Powering Research through Innovative Methods for Mixtures in Epidemiology (PRIME) Program: Novel and Expanded Statistical Methods

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dc.citation.articleNumber1378en_US
dc.citation.issueNumber3en_US
dc.citation.journalTitleInternational Journal of Environmental Research and Public Healthen_US
dc.citation.volumeNumber19en_US
dc.contributor.authorJoubert, Bonnie R.en_US
dc.contributor.authorKioumourtzoglou, Marianthi-Annaen_US
dc.contributor.authorChamberlain, Toccaraen_US
dc.contributor.authorChen, Hua Yunen_US
dc.contributor.authorGennings, Chrisen_US
dc.contributor.authorTuryk, Mary E.en_US
dc.contributor.authorMiranda, Marie Lynnen_US
dc.contributor.authorWebster, Thomas F.en_US
dc.contributor.authorEnsor, Katherine B.en_US
dc.contributor.authorDunson, David B.en_US
dc.contributor.authorCoull, Brent A.en_US
dc.date.accessioned2022-02-04T19:19:11Zen_US
dc.date.available2022-02-04T19:19:11Zen_US
dc.date.issued2022en_US
dc.description.abstractHumans are exposed to a diverse mixture of chemical and non-chemical exposures across their lifetimes. Well-designed epidemiology studies as well as sophisticated exposure science and related technologies enable the investigation of the health impacts of mixtures. While existing statistical methods can address the most basic questions related to the association between environmental mixtures and health endpoints, there were gaps in our ability to learn from mixtures data in several common epidemiologic scenarios, including high correlation among health and exposure measures in space and/or time, the presence of missing observations, the violation of important modeling assumptions, and the presence of computational challenges incurred by current implementations. To address these and other challenges, NIEHS initiated the Powering Research through Innovative methods for Mixtures in Epidemiology (PRIME) program, to support work on the development and expansion of statistical methods for mixtures. Six independent projects supported by PRIME have been highly productive but their methods have not yet been described collectively in a way that would inform application. We review 37 new methods from PRIME projects and summarize the work across previously published research questions, to inform methods selection and increase awareness of these new methods. We highlight important statistical advancements considering data science strategies, exposure-response estimation, timing of exposures, epidemiological methods, the incorporation of toxicity/chemical information, spatiotemporal data, risk assessment, and model performance, efficiency, and interpretation. Importantly, we link to software to encourage application and testing on other datasets. This review can enable more informed analyses of environmental mixtures. We stress training for early career scientists as well as innovation in statistical methodology as an ongoing need. Ultimately, we direct efforts to the common goal of reducing harmful exposures to improve public health.en_US
dc.identifier.citationJoubert, Bonnie R., Kioumourtzoglou, Marianthi-Anna, Chamberlain, Toccara, et al.. "Powering Research through Innovative Methods for Mixtures in Epidemiology (PRIME) Program: Novel and Expanded Statistical Methods." <i>International Journal of Environmental Research and Public Health,</i> 19, no. 3 (2022) MDPI: https://doi.org/10.3390/ijerph19031378.en_US
dc.identifier.digitalijerph-19-01378en_US
dc.identifier.doihttps://doi.org/10.3390/ijerph19031378en_US
dc.identifier.urihttps://hdl.handle.net/1911/111971en_US
dc.language.isoengen_US
dc.publisherMDPIen_US
dc.rightsThis is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly citeden_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.titlePowering Research through Innovative Methods for Mixtures in Epidemiology (PRIME) Program: Novel and Expanded Statistical Methodsen_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
dc.type.publicationpublisher versionen_US
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