Title | Expanding the access of wearable silicone wristbands in community-engaged research through best practices in data analysis and integration. |
Publication Type | Journal Article |
Year of Publication | 2024 |
Authors | Bramer, LM, Dixon, HM, Degnan, DJ, Rohlman, D, Herbstman, JB, Anderson, KA, Waters, KM |
Journal | Pac Symp Biocomput |
Volume | 29 |
Pagination | 170-186 |
Date Published | 2024 |
ISSN | 2335-6936 |
Keywords | Computational Biology, Data Analysis, Environmental Monitoring, Humans, Silicones, Wearable Electronic Devices |
Abstract |
Wearable silicone wristbands are a rapidly growing exposure assessment technology that offer researchers the ability to study previously inaccessible cohorts and have the potential to provide a more comprehensive picture of chemical exposure within diverse communities. However, there are no established best practices for analyzing the data within a study or across multiple studies, thereby limiting impact and access of these data for larger meta-analyses. We utilize data from three studies, from over 600 wristbands worn by participants in New York City and Eugene, Oregon, to present a first-of-its-kind manuscript detailing wristband data properties. We further discuss and provide concrete examples of key areas and considerations in common statistical modeling methods where best practices must be established to enable meta-analyses and integration of data from multiple studies. Finally, we detail important and challenging aspects of machine learning, meta-analysis, and data integration that researchers will face in order to extend beyond the limited scope of individual studies focused on specific populations.
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Alternate Journal | Pac Symp Biocomput |
PubMed ID | 38160278 |
PubMed Central ID | PMC10766083 |
Grant List | P30 ES030287 / ES / NIEHS NIH HHS / United States P42 ES016465 / ES / NIEHS NIH HHS / United States R21 ES024718 / ES / NIEHS NIH HHS / United States R33 ES024718 / ES / NIEHS NIH HHS / United States |