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Original Article
 Prevalence of cardiovascular-kidney-metabolic syndrome in Korea: Korea National Health and Nutrition Examination Survey 2011-2021
Sung-Bin Hong1*orcid, Ji-Eun Kim2,3*orcid, Seung Seok Han4orcid, Joseph J. Shearer2orcid, Jungnam Joo5orcid, Ji-Yeob Choi6,7,8,9orcid, Véronique L. Roger2orcid
Epidemiol Health 2025;47:e2025005.
DOI: https://doi.org/10.4178/epih.e2025005
Published online: February 14, 2025

1Department of Biology Education, Seoul National University, Seoul, Korea

2Heart Disease Phenomics Laboratory, Epidemiology and Community Health Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA

3Institute of Health Policy and Management, Seoul National University Medical Research Center, Seoul, Korea

4Division of Nephrology, Department of Internal Medicine, Seoul National University Hospital, Seoul National University College of Medicine Seoul, Korea

5Office of Biostatistics Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA

6Department of Biomedical Sciences, Seoul National University Graduate School, Seoul, Korea

7BK21Plus Biomedical Science Project, Seoul National University College of Medicine, Seoul, Korea

8Institute of Health Policy and Management, Seoul National University Medical Research Center, Seoul, Korea

9Cancer Research Institute, Seoul National University, Seoul, Korea

Correspondence: Ji-Yeob Choi Department of Biomedical Sciences, Seoul National University Graduate School, 103 Daehak-ro, Jongno-gu, Seoul 03080, Korea E-mail: miso77@snu.ac.kr
Co-correspondence: Véronique L. Roger Heart Disease Phenomics Laboratory, Epidemiology and Community Health Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, 10 Center Drive, BG 10, Bethesda, MD 20814, USA E-mail: veronique.roger@nih.gov
*Hong & Kim contributed equally to this work as joint first authors.
• Received: October 31, 2024   • Accepted: January 23, 2025

