Jahidur Rahman Khan, Raghu Lingam, Louisa Owens, Katherine Chen, Shivanthan Shanthikumar, Steve Oo, Andre Schultz, John Widger, K Shuvo Bakar, Adam Jaffe, Nusrat Homaira
{"title":"澳大利亚儿童哮喘的社会贫困和空间聚集。","authors":"Jahidur Rahman Khan, Raghu Lingam, Louisa Owens, Katherine Chen, Shivanthan Shanthikumar, Steve Oo, Andre Schultz, John Widger, K Shuvo Bakar, Adam Jaffe, Nusrat Homaira","doi":"10.1186/s41256-024-00361-2","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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).</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":52405,"journal":{"name":"Global Health Research and Policy","volume":"9 1","pages":"22"},"PeriodicalIF":4.0000,"publicationDate":"2024-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11194868/pdf/","citationCount":"0","resultStr":"{\"title\":\"Social deprivation and spatial clustering of childhood asthma in Australia.\",\"authors\":\"Jahidur Rahman Khan, Raghu Lingam, Louisa Owens, Katherine Chen, Shivanthan Shanthikumar, Steve Oo, Andre Schultz, John Widger, K Shuvo Bakar, Adam Jaffe, Nusrat Homaira\",\"doi\":\"10.1186/s41256-024-00361-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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).</p><p><strong>Conclusions: </strong>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.</p>\",\"PeriodicalId\":52405,\"journal\":{\"name\":\"Global Health Research and Policy\",\"volume\":\"9 1\",\"pages\":\"22\"},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2024-06-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11194868/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Global Health Research and Policy\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s41256-024-00361-2\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Global Health Research and Policy","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s41256-024-00361-2","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
Social deprivation and spatial clustering of childhood asthma in Australia.
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.
期刊介绍:
Global Health Research and Policy, an open-access, multidisciplinary journal, publishes research on various aspects of global health, addressing topics like health equity, health systems and policy, social determinants of health, disease burden, population health, and other urgent global health issues. It serves as a forum for high-quality research focused on regional and global health improvement, emphasizing solutions for health equity.