Cargando…

Using latent class cluster analysis to screen high risk clusters of birth defects between 2009 and 2013 in Northwest China

In the study, we aimed to explore the synergistic effects of multiple risk factors on birth defects, and examine temporal trend of the synergistic effects over time. Two cross-sectional surveys conducted in 2009 and 2013 were merged and then latent class cluster analysis and generalized linear Poiss...

Descripción completa

Detalles Bibliográficos
Autores principales: Pei, Leilei, Zeng, Lingxia, Zhao, Yaling, Wang, Duolao, Yan, Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5537369/
https://www.ncbi.nlm.nih.gov/pubmed/28761054
http://dx.doi.org/10.1038/s41598-017-07076-0
_version_ 1783254162519097344
author Pei, Leilei
Zeng, Lingxia
Zhao, Yaling
Wang, Duolao
Yan, Hong
author_facet Pei, Leilei
Zeng, Lingxia
Zhao, Yaling
Wang, Duolao
Yan, Hong
author_sort Pei, Leilei
collection PubMed
description In the study, we aimed to explore the synergistic effects of multiple risk factors on birth defects, and examine temporal trend of the synergistic effects over time. Two cross-sectional surveys conducted in 2009 and 2013 were merged and then latent class cluster analysis and generalized linear Poisson model were used. A total of 9085 and 29094 young children born within the last three years and their mothers were enrolled in 2009 and 2013 respectively. Three latent maternal exposure clusters were determined: a high-risk, a moderate-risk, and a low-risk cluster (88.97%, 1.49%, 9.54% in 2009 and 82.42%, 3.39%, 14.19% in 2013). The synthetic effects of maternal exposure to multiple risk factors could increase the risk of overall birth defects and cardiovascular system malformation among live births, and this risk is significantly higher in high-risk cluster than that in low-risk cluster. After adjusting for confounding factors using a generalized linear Poisson model, in high-risk cluster the prevalence of nervous system malformation decreased by approximately 2.71%, and the proportion of cardiovascular system malformation rose by 0.92% from 2009 to 2013. The Chinese government should make great efforts to provide primary prevention for those on high-risk cluster as a priority target population.
format Online
Article
Text
id pubmed-5537369
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-55373692017-08-03 Using latent class cluster analysis to screen high risk clusters of birth defects between 2009 and 2013 in Northwest China Pei, Leilei Zeng, Lingxia Zhao, Yaling Wang, Duolao Yan, Hong Sci Rep Article In the study, we aimed to explore the synergistic effects of multiple risk factors on birth defects, and examine temporal trend of the synergistic effects over time. Two cross-sectional surveys conducted in 2009 and 2013 were merged and then latent class cluster analysis and generalized linear Poisson model were used. A total of 9085 and 29094 young children born within the last three years and their mothers were enrolled in 2009 and 2013 respectively. Three latent maternal exposure clusters were determined: a high-risk, a moderate-risk, and a low-risk cluster (88.97%, 1.49%, 9.54% in 2009 and 82.42%, 3.39%, 14.19% in 2013). The synthetic effects of maternal exposure to multiple risk factors could increase the risk of overall birth defects and cardiovascular system malformation among live births, and this risk is significantly higher in high-risk cluster than that in low-risk cluster. After adjusting for confounding factors using a generalized linear Poisson model, in high-risk cluster the prevalence of nervous system malformation decreased by approximately 2.71%, and the proportion of cardiovascular system malformation rose by 0.92% from 2009 to 2013. The Chinese government should make great efforts to provide primary prevention for those on high-risk cluster as a priority target population. Nature Publishing Group UK 2017-07-31 /pmc/articles/PMC5537369/ /pubmed/28761054 http://dx.doi.org/10.1038/s41598-017-07076-0 Text en © The Author(s) 2017 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Pei, Leilei
Zeng, Lingxia
Zhao, Yaling
Wang, Duolao
Yan, Hong
Using latent class cluster analysis to screen high risk clusters of birth defects between 2009 and 2013 in Northwest China
title Using latent class cluster analysis to screen high risk clusters of birth defects between 2009 and 2013 in Northwest China
title_full Using latent class cluster analysis to screen high risk clusters of birth defects between 2009 and 2013 in Northwest China
title_fullStr Using latent class cluster analysis to screen high risk clusters of birth defects between 2009 and 2013 in Northwest China
title_full_unstemmed Using latent class cluster analysis to screen high risk clusters of birth defects between 2009 and 2013 in Northwest China
title_short Using latent class cluster analysis to screen high risk clusters of birth defects between 2009 and 2013 in Northwest China
title_sort using latent class cluster analysis to screen high risk clusters of birth defects between 2009 and 2013 in northwest china
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5537369/
https://www.ncbi.nlm.nih.gov/pubmed/28761054
http://dx.doi.org/10.1038/s41598-017-07076-0
work_keys_str_mv AT peileilei usinglatentclassclusteranalysistoscreenhighriskclustersofbirthdefectsbetween2009and2013innorthwestchina
AT zenglingxia usinglatentclassclusteranalysistoscreenhighriskclustersofbirthdefectsbetween2009and2013innorthwestchina
AT zhaoyaling usinglatentclassclusteranalysistoscreenhighriskclustersofbirthdefectsbetween2009and2013innorthwestchina
AT wangduolao usinglatentclassclusteranalysistoscreenhighriskclustersofbirthdefectsbetween2009and2013innorthwestchina
AT yanhong usinglatentclassclusteranalysistoscreenhighriskclustersofbirthdefectsbetween2009and2013innorthwestchina