© 2025, Korean Society of Epidemiology

This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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  • OBJECTIVES
    The American Heart Association (AHA) recently defined cardiovascular-kidney-metabolic (CKM) syndrome to better characterize the associations among cardiovascular, kidney, and metabolic diseases. Although about 9 in 10 United States adults have at least 1 risk factor for CKM syndrome, its prevalence in other populations is less understood. To fill this gap, we examined the prevalence of CKM syndrome in Korea and its association with demographic and socioeconomic status (SES).
  • METHODS
    Using data from the Korean National Health and Nutrition Examination Survey between 2011 and 2021, we calculated the prevalence of CKM syndrome across the following stages: stage 0 (no risk factors), stage 1 (excess or dysfunctional adiposity), stage 2 (other metabolic risk factors or chronic kidney disease), and stages 3-4 (subclinical/clinical cardiovascular diseases) among adults aged ≥20 years. Weighted analyses were used to estimate prevalence and 95% confidence intervals (CIs) for each CKM syndrome stage, stratified by age, gender, and SES factors.
  • RESULTS
    Among 54,994 Korean adults, the prevalence of CKM syndrome was as follows: stage 0 (25.2%; 95% CI, 24.7 to 25.8), stage 1 (19.3%; 95% CI, 18.9 to 19.7), stage 2 (51.6%; 95% CI, 51.1 to 52.2), and stages 3-4 (3.9%; 95% CI, 3.7 to 4.0). The prevalence of stages 2 and 3-4 was higher in men than in women. In addition, stages 3-4 were more prevalent among rural residents and those with lower education or income.
  • CONCLUSIONS
    About 3 out of 4 Koreans are at risk for CKM syndrome. These findings highlight that CKM syndrome is a global health problem and that interventions are urgently needed to prevent further progression.
  • Keywords: Cardiovascular diseases, Chronic kidney diseases, Metabolic syndrome, Socioeconomic status, Pandemic
Recently, the need for an integrated approach to managing cardiovascular-kidney-metabolic (CKM) syndrome has been emphasized. This study found that 74.8% of Korean adults aged 20 and older had a risk for CKM syndrome. Moreover, the prevalence is increasing, highlighting the necessity of proper management.
The American Heart Association (AHA) recommends defining cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic syndromes collectively as cardiovascular-kidney-metabolic (CKM) syndrome [1]. CKM syndrome refers to a systemic condition characterized by metabolic risk factors, CKD, and CVD, which together result in multi-organ dysfunction and an elevated risk of adverse cardiovascular events and mortality [2]. According to the Global Burden of Disease Study 2021, diseases related to CKM syndrome—including CVD—are among the leading causes of global deaths [3]. In addition, CKM syndrome can affect almost every major organ system, contributing to kidney failure and cancer, which pose significant clinical challenges [4,5]. Some studies have investigated the complex interrelationships among these conditions [6-11]. Although research on individual components of CKM syndrome and the associations between metabolic diseases and CVD has been conducted in Korea [12-17], the overall prevalence of CKM syndrome in Korea has not been examined. Therefore, understanding the progressive pathology of CKM syndrome is critical for preventing CVD morbidity and mortality, rather than focusing solely on each individual condition.
The current study aimed to investigate the prevalence and annual trends of CKM syndrome stages from 2011 to 2021 using data from the Korean National Health and Nutrition Examination Survey (KNHANES). Additionally, we examined the association between socioeconomic status (SES) and CKM syndrome, assessing changes during the coronavirus disease 2019 (COVID-19) pandemic.
Data source and study population
The KNHANES is a cross-sectional survey of nationally representative samples of the civilian, non-institutionalized Korean population, conducted by the Korea Disease Control and Prevention Agency to evaluate health and nutritional status and to track significant chronic diseases [18,19]. This study utilized KNHANES data from 2011 to 2021 to examine the prevalence and trends of CKM syndrome. Participants aged 20 years or older with complete information on CKM syndrome component variables and SES were included in the analysis.
Definition of chronic kidney disease syndrome
