Navigating Demographic Disparities in Louisiana Women’s Health Using Machine Learning Within Geographic Analysis

Overview

The issue of women's health in Louisiana is critical, given the state's extremely high maternal mortality rates. Women's health issues disproportionately impact Black and low -income women in our state, underscoring a persistent challenge in providing quali ty healthcare. By integrating datasets from the Louisiana Department of Health and other state and federal -level organizations, a geospatial model was made in ArcGIS, associating socioeconomic factors with infant mortality rate. Because infant mortality rate is a prominent health issue for Louisiana women, it was used as the primary determinant of women’s health for this research. Following the trend analysis between analysis fields, machine learning tools within the software were used to cluster parishes into regions of “High,” “Medium,” and “Low” threat to maternal health. The majority of the parishes labeled under “High” threat were located in the northeast region of the state. Their poverty rates, distance from maternal crisis care, and Medicare enrollment tended to be higher, while their income levels tended to be lower. Additionally, regions with a high Black population were typically labeled as “High” or “Medium” threat parishes. Ultimately, this model aims to highlight the urgency of addressing matern al health disparities and advocate for informed strategies in partnership with policymakers and healthcare providers to improve women's health outcomes in Louisiana.

Competition history

• JSHS 2024 Category not listed

Resources

• National JSHS abstract book ↗

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