Abstract
Purpose
To examine the association between pre-existing cardiovascular disorders and the risk of coronavirus disease 2019 (COVID-19) among community-dwelling adults in the United States.
Methods
We analyzed data from the 2021 National Health Interview Survey, encompassing 28,848 nationally representative participants aged ≥18. We examined the association by two age groups, younger adults (aged 18-59) and older adults (aged ≥60). Weighted analyses were conducted to consider the complex sampling design used in the National Health Interview Survey.
Results
The results show that 13.9% of younger and 8.2% of older adults were infected with coronavirus, corresponding to a nationwide estimate of 23,701,358 COVID-19 cases in younger adults and 6310,206 in older adults in 2021. Pre-existing cardiovascular risk factors (overweight, obesity, hypertension, and diabetes) in both age groups and pre-existing cardiovascular diseases (angina, heart attack, and coronary heart disease) in older adults were significantly associated with COVID-19 infection. Significant dose-response relationships existed between increased pre-existing cardiovascular risk factors and COVID-19 infection, with the strongest association in non-Hispanic Black, followed by Hispanic ethnicities and non-Hispanic White.
Conclusions
Pre-existing cardiovascular disorders are significantly associated with the risk of COVID-19 infection. The magnitudes of this risk association are more substantial among minority populations.
Keywords: Cardiovascular disorders, COVID-19, Health disparity
Introduction
Coronavirus disease 2019 (COVID-19) is a worldwide pandemic caused by severe acute respiratory syndrome coronavirus 2. It has posted severe public health concerns. Cardiovascular risk factors may predispose individuals to develop COVID-19. Early studies suggested that hypertension and cardiometabolic disorders (a clustering of risk factors for cardiovascular disease and diabetes) were associated with higher susceptibility to COVID-19, more severe outcomes, and increased COVID-19-related deaths [1]. These studies were predominantly conducted among hospitalized patients [2], [3], [4], [5]. However, the association between pre-existing cardiovascular disorders and the risk of COVID-19 among community-dwelling (i.e., noninstitutionalized) populations remains understudied. Given the spread and impact of COVID-19 on public health, it is important to understand how was the impact of the COVID-19 pandemic on the total population. In this study, we aimed to build upon reports conducted on hospitalized patients by examining the epidemiology of COVID-19 and its association with pre-existing cardiovascular disorders among community-dwelling populations using data from the 2021 National Health Interview Survey (NHIS).
Methods
Study design and data source
The NHIS is a nationally representative survey that has been conducted since 1957 to monitor the nation's health. The NHIS, using a cross-sectional study design, is typically conducted annually in person at the participants’ homes. At the time of the interview, the NHIS targets the civilian noninstitutionalized population residing within the United States, compromising 50 states and the District of Columbia [6], [7]. From March 2020, the COVID-19 pandemic disrupted the survey through the household interview approach. However, in response to the in-person contact challenge of the pandemic, the NHIS developed online data collection platforms via telephone interviews from April to June 2020 [8], [9]. In July 2020, although telephone surveying remained the primary data collection method, the NHIS households survey resumed in selected areas progressing to all areas from September 2020. Safety protocols for in-person interviewing included wearing masks, social distancing, outdoor interviews, not entering respondents’ homes, and not allowing respondents to touch Census Bureau equipment or materials [10].
In this study, we analyzed the 2021 NHIS data, which included measures of the COVID-19 status from January to December 2021 [11]. Of 29,289 participants aged ≥18 who were asked whether or not they had been told by a doctor or other health professional that they had or likely had coronavirus or COVID-19, we excluded 441 who had false-positive COVID-19 laboratory test (n = 284), those who had not yet received the results of their COVID-19 Lab tests when participating in the survey (n = 10), and those who had missing data of the Lab tests (n = 147). Therefore, the final sample size used in this study was 28,848 (98%). Figure 1 shows the sample size flow chart. Our study was a secondary data analysis project using NHIS data which is publicly available with de-identified data for researchers. Therefore Institutional Review Board approval was not required [7], [12], [13].
Fig. 1.
Sample size flow chart.
Outcome
Participants with COVID-19 are defined as those with self-reported COVID-19 infection based on the diagnosis from doctors or health professionals and/or with Lab testing-confirmed history of COVID-19 infection [10], [11].
