Evidence map›Paper›PMID 39282533›Full record

ArticlePreventive medicine reports2024

The economic cost of direct smoking in South Korea.

Kristine Namhee Kwon, Kangyeon Lee, Wankyo Chung

Abstract read
In one paragraph

Article in Preventive medicine reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
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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

3 authors.

Kristine Namhee KwonDepartment of Health Policy and Management, Milken Institute School of Public Health, George Washington University, Washington, DC, USA.
Kangyeon LeeDivision of Health Services Management and Policy, College of Public Health, The Ohio State University, Columbus, OH, USA.
Wankyo ChungDepartment of Public Health Sciences, Graduate School of Public Health, Seoul National University, Seoul, South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Smoking not only causes negative health outcomes for individuals but also causes an economic burden to society. This study estimated the socioeconomic costs of direct smoking in South Korea in 2020. Methods: We used the prevalence-based cost-of-illness approach to estimate the sum of the direct (medical, transportation, and caregiving) and indirect (productivity loss due to health service utilization and premature death) costs of 41 smoking-related diseases. We assumed that diseases with death-based hazard ratios greater than 1.0 were related to smoking and used them in cost estimation. Results: The socioeconomic cost of direct smoking in Korea was USD 10.9 billion in 2020, accounting for 0.67 % of the gross domestic product and 8.0 % of current health expenditures. The direct cost was USD 4,172 million and the indirect cost was USD 6,753 million. The cost of productivity loss due to premature death took up the largest amount of the total cost, accounting for 52.3 %. The amount attributed to males accounted for 90.4 % of the overall cost, totaling to USD 9,877 million. This is attributable to higher smoking rates and higher medical costs in men. Cancer costs accounted for 40.0 % of the total cost, causing the greatest burden of diseases. Conclusion: Direct smoking imposed a harmful and heavy economic burden on South Korea. Our estimate provides the latest evidence on the financial burden of smoking and strengthens the case for strong tobacco control policies and interventions.

Indexed as

Cost-of-illnessDirect smokingSmokingSmoking policySmoking-related diseasesSocioeconomic cost of smoking

Identifiers

PMID39282533
PMCPMC11399556

What OpenQuestion holds

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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.