Other Titles
Rising Star Poster/Presentation
Abstract
Purpose: The purpose of this presentation is to demonstrate how microbiome data is presented in the literature and evaluate the effect of inconsistencies in reporting on the interpretation of microbiome data for research and clinical practice.
Background: Examination of the relationship between the microbiome and human health is a burgeoning area of research1-5. However, across microbiome literature, there is an inconsistency in reporting concerning bacterial taxonomies, abundance values, ranking, and alpha and beta diversity. This inconsistency demonstrates the need for greater consistency in reporting microbiome results so that researchers and nurses can compare results across studies.
Methods: Using newborn oral microbiome data from the Clearance of the Airways study and the existing literature, common metrics in microbiome data reporting will be presented including bacterial nomenclature, abundance, alpha and beta diversity, and ranking of bacterial taxonomies1-5. However, these metrics are variably reported in previous studies. Text and graphic presentations of the data and statistical analyses from these studies will then be compared for similarities and inconsistencies.
Discussion: Diversity informs the understanding of the abundance and ranking of microbiome taxonomic data and therefore should be reported consistently across studies. Consistency in microbiome reporting would increase the potential for replicability in science, enhance comparison between studies, and add to the applicability in practice. Furthermore, nursing researchers will be encouraged to seek consistency in reporting microbiome data. Through this analysis and comparison, nurses will consider how to use microbiome data and apply it to practice.
Notes
References
1. Keski-Nisula L, Kyynäräinen HR, Kärkkäinen U, Karhukorpi J, Heinonen S, Pekkanen J. Maternal intrapartum antibiotics and decreased vertical transmission of Lactobacillus to neonates during birth. Acta Paediatr. 2013;102(5):480-485. doi:10.1111/apa.12186
2. Li H, Xiao B, Zhang Y, Xiao S, Luo J, Huang W. Impact of maternal intrapartum antibiotics on the initial oral microbiome of neonates. Pediatr Neonatol. 2019;60(6):654-661. doi:10.1016/j.pedneo.2019.03.011
3. Li H, Chen S, Wu L, et al. The effects of perineal disinfection on infant's oral microflora after transvaginal examination during delivery. BMC Pregnancy Childbirth. 2019;19(1):213. Published 2019 Jun 24. doi:10.1186/s12884-019-2350-3
4. Gomez-Arango LF, Barrett HL, McIntyre HD, Callaway LK, Morrison M, Nitert MD. Contributions of the maternal oral and gut microbiome to placental microbial colonization in overweight and obese pregnant women. Sci Rep. 2017;7(1):2860. Published 2017 Jun 6. doi:10.1038/s41598-017-03066-4
5. O'Neal PV, Adams ED. Is the Newborn Microbiome Disrupted by Routine Newborn Suctioning? An Exploratory Approach for Policy Development. J Perinat Neonatal Nurs. 2020;34(3):231-238. doi:10.1097/JPN.0000000000000499
Sigma Membership
Epsilon Omega
Type
Poster
Format Type
Text-based Document
Study Design/Type
Other
Research Approach
Translational Research/Evidence-based Practice
Keywords:
Microbiome Data, Reporting Inconsistencies, Clinical Practice
Recommended Citation
Johnson, Jessica M., "Interpreting and Applying Microbiome Data for Evidence-Based Practice" (2025). International Nursing Research Congress (INRC). 187.
https://www.sigmarepository.org/inrc/2025/posters_2025/187
Conference Name
36th International Nursing Research Congress
Conference Host
Sigma Theta Tau International
Conference Location
Seattle, Washington, USA
Conference Year
2025
Rights Holder
All rights reserved by the author(s) and/or publisher(s) listed in this item record unless relinquished in whole or part by a rights notation or a Creative Commons License present in this item record.
Review Type
Invited Presentation
Acquisition
Proxy-submission
Interpreting and Applying Microbiome Data for Evidence-Based Practice
Seattle, Washington, USA
Purpose: The purpose of this presentation is to demonstrate how microbiome data is presented in the literature and evaluate the effect of inconsistencies in reporting on the interpretation of microbiome data for research and clinical practice.
Background: Examination of the relationship between the microbiome and human health is a burgeoning area of research1-5. However, across microbiome literature, there is an inconsistency in reporting concerning bacterial taxonomies, abundance values, ranking, and alpha and beta diversity. This inconsistency demonstrates the need for greater consistency in reporting microbiome results so that researchers and nurses can compare results across studies.
Methods: Using newborn oral microbiome data from the Clearance of the Airways study and the existing literature, common metrics in microbiome data reporting will be presented including bacterial nomenclature, abundance, alpha and beta diversity, and ranking of bacterial taxonomies1-5. However, these metrics are variably reported in previous studies. Text and graphic presentations of the data and statistical analyses from these studies will then be compared for similarities and inconsistencies.
Discussion: Diversity informs the understanding of the abundance and ranking of microbiome taxonomic data and therefore should be reported consistently across studies. Consistency in microbiome reporting would increase the potential for replicability in science, enhance comparison between studies, and add to the applicability in practice. Furthermore, nursing researchers will be encouraged to seek consistency in reporting microbiome data. Through this analysis and comparison, nurses will consider how to use microbiome data and apply it to practice.
Description
Microbiome data commonly includes bacterial nomenclature and taxonomies, abundance, ranking, and alpha and beta diversity, but is reported inconsistently across the literature. Inconsistent reporting leads to difficulties with comparison between studies and impedes application to practice. Using newborn oral microbiome data from the CLEAR study and existing literature, common metrics in microbiome data reporting will be presented and compared. Nurses will interpret and apply microbiome findings.