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Metrics of early childhood growth in recent epidemiological research: A scoping review
Metrics to quantify child growth vary across studies of the developmental origins of health and disease. We conducted a scoping review of child growth studies in which length/height, weight or body mass index (BMI) was measured at ≥ 2 time points. From a 10% random sample of eligible studies publish...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5860780/ https://www.ncbi.nlm.nih.gov/pubmed/29558499 http://dx.doi.org/10.1371/journal.pone.0194565 |
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author | Leung, Michael Perumal, Nandita Mesfin, Elnathan Krishna, Aditi Yang, Seungmi Johnson, William Bassani, Diego G. Roth, Daniel E. |
author_facet | Leung, Michael Perumal, Nandita Mesfin, Elnathan Krishna, Aditi Yang, Seungmi Johnson, William Bassani, Diego G. Roth, Daniel E. |
author_sort | Leung, Michael |
collection | PubMed |
description | Metrics to quantify child growth vary across studies of the developmental origins of health and disease. We conducted a scoping review of child growth studies in which length/height, weight or body mass index (BMI) was measured at ≥ 2 time points. From a 10% random sample of eligible studies published between Jan 2010-Jun 2016, and all eligible studies from Oct 2015-June 2016, we classified growth metrics based on author-assigned labels (e.g., ‘weight gain’) and a ‘content signature’, a numeric code that summarized the metric’s conceptual and statistical properties. Heterogeneity was assessed by the number of unique content signatures, and label-to-content concordance. In 122 studies, we found 40 unique metrics of childhood growth. The most common approach to quantifying growth in length, weight or BMI was the calculation of each child’s change in z-score. Label-to-content discordance was common due to distinct content signatures carrying the same label, and because of instances in which the same content signature was assigned multiple different labels. In conclusion, the numerous distinct growth metrics and the lack of specificity in the application of metric labels challenge the integration of data and inferences from studies investigating the determinants or consequences of variations in childhood growth. |
format | Online Article Text |
id | pubmed-5860780 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-58607802018-03-28 Metrics of early childhood growth in recent epidemiological research: A scoping review Leung, Michael Perumal, Nandita Mesfin, Elnathan Krishna, Aditi Yang, Seungmi Johnson, William Bassani, Diego G. Roth, Daniel E. PLoS One Research Article Metrics to quantify child growth vary across studies of the developmental origins of health and disease. We conducted a scoping review of child growth studies in which length/height, weight or body mass index (BMI) was measured at ≥ 2 time points. From a 10% random sample of eligible studies published between Jan 2010-Jun 2016, and all eligible studies from Oct 2015-June 2016, we classified growth metrics based on author-assigned labels (e.g., ‘weight gain’) and a ‘content signature’, a numeric code that summarized the metric’s conceptual and statistical properties. Heterogeneity was assessed by the number of unique content signatures, and label-to-content concordance. In 122 studies, we found 40 unique metrics of childhood growth. The most common approach to quantifying growth in length, weight or BMI was the calculation of each child’s change in z-score. Label-to-content discordance was common due to distinct content signatures carrying the same label, and because of instances in which the same content signature was assigned multiple different labels. In conclusion, the numerous distinct growth metrics and the lack of specificity in the application of metric labels challenge the integration of data and inferences from studies investigating the determinants or consequences of variations in childhood growth. Public Library of Science 2018-03-20 /pmc/articles/PMC5860780/ /pubmed/29558499 http://dx.doi.org/10.1371/journal.pone.0194565 Text en © 2018 Leung et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Leung, Michael Perumal, Nandita Mesfin, Elnathan Krishna, Aditi Yang, Seungmi Johnson, William Bassani, Diego G. Roth, Daniel E. Metrics of early childhood growth in recent epidemiological research: A scoping review |
title | Metrics of early childhood growth in recent epidemiological research: A scoping review |
title_full | Metrics of early childhood growth in recent epidemiological research: A scoping review |
title_fullStr | Metrics of early childhood growth in recent epidemiological research: A scoping review |
title_full_unstemmed | Metrics of early childhood growth in recent epidemiological research: A scoping review |
title_short | Metrics of early childhood growth in recent epidemiological research: A scoping review |
title_sort | metrics of early childhood growth in recent epidemiological research: a scoping review |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5860780/ https://www.ncbi.nlm.nih.gov/pubmed/29558499 http://dx.doi.org/10.1371/journal.pone.0194565 |
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