The 2023 AHA advisory defined CKM syndrome across 5 stages: stage 0 (no CKM risk factors), stage 1 (excess/dysfunctional adipose tissue), stage 2 (metabolic risk factors and CKD), stage 3 (subclinical CVD), and stage 4 (clinical CVD) [2]. Specific criteria for each stage, as defined by the AHA, are provided in Supplementary Material 1. Because data on subclinical CVD were not available, stages 3 and 4 were combined into a single category (stages 3-4) for analysis.
Table 1 shows the definition of CKM syndrome used in this study. Supplementary Material 2 provides the KNHANES variables and the definitions of CKM syndrome components.
Obesity was defined as a body mass index (BMI) of 25.0 kg/m2 rather than 23.0 kg/m2 as suggested by the AHA advisory for Asian populations [1]. Participants were considered to have hypertension if their systolic blood pressure was ≥ 140 mmHg, their diastolic blood pressure was ≥ 90 mmHg, if they had been diagnosed with hypertension, or if they were taking antihypertensive medications. Participants were classified as having diabetes if their fasting blood glucose level was ≥ 126 mg/dL, their glycated hemoglobin (HbA1c) was ≥ 6.5%, they had a history of diabetes diagnosis, or they were receiving treatment with diabetes-related medications or insulin. Individuals with total blood triglyceride levels ≥ 135 mg/dL were classified as having hypertriglyceridemia [19]. The estimated glomerular filtration rate (eGFR) was calculated using the Chronic Kidney Disease Epidemiology Collaboration equation (2021) [20], and CKD was reclassified using dipstick proteinuria values due to missing albuminuria data in KNHANES from 2015 to 2018 (Supplementary Material 3). Cases with an albumin-creatinine ratio (ACR) of less than 30 mg/g were replaced with “negative” or “trace” results on the dipstick test, and cases with an ACR of 30 mg/g or more were replaced with “positive” results. Individuals in the eGFR G3a category who were also positive for proteinuria presented classification challenges. To assess whether proteinuria could substitute for ACR, we calculated the kappa coefficient among participants with both ACR and dipstick proteinuria data (n= 33,915). A proteinuria result of +2 was defined as “moderate to high risk,” while a result of +3 was defined as “very high risk.” CVD was defined as a self-reported diagnosis of stroke, angina pectoris, or myocardial infarction (MI) [19].
Statistical analysis
Weighted prevalence and 95% confidence intervals (CIs) were estimated. For trend analysis, the annual percent change (APC) was calculated using Joinpoint regression version 5.1.0 (National Cancer Institute, Rockville, MD, USA). Trends were considered significant when the p-value was < 0.05.
The overall analysis of CKM syndrome was stratified by gender and assessed across SES-related variables, including residential area (urban/rural, corresponding to dong vs. eup or myeon in KNHANES), education level (middle school or lower/high school/college or higher), and household income (low/lower middle/higher middle/high). Given the close relationship between SES and age, the association between SES and CKM syndrome was further examined by stratifying by age (20-49 and ≥ 50), and the proportions and trends of CKM syndrome stages were analyzed within each age group. Changes during the pandemic were assessed by comparing data from before the pandemic (2018-2019, n= 10,976) and during the pandemic (2020-2021, n= 9,935). Statistical significance for differences between groups was determined when the 95% CIs for each CKM stage prevalence did not overlap. Additional trend analysis was conducted after excluding the pandemic period (2020-2021) to examine its influence on CKM syndrome prevalence.
Additional analyses compared the distribution of age, gender, residential area, and education level between included and excluded participants and recalculated CKM stage using a BMI threshold of 23.0 kg/m2 for obesity. Analyses were performed using Stata/SE 18.0 (StataCorp., College Station, TX, USA) and SAS version 9.4 (SAS Institute Inc., Cary, NC, USA).
Ethics statement
This study was approved by the Institutional Review Board (IRB) of Seoul National University Hospital (IRB No. E-2410-120-1578). Informed consent was waived by the IRB.
Among 86,352 participants (39,337 men and 47,015 women), we excluded individuals under 20 years old (n= 18,135), those with incomplete CKM component data (n= 12,781), and those with missing SES information (n= 442). This resulted in a final analytic sample of 54,994 adults (24,556 men and 30,438 women) (Figure 1).
The characteristics of the participants are shown in Table 2. There were no significant differences between included and excluded participants except for gender; the proportion of women was higher among those excluded (Supplementary Material 4).
