Evidence map›Paper›PMID 39208285›Full record

ArticlePloS one2024

Lifestyle risk behavior and atherosclerotic cardiovascular risk: An analysis using the Korea National Health and Nutrition Examination Survey.

Minwoo Lee, Hyo-Jeong Ahn, Su Jung Lee, Pum-Jun Kim, Chulho Kim, Sang-Hwa Lee, Jong-Hee Sohn, Jae-Jun Lee

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Article in PloS one, 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

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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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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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

8 authors.

Minwoo LeeDepartment of Neurology, Hallym University Sacred Heart Hospital, Anyang, Korea.ORCID 0000-0001-8474-5744
Hyo-Jeong AhnHealth Insurance Review and Assessment Research Institute, Health Insurance Review & Assessment Service, Wonju, Korea.
Su Jung LeeResearch Institute on Nursing Science, School of Nursing, Hallym University, Chuncheon, Korea.
Pum-Jun KimDepartment of Artificial Intelligence, Ulsan National Institute of Science and Technology, Ulsan, Korea.
Chulho KimDepartment of Neurology, Chuncheon Sacred Heart Hospital, Chuncheon, Korea.ORCID 0000-0001-8762-8340
Sang-Hwa LeeDepartment of Neurology, Chuncheon Sacred Heart Hospital, Chuncheon, Korea.
Jong-Hee SohnDepartment of Neurology, Chuncheon Sacred Heart Hospital, Chuncheon, Korea.
Jae-Jun LeeInstitute of New Frontier Research Team, Hallym University College of Medicine, Chuncheon, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundClustering lifestyle risk behaviors is important for predicting cardiovascular disease risk. However, it is unclear which behavior mediates other ones to influence cardiovascular disease risk. We aimed to assess the causal inference of each lifestyle risk behavior for the atherosclerotic cardiovascular disease (ASCVD) risk of the general population.

methodsWe performed a Bayesian network mediation analysis using data from the Korea National Health and Nutrition Examination Survey from 2014 to 2019. The main exposure was a combination of lifestyle risk behaviors including unhealthy weight, heavy alcohol consumption, inadequate sleep, physical inactivity, excessive sodium intake, and current smoking among subjects 40 to 79 years of age. The high risk of ASCVD (≥7.5% for the 10-year risk) was assessed using logistic regression, Bayesian networks, and structural equational models to examine the causal relationships between these six lifestyle risk behaviors.

resultsAmong all participants, the most prevalent lifestyle risk behavior for those at high risk for ASCVD was excessive sodium intake (95.6%), followed by inadequate sleep (49.9%) and physical inactivity (43.8%). Older age (65-79 years) and male sex were directly associated with a high risk for ASCVD. Physical inactivity, current smoking, excessive sodium intake, and unhealthy weight indirectly mediated the effects of older age (8.2% of the older age) and male sex (39.9% of males) to high ASCVD risk. Physical inactivity, current smoking, excessive sodium intake, and unhealthy weight particularly mediated the high ASCVD risk sequentially. Heavy alcohol consumption and inadequate sleep were not directly associated with high ASCVD risk and did not indirectly mediate the effects of older age and males on the high ASCVD risk.

conclusionLifestyle risk behaviors mediated the atherosclerotic cardiovascular disease risk in a different manner. Especially, physical inactivity preceded current smoking, excessive sodium intake, and unhealthy weight in relation to high ASCVD risk, and this causal relationship was different according to age and sex. Therefore, tailored strategies according to specific target populations may be needed to effectively reduce the high ASCVD risk.

Indexed as

AtherosclerosisLife StyleNutrition SurveysAdultAgedAlcohol DrinkingBayes TheoremCardiovascular DiseasesFemaleHumansMaleMiddle AgedRepublic of KoreaRisk FactorsRisk-TakingSmoking

Identifiers

PMID39208285
PMCPMC11361657

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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.