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Data Science for All by Correlation One - Empowerment Cohort 4

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GabrielBrionesL/DS4A-Capstone

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DS4A Capstone

Data Science for All by Correlation One - Empowerment Cohort 4

February 2023

Team 26: Cynthia Fonderson, Gabriel Briones, Solomon Berhe, Moradeke Adeniji-Somefun

This folder contains the work my team and I completed in fulfillment of our DS4A Fellowship. For our capstone project, we chose to investigate the interplay between racial disparities in pregnancy-related mortality and socioeconomic factors.

datafolio

Introduction:

The project addresses persistent racial disparities in maternal health in the U.S., particularly focusing on the impact of socio-economic factors. Despite advancements in medical care, maternal mortality rates, especially among Black women, remain high. The study aims to investigate the association between maternal mortality and factors such as race, income, education, and location, exploring trends over time and predicting pregnancy-related deaths.

Data Analysis:

Two datasets from the Centers for Disease Control and Prevention and the U.S. Census were used for analysis. The data underwent extensive wrangling and cleaning, merging mortality and socio-economic information by state and race. The project's goal is to expose systemic factors contributing to racial disparities in maternal health outcomes.

Exploratory Data Analysis:

Univariate and bivariate analyses revealed insights into mortality rates, socio-economic factors, and racial differences. The data was explored for trends, revealing correlations and discrepancies, particularly between Black and White populations. Challenges in data availability for certain racial categories were addressed.

Statistical Analysis & Predictive Modeling:

Statistical analyses, including hypothesis testing, revealed significant differences in pregnancy-related death rates between Black and White women. The project then employed predictive modeling, using multiple linear regression. Key factors influencing mortality rates were identified, emphasizing the role of race, access to healthcare, poverty rates, and marital status.

Dashboard:

An explanatory dashboard in Tableau was created to present insights visually, showcasing an overview, racial breakdowns, correlation implications, and regression model details. The dashboard provides an interactive platform to explore the project's findings. You can visit our dashboard to explore further.

Conclusions:

The study concludes that Black women experience higher maternal mortality rates compared to White counterparts across 26 states. Socio-economic factors significantly impact mortality rates for both racial groups, but further investigations are recommended to understand additional contributing factors and promote racial equity in maternal health outcomes.

Future Work:

The analysis suggests that socio-economic factors play a greater role in maternal mortality rates for Black populations. However, additional factors contributing to observed variances need consideration. Policy recommendations include expanding health insurance access to address mortality disparities. Further research is recommended to enhance understanding and promote racial equity in maternal health outcomes.

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