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Health & Lifestyle is a health lifestyle dataset released in 2025. It aims to explore the relationship between lifestyle factors and individual health status and provide an experimental basis for health prediction modeling, cluster analysis and data mining.

This dataset contains 100,000 individual records, provided in a CSV format. It covers a wide range of information, from demographics to health status and lifestyle habits. The data does not contain any real personal information; all values are artificially synthesized, while maintaining statistical consistency with real-world distributions.

Data Structure

The fields of a dataset can be roughly divided into the following categories:

• Demographic characteristics: including individual number (ID), age (age), gender (gender), and body mass index (BMI).
• Health indicators: including resting heart rate (resting_hr), systolic blood pressure (systolic_bp), diastolic blood pressure (diastolic_bp), and cholesterol level (cholesterol).
• Lifestyle habits: including average daily steps (daily_steps), average sleep duration (sleep_hours), daily water intake (water_intake_l), daily calorie intake (calories_consumed), smoking status (smoker), and drinking status (alcohol).
• Family and disease risk: includes family medical history (family_history) and disease risk (disease_risk, label field).