Power BI Interactive Dashboard Project
This Power BI project analyses the impact of smoking on five key areas: Lungs, Kidneys, Liver, Heart, and Systemic (Overall) Health.
The dashboards compare Healthy vs Damaged cohorts across:
- Total patients & average age/BMI
- Smoking status (Never / Current / Former)
- Smoking intensity (Years of Smoking & Cigarettes per Day)
- Gender distribution
- Cholesterol & Hypertension risk by age group
Total records analysed: 1,500+ patient entries (organ-specific cohorts).
Objective: To visually demonstrate the strong association between current smoking and organ damage, and to highlight the protective effect of quitting.
- Current smokers are dramatically over-represented in damaged groups for lungs (+18.5 pp), kidneys (+22 pp), liver (+5.7 pp), and systemic health (+20.3 pp).
- Damaged lung and liver patients are younger on average → smoking accelerates premature organ damage.
- Former smokers consistently appear in higher proportions in healthy cohorts → quitting works.
- Heart damage shows almost identical smoking status distribution → other factors (cholesterol, hypertension, age) dominate.
- Smoking intensity peaks in the 30–50 age group among damaged cases.
- Males dominate current and former smoker categories across all dashboards.
Key Insight: Largest visible smoking-related damage. Current smokers are 18.5 percentage points higher in the damaged group.
Healthy Lungs (310 patients, avg age 54.6)
Damaged Lungs (168 patients, avg age 51.1)
Findings:
- Current smokers: 48.81% (damaged) vs 30.32% (healthy)
- Never smokers drop from 40.32% to 26.79%
- Damaged patients are 3.5 years younger on average.
Key Insight: Strongest association with current smoking.
Healthy Kidneys (296 patients, avg age 54.1)
Damaged Kidneys (174 patients, avg age 53.9)
Findings:
- Current smokers: 51.72% (damaged) vs 29.73% (healthy) → +22 pp (largest gap)
- Never smokers: only 26.44% in damaged group.
Healthy Liver (342 patients, avg age 53.3)
Damaged Liver (207 patients, avg age 52.5)
Findings:
- Current smokers: 32.85% (damaged) vs 27.19% (healthy) → +5.7 pp
- Damaged patients are younger and have slightly lower BMI.
Healthy Heart (336 patients, avg age 53.7)
Damaged Heart (193 patients, avg age 54.9)
Findings:
- Current smokers: 30.95% (healthy) vs 30.57% (damaged) → almost identical distribution.
- Damaged patients are older → cumulative effect more visible.
Healthy Systemic (319 patients, avg age 54.9)
Damaged Systemic (155 patients, avg age 57.5)
Findings:
- Current smokers: 50.97% in damaged cohort (highest rate observed).
- Clear systemic impact of continued smoking.
- Smoking is the single strongest modifiable risk factor for preventable damage to lungs, kidneys, liver, and overall health.
- Damage appears earlier in smokers (especially lungs and liver).
- Quitting smoking demonstrably shifts patients toward the healthy cohort.
- Heart damage is driven more by the combination of smoking + cholesterol + hypertension.
Clinical
- Mandatory smoking-status screening in pulmonology, nephrology, hepatology, and cardiology.
- Flag current smokers as high-risk for lung, kidney, and liver damage regardless of age.
- Integrate smoking-cessation counselling into routine visits for patients with high cholesterol/hypertension.
Public Health
- Target 30–50 age group with aggressive cessation campaigns (highest intensity & earliest damage).
- Prioritise male smokers in cessation programmes.
- Expand access to free nicotine replacement, counselling, and medication.
Policy
- Fund early screening (low-dose CT, eGFR, LFTs) specifically for current smokers aged 40+.
- Support workplace and community smoking-cessation initiatives.
Further Research
- Longitudinal studies on risk reduction after quitting.
- Pack-year dose-response analysis.
- Interaction between smoking and metabolic risks.
- Open the
.pbixfile in Power BI Desktop. - Use the left navigation to switch between organs.
- Toggle between Healthy and Damaged views using the top buttons.
- Hover over charts for exact values and tooltips.
Technologies: Power BI Desktop, DAX, Power Query, custom visuals.