Chronic kidney disease classification kappa coefficient
The kappa test for the CKD definition among individuals with both ACR and proteinuria data showed moderate agreement (0.5213 for proteinuria 2+ and 0.5232 for proteinuria 3+), supporting the use of proteinuria-based CKD classification in place of the Kidney Disease Improving Global Outcomes (KDIGO) classification (Supplementary Material 5).
The prevalence of cardiovascular-kidney-metabolic syndrome and components
Figure 2 and Table 2 display the prevalence of CKM syndrome and its components in Korean adults from 2011 to 2021. More than half of the participants were classified as CKM syndrome stage 2 (51.6%; 95% CI, 51.1 to 52.2). The prevalence of the other stages was as follows: stage 0 (25.2%; 95% CI, 24.7 to 25.8), stage 1 (19.3%; 95% CI, 18.9 to 19.7), and stages 3-4 (3.9%; 95% CI, 3.7 to 4.0). The prevalence of advanced CKM syndrome stages was higher in men (stage 2: 59.4%; 95% CI, 58.7 to 60.2; stages 3-4: 4.3%; 95% CI, 4.1 to 4.6) than in women (stage 2: 43.4%; 95% CI, 42.7 to 44.2; stages 3-4: 3.4%; 95% CI, 3.1 to 3.6). When stratified by age groups (20-49, 50-64, ≥ 65), older age groups had higher proportions of stages 3-4 and lower proportions of stage 0 (Supplementary Material 6).
With the exception of abdominal obesity, the prevalence of individual CKM syndrome components was higher in men than in women. When the overweight/obesity threshold was set at a BMI of 25.0 kg/m2, 5% of participants originally classified as stage 1 under the criteria of a BMI of 23.0 kg/m2 were reclassified as stage 0.
Trends in cardiovascular-kidney-metabolic syndrome
Figure 3 illustrates the annual trends in CKM syndrome prevalence. There was a significant increase in the proportion of stages 3-4 in the overall population (APC, 0.12; p< 0.01) and among men (APC, 0.19; p< 0.01). Additionally, a significant decrease in stage 0 was observed among men (APC, -0.52; p= 0.02). When the pandemic period was excluded (2011–2019), a significantly larger increase in the proportion of stages 3-4 was observed among all participants (APC, 3.65; p=0.01) and in men (APC, 6.28; p=0.01) (Supplementary Material 7). Supplementary Material 8 provides the annual prevalence rate of each CKM syndrome component and stage.
Socioeconomic status and cardiovascular-kidney-metabolic syndrome
The overall weighted prevalence of CKM syndrome stratified by SES is presented in Figure 4 and Supplementary Material 9. The proportion of advanced CKM syndrome stages was higher in rural areas and among individuals with lower education levels in both age groups (20-49 and ≥ 50). Household income was also associated with CKM syndrome among participants aged 50 years and older, with higher income groups exhibiting a lower proportion of advanced CKM syndrome stages. This trend was similar when the analysis was stratified by gender.
Pandemic and cardiovascular-kidney-metabolic syndrome
Figure 5 and Supplementary Material 10 present CKM syndrome prevalence and its components, stratified by gender and by pandemic period (before vs. during the pandemic). There was a significant increase in stage 1 during the pandemic, particularly among women. In addition, the prevalence of obesity, abdominal obesity, prediabetes, and diabetes increased significantly, whereas CKD prevalence decreased.
This study examined the prevalence and trends of CKM syndrome in Korea using KNHANES data from 2011 to 2021, revealing that nearly three-quarters (74.8%) of Koreans are at risk. Trend analysis uncovered a marked increase in the prevalence of advanced CKM syndrome (stages 3-4) over the decade, with men being particularly affected. This surge mirrors the growing burden of cardiovascular and metabolic diseases in Korea [13,15-17]. Notably, men exhibited more severe CKM conditions than women, a disparity likely driven by a combination of genetic factors, lifestyle choices, behavioral patterns, and differences in health perception and healthcare-seeking [21-23].
Compared with data from the National Health and Nutrition Examination Survey (NHANES), Korea had lower proportions of individuals in advanced CKM syndrome stages: stage 0 (25.2% in Korea vs. 10.6% in the USA), stage 1 (19.3 vs. 25.9%), stage 2 (51.6 vs. 49.0%), and stages 3-4 (3.9 vs. 14.6%) [24]. The lower prevalence of advanced CKM stages in Korea may reflect differences in dietary habits, lifestyle, and healthcare systems between various Asian racial groups in the United States [25] and/or between Western and Asian countries [26-28]. Although the proportion of advanced CKM syndrome was lower in Korea than in the United States, trend analysis indicates that CKM syndrome is becoming a major health issue in Korea.
