Next Article in Journal
Assessment of Self-Reported Executive Function in Patients with Irritable Bowel Syndrome Using a Machine-Learning Framework
Previous Article in Journal
The Effect of Metformin on Plasma Prolactin Levels in Young Women with Autoimmune Thyroiditis
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
JCM
Volume 12
Issue 11
10.3390/jcm12113770
jcm-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Assessment of Normal Systolic Blood Pressure Maintenance with the Risk of Coronary Artery Calcification Progression in Asymptomatic Metabolically Healthy Korean Adults with Normal Weight, Overweight, and Obesity

by
Ki-Bum Won
1,2,
Su-Yeon Choi
3,
Eun Ju Chun
4,
Sung Hak Park
5,
Jidong Sung
6,
Hae Ok Jung
7 and
Hyuk-Jae Chang
2,*
1
Division of Cardiology, Dongguk University Ilsan Hospital, Dongguk University College of Medicine, Goyang 10326, Republic of Korea
2
Division of Cardiology, Severance Cardiovascular Hospital, Yonsei University College of Medicine, Yonsei University Health System, Seoul 03722, Republic of Korea
3
Division of Cardiology, Healthcare System Gangnam Center, Seoul National University Hospital, Seoul 06236, Republic of Korea
4
Division of Radiology, Seoul National University Bundang Hospital, Seongnam 13620, Republic of Korea
5
Division of Radiology, Gangnam Heartscan Clinic, Seoul 06168, Republic of Korea
6
Division of Cardiology, Heart Stroke & Vascular Institute, Samsung Medical Center, Seoul 06351, Republic of Korea
7
Division of Cardiology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea
*
Author to whom correspondence should be addressed.
J. Clin. Med. 2023, 12(11), 3770; https://doi.org/10.3390/jcm12113770
Submission received: 3 April 2023 / Revised: 27 May 2023 / Accepted: 29 May 2023 / Published: 31 May 2023
(This article belongs to the Section Cardiovascular Medicine)
Browse Figures
Versions Notes

Abstract

:
Metabolically healthy obesity (MHO) is known to have a close association with subclinical coronary atherosclerosis. Despite recent data on the benefit of intensive systolic blood pressure (SBP) control in diverse clinical conditions, little is known regarding the association of normal SBP maintenance (SBPmaintain) with coronary artery calcification (CAC) progression in MHO. This study included 2724 asymptomatic adults (48.8 ± 7.8 years; 77.9% men) who had no metabolic abnormalities except overweight and obesity. Participants with normal weight (44.2%), overweight (31.6%), and obesity (24.2%) were divided into two groups: normal SBPmaintain (follow-up SBP < 120 mm Hg) and ≥elevated SBPmaintain (follow-up SBP ≥ 120 mm Hg). CAC progression was defined using the SQRT method, a difference of ≥2.5 between the square root (√) of the baseline and follow-up coronary artery calcium score. During a mean follow-up of 3.4 years, the proportion of normal SBPmaintain (76.2%, 65.2%, and 59.1%) and the incidence of CAC progression (15.0%, 21.3%, and 23.5%) was different in participants with normal weight, overweight, and obesity (all p < 0.05, respectively). The incidence of CAC progression was lower in the normal SBPmaintain group than in the ≥elevated SBPmaintain group in only participants with obesity (20.8% vs. 27.4%, p = 0.048). In multiple logistic models, compared to participants with normal weight, those with obesity had a higher risk of CAC progression. Normal SBPmaintain was independently associated with the decreased risk of CAC progression in participants with obesity. MHO had a significant association with CAC progression. Normal SBPmaintain reduced the risk of CAC progression in asymptomatic adults with MHO.

1. Introduction

Obesity is a substantial cardiovascular (CV) risk factor [1,2], contributing to the development of CV disease through numerous metabolic abnormalities, including hypertension, hyperglycemia, and dyslipidemia [3,4]. It has been of interest whether individuals with obesity but without other metabolic abnormalities are still at an increased risk of CV disease [5,6]. For this population, the term of metabolically healthy obesity (MHO) has been used in clinical practice. A number of studies have reported that MHO is not a benign health condition with respect to atherosclerotic CV disease [7,8,9].
Recent randomized trials consistently reported the benefit of intensive systolic blood pressure (SBP) control for reducing major adverse events in patients with an increased CV risk [10,11]. Thus, the American College of Cardiology (ACC)/American Heart Association (AHA) guidelines lowered the blood pressure thresholds for the diagnosis of hypertension [12]. In addition, the Kidney Disease Improving Global Outcomes guidelines also recommend targeting SBP lower than or equal to 120 mmHg in chronic kidney disease patients excluding those with dialysis or a kidney transplant [13]. However, little is known as to whether the normal SBP maintenance (SBPmaintain) is an effective strategy for attenuating coronary atherosclerosis in asymptomatic adult population with MHO. This is an important issue considering that recent data showed no significant association of body mass index (BMI) changes with the progression of coronary arteriosclerosis during a near-term period [14].
In asymptomatic adult population, the coronary artery calcium score (CACS) is widely used for CV risk stratification because of its prognostic significance beyond clinical risk factors [15,16,17]. In addition, coronary artery calcification (CAC) progression provides additional prognostic information in conditions without baseline heavy CAC [18]. This suggests that early detection of the presence and progression of CAC is important in the era of primary prevention. Numerous studies have suggested using CACS to determine therapeutic targets in various clinical conditions [19,20,21,22]. The present study aimed to evaluate the association between normal SBPmaintain and the risk of CAC progression among asymptomatic metabolically healthy Korean adults with normal weight, overweight, and obesity.

