Evidence map›Paper›PMID 40369446›Full record

ArticleBMC public health2025

Cohort profile: the Korean National Health Examination Baseline (KNHEB) cohort for longitudinal health monitoring in South Korea.

Suyoung Jo, Eunsil Cheon, Heewon Kang, Min Kyung Lim, Wankyo Chung, Sun Ha Jee, Keum Ji Jung, Yeun Soo Yang, Seong Yong Park, Sunmi Lee and 5 more

Abstract read
In one paragraph

Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Suyoung JoInstitute of Health and Environment, Seoul National University, Seoul, Republic of Korea.ORCID http://orcid.org/0000-0001-7790-0160
Eunsil CheonDepartment of Public Health Science, Graduate School of Public Health, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, Republic of Korea.ORCID http://orcid.org/0000-0003-4099-8365
Heewon KangInstitute of Health and Environment, Seoul National University, Seoul, Republic of Korea.ORCID http://orcid.org/0000-0002-1519-5678
Min Kyung LimDepartment of Social & Preventive Medicine, College of Medicine, Inha University, Incheon, Republic of Korea.ORCID http://orcid.org/0000-0002-8224-2171
Wankyo ChungInstitute of Health and Environment, Seoul National University, Seoul, Republic of Korea.ORCID http://orcid.org/0000-0001-8094-2433
Sun Ha JeeDepartment of Transdisciplinary Healthcare Sciences, Graduate School of Transdisciplinary Health Sciences, Yonsei University, Seoul, Republic of Korea.ORCID http://orcid.org/0000-0001-9519-3068
Keum Ji JungDepartment of Epidemiology and Health Promotion, Institute for Health Promotion, Graduate School of Public Health, Yonsei University, Seoul, Republic of Korea.ORCID http://orcid.org/0000-0003-4993-0666
Yeun Soo YangDepartment of Epidemiology and Health Promotion, Institute for Health Promotion, Graduate School of Public Health, Yonsei University, Seoul, Republic of Korea.ORCID http://orcid.org/0000-0002-2729-3136
Seong Yong ParkDepartment of Big Data Service, National Health Insurance Service, Wonju, Republic of Korea.ORCID http://orcid.org/0009-0001-4101-8851
Sunmi LeeHealth Insurance Policy Research Institute, National Health Insurance Service, Wonju, Republic of Korea.ORCID http://orcid.org/0000-0003-3051-2798
Jin-Kyoung OhGraduate School of Cancer Science and Policy, National Cancer Center, Goyang, Republic of Korea.ORCID http://orcid.org/0000-0001-9331-3054
Kyoungin NaDivision of Health Hazard Response, Korea Disease Control and Prevention Agency, Cheongju, Republic of Korea.ORCID http://orcid.org/0000-0002-7142-0761
Soyeon KimDivision of Health Hazard Response, Korea Disease Control and Prevention Agency, Cheongju, Republic of Korea.ORCID http://orcid.org/0000-0002-5027-1808
Jieun HwangDepartment of Health Administration, College of Health Science, Dankook University, 119 Dandae-ro, Dongnam-gu, Cheonan-si, Chungcheongnam-do, 31116, Republic of Korea. hwang0310@dankook.ac.kr.ORCID http://orcid.org/0000-0002-5094-6107
Sung-Il ChoInstitute of Health and Environment, Seoul National University, Seoul, Republic of Korea. persontime@hotmail.com.ORCID http://orcid.org/0000-0003-4085-1494

Funding

Korea Disease Control and Prevention Agency 2023-12-104
6 · The paper itself

Abstract

backgroundThe Korean National Health Examination Baseline (KNHEB) cohort was established in 2019 by the Korea Disease Control and Prevention Agency and the National Health Insurance Service to address research gaps and improve standardized monitoring of the health effects of smoking and other modifiable risk factors. It provides scientific evidence to inform national policies on tobacco control and other health determinants, aiming to reduce preventable mortality and disease burden in South Korea.

methodsThe cohort includes 8,916,544 individuals aged ≥ 20 who underwent general health screenings in 2002-2003. It integrates three linked databases: insurance eligibility, medical visits (diagnostic codes, healthcare utilization), and health check-ups (behavioral risk factors, blood test results, etc.). Medical visit and health check-up data were collected until December 2018, while mortality records have been updated through 2019 and continue to be updated annually. At baseline, the mean age of participants was 44.2 years (SD 13.8). The mean follow-up duration was 16.2 years (SD 2.6) for health check-ups among all participants and 9.7 years (SD 4.6) for mortality among deceased individuals. The cohort enables long-term analysis of health outcomes, including cause-specific mortality based on death records and disease incidence identified through diagnostic codes and medical visit data. FINDINGS TO DATE: Analyses using the KNHEB cohort have provided key insights into smoking-related health risks. One study estimated that 60,213 smoking-attributable deaths occurred in South Korea in 2020, while another identified smoking intensity as the strongest predictor of all-cause mortality. Ongoing research include examining the effect of combined health-related factors (HRFs) on cause-specific mortality across age groups and investigating long-term smoking trajectories and alcohol consumption patterns in relation to major non-communicable diseases (NCDs).

conclusionsThe KNHEB cohort provides a large-scale, population-based dataset that supports comprehensive analyses of the long-term effects of modifiable risk factors on NCDs. Its findings contribute to evidence-based policymaking in South Korea and offer comparative insights for global research on chronic disease prevention and risk factor management. Furthermore, its standardized data collection and integration with health records facilitate cross-country comparisons, reinforcing its value as a model for large-scale epidemiological studies on NCDs.

Indexed as

Health SurveysAdultAgedCohort StudiesFemaleHumansLongitudinal StudiesMaleMiddle AgedRepublic of KoreaRisk FactorsSmokingYoung AdultDisease burdenKorean National health examination baseline (KNHEB) cohortModifiable risk factorsNon-communicable diseases (NCDs)Tobacco control policy

Identifiers

PMID40369446
PMCPMC12076992

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.