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2817. Spatial analysis techniques for diagnosis situational of low birth weight at term in the state of São Paulo
Invited abstract in session TA-6: Advancements of OR-analytics in statistics, machine learning and data science 12, stream Advancements of OR-analytics in statistics, machine learning and data science.
Tuesday, 8:30-10:00Room: 1013 (building: 202)
Authors (first author is the speaker)
1. | Diego Eduardo Quagliato Scarelli Cava
|
São Paulo State University | |
2. | Fernando Augusto Silva Marins
|
São Paulo State University | |
3. | Elen Yanina Aguirre Rodríguez
|
São Paulo State University | |
4. | Aneirson Silva
|
UNESP | |
5. | Elias Carlos Aguirre Rodríguez
|
São Paulo State University |
Abstract
Low birth weight (LBW) is defined when newborns weigh less than 2,500 grams,and is considered at term when born at greater than or equal to 37 weeks of gestation. The incidence of LBW is considered a significant public health issue, closely associated with an increased risk of mortality and future morbidity. Furthermore, it is important to highlight that between 15% and 20% of children born worldwide have LBW. Therefore, to overcome this situation, researchers started to develop and use the Geographic Information System to identify areas at risk of health problems and create solutions for these places. Based on this, this study aimed to utilize spatial analysis to verify the distribution of LBW at term and identify high-risk areas within the 645 municipalities in the state of São Paulo from 2012 to 2021. Specifically, this study used the global Moran index to measure the degree of spatial association in the study area and the local Moran index to identify risk areas with high prevalence. The findings indicate potential presence of significant clusters of municipalities revealed by the global moran index, which was substantiated by the local moran index, highlighting three small clusters in the northern part of the state. This approach can assist health professionals and governmental bodies to formulate precise strategies and initiatives to mitigate LBW in these localities.
Keywords
- Analytics and Data Science
Status: accepted
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