The effects of coffee consumption on lifestyle factors
Context and objective
Context
Coffee plays a big part in many people’s lives across the globe. So much so that around 400 billion cups of coffee per year which makes it the second most consumed beverage after water!
At the same time people are becoming more conscious of their health and how what they consume effects their health.
In recent years there have been a number of studies that suggest that moderate coffee consumption can lead to longer and healthier life, with some even showing it may lower the risk of death, cardiovascular disease, and certain cancers.
Client
General Practitioners and coffee drinkers interested in exploring relationships with coffee consumption and wider lifestyle health factors.
Objective
To draw out some key insights around coffee consumption and lifestyle factors including Body Mass Index (BMI), hours of sleep and reported health issues.
Data and tools
Dataset
The data within this dataset is synthetic but captures realistic correlations observed in research.
It contains 10,000 synthetic records reflecting real-world patterns of coffee consumption, sleep behavior, and health outcomes across 20 countries.
It includes demographics, daily coffee intake, caffeine levels, sleep duration and quality, BMI, heart rate, stress, physical activity, health issues, occupation, smoking, and alcohol consumption.
Tools
Excel, Python (Pandas, Matplotlib, Seaborn, Scikit-learn) and Tableau
Procedures
→ Machine Learning Linear Regression
→ Clustering Analysis
→ Presenting findings to stakeholders
