Data to Accompany: Expanding the access of wearable silicone wristbands in community-engaged research through best practices in data analysis and integration

Bramer, Lisa M; Dixon, Holly M; Degnan, David J; Rohlman, Diana; Herbstman, Julie B; Anderson, Kim A; Waters, Katrina M

doi:10.25584/2006568

Title: Data to Accompany: Expanding the access of wearable silicone wristbands in community-engaged research through best practices in data analysis and integration

Dataset
Other Related Research

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.

Authors:

; Dixon, Holly M;

; Rohlman, Diana; Herbstman, Julie B; Anderson, Kim A;

PNNL

Publication Date:: Fri Sep 22 00:00:00 EDT 2023

DOE Contract Number:: AC05-76RL01830

Research Org.:: Pacific Northwest National Laboratory 2

Sponsoring Org.:: DOE

OSTI Identifier:: 2006568

DOI:: https://doi.org/10.25584/2006568

Citation Formats


                    Bramer, Lisa M, Dixon, Holly M, Degnan, David J, Rohlman, Diana, Herbstman, Julie B, Anderson, Kim A, and Waters, Katrina M. Data to Accompany: Expanding the access of wearable silicone wristbands in community-engaged research through best practices in data analysis and integration.  United States: N. p., 2023. 
        Web.  doi:10.25584/2006568.

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                    Bramer, Lisa M, Dixon, Holly M, Degnan, David J, Rohlman, Diana, Herbstman, Julie B, Anderson, Kim A, & Waters, Katrina M. Data to Accompany: Expanding the access of wearable silicone wristbands in community-engaged research through best practices in data analysis and integration.  United States.  doi:https://doi.org/10.25584/2006568

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                    Bramer, Lisa M, Dixon, Holly M, Degnan, David J, Rohlman, Diana, Herbstman, Julie B, Anderson, Kim A, and Waters, Katrina M. 2023.  
"Data to Accompany: Expanding the access of wearable silicone wristbands in community-engaged research through best practices in data analysis and integration".  United States.  doi:https://doi.org/10.25584/2006568.  https://www.osti.gov/servlets/purl/2006568. Pub date:Fri Sep 22 00:00:00 EDT 2023

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@article{osti_2006568,

  title        = {Data to Accompany: Expanding the access of wearable silicone wristbands in community-engaged research through best practices in data analysis and integration},

  author       = {Bramer, Lisa M and Dixon, Holly M and Degnan, David J and Rohlman, Diana and Herbstman, Julie B and Anderson, Kim A and Waters, Katrina M},

  abstractNote = {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.},

  doi          = {10.25584/2006568},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Fri Sep 22 00:00:00 EDT 2023},

  month        = {Fri Sep 22 00:00:00 EDT 2023}

}

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DOI: https://doi.org/10.25584/2006568

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