SES analysis revealed more advanced CKM syndrome among individuals in rural areas and those with lower education levels and household incomes. These findings are consistent with previous research showing that lower SES is associated with higher CKM risk factors and related-mortality [29-32]. In addition, our findings align with a previous United States study demonstrating an association between adverse socioeconomic conditions and higher CKM syndrome stages [33]. This disparity highlights the need for targeted public health interventions to address social determinants of health and improve access to healthcare and preventive services among disadvantaged populations.
The potential impact of the COVID-19 pandemic on CKM syndrome was also notable. The significant increase in stage 1 prevalence during the pandemic, particularly among women, suggests that lifestyle changes—such as reduced physical activity [34,35] and increased consumption of high-calorie foods [36,37]—may have exacerbated metabolic risk factors. The marked increase in stage 1 among women might be explained by a previous study that reported a significant decline in physical activity exclusively among women during the pandemic [35]. These findings underscore the importance of maintaining healthy behaviors during times of crisis and the need for public health strategies to mitigate the adverse health impacts of pandemics. However, data from 2020 to 2021 alone are insufficient to fully explore the pandemic’s impact. Continuous monitoring is necessary to determine whether this trend will persist or return to healthier stages. Furthermore, the gender differences in CKM syndrome prevalence before and during the pandemic warrant further research. For example, nutrition survey data from KNHANES could be used to analyze gender differences in dietary habits, offering insights into the observed trends, alongside longitudinal follow-up studies to track changes.
In this study, we set the BMI threshold for overweight/obesity at 25.0 kg/m2 rather than 23.0 kg/m2 as suggested by the AHA [1]. A report from the Asian Cohort Consortium suggests that BMI levels up to 27.5 kg/m2 may not significantly affect mortality [38]. When the BMI threshold was set at 23.0 kg/m2, the prevalence of overweight and/or obesity was 58.1%—23.1% higher than when using a threshold of 25.0 kg/m2. However, the lower BMI threshold resulted in only a 5% difference between stage 0 and stage 1 of CKM syndrome, likely because the CKM syndrome staging incorporates multiple factors such as abdominal obesity and diabetes.
Several limitations of this study should be acknowledged. First, distinguishing between stage 3 and stage 4 CKM syndrome was challenging due to the lack of subclinical CVD data in KNHANES. Second, the CVD outcomes available in KNHANES were limited to MI, angina, and stroke, potentially leading to an underestimation of advanced CKM syndrome prevalence. Although NHANES data include additional information on heart failure and heart attack, the differences between the 2 CVD definitions were minimal (data not shown). Third, the absence of ACR data in KNHANES from 2015 to 2018 necessitated the use of dipstick proteinuria values for CKD classification, which may be less precise than ACR measurements. Fourth, as this study is cross-sectional, it cannot establish causal relationships among the components of CKM syndrome. Prospective cohort studies are recommended to further explore the causal relationships, interactions, and relative importance of each CKM syndrome component. Nevertheless, our study is significant in that it defines CKM syndrome in an Asian population.
Future research should focus on longitudinal studies to better understand the progression of CKM syndrome and the effectiveness of targeted interventions. Additionally, improving data collection in national health surveys to include comprehensive measures of CVD and CKD will enhance the accuracy of CKM syndrome classification and facilitate more precise public health planning.
In conclusion, CKM syndrome represents a growing public health challenge in Korea with significant implications. This study provides guidance for developing policies aimed at reducing the burden of CKM syndrome by considering the interplay among cardiovascular, kidney, and metabolic diseases and socioeconomic factors.
Supplementary materials are available at https://doi.org/10.4178/epih.e2025005.

