Individual participant data (IPD)-level meta-analysis of randomised controlled trials among dark-skinned populations to estimate the dietary requirement for vitamin D

cb
Thumbnail Image
Files
s13643-019-1032-6.pdf(634.54 KB)
Published version
13643_2019_1032_MOESM1_ESM.docx(14.54 KB)
Supplementary file 1
Date
2019-05-28
Authors
Cashman, Kevin D.
Ritz, Christian
Journal Title
Journal ISSN
Volume Title
Publisher
BMC part of Springer Nature
Published Version
10.1186/s13643-019-1032-6
Research Projects
Organizational Units
Journal Issue
Abstract
Estimation of the dietary requirements for vitamin D is crucial from a public health perspective in providing a framework for the prevention of vitamin D deficiency. It has been shown that pooling individual participant-level data (IPD) from selected randomised controlled trials (RCTs) of white children and adults facilitated the generation of more accurate estimates of the vitamin D requirement. Recent RCT data suggest the vitamin D requirement of dark-skinned, particularly black, individuals, an at-risk group of vitamin D deficiency, is greater than those of white counterparts. Thus, we wished to develop a study protocol for the conduct of an IPD-level meta-analysis of vitamin D requirements using data from appropriate vitamin D RCTs in dark-skinned population subgroups.
Description
Keywords
Vitamin D requirements , Ethnic-related differences , Individual participant data-level meta-regression analyses , Dietary reference values , RCT
Citation
Cashman, K.D. and Ritz, C. (2019). 'Individual participant data (IPD)-level meta-analysis of randomised controlled trials among dark-skinned populations to estimate the dietary requirement for vitamin D'. Systematic reviews, 8(1), 128. (17pp). doi:10.1186/s13643-019-1032-6
Link to publisher’s version
https://systematicreviewsjournal.biomedcentral.com/articles/10.1186/s13643-019-1032-6
URI
https://hdl.handle.net/10468/9130
Collections
Cork Centre for Vitamin D and Nutrition Research - Journal Articles
Medicine - Journal Articles
Copyright
© The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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.