2. Materials and Methods

2.1. Study Design and Population

Data from the Korea Initiatives on Coronary Artery Calcification (KOICA) registry were analyzed in this study. The KOICA registry is a retrospective, single-ethnicity, multicenter, and observational study designed to investigate the effectiveness and prognostic value of CACS for primary prevention of CV disease in asymptomatic Korean adults [23,24]. All data were obtained using a health check database at the healthcare center of each site in South Korea (Severance Cardiovascular Hospital; Seoul National University Hospital; Seoul National University Bundang Hospital; Gangnam Heartscan Clinic; Samsung Medical Center; Seoul St. Mary’s Hospital). Initially, 93,914 Korean subjects who underwent a CAC scan that was performed at the time of voluntary visit to a healthcare center were enrolled in the KOICA registry between 2003 and 2017. For evaluating the changes of CAC, we identified 12,638 subjects who underwent at least two CAC scans among these subjects. After excluding 9914 subjects who had any component of metabolic syndrome (MetS) or incomplete data for identifying the component of MetS at enrollment, 2724 subjects were finally included in this analysis (Supplementary Figure S1). At each visit to a healthcare center, self-reported medical questionnaires were employed to collect information on the participants’ medical history. Height and weight were measured with the participants wearing light clothing and without shoes. BMI was calculated as weight (kg)/height (m2). Blood pressure was measured using an automatic manometer on the right arm after resting for at least 5 min. All blood tests, including total cholesterol, triglyceride, high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, glucose, and creatinine, were obtained after at least 8 h of fasting. To measure CACS, computed tomography (CT) was performed with ≥16-slice multidetector scanners (Siemens 16-slice Sensation, Siemens, Forchheim, Germany; GE 64-slice Lightspeed, GE Healthcare, Milwaukee, WI, USA; Philips Brilliance 40-channel multidetector CT, Philips Healthcare, Cleveland, OH, USA; Philips Brilliance 256 iCT, Philips Healthcare). All scans were performed with a standard ECG-triggered scan protocol. The CACS was assessed by experienced CV radiologists, and the results were reported in the electronic health records. Informed consent for CT examination was obtained from each participant. All methods were performed in accordance with the relevant guidelines and regulations. The institutional review board committee of Yonsei University Health System, Severance Hospital approved the protocol of the present study (IRB No. 4-2014-0309).

2.2. Definitions

To define metabolically healthy condition except overweight and obesity, the present study employed the criteria of the National Cholesterol Education Program Adult Treatment Panel III for MetS as follows: (a) SBP ≥ 130 mm Hg or diastolic blood pressure (DBP) ≥ 85 mm Hg, previous history of hypertension, or the use of antihypertensive medications; (b) HDL cholesterol < 40 mg/dL in men or <50 mg/dL in women or the use of any medications for the treatment of dyslipidemia; (c) triglycerides ≥ 150 mg/dL or the use of any medications for dyslipidemia; and (d) fasting glucose ≥ 100 mg/dL, previous history of diabetes, or the use of antidiabetic medications [25]. Metabolically healthy condition except overweight and obesity was defined as clinical status without any components mentioned above. Categorical BMI was defined with the current Korean Society for the Study of Obesity Guidelines as follows: normal weight (18.5–22.9 kg/m2), overweight (23.0–24.9 kg/m2), and obesity (≥25.0 kg/m2) [26,27]. All participants with normal weight, overweight, and obesity were divided into two groups: normal SBPmaintain (follow-up SBP < 120 mm Hg) and ≥elevated SBPmaintain (follow-up SBP ≥ 120 mm Hg), respectively. Current smoking was defined as those who currently smoked or had smoked until 1 month before the study [28]. CACS was measured using the scoring system previously described by Agatston et al. [29]. CAC progression was defined using the SQRT method, as a difference of ≥2.5 between the square root (√) of the baseline and follow-up CACS (Δ√transformed CACS) [30,31], considering the proportion of CACS of 0 at baseline and the prognostic value of CAC progression defined using the SQRT method. Annual change of Δ√transformed CACS was defined as Δ√transformed CACS divided by the interscan period.

2.3. Statistical Analysis

The continuous variables are expressed as mean ± standard deviation. The categorical variables are presented as absolute values and proportions. After checking the distribution status of independent variables, we compared the participants’ characteristics among the categorical BMI groups using a one-way analysis of variance or a Kruskal–Wallis test for the continuous variables, as appropriate, and using the chi-squared test or Fisher’s exact test for the categorical variables, as appropriate. To compare the characteristics between normal SBPmaintain and ≥elevated SBPmaintain, we employed an independent t-test or a Mann–Whitney U-test for the continuous variables, as appropriate, and the chi-squared test or Fisher’s exact test for the categorical variables, as appropriate. We used multiple logistic regression models to identify (1) the risk of CAC progression according to the categorical BMI and (2) the association of normal SBPmaintain with the risk of CAC progression in each categorical BMI. The forced entry method was used to enter independent variables for consecutive adjustment, including (1) unmodifiable clinical risk factors of age and sex, (2) modifiable clinical risk factors of SBP, DBP, and serum levels of triglyceride, HDL and LDL cholesterol, glucose, and creatinine, and current smoking, and (3) baseline CACS and interscan period into the multiple regression models. We performed all the statistical analyses using the Statistical Package for the Social Sciences version 19 (Chicago, IL, USA). A p-value of <0.05 was considered significant.

