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利用地理空间分析评估5岁以下儿童社区获得性肺炎住院风险及其与社会弱势群体地区(巴西)的关联。

Using geo-spatial analysis for assessing the risk of hospital admissions due to community-acquired pneumonia in under-5 children and its association with socially vulnerable areas (Brazil).

作者信息

Pina Juliana Coelho, Alves Luana Seles, Arroyo Luiz Henrique, Arcêncio Ricardo Alexandre, Gondim Ellen Cristina, Furtado Maria Cândida de Carvalho, de Mello Débora Falleiros

机构信息

Federal University of Santa Catarina, Campus Universitário Reitor João David Ferreira Lima, Trindade, Florianópolis, SC, CEP: 88040-900, Brazil.

University of São Paulo at Ribeirão Preto College of Nursing, Avenida dos Bandeirantes, 3900, Monte Alegre, Ribeirão Preto, SP, CEP: 14040-902, Brazil.

出版信息

BMC Pediatr. 2020 Nov 3;20(1):502. doi: 10.1186/s12887-020-02398-x.

DOI:10.1186/s12887-020-02398-x
PMID:33138791
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7606062/
Abstract

BACKGROUND

The concentration of under-5 child morbidity and mortality due to pneumonia in developing countries reflects the social inequities. This study aimed to map and assess the spatial risk for hospitalization due to Community-Acquired Pneumonia in children under 5 years of age and its association with vulnerable areas.

METHODS

Ecological study in the city of Ribeirão Preto, state of São Paulo, Brazil. The study population consisted of hospitalized under-5 children, diagnosed with community-acquired pneumonia, in Ribeirão Preto-São Paulo-Brazil, from 2012 to 2013. Data were collected in different databases, by a trained team, between March 2012 and August 2013 and from the 2010 Demographic Census of the Brazilian Institute of Geography and Statistics. The 956 urban census tracts were considered as the units of analysis. The incidence of cases per 10,000 inhabitants was calculated by census tracts during the study period. For the identification of the spatial risk clusters, the Kernel density estimator and the Getis-Ord Gi* technique were performed. Generalized additive models were used to verify the association between areas with social vulnerability and the occurrence of childhood pneumonia.

RESULTS

The study included 265 children under the age of five, hospitalized due to community-acquired pneumonia. A concentration of cases was identified in the regions with greater social vulnerability (low income, poor housing conditions and homelessness), as well as a lower occurrence of cases in the most developed and economically privileged area of the city. The majority of the children lived in territories served by traditional primary healthcare units, in which the health surveillance and family and community focus are limited. It is important to highlight that the tracts with the highest degrees of vulnerability, such as those identified as high vulnerability (urban) and very high vulnerability (subnormal urban clusters).

CONCLUSIONS

The results contribute to the comprehension of the social factors involved in child hospitalization due to pneumonia, based on the analysis of the spatial distribution. This approach revealed a strategic tool for diagnosing the disparities as well presenting evidences for the planning in health and strength health care system in achieving equity, welfare and social protection of children.

摘要

背景

发展中国家5岁以下儿童因肺炎导致的发病率和死亡率集中反映了社会不平等现象。本研究旨在绘制和评估5岁以下儿童社区获得性肺炎住院的空间风险及其与脆弱地区的关联。

方法

在巴西圣保罗州里贝朗普雷图市进行的生态研究。研究人群包括2012年至2013年在巴西圣保罗州里贝朗普雷图市因社区获得性肺炎住院的5岁以下儿童。2012年3月至2013年8月期间,由一个经过培训的团队在不同数据库中收集数据,并从巴西地理与统计研究所2010年人口普查中获取数据。956个城市普查区被视为分析单位。在研究期间,按普查区计算每10000名居民中的病例发病率。为了识别空间风险聚集区,采用了核密度估计器和Getis-Ord Gi*技术。使用广义相加模型来验证社会脆弱地区与儿童肺炎发生之间的关联。

结果

该研究纳入了265名5岁以下因社区获得性肺炎住院的儿童。在社会脆弱性较高的地区(低收入、住房条件差和无家可归)发现了病例集中现象,而在该市最发达和经济条件优越的地区病例发生率较低。大多数儿童居住在由传统初级卫生保健单位服务的地区,这些地区的健康监测以及家庭和社区关注有限。需要强调的是,脆弱程度最高的普查区,如被确定为高脆弱性(城市)和极高脆弱性(次正常城市集群)的地区。

结论

基于空间分布分析,这些结果有助于理解儿童因肺炎住院所涉及的社会因素。这种方法揭示了一种诊断差异的战略工具,并为卫生规划提供了证据,同时加强了卫生保健系统在实现儿童公平、福利和社会保护方面的作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9952/7607858/69d732c5bd54/12887_2020_2398_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9952/7607858/03a7ac30e339/12887_2020_2398_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9952/7607858/25a154a88ab3/12887_2020_2398_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9952/7607858/ed681098f13b/12887_2020_2398_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9952/7607858/3b650b6f7dd0/12887_2020_2398_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9952/7607858/60e21e47ff61/12887_2020_2398_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9952/7607858/69d732c5bd54/12887_2020_2398_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9952/7607858/03a7ac30e339/12887_2020_2398_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9952/7607858/25a154a88ab3/12887_2020_2398_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9952/7607858/ed681098f13b/12887_2020_2398_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9952/7607858/3b650b6f7dd0/12887_2020_2398_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9952/7607858/60e21e47ff61/12887_2020_2398_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9952/7607858/69d732c5bd54/12887_2020_2398_Fig6_HTML.jpg

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