Evidence map›Paper›PMID 40045675›Full record

ArticleJournal of preventive medicine and public health = Yebang Uihakhoe chi2025

Who Dies Alone? Demographics, Underlying Diseases, and Healthcare Utilization Patterns of Lonely Death Individuals in Korea.

Haibin Bai, Jae-Ryun Lee, Min Jung Kang, Young-Ho Jun, Hye Yeon Koo, Jieun Yun, Jee Hoon Sohn, Jin Yong Lee, Hyejin Lee

Abstract read
In one paragraph

Article in Journal of preventive medicine and public health = Yebang Uihakhoe chi, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Haibin BaiDepartment of Health Policy and Management, Seoul National University College of Medicine, Seoul, Korea.
Jae-Ryun LeeInstitute of Health Policy and Management, Seoul National University Medical Research Center, Seoul, Korea.
Min Jung KangKorea Social Security Information Service, Support Center for Case Management Policy, Seoul, Korea.
Young-Ho JunKorea Social Security Information Service, Support Center for Case Management Policy, Seoul, Korea.
Hye Yeon KooDepartment of Family Medicine, Seoul National University Bundang Hospital, Seongnam, Korea.
Jieun YunDepartment of Pharmaceutical Engineering, Cheongju University, Cheongju, Korea.
Jee Hoon SohnPublic Healthcare Center, Seoul National University Hospital, Seoul, Korea.
Jin Yong LeeDepartment of Health Policy and Management, Seoul National University College of Medicine, Seoul, Korea.
Hyejin LeeDepartment of Family Medicine, Seoul National University Bundang Hospital, Seongnam, Korea.

Funding

Ministry of Health and Welfare
6 · The paper itself

Abstract

objectivesLonely death is defined as "a person living in a state of social isolation, disconnected from family, relatives, and others, who dies from suicide, illness, or other causes". This study investigated the characteristics of individuals who die alone in Korea.

methodsWe constructed a database of lonely death cases by linking data from the Korea Crime Scene Investigation Unit of the Korea National Police Agency with National Health Insurance Service (NHIS) records. A descriptive analysis was performed to evaluate the demographics, underlying diseases, and healthcare utilization patterns among lonely death cases.

resultsAmong the 3122 individuals identified as lonely death cases, 2621 (84.0%) were male and 501 (16.0%) were female. The most common age group was 50-59 years (n=930, 29.8%). The NHIS covered 2161 individuals (69.2%), whereas 961 individuals (30.8%) were enrolled in Medical Aid (MA). The highest number of lonely deaths occurred in Seoul areas, with 1468 cases (47.0%). Mood disorders were diagnosed in 1020 individuals (32.7%), and various alcohol-related diseases, including alcoholic liver disease, were also observed. Outpatient visits increased leading up to death but declined in the final 3 months, while hospitalizations decreased and emergency room visits slightly increased.

conclusionsMost lonely death cases involved male in their 50s, with a disproportionately high number of MA beneficiaries compared to the general population. Many of these individuals also experienced mental health issues or alcohol-related disorders. Preventing social isolation and strengthening social safety nets are critical to reducing the occurrence of lonely deaths.

Indexed as

Patient Acceptance of Health CareAdolescentAdultAgedAged, 80 and overDatabases, FactualDemographyFemaleHumansMaleMiddle AgedRepublic of KoreaSocial IsolationSuicideYoung AdultHealthcare utilizationLonelinessLonely deathNational Health InsurancePre-existing diseaseSocial isolation

Identifiers

PMID40045675
PMCPMC11986590

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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.