Smoking and Drinking Prediction Data

Columns

• Sex: Indicates the biological sex of the individual, with values 'male' and 'female'. Approximately 53% of records are male and 47% are female.
• Age: Rounded up to 5-year intervals, representing the age of the individual. The age range in the dataset is from 20 to 85 years, with a mean age of 47.6 years.
• Height: Measured in centimetres [cm], rounded up to 5 cm. Heights range from 130 to 190 cm, with a mean height of 162 cm.
• Weight: Measured in kilograms [kg]. Weights range from 25 to 140 kg, with a mean weight of 63.3 kg.
• Waistline: Measured in centimetres [cm]. Waistline measurements range from 8 to 999 cm, with a mean of 81.2 cm.
• Sight_left: Represents left eyesight. Values range from 0.1 to 9.9, with a mean of 0.98.
• Sight_right: Represents right eyesight. Values range from 0.1 to 9.9, with a mean of 0.98.
• Hear_left: Indicates left hearing, where 1 is normal and 2 is abnormal. Approximately 96.8% of records are normal hearing.
• Hear_right: Indicates right hearing, where 1 is normal and 2 is abnormal. Approximately 96.9% of records are normal hearing.
• SBP: Systolic blood pressure [mmHg]. Readings range from 67 to 273 mmHg, with a mean of 122 mmHg.
• DBP: Diastolic blood pressure [mmHg]. Readings range from 32 to 185 mmHg, with a mean of 76.1 mmHg.
• BLDS: BLDS or FSG (fasting blood glucose) [mg/dL]. Values range from 25 to 852 mg/dL, with a mean of 100 mg/dL.
• Tot_chole: Total cholesterol [mg/dL]. Values range from 30 to 2340 mg/dL, with a mean of 196 mg/dL.
• HDL_chole: HDL cholesterol [mg/dL]. Values range from 1 to 8110 mg/dL, with a mean of 56.9 mg/dL.
• LDL_chole: LDL cholesterol [mg/dL]. Values range from 1 to 5120 mg/dL, with a mean of 113 mg/dL.
• Triglyceride: Triglyceride [mg/dL]. Values range from 1 to 9490 mg/dL, with a mean of 132 mg/dL.
• Hemoglobin: Hemoglobin [g/dL]. Values range from 1 to 25 g/dL, with a mean of 14.2 g/dL.
• Urine_protein: Protein in urine, categorised from 1 (-) to 6 (+4). The vast majority of records (94.3%) are category 1 (-).
• Serum_creatinine: Serum (blood) creatinine [mg/dL]. Values range from 0.1 to 98 mg/dL, with a mean of 0.86 mg/dL.
• SGOT_AST: SGOT (Glutamate-oxaloacetate transaminase) AST (Aspartate transaminase) [IU/L]. Values range from 1 to 10000 IU/L, with a mean of 26 IU/L.
• SGOT_ALT: ALT (Alanine transaminase) [IU/L]. Values range from 1 to 7210 IU/L, with a mean of 25.8 IU/L.
• Gamma_GTP: Y-glutamyl transpeptidase [IU/L]. Values range from 1 to 999 IU/L, with a mean of 37.1 IU/L.
• SMK_stat_type_cd: Smoking state, categorised as 1 (never), 2 (used to smoke but quit), or 3 (still smoke). Approximately 60.7% are never smokers, 17.6% used to smoke, and 21.6% still smoke.
• DRK_YN: Drinker or Not, a boolean field indicating if the individual is a drinker. The dataset is nearly balanced with 50% true (drinker) and 50% false (not a drinker).

Distribution

Usage

• Developing predictive models to classify individuals as smokers or drinkers based on their body signal data.
• Conducting in-depth analysis of the relationship between various body signals and smoking/drinking habits.
• Building binary classification models in the health and medicine domains.
• Researching public health trends and risk factors related to lifestyle choices.

Coverage

License

Who Can Use It

• Data Scientists and Machine Learning Engineers: For building and testing classification models to predict health behaviours.
• Public Health Researchers: To analyse health trends, identify correlations between body signals and lifestyle, and inform public health initiatives.
• Medical Professionals and Researchers: For studying the impact of smoking and drinking on various physiological markers.
• Students and Academics: As a practical resource for learning about health data analysis, classification, and predictive modelling.

Dataset Name Suggestions

• Korean Health Habits and Body Signals Dataset
• Smoking and Drinking Prediction Data
• Health Behaviour Classification Dataset
• Korean Biomedical Lifestyle Data
• Physiological Markers of Habits

Attributes