Exposures
We examined two groups of cardiovascular disorders [14]: (1) cardiovascular risk factors and (2) cardiovascular diseases (CVD). Cardiovascular risk factors include overweight, obesity, smoking, hyperlipidemia, hypertension, and diabetes. Overweight and obesity are assessed by body mass index (BMI), calculated from the participant's weight (kg) divided by height (m2). Subjects with BMI ≥ 25 kg/m2 are classified as overweight, and those with BMI ≥ 30 kg/m2 as obese. On cigarette smoking status, participants were asked three questions: (1) “do you smoke now?”, (2) “do you smoke every day, some days, or not at all?", and (3) "have you ever smoked 100 cigarettes in your lifetime?" A participant was classified as a current smoker if they reported smoking now, daily, or some days smoking during the survey. Those who currently did not smoke but had ever smoked 100 cigarettes were classified as former smokers. The rest of the participants were classified as never-smokers [15]. Hypercholesterolemia, hypertension, and diabetes were classified if a participant had a positive answer to "have you ever been told by a doctor or health professional that you had high cholesterol, hypertension, or diabetes?" Participants with CVD (angina, heart attack, coronary heart disease [CHD], or stroke) are classified if they had a positive answer to the question, "have you ever been told by a doctor or health professional that you had angina, heart attack, CHD, or stroke?" Total CVD includes any of the abovementioned four CVD conditions. It should be noted that this survey approach to defining a history of the chronic condition using participants' self-reports of a physician or health professional diagnosed disease has been confirmed as a valid measure [16], [17], and has been applied in the majority of national health surveys, coordinated by the National Center for Health Statistics of the Center for Disease Control and Prevention [6], [7], [18], [19].
Covariates
To control the potential confounding effects attributable to age and other covariates, we conducted stratification analysis by two age groups (younger adults aged 18–59 and older adults aged ≥ 60 years old) and adjusted for sex (male and female), race/ethnicity (non-Hispanic [NH] White, NH Black/African American, Hispanic, and the other race/ethnicity group), educational attainment, and family income index. Educational attainment is classified into four groups: (a) those with< high school (<12th grade or a general educational development program), (b) those with high school graduate, (c) those with an associate degree (some college, associate degree, occupational, technical, or vocational program), and (d) those with ≥ college (Bachelor’s or Master’s degree, or doctoral degree). The family income index is the ratio of the family’s income to the federal poverty threshold. It ranges from 0.00 to 10.99, toward a better family income [20].
Statistical analyses
Given the study design of the NHIS, we applied cross-sectional analysis approaches in the study. In the first group analysis, we examined the characteristics of participants by COVID-19 status. We estimated the number of observed COVID-19 cases, the weighted number of cases, and rates using weighted sampling analysis techniques for data from a complex sampling survey [11], [21]. Chi-square was used to test differences in the weighted rates. In the second group analysis, we estimated COVID-19 rates by CVD risk factors and CVD conditions by younger and older age groups. In the third group analysis, we used logistic regression models to estimate adjusted odds ratios (ORs) of CVD disorders for COVID-19 by younger and older adult groups. Model 1 adjusted for sex, race/ethnicity, region (Northeast, Midwest, South, and West), and sampling survey period (quarters 1–4). Model 2 adjusted for the covariates in model 1 plus socioeconomic status (educational attainment and family income index). In the last group analysis, we examined whether there was a significant dose-response association between an increased number of pre-existing CVD risk factors and the risk of COVID-19. We further estimated the interaction effects of race/ethnicity on the association between CVD risk factors and COVID-19.
All statistical analyses were performed using Statistical Analysis System (SAS) software 9.4 version (SAS Institute, Cary, NC). As NHIS applied a complex sampling design with multistage and probability sampling design, we applied SAS Survey Procedures (i.e., Proc Surveymeans, Proc Surveyfreq, and Proc Surveylogistic) to estimate sampling weighted rates and ORs of cardiovascular disorders for the risk of COVID-19 [21]. A 2-sided P value < .05 was considered statistically significant in all data analyses.
