Health and Lifestyle Factors Dataset

Columns

• Name: The full name of the individual. This column has 196,851 unique values and is 100% valid across 414,000 records [3, 5].
• Age: The age of the individual in years, ranging from 18 to 80, with a mean of 49 years [3, 6]. This column is 100% valid [6].
• Marital Status: The marital status of the individual, with possible values including Single, Married, Divorced, and Widowed [3]. The most common status is Married, accounting for 58% of records [7].
• Education Level: The highest level of education attained, including High School, Associate Degree, Bachelor's Degree, Master's Degree, and PhD [8]. Bachelor's Degree is the most common at 30% [7].
• Number of Children: The count of children the individual has, ranging from 0 to 4, with a mean of 1.3 [7-9].
• Smoking Status: Indicates whether the individual is a Smoker, Former, or Non-smoker [8]. Non-smokers represent 60% of the dataset [9].
• Physical Activity Level: The individual's physical activity, categorised as Sedentary, Moderate, or Active [8]. Sedentary is the most prevalent level at 43% [9, 10].
• Employment Status: The individual's employment situation, either Employed or Unemployed [11]. Employed individuals make up 64% of the dataset [10].
• Income: The annual income of the individual in USD, ranging from 0.41 to 210,000 USD, with a mean of 50,700 USD [11, 12].
• Alcohol Consumption: The level of alcohol consumption, specified as Low, Moderate, or High [11]. Moderate consumption is the most common at 42% [12].
• Dietary Habits: The individual's dietary habits, categorised as Healthy, Moderate, or Unhealthy [11]. Unhealthy and Moderate are both common at 41% each [13].
• Sleep Patterns: The quality of sleep, defined as Good, Fair, or Poor [11]. Fair sleep patterns are most common at 48% [13].
• History of Mental Illness: Indicates whether the individual has a history of mental illness (Yes or No) [11]. Approximately 30% of individuals have a history of mental illness [13, 14].
• History of Substance Abuse: Indicates whether the individual has a history of substance abuse (Yes or No) [4]. Approximately 31% of individuals have a history of substance abuse [14].
• Family History of Depression: Indicates if there is a family history of depression (Yes or No) [4]. About 27% of individuals have a family history of depression [15].
• Chronic Medical Conditions: Indicates whether the individual has chronic medical conditions (Yes or No) [4]. Approximately 33% of individuals have chronic medical conditions [15].

Distribution

Usage

• Predictive modelling: For example, predicting health outcomes based on lifestyle.
• Clustering: Grouping individuals with similar health and lifestyle profiles.
• Exploratory data analysis: Gaining insights into the relationships between different factors [4].

Coverage

License

Who Can Use It

• Data scientists and machine learning engineers for developing predictive models.
• Researchers in public health, sociology, and behavioural sciences for exploratory data analysis and understanding correlations.
• Healthcare analysts and policymakers for identifying trends and informing health initiatives.
• Students and academics for educational purposes and research projects related to health and socio-economic factors.

Dataset Name Suggestions

• Health and Lifestyle Factors Dataset
• Socio-Economic Health Indicators
• Individual Health Attributes Dataset
• Synthetic Lifestyle Data
• Well-being Factors Dataset

Attributes