Supplementary Material 1.

Definition of CKM syndrome in AHA advisory
epih-47-e2025005-Supplementary-1.docx

Supplementary Material 2.

Definition of diseases components for CKM syndrome in KNHANES
epih-47-e2025005-Supplementary-2.docx

Supplementary Material 3.

CKD classification with proteinuria
epih-47-e2025005-Supplementary-3.docx

Supplementary Material 4.

Sensitive analysis between participants who were included and excluded
epih-47-e2025005-Supplementary-4.docx

Supplementary Material 5.

CKD classification using ACR and dipstick proteinuria test
epih-47-e2025005-Supplementary-5.docx

Supplementary Material 6.

Proportion of CKM syndrome stage strtified with age group and sex.
epih-47-e2025005-Supplementary-6.xlsx

Supplementary Material 7.

Trends in the prevalence of CKM syndrome in (A) all participants, (B) men, and (C) women from 2011 to 2019.
epih-47-e2025005-Supplementary-7.docx

Supplementary Material 8.

Characteristics of participants by year.
epih-47-e2025005-Supplementary-8.xlsx

Supplementary Material 9.

Socioeconomic status and prevalence of CKM syndrome stratified with before 50yr and after 50yr.
epih-47-e2025005-Supplementary-9.xlsx

Supplementary Material 10.

Comparison of each component of CKM syndrome and CKM syndrome stage before and during pandemic.
epih-47-e2025005-Supplementary-10.xlsx

Data availability

Approval of the KNHANES data is available through https://knhanes.kdca.go.kr/knhanes/postSendPage.do?url=/rawDataDwnld/rawDataDwnld.do&postparam=%7B%22menuId%22:%2210031001%22%7D. Korea Disease Control and Prevention Agency (KDCA) permits access to all of these data via download for any researcher who promises to follow the research ethics.

Conflict of interest

The authors have no conflicts of interest to declare for this study.

Funding

This research was supported by the National Heart Lung and Blood Institute of the National Institutes of Health (NIH), the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), the Ministry of Health & Welfare, Republic of Korea (RS2023-00273555) and the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2022R1A2B5 B01002471 and RS-2025-00556168).

Acknowledgements

The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Author contributions

Conceptualization: Roger VL, Choi JY. Data curation: Hong SB. Formal analysis: Hong SB, Kim JE. Funding acquisition: Roger VL, Choi JY. Methodology: Kim JE, Han SS, Shearer JJ, Joo J, Roger VL, Choi JY. Project administration: Roger VL, Choi JY. Visualization: Hong SB. Writing – original draft: Hong SB, Kim JE.Writing – review & editing: Hong SB, Kim JE, Han SS, Shearer JJ, Joo J, Roger VL, Choi JY.

Figure 1.
Flowchart of participation selection. KNHANES, Korean National Health and Nutrition Examination Survey; CKM, cardiovascular-kidney-metabolic; SES, socioeconomic status.
epih-47-e2025005f1.jpg
Figure 2.
Cardiovascular-kidney-metabolic (CKM) syndrome and component prevalence stratified by gender. CKM syndrome stages in (A) all participants, (B) men, and (C) women. Each component of CKM syndrome in (D) all participants, (E) men, and (F) women. CKD, chronic kidney disease; CVD, cardiovascular disease.
epih-47-e2025005f2.jpg
Figure 3.
Trends in the prevalence of cardiovascular-kidney-metabolic (CKM) syndrome in (A) all participants, (B) men, and (C) women.
epih-47-e2025005f3.jpg
Figure 4.
Socioeconomic status and prevalence of cardiovascular-kidney-metabolic (CKM) syndrome stratified by age group (before 50 years and after 50 years) by (A) residential area, (B) education level, and (C) household income. *p<0.05.
epih-47-e2025005f4.jpg
Figure 5.
Comparison of overall cardiovascular-kidney-metabolic (CKM) syndrome prevalence before and during the pandemic in (A) all participants, (B) men, and (C) women. Prevalence of each CKM syndrome component in (D) all participants, (E) men, and (F) women. CKD, chronic kidney disease; CVD, cardiovascular disease. *p<0.05.
epih-47-e2025005f5.jpg
epih-47-e2025005f6.jpg
Table 1.
Definition of CKM syndrome in this study
CKM syndrome stage Definition
Stage 0 Normal BMI, WC, normoglycemia, normotension, normal lipid profile, no evidence of CKD, no subclinical and clinical CVD
 No CKM risk factors
Stage 1 BMI≥25.0 kg/m2 OR
 Excess/dysfunctional adipose tissue  WC≥80/90 cm in women/men OR
 Prediabetes (FG: 100-125 mg/dL or HbA1c: 5.7-6.4%)
Stage 2 Hypertriglyceridemia (TG≥135 mg/dL) OR
 Metabolic risk factors and CKD  Hypertension (SBP≥140 mmHg or DBP≥90 mmHg or self-reported diagnosis of hypertension or taking medicine) OR
 MetS1≥3 OR
 Diabetes (FG≥126 mg/dL or HbA1c≥6.5% or self-reported diagnosis of diabetes or taking medication or insulin) OR
 CKD (moderate to high risk)
Stage 3-4 Very high-risk CKD OR
 Subclinical or clinical CVD in CKM syndrome  Clinical CVD (stroke, angina pectoris, myocardial infraction)

