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Using latent profile analysis to examine associations between gestational chemical mixtures and child neurodevelopment

Thesis type
(Thesis) M.Sc.
Date created
2021-08-03
Authors/Contributors
Abstract
In this study, we introduced Latent Profile Analysis (LPA) as a novel technique for studying gestational chemical mixtures. Using data from the Maternal-Infant Research on Environmental Chemicals Study, a longitudinal birth cohort study of pregnant Canadian women and their children, we examined the relationship between 30 gestational biomarkers and Verbal IQ, Performance IQ, and Full-Scale IQ. We generated five latent profiles: A Reference profile, a High Level profile, a Low Level profile, a High Organophosphate Pesticides profile, and a Smoking Chemicals profile. Multiple regression analysis showed strong negative associations between the Smoking Chemicals profile and IQ scores. We also found positive associations between the Low Level profile and IQ, and a negative association between the High Level profile and Verbal IQ. However, all 95% confidence intervals spanned the null. After conducting sensitivity analysis comparing LPA with k-means clustering, we concluded that LPA is a promising alternative to other clustering methods.
Document
Identifier
etd21494
Copyright statement
Copyright is held by the author(s).
Permissions
This thesis may be printed or downloaded for non-commercial research and scholarly purposes.
Supervisor or Senior Supervisor
Thesis advisor: McCandless, Lawrence
Language
English
Member of collection
Download file Size
input_data\22262\etd21494.pdf 1.39 MB

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