Publication Date

Spring 4-8-2025

Abstract

This study investigates the association between prenatal PM2.5 exposure and preterm birth risk in New Mexico (2014–2021). Using descriptive statistics, time series models, and spatial analyses, findings show an average preterm birth rate of 14.87 per 1,000 live births, with moderate correlation (r = 0.727) between PM2.5 levels and very preterm births. While traditional models revealed no significant global effect, spatial methods such as Geographically Weighted Regression (GWR) and Multiscale GWR uncovered strong spatial heterogeneity. PM2.5 effects varied by county (coefficients: -0.00154 to 0.00150), with clustering evident in 2018–2019 (Moran’s I = 0.155–0.174). Results highlight the limitations of global models and advocate for spatially targeted interventions and seasonal risk mitigation. Recommendations include localized air quality alerts, improved monitoring, and policies tailored to high-risk areas.

Degree Name

Statistics

Level of Degree

Masters

Department Name

Mathematics & Statistics

First Committee Member (Chair)

James Degnan

Second Committee Member

Davood Tofighi

Third Committee Member

Miheer Dewaskar

Project Sponsors

James Degnan

Language

English

Keywords

PM2.5 exposure, Preterm birth risk, Spatio-temporal modeling, Multiscale Geographically Weighted Regression, Environmental health disparities, Spatio-temporal modeling

Document Type

Thesis

Comments

To every family and woman who has experienced the pain of preterm birth this work is for you.

This thesis is for academic purposes only. The findings, interpretations, and conclusions expressed are solely those of the author and do not represent official policy or medical advice.

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