Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/118261
Citations | ||
Scopus | Web of Science® | Altmetric |
---|---|---|
?
|
?
|
Type: | Journal article |
Title: | Tightrope walking: using predictors of 25 (OH)D concentration based on multivariable linear regression to infer associations with health risks |
Author: | Ding, N. Dear, K. Guo, S. Xiang, F. Lucas, R. |
Citation: | PLoS One, 2015; 10(5) |
Publisher: | Public Library Science |
Issue Date: | 2015 |
ISSN: | 1932-6203 1932-6203 |
Editor: | Stover, C.M. |
Statement of Responsibility: | Ning Ding, Keith Dear, Shuyu Guo, Fan Xiang, Robyn Lucas |
Abstract: | The debate on the causal association between vitamin D status, measured as serum concentration of 25-hydroxyvitamin D (25[OH]D), and various health outcomes warrants investigation in large-scale health surveys. Measuring the 25(OH)D concentration for each participant is not always feasible, because of the logistics of blood collection and the costs of vitamin D testing. To address this problem, past research has used predicted 25(OH)D concentration, based on multivariable linear regression, as a proxy for unmeasured vitamin D status. We restate this approach in a mathematical framework, to deduce its possible pitfalls. Monte Carlo simulation and real data from the National Health and Nutrition Examination Survey 2005-06 are used to confirm the deductions. The results indicate that variables that are used in the prediction model (for 25[OH]D concentration) but not in the model for the health outcome (called instrumental variables), play an essential role in the identification of an effect. Such variables should be unrelated to the health outcome other than through vitamin D; otherwise the estimate of interest will be biased. The approach of predicted 25(OH)D concentration derived from multivariable linear regression may be valid. However, careful verification that the instrumental variables are unrelated to the health outcome is required. |
Keywords: | Instrumental variable analysis; vitamin D; blood pressure; Monte Carlo method; obesity; linear regression analysis; vitamin D deficiency; nutrition |
Rights: | © 2015 Ding et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited |
DOI: | 10.1371/journal.pone.0125551 |
Published version: | http://dx.doi.org/10.1371/journal.pone.0125551 |
Appears in Collections: | Aurora harvest 3 Public Health publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
hdl_118261.pdf | Published version | 235.18 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.