Results
Characteristics of the participants
Table 1 shows that 3053 cases were observed in the participants with classified COVID-19, corresponding to an estimated total of 30,011,564 COVID-19 cases. The weighted rate of COVID-19 was 13.9% in the younger and 8.2% in the older adults. Subjects who lived in the South had the highest COVID-19 rate (13.4%), followed by Midwest (12.6%), West (10.9%), and Northeast (10.4%). Females, Hispanics, and those with lower educational levels and with lower family income had significantly higher COVID-19 rates than their corresponding counterparts (P < .05).
Table 1.
Characteristics of participants in 2021 NHIS
| Weighted analysis* |
||||||
|---|---|---|---|---|---|---|
| COVID-19 case† | Weighted case | Weighted population | Weighted rate, % | P-value | ||
| Age, years | <.001 | |||||
| 18–59 | 2223 | 23,701,358 | 170,619,216 | 13.9 | ||
| ≥60 | 830 | 6,310,206 | 76,899,969 | 8.2 | ||
| Total | 3053 | 30,011,564 | 247,519,184 | 12.1 | ||
| Sex | .037 | |||||
| Male | 1346 | 13,850,815 | 119,496,597 | 11.6 | ||
| Female | 1707 | 16,160,748 | 128,022,587 | 12.6 | ||
| Race/ethnicity | <.001 | |||||
| NH White | 1865 | 17,172,650 | 155,177,834 | 11.1 | ||
| NH Black | 329 | 3,465,093 | 29,037,916 | 11.9 | ||
| Hispanic | 671 | 7,650,891 | 41,924,419 | 18.2 | ||
| Others | 188 | 1,722,930 | 21,379,015 | 8.1 | ||
| Region | <.001 | |||||
| Northeast | 423 | 4,509,106 | 43,167,289 | 10.4 | ||
| Midwest | 694 | 6,506,567 | 51,448,957 | 12.6 | ||
| South | 1244 | 12,573,545 | 94,122,703 | 13.4 | ||
| West | 692 | 6,422,345 | 58,780,234 | 10.9 | ||
| Education | <.001 | |||||
| < High school | 353 | 3,872,887 | 29,144,848 | 13.3 | ||
| High school | 784 | 8,925,384 | 64,061,523 | 13.9 | ||
| Associate degree | 895 | 8,342,696 | 65,085,295 | 12.8 | ||
| ≥ College | 1004 | 8,686,992 | 87,697,871 | 9.9 | ||
| Family income index | .01 | |||||
| 0–0.99 | 321 | 3,388,201 | 24,397,575 | 13.9 | ||
| 1–1.74 | 428 | 4,304,414 | 31,475,797 | 13.7 | ||
| 1.75–2.99 | 648 | 6,519,993 | 52,692,151 | 12.4 | ||
| ≥3.00 | 1656 | 15,798,956 | 138,953,661 | 11.4 | ||
COVID-19 = coronavirus disease 2019; NH = non-Hispanic; NHIS = National Health Interview Survey.
Weighted population: population at risk. The family income index is the ratio of family income to the poverty threshold. A 2-sided P value < .05 was considered statistically significant.
NHIS used a complex sampling design, so weighted analyses are conducted.
Observed COVID-19 case.
Table 2 shows that among the younger adults, subjects with overweight (BMI 25–29 kg/m2), obesity (BMI ≥ 30 kg/m2), and history of hypertension or diabetes had significantly higher COVID-19 rates than their corresponding counterparts. Among older adults, subjects with CVD risk factors of overweight, obesity, and diabetes, and those with angina, heart attack, CHD, or total CVD had significantly higher COVID-19 rates than those without these conditions.
Table 2.
