Revealing the U-shaped nonlinear relationship between lipid accumulation product levels and cardiovascular disease risk using the large CHARLS cohort study in China

Cardiovascular disease (CVD) poses a major health challenge in China. Lipid accumulation product (LAP), reflecting body fat distribution, has been associated with CVD risk. However, evidence regarding the relationship between LAP and CVD among Chinese populations remains limited. This study utilized data from the China Health and Retirement Longitudinal Study, a large national cohort study. A total of 4,481 participants aged ≥ 45 years without CVD at baseline were included, with a 9-year follow-up. Cox regression analyses were performed to examine the association between LAP and CVD incidence. Subgroup and sensitivity analyses were also conducted. LAP was associated with CVD risk in a U-shaped manner, with higher risks observed at both low and high LAP levels (inflection point = 2.7). For LAP ≤ 2.7, the hazard ratio (HR) for CVD was 0.62 (95% CI: 0.40, 0.96, P = 0.0309), indicating a 38% decreased risk with increasing LAP. For LAP > 2.7, the HR was 1.22 (95% CI: 1.04, 1.44, P = 0.0153), suggesting a 22% increased risk. This study revealed a U-shaped nonlinear relationship between LAP and CVD risk in Chinese adults, with risks elevated at both low and high LAP levels. The findings suggest LAP could serve as an effective predictor for CVD among the Chinese population. Further studies are warranted to validate the results.

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Publication Details

Journal
BMC Public Health
Published
2025-11-14
DOI
https://doi.org/10.1186/s12889-025-25096-8
Citations
1
Primary Topic
Diabetes, Cardiovascular Risks, and Lipoproteins
Type
article
Field-Weighted Citation Impact
1.29
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article

Revealing the U-shaped nonlinear relationship between lipid accumulation product levels and cardiovascular disease risk using the large CHARLS cohort study in China

Yuanbo Zhang, Tao Zheng, Gang Sun, Chen Chi
1 citations
BMC Public Health
Diabetes, Cardiovascular Risks, and Lipoproteins
1.29
article

Revealing the U-shaped nonlinear relationship between lipid accumulation product levels and cardiovascular disease risk using the large CHARLS cohort study in China

Yuanbo Zhang, Tao Zheng, Gang Sun, Chen Chi
article en
1 citations

Abstract

Cardiovascular disease (CVD) poses a major health challenge in China. Lipid accumulation product (LAP), reflecting body fat distribution, has been associated with CVD risk. However, evidence regarding the relationship between LAP and CVD among Chinese populations remains limited. This study utilized data from the China Health and Retirement Longitudinal Study, a large national cohort study. A total of 4,481 participants aged ≥ 45 years without CVD at baseline were included, with a 9-year follow-up. Cox regression analyses were performed to examine the association between LAP and CVD incidence. Subgroup and sensitivity analyses were also conducted. LAP was associated with CVD risk in a U-shaped manner, with higher risks observed at both low and high LAP levels (inflection point = 2.7). For LAP ≤ 2.7, the hazard ratio (HR) for CVD was 0.62 (95% CI: 0.40, 0.96, P = 0.0309), indicating a 38% decreased risk with increasing LAP. For LAP > 2.7, the HR was 1.22 (95% CI: 1.04, 1.44, P = 0.0153), suggesting a 22% increased risk. This study revealed a U-shaped nonlinear relationship between LAP and CVD risk in Chinese adults, with risks elevated at both low and high LAP levels. The findings suggest LAP could serve as an effective predictor for CVD among the Chinese population. Further studies are warranted to validate the results.

BMC Public HealthVol. 25(1)
Guiyang College of Traditional Chinese Medicine (CN), Affiliated Hospital of Guizhou Medical University (CN)
Openalex Percentile: Top 14%
Diabetes, Cardiovascular Risks, and Lipoproteins
1.29
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Revealing the U-shaped nonlinear relationship between lipid accumulation product levels and cardiovascular disease risk using the large CHARLS cohort study in China — Yuanbo Zhang, Tao Zheng, et al. · BMC Public Health (2025) | TGRS Research Map | TGRS