3. Results

3.1. Baseline Characteristics

The baseline characteristics of the overall population are shown in Table 1. The mean age was 48.8 ± 7.8 years, and 2122 (77.9%) were men. The proportion of participants with normal weight, overweight, and obesity was 44.2%, 31.6%, and 24.2%, respectively. The mean levels of SBP and DBP were 110.4 ± 10.3 mm Hg and 68.9 ± 7.9 mm Hg, respectively. Current smokers comprised 25.8% of the population.
Table 2 shows baseline CACS according to the categorical BMI. In participants with a higher BMI, the proportion with a CACS of 0 was decreased; in contrast, the proportion with CACS of 1–100 was increased. No significant difference in the proportion of participants with a CACS of >100 was observed among the participants. The mean values of CACS across three BMI groups were not significantly different (Supplementary Table S1).

3.2. CAC Changes according to Categorical BMI

During the mean follow-up of 3.4 ± 1.9 years, the annual change of Δ√transformed CACS (normal weight 0.29 ± 0.92 vs. overweight 0.45 ± 1.05 vs. obesity 0.50 ± 1.18, p < 0.001) and the incidence of CAC progression (normal weight 15.0% vs. overweight 21.3% vs. obesity 23.5%, p < 0.001) were increased in the participants with higher BMI (Figure 1). In the multiple logistic regression models, compared with participants with normal weight, those with obesity had a higher risk for CAC progression (Table 3).

3.3. Normal SBPmaintain and CAC Progression in Categorical BMI

The overall proportion of normal SBPmaintain was 68.6%; the proportion of normal SBPmaintain in participants with normal weight, overweight, and obesity was 76.2%, 65.2%, and 59.1%, respectively. At follow-up, the use of antihypertensive medication was identified in 4.6% of overall participants; the proportion of antihypertensive medication use in those with normal weight, overweight, and obesity was 2.8%, 6.0%, and 6.0%, respectively (p = 0.001). Compared with the ≥elevated SBPmaintain group, the incidence of CAC progression was not different in the normal SBPmaintain group among participants with normal weight (normal SBPmaintain 13.8% vs. ≥elevated SBPmaintain 18.5%, p = 0.052) and overweight (normal SBPmaintain 21.0% vs. ≥elevated SBPmaintain 21.7%, p = 0.810). However, the incidence of CAC progression was significantly lower in the normal SBPmaintain group than in the ≥elevated SBPmaintain group among the participants with obesity (20.8% vs. 27.4%, p = 0.048) (Figure 2). In multiple logistic regression models, normal SBPmaintain did not show a significant association with the risk of CAC progression among participants with normal weight and overweight. However, normal SBPmaintain was independently associated with a reduced risk of CAC progression in the participants with obesity (Table 4).

