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Association between early preterm birth and maternal exposure to fine particular matter (PM(10)): A nation-wide population-based cohort study using machine learning

Although preterm birth (PTB), a birth before 34 weeks of gestation accounts for only less than 3% of total births, it is a critical cause of various perinatal morbidity and mortality. Several studies have been conducted on the association between maternal exposure to PM and PTB, but the results were...

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Autores principales: Choi, Eun-Saem, Lee, Jue Seong, Hwang, Yujin, Lee, Kwang-Sig, Ahn, Ki Hoon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10406328/
https://www.ncbi.nlm.nih.gov/pubmed/37549180
http://dx.doi.org/10.1371/journal.pone.0289486
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author Choi, Eun-Saem
Lee, Jue Seong
Hwang, Yujin
Lee, Kwang-Sig
Ahn, Ki Hoon
author_facet Choi, Eun-Saem
Lee, Jue Seong
Hwang, Yujin
Lee, Kwang-Sig
Ahn, Ki Hoon
author_sort Choi, Eun-Saem
collection PubMed
description Although preterm birth (PTB), a birth before 34 weeks of gestation accounts for only less than 3% of total births, it is a critical cause of various perinatal morbidity and mortality. Several studies have been conducted on the association between maternal exposure to PM and PTB, but the results were inconsistent. Moreover, no study has analyzed the risk of PM on PTB among women with cardiovascular diseases, even though those were thought to be highly susceptible to PM considering the cardiovascular effect of PM. Therefore, we aimed to evaluate the effect of PM(10) on early PTB according to the period of exposure, using machine learning with data from Korea National Health Insurance Service (KNHI) claims. Furthermore, we conducted subgroup analysis to compare the risk of PM on early PTB among pregnant women with cardiovascular diseases and those without. A total of 149,643 primiparous singleton women aged 25 to 40 years who delivered babies in 2017 were included. Random forest feature importance and SHAP (Shapley additive explanations) value were used to identify the effect of PM(10) on early PTB in comparison with other well-known contributing factors of PTB. AUC and accuracy of PTB prediction model using random forest were 0.9988 and 0.9984, respectively. Maternal exposure to PM(10) was one of the major predictors of early PTB. PM(10) concentration of 5 to 7 months before delivery, the first and early second trimester of pregnancy, ranked high in feature importance. SHAP value showed that higher PM(10) concentrations before 5 to 7 months before delivery were associated with an increased risk of early PTB. The probability of early PTB was increased by 7.73%, 10.58%, or 11.11% if a variable PM(10) concentration of 5, 6, or 7 months before delivery was included to the prediction model. Furthermore, women with cardiovascular diseases were more susceptible to PM(10) concentration in terms of risk for early PTB than those without cardiovascular diseases. Maternal exposure to PM(10) has a strong association with early PTB. In addition, in the context of PTB, pregnant women with cardiovascular diseases are a high-risk group of PM(10) and the first and early second trimester is a high-risk period of PM(10).
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spelling pubmed-104063282023-08-08 Association between early preterm birth and maternal exposure to fine particular matter (PM(10)): A nation-wide population-based cohort study using machine learning Choi, Eun-Saem Lee, Jue Seong Hwang, Yujin Lee, Kwang-Sig Ahn, Ki Hoon PLoS One Research Article Although preterm birth (PTB), a birth before 34 weeks of gestation accounts for only less than 3% of total births, it is a critical cause of various perinatal morbidity and mortality. Several studies have been conducted on the association between maternal exposure to PM and PTB, but the results were inconsistent. Moreover, no study has analyzed the risk of PM on PTB among women with cardiovascular diseases, even though those were thought to be highly susceptible to PM considering the cardiovascular effect of PM. Therefore, we aimed to evaluate the effect of PM(10) on early PTB according to the period of exposure, using machine learning with data from Korea National Health Insurance Service (KNHI) claims. Furthermore, we conducted subgroup analysis to compare the risk of PM on early PTB among pregnant women with cardiovascular diseases and those without. A total of 149,643 primiparous singleton women aged 25 to 40 years who delivered babies in 2017 were included. Random forest feature importance and SHAP (Shapley additive explanations) value were used to identify the effect of PM(10) on early PTB in comparison with other well-known contributing factors of PTB. AUC and accuracy of PTB prediction model using random forest were 0.9988 and 0.9984, respectively. Maternal exposure to PM(10) was one of the major predictors of early PTB. PM(10) concentration of 5 to 7 months before delivery, the first and early second trimester of pregnancy, ranked high in feature importance. SHAP value showed that higher PM(10) concentrations before 5 to 7 months before delivery were associated with an increased risk of early PTB. The probability of early PTB was increased by 7.73%, 10.58%, or 11.11% if a variable PM(10) concentration of 5, 6, or 7 months before delivery was included to the prediction model. Furthermore, women with cardiovascular diseases were more susceptible to PM(10) concentration in terms of risk for early PTB than those without cardiovascular diseases. Maternal exposure to PM(10) has a strong association with early PTB. In addition, in the context of PTB, pregnant women with cardiovascular diseases are a high-risk group of PM(10) and the first and early second trimester is a high-risk period of PM(10). Public Library of Science 2023-08-07 /pmc/articles/PMC10406328/ /pubmed/37549180 http://dx.doi.org/10.1371/journal.pone.0289486 Text en © 2023 Choi et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Choi, Eun-Saem
Lee, Jue Seong
Hwang, Yujin
Lee, Kwang-Sig
Ahn, Ki Hoon
Association between early preterm birth and maternal exposure to fine particular matter (PM(10)): A nation-wide population-based cohort study using machine learning
title Association between early preterm birth and maternal exposure to fine particular matter (PM(10)): A nation-wide population-based cohort study using machine learning
title_full Association between early preterm birth and maternal exposure to fine particular matter (PM(10)): A nation-wide population-based cohort study using machine learning
title_fullStr Association between early preterm birth and maternal exposure to fine particular matter (PM(10)): A nation-wide population-based cohort study using machine learning
title_full_unstemmed Association between early preterm birth and maternal exposure to fine particular matter (PM(10)): A nation-wide population-based cohort study using machine learning
title_short Association between early preterm birth and maternal exposure to fine particular matter (PM(10)): A nation-wide population-based cohort study using machine learning
title_sort association between early preterm birth and maternal exposure to fine particular matter (pm(10)): a nation-wide population-based cohort study using machine learning
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10406328/
https://www.ncbi.nlm.nih.gov/pubmed/37549180
http://dx.doi.org/10.1371/journal.pone.0289486
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