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Biases in self-reported height and weight measurements and their effects on modeling health outcomes
Self-reported anthropometrics are often used as proxies for measured anthropometrics, but research has shown that heights and weights are often misreported. Using the Study on global AGEing and adult health, I analyze misreporting patterns of height, weight, and BMI in China, India, Russia, and Sout...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Elsevier
2019
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6527819/ https://www.ncbi.nlm.nih.gov/pubmed/31193386 http://dx.doi.org/10.1016/j.ssmph.2019.100405 |
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author | Ng, Carmen D. |
author_facet | Ng, Carmen D. |
author_sort | Ng, Carmen D. |
collection | PubMed |
description | Self-reported anthropometrics are often used as proxies for measured anthropometrics, but research has shown that heights and weights are often misreported. Using the Study on global AGEing and adult health, I analyze misreporting patterns of height, weight, and BMI in China, India, Russia, and South Africa. Adjustments of self-reported heights and weights using demographic, social, and anthropometric characteristics are evaluated and found to be useful in studying the distribution of anthropometrics within a population. Measured, self-reported, and adjusted BMI are then compared in logistic regression models on the reporting of health outcomes, as well as the resulting accuracy of individual prediction. When BMI is used as a continuous variable in models of health outcomes, measured, self-reported, and adjusted BMI produce similar coefficient estimates, and so self-reported data would be a natural choice because of its accessibility and convenience. In other applications, such as models using categorical BMI and individual prediction using either continuous or categorical BMI, self-reported data in lieu of measured data might not be accurate enough, but adjustments could serve as a potential compromise. |
format | Online Article Text |
id | pubmed-6527819 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-65278192019-05-28 Biases in self-reported height and weight measurements and their effects on modeling health outcomes Ng, Carmen D. SSM Popul Health Article Self-reported anthropometrics are often used as proxies for measured anthropometrics, but research has shown that heights and weights are often misreported. Using the Study on global AGEing and adult health, I analyze misreporting patterns of height, weight, and BMI in China, India, Russia, and South Africa. Adjustments of self-reported heights and weights using demographic, social, and anthropometric characteristics are evaluated and found to be useful in studying the distribution of anthropometrics within a population. Measured, self-reported, and adjusted BMI are then compared in logistic regression models on the reporting of health outcomes, as well as the resulting accuracy of individual prediction. When BMI is used as a continuous variable in models of health outcomes, measured, self-reported, and adjusted BMI produce similar coefficient estimates, and so self-reported data would be a natural choice because of its accessibility and convenience. In other applications, such as models using categorical BMI and individual prediction using either continuous or categorical BMI, self-reported data in lieu of measured data might not be accurate enough, but adjustments could serve as a potential compromise. Elsevier 2019-05-10 /pmc/articles/PMC6527819/ /pubmed/31193386 http://dx.doi.org/10.1016/j.ssmph.2019.100405 Text en © 2019 The Author http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Ng, Carmen D. Biases in self-reported height and weight measurements and their effects on modeling health outcomes |
title | Biases in self-reported height and weight measurements and their effects on modeling health outcomes |
title_full | Biases in self-reported height and weight measurements and their effects on modeling health outcomes |
title_fullStr | Biases in self-reported height and weight measurements and their effects on modeling health outcomes |
title_full_unstemmed | Biases in self-reported height and weight measurements and their effects on modeling health outcomes |
title_short | Biases in self-reported height and weight measurements and their effects on modeling health outcomes |
title_sort | biases in self-reported height and weight measurements and their effects on modeling health outcomes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6527819/ https://www.ncbi.nlm.nih.gov/pubmed/31193386 http://dx.doi.org/10.1016/j.ssmph.2019.100405 |
work_keys_str_mv | AT ngcarmend biasesinselfreportedheightandweightmeasurementsandtheireffectsonmodelinghealthoutcomes |