4. Discussion

To date, data on the change of subclinical coronary atherosclerosis related to normal SBPmaintain have been limited in asymptomatic metabolically healthy adults. Based on recent suggestions to use CACS for determining therapeutic targets in diverse clinical conditions, this study evaluated the association between normal SBPmaintain and CAC progression among asymptomatic metabolically healthy adults with normal weight, overweight, and obesity. In the present study, we initially confirmed that MHO was associated with the increased risk of CAC progression, as previous numerous studies suggested. The major finding of the present study is that normal SBPmaintain is associated with the decreased risk of CAC progression in conditions with MHO.
There has been no consensus on the definition of MHO [5]. In addition, the BMI cutoffs for defining obesity differ according to ethnicity. A previous cross-sectional cohort study by Chang et al. reported that MHO was associated with a higher prevalence of CAC than in metabolically healthy normal weight among 14,828 metabolically healthy Korean adults [7]. A recent longitudinal study from the Heinz Nixdorf Recall cohort found that subjects with MHO had a higher risk of CAC progression than metabolically healthy subjects with normal weight among 1585 Caucasian adults during a follow-up of 5 years [8]. Furthermore, Caleyachetty et al. identified that subjects with MHO had a higher risk of coronary heart disease, cerebrovascular disease, and heart failure than metabolically healthy subjects with normal weight in a Western population of 3.5 million adults without previous CV disease during a mean follow-up of 5.4 years [9]. Recent meta-analysis also showed that MHO was substantially associated with the increased risk of CAC [32]. These findings reveal that MHO is not a purely benign health condition regardless of MHO definitions and ethnicity.
The lowered blood pressure threshold for diagnosing hypertension by the 2017 ACC/AHA guidelines emphasizes the significance of blood pressure in preventing adverse CV events [12]. This change could lead to the overdiagnosis of hypertension and result in unnecessary treatment, particularly in young adults or in adults with low CV risk. Although both the SPRINT and STEP trials have recently shown the benefit of intensive SBP control in conditions with high CV risk [10,11], the significance of normal SBPmaintain for preventing the progression of subclinical coronary atherosclerosis has not been evaluated among metabolically healthy adults. In the present study, unlike in metabolically healthy adults with normal weight and overweight, normal SBPmaintain independently attenuated the risk of CAC progression in those with obesity. According to the data from the Progression of Atherosclerotic Plaque Determined by Computed Tomographic Angiography Imaging (PARADIGM) registry with a median follow-up of 3.3 years [14], the proportion of shift to a decreased BMI group was only 17.0% in obese subjects. It should be noted that that neither a categorical BMI group change nor a 5% change of BMI in the near-term period were associated with coronary plaque volume changes in the PARADIGM registry. Considering that the majority of subjects with MHO, about 59.1%, maintained normal SBP at follow-up in the present study, the normal SBPmaintain might be an effective target for preventing the progression of subclinical coronary atherosclerosis in conditions with MHO.
Among asymptomatic population, the CACS is an effective and noninvasive tool for CV risk stratification because of its powerful prognostic value across age, sex, ethnicities, and baseline risk factors [15,16,17]. Pharmacological agents such as statins could affect the progression of coronary atherosclerosis [33,34]. For this reason, coronary computed tomographic angiography (CCTA) has been proposed to have additional benefits over CACS and traditional risk factors in asymptomatic subjects due to its ability to provide more detailed information, including plaque burden and its composition. However, recent data from the CONFIRM (Coronary CT Angiography Evaluation For Clinical Outcomes: An International Multicenter) registry showed that further prognostic benefit was not conferred by CCTA when considering the traditional risk factors and CACS in an asymptomatic population [35]. Compared to the CV risk stratification using the traditional risk factors and CACS, the role of CCTA may be limited in asymptomatic clinical conditions.
There is a paucity of consensus for the definition of hypertension in recent clinical practice. Therefore, several studies have suggested the use of CACS to determine individualized therapeutic blood pressure goals [19,36], based on the recent evidence regarding the usefulness of CACS use in diverse clinical situations [21,37]. It may be possible that CACS helps to identify specific patients who may benefit from strict blood pressure control. Further outcome studies should be necessary to support this approach.
There are several limitations to the current study. First, the present cohort of self-referred asymptomatic subjects may not be fully representative of the general population. In addition, we only included participants without metabolic abnormalities except overweight and obesity at enrollment who underwent at least two CAC scans from the KOICA registry. Therefore, the characteristics of our study population did not represent the overall characteristics of the patients in the KOICA registry and a selection bias could be present. Second, different CT scanners were used among the participating centers. However, low inter- and intraobserver variability and high reproducibility across various vendors to measure CACS was well-established [38,39,40]. In addition, the same CT scanner was used with the ECG-trigger method at both image acquisitions. Third, because of the absence of a specific study protocol guiding follow-up CT scanning, the interscan period was relatively short and was not constant. However, we compared (a) the annual change of CAC and (b) the association of normal SBPmaintain with the risk of CAC progression after strict adjustment of confounding factors, including interscan period, among our participants with normal weight, overweight, and obesity. Fourth, data on consecutive changes in the clinical variables were unavailable during follow-up periods because of the observational nature of the study. In the present study, normal SBPmaintain was defined based on a follow-up SBP < 120 mm Hg without considering antihypertensive medication in participants with newly developed hypertension [41]. Some participants with normal SBPmaintain were misclassified into those with ≥elevated SBPmaintain because of white-coat effect and it could attenuate the effect ≥elevated SBPmaintain on the risk of CAC progression. However, this study identified the significance of normal SBPmaintain in subjects with MHO for preventing CAC progression despite the mentioned possibility. Fifth, this study did not evaluate the association of DBP status with the risk of CAC progression in the participants. Finally, considering that all the participants were Korean, it is hard to generalize the results of the present study. Despite these limitations, to the best of our knowledge, the present study is the first to identify that normal SBPmaintain is an effect target for reducing the risk of CAC progression in asymptomatic adults with MHO.

5. Conclusions

MHO was associated with a higher incidence of CAC progression among asymptomatic metabolically healthy Korean adults. Unlike in metabolically healthy subjects with normal weight and overweight, normal SBPmaintain independently reduced the risk of CAC progression in those with obesity. These results might imply that target levels of SBP for attenuating subclinical atherosclerosis might be somewhat different even in conditions with low CV risk. Further randomized investigations with larger sample size should be necessary to identify this issue.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/jcm12113770/s1, Figure S1: Flow chart of the study participant selection process; Table S1: Baseline CACS according to the categorical BMI.

Author Contributions

Conception and design: K.-B.W. and H.-J.C.; collection of data: K.-B.W., S.-Y.C., E.J.C., S.H.P., J.S., H.O.J. and H.-J.C.; data analysis and interpretation: K.-B.W. and H.-J.C.; manuscript writing: K.-B.W.; critical revision: H.-J.C.; final approval of manuscript: all authors. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Korea Medical Device Development Fund grant funded by the Korea Government (the Ministry of Science and ICT, the Ministry of Trade, Industry and Energy, the Ministry of Health & Welfare, Republic of Korea, the Ministry of Food and Drug Safety) (Project Number: 202016B02).

Institutional Review Board Statement

The study received the approval from the research ethics committee of Severance Cardiovascular Hospital (approval number: 4-2014-0309) and was conducted following the guidelines of the Declaration of Helsinki.

Informed Consent Statement

IRB waived the need for written informed consent from the participants.