Rate of COVID-19 by cardiovascular risk factors and disease, and by age in 2021 NHIS
| Age 18–59 |
Age ≥ 60 |
||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| COVID-19 case | Weighted case | Weighted population | Weighted rate, % | P-value | COVID-19 case | Weighted case | Weighted population | Weighted rate, % | P-value | ||
| Body mass index, kg/m2 | <.001 | <.001 | |||||||||
| < 18.5 | 26 | 363,346 | 3,000,486 | 12.1 | 8 | 56,621 | 1,278,336 | 4.4 | |||
| 18.5–24.9 | 581 | 6,228,358 | 53,667,631 | 11.6 | 200 | 1,438,342 | 22,343,781 | 6.4 | |||
| 25–29.9 | 727 | 7,696,971 | 54,011,989 | 14.3 | 320 | 2,470,555 | 28,282,547 | 8.7 | |||
| ≥ 30 | 844 | 8,937,954 | 56,275,473 | 15.9 | 284 | 2,221,332 | 23,016,566 | 9.7 | |||
| Ever smoking | .075 | .095 | |||||||||
| No | 1035 | 11,598,608 | 84,460,432 | 13.7 | 390 | 3,040,800 | 34,664,825 | 8.8 | |||
| Yes | 1124 | 11,384,452 | 81,887,547 | 13.9 | 422 | 3,114,678 | 40,376,045 | 7.7 | |||
| Hyperlipidemia | .129 | .337 | |||||||||
| No | 1789 | 19,359,755 | 141,742,744 | 13.7 | 387 | 3,030,436 | 38,244,233 | 7.9 | |||
| Yes | 429 | 4,296,416 | 28,599,853 | 15.0 | 441 | 3,271,620 | 38,370,442 | 8.5 | |||
| Hypertension | .001 | .078 | |||||||||
| No | 1674 | 18,324,524 | 136,811,668 | 13.4 | 319 | 2,445,547 | 32,312,564 | 7.6 | |||
| Yes | 546 | 5,349,212 | 33,624,923 | 15.9 | 511 | 3,864,659 | 44,449,405 | 8.7 | |||
| Diabetes mellitus | .017 | .012 | |||||||||
| No | 2033 | 21,785,239 | 159,162,365 | 13.7 | 628 | 4,677,121 | 60,452,610 | 7.7 | |||
| Yes | 182 | 1,864,889 | 11,062,048 | 16.9 | 201 | 1,626,972 | 16,277,396 | 10.0 | |||
| Angina | .403 | .012 | |||||||||
| No | 2197 | 23,439,339 | 169,067,400 | 13.9 | 790 | 5,979,101 | 74,173,699 | 8.1 | |||
| Yes | 23 | 222,072 | 1,292,606 | 17.2 | 40 | 331,105 | 2,434,601 | 13.6 | |||
| Heart attack | .378 | .012 | |||||||||
| No | 2200 | 23,454,311 | 168,428,775 | 13.9 | 752 | 5,676,911 | 71,378,281 | 8.0 | |||
| Yes | 23 | 247,046 | 2,128,214 | 11.6 | 77 | 630,861 | 5,422,322 | 11.6 | |||
| CHD | .814 | .002 | |||||||||
| No | 2165 | 23,103,575 | 166,113,281 | 13.9 | 669 | 5,042,017 | 64,948,476 | 7.8 | |||
| Yes | 58 | 597,782 | 4,452,179 | 13.4 | 161 | 1,268,189 | 11,900,827 | 10.7 | |||
| Stroke | .775 | .391 | |||||||||
| No | 2200 | 2,346,0452 | 168,691,389 | 13.9 | 768 | 5,829,264 | 71,621,390 | 8.1 | |||
| Yes | 23 | 240,905 | 1,854,022 | 13.0 | 62 | 480,942 | 5,137,372 | 9.4 | |||
| CVD | .765 | .004 | |||||||||
| No | 2145 | 22,899,402 | 164,640,725 | 13.9 | 636 | 4,761,625 | 61,529,755 | 7.7 | |||
| Yes | 76 | 770,838 | 576,1504 | 13.4 | 194 | 1,548,581 | 15,178,611 | 10.2 | |||
COVID-19 = coronavirus disease 2019; NHIS = National Health Interview Survey.
Missing data are excluded. NHIS used a complex sampling design, so weighted analyses are conducted. Weighted population: Population at risk. Weighted rates (%) are estimated using a complex sampling survey study method. CHD: Coronary heart disease includes angina, heart attack, and chronic ischemic heart disease. CVD: Cardiovascular disease includes CHD and stroke. A 2-sided P value < .05 was considered statistically significant.
