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Methodological approaches to imputing early-pregnancy weight based on weight measures collected during pregnancy
BACKGROUND: Early pregnancy weights are needed to quantify gestational weight gain accurately. Different methods have been used in previous studies to impute early-pregnancy weights. However, no studies have systematically compared imputed weight accuracy across different imputation techniques. This...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7863454/ https://www.ncbi.nlm.nih.gov/pubmed/33546607 http://dx.doi.org/10.1186/s12874-021-01210-3 |
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author | Yang, Jiaxi Wang, Dongqing Darling, Anne Marie Liu, Enju Perumal, Nandita Fawzi, Wafaie W. Wang, Molin |
author_facet | Yang, Jiaxi Wang, Dongqing Darling, Anne Marie Liu, Enju Perumal, Nandita Fawzi, Wafaie W. Wang, Molin |
author_sort | Yang, Jiaxi |
collection | PubMed |
description | BACKGROUND: Early pregnancy weights are needed to quantify gestational weight gain accurately. Different methods have been used in previous studies to impute early-pregnancy weights. However, no studies have systematically compared imputed weight accuracy across different imputation techniques. This study aimed to compare four methodological approaches to imputing early-pregnancy weight, using repeated measures of pregnancy weights collected from two pregnancy cohorts in Tanzania. METHODS: The mean gestational ages at enrollment were 17.8 weeks for Study I and 10.0 weeks for Study II. Given the gestational age distributions at enrollment, early-pregnancy weights were extrapolated for Study I and interpolated for Study II. The four imputation approaches included: (i) simple imputation based on the nearest measure, (ii) simple arithmetic imputation based on the nearest two measures, (iii) mixed-effects models, and (iv) marginal models with generalized estimating equations. For the mixed-effects model and the marginal model with generalized estimating equation methods, imputation accuracy was further compared across varying degrees of model flexibility by fitting splines and polynomial terms. Additional analyses included dropping third-trimester weights, adding covariate to the models, and log-transforming weight before imputation. Mean absolute error was used to quantify imputation accuracy. RESULTS: Study I included 1472 women with 6272 weight measures; Study II included 2131 individuals with 11,775 weight measures. Among the four imputation approaches, mixed-effects models had the highest accuracy (smallest mean absolute error: 1.99 kg and 1.60 kg for Studies I and II, respectively), while the other three approaches showed similar degrees of accuracy. Depending on the underlying data structure, allowing appropriate degree of model flexibility and dropping remote pregnancy weight measures may further improve the imputation performance. CONCLUSIONS: Mixed-effects models had superior performance in imputing early-pregnancy weight compared to other commonly used strategies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-021-01210-3. |
format | Online Article Text |
id | pubmed-7863454 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-78634542021-02-05 Methodological approaches to imputing early-pregnancy weight based on weight measures collected during pregnancy Yang, Jiaxi Wang, Dongqing Darling, Anne Marie Liu, Enju Perumal, Nandita Fawzi, Wafaie W. Wang, Molin BMC Med Res Methodol Research Article BACKGROUND: Early pregnancy weights are needed to quantify gestational weight gain accurately. Different methods have been used in previous studies to impute early-pregnancy weights. However, no studies have systematically compared imputed weight accuracy across different imputation techniques. This study aimed to compare four methodological approaches to imputing early-pregnancy weight, using repeated measures of pregnancy weights collected from two pregnancy cohorts in Tanzania. METHODS: The mean gestational ages at enrollment were 17.8 weeks for Study I and 10.0 weeks for Study II. Given the gestational age distributions at enrollment, early-pregnancy weights were extrapolated for Study I and interpolated for Study II. The four imputation approaches included: (i) simple imputation based on the nearest measure, (ii) simple arithmetic imputation based on the nearest two measures, (iii) mixed-effects models, and (iv) marginal models with generalized estimating equations. For the mixed-effects model and the marginal model with generalized estimating equation methods, imputation accuracy was further compared across varying degrees of model flexibility by fitting splines and polynomial terms. Additional analyses included dropping third-trimester weights, adding covariate to the models, and log-transforming weight before imputation. Mean absolute error was used to quantify imputation accuracy. RESULTS: Study I included 1472 women with 6272 weight measures; Study II included 2131 individuals with 11,775 weight measures. Among the four imputation approaches, mixed-effects models had the highest accuracy (smallest mean absolute error: 1.99 kg and 1.60 kg for Studies I and II, respectively), while the other three approaches showed similar degrees of accuracy. Depending on the underlying data structure, allowing appropriate degree of model flexibility and dropping remote pregnancy weight measures may further improve the imputation performance. CONCLUSIONS: Mixed-effects models had superior performance in imputing early-pregnancy weight compared to other commonly used strategies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-021-01210-3. BioMed Central 2021-02-05 /pmc/articles/PMC7863454/ /pubmed/33546607 http://dx.doi.org/10.1186/s12874-021-01210-3 Text en © The Author(s) 2021 Open AccessThis 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/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Yang, Jiaxi Wang, Dongqing Darling, Anne Marie Liu, Enju Perumal, Nandita Fawzi, Wafaie W. Wang, Molin Methodological approaches to imputing early-pregnancy weight based on weight measures collected during pregnancy |
title | Methodological approaches to imputing early-pregnancy weight based on weight measures collected during pregnancy |
title_full | Methodological approaches to imputing early-pregnancy weight based on weight measures collected during pregnancy |
title_fullStr | Methodological approaches to imputing early-pregnancy weight based on weight measures collected during pregnancy |
title_full_unstemmed | Methodological approaches to imputing early-pregnancy weight based on weight measures collected during pregnancy |
title_short | Methodological approaches to imputing early-pregnancy weight based on weight measures collected during pregnancy |
title_sort | methodological approaches to imputing early-pregnancy weight based on weight measures collected during pregnancy |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7863454/ https://www.ncbi.nlm.nih.gov/pubmed/33546607 http://dx.doi.org/10.1186/s12874-021-01210-3 |
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