Data Availability Statement

The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Eckel, R.H.; Kahn, R.; Robertson, R.M.; Rizza, R.A. Preventing cardiovascular disease and diabetes: A call to action from the American Diabetes Association and the American Heart Association. Circulation 2006, 113, 2943–2946. [Google Scholar] [CrossRef] [PubMed]
  2. Lavie, C.J.; Milani, R.V.; Ventura, H.O. Obesity and cardiovascular disease: Risk factor, paradox, and impact of weight loss. J. Am. Coll. Cardiol. 2009, 53, 1925–1932. [Google Scholar] [CrossRef] [PubMed]
  3. Wilson, P.W.; D’Agostino, R.B.; Sullivan, L.; Parise, H.; Kannel, W.B. Overweight and obesity as determinants of cardiovascular risk. The Framingham Experience. Arch. Intern. Med. 2002, 162, 1867–1872. [Google Scholar] [CrossRef]
  4. Arnlöv, J.; Ingelsson, E.; Sundström, J.; Lind, L. Impact of body mass index and the metabolic syndrome on the risk of cardiovascular disease and death in middle-aged men. Circulation 2010, 121, 230–236. [Google Scholar] [CrossRef] [PubMed]
  5. Rey-López, J.P.; de Rezende, L.F.; Pastor-Valero, M.; Tess, B.H. The prevalence of metabolic healthy obesity: A systematic review and critical evaluation of the definitions used. Obes. Rev. 2014, 15, 781–790. [Google Scholar] [CrossRef] [PubMed]
  6. Bradshaw, P.T.; Stevens, J. Invited commentary: Limitations and usefulness of the metabolically healthy obesity phenotype. Am. J. Epidemiol. 2015, 182, 742–744. [Google Scholar] [CrossRef]
  7. Chang, Y.; Kim, B.K.; Yun, K.E.; Cho, J.; Zhang, Y.; Rampal, S.; Zhao, D.; Jung, H.S.; Choi, Y.; Ahn, J.; et al. Metabolically-healthy obesity and coronary artery calcification. J. Am. Coll. Cardiol. 2014, 63, 2679–2686. [Google Scholar] [CrossRef]
  8. Kowall, B.; Lehmann, N.; Mahabadi, A.A.; Moebus, S.; Erbel, R.; Jöckel, K.H.; Stang, A. Associations of metabolically healthy obesity with prevalence and progression of coronary artery calcification: Results from the Heinz Nixdorf Recall Cohort Study. Nutr. Metab. Cardiovasc. Dis. 2019, 29, 228–235. [Google Scholar] [CrossRef]
  9. Caleyachetty, R.; Thomas, G.N.; Toulis, K.A.; Mohammed, N.; Gokhale, K.M.; Balachandran, K.; Nirantharakumar, K. Metabolically healthy obese and incident cardiovascular disease events among 3.5 million men and women. J. Am. Coll. Cardiol. 2017, 70, 1429–1437. [Google Scholar] [CrossRef]
  10. Lewis, C.E.; Fine, L.J.; Beddhu, S.; Cheung, A.K.; Cushman, W.C.; Cutler, J.A.; Evans, G.W.; Johnson, K.C.; Kitzman, D.W.; Oparil, S.; et al. Final report of a trial of intensive versus standard blood-pressure control. N. Engl. J. Med. 2021, 384, 1921–1930. [Google Scholar]
  11. Zhang, W.; Zhang, S.; Deng, Y.; Wu, S.; Ren, J.; Sun, G.; Yang, J.; Jiang, Y.; Xu, X.; Wang, T.D.; et al. Trial of Intensive Blood-Pressure Control in Older Patients with Hypertension. N. Engl. J. Med. 2021, 385, 1268–1279. [Google Scholar] [CrossRef] [PubMed]
  12. Whelton, P.K.; Carey, R.M.; Aronow, W.S.; Casey, D.E., Jr.; Collins, K.J.; Dennison Himmelfarb, C.; DePalma, S.M.; Gidding, S.; Jamerson, K.A.; Jones, D.W.; et al. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA guideline for the prevention, detection, evaluation, and management of high blood pressure in adults: A report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Hypertension 2018, 71, e13–e115. [Google Scholar]
  13. Kidney Disease: Improving Global Outcomes (KDIGO) Blood Pressure Work Group. KDIGO 2021 Clinical Practice Guideline for the Management of Blood Pressure in Chronic Kidney Disease. Kidney Int. 2021, 99, S1–S87. [Google Scholar] [CrossRef] [PubMed]
  14. Won, K.B.; Lee, S.E.; Lee, B.K.; Park, H.B.; Heo, R.; Rizvi, A.; Hadamitzky, M.; Kim, Y.J.; Sung, J.M.; Conte, E.; et al. Longitudinal quantitative assessment of coronary plaque progression related to body mass index using serial coronary computed tomography angiography. Eur Heart J. Cardiovasc. Imaging 2019, 20, 591–599. [Google Scholar] [CrossRef] [PubMed]
  15. Detrano, R.; Guerci, A.D.; Carr, J.J.; Bild, D.E.; Burke, G.; Folsom, A.R.; Liu, K.; Shea, S.; Szklo, M.; Bluemke, D.A.; et al. Coronary calcium as a predictor of coronary events in four racial or ethnic groups. N. Engl. J. Med. 2008, 358, 1336–1345. [Google Scholar] [CrossRef] [PubMed]
