# 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, Maria Luiza Melo da Silva, Natan Nascimento de Oliveira, Andreia Ferdin, Maria José Quina Galdino, Emiliana Cristina Melo, Rosana Rosseto de Oliveira

PMC · DOI: 10.1590/1980-549720250023 · Revista Brasileira de Epidemiologia (Brazilian Journal of Epidemiology) · 2025-05-09

## TL;DR

This study maps neonatal near miss cases in Paraná, linking them to socioeconomic and healthcare factors to identify regions and groups needing urgent attention.

## Contribution

The paper provides a spatial analysis of neonatal near miss in Paraná, highlighting disparities and clusters for targeted healthcare interventions.

## Key findings

- The neonatal near miss rate in Paraná was 28.46 per thousand live births.
- High rates were observed in health regions like Irati, Ponta Grossa, and Londrina.
- Black, Yellow, and Indigenous women and inadequate prenatal care were associated with higher near miss rates.

## Abstract

To analyze the spatial distribution of neonatal near miss and socioeconomic and healthcare indicators in the state of Paraná.

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.

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.

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.

Analisar a distribuição espacial do near miss neonatal e indicadores socioeconômicos e assistenciais no estado do Paraná.

Estudo ecológico e transversal das taxas de near miss neonatal nos municípios do estado do Paraná do período de 2020 a 2022, obtidas por meio de linkage determinístico do Sistema de Informações sobre Nascidos Vivos e do Sistema de Informações sobre Mortalidade. Foi realizada a distribuição espacial das taxas de near miss neonatal e dos indicadores socioeconômicos (idade materna e raça/cor) e assistenciais (via de parto e número de consultas pré-natais). Para a análise espacial foram empregados os índices de Moran global e local.

A taxa de near miss neonatal no Paraná foi de 28,46 por 1.000 nascidos vivos. As regionais de saúde Irati, Ponta Grossa, União da Vitória e Londrina se destacaram com altas taxas de near miss neonatal. Em relação aos indicadores, evidenciaram-se taxas expressivas em mulheres da raça/cor negra, amarela e indígena e a inadequação do pré-natal.

Os resultados apontam prioridades nas macrorregiões leste e norte, onde há clusters alto-alto, evidenciando a urgência de se avaliarem o acesso e a qualidade da assistência. Além disso, destaca-se a necessidade de investigar o near miss neonatal em mulheres negras, amarelas e indígenas, bem como a baixa adesão ou cobertura do pré-natal.

## Full-text entities

- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

4 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12068812/full.md

## References

35 references — full list in the complete paper: https://tomesphere.com/paper/PMC12068812/full.md

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Source: https://tomesphere.com/paper/PMC12068812