Table 3 shows that after adjustment for sex, race/ethnicity, survey time (in quarters), and regions (model 1), the ORs (95%CI) of overweight, obesity, hypertension, and diabetes were significantly associated with COVID-19 in both age groups, and a significant association between hyperlipidemia and COVID-19 among the younger adults. These associations remained significant after further adjustment for education and family income index (model 2), except for the association between hypertension and COVID-19 in older adults (P = .059). Of CVD conditions, there were significant associations of pre-existing angina, heart attack, CHD, and total CVD with the risk of COVID-19 in older adults (P < .01, models 1 and 2). However, these associations were not significant in younger adults (models 1 and 2).
Table 3.
Adjusted odds ratios (95%CI) of exposures for risk of COVID-19
| Model 1 |
Model 2 |
||||||||
|---|---|---|---|---|---|---|---|---|---|
| OR | (95%CI) | P-value | OR | (95%CI) | P-value | ||||
| Adults aged 18–59 | |||||||||
| CVD risk factors (yes vs. no) | |||||||||
| Underweight | 0.98 | (0.62–1.54) | .93 | 0.95 | (0.61–1.50) | .84 | |||
| Overweight | 1.35 | (1.16–1.56) | <.001 | 1.32 | (1.14–1.53) | <.001 | |||
| Obesity | 1.51 | (1.33–1.72) | <.001 | 1.45 | (1.27–1.65) | <.001 | |||
| Ever smoked | 1.07 | (0.96–1.19) | .22 | 1.05 | (0.94–1.17) | .40 | |||
| Hyperlipidemia | 1.22 | (1.05–1.41) | .01 | 1.21 | (1.04–1.40) | .013 | |||
| Hypertension | 1.34 | (1.18–1.51) | <.001 | 1.29 | (1.14–1.47) | <.001 | |||
| Diabetes | 1.38 | (1.14–1.67) | .001 | 1.30 | (1.07–1.57) | .008 | |||
| CVD (yes vs. no) | |||||||||
| Angina pectoris | 1.39 | (0.80–2.43) | .24 | 1.25 | (0.71–2.22) | .44 | |||
| Heart attack | 0.88 | (0.53–1.47) | .63 | 0.81 | (0.49–1.34) | .41 | |||
| CHD | 1.05 | (0.74–1.49) | .80 | 0.96 | (0.68–1.35) | .82 | |||
| Stroke | 0.99 | (0.56–1.74) | .97 | 0.86 | (0.48–1.55) | .62 | |||
| Total CVD | 1.04 | (0.76–1.42) | .80 | 0.96 | (0.71–1.29) | .77 | |||
| Adults aged ≥ 60 | |||||||||
| CVD risk factors (yes vs. no) | |||||||||
| Underweight | 0.69 | (0.31–1.56) | .37 | 0.67 | (0.30–1.52) | .34 | |||
| Overweight | 1.41 | (1.12–1.77) | .003 | 1.37 | (1.10–1.72) | .01 | |||
| Obesity | 1.53 | (1.21–1.92) | <.001 | 1.45 | (1.15–1.82) | .002 | |||
| Ever smoked | 0.89 | (0.74–1.05) | .17 | 0.85 | (0.72–1.02) | .08 | |||
| Hyperlipidemia | 1.11 | (0.94–1.30) | .24 | 1.11 | (0.94–1.31) | .22 | |||
| Hypertension | 1.21 | (1.02–1.44) | .028 | 1.18 | (0.99–1.40) | .059 | |||
| Diabetes | 1.30 | (1.06–1.59) | .012 | 1.26 | (1.03–1.55) | .02 | |||
| CVD (yes vs. no) | |||||||||
| Angina pectoris | 1.92 | (1.32–2.78) | .001 | 1.95 | (1.34–2.84) | .001 | |||
| Heart attack | 1.67 | (1.25–2.23) | .001 | 1.62 | (1.21–2.17) | .001 | |||
| CHD | 1.59 | (1.29–1.97) | <.001 | 1.60 | (1.29–1.98) | <.001 | |||
| Stroke | 1.22 | (0.87–1.71) | .243 | 1.23 | (0.88–1.73) | .23 | |||
| Total CVD | 1.51 | (1.23–1.84) | <.001 | 1.52 | (1.24–1.85) | <.001 | |||
COVID-19 = coronavirus disease 2019; NIHS = National Health Interview Survey; OR = odds ratio.
CHD: Coronary heart disease includes angina, heart attack, and chronic ischemic heart disease. CVD: Cardiovascular disease includes angina, heart attack, CHD, and stroke. Odd ratios are estimated using the SAS Surveylogistic procedure for taking account of the complex sampling survey design used in the NIHS. Model 1: adjusted for age, sex, race/ethnicity, survey quarter, and regions. Model 2 adjusted for covariates in Model 1 plus education, and family income index. A 2-sided P value < .05 was considered statistically significant.
Fig. 2 depicts that as the number of CVD risk factors increased, the risk of COVID-19 increased (test for trend: P < .001), with a stronger association (assessed by the values of ORs) among NH Black and Hispanics than NH White. No significant interaction effects of race/ethnicity on the association between CVD risk factors and the risk of COVID-19 were observed.
Fig. 2.
Adjusted OR (95%CI) of no. of CVD risk factors for COVID-19. *No. of risk factors includes ever smoked, overweight or obesity, hyperlipidemia, hypertension, and diabetes mellitus. OR = odds ratio; COVID = coronavirus disease 2019; CVD = cardiovascular diseases.
Discussion
In this study, using a nationally representative dataset, we are the first study to examine the association between pre-existing cardiovascular disorders and the risk of COVID-19 infection among community-dwelling participants. The main results show that younger adults had a significantly higher COVID-19 rate than older adults. Pre-existing CVD risk factors were significantly associated with COVID-19 in younger and older adults. Angina, heart attack, CHD, and total CVD were significantly associated with COVID-19 in older adults. As the number of CVD risk factors increased, so did the risk of COVID-19, with the strongest risk association in NH Black and Hispanic than NH White. The results of this study add new evidence of the related studies to the body of literature among community-dwelling populations. The findings of this study may serve as an important reference for further post-COVID conditions (Long COVID) and outcomes studies.
The COVID-19 pandemic started in early 2020, and risk studies for COVID-19 were predominately conducted among hospitalized patients. This is most likely attributable to the fact that there were more severe cases that require hospitalization treatment and intervention and a relatively small proportion of COVID-19 with mild symptoms in community settings in the early pandemic of COVID-19 infection. Our results reporting on age differences in COVID-19 rates between younger and older adults are consistent with studies from the National Centers for Disease Control and Prevention and others [22], [23]. Although it is known that older adults with COVID-19 have a significantly higher risk of mortality than younger adults with COVID-19, it shows that older adults are not necessarily more likely to get coronavirus infection. A couple of possible reasons could be linked to these results. First, the participation rate in testing for COVID-19 shifted the profile of COVID-19 patients. At the beginning of the outbreak (March–April 2020), when tests were in short supply, only the most severely affected COVID-19 patients were tested. Since May 2020, with the increased accessibility and availability of COVID-19 tests, public-health networks have captured more mild and asymptomatic cases, including those in the younger age group [22]. Second, the NHIS included noninstitutionalized participants only and did not include hospitalization patients, those living in nursing homes, those in military service, or prisoners [8]. It is known that older adults have a higher rate of CVD and a higher proportion of hospitalization than younger adults. Therefore, data from community-based surveys will likely include more healthy older adults. Third, younger adults may be more likely to have exposure to COVID-19 because of their relatively more active social life and outdoor activities than older adults [23]. Similarly to other studies [24], [25], [26], our study shows that Hispanics had the highest COVID-19 rate, followed by NH Black and NH White. One of the explanations could be that Hispanics and NH Black have a significantly higher prevalence of CVD risk factors than NH Whites [24], [25], [26]. For example, our study indicates that Hispanic (37%) and NH Black (44%) had significantly higher obesity rates than NH White (32%). NH Black had the highest diabetes rate (14%), followed by Hispanic (11%) and NH White (10%). These disproportionate distributions of cardiovascular risk factors by race/ethnicity call for further assessments as these factors are associated with the risk of COVID-19.
There were significant associations between pre-existing CVD and COVID-19 in older adults, but this association was insignificant in younger adults. To consider whether social-economic status (SES) confounds this association, we further adjusted for educational attainment and family income index (two markers of SES) in model 2. The results show that the associations between pre-existing CVD and risk of COVID-19 became slightly weaker among younger adults in model 2 versus model 1 (assessed by the values of ORs), but these associations of pre-existing CVD (angina, CHD, stroke, and total CVD) with risk of COVID-19 became slightly stronger in older adults. These different effects of SES by age are likely linked to an increased occurrence and prevalence of CVD in older adults compared to younger adults. Meanwhile, reverse causation may occur in a cross-sectional study (e.g., NIHS). For example, patients after being diagnosed with CVD may change their behavior risk factors (e.g., from smokers to quit smoking). This change may result in a stronger association between CVD and COVID-19 than that between cardiovascular risk factors and COVID-19. Further studies are needed to examine the effects of multivariate factors on the risk of COVID-19 using data from a longitudinal cohort study. Nevertheless, the overall results of these associations between pre-existing CVD and risk of COVID-19 were consistently significant among older adults in models 1 and 2. These results by age difference emphasize the priority for prevention strategies in CVD and COVID-19 control. Our studies further identified a dose-response relationship between increased cardiovascular risk factors and the risk of COVID-19. This dose-response effect may represent a cumulative effect of multiple risk factors on the occurrence and severity of COVID-19 [27]. Further prospective cohort studies are needed to determine potential causal associations.
The mechanisms by which pre-existing CVD disorders impact the risk of COVID-19 are not fully understood. Inflammation, multiorgan dysfunction, vascular injury, and metabolic and endothelial disarray may play a role in the risk of COVID-19 [3], [27]. For example, studies have shown that excess adiposity and cardiometabolic disorders may increase the risk of COVID-19 and the severity of the disease outcomes by increased risks of inflammation, immune dysfunction, hypercoagulation, and mechanical obstruction [3], [4], [28], [29], [30]. In this study, we observed that individuals ≥ 2 pre-existing CVD risk factors in NH Black had the highest probability of COVID-19 infection, followed by Hispanic and NH White. These race/ethnicity variations in the risk of COVID-19 may be associated with the severity of CVD risks. For instance, NH Black had a much higher prevalence of diabetes and hypertension than NH White. These health disparities by race/ethnicity groups need further investigation.
In conclusion, this study contributes in many aspects to our understanding of pre-existing conditions and COVID-19 infections. First, it provides a U.S. national estimate of the COVID-19 burden among community-dwelling populations in 2021. Results from this study could serve as an important reference for a future post (long) COVID conditions investigations. Second, the significant association between CVD risk factors and the risk of COVID-19 highlights a potential risk reduction of COVID-19 by managing CVD risk factors. Third, the dose-response association between accruing CVD risk factors and increased risk of COVID-19 supports the importance of identifying individuals with a high risk of COVID-19 among the study populations. It also should be noted that this study has several limitations when extrapolating the results. First, this study included noninstitutionalized participants. The findings of this study cannot be interpreted by institutionalized participants, such as those in hospital care, nursing homes, military service, and/or in prisons. It is because community-dwelling and institutionalized populations are hugely different populations. For example, in general, adults are healthier among community-dwelling residents than those who are hospitalized due to their disease status. Therefore, studies among noninstitutionalized and institutionalized populations should be conducted separately. Second, NHIS is conducted using a cross-sectional study design. Therefore, results cannot be extended to interpret a causal association between CVD disorders and COVID-19. Third, in an observational study, unmeasured confounders may influence the observed associations. For instance, air pollution and neighborhoods with poor health conditions (e.g., difficulty accessing healthcare centers, healthy supermarkets, etc.) may contribute to the spread of COVID-19 at community and population levels. Studies have shown that residents living in disadvantaged neighborhoods had a higher risk of cardiovascular disease and diabetes [31], [32], with impaired control of coronavirus infection [33]. However, these factors were not included in the multivariate adjustment analysis, because they were not available in the NHIS dataset. Despite these limitations, using a nationally representative population sample, the findings of this study add new evidence to the body of literature on the epidemiology of COVID-19 by demographic factors and CVD disorders. A significant association between pre-existing CVD disorders and the risk of COVID-19 among community-dwelling populations was identified. The findings of this study provide the basis for future investigations into the post (long) COVID conditions among community-dwelling populations.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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