PDF(Pubmed)
Abstract：
BACKGROUND: Asthma is the most common chronic respiratory illness among children in Australia. While childhood asthma prevalence varies by region, little is known about variations at the small geographic area level. Identifying small geographic area variations in asthma is critical for highlighting hotspots for targeted interventions. This study aimed to investigate small area-level variation, spatial clustering, and sociodemographic risk factors associated with childhood asthma prevalence in Australia.
METHODS: Data on self-reported (by parent/carer) asthma prevalence in children aged 0-14 years at statistical area level 2 (SA2, small geographic area) and selected sociodemographic features were extracted from the national Australian Household and Population Census 2021. A spatial cluster analysis was used to detect hotspots (i.e., areas and their neighbours with higher asthma prevalence than the entire study area average) of asthma prevalence. We also used a spatial Bayesian Poisson model to examine the relationship between sociodemographic features and asthma prevalence. All analyses were performed at the SA2 level.
RESULTS: Data were analysed from 4,621,716 children aged 0-14 years from 2,321 SA2s across the whole country. Overall, children\'s asthma prevalence was 6.27%, ranging from 0 to 16.5%, with significant hotspots of asthma prevalence in areas of greater socioeconomic disadvantage. Socioeconomically disadvantaged areas had significantly higher asthma prevalence than advantaged areas (prevalence ratio [PR] = 1.10, 95% credible interval [CrI] 1.06-1.14). Higher asthma prevalence was observed in areas with a higher proportion of Indigenous individuals (PR = 1.13, 95% CrI 1.10-1.17).
CONCLUSIONS: We identified significant geographic variation in asthma prevalence and sociodemographic predictors associated with the variation, which may help in designing targeted asthma management strategies and considerations for service enhancement for children in socially deprived areas.
METHODS: Data on self-reported (by parent/carer) asthma prevalence in children aged 0-14 years at statistical area level 2 (SA2, small geographic area) and selected sociodemographic features were extracted from the national Australian Household and Population Census 2021. A spatial cluster analysis was used to detect hotspots (i.e., areas and their neighbours with higher asthma prevalence than the entire study area average) of asthma prevalence. We also used a spatial Bayesian Poisson model to examine the relationship between sociodemographic features and asthma prevalence. All analyses were performed at the SA2 level.
RESULTS: Data were analysed from 4,621,716 children aged 0-14 years from 2,321 SA2s across the whole country. Overall, children\'s asthma prevalence was 6.27%, ranging from 0 to 16.5%, with significant hotspots of asthma prevalence in areas of greater socioeconomic disadvantage. Socioeconomically disadvantaged areas had significantly higher asthma prevalence than advantaged areas (prevalence ratio [PR] = 1.10, 95% credible interval [CrI] 1.06-1.14). Higher asthma prevalence was observed in areas with a higher proportion of Indigenous individuals (PR = 1.13, 95% CrI 1.10-1.17).
CONCLUSIONS: We identified significant geographic variation in asthma prevalence and sociodemographic predictors associated with the variation, which may help in designing targeted asthma management strategies and considerations for service enhancement for children in socially deprived areas.
摘要：
背景：哮喘是澳大利亚儿童中最常见的慢性呼吸系统疾病。虽然儿童哮喘患病率因地区而异，对小地理区域水平的变化知之甚少。识别哮喘的小地理区域变化对于突出有针对性干预的热点至关重要。本研究旨在调查小区域水平的变化，空间聚类，以及与澳大利亚儿童哮喘患病率相关的社会人口统计学危险因素。
方法：从2021年全国澳大利亚家庭和人口普查中提取了0-14岁儿童在统计区域2级（SA2，小地理区域）和选定的社会人口统计学特征的自我报告（按父母/照顾者）哮喘患病率数据。使用空间聚类分析来检测热点(即，哮喘患病率高于整个研究区域平均水平的地区及其邻居）的哮喘患病率。我们还使用空间贝叶斯泊松模型来检查社会人口统计学特征与哮喘患病率之间的关系。所有分析均在SA2水平进行。
结果：分析了来自全国2,321个SA2的4,621,716名0-14岁儿童的数据。总的来说,儿童哮喘患病率为6.27%,范围从0到16.5%，在社会经济劣势较大的地区，哮喘流行的重要热点。社会经济弱势地区的哮喘患病率明显高于优势地区（患病率[PR]=1.10，95％可信区间[CrI]1.06-1.14）。在土著个体比例较高的地区观察到较高的哮喘患病率（PR=1.13，95％CrI1.10-1.17）。
结论：我们确定了哮喘患病率的显著地理差异以及与该差异相关的社会人口统计学预测因子。这可能有助于为社会贫困地区的儿童设计有针对性的哮喘管理策略和增强服务的注意事项。
方法：从2021年全国澳大利亚家庭和人口普查中提取了0-14岁儿童在统计区域2级（SA2，小地理区域）和选定的社会人口统计学特征的自我报告（按父母/照顾者）哮喘患病率数据。使用空间聚类分析来检测热点(即，哮喘患病率高于整个研究区域平均水平的地区及其邻居）的哮喘患病率。我们还使用空间贝叶斯泊松模型来检查社会人口统计学特征与哮喘患病率之间的关系。所有分析均在SA2水平进行。
结果：分析了来自全国2,321个SA2的4,621,716名0-14岁儿童的数据。总的来说,儿童哮喘患病率为6.27%,范围从0到16.5%，在社会经济劣势较大的地区，哮喘流行的重要热点。社会经济弱势地区的哮喘患病率明显高于优势地区（患病率[PR]=1.10，95％可信区间[CrI]1.06-1.14）。在土著个体比例较高的地区观察到较高的哮喘患病率（PR=1.13，95％CrI1.10-1.17）。
结论：我们确定了哮喘患病率的显著地理差异以及与该差异相关的社会人口统计学预测因子。这可能有助于为社会贫困地区的儿童设计有针对性的哮喘管理策略和增强服务的注意事项。
