The Smoking Health Risk Analysis Dashboard is an interactive Power BI project developed to analyze the impact of smoking on human health using healthcare-related data. The dashboard focuses on understanding smoking patterns, organ conditions, health risks, BMI levels, cholesterol and hypertension risks, and smoking behavior across different age groups and genders.
The project combines healthcare analytics and data visualization techniques to transform raw health data into meaningful visual insights.
Smoking is one of the major causes of health complications affecting organs such as lungs, heart, liver, and kidneys. The objective of this project is to analyze smoking-related health risks and identify patterns associated with age, gender, BMI, and medical conditions.
- Project introduction
- Navigation panel
- Key metrics overview
- Health risk visualization
- Total patient count
- Average age and BMI
- Smoking status distribution
- Smoking intake analysis
- Gender-wise smoking comparison
- Cholesterol & hypertension risk analysis
- Analysis of smokers, former smokers, and non-smokers
- Smoking trends visualization
- Organ-wise health impact analysis
- Damaged vs healthy organ comparison
- Human organ visuals for better storytelling
- Age-group based risk analysis
- Health condition comparison across age categories
- Gender-based smoking behavior analysis
- Smoking distribution comparison between male and female patients
- Power BI
- Power Query
- DAX
- Data Modeling
- Data Cleaning
- Healthcare Dataset
- Interactive Dashboard Design
- Total Patients
- Average Age
- Average BMI
- High Risk Count
- Smoking Status Percentage
- Cholesterol Risk
- Hypertension Risk
- Interactive navigation buttons
- Healthcare-themed UI design
- Organ-based visual storytelling
- Dynamic charts and KPI cards
- Age-group segmentation
- Gender-wise analysis
- Risk categorization
- Most health risks are observed among active smokers
- BMI and age significantly affect health conditions
- Cholesterol and hypertension risks increase with smoking habits
- Male smoking percentage is comparatively higher
- Organ damage is more visible among high-risk categories
- Power BI Dashboard (.pbix)
- Dataset Files
- Dashboard Screenshots
- README Documentation
This project demonstrates how Power BI can be used in healthcare analytics to identify smoking-related health risks and generate data-driven insights through interactive visual dashboards.
Shreenidhi B D