A Curated Multimodal Dataset for Sleep Apnea and Cardiometabolic Comorbidities (Healthcare)

Abstract

This dataset represents the Gold Layer of a Sleep Apnea Data Warehouse developed using a Medallion Architecture (Bronze–Silver–Gold) in Microsoft SQL Server. It contains 10,044 unique patient records and 47 curated analytical features integrating demographic, physiological, clinical, lifestyle, and diagnostic data for research on obstructive sleep apnea (OSA) and metabolic comorbidities. The dataset was generated by integrating multiple structured health data sources through ETL processes, dimensional modeling, and feature engineering into a unified star-schema warehouse. Each record corresponds to a single patient and includes demographics (age, gender, occupation), metabolic indicators (BMI, glucose, insulin, HbA1c, cholesterol), cardiovascular variables (blood pressure, heart rate), sleep-related physiological measurements (AHI, oxygen saturation, EEG sleep stage, nasal airflow, chest movement), lifestyle indicators (physical activity, stress, diet, alcohol use), and diagnostic labels for sleep apnea, hypertension, and diabetes. The Gold Layer includes engineered variables such as age bands, BMI categories, comorbidity profiles, binary health flags, and standardized analytical features optimized for machine learning and clinical analytics. The repository was designed to support predictive modeling, multi-label classification, risk stratification, clustering, and healthcare business intelligence applications. Exported in CSV format with UTF-8 encoding, the dataset is compatible with Python, R, SQL Server, Power BI, Tableau, and statistical analysis tools. Synthetic composite identifiers are used, and no personally identifiable information is included, supporting ethical data sharing for research and educational purposes. Potential applications include OSA diagnosis prediction, comorbidity risk scoring, explainable machine learning, patient segmentation, feature engineering research, and demonstration of Medallion Architecture implementation in healthcare data warehousing. This dataset also serves as a reproducible benchmark for integrating data engineering and medical analytics workflows. Keywords: Sleep Apnea, OSA, Healthcare Analytics, Data Warehouse, Gold Layer, Medallion Architecture, Predictive Modeling, Multi-label Classification, Clinical Data Engineering.