  16. Erbel, R.; Möhlenkamp, S.; Moebus, S.; Schmermund, A.; Lehmann, N.; Stang, A.; Dragano, N.; Grönemeyer, D.; Seibel, R.; Kälsch, H.; et al. Coronary risk stratification, discrimination, and reclassification improvement based on quantification of subclinical coronary atherosclerosis: The Heinz Nixdorf Recall study. J. Am. Coll. Cardiol. 2010, 56, 1397–1406. [Google Scholar] [CrossRef]
  17. Wong, N.D. Evolution of Coronary Calcium Screening for Assessment of Atherosclerotic Cardiovascular Disease Risk and Role in Preventive Cardiology. Curr. Atheroscler. Rep. 2022, 24, 949–957. [Google Scholar] [CrossRef]
  18. Lehmann, N.; Erbel, R.; Mahabadi, A.A.; Rauwolf, M.; Möhlenkamp, S.; Moebus, S.; Kälsch, H.; Budde, T.; Schmermund, A.; Stang, A.; et al. Value of Progression of Coronary Artery Calcification for Risk Prediction of Coronary and Cardiovascular Events: Result of the HNR Study (Heinz Nixdorf Recall). Circulation 2018, 137, 665–679. [Google Scholar] [CrossRef]
  19. McEvoy, J.W.; Martin, S.S.; Dardari, Z.A.; Miedema, M.D.; Sandfort, V.; Yeboah, J.; Budoff, M.J.; Goff, D.C., Jr.; Psaty, B.M.; Post, W.S.; et al. Coronary artery calcium to guide a personalized risk-based approach to initiation and intensification of antihypertensive therapy. Circulation 2017, 135, 153–165. [Google Scholar] [CrossRef]
  20. Uddin, S.M.I.; Mirbolouk, M.; Kianoush, S.; Orimoloye, O.A.; Dardari, Z.; Whelton, S.P.; Miedema, M.D.; Nasir, K.; Rumberger, J.A.; Shaw, L.J.; et al. Role of coronary artery calcium for stratifying cardiovascular risk in adults with hypertension. Hypertension 2019, 73, 983–989. [Google Scholar] [CrossRef]
  21. Spahillari, A.; Zhu, J.; Ferket, B.S.; Hunink, M.G.M.; Carr, J.J.; Terry, J.G.; Nelson, C.; Mwasongwe, S.; Mentz, R.J.; O’Brien, E.C.; et al. Cost-effectiveness of contemporary statin use guidelines with or without coronary artery calcium assessment in African American individuals. JAMA Cardiol. 2020, 5, 871–880. [Google Scholar] [CrossRef] [PubMed]
  22. Venkataraman, P.; Kawakami, H.; Huynh, Q.; Mitchell, G.; Nicholls, S.J.; Stanton, T.; Tonkin, A.; Watts, G.F.; Marwick, T.H. Cost-effectiveness of coronary artery calcium scoring in people with a family history of coronary disease. JACC Cardiovasc. Imaging 2021, 14, 1206–1217. [Google Scholar] [CrossRef] [PubMed]
  23. Lee, J.H.; Hartaigh, B.Ó.; Han, D.; Park, H.E.; Choi, S.Y.; Sung, J.; Chang, H.J. Reassessing the Usefulness of Coronary Artery Calcium Score among Varying Racial and Ethnic Groups by Geographic Locations: Relevance of the Korea Initiatives on Coronary Artery Calcification Registry. J. Cardiovasc. Ultrasound 2015, 23, 195–203. [Google Scholar] [CrossRef] [PubMed]
  24. Lee, W.; Yoon, Y.E.; Cho, S.Y.; Hwang, I.C.; Kim, S.H.; Lee, H.; Park, H.E.; Chun, E.J.; Kim, H.K.; Choi, S.Y.; et al. Sex differences in coronary artery calcium progression: The Korea Initiatives on Coronary Artery Calcification (KOICA) registry. PLoS ONE 2021, 16, e0248884. [Google Scholar] [CrossRef]
  25. Alberti, K.G.; Eckel, R.H.; Grundy, S.M.; Zimmet, P.Z.; Cleeman, J.I.; Donato, K.A.; Fruchart, J.C.; James, W.P.; Loria, C.M.; Smith, S.C., Jr.; et al. Harmonizing the metabolic syndrome. A Joint Interim Statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation 2009, 120, 1640–1645. [Google Scholar]
  26. Kim, B.Y.; Kang, S.M.; Kang, J.H.; Kang, S.Y.; Kim, K.K.; Kim, K.B.; Kim, B.; Kim, S.J.; Kim, Y.H.; Kim, J.H.; et al. 2020 Korean Society for the Study of Obesity Guidelines for the Management of Obesity in Korea. J. Obes. Metab. Syndr. 2021, 30, 81–92. [Google Scholar] [CrossRef]
  27. Kim, K.K.; Haam, J.H.; Kim, B.T.; Kim, E.M.; Park, J.H.; Rhee, S.Y.; Jeon, E.; Kang, E.; Nam, G.E.; Koo, H.Y.; et al. Evaluation and Treatment of Obesity and Its Comorbidities: 2022 Update of Clinical Practice Guidelines for Obesity by the Korean Society for the Study of Obesity. J. Obes. Metab. Syndr. 2023, 32, 1–24. [Google Scholar] [CrossRef]
  28. Shin, S.; Kim, K.J.; Chang, H.J.; Cho, I.; Kim, Y.J.; Choi, B.W.; Rhee, Y.; Lim, S.K.; Yang, W.I.; Shim, C.Y.; et al. Impact of serum calcium and phosphate on coronary atherosclerosis detected by cardiac computed tomography. Eur. Heart J. 2012, 33, 2873–2881. [Google Scholar] [CrossRef]
  29. Agatston, A.S.; Janowitz, W.R.; Hildner, F.J.; Zusmer, N.R.; Viamonte, M., Jr.; Detrano, R. Quantification of coronary artery calcium using ultrafast computed tomography. J. Am. Coll. Cardiol. 1990, 15, 827–832. [Google Scholar] [CrossRef]
