Cardiovascular disease (CVD) is highly prevalent worldwide and its number nearly doubled from 271 million in 1990 to 523 million in 2019 (1, 2). The global trends for disability-adjusted life years and years of life lost also increased significantly and the number of CVD deaths increased steadily by 53.7% from 1990 to 2019 (2, 3). Among the modifiable risk factors for attributable CVD burden, high body mass index (BMI) ranked fifth and could worsen most other CVD risk factors (2, 4, 5). Unfortunately, 50.7% of Chinese adults were overweight or obesity in the most recent national survey (6), which may result in larger CVD burden. However, BMI might not fully capture cardiometabolic risk because of its failure in discriminating adequately between body fat mass and lean tissues or identifying regional body fat distribution (7, 8). Therefore, identifying reliable and applicable obesity indices would benefit to reducing CVD burden among Chinese population.

Recently, Chinese visceral adiposity index (CVAI), like visceral adiposity index (VAI) for Western population, was established to assess visceral adiposity among Chinese population and could predict metabolic disorders incidence well (9, 10). Numerous studies have demonstrated that CVAI has better performance than other obesity indices for predicting hypertension, diabetes, and their comorbidity (11–16). However, whether CVAI also predict incident CVD well among general population remains unclear. Studies based on rural population from a Chinese county or health examination population in a Beijing hospital reported positive associations between CVAI and stroke or coronary heart disease (17, 18), respectively. Another study from a Chinese province showed that CVAI was positively associated with CVD in women but not in men (19). Therefore, prospective cohort studies based on national data are needed to further validate CVAI as a visceral obesity index to predict incident CVD, which would provide additional epidemiological evidence for future CVD prevention.

Our study aimed to explore the dose–response associations of CVAI with CVD, heart disease, and stroke and compare the predictive ability of CVAI with that of other obesity indices (VAI, a body shape index [ABSI], conicity index [CI], waist circumference [WC], and BMI) based on China Health and Retirement Longitudinal Study (CHARLS).

This prospective cohort study found linear associations of CVAI with CVD, heart disease, and stroke. Compared with quartile 1 of CVAI, the risk of CVD, heart disease, and stroke in quartile 4 increased 50%, 29%, and 145%, respectively. Per-SD increase in CVAI was associated with 17%, 12%, and 31% increased risk of CVD, heart disease, and stroke and confer higher risk in participants aged<60 years than those aged ≥60 years. Finally, we compared the ability of CVAI, VAI, ABSI, CI, WC, and BMI in predicting CVD, heart disease, and stroke and found CVAI as the best predictor among these obesity indices. Our study suggested CVAI as a reliable visceral obesity index for predicting CVD in Chinese adults.

Recent national survey showed that more than half of Chinese adults had overweight or obesity (6). Mounting evidence supported that visceral obesity was more strongly associated with CVD than overall obesity (27–29). Considering higher visceral fat in Asian people than Western people at a given BMI level (30, 31), evaluating visceral obesity would be more helpful for assessing risk of CVD among Chinese people. However, routine access to CT and MRI to assess visceral fat might be not suitable in general clinical practice and large cohort studies; thus, CVAI, constructed based on visceral fat by CT, was developed to evaluate visceral obesity among Chinese population (9). A study from a province in Southwest China study showed CVAI was associated with CVD in women but not in men (19). In our study, we visualized the association of CVAI with CVD and found positive associations in both men and women. Consistent with our findings, Zhao et al. found CVAI associated with stroke based on rural population of a Chinese county (17). We additionally found linear association between CVAI and stroke using national data, which was in line with Zhang et al. using logistic model (32). Similar to our findings, a study based on examination population in a Beijing hospital also found positive associations between CVAI and coronary heart disease in both men and women (18). Previous studies also reported that CVAI was positively associated with carotid atherosclerosis or carotid plaque (33, 34), which verified the rationality of the association between CVAI and CVD. Besides, we further explored the interaction of age, gender, hypertension, diabetes, and elevated TC on the associations of CVAI with CVD, heart disease, and stroke. Subgroup analyses showed participants aged<60 years had higher risk of CVD, heart disease, and stroke than those aged ≥60 years, which may be explained by longer duration of exposure to excess visceral fat.

