Depression Survey of Rural Populations with Socioeconomic Indicators

1432 survey records from a study on life conditions in rural zones, focusing on depression. The dataset includes 23 columns covering demographic, family, asset, income, and expense information, with a binary target variable for depression status. It was originally published by Frankcc on Kaggle and curated by Diego Babativa.

Use Cases

• Predicting depression status based on demographic and socioeconomic features like age, education, and assets.
• Analyzing correlations between family structure (e.g., number of children, total members) and mental health outcomes.
• Investigating the relationship between various income sources (salary, farm, business) and depression.
• Studying the impact of living expenses and investments on mental well-being in rural populations.

Strengths

• Contains 1432 rows, providing a substantive sample for analysis.
• Includes 23 features covering a range of demographic, economic, and household variables.
• Has a clear binary target variable ('depressed') for classification tasks.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

Kaggle, originally by Frankcc, curated by Diego Babativa.

Collection Method

Survey study of people living in rural zones.

Time Range

null

Freshness

null

Geography

Rural zones (specific location not stated).