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Family tree database of the National Health Information Database in Korea
Yeon-Yong Kim, Hae-young Hong, Kyu-Dong Cho, Jong Heon Park
Epidemiol Health. 2019;41:e2019040.   Published online October 1, 2019
DOI: https://doi.org/10.4178/epih.e2019040
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  • 7 Web of Science
  • 6 Crossref
AbstractAbstract AbstractSummary PDFSupplementary Material
Abstract
We constructed the family tree database (DB) by using a new family code system that can logically express interpersonal family relationships and by comparing and complementing health insurance eligibility data and resident register data of the National Health Information Database (NHID). In the family tree DB, Parents and grandparents are matched for more than 95% of those who were born between 2010 and 2017. Codes for inverse relationships and extended relationships are generated using sequences of the three-digit basic family codes. The family tree DB contains variables such as sex, birth year, family relations, and degree of kinship (maximum of 4) between subjects and family members. Using the family tree DB, we find that prevalence rates of hypertension, diabetes, ischemic heart disease, cerebrovascular disease, and cancer are higher for those with family history. The family tree DB may omit some relationships due to incomplete past data, and some family relations cannot be uniquely determined because the source data only contain relationships between head and members of the household. The family tree DB is a part of the NHID, and researchers can submit requests for data on the website at http://nhiss.nhis.or.kr. Requested data will be provided after approval from the data service review board. However, the family tree DB can be limitedly provided for studies with high public value in order to maximize personal information protection.
Summary
Korean summary
가족관계도(family tree) DB는 건강보험공단이 보유하는 건강보험 가입자정보와 행정전산망 정보를 바탕으로 가공·구축된 자료다. 4촌까지의 가족 관계를 파악할 수 있으며, 세대주 중심의 관계코드가 아닌 개인 단위의 논리적 기호로 구성된 관계코드를 통해 촌수, 계통, 성별을 구분하도록 하였다. 이를 바탕으로 의학적, 사회정책적으로 다양한 연구가 가능하다.

Citations

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    Journal of the American Heart Association.2023;[Epub]     CrossRef
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    Journal of Diabetes & Metabolic Disorders.2020; 19(1): 405.     CrossRef

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