检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:Jahidur Rahman Khan Raghu Lingam Louisa Owens Katherine Chen Shivanthan Shanthikumar Steve Oo Andre Schultz John Widger KShuvo Bakar Adam Jaffe Nusrat Homaira
机构地区:[1]School of Clinical Medicine,University of New South Wales,Randwick,NSW 2031,Australia [2]Sydney Children’s Hospital Network,Randwick,NSW,Australia [3]Murdoch Children’s Research Institute,Melbourne,VIC,Australia [4]The Royal Children’s Hospital,Melbourne,VIC,Australia [5]Perth Children’s Hospital,Perth,WA,Australia [6]University of Western Australia,Perth,WA,Australia [7]Women’s and Children’s Hospital,Adelaide,SA,Australia [8]Sydney School of Public Health,University of Sydney,Sydney,NSW,Australia [9]James P.Grant School of Public Health,BRAC University,Dhaka,Bangladesh
出 处:《Global Health Research and Policy》2024年第1期377-386,共10页全球健康研究与政策(英文)
基 金:The research was funded through philanthropy funding through UNSW Philanthropy(CIA Homaira).
摘 要: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 coun-try.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 considera-tions for service enhancement for children in socially deprived areas.
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.38