了入学后儿童早期发育的衡量指标。这项研究的两个主要目标是：（i）对整个澳大利亚地区被认为具有发展脆弱性的儿童的患病率进行评估。（ii）确定社会经济劣势如何部分解释了空间变化。我们使用贝叶斯空间层次模型与区域社会经济指数（SEIFA）作为协变量，以提供对澳大利亚所有335个SA3地区的改进估计。该研究包括308,953名参与2018年AEDC的儿童，其中21.7％的儿童被认为在至少一个领域内处于发育脆弱状态。发育脆弱性有五个领域–身体健康和福祉；社会能力 情绪成熟；语言和认知能力；以及沟通和常识。通过纳入一个地区的社会经济劣势，对发展脆弱性患病率的估计有了显着改善。这些改进在所有五个领域中都将持续存在-最大的改进发生在语言和认知技能领域。此外，我们的结果表明，澳大利亚的发展脆弱性具有重要的地理意义。抽样调查中人口稀少的地区导致对儿童脆弱性患病率相对较小的直接估计不可靠。贝叶斯空间模型可以解释儿童脆弱性的空间格局，同时包括社会经济劣势对地理变异的影响。使用更广泛的协变量进行进一步的研究，可以为解释这种空间变化提供更多的启示。贝叶斯空间模型可以解释儿童脆弱性的空间格局，同时包括社会经济劣势对地理变异的影响。使用更广泛的协变量进行进一步的研究，可以为解释这种空间变化提供更多的启示。贝叶斯空间模型可以解释儿童脆弱性的空间格局，同时包括社会经济劣势对地理变异的影响。使用更广泛的协变量进行进一步的研究，可以为解释这种空间变化提供更多的启示。