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Effective gestational weight gain advice to optimize infant birth weight in Japan based on quantile regression analysis
The optimal range of gestational weight gain (GWG) was recently raised in Japan. This may help reduce small-for-gestational-age (SGA) infants, but may also increase large-for-gestational-age (LGA) infants. This study performed hypothetical experiments to determine effective GWG advice based on quant...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10684669/ https://www.ncbi.nlm.nih.gov/pubmed/38017257 http://dx.doi.org/10.1038/s41598-023-48375-z |
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author | Sato, Noriko Haruyama, Rei Miyasaka, Naoyuki |
author_facet | Sato, Noriko Haruyama, Rei Miyasaka, Naoyuki |
author_sort | Sato, Noriko |
collection | PubMed |
description | The optimal range of gestational weight gain (GWG) was recently raised in Japan. This may help reduce small-for-gestational-age (SGA) infants, but may also increase large-for-gestational-age (LGA) infants. This study performed hypothetical experiments to determine effective GWG advice based on quantile regression analysis. In a total of 354,401 singleton pregnancies registered in the perinatal database of the Japan Society of Obstetrics and Gynecology (2013–2017), the proportions of SGA and LGA were 9.33% and 11.13%, respectively. Using regression coefficients of GWG across the birth weight-for-gestational-age quantile distribution, we analyzed changes in their proportions by simulating a uniform 3-kg extra increase in GWG or an increase or decrease based on GWG adequacy. A hypothetical experiment of a uniform increase in GWG resulted in SGA and LGA proportions of 7.26% (95% confidence interval 7.15–7.36) and 14.51% (14.37–14.66), respectively. By contrast, assuming a 3-kg increase in women with inadequate GWG and a 3-kg decrease in women with excessive GWG resulted in SGA and LGA proportions of 8.42% (8.31–8.54) and 11.50% (11.37–11.62), respectively. Our real-world data analysis suggests that careful adjustment of GWG based on GWG adequacy will be effective in optimizing infant birth weight in Japan |
format | Online Article Text |
id | pubmed-10684669 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-106846692023-11-30 Effective gestational weight gain advice to optimize infant birth weight in Japan based on quantile regression analysis Sato, Noriko Haruyama, Rei Miyasaka, Naoyuki Sci Rep Article The optimal range of gestational weight gain (GWG) was recently raised in Japan. This may help reduce small-for-gestational-age (SGA) infants, but may also increase large-for-gestational-age (LGA) infants. This study performed hypothetical experiments to determine effective GWG advice based on quantile regression analysis. In a total of 354,401 singleton pregnancies registered in the perinatal database of the Japan Society of Obstetrics and Gynecology (2013–2017), the proportions of SGA and LGA were 9.33% and 11.13%, respectively. Using regression coefficients of GWG across the birth weight-for-gestational-age quantile distribution, we analyzed changes in their proportions by simulating a uniform 3-kg extra increase in GWG or an increase or decrease based on GWG adequacy. A hypothetical experiment of a uniform increase in GWG resulted in SGA and LGA proportions of 7.26% (95% confidence interval 7.15–7.36) and 14.51% (14.37–14.66), respectively. By contrast, assuming a 3-kg increase in women with inadequate GWG and a 3-kg decrease in women with excessive GWG resulted in SGA and LGA proportions of 8.42% (8.31–8.54) and 11.50% (11.37–11.62), respectively. Our real-world data analysis suggests that careful adjustment of GWG based on GWG adequacy will be effective in optimizing infant birth weight in Japan Nature Publishing Group UK 2023-11-28 /pmc/articles/PMC10684669/ /pubmed/38017257 http://dx.doi.org/10.1038/s41598-023-48375-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 Sato, Noriko Haruyama, Rei Miyasaka, Naoyuki Effective gestational weight gain advice to optimize infant birth weight in Japan based on quantile regression analysis |
title | Effective gestational weight gain advice to optimize infant birth weight in Japan based on quantile regression analysis |
title_full | Effective gestational weight gain advice to optimize infant birth weight in Japan based on quantile regression analysis |
title_fullStr | Effective gestational weight gain advice to optimize infant birth weight in Japan based on quantile regression analysis |
title_full_unstemmed | Effective gestational weight gain advice to optimize infant birth weight in Japan based on quantile regression analysis |
title_short | Effective gestational weight gain advice to optimize infant birth weight in Japan based on quantile regression analysis |
title_sort | effective gestational weight gain advice to optimize infant birth weight in japan based on quantile regression analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10684669/ https://www.ncbi.nlm.nih.gov/pubmed/38017257 http://dx.doi.org/10.1038/s41598-023-48375-z |
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