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Application and Comparison of Different Regression Models in Iodine Balance Experiment on Women of Childbearing Age and Pregnant Women.

Authors :
Wang Y
Tian X
Song Q
Wang W
Guo X
Cui T
Pan Z
Chen Y
Chen W
Tan L
Zhang W
Source :
Biological trace element research [Biol Trace Elem Res] 2024 Jun; Vol. 202 (6), pp. 2474-2487. Date of Electronic Publication: 2023 Oct 09.
Publication Year :
2024

Abstract

The iodine balance experiment is a traditional approach to evaluate the physiological requirement for iodine, while the simple linear regression model (SLM) and the mixed effects model (MEM) are two primary methods used to analyze iodine balance experiments. In the present study, we aimed to compare the effects of these two regression models on the evaluation of iodine balance experiments to investigate appropriate valuation methods. By constructing SLM and MEM, zero iodine balance values (IBV) were determined, and the evaluation effects were compared. No changes were made to the experimental data for women of childbearing age, and cutoff values of 600 µg/day and 1000 µg/day, respectively, were chosen for further processing of the experimental data for pregnant women. Equation combinations 1-3 (EC1-3) were obtained by fitting SLM, and zero IBV were calculated as 110.26 µg/day, 333.06 µg/day, and 434.84 µg/day, respectively. EC4-6 were obtained by fitting MEM, and zero IBV were calculated as 110.44 µg/day, 335.79 µg/day, and 418.06 µg/day, respectively. The inclusion of inter-measurement variation as a random factor in the MEM yielded EC7-8, which reduced the test power of the iodine balance experiment on women of childbearing age. Our study suggested that when experimental conditions were tightly controlled, with fewer uncertainties or significant influences, computationally straightforward and well-understood SLM was preferred. If some uncertain factors might cause large changes in the experimental results, it was advised to use a more "conservative" MEM to calculate the zero IBV. ClinicalTrials.gov Identifier: Registered at Clinicaltrials.gov, NCT03279315 (17th September 2017, retrospectively registered), NCT03710148 (18th October 2018, retrospectively registered).<br /> (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Details

Language :
English
ISSN :
1559-0720
Volume :
202
Issue :
6
Database :
MEDLINE
Journal :
Biological trace element research
Publication Type :
Academic Journal
Accession number :
37807000
Full Text :
https://doi.org/10.1007/s12011-023-03867-x