Statistical approaches in the studies assessing associations between human milk immune composition and allergic diseases: A scoping review
File(s)nutrients BM research stats methodsreview.pdf (657.48 KB)
Published version
Author(s)
Type
Journal Article
Abstract
A growing number of studies are focusing on the associations between human milk (HM) immunological composition and allergic diseases. This scoping review aims to identify statistical methods applied in the field and highlight pitfalls and unmet needs. A comprehensive literature search in MEDLINE and Embase retrieved 13,607 unique records. Following title/abstract screening, 29 studies met the selection criteria and were included in this review. We found that definitions of colostrum and mature milk varied across the studies. A total of 17 out of 29 (59%) studies collected samples longitudinally, but only 12% of these used serial (longitudinal) analyses. Multivariable analysis was used in 45% of the studies, but statistical approaches to modelling varied largely across the studies. Types of variables included as potential confounding factors differed considerably between models. Discrimination analysis was absent from all studies and only a single study reported classification measures. Outcomes of this scoping review highlight lack of standardization, both in data collection and handling, which remains one of the main challenges in the field. Improved standardization could be obtained by a consensus group of researchers and clinicians that could recommend appropriate methods to be applied in future prospective studies, as well as already existing datasets.
Date Issued
2019-10-10
Date Acceptance
2019-10-01
Citation
Nutrients, 2019, 11 (10), pp.1-15
ISSN
2072-6643
Publisher
MDPI AG
Start Page
1
End Page
15
Journal / Book Title
Nutrients
Volume
11
Issue
10
Copyright Statement
© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Identifier
https://www.mdpi.com/2072-6643/11/10/2416
Publication Status
Published
Date Publish Online
2019-10-10