In this population-based cross-sectional study, we confirmed for the first time a linear positive correlation between Hs-CRP and the prevalence of CVD in people with diabetes, and further found a stratified correlation between Hs-CRP and CVD prevalence in the less than 60 years, male, non-hypertension or non-hypercholesterolemia population, which warrants further discussion on the importance of Hs-CRP in the occurrence and development of CVD.

In recent years, the correlation between inflammation and CVD has been increasingly reported. For example, new inflammatory markers representing systemic inflammation have been shown to be closely related not only to CVD in diabetic patients but also to the mortality of CVD [11, 12]. Besides, current evidence suggests that Hs-CRP is also associated with CVD and a number of metabolic-related diseases. For example, a systematic review and meta-analysis including 12 case-control studies and 8,345 patients showed that Hs-CRP could predict the risk of abdominal aortic aneurysms of intermediate or small aortic diameter [13]. In addition, Liu et al. revealed an independent association of Hs-CRP with all-cause death, cardiac death, and major adverse cardiovascular and cerebrovascular events in a study involving 3,069 elderly patients with coronary artery disease with three-vessel disease [14]. Furthermore, in a cross-sectional study including only patients with type 2 diabetes, Tang et al. found that patients with Hs-CRP levels in the fourth quartile had a 96.8% increased risk of diabetic nephropathy compared to patients with Hs-CRP levels in the first quartile, and both in the total population and in a sex-specific population, the RCS further revealed a a linear positive association between Hs-CRP and risk of diabetic nephropathy [15]. In another real-world study that included only 1,804 patients with acute myocardial infarction, Hs-CRP was not only shown to be an independent predictor of in-hospital poor prognosis, but was also shown to improve the predictive power of the GRACE score for in-hospital poor prognosis [16]. Moreover, in a prospective cohort study including 4.8 years of follow-up and 1,281 patients with acute heart failure, long-term cumulative exposure to higher levels of Hs-CRP also had a significant impact on poor prognosis and mortality in hospitalised patients with heart failure, suggesting that long-term monitoring of Hs-CRP is of great interest for the prevention of cardiovascular events [17]. Additionally, in a community-based prospective cohort study, Yoshikawa et al. found that after 24 years of follow-up, participants in the third and fourth quartiles of Hs-CRP levels had 1.77 and 1.89 times the risk of developing atrial fibrillation compared with those in the first quartile of Hs-CRP levels, respectively [18]. Furthermore, another community-based cohort study from China demonstrated a 64%, 25%, and 31% increased risk of atrioventricular block, left bundle branch block, and right bundle branch block, respectively, in individuals with Hs-CRP > 3 mg/L compared to individuals with Hs-CRP ≤ 3 mg/L, and the RCS further showed a linear positive correlation between Hs-CRP and the risk of atrioventricular block, left bundle branch block and right bundle branch block, suggesting that lowering high levels of Hs-CRP is also essential for preventing the risk of heart block [19]. In addition, Lee et al. found that higher levels of Hs-CRP were strongly associated with a higher risk of all-cause mortality, cancer mortality, and CVD mortality in the general population after a 6.8-year follow-up of 41,070 men and 81,011 women [20]. For CVD, Kuppa et al. have confirmed the causal relationship between CRP and the risk of CVD in the Mendelian randomization study, but the causal relationship between Hs-CRP and the risk of CVD is still unknown [21]. Nevertheless, several observational studies have consistently shown a close correlation between Hs-CRP and CVD. For example, Dong et al. found in a large prospective cohort study that included 8,688 CVD-free middle-aged adults and a median follow-up time of 6.34 years that individuals in the third tertile of Hs-CRP had a 1.62-fold higher risk of CVD than those in the first tertile, but they did not confirm a correlation between changes in Hs-CRP during follow-up and the incidence of CVD [22]. In addition, although Koosha et al. confirmed the association of Hs-CRP with the prevalence of CVD in the total population in the Isfahan Cohort Study, the association of Hs-CRP with the prevalence of CVD in the diabetic population was not determined in multivariate logistic regression model adjusted only for age and sex [23]. Additionally, in a community-based cohort study that included 53,065 participants with three Hs-CRP measurements over a 6-year period, Wang et al. found that individuals with all three measurements of Hs-CRP ≥ 3 mg/L had a 38% increased risk of CVD compared with individuals with all three measurements of Hs-CRP < 3 mg/L, and that the risk of CVD increased by 4% for every 1 mg/L increase in baseline Hs-CRP and by 17% for every 1 mg/L increase in the mean of the three measurements of Hs-CRP [24]. For the diabetic population, several studies have also found that Hs-CRP has a certain predictive value for CVD among diabetes. For instance, Aryan and colleagues followed up with 1,301 diabetic patients and found that baseline Hs-CRP levels could predict both coronary heart disease and microvascular complications in diabetic patients [25]. Additionally, Hsieh and others have indicated that Hs-CRP may help in detecting asymptomatic myocardial ischemia in diabetic patients, thereby reducing future incidence and mortality rates of CVD [26]. Furthermore, Zhou and colleagues also discovered that Hs-CRP can accurately detect the characteristics of coronary artery narrowing and plaque in diabetic patients, having significant clinical value in the risk assessment of CVD [27]. However, these studies did not further explore the association between Hs-CRP and CVD prevalence among individuals with diabetes. Based on this research background, we assessed the association between multiple Hs-CRP metrics and CVD prevalence among individuals with diabetes in this community-based cohort study, and found that individuals in the third and fourth quartiles of Hs-CRP levels had a 50.5% and 71.1% increased prevalence of CVD, respectively, compared with individuals in the first quartile of Hs-CRP levels, and for each unit increase in log10 (Hs-CRP), a 50.4% increase in CVD prevalence. In addition, we also found that the CVD prevalence of Q4 patients under 60 years old, male, without hypertension and without hypercholesterolemia was 4.09, 1.96, 6.43 and 2.34 times higher than that of Q1 patients, respectively. In addition, our study showed that Hs-CRP levels vary significantly among different ethnic groups and sexes. Therefore, when forming the quartile groups for regression analysis, we adjusted for gender and ethnicity to account for these differences. This helps to ensure that our results are more accurate and representative. More importantly, we also confirmed a linear positive correlation between Hs-CRP and CVD prevalence in RCS analysis. Furthermore, in Model 1, we used Hs-CRP as a continuous variable, which allows us to capture the subtle variations in Hs-CRP levels and their association with the prevalence of CVD. Continuous variable analysis typically has higher statistical power because it utilizes the information from all data points. However, when we divided the Hs-CRP data into four groups for quartile analysis, although this method simplifies analysis and interpretation, it can also lead to information loss. For example, the variability of Hs-CRP levels within groups might be overlooked, reducing the ability to detect small but significant associations. Therefore, in Model 1, the quartiles were not associated with the presence of prevalent CVD. In the adjusted models, we controlled for other potential confounding variables such as age, sex, and ethnicity, which helps to eliminate their impact on the association between Hs-CRP and CVD. The adjusted models better reflect the true relationship between Hs-CRP and CVD, resulting in significant associations between Hs-CRP quartiles and the outcome in the adjusted models. To further verify this phenomenon, we conducted sensitivity analyses using both continuous variables and categorical variables (quartiles). The results showed that the adjusted models demonstrated a significant association between Hs-CRP and CVD regardless of the variable type. This supports our hypothesis that the association between Hs-CRP and CVD becomes more pronounced after adjusting for confounding variables. In summary, continuous variable analysis can utilize more information and has higher statistical power, while categorical variable analysis is easier to interpret but may lose some information. These steps help us ensure the stability of the regression models and the reliability of the results.