CKM, cardiovascular-kidney-metabolic; CKD, chronic kidney disease; CVD, cardiovascular disease; BMI, body mass index; WC, waist circumference; FG, fasting blood glucose; HbA1c, glycated hemoglobin; TG, total triglyceride; SBP, systolic blood pressure; DBP, diastolic blood pressure; MetS, metabolic syndrome.

1 MetS: (1) WC≥80/90 cm in women/men, (2) high-density lipoprotein cholesterol<40/50 mg/dL in men/women, (3) TG≥150 mg/dL, (4) blood pressure≥130/80 mmHg, or taking medication, (5) FG≥100 mm/dL.

Table 2.
Characteristics of participants included in the analysis
Characteristics Total (n=54,994, 100%)
 Men (n=24,556, 51.2%)
 Women (n=30,438, 48.8%)
Unweighted (n) Weighted % (95% CI) Unweighted (n) Weighted % (95% CI) Unweighted (n) Weighted % (95% CI)
Age (yr)
 20-29 6,055 16.8 (16.3, 17.4) 2,987 18.5 (17.8, 19.3) 3,068 15.1 (14.5, 15.6)
 30-39 8,525 18.4 (17.9, 19.0) 3,877 19.5 (18.8, 20.3) 4,648 17.3 (16.7, 18.0)
 40-49 10,017 20.9 (20.3, 21.4) 4,481 21.3 (20.6, 22.0) 5,536 20.4 (19.8, 21.0)
 50-59 11,118 20.6 (20.1, 21.1) 4,680 19.9 (19.3, 20.5) 6,438 21.3 (20.7, 21.9)
 60-69 10,301 13.3 (13.0, 13.7) 4,586 12.7 (12.2, 13.1) 5,715 14.1 (13.6, 14.5)
 70-79 7,261 7.9 (7.6, 8.2) 3,239 6.6 (6.3, 7.0) 4,022 9.2 (8.9, 9.6)
 80-89 1,717 2.0 (1.9, 2.1) 706 1.4 (1.3, 1.6) 1,011 2.6 (2.4, 2.8)
Area of residence
 Dong 44,654 83.7 (82.1, 85.1) 19,773 83.3 (81.7, 84.8) 24,881 84.1 (82.6, 85.5)
 Eup/Myeon 10,782 16.3 (14.9, 17.9) 4,964 16.7 (15.2, 18.3) 5,818 15.9 (14.5, 17.4)
Type of house
 General 26,603 49.2 (48.4, 50.0) 12,016 49.6 (48.6, 50.5) 14,587 48.8 (47.9, 49.7)
 Apartment 28,833 50.8 (50.0, 51.6) 12,721 50.4 (49.5, 51.4) 16,112 51.2 (50.3, 52.1)
Individual income
 Low 13,229 24.5 (23.9, 25.2) 5,885 24.5 (23.7, 25.3) 7,344 24.6 (23.8, 25.3)
 Lower middle 13,886 25.3 (24.7, 25.9) 6,197 25.4 (24.6, 26.2) 7,689 25.2 (24.6, 25.9)
 Higher middle 13,954 25.2 (24.6, 25.8) 6,228 25.2 (24.5, 25.9) 7,726 25.1 (24.5, 25.8)
