ABSTRACT Latent class analysis (LCA), although minimally applied to the statistical analysis of mixtures, may serve as a useful tool for identifying individuals with shared real-life

profiles of chemical exposures. Knowledge of these groupings and their risk of adverse outcomes has the potential to inform targeted public health prevention strategies. This example applies

LCA to identify clusters of pregnant women from a case–control study within the LIFECODES birth cohort with shared exposure patterns across a panel of urinary phthalate metabolites and

parabens, and to evaluate the association between cluster membership and urinary oxidative stress biomarkers. LCA identified individuals with: “low exposure,” “low phthalates, high

(31% higher, 95% CI = −5, 64%). However, contrast examinations indicated that associations between oxidative stress biomarkers and “high exposure” were not statistically different from those

with “high phthalates, low parabens” suggesting a minimal effect of higher paraben exposure in the presence of high phthalates. The presented example offers verification of latent class

assignments through application to an additional data set as well as a comparison to another unsupervised clustering approach, k-means clustering. LCA may be more easily implemented, more

consistent, and more able to provide interpretable output. Access through your institution Buy or subscribe This is a preview of subscription content, access via your institution ACCESS

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institutional subscriptions * Read our FAQs * Contact customer support SIMILAR CONTENT BEING VIEWED BY OTHERS PRENATAL EXPOSURE TO PERSISTENT AND NON-PERSISTENT CHEMICAL MIXTURES AND

ASSOCIATIONS WITH ADVERSE BIRTH OUTCOMES IN THE ATLANTA AFRICAN AMERICAN MATERNAL-CHILD COHORT Article 25 February 2023 APPLICATIONS OF MIXTURE METHODS IN EPIDEMIOLOGICAL STUDIES

INVESTIGATING THE HEALTH IMPACT OF PERSISTENT ORGANIC POLLUTANTS EXPOSURES: A SCOPING REVIEW Article Open access 10 September 2024 APPLICATION OF THREE STATISTICAL APPROACHES TO EXPLORE

EFFECTS OF DIETARY INTAKE OF MULTIPLE PERSISTENT ORGANIC POLLUTANTS ON ER-POSITIVE BREAST CANCER RISK IN THE FRENCH E3N COHORT Article Open access 15 January 2025 CODE AVAILABILITY

Accompanying code for the LCA methods is available at GitHub repository “LCAmix” from user “carrollrm.” This is available as an R markdown file to lead viewers through a simple example of

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references ACKNOWLEDGEMENTS This research was supported by the Intramural Research Program of the National Institute of Environmental Health Sciences (NIEHS), National Institute of Health

(Z1AES103321). Additional funding was provided by NIEHS (R01ES018872 and R01ES029531). AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * Biostatistics and Computational Biology Branch, National

Institute of Environmental Health Sciences, Research Triangle Park, NC, USA Rachel Carroll & Shanshan Zhao * Department of Mathematics and Statistics, University of North Carolina,

Wilmington, NC, USA Rachel Carroll * Epidemiology Branch, National Institute of Environmental Health Sciences, 111 T.W. Alexander Drive, Research Triangle Park, NC, 27709, USA Alexandra J.

White, Alexander P. Keil & Kelly K. Ferguson * Department of Epidemiology, University of North Carolina Gillings Global School of Public Health, Chapel Hill, NC, USA Alexander P. Keil *

Department of Environmental Health Sciences, University of Michigan School of Public Health, Ann Arbor, MI, USA John D. Meeker * Division of Maternal-Fetal Medicine, Brigham and Women’s

Hospital, Harvard Medical School, Boston, MA, USA Thomas F. McElrath Authors * Rachel Carroll View author publications You can also search for this author inPubMed Google Scholar * Alexandra

J. White View author publications You can also search for this author inPubMed Google Scholar * Alexander P. Keil View author publications You can also search for this author inPubMed 

Google Scholar * John D. Meeker View author publications You can also search for this author inPubMed Google Scholar * Thomas F. McElrath View author publications You can also search for

this author inPubMed Google Scholar * Shanshan Zhao View author publications You can also search for this author inPubMed Google Scholar * Kelly K. Ferguson View author publications You can

also search for this author inPubMed Google Scholar CORRESPONDING AUTHOR Correspondence to Kelly K. Ferguson. ETHICS DECLARATIONS CONFLICT OF INTEREST The authors declare that they have no

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SUPPLEMENTARY INFORMATION SUPPLEMENTARY INFORMATION RIGHTS AND PERMISSIONS Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Carroll, R., White, A.J., Keil, A.P. _et al._ Latent

classes for chemical mixtures analyses in epidemiology: an example using phthalate and phenol exposure biomarkers in pregnant women. _J Expo Sci Environ Epidemiol_ 30, 149–159 (2020).

https://doi.org/10.1038/s41370-019-0181-y Download citation * Received: 09 April 2019 * Revised: 20 August 2019 * Accepted: 05 September 2019 * Published: 21 October 2019 * Issue Date:

January 2020 * DOI: https://doi.org/10.1038/s41370-019-0181-y SHARE THIS ARTICLE Anyone you share the following link with will be able to read this content: Get shareable link Sorry, a

shareable link is not currently available for this article. Copy to clipboard Provided by the Springer Nature SharedIt content-sharing initiative KEYWORDS * Latent class models * Mixtures

methods * Phthalates * Phenols * Oxidative stress