A nationally representative linked cohort integrating KNHANES, health insurance claims, and mortality data in Korea: construction, linkage performance, and research applications

Abstract

Understanding the determinants and long-term outcomes of chronic diseases requires integrated population-based data linking health behaviors, healthcare utilization, and mortality. Despite Korea’s high-quality nationwide databases, systematic linkage between nationally representative survey data, insurance claims, and mortality records has remained limited. This study aimed to construct a nationally linked health cohort integrating the Korea National Health and Nutrition Examination Survey (KNHANES) with administrative health databases. KNHANES (2013–2021) was deterministically linked to the National Health Insurance Service (NHIS) eligibility and health screening databases, the Health Insurance Review and Assessment Service (HIRA) claims database, and the Statistics Korea mortality registry using pseudonymized encrypted identifiers. A cross-sectional cohort ( n = 53,326) was used to assess linkage performance and baseline comparability, and a longitudinal cohort ( n = 65,447) enabled outcome analyses. Chronic diseases were defined using ICD-10 codes, and age-standardized rates were estimated. Linkage rates ranged from 64.1% to 85.8% across databases, and baseline characteristics of the linked cohort were comparable to the original KNHANES population. Temporal patterns indicated declining smoking and high-risk alcohol consumption, alongside increasing metabolic conditions such as obesity and diabetes mellitus. The dataset enabled estimation of incidence and mortality outcomes, with higher cardiometabolic disease burden observed in men. This linked cohort, derived from a nationally representative survey integrates behavioral, clinical, and outcome data at the individual level, addressing key limitations of single-source datasets. It provides a scalable resource for chronic disease surveillance, longitudinal risk factor analysis, and evidence generation to inform public health policy.