  30. Hokanson, J.E.; MacKenzie, T.; Kinney, G.; Snell-Bergeon, J.K.; Dabelea, D.; Ehrlich, J.; Eckel, R.H.; Rewers, M. Evaluating changes in coronary artery calcium: An analytical approach that accounts for interscan variability. AJR Am. J. Roentgenol. 2004, 182, 1327–1332. [Google Scholar] [CrossRef]
  31. Budoff, M.J.; Hokanson, J.E.; Nasir, K.; Shaw, L.J.; Kinney, G.L.; Chow, D.; Demoss, D.; Nuguri, V.; Nabavi, V.; Ratakonda, R.; et al. Progression of coronary artery calcium predicts all-cause mortality. JACC Cardiovasc. Imaging 2010, 3, 1229–1236. [Google Scholar] [CrossRef] [PubMed]
  32. Hsueh, Y.W.; Yeh, T.L.; Lin, C.Y.; Tsai, S.Y.; Liu, S.J.; Lin, C.M.; Chen, H.H. Association of metabolically healthy obesity and elevated risk of coronary artery calcification: A systematic review and meta-analysis. PeerJ 2020, 8, e8815. [Google Scholar] [CrossRef]
  33. Lee, S.E.; Chang, H.J.; Sung, J.M.; Park, H.B.; Heo, R.; Rizvi, A.; Lin, F.Y.; Kumar, A.; Hadamitzky, M.; Kim, Y.J.; et al. Effects of statins on coronary atherosclerotic plaques: The PARADIGM study. JACC Cardiovasc. Imaging 2018, 11, 1475–1484. [Google Scholar] [CrossRef] [PubMed]
  34. Czaja-Ziółkowska, M.Z.; Wasilewski, J.; Gąsior, M.; Głowacki, J. An update on the coronary calcium score: A review for clinicians. Postep. Kardiol. Interwencyjnej. 2022, 18, 201–205. [Google Scholar] [CrossRef] [PubMed]
  35. Cho, I.; Al’Aref, S.J.; Berger, A.; Hartaigh, B.Ó.; Gransar, H.; Valenti, V.; Lin, F.Y.; Achenbach, S.; Berman, D.S.; Budoff, M.J.; et al. Prognostic value of coronary computed tomographic angiography findings in asymptomatic individuals: A 6-year follow-up from the prospective multicentre international CONFIRM study. Eur. Heart J. 2018, 39, 934–941. [Google Scholar] [CrossRef]
  36. Aljizeeri, A.; Alsaileek, A.; Al-Mallah, M.H. Coronary artery calcium score to guide hypertension therapy! Atherosclerosis 2019, 282, 162–164. [Google Scholar] [CrossRef]
  37. Hong, J.C.; Blankstein, R.; Shaw, L.J.; Padula, W.V.; Arrieta, A.; Fialkow, J.A.; Blumenthal, R.S.; Blaha, M.J.; Krumholz, H.M.; Nasir, K. Implications of coronary artery calcium testing for treatment decisions among statin candidates according to the ACC/AHA cholesterol management guidelines: A cost-effectiveness analysis. JACC Cardiovasc. Imaging 2017, 10, 938–952. [Google Scholar] [CrossRef]
  38. Halliburton, S.S.; Stillman, A.E.; Lieber, M.; Kasper, J.M.; Kuzmiak, S.A.; White, R.D. Potential clinical impact of variability in the measurement of coronary artery calcification with sequential MDCT. AJR Am. J. Roentgenol. 2005, 184, 643–648. [Google Scholar] [CrossRef]
  39. Oudkerk, M.; Stillman, A.E.; Halliburton, S.S.; Kalender, W.A.; Möhlenkamp, S.; McCollough, C.H.; Vliegenthart, R.; Shaw, L.J.; Stanford, W.; Taylor, A.J.; et al. Coronary artery calcium screening: Current status and recommendations from the European Society of Cardiac Radiology and North American Society for Cardiovascular Imaging. Eur. Radiol. 2008, 18, 2785–2807. [Google Scholar] [CrossRef]
  40. Budoff, M.J.; McClelland, R.L.; Chung, H.; Wong, N.D.; Carr, J.J.; McNitt-Gray, M.; Blumenthal, R.S.; Detrano, R.C. Reproducibility of coronary artery calcified plaque with cardiac 64-MDCT: The Multi-Ethnic Study of Atherosclerosis. AJR Am. J. Roentgenol. 2009, 192, 613–617. [Google Scholar] [CrossRef]
  41. Won, K.B.; Park, H.B.; Heo, R.; Lee, B.K.; Lin, F.Y.; Hadamitzky, M.; Kim, Y.J.; Sung, J.M.; Conte, E.; Andreini, D.; et al. Longitudinal quantitative assessment of coronary atherosclerosis related to normal systolic blood pressure maintenance in the absence of established cardiovascular disease. Clin. Cardiol. 2022, 45, 873–881. [Google Scholar] [CrossRef] [PubMed]
Jcm 12 03770 g001 550
Figure 1. Changes of CAC according to categorical BMI.
Figure 1. Changes of CAC according to categorical BMI.
Jcm 12 03770 g001
Jcm 12 03770 g002 550
Figure 2. CAC progression related to normal SBPmaintain in categorical BMI.
Figure 2. CAC progression related to normal SBPmaintain in categorical BMI.
Jcm 12 03770 g002
Table
Table 1. Baseline characteristics.
Table 1. Baseline characteristics.
CharacteristicsN = 2724
Age, year48.8 ± 7.8
Men, n (%)2122 (77.9)
SBP, mmHg110.4 ± 10.3
DBP, mmHg68.9 ± 7.9
BMI, kg/m223.4 ± 2.4
Categorical BMI, n (%)