In addition, further discussion is still needed on the potential mechanisms underlying the association of Hs-CRP with CVD. At the clinical phenotype level, there is an inextricable correlation between Hs-CRP and hypertension, diabetes, chronic kidney disease, metabolic syndrome, and cardiac arrhythmias [28,29,30,31,32], and thus Hs-CRP may indirectly increase the risk of CVD through these diseases. At the molecular and cellular level, Hs-CRP as a major inflammatory marker may promote mechanisms such as inflammatory stress and oxidative stress, which in turn lead to thrombosis, vascular calcification and atherosclerosis, ultimately contributing to the development of CVD [33,34,35,36]. These potential mechanisms are now widely recognised, but more basic and clinical studies are needed to continue to uncover more mechanisms.

Although the study had meaningful results, there were still several limitations. First, NHANES is a national sample survey in the United States, but we did not take into account the adjustment of weights when analyzing the data, so the results of this study did not represent the real situation of the American population, but could only reflect the health and nutritional status of these participants. Second, due to the cross-sectional nature of this study, we could not determine the causal link between Hs-CRP and CVD prevalence. Besides, one limitation of this study was the lack of a sample size analysis. This was primarily due to the nature and data source of our study. This study was observational, aiming to explore the relationship between Hs-CRP levels and the prevalence of CVD in the diabetic population. Observational studies primarily analyze existing data rather than conducting interventions with predefined control groups, hence there is no necessity for a sample size analysis. And the data used in this study was sourced from NHANES, a national cross-sectional survey with a predetermined sample size and distribution. Therefore, we used the existing sample data for analysis rather than conducting a sample size analysis through additional data collection or intervention. Nevertheless, we adhered strictly to statistical principles during the data analysis process and provided detailed explanations and discussions of the subgroup analysis results to ensure the scientific validity and reliability of the study findings. Although we did not conduct a sample size analysis, this did not affect the main conclusions of our research. Third, this study did not include data from other countries and regions, so the promotion of the study results was limited. Fourth, we did not test the correlation between Hs-CRP and CVD prevalence in non-diabetic people, so it is unknown whether diabetes status affects major outcomes. Fifth, since the CVD in this study was defined by an arbitrary combination of several diseases, it is impossible to know whether Hs-CRP can predict a single CVD component. Sixth, CRP, which is also a marker of inflammation like Hs-CRP, has also been confirmed to be involved in the occurrence and development of atherosclerosis, but due to the lack of CRP indicators in these data, we have not been able to explore the correlation between CRP and the prevalence of CVD in people with diabetes. Seventh, another limitation of this study was the lack of data on the duration of diabetes. We could not assess the potential impact of disease duration on the association between Hs-CRP and CVD. Additionally, we did not have detailed data to analyze the differences in the association between Hs-CRP and CVD in screen-detected diabetes versus physician-diagnosed diabetes. Finally, this study lacked specific data on the use of major drug categories. Although certain drugs are known to reduce Hs-CRP levels, we did not have data on their use, making it impossible to assess the potential impact of these drugs on our research findings. This limitation may restrict our comprehensive understanding of the relationship between Hs-CRP levels and the prevalence of CVD.