Date of Award

2007

Degree Type

Thesis

Degree Name

Master of Science

Program

Epidemiology and Biostatistics

Supervisor

Dr. M. Karen Campbell

Second Advisor

Dr. Victor Han

Third Advisor

Dr. Bin Xie

Abstract

Background: Small for Gestational Age (SGA) confers increased risk to the infant, and causal pathways are poorly understood. Objective: To develop and test a conceptual model for SGA, allowing us to distinguish causal pathways. Methods: This investigation used data on 2356 women from the “Prenatal Health Project” cohort. Associations between prenatal variables and SGA, both severe (<3rd percentile) and moderate (3rd-10 percentile) were investigated using multinomial logistic regression models. Variables were entered according to our conceptual framework. Variable entry that attenuated beta values by >10% indicated these variables might act along the same pathway. Results: The final models illustrated multiple pathways associated with SGA. Different pathways were associated with moderate or severe SGA. Smoking and preeclampsia related to separate pathways both associated with severe SGA. Gestational hypertension was associated with moderate SGA, possibly working through low placental weight. Conclusions: These results illustrated differing causal pathways, and suggest different underlying biological mechanisms.

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