Evidence map›Paper›PMID 39987443›Full record

ArticleEuropean journal of medical research2025

Correlation of visceral adiposity index and dietary profile with cardiovascular disease based on decision tree modeling: a cross-sectional study of NHANES.

Shiyong Xu, Yirou Cai, Haizhen Hu, Changlin Zhai

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Article in European journal of medical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

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9citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Shiyong Xu *Department of Cardiology, Affiliated Hospital of Jiaxing University, 1882 Zhonghuan S Rd, Jiaxing, 314000, Zhejiang Province, China.
Yirou Cai *Hospital of the Chinese People's Armed Police Force Maritime Safety Bureau, Zhejiang, China.
Haizhen HuDepartment of Cardiology, Affiliated Hospital of Jiaxing University, 1882 Zhonghuan S Rd, Jiaxing, 314000, Zhejiang Province, China.
Changlin ZhaiDepartment of Cardiology, Affiliated Hospital of Jiaxing University, 1882 Zhonghuan S Rd, Jiaxing, 314000, Zhejiang Province, China. yesterdaygun@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundVisceral adiposity index (VAI) and diets are associated with the risk of cardiovascular disease (CVD). It is unclear how well VAI and diet predict CVD.

methodsData were obtained from the National Health and Nutrition Examination Survey (NHANES 2017-2018). Demographic data, diets, biochemical examination, and questionnaire information were collected. VAI was calculated using body mass index, waist circumference, triglycerides, and high-density lipoprotein cholesterol. Binary logistic regression was adopted to examine the correlation of VAI and diets with CVD. A decision tree model was developed to predict CVD risk according to different factors.

results2104 participants (mean age: 50.87 ± 17.35 years, 48.38% males) were included. Participants with high levels of VAI (≥ 2.18) had an elevated risk of CVD compared to those with low levels of VAI (≤ 0.76) (OR = 1.654, 95% CI: 1.025-2.669, P = 0.039). Compared with the low protein intake level (≤ 50.34 g), the upper intermediate (72.10-99.92 g) (OR = 0.445, 95% CI: 0.257-0.770, P = 0.004) and high (≥ 99.93 g) levels of protein intake (OR = 0.450, 95% CI: 0.236-0.858, P = 0.015) reduced CVD risk. The decision tree model unveiled that VAI, protein intake, and dietary fiber intake were predictors for CVD.

conclusionVAI and protein intake levels are independently associated with CVD risk and have predictive power for CVD. These findings can provide insights into the development of appropriate lifestyle and treatment strategies for patients to reduce the incidence of CVD.

Indexed as

Cardiovascular DiseasesDietIntra-Abdominal FatObesity, AbdominalAdiposityAdultAgedBody Mass IndexCross-Sectional StudiesDecision TreesFemaleHumansMaleMiddle AgedNutrition SurveysRisk FactorsCardiovascular diseaseDecision treeNHANESVisceral adiposity index

Identifiers

PMID39987443
PMCPMC11847326

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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.