Abstract
Background
Data are limited on the association between marital status and subclinical coronary atherosclerosis. This study investigated the influence of marital status on subclinical coronary atherosclerosis detected by coronary computed tomographic angiography in an asymptomatic population.
Methods and Results
This retrospective study analyzed 9288 asymptomatic individuals (mean age, 53.7±8.0 years; 6041 [65%] men) with no history of coronary artery disease who voluntarily underwent coronary computed tomographic angiography during a general health examination. Marital categories were married (n=8481) versus unmarried (n=807), comprising never married (n=195), divorced (n=183), separated (n=119), and widowed (n=310) individuals. The degree and extent of subclinical coronary atherosclerosis were evaluated by coronary computed tomographic angiography; ≥50% diameter stenosis was defined as significant. Logistic regression and propensity score matching analyses were used to determine the association between marital status and subclinical coronary atherosclerosis. After adjustment for cardiovascular risk factors, no significant differences were observed in the adjusted odds ratio (OR) of unmarried status for any coronary plaque (OR, 1.077; 95% CI, 0.899–1.291), calcified plaque (OR, 1.058; 95% CI, 0.881–1.271), noncalcified plaque (OR, 0.966; 95% CI, 0.691–1.351), mixed plaque (OR, 1.301; 95% CI, 0.884–1.917), and significant coronary artery stenosis (OR, 1.066; 95% CI, 0.771–1.474). Similarly, in the 2:1 propensity‐score matched population (n=2398), no statistically significant differences were observed for the OR of marital status for any subclinical coronary atherosclerosis (P>0.05 for all).
Conclusions
In this large cross‐sectional study, marital status was not associated with an increased risk of subclinical coronary atherosclerosis.
Keywords: atherosclerosis, divorced, heart disease risk factors, marital status, never married, separated, widowed
Subject Categories: Risk Factors, Computerized Tomography (CT), Coronary Artery Disease
Clinical Perspective
What Is New?
Marital status is not associated with subclinical coronary atherosclerosis on coronary computed tomographic angiography.
In addition, each unmarried status (never married, divorced, separated, and widowed) did not have any association with subclinical coronary atherosclerosis.
What Are the Clinical Implications?
Both married and unmarried individuals may be managed with similar prevention strategies for coronary artery disease.
Coronary artery disease (CAD) remains the global leading cause of death. 1 Epidemiologic studies have identified risk factors for CAD, including age, sex, diabetes, hypertension, hyperlipidemia, obesity, current smoking, family history of CAD, and CRP (C‐reactive protein). 2 , 3 , 4 The standard of care for patients with CAD was established on the basis of these traditional risk factors. 5 , 6 Furthermore, the evolving role of nontraditional risk factors, such as socioeconomic and psychosocial factors, has been increasingly recognized. 7 , 8 Previous studies have acknowledged an association between marital status and not only incidence of CAD but also CAD‐related clinical outcomes. 8 , 9 , 10 , 11 However, to date, no studies have focused on the association between marital status and subclinical coronary atherosclerosis in asymptomatic individuals. It is still unclear whether specific marital status, defined as married, never married, divorced, separated, or widowed, is a risk factor for CAD. With the advent of multidetector computed tomography, coronary computed tomographic angiography (CCTA) can provide comprehensive assessment of CAD, including lesion location, disease severity, and plaque characteristics. 12 Therefore, this study sought to (1) evaluate the association between marital status and subclinical coronary atherosclerosis and (2) specifically examine the impact of marital status for each unmarried group (never married, divorced, separated, or widowed) on subclinical coronary atherosclerosis in a large cohort of asymptomatic Korean individuals who voluntarily underwent CCTA for early detection of CAD.
Methods
The data that support the findings of this study are available from the corresponding authors on reasonable request.
Study Population
As a compulsory social insurance, South Korea has a National Health Insurance system that covers the whole population living in the country. The National Health Insurance has actively operated the business of promoting health checkups and health level in an effort to detect diseases early and enhance public health. These general health screenings have been performed to the employee insured with no age limit (annually) and the self‐employed insured, such as householders or dependents aged >40 years (biannually). These general checkups are free and covered by the National Health Insurance. In addition, if individuals undergoing general medical checkups paid additional costs, they could take additional tests, such as CCTA. In the present study, we analyzed 10 581 consecutive South Korean individuals, aged ≥20 years, who underwent self‐referred CCTA as part of a general health examination at the Health Promotion Center of Ulsan University Hospital from January 2009 to March 2020. At the time of medical checkups, the potential risk of radiation hazards, use of contrast, and higher cost for CCTA were explained to all study participants. A written informed consent for the additional CCTA test was also obtained from each participant. Of the 10 581 enrolled, 1293 individuals were excluded on the basis of these criteria: (1) insufficient medical records (n=581); (2) history of angina or myocardial infarction and/or percutaneous coronary intervention (n=340); (3) no response for marital status (n=171); (4) abnormal 12‐lead ECG results, including pathological Q waves, ischemic ST segments or T‐wave changes, left bundle‐branch blocks, or complete atrioventricular block (n=90); (5) renal insufficiency (creatinine >1.5 mg/dL) (n=47); (6) structural heart diseases (n=41); (7) history of open heart surgery (n=18); (8) history of radiofrequency catheter ablation (n=3); (9) history of patent foramen ovale device closure (n=1); and (10) poor image quality (n=1). Final analysis included 9288 participants (Figure). This retrospective cross‐sectional study was approved by the local Institutional Review Board of the Ulsan University Hospital, Ulsan, Korea, which waived the requirement for informed consent because of the retrospective study design (IRB No. UUH 2020‐12‐033).
