1. Introduction

As the primary cause of death, cardiovascular disease (CVD) is one of the most significant public health issues[1]. Over the past few decades, the burden of CVD incidence and mortality has been rising[2]. One of the most common major modifiable CVD risk factors among US adults is hypertension[3,4], which affects roughly 1 in 3 Americans, or 65 million adults. As such, hypertension is a significant economic and public health burden.

Diabetes increases the risk of cardiovascular disease (CVD). A review of numerous studies found that individuals with diabetes had higher rates of coronary heart disease (CHD) [HR 2.00 (95% CI 1.83-2.19)], coronary death [HR 2.31 (95% CI 2.05-2.60)], and myocardial infarction (MI) [HR 1.82 (95% CI 1.64–2.03] than those without the condition [5]. The Centers for Disease Control and Prevention (CDC) estimates that 38.4 million Americans had diabetes in 2021 [6]. Researchers have documented disparities in the prevalence of both type 1 and type 2 diabetes among various racial and ethnic groups.

The association between diabetes, hypertension, and CVD will be the main focus of the study, and logistic regression and t tests will be used to determine this relationship. In order to identify the differences between the two groups, we will first list and compare a few participant characteristics between the CVD group and the non-CVD group using a t test. In addition, we will quickly look at the connection between the two main variables and CVD using a chi-square test. To further investigate the association between these variables, we will also use logistic regression, which incorporates both univariate and multivariate regression. Researchers will be able to investigate further using the above results, such as determining whether there is a bidirectional relationship between them.

It is well established that there is a connection between CVD and both diabetes and hypertension. Because these conditions have a significant negative influence on human health and require significant financial, material, and human resources, it makes sense to conduct this kind of research.

2. Methods

2.1. Source of data and study population

After taking into account the intricate survey design and sampling weights to be representative of the noninstitutionalized U.S. population, the research evaluated 11463 people in the US who were over 40 years old in terms of age, gender, race, smoking status, BMI, and the relationship between hypertension, diabetes, and cardiovascular disease from the National Health and Nutrition Examination Survey (NHANES, 2013–2014, 2015–2016, 2017–2018). NHANES gathers information on health, nutrition, socioeconomic status, and demographics in addition to standardizing lab tests and physical examinations. NHANES was authorized by the Institutional Review Board of the National Center for Health Statistics, and written informed permission was given by each participant. Those under 40 were not allowed to participate in the study. In the end, 9616 individuals were in the non-CVD group and 1847 participants were in the CVD group.

2.2. Variables and covariables

The subjects' self-reported interview data served as the basis for the diagnosis of diabetes, hypertension, and CVD. The study divided the participants into two groups: the CVD group comprised those who reported having heart failure (HF), coronary heart disease (CHD), angina pectoris (AP), heart attack (HA), and stroke, while the non-CVD group included those who did not. Age (40–59, 60–plus), gender, race (Mexican American, Other Hispanic, Non-Hispanic White, Non-Hispanic Black, Other Race), BMI (weight divided by square of height, <25, ≥25), and smoking status (Every day, Someday, Not at all) were the subgroups that the research examined the results in.

2.3. Statistical analyses

The demographic parameters of the CVD group and the non-CVD group were explained by component ratios (%). We present the participant characteristics according to their status for CVD, with a mean and a percentage in parenthesis. To find out if there were any statistically significant differences between the participants with and without CVD in terms of age, gender, race, BMI, smoking status, number of participants with hypertension, and number of participants with diabetes, the author employed a T test. In addition, the Chi-square test was employed to assess the distinctions in categorical attributes (such as the presence of diabetes or hypertension) between the CVD and non-CVD groups. Three logistic models were used to show the association between the two main factors (diabetes and hypertension) and cardiovascular disease and then estimate the odds ratio (OR) with a 95% confidence interval (CI).

All of the analyses were operated with RStudio version 4.3.2, with a 2-sided ɑ-level = 0.05.

3. Results

Table 1. Characteristics of Participants According to the Status of CVD

The characteristics of the individuals are presented in Table 1 based on their status with CVD. 11,463 participants in total were included by the author. In the CVD group, 1,847 participants were included (median age = 69, age 40~59 = 392 (21.2%), age≥60 = 1,453 (78.8%), men = 1,056 (57.2%), and women = 791 (42.8%)). In comparison, 9616 participants were included in the non-CVD group (median age = 58, age 40~59 = 5,177 (52.5%), age≥60 = 4,439 (47.5%), men = 4,464 (46.4%), and women = 5,152 (53.6%)). Table 1 demonstrates that there are significant differences in age (p<0.001), gender (p<0.001), race (p<0.001), BMI (p<0.001), smoking status (p<0.001), hypertension (p<0.001), and diabetes (p<0.001) between the CVD group and the non-CVD group.