Our results indicated that CVAI had the best ability to predict incident CVD, heart disease, and stroke among these obesity indices (CVAI, VAI, ABSI, CI, WC, and BMI). Previous studies also showed that CVAI was a better obesity indicator for coronary heart disease incidence than VAI, WC, and BMI and for stroke than other insulin resistance indices (17, 18). Besides, CVAI also had larger predictive value for cardiovascular events than VAI, WC, and BMI in Chinese diabetic patients (35, 36). A potential explanation for those findings may be that CVAI could evaluate visceral fat better in Chinese population (9). Contrast with measurement of visceral fat by CT and MRI (29, 37), CVAI, based on age, BMI, WC, TG, and HDL-C, are available and reliable to assess obesity in routine clinical practice and large cohort studies. Identifying participants with higher risk of CVD and then implementing lifestyle interventions may benefit to lower CVD risk.

Several potential mechanisms were suggested to explain the association between visceral obesity and CVD. Visceral adiposity promotes systemic and vascular inflammation by increasing production of interleukin-6, tumor necrosis factor-α, and high-sensitivity C-reactive protein, which lead to atherogenesis and subsequently incident CVD (38–40). Besides, visceral adiposity disturbs the renin–angiotensinogen system and produces excessive reactive oxygen species and reactive nitrogen species, and then induce oxidative stress, which could be presented as oxidized low-density lipoprotein, 8-hydroxylated deoxyguanosine, malondialdehyde, thioredoxin, and advanced oxidation protein products; the oxidative stress would induce a vicious cycle of endothelial dysfunction, inflammation, fibroblast proliferation and affect cerebral arteries through stenosis and occlusion, leading to CVD incidence (38, 41–44). Also, visceral obesity causes insulin resistance through increasing the production of inflammatory markers and adipocytokines and reducing that of adiponectin, which result in CVD incidence (45–47).

The present study comprehensively explored the associations of CVAI with CVD, heart disease, and stroke and compared the predictive ability of CVAI with other obesity indices (VAI, ABSI, CI, WC, and BMI) based on a national prospective cohort study. The findings are reliable and can be generalized to Chinese or other Asian people. Some limitations should be noted. First, we did not evaluate the effect of dynamic change in CVAI on CVD. Second, we failed to adjust for residual confounders, such as diet, air pollution, etc. Third, our study did not enable conclusions causal despite the prospective cohort design.

Our study showed that CVAI was linearly associated with risk of CVD, heart disease, and stroke and CVAI had the best predictive ability among these obesity indices. The findings support CVAI as a suitable visceral obesity index for predicting CVD in Chinese or other Asian adults because of the availability of its components in large prospective studies and routine clinical practice.

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: This analysis uses data or information from the Harmonized CHARLS dataset and Codebook, Version D as of June 2021 developed by the Gateway to Global Aging Data. The development of the Harmonized CHARLS was funded by the National Institute on Aging (R01 AG030153, RC2 AG036619, R03 AG043052). For more information, please refer to https://g2aging.org/.

The studies involving humans were approved by public databases-China Health and Retirement Longitudinal Study (CHARLS). Besides, the protocols of CHARLS were approved by the Biomedical Ethics Review Committee of Peking University (IRB00001052-11015). The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

YR: Conceptualization, Data curation, Formal analysis, Funding acquisition, Project administration, Resources, Writing – original draft, Writing – review & editing. QH: Data curation, Writing – review & editing. ZL: Data curation, Investigation, Writing – review & editing. XZ: Data curation, Methodology, Writing – review & editing. LY: Conceptualization, Resources, Writing – review & editing. LK: Resources, Writing – review & editing.