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Using space–time cube to analyze trends in adverse birth outcomes and maternal characteristics in Massachusetts, USA
Rates of preterm births (< 37 gestational weeks) and low birthweight (≤ 2500 g) are rising throughout the United States. This study uses singleton live birth data, Empirical Bayes approach, space–time cube and Mann–Kendall statistic to evaluate temporal trends in these adverse birth outcomes (AB...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7873513/ https://www.ncbi.nlm.nih.gov/pubmed/33583998 http://dx.doi.org/10.1007/s10708-021-10382-w |
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author | Ogneva-Himmelberger, Yelena Haynes, Madeleine |
author_facet | Ogneva-Himmelberger, Yelena Haynes, Madeleine |
author_sort | Ogneva-Himmelberger, Yelena |
collection | PubMed |
description | Rates of preterm births (< 37 gestational weeks) and low birthweight (≤ 2500 g) are rising throughout the United States. This study uses singleton live birth data, Empirical Bayes approach, space–time cube and Mann–Kendall statistic to evaluate temporal trends in these adverse birth outcomes (ABO) and maternal characteristics over 15 years (2000–2014) at the census tract level for non-Hispanic white and black women in Massachusetts. In addition to analyzing trends for each variable individually, the study analyzes spatial coincidence of trends to determine which maternal characteristics exhibited trends that most strongly correlated with the ABO trends. The 15-year average rate of ABO was 7.34% for white women, and 12.05% for black women. Results show that more census tracts exhibited an increasing trend than decreasing trend in birth outcomes and in several maternal characteristics for both races (gestational and chronic hypertension, gestational diabetes, and previous preterm birth). Study identified 52 census tracts concurrently experiencing an increasing trend in ABO and in four maternal characteristics for black women, indicating that multiple negative trends in health outcomes are concentrated at the same location creating a potential for even more adverse outcomes in the future. This study provides a novel, spatially explicit analytical framework based on Empirical Bayes rates and space–time cube, which could be extended to analyze trends in other health outcomes at various spatial scales. SUPPLEMENTARY INFORMATION: The online version supplementary material available at 10.1007/s10708-021-10382-w. |
format | Online Article Text |
id | pubmed-7873513 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-78735132021-02-10 Using space–time cube to analyze trends in adverse birth outcomes and maternal characteristics in Massachusetts, USA Ogneva-Himmelberger, Yelena Haynes, Madeleine GeoJournal Article Rates of preterm births (< 37 gestational weeks) and low birthweight (≤ 2500 g) are rising throughout the United States. This study uses singleton live birth data, Empirical Bayes approach, space–time cube and Mann–Kendall statistic to evaluate temporal trends in these adverse birth outcomes (ABO) and maternal characteristics over 15 years (2000–2014) at the census tract level for non-Hispanic white and black women in Massachusetts. In addition to analyzing trends for each variable individually, the study analyzes spatial coincidence of trends to determine which maternal characteristics exhibited trends that most strongly correlated with the ABO trends. The 15-year average rate of ABO was 7.34% for white women, and 12.05% for black women. Results show that more census tracts exhibited an increasing trend than decreasing trend in birth outcomes and in several maternal characteristics for both races (gestational and chronic hypertension, gestational diabetes, and previous preterm birth). Study identified 52 census tracts concurrently experiencing an increasing trend in ABO and in four maternal characteristics for black women, indicating that multiple negative trends in health outcomes are concentrated at the same location creating a potential for even more adverse outcomes in the future. This study provides a novel, spatially explicit analytical framework based on Empirical Bayes rates and space–time cube, which could be extended to analyze trends in other health outcomes at various spatial scales. SUPPLEMENTARY INFORMATION: The online version supplementary material available at 10.1007/s10708-021-10382-w. Springer Netherlands 2021-02-10 2022 /pmc/articles/PMC7873513/ /pubmed/33583998 http://dx.doi.org/10.1007/s10708-021-10382-w Text en © The Author(s), under exclusive licence to Springer Nature B.V. part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Ogneva-Himmelberger, Yelena Haynes, Madeleine Using space–time cube to analyze trends in adverse birth outcomes and maternal characteristics in Massachusetts, USA |
title | Using space–time cube to analyze trends in adverse birth outcomes and maternal characteristics in Massachusetts, USA |
title_full | Using space–time cube to analyze trends in adverse birth outcomes and maternal characteristics in Massachusetts, USA |
title_fullStr | Using space–time cube to analyze trends in adverse birth outcomes and maternal characteristics in Massachusetts, USA |
title_full_unstemmed | Using space–time cube to analyze trends in adverse birth outcomes and maternal characteristics in Massachusetts, USA |
title_short | Using space–time cube to analyze trends in adverse birth outcomes and maternal characteristics in Massachusetts, USA |
title_sort | using space–time cube to analyze trends in adverse birth outcomes and maternal characteristics in massachusetts, usa |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7873513/ https://www.ncbi.nlm.nih.gov/pubmed/33583998 http://dx.doi.org/10.1007/s10708-021-10382-w |
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