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Maternal weight latent trajectories and associations with adverse pregnancy outcomes using a smoothing mixture model

Class membership is a critical issue in health data sciences. Different types of statistical models have been widely applied to identify participants within a population with heterogeneous longitudinal trajectories. This study aims to identify latent longitudinal trajectories of maternal weight asso...

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Autores principales: Faraji Azad, Shirin, Biglarian, Akbar, Rostami, Maryam, Bidhendi-Yarandi, Razieh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10238470/
https://www.ncbi.nlm.nih.gov/pubmed/37268823
http://dx.doi.org/10.1038/s41598-023-36312-z
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author Faraji Azad, Shirin
Biglarian, Akbar
Rostami, Maryam
Bidhendi-Yarandi, Razieh
author_facet Faraji Azad, Shirin
Biglarian, Akbar
Rostami, Maryam
Bidhendi-Yarandi, Razieh
author_sort Faraji Azad, Shirin
collection PubMed
description Class membership is a critical issue in health data sciences. Different types of statistical models have been widely applied to identify participants within a population with heterogeneous longitudinal trajectories. This study aims to identify latent longitudinal trajectories of maternal weight associated with adverse pregnancy outcomes using smoothing mixture model (SMM). Data were collected from the Khuzestan Vitamin D Deficiency Screening Program in Pregnancy. We applied the data of 877 pregnant women living in Shooshtar city, whose weights during the nine months of pregnancy were available. In the first step, maternal weight was classified and participants were assigned to only one group for which the estimated trajectory is the most similar to the observed one using SMM; then, we examined the associations of identified trajectories with risk of adverse pregnancy endpoints by applying logistic regression. Three latent trajectories for maternal weight during pregnancy were identified and named as low, medium and high weight trajectories. Crude estimated odds ratio (OR) for icterus, preterm delivery, NICU admission and composite neonatal events shows significantly higher risks in trajectory 1 (low weight) compared to trajectory 2 (medium weight) by 69% (OR = 1.69, 95%CI 1.20, 2.39), 82% (OR = 1.82, 95%CI 1.14, 2.87), 77% (OR = 1.77, 95%CI 1.17, 2.43), and 85% (OR = 1.85, 95%CI 1.38, 2.76), respectively. Latent class trajectories of maternal weights can be accurately estimated using SMM. It is a powerful means for researchers to appropriately assign individuals to their class. The U-shaped curve of association between maternal weight gain and risk of maternal complications reveals that the optimum place for pregnant women could be in the middle of the growth curve to minimize the risks. Low maternal weight trajectory compared to high had even a significantly higher hazard for some neonatal adverse events. Therefore, appropriate weight gain is critical for pregnant women. Trial registration International Standard Randomized Controlled Trial Number (ISRCTN): 2014102519660N1; http://www.irct.ir/searchresult.php?keyword=&id=19660&number=1&prt=7805&total=10&m=1 (Archived by WebCite at http://www.webcitation.org/6p3lkqFdV).
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spelling pubmed-102384702023-06-04 Maternal weight latent trajectories and associations with adverse pregnancy outcomes using a smoothing mixture model Faraji Azad, Shirin Biglarian, Akbar Rostami, Maryam Bidhendi-Yarandi, Razieh Sci Rep Article Class membership is a critical issue in health data sciences. Different types of statistical models have been widely applied to identify participants within a population with heterogeneous longitudinal trajectories. This study aims to identify latent longitudinal trajectories of maternal weight associated with adverse pregnancy outcomes using smoothing mixture model (SMM). Data were collected from the Khuzestan Vitamin D Deficiency Screening Program in Pregnancy. We applied the data of 877 pregnant women living in Shooshtar city, whose weights during the nine months of pregnancy were available. In the first step, maternal weight was classified and participants were assigned to only one group for which the estimated trajectory is the most similar to the observed one using SMM; then, we examined the associations of identified trajectories with risk of adverse pregnancy endpoints by applying logistic regression. Three latent trajectories for maternal weight during pregnancy were identified and named as low, medium and high weight trajectories. Crude estimated odds ratio (OR) for icterus, preterm delivery, NICU admission and composite neonatal events shows significantly higher risks in trajectory 1 (low weight) compared to trajectory 2 (medium weight) by 69% (OR = 1.69, 95%CI 1.20, 2.39), 82% (OR = 1.82, 95%CI 1.14, 2.87), 77% (OR = 1.77, 95%CI 1.17, 2.43), and 85% (OR = 1.85, 95%CI 1.38, 2.76), respectively. Latent class trajectories of maternal weights can be accurately estimated using SMM. It is a powerful means for researchers to appropriately assign individuals to their class. The U-shaped curve of association between maternal weight gain and risk of maternal complications reveals that the optimum place for pregnant women could be in the middle of the growth curve to minimize the risks. Low maternal weight trajectory compared to high had even a significantly higher hazard for some neonatal adverse events. Therefore, appropriate weight gain is critical for pregnant women. Trial registration International Standard Randomized Controlled Trial Number (ISRCTN): 2014102519660N1; http://www.irct.ir/searchresult.php?keyword=&id=19660&number=1&prt=7805&total=10&m=1 (Archived by WebCite at http://www.webcitation.org/6p3lkqFdV). Nature Publishing Group UK 2023-06-02 /pmc/articles/PMC10238470/ /pubmed/37268823 http://dx.doi.org/10.1038/s41598-023-36312-z Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Faraji Azad, Shirin
Biglarian, Akbar
Rostami, Maryam
Bidhendi-Yarandi, Razieh
Maternal weight latent trajectories and associations with adverse pregnancy outcomes using a smoothing mixture model
title Maternal weight latent trajectories and associations with adverse pregnancy outcomes using a smoothing mixture model
title_full Maternal weight latent trajectories and associations with adverse pregnancy outcomes using a smoothing mixture model
title_fullStr Maternal weight latent trajectories and associations with adverse pregnancy outcomes using a smoothing mixture model
title_full_unstemmed Maternal weight latent trajectories and associations with adverse pregnancy outcomes using a smoothing mixture model
title_short Maternal weight latent trajectories and associations with adverse pregnancy outcomes using a smoothing mixture model
title_sort maternal weight latent trajectories and associations with adverse pregnancy outcomes using a smoothing mixture model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10238470/
https://www.ncbi.nlm.nih.gov/pubmed/37268823
http://dx.doi.org/10.1038/s41598-023-36312-z
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