Table 2. Chi-square table of Hypertension

Table 3. Chi-square table of Diabetes

Table 4. Chi-square test results

Table 4 displays the results of the Chi-square test, which indicate that there are significant differences between the CVD group and the non-CVD group in terms of hypertension (p<0.001, OR, 3.99, 95%CI, 3.56~4.48) and diabetes (p<0.001, OR, 2.94, 95%CI, 2.63~3.28).

Table 5. Univariate logistic regression analysis of two major factors and CVD

Table 6. Multivariate logistic regression analysis of two major factors and CVD

Table 5 and 6 used the grouping of CVD and non-CVD as the dependent variable (non-CVD group = 0, CVD group = 1), and used the two main factors (hypertension and diabetes) in the samples of the CVD and non-CVD groups as independent variables for multivariate logistic regression analysis. The overall univariate logistic regression and multivariate logistic regression results showed that Hypertension and Diabetes had an increased risk of Cardiovascular disease.

Univariate logistic regression (hypertension (p<0.001, OR, 3.99, 95%CI, 3.57~4.48), diabetes (p<0.001, OR, 2.94, 95%CI, 2.64~3.28)). Multivariate logistic regression (hypertension (p<0.001, OR, 3.45, 95%CI, 3.08~3.88), diabetes (p<0.001, OR, 2.24, 95%CI, 1.99~2.50)).

4. Discussion

According to NHANES data from 2013-2018 in the United States of America, participants with cardiovascular disease were more likely to be older, male, smokers, with a higher BMI, and with hypertension and diabetes. After adjusting confounders, hypertension and diabetes was associated with an extremely high risk of developing CVD, as the chi-square test and logistic regression showed. The findings indicate a strong correlation between the two major factors (hypertension and diabetes) and CVD, consistent with previous studies. The American Heart Association committee and stroke statistics subcommittee reported in 2006 and 2008 that age, gender, smoking, and having a higher BMI had certain relationships with CVD, including stroke and heart failure [3, 7]. Blood pressure and the risk of CVD events are continuously correlated, consistently elevated, and unaffected by other risk variables. The risk of heart failure, stroke, myocardial infarction, and kidney disease increases with blood pressure [4]. Furthermore, for people between the ages of 40 and 70, the risk of CVD doubles for every 10 mmHg increase in diastolic blood pressure or 20 mmHg increase in systolic blood pressure over the whole blood pressure range of 115/75 to 185/115 mmHg[8].

5. Conclusion

This study evaluated the two major factors, Hypertension and Diabetes in 11,463 participants recorded in the NHANES dataset [2013-2018]. The results revealed some characteristics of the participants with cardiovascular disease, revealing significant differences between the CVD group and the non-CVD group in age, gender, race, BMI, smoking status, and the presence of hypertension and diabetes. These findings suggest that these two major factors could potentially increase the risk of cardiovascular disease, with a clear association between them.

This study has certain strengthens in that the data we assessed covered several years, from 2013 to 2018; what’s more, as the relationship between hypertension, diabetes and CVD is what we focused on and the outbreak of coronavirus since 2020 means that some other complex relationship may appear as a result, the relationship we discovered is persuasive and consistent with the conclusion of the previous article. Moreover, while most research has concentrated on the correlation between a single factor and CVD, this study incorporates two significant factors.

Addressing the study's limitations is also necessary. First, the study only assessed the common cardiovascular disease subtypes, including coronary heart disease, heart failure, angina pectoris stroke, and heart attack, and did not consider other cardiovascular disease events. Second, the study only included cardiovascular disease from the NHANES surveys, potentially missing some diagnosed cases. Third, the study only examined the basic relationship between the two primary factors, hypertension and diabetes, and cardiovascular disease. To address the need for modern medications, further studies should explore the association between cardiovascular disease and certain cancers.

Overall, these results support the need for clinical, public health, and policy actions aimed at enhancing cardiovascular health in the US. It would be beneficial to investigate cardiovascular illness in more detail.