Normal weight1204 (44.2)
Overweight860 (31.6)
Obesity660 (24.2)
Current smoking, n (%)702 (25.8)
Laboratory
Total cholesterol, mg/dL194.3 ± 31.4
Triglyceride, mg/dL90.5 ± 28.5
HDL cholesterol, mg/dL60.0 ± 16.1
LDL cholesterol, mg/dL119.6 ± 30.8
Glucose, mg/dL87.4 ± 7.1
Creatinine, mg/dL0.9 ± 0.2
Values are presented as mean ± standard deviation or as number (%). BMI: body mass index; DBP: diastolic blood pressure; HDL: high-density lipoprotein; LDL: low-density lipoprotein; SBP: systolic blood pressure.
Table
Table 2. Baseline CACS according to the categorical BMI.
Table 2. Baseline CACS according to the categorical BMI.
Normal Weight
(n = 1204)		Overweight
(n = 860)		Obesity
(n = 660)		p
CACS17.8 ± 88.716.4 ± 67.514.2 ± 54.90.596
Categorical CACS
 0929 (77.2)624 (72.6)472 (71.5)0.010
 1–100226 (18.8)195 (22.6)164 (24.9)0.005
 >10049 (4.0)41 (4.8)24 (3.6)0.532
Values are given as mean ± standard deviation or number (%). BMI: body mass index; CACS: coronary artery calcium score.
Table
Table 3. Risk of CAC progression according to the categorical BMI.
Table 3. Risk of CAC progression according to the categorical BMI.
CAC Progression
OR (95% CI)p
Model 1
 Normal weight1–
 Overweight1.29 (1.01–1.65)0.040
 Obesity1.52 (1.17–1.97)0.001
Model 2
 Normal weight1–
 Overweight1.21 (0.95–1.56)0.129
 Obesity1.42 (1.08–1.84)0.012
Model 3
 Normal weight1–
 Overweight1.14 (0.87–1.50)0.331
 Obesity1.35 (1.01–1.82)0.043
BMI: body mass index; CAC: coronary artery calcification; CACS: coronary artery calcium score; CI: confidence interval; DBP: diastolic blood pressure; HDL: high-density lipoprotein; LDL: low-density lipoprotein; OR: odds ratio; SBP: systolic blood pressure. Model 1: adjusted for age and sex. Model 2: Model 1 + adjusted for SBP, DBP, and serum levels of triglyceride, HDL and LDL cholesterol, and glucose. Model 3: Model 2 + serum creatinine levels, current smoking, baseline CACS, and interscan period.
Table
Table 4. Association between normal SBPmaintain and CAC progression according to the categorical BMI.
Table 4. Association between normal SBPmaintain and CAC progression according to the categorical BMI.
CAC Progression
Categorical BMIOR (95% CI)p
Normal weight
 Model 10.85 (0.58–1.25)0.414
 Model 20.96 (0.63–1.45)0.841
 Model 30.99 (0.63–1.55)0.957
Overweight
 Model 11.04 (0.73–1.49)0.827
 Model 21.04 (0.70–1.52)0.860
 Model 30.93 (0.61–1.42)0.731
Obesity
 Model 10.64 (0.43–0.96)0.029
 Model 20.49 (0.31–0.78)0.002
 Model 30.55 (0.33–0.91)0.020
p for interaction between categorical BMI and intensive SBP control was 0.919. BMI: body mass index; CAC: coronary artery calcification; CACS: coronary artery calcium score; CI: confidence interval; DBP: diastolic blood pressure; HDL: high-density lipoprotein; LDL: low-density lipoprotein; OR: odds ratio; SBP: systolic blood pressure. Model 1: adjusted for age and sex. Model 2: Model 1 + adjusted for SBP, DBP, and serum levels of triglyceride, HDL and LDL cholesterol, and glucose. Model 3: Model 2 + serum creatinine levels, current smoking, baseline CACS, and interscan period.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Won, K.-B.; Choi, S.-Y.; Chun, E.J.; Park, S.H.; Sung, J.; Jung, H.O.; Chang, H.-J. Assessment of Normal Systolic Blood Pressure Maintenance with the Risk of Coronary Artery Calcification Progression in Asymptomatic Metabolically Healthy Korean Adults with Normal Weight, Overweight, and Obesity. J. Clin. Med. 2023, 12, 3770. https://doi.org/10.3390/jcm12113770

AMA Style

Won K-B, Choi S-Y, Chun EJ, Park SH, Sung J, Jung HO, Chang H-J. Assessment of Normal Systolic Blood Pressure Maintenance with the Risk of Coronary Artery Calcification Progression in Asymptomatic Metabolically Healthy Korean Adults with Normal Weight, Overweight, and Obesity. Journal of Clinical Medicine. 2023; 12(11):3770. https://doi.org/10.3390/jcm12113770

Chicago/Turabian Style

Won, Ki-Bum, Su-Yeon Choi, Eun Ju Chun, Sung Hak Park, Jidong Sung, Hae Ok Jung, and Hyuk-Jae Chang. 2023. "Assessment of Normal Systolic Blood Pressure Maintenance with the Risk of Coronary Artery Calcification Progression in Asymptomatic Metabolically Healthy Korean Adults with Normal Weight, Overweight, and Obesity" Journal of Clinical Medicine 12, no. 11: 3770. https://doi.org/10.3390/jcm12113770

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop