Reena Pinto

Contact

Maternal Health Analysis

About Project

This project analyzes the relationship between maternal lifestyle, body fat distribution, and pregnancy outcomes using Power BI. By exploring factors such as BMI, waist-hip ratio, visceral fat, smoking, alcohol, and eating habits, the study highlights how lifestyle and health metrics influence risks like gestational diabetes, preeclampsia, miscarriage, and cesarean delivery. The goal was to use data visualization to identify high-risk groups early and design effective intervention strategies.

With over 125 million transaction records, the dashboard delivers insights into unit sales, product demand, and store performance. It also demonstrates how external factors—such as oil prices, transferred holidays, and national events like the 2016 Ecuador earthquake—influence consumer behavior.

The goal of this project is to simplify complex retail data into actionable intelligence, empowering businesses to make smarter decisions on inventory management, pricing strategies, and marketing campaigns.

 

Heading Description
Location :
Ecuador
Client :
Favorita Stores
Project Type :
Data Analytics & Visualization
Duration :
2 Weeks
Completion :
15 Apr 2022
Tools:
Python, Power BI
Deliverables:
Interactive Sales Dashboard

Summary

The analysis revealed significant links between BMI, nutrition, lifestyle choices, and pregnancy risks. High BMI, excessive visceral fat, and poor eating habits were associated with higher rates of cesarean delivery, gestational diabetes, miscarriage, and neonatal complications. Conversely, healthier eating and lifestyle behaviors correlated with improved maternal and fetal outcomes.

Power BI dashboards enabled clear visualization of risk factors, showing that early identification and continuous monitoring can significantly reduce complications. The project demonstrated how data-driven healthcare insights can guide better prenatal care, improve outcomes, and support long-term maternal health.

Recommendations

  1. Strengthen Early Risk Identification

    • Include BMI, waist-hip ratio, visceral fat, and lifestyle screening at the first antenatal visit.

    • Use dashboards and EMR alerts for real-time detection.

    • Impact: +20% earlier high-risk pregnancy detection, -15% emergency C-section rates.

  2. Personalized Lifestyle Interventions

    • Tailor nutrition and physical activity programs for high-BMI mothers.

    • Provide counseling, trimester-specific plans, and community support.

    • Impact: -10–15% gestational diabetes cases within 12 months.

  3. Continuous Monitoring & Feedback

    • Track patient progress through dashboards and mobile apps.

    • Enable multidisciplinary monthly reviews and rapid response.

    • Impact: +25% faster interventions, +20% Apgar score improvements.

  4. Lifestyle Risk Mitigation

    • Reduce smoking, alcohol, and drug use through education and support.

    • Integrate lifestyle counseling in early pregnancy care.

    • Impact: Up to -25% miscarriage risk in high-BMI groups, healthier long-term outcomes.