Evidence map›Paper›PMID 40762595›Full record

ArticleJournal of Korean medical science2025

Correlation of Income Instability With 12 Non-Communicable Disease Risks in Korea: A Prospective Cohort Study.

Jaehyeong Cho, Yejun Son, Soeun Kim, Jaeyu Park, Kyeongmin Lee, Hyesu Jo, Tae Hyeon Kim, Hayeon Lee, Sooji Lee, Jiyeon Oh and 5 more

Abstract read
In one paragraph

Article in Journal of Korean medical science, 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.

Jaehyeong Cho *Center for Digital Health, Medical Science Research Institute, Kyung Hee University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0009-0008-7892-3741
Yejun Son *Center for Digital Health, Medical Science Research Institute, Kyung Hee University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0009-0001-3939-2983
Soeun KimCenter for Digital Health, Medical Science Research Institute, Kyung Hee University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0009-0009-5874-417X
Jaeyu ParkCenter for Digital Health, Medical Science Research Institute, Kyung Hee University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0009-0005-2009-386X
Kyeongmin LeeCenter for Digital Health, Medical Science Research Institute, Kyung Hee University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0009-0004-0379-2151
Hyesu JoCenter for Digital Health, Medical Science Research Institute, Kyung Hee University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0009-0004-1895-300X
Tae Hyeon KimCenter for Digital Health, Medical Science Research Institute, Kyung Hee University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0009-0008-8555-8156
Hayeon LeeCenter for Digital Health, Medical Science Research Institute, Kyung Hee University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0009-0000-2403-6241
Sooji LeeCenter for Digital Health, Medical Science Research Institute, Kyung Hee University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0009-0002-1413-378X
Jiyeon OhCenter for Digital Health, Medical Science Research Institute, Kyung Hee University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0009-0005-3291-4370
Hanseul ChoDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.ORCID https://orcid.org/0009-0005-7463-4094
Ho Geol WooCenter for Digital Health, Medical Science Research Institute, Kyung Hee University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0001-6489-0100
Damiano PizzolHealth Unit, Eni, Maputo, Mozambique.ORCID https://orcid.org/0000-0003-4122-0774
Selin WooCenter for Digital Health, Medical Science Research Institute, Kyung Hee University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0001-7961-2074
Dong Keon YonCenter for Digital Health, Medical Science Research Institute, Kyung Hee University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0003-1628-9948

Funding

Institute for Information & Communications Technology Planning & Evaluation IITP-2024-RS-2024-00438239National Research Foundation of Korea RS-2024-00460379
6 · The paper itself

Abstract

backgroundDue to the lack of comprehensive longitudinal studies examining the impact of long-term volatility on health issues, existing research primarily focused on income levels rather than fluctuation. Thus, we aimed to investigate the relationship between income instability and a range of physical health conditions using an extensive longitudinal dataset.

methodsThis study utilized data from the Korean Genome and Epidemiology Study (KoGES) Ansan-Anseong cohort (2001-2022), which includes valuable confounding factors such as demographic, socioeconomic, lifestyle, and clinical factors. Income volatility was calculated as the intra-individual standard deviation of income changes across study waves. A Cox proportional hazards model was employed to assess correlations between income volatility and the risk of 12 non-communicable diseases (NCDs; hypertension, myocardial infarction [MI], coronary artery disease [CAD], cerebrovascular disease, diabetes, hyperlipidemia, gout, gastric disease, renal disease, arthritis, allergic disease, and asthma).

resultsA total of 9,185 participants (mean age, 52.21; male, 47.59%) were analyzed. In the fully adjusted model, medium volatility was correlated with a higher disease risk (hazard ratio, 1.14; 95% confidence interval, 1.07-1.21), as similar to high volatility (1.09; 1.03-1.16). The highest risk was observed in individuals experiencing income decreases (1.61; 1.13-2.28). All health conditions examined in this study showed an increased risk correlated with higher income volatility as follows: hypertension (1.13; 1.03-1.25); MI (2.15; 1.33-3.48); CAD (1.37; 1.04-3.48); cerebrovascular disease (1.69; 1.21-2.37); hyperlipidemia (1.14; 1.01-1.28); gout (2.11; 1.12-3.95); gastric disease (1.15; 1.01-1.32); renal disease (2.28; 1.22-4.25); arthritis (1.33; 1.04-1.70); allergic disease (1.54; 1.16-2.03); asthma (1.67; 1.04-1.67).

conclusionIncome volatility, particularly income decreases and fluctuations, is significantly correlated with higher risk of chronic NCDs in South Korea. These findings underscore the need to develop interventions to mitigate financial instability, thereby improving public health outcomes.

Indexed as

IncomeNoncommunicable DiseasesAdultAgedAsthmaCerebrovascular DisordersCoronary Artery DiseaseDiabetes MellitusFemaleGoutHumansHyperlipidemiasHypertensionMaleMiddle AgedMyocardial InfarctionDisease RiskIncome InstabilityKoreaNon-communicable Disease

Identifiers

PMID40762595
PMCPMC12322588

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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 Socratic graph.