Maria Luiza Melo da Silva, Natan Nascimento de Oliveira, Andreia Ferdin, Maria José Quina Galdino, Emiliana Cristina Melo, Rosana Rosseto de Oliveira
{"title":"帕拉纳州新生儿近漏及社会经济和保健指标的空间分析。","authors":"Maria Luiza Melo da Silva, Natan Nascimento de Oliveira, Andreia Ferdin, Maria José Quina Galdino, Emiliana Cristina Melo, Rosana Rosseto de Oliveira","doi":"10.1590/1980-549720250023","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>To analyze the spatial distribution of neonatal near miss and socioeconomic and healthcare indicators in the state of Paraná.</p><p><strong>Methods: </strong>Ecological, cross-sectional study of neonatal near miss rates in municipalities in the state of Paraná, from 2020 to 2022, obtained through data from the Live Birth Information System (SINASC) and the Mortality Information System (SIM), connected through deterministic linkage. The spatial distribution of neonatal near miss rates, socioeconomic indicators (maternal age and race/ethnicity), and healthcare indicators (type of delivery and number of prenatal consultations) were performed. Global and Local Moran's Index were used for spatial analysis.</p><p><strong>Results: </strong>The neonatal near miss rate in Paraná was 28.46 per thousand live births. Health regions (HR) 4th HR - Irati, 3rd HR - Ponta Grossa, 6th HR - União da Vitória, and 17th HR - Londrina stood out with high rates of neonatal near miss. Concerning the indicators, significant rates were evident among women of black, yellow, and indigenous race/color, as well as inadequacies in prenatal.</p><p><strong>Conclusions: </strong>The results highlight priorities in the Eastern and Northern macro-regions, where high-high clusters indicate an urgent need to assess access and quality of care. Additionally, there is a need to investigate neonatal near miss in Black, Yellow, and Indigenous women, as well as low prenatal adherence or coverage.</p>","PeriodicalId":74697,"journal":{"name":"Revista brasileira de epidemiologia = Brazilian journal of epidemiology","volume":"28 ","pages":"e250023"},"PeriodicalIF":0.0000,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12068812/pdf/","citationCount":"0","resultStr":"{\"title\":\"Spatial analysis of neonatal near miss and socioeconomic and healthcare indicators in the state of Paraná.\",\"authors\":\"Maria Luiza Melo da Silva, Natan Nascimento de Oliveira, Andreia Ferdin, Maria José Quina Galdino, Emiliana Cristina Melo, Rosana Rosseto de Oliveira\",\"doi\":\"10.1590/1980-549720250023\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>To analyze the spatial distribution of neonatal near miss and socioeconomic and healthcare indicators in the state of Paraná.</p><p><strong>Methods: </strong>Ecological, cross-sectional study of neonatal near miss rates in municipalities in the state of Paraná, from 2020 to 2022, obtained through data from the Live Birth Information System (SINASC) and the Mortality Information System (SIM), connected through deterministic linkage. The spatial distribution of neonatal near miss rates, socioeconomic indicators (maternal age and race/ethnicity), and healthcare indicators (type of delivery and number of prenatal consultations) were performed. Global and Local Moran's Index were used for spatial analysis.</p><p><strong>Results: </strong>The neonatal near miss rate in Paraná was 28.46 per thousand live births. Health regions (HR) 4th HR - Irati, 3rd HR - Ponta Grossa, 6th HR - União da Vitória, and 17th HR - Londrina stood out with high rates of neonatal near miss. Concerning the indicators, significant rates were evident among women of black, yellow, and indigenous race/color, as well as inadequacies in prenatal.</p><p><strong>Conclusions: </strong>The results highlight priorities in the Eastern and Northern macro-regions, where high-high clusters indicate an urgent need to assess access and quality of care. Additionally, there is a need to investigate neonatal near miss in Black, Yellow, and Indigenous women, as well as low prenatal adherence or coverage.</p>\",\"PeriodicalId\":74697,\"journal\":{\"name\":\"Revista brasileira de epidemiologia = Brazilian journal of epidemiology\",\"volume\":\"28 \",\"pages\":\"e250023\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12068812/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Revista brasileira de epidemiologia = Brazilian journal of epidemiology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1590/1980-549720250023\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Revista brasileira de epidemiologia = Brazilian journal of epidemiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1590/1980-549720250023","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
Spatial analysis of neonatal near miss and socioeconomic and healthcare indicators in the state of Paraná.
Objective: To analyze the spatial distribution of neonatal near miss and socioeconomic and healthcare indicators in the state of Paraná.
Methods: Ecological, cross-sectional study of neonatal near miss rates in municipalities in the state of Paraná, from 2020 to 2022, obtained through data from the Live Birth Information System (SINASC) and the Mortality Information System (SIM), connected through deterministic linkage. The spatial distribution of neonatal near miss rates, socioeconomic indicators (maternal age and race/ethnicity), and healthcare indicators (type of delivery and number of prenatal consultations) were performed. Global and Local Moran's Index were used for spatial analysis.
Results: The neonatal near miss rate in Paraná was 28.46 per thousand live births. Health regions (HR) 4th HR - Irati, 3rd HR - Ponta Grossa, 6th HR - União da Vitória, and 17th HR - Londrina stood out with high rates of neonatal near miss. Concerning the indicators, significant rates were evident among women of black, yellow, and indigenous race/color, as well as inadequacies in prenatal.
Conclusions: The results highlight priorities in the Eastern and Northern macro-regions, where high-high clusters indicate an urgent need to assess access and quality of care. Additionally, there is a need to investigate neonatal near miss in Black, Yellow, and Indigenous women, as well as low prenatal adherence or coverage.