Figure 1. Overview of the study population.
CCTA indicates coronary computed tomographic angiography; MI, myocardial infarction; and PCI, percutaneous coronary intervention.
Clinical and Laboratory Measurements
Clinical and laboratory data were collected from a clinical data warehouse platform and electronic medical records of Ulsan University Hospital. Any clinical data, including age, sex, and any medical history, were obtained from the systemized self‐report questionnaire administered before the general health examination, including the following factors: angina, myocardial infarction, percutaneous coronary intervention, structural heart disease, open heart surgery, previous cardiac procedures, marital status, diabetes, hypertension, hyperlipidemia, smoking status, and family medical history. Participants listed their marital status as married, never married, divorced, separated, or widowed.
Height and weight were obtained with participants wearing light clothing and no shoes. Body mass index was calculated as the weight in kilograms divided by the square of the height in meters (kg/m2). The waist circumference (cm) was measured midway between the lower costal margin and the iliac crest at the end of a normal expiration by a well‐trained nurse. Blood pressure was measured on the right arm after a ≥5‐minute rest using an automatic manometer and an appropriate cuff size. A standard 12‐lead ECG was obtained from each subject.
After overnight fasting, early morning blood samples were drawn from the antecubital vein into vacuum tubes and subsequently analyzed at the certified central laboratory of Ulsan University Hospital. The concentrations of glucose, hemoglobin A1c, total cholesterol, low‐density lipoprotein cholesterol, high‐density lipoprotein cholesterol, triglycerides, creatinine, uric acid, and CRP were measured. Left ventricular ejection fraction was measured using echocardiography.
Obesity was defined as a body mass index ≥25 kg/m2, according to the Asian‐specific cutoff recommended by the World Health Organization. Diabetes was defined as a self‐reported history of diabetes or current diabetes‐specific treatment (either dietary or pharmacologic) on the systemized questionnaire or as a fasting plasma glucose level ≥126 mg/dL or hemoglobin A1c ≥6.5%. Hypertension was defined as blood pressure ≥140/90 mm Hg or a self‐reported history of hypertension and/or the use of antihypertensive medication. Hyperlipidemia was defined as total cholesterol ≥240 mg/dL or a self‐reported history of hyperlipidemia and/or the use of an antihyperlipidemic medication. A family history of CAD was defined as having a first‐degree relative of any age with CAD, as reported on the self‐report questionnaire. 13 The 10‐year CAD risk score was calculated using the Framingham risk model. 4
CCTA Image Acquisition and Analysis
Imaging with CCTA was conducted by using single‐source, 256‐slice computed tomography (CT) (Brilliance iCT; Philips Healthcare, Best, the Netherlands) or dual‐source CT (Somatom Definition Flash; Siemens, Erlangen, Germany). Participants with no contraindication to β‐adrenergic blocking agents and with a baseline heart rate of >65 beats/min were administrated 100 mg of metoprolol tartrate orally (Betaloc; Yuhan, Seoul, Korea). Participants also took nitroglycerin sublingually before contrast injection. The CT scanning was performed in the prospective ECG‐triggering mode or the retrospective ECG‐gating mode with ECG‐based tube current modulation. During acquisition of CCTA images, 60 to 80 mL of iodinated contrast material (Iomeron 400; Bracco, Milan, Italy) was injected at 4 mL/s, followed by a 40‐mL saline flush. A region of interest was placed in the ascending aorta, and image acquisition was initiated automatically once a selected threshold (100 Hounsfield units) had been reached by using bolus tracking. A standard coronary scanning protocol was used, and the tube voltage and tube current‐time product were adjusted according to the patient’s body size as follows: 80‐ to 120‐kVp tube voltage, 240 to 400 mAs per rotation (dual‐source CT), and 400‐ to 800‐mA tube current (256‐ slice CT).
All CCTA image interpretation and calcium scoring were performed using a dedicated workstation (Syngo.via [Siemens] or Aquarius iNtuition [Terarecon]) by an experienced cardiovascular radiologist and cardiologist, each with >10 years of experience (S.H.C., W.J.K., and G.M.P.). Final decisions on the findings were reached by consensus. According to the guidelines of the Society of Cardiovascular Computed Tomography, a 16‐segment coronary artery tree model was used. 14 The coronary artery calcium score was measured and categorized by scores of 0, 1 to 10, 11 to 100, 101 to 400, and >400. 15 Plaques containing calcified tissue involving >50% of the plaque area (density, >130 Hounsfield units) were classified as calcified, plaques with <50% calcium were classified as mixed, and plaques without calcium were classified as noncalcified. 16 The contrast‐enhanced portion of the coronary lumen was semiautomatically traced at the site of maximal stenosis and compared with the mean value of the proximal and distal reference sites. 17 Stenosis ≥50% was defined as significant.
Statistical Analysis
Categorical variables were expressed as frequencies with percentages, and continuous variables were expressed as the mean and SD. Comparisons were performed using the χ2 test or the Fisher exact test for categorical variables and the unpaired Student t‐test or nonparametric Mann‐Whitney test for numerical variables, as appropriate. Logistic regression analyses were performed to evaluate the association between marital status and subclinical coronary atherosclerosis detected by CCTA. On the basis of previous epidemiologic studies, 2 , 3 , 4 these clinically important variables were selected: age, sex, diabetes, hypertension, hyperlipidemia, obesity, current smoking, family history of CAD, and CRP. Multivariable logistic regression analyses were performed using these covariates. In addition, to reduce the potential confounding factors in an observational study, propensity score matching analysis was performed on the basis of variables in Table 1. Propensity score matching was conducted by a 2:1 nearest‐neighbor matching using a caliper size of 0.2. The balance of covariates in the matched groups was evaluated by measuring their standardized differences in means. All standardized mean differences in the baseline variables were <0.2 (20%) (Figure S1). In the propensity‐score matched pairs, the risks of subclinical coronary atherosclerosis were compared by logistic regression using generalized estimating equations for categorical variables or by the linear mixed model for continuous variables that accounted for the clustering of matched pairs. Data manipulation and statistical analyses were performed using the SPSS software, version 24 (SPSS, Chicago, IL) and the R software version 4.0.2 (R Foundation for Statistical Computing, Vienna, Austria; www.r‐project.org). R “MatchIt” package was used for the propensity score matching. All reported P values are 2 sided, and P<0.05 was considered statistically significant.
Table 1.
Baseline Characteristics of Individuals, According to Marital Status
| Characteristics | Overall population (n=9288) | Propensity score–matched population (2:1) | ||||
|---|---|---|---|---|---|---|
| Married (n=8481) | Unmarried (n=807) | P value | Married (n=1594) | Unmarried (n=804) | P value | |
| Age, y | 53.5±7.5 | 55.4±12.0 | <0.001 | 55.3±7.9 | 55.3±12.0 | 0.960 |
| Men, n (%) | 5663 (66.8) | 378 (46.8) | <0.001 | 791 (49.6) | 378 (47.0) | 0.239 |
| Body mass index, kg/m2 | 24.2±2.9 | 24.1±3.5 | 0.082 | 24.3±3.1 | 24.1±3.5 | 0.204 |
| Waist circumference, cm | 85.6±7.7 | 85.5±9.0 | 0.361 | 86.1±7.8 | 85.5±9.0 | 0.115 |
| Systolic blood pressure, mm Hg | 124.6±13.7 | 126.2±14.7 | 0.007 | 127.2±15.1 | 126.1±14.6 | 0.068 |
| Diastolic blood pressure, mm Hg | 78.5±9.3 | 78.4±9.7 | 0.768 | 78.8±9.7 | 78.4±9.7 | 0.307 |
| Diabetes, n (%) | 1075 (12.9) | 121 (15.2) | 0.069 | 251 (15.7) | 120 (14.9) | 0.625 |
| Hypertension, n (%) | 2788 (33.3) | 312 (39.2) | 0.001 | 677 (42.5) | 313 (38.9) | 0.100 |
| Hyperlipidemia, n (%) | 1518 (18.2) | 138 (17.4) | 0.571 | 291 (18.3) | 140 (17.4) | 0.655 |
| Lipid‐lowering medication, n (%) | 548 (6.6) | 46 (5.8) | 0.378 | 95 (6.1) | 46 (5.8) | 0.807 |
| Current smoker, n (%) | 1862 (22.3) | 176 (22.3) | 0.994 | 340 (21.3) | 176 (21.9) | 0.750 |
| Obesity, n (%) | 3103 (36.7) | 275 (34.2) | 0.160 | 591 (37.1) | 276 (34.3) | 0.187 |
| Family history of coronary artery disease, n (%)* | 753 (9.1) | 71 (9.0) | 0.922 | 155 (9.7) | 72 (9.0) | 0.540 |
| Fasting blood glucose, mg/dL | 96.6±22.7 | 94.8±21.1 | 0.031 | 95.4±21.0 | 94.8±21.1 | 0.505 |
| Glycated hemoglobin, % | 5.7±0.8 | 5.7±0.8 | 0.640 | 5.7±0.8 | 5.7±0.8 | 0.527 |
| Total cholesterol, mg/dL | 191.3±36.6 | 191.5±38.3 | 0.988 | 192.1±36.7 | 191.5±38.4 | 0.719 |
| Low‐density lipoprotein cholesterol, mg/dL | 127.2±33.9 | 128.1±35.7 | 0.625 | 128.5±34.5 | 128.1±35.8 | 0.766 |
| High‐density lipoprotein cholesterol, mg/dL | 52.7±14.8 | 53.7±15.1 | 0.046 | 52.9±15.5 | 53.8±15.1 | 0.162 |
| Triglyceride, mg/dL | 117.2±78.0 | 111.5±72.1 | 0.047 | 116.6±79.8 | 111.5±72.2 | 0.118 |
| Creatinine, mg/dL | 0.9±0.2 | 0.8±0.2 | <0.001 | 0.8±0.2 | 0.8±0.2 | 0.382 |
| Uric acid, mg/dL | 5.4±1.4 | 5.2±1.4 | <0.001 | 5.2±1.3 | 5.2±1.4 | 0.342 |
| CRP ≥2 mg/L, n (%) | 47 (0.6) | 4 (0.5) | 0.999 | 5 (0.3) | 4 (0.5) | 0.491 |
| Ejection fraction, % | 64.4±4.6 | 64.0±4.7 | 0.055 | 64.1±5.0 | 64.0±4.6 | 0.497 |
| Framingham risk score | 6.8±4.8 | 8.3±6.3 | <0.001 | 8.5±6.0 | 8.2±6.2 | 0.175 |
Values are shown as mean±SD or number (percentage). CRP indicates C‐reactive protein.
Coronary artery disease in a first‐degree relative of any age.
Results
Baseline Characteristics
The mean age of the study population was 53.7±8.0 years, and 6041 (65.0%) were men. Marital status classifications were married (n=8481) versus unmarried (n=807), including never married (n=195), divorced (n=183), separated (n=119), and widowed (n=310). Table 1 shows the baseline characteristics of participants by marital status. Mean age, prevalence of women, prevalence of hypertension, systolic blood pressure levels, high‐density lipoprotein cholesterol levels, and Framingham risk score were higher in unmarried participants. By contrast, fasting blood glucose, triglyceride, creatinine, and uric acid concentrations were lower in unmarried participants. After 2:1 propensity score matching, there were 2398 matched participants. In the matched cohort, no significant differences were observed in any baseline variable between the married and unmarried groups (Table 1).
CCTA Findings
Table 2 shows the CCTA findings. The mean coronary artery calcium score of the study population was 38.9±156.9. Any coronary plaques were detected in 3118 (33.6%) participants, specifically: calcified in 2882 (31.0%), noncalcified in 544 (5.9%), and mixed plaques in 349 (3.8%) participants. Of all study participants, 568 (6.1%) had significant coronary artery stenosis (≥50% diameter stenosis) in at least one coronary artery on CCTA as follows: left main in 9 (0.1%), left anterior descending in 429 (4.6%), left circumflex in 140 (1.5%), and right coronary artery in 207 (2.2%) participants. The prevalence of any coronary, calcified, noncalcified, mixed plaques and significant stenosis did not differ between married and unmarried individuals (P>0.05 for all).
Table 2.
Comparison of CCTA Findings, According to Marital Status
| Variables | Overall |
Married (n=8481) |
Unmarried (n=807) |
P value |
|---|---|---|---|---|
| Coronary artery calcium score | 38.9±156.9 | 38.1±154.0 | 47.8±185.1 | 0.293 |
| Coronary artery calcium score, n (%) | 0.485 | |||
| 0 | 6298 (68.1) | 5757 (68.2) | 541 (67.2) | |
| 1–10 | 798 (8.6) | 732 (8.7) | 66 (8.2) | |
| 11–100 | 1306 (14.1) | 1191 (14.1) | 115 (14.3) | |
| 101–400 | 626 (6.8) | 569 (6.7) | 57 (7.1) | |
| >400 | 216 (2.3) | 190 (2.3) | 26 (3.2) | |
| Any atherosclerotic plaque, n (%) | 3118 (33.6) | 2837 (33.5) | 281 (34.8) | 0.431 |
| Plaque characteristics, n (%) | ||||
| Calcified plaque | 2882 (31.0) | 2624 (30.9) | 258 (32.0) | 0.545 |
| Noncalcified plaque | 544 (5.9) | 498 (5.9) | 46 (5.7) | 0.843 |
| Mixed plaque | 349 (3.8) | 313 (3.7) | 36 (4.5) | 0.271 |
| Significant stenosis, n (%) | 568 (6.1) | 513 (6.0) | 55 (6.8) | 0.385 |
Values are shown as mean±SD or number (percentage). CCTA indicates coronary computed tomographic angiography.
Association Between Marital Status and Subclinical Coronary Atherosclerosis
The association between marital status and subclinical atherosclerosis is shown in Table 3. After adjustment for cardiovascular risk factors (age, sex, obesity, diabetes, hypertension, hyperlipidemia, current smoking, family history of CAD, and CRP), logistic regression analyses revealed that unmarried status was not associated with coronary artery calcification, any coronary, calcified, noncalcified, mixed plaques, or significant coronary artery stenosis (P>0.05 for all). Furthermore, in the 2:1 propensity score matched population (2398 participants), no statistically significant differences was observed in the odds ratio (OR) for any subclinical coronary atherosclerosis between married and unmarried participants (P>0.05 for all) (Table 3).
Table 3.
Association Between Marital Status and CCTA Findings
| Univariable | Multivariable | Propensity score–matching analysis | ||||
|---|---|---|---|---|---|---|
| Variables | Odds ratio (95% CI) | P value | Adjusted odds ratio (95% CI) | P value | Odds ratio (95% CI) | P value |
| Coronary artery calcification* | ||||||
| Unmarried | 1.070 (0.904–1.266) | 0.432 | 1.021 (0.835–1.249) | 0.839 | 1.007 (0.830–1.221) | 0.947 |
| Married (reference) | 1 | … | 1 | … | 1 | … |
| Any atherosclerotic plaque | ||||||
| Unmarried | 1.063 (0.913–1.237) | 0.431 | 1.077 (0.899–1.291) | 0.419 | 1.055 (0.882–1.261) | 0.558 |
| Married (reference) | 1 | … | 1 | … | 1 | … |
| Calcified plaque | ||||||
| Unmarried | 1.049 (0.898–1.225) | 0.545 | 1.058 (0.881–1.271) | 0.546 | 1.031 (0.861–1.235) | 0.739 |
| Married (reference) | 1 | … | 1 | … | 1 | … |
| Noncalcified plaque | ||||||
| Unmarried | 0.969 (0.710–1.323) | 0.843 | 0.966 (0.691–1.351) | 0.839 | 0.934 (0.645–1.354) | 0.720 |
| Married (reference) | 1 | … | 1 | … | 1 | … |
| Mixed plaque | ||||||
| Unmarried | 1.218 (0.856–1.734) | 0.272 | 1.301 (0.884–1.917) | 0.182 | 0.935 (0.620–1.410) | 0.748 |
| Married (reference) | 1 | … | 1 | … | 1 | … |
| Significant stenosis | ||||||
| Unmarried | 1.136 (0.852–1.515) | 0.385 | 1.066 (0.771–1.474) | 0.697 | 0.981 (0.704–1.368) | 0.910 |
| Married (reference) | 1 | … | 1 | … | 1 | … |
Covariates in the multivariable model include age, sex, obesity, diabetes, hypertension, hyperlipidemia, current smoking, family history of coronary artery disease, and CRP (C‐reactive protein) ≥2 mg/L. CCTA indicates coronary computed tomographic angiography.
Coronary artery calcification is defined as coronary artery calcium score >10.
Subgroup Analyses According to Each Unmarried Status
The study specifically analyzed the married group (n=8481) versus each unmarried group, comprising never married (n=195), divorced (n=183), separated (n=119), and widowed (n=310). According to married versus each unmarried group, baseline characteristics of individuals are shown in Tables S1, S4, S7, and S10. The CCTA findings between married and each unmarried group were also presented in Tables S2, S5, S8, and S11. On multivariable logistic regression analyses, adjusted with cardiovascular risk factors, the adjusted ORs of each unmarried group relative to married were not associated with coronary artery calcification; any coronary, calcified, noncalcified, mixed plaque; or significant coronary artery stenosis. In each propensity‐matched population, the OR of subclinical coronary atherosclerosis did not differ between married and each unmarried group, except for noncalcified plaque in separated participants (OR, 0.279; 95% CI, 0.084–0.934) (Tables S3, S6, S9, and S12).
Discussion
The main finding of this study with asymptomatic individuals assessed by CCTA is that unmarried status was not associated with an increased risk of any subclinical coronary atherosclerosis. Specifically, the risk of subclinical coronary atherosclerosis in each unmarried group, categorized as never married, divorced, separated, or widowed, did not differ from that of the married group. In addition, to the best of our knowledge, this study is the first to assess the association between marital status and subclinical coronary atherosclerosis detected by CCTA in asymptomatic participants.
Marital status has shown a clinical impact on cardiovascular outcomes in patients with CAD. 8 In a previous prospective study of 1401 patients after myocardial infarction, married patients had a significantly better survival benefit with respect to both in‐hospital and long‐term mortality. 9 In another prospective cohort of 6051 patients undergoing cardiac catheterization for suspected or confirmed CAD, unmarried participants had higher risk for all‐cause mortality, cardiovascular death, and cardiovascular death or myocardial infarction compared with married participants. 10 An observational study with 11 216 patients undergoing percutaneous coronary intervention also demonstrated higher cardiac event rates in unmarried versus married patients. 11 The support social network, early recognition for health changes, improved adherence, and financial resources afforded by spouses may be important benefits in married patients with CAD. 7 , 8 On the basis of these benefits, protective role of marriage on cardiovascular outcomes is well established in patients with CAD. 7
Previously, some studies grouped individuals with an unmarried status together, whereas other studies differentiated unmarried participants into never married, divorced, separated, or widowed groups, which may reflect heterogeneity among studies. 8 , 10 , 18 , 19 , 20 In a meta‐analysis, the risk of all‐cause and CAD‐related mortality increased in the divorced individuals, but this increase was not seen in widowed participants in the general population. 8 In the US National Health Interview Survey, never married individuals were less likely to be smokers, alcohol consumers, or overweight and more likely to exercise compared with married individuals, suggesting that those who never married may have better health habits. 21 These findings suggest that clinical impact on CAD may be different even among the unmarried groups. Moreover, it remains unknown whether each marital status is associated with subclinical coronary atherosclerosis, which suggests a need for in‐depth analysis of observational data from a sizable population. Therefore, the present study aimed to evaluate the association between marital status and the risk of subclinical coronary atherosclerosis through analysis from a large CCTA registry.
In the multivariable analysis of this study, traditional risk factors, including age (OR, 1.106; 95% CI, 1.098–1.114), men (OR, 3.511; 95% CI, 3.106–3.969), obesity (OR, 1.237; 95% CI, 1.117–1.371), diabetes (OR, 1.856; 95% CI, 1.614–2.133), hypertension (OR, 1.913; 95% CI, 1.724–2.122), hyperlipidemia (OR, 1.418; 95% CI, 1.614–2.133), current smoking (OR, 1.283; 95% CI, 1.136–1.450), and family history of CAD (OR, 1.262; 95% CI, 1.065–1.496), were significantly associated with any coronary plaque on CCTA. However, unmarried status was not associated with an increased risk of subclinical coronary atherosclerosis detected by CCTA. Furthermore, the risk of each unmarried group, such as never married, divorced, separated, or widowed, did not differ from married group. Previous multicenter studies have reported a high diagnostic accuracy of CCTA for CAD in various populations. 22 In addition, CCTA has a proven long‐term prognostic value for patients with suspected CAD, even for asymptomatic participants. 23 , 24 , 25 Thus, considering the findings of the present study, the association between unmarried status and subclinical disease before CAD events is not more influential than traditional risk factors. Therefore, in unmarried individuals without CAD events, the modification of traditional cardiovascular risk factors and lifestyles should be prioritized to reduce the risk of CAD. In contrast, in those with established CAD, evidence showed that marital status played a role influencing CAD‐related morbidity and mortality. 8 , 9 , 10 , 11 Therefore, to prevent future cardiac events in unmarried patients with CAD, an increased focus on these patients may be warranted.
Our study had several limitations. First, the current study was conducted at a single center. Our study population was at relatively low risk for CAD (mean 10‐year Framingham risk score, 6.9%). In addition, because all study participants voluntarily underwent CCTA for a general health examination, it is possible that the study enrolled many participants who were more interested in their health than may be represented in the general population. Therefore, selection bias is possible. In addition, because the different groups of unmarried population are relatively limited in number, prospective studies with larger populations are needed to confirm these findings. Second, calcified plaques and higher coronary artery calcium score may have led to an overestimation of significant coronary artery stenosis. Third, the study participants were exclusively Korean, which may limit the applicability of findings to other ethnic groups. Fourth, despite using propensity score analysis to control for measured confounders, hidden or unmeasured confounders might have influenced our findings. In addition, because our study relied on self‐reported medical history, there was a possibility of recall bias. Finally, CCTA has potential shortcomings, such as radiation hazards, use of contrast, and high cost. Therefore, although this study population only included volunteers, the performance of CCTA in asymptomatic individuals cannot be justified. Despite these limitations, we believe that our study may have important clinical implications in revealing the association between marital status and subclinical coronary atherosclerosis in asymptomatic individuals.
In conclusion, this large cross‐sectional study with asymptomatic individuals undergoing CCTA showed that unmarried status was not associated with subclinical coronary atherosclerosis. In addition, the risk of subclinical coronary atherosclerosis in each unmarried group, such as never married, divorced, separated, or widowed, did not differ from that of the married group. These findings should be further investigated and validated in prospective studies.
Sources of Funding
This research was supported by the Basic Science Research Program through the National Research Foundation of Korea, funded by the Ministry of Education (2018R1D1A3B07043344), and the medical data‐driven hospital support project, through the Korea Health Information Service, funded by the Ministry of Health and Welfare, Republic of Korea. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Disclosures
None.
Supporting information
Tables S1–S12
Figure S1
Acknowledgments
The Big Data Center of Ulsan University Hospital supported this work in terms of statistical analysis.
S.H. Ann and H. Lee contributed equally.
Contributor Information
Woon Jung Kwon, Email: becareful123@uuh.ulsan.kr.
Gyung‐Min Park, Email: gmpark@uuh.ulsan.kr.
References
- 1. Vos T, Lim SS, Abbafati C, Abbas KM, Abbasi M, Abbasifard M, Abbasi‐Kangevari M, Abbastabar H, Abd‐Allah F, Abdelalim A, et al. Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet. 2020;396:1204–1222. doi: 10.1016/S0140-6736(20)30925-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Goff DC, Lloyd‐Jones DM, Bennett G, Coady S, D’Agostino RB, Gibbons R, Greenland P, Lackland DT, Levy D, O’Donnell CJ, et al. 2013 ACC/AHA guideline on the assessment of cardiovascular risk: a report of the American College of Cardiology/American Heart Association task force on practice guidelines. Circulation. 2014;129:S49–S73. doi: 10.1161/01.cir.0000437741.48606.98 [DOI] [PubMed] [Google Scholar]
- 3. Conroy RM, Pyörälä K, Fitzgerald AP, Sans S, Menotti A, De Backer G, De Bacquer D, Ducimetière P, Jousilahti P, Keil U, et al. Estimation of ten‐year risk of fatal cardiovascular disease in Europe: the SCORE project. Eur Heart J. 2003;24:987–1003. doi: 10.1016/s0195-668x(03)00114-3 [DOI] [PubMed] [Google Scholar]
- 4. Wilson PW, D'Agostino RB, Levy D, Belanger AM, Silbershatz H, Kannel WB. Prediction of coronary heart disease using risk factor categories. Circulation. 1998;97:1837–1847. doi: 10.1161/01.cir.97.18.1837 [DOI] [PubMed] [Google Scholar]
- 5. Knuuti J, Wijns W, Saraste A, Capodanno D, Barbato E, Funck‐Brentano C, Prescott E, Storey RF, Deaton C, Cuisset T, et al. 2019 ESC guidelines for the diagnosis and management of chronic coronary syndromes. Eur Heart J. 2020;41:407–477. doi: 10.1093/eurheartj/ehz425 [DOI] [PubMed] [Google Scholar]
- 6. Arnett DK, Blumenthal RS, Albert MA, Buroker AB, Goldberger ZD, Hahn EJ, Himmelfarb CD, Khera A, Lloyd‐Jones D, McEvoy JW, et al. 2019 ACC/AHA guideline on the primary prevention of cardiovascular disease: a report of the American College of Cardiology/American Heart Association task force on clinical practice guidelines. Circulation. 2019;140:e596–e646. doi: 10.1161/CIR.0000000000000678 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Dhindsa DS, Khambhati J, Schultz WM, Tahhan AS, Quyyumi AA. Marital status and outcomes in patients with cardiovascular disease. Trends Cardiovasc Med. 2020;30:215–220. doi: 10.1016/j.tcm.2019.05.012 [DOI] [PubMed] [Google Scholar]
- 8. Wong CW, Kwok CS, Narain A, Gulati M, Mihalidou AS, Wu P, Alasnag M, Myint PK, Mamas MA. Marital status and risk of cardiovascular diseases: a systematic review and meta‐analysis. Heart. 2018;104:1937–1948. doi: 10.1136/heartjnl-2018-313005 [DOI] [PubMed] [Google Scholar]
- 9. Chandra V, Szklo M, Goldberg R, Tonascia J. The impact of marital status on survival after an acute myocardial infarction: a population‐based study. Am J Epidemiol. 1983;117:320–325. doi: 10.1093/oxfordjournals.aje.a113544 [DOI] [PubMed] [Google Scholar]
- 10. Schultz WM, Hayek SS, Samman Tahhan A, Ko Y‐A, Sandesara P, Awad M, Mohammed KH, Patel K, Yuan M, Zheng S, et al. Marital status and outcomes in patients with cardiovascular disease. J Am Heart Assoc. 2017;6:e005890. doi: 10.1161/JAHA.117.005890 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Barbash IM, Gaglia MA Jr, Torguson R, Minha S, Satler LF, Pichard AD, Waksman R. Effect of marital status on the outcome of patients undergoing elective or urgent coronary revascularization. Am Heart J. 2013;166:729–736. doi: 10.1016/j.ahj.2013.07.018 [DOI] [PubMed] [Google Scholar]
- 12. Park GM, Yun SC, Cho YR, Gil EH, Her SH, Kim SH, Jo MW, Lee MS, Lee SW, Kim Y‐H, et al. Prevalence of coronary atherosclerosis in an Asian population: findings from coronary computed tomographic angiography. Int J Cardiovasc Imaging. 2015;31:659–668. doi: 10.1007/s10554-015-0587-0 [DOI] [PubMed] [Google Scholar]
- 13. Park GM, Han S, Kim SH, Jo MW, Her SH, Lee JB, Lee MS, Kim HC, Ahn JM, Lee SW, et al. Model for assessing cardiovascular risk in a Korean population. Circ Cardiovasc Qual Outcomes. 2014;7:944–951. doi: 10.1161/CIRCOUTCOMES.114.001305 [DOI] [PubMed] [Google Scholar]
- 14. Raff GL, Abidov A, Achenbach S, Berman DS, Boxt LM, Budoff MJ, Cheng V, DeFrance T, Hellinger JC, Karlsberg RP. SCCT guidelines for the interpretation and reporting of coronary computed tomographic angiography. J Cardiovasc Comput Tomogr. 2009;3:122–136. doi: 10.1016/j.jcct.2009.01.001 [DOI] [PubMed] [Google Scholar]
- 15. Agatston AS, Janowitz WR, Hildner FJ, Zusmer NR, Viamonte M Jr, Detrano R. Quantification of coronary artery calcium using ultrafast computed tomography. J Am Coll Cardiol. 1990;15:827–832. doi: 10.1016/0735-1097(90)90282-t [DOI] [PubMed] [Google Scholar]
- 16. Leber AW, Becker A, Knez A, von Ziegler F, Sirol M, Nikolaou K, Ohnesorge B, Fayad ZA, Becker CR, Reiser M, et al. Accuracy of 64‐slice computed tomography to classify and quantify plaque volumes in the proximal coronary system: a comparative study using intravascular ultrasound. J Am Coll Cardiol. 2006;47:672–677. doi: 10.1016/j.jacc.2005.10.058 [DOI] [PubMed] [Google Scholar]
- 17. Hausleiter J, Meyer T, Hadamitzky M, Kastrati A, Martinoff S, Schömig A. Prevalence of noncalcified coronary plaques by 64‐slice computed tomography in patients with an intermediate risk for significant coronary artery disease. J Am Coll Cardiol. 2006;48:312–318. doi: 10.1016/j.jacc.2006.02.064 [DOI] [PubMed] [Google Scholar]
- 18. Ikeda A, Iso H, Toyoshima H, Fujino Y, Mizoue T, Yoshimura T, Inaba Y, Tamakoshi A, JACC Study Group . Marital status and mortality among Japanese men and women: the Japan Collaborative Cohort Study. BMC Public Health. 2007;7:73. doi: 10.1186/1471-2458-7-73 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Manzoli L, Villari P, M Pirone G, Boccia A. Marital status and mortality in the elderly: a systematic review and meta‐analysis. Soc Sci Med. 2007;64:77–94. doi: 10.1016/j.socscimed.2006.08.031 [DOI] [PubMed] [Google Scholar]
- 20. Va P, Yang W‐S, Nechuta S, Chow W‐H, Cai H, Yang G, Gao S, Gao Y‐T, Zheng W, Shu X‐O, et al. Marital status and mortality among middle age and elderly men and women in urban Shanghai. PLoS One. 2011;6:e26600. doi: 10.1371/journal.pone.0026600 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Kaplan RM, Kronick RG. Marital status and longevity in the United States population. J Epidemiol Community Health. 2006;60:760–765. doi: 10.1136/jech.2005.037606 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Min JK, Shaw LJ, Berman DS. The present state of coronary computed tomography angiography a process in evolution. J Am Coll Cardiol. 2010;55:957–965. doi: 10.1016/j.jacc.2009.08.087 [DOI] [PubMed] [Google Scholar]
- 23. Hadamitzky M, Täubert S, Deseive S, Byrne RA, Martinoff S, Schömig A, Hausleiter J. Prognostic value of coronary computed tomography angiography during 5 years of follow‐up in patients with suspected coronary artery disease. Eur Heart J. 2013;34:3277–3285. doi: 10.1093/eurheartj/eht293 [DOI] [PubMed] [Google Scholar]
- 24. Kang SH, Park GM, Lee SW, Yun SC, Kim YH, Cho YR, Park HW, Suh J, Yang DH, Kang JW, et al. Long‐term prognostic value of coronary CT angiography in asymptomatic type 2 diabetes mellitus. JACC Cardiovasc Imaging. 2016;9:1292–1300. doi: 10.1016/j.jcmg.2016.01.040 [DOI] [PubMed] [Google Scholar]
- 25. Park HW, Kim Y‐G, Park G‐M, Park S, Cho Y‐R, Suh J, Lee Y, Yang DH, Kang J‐W, Kim H‐K, et al. Cholesterol control for subclinical coronary atherosclerosis in subjects without indication for statin therapy. Am J Cardiol. 2021;153:51–57. doi: 10.1016/j.amjcard.2021.05.019 [DOI] [PubMed] [Google Scholar]
Associated Data
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Supplementary Materials
Tables S1–S12
Figure S1