 High 14,118 25.0 (24.2, 25.8) 6,318 24.9 (24.0, 25.8) 7,800 25.0 (24.2, 25.9)
Household income
 Low 10,164 14.4 (13.9, 15.0) 4,004 12.3 (11.7, 12.9) 6,160 16.6 (15.9, 17.3)
 Lower middle 13,676 24.2 (23.6, 24.9) 6,034 23.6 (22.9, 24.4) 7,642 24.8 (24.1, 25.6)
 Higher middle 15,153 29.6 (29.0, 30.3) 6,968 30.6 (29.8, 31.4) 8,185 28.7 (27.9, 29.4)
 High 16,194 31.7 (30.8, 32.7) 7,622 33.5 (32.5, 34.5) 8,572 29.9 (28.9, 30.9)
Education level
 Middle school or lower 17,575 23.7 (23.0, 24.3) 6,169 17.8 (17.1, 18.4) 11,406 29.9 (29.0, 30.7)
 High school 18,111 36.5 (35.9, 37.1) 8,720 38.8 (38.0, 39.6) 9,391 34.1 (33.3, 34.8)
 College or higher 19,549 39.8 (39.0, 40.7) 9,774 43.4 (42.5, 44.4) 9,775 36.1 (35.2, 37.0)
BMI (kg/m2)
 Underweight (<18.5) 2,055 4.0 (3.8, 4.2) 531 2.4 (2.2, 2.7) 1,464 5.7 (5.3, 6.0)
 Normal (18.5-22.9) 33,861 61.0 (60.5, 61.5) 14,148 56.6 (55.8, 57.3) 19,713 65.6 (64.9, 66.2)
 Overweight/obesity (≥23.0) 19,078 35.0 (34.5, 35.5) 3,817 41.0 (40.2, 41.7) 9,261 28.7 (28.1, 29.4)
BMI (Asia criteria) (kg/m2)
 Underweight (<18.5) 2,055 4 (3.8, 4.2) 591 2.4 (2.2, 2.7) 1,464 5.7 (5.3, 6.0)
 Normal (18.5-24.9) 20,875 37.9 (37.4, 38.4) 7,691 30.8 (30.1, 31.5) 13,184 45.4 (44.7, 46.1)
 Overweight/obesity (≥25.0) 32,064 58.1 (57.6, 58.6) 16,274 66.8 (66.1, 67.5) 15,790 48.9 (48.2, 49.7)
WC (women/men) (cm)
 Normal (<80/90) 32,684 62.6 (62.0, 63.2) 16,309 67.3 (66.6, 68.1) 16,375 57.6 (56.8, 58.4)
 Abdominal obesity (≥80/90) 22,310 37.4 (36.8, 38.0) 8,247 32.7 (31.9, 33.4) 14,063 42.4 (41.6, 43.2)
Glycemic status
 Normoglycemia 25,039 50.7 (50.1, 51.3) 10,176 47.4 (46.5, 48.2) 14,863 54.2 (53.4, 54.9)
 Prediabetes 22,046 37.4 (36.9, 38.0) 10,321 39.5 (38.7, 40.3) 11,725 35.3 (34.6, 35.9)
 Diabetes 7,909 11.9 (11.5, 12.2) 4,059 13.1 (12.7, 13.6) 3,850 10.6 (10.2, 11.0)
Hypertension
 No 36,724 72.2 (71.6, 72.7) 15,618 69.6 (68.9, 70.3) 21,106 74.9 (74.2, 75.5)
 Yes 18,270 27.8 (27.3, 28.4) 8,938 30.4 (29.7, 31.1) 9,332 25.1 (24.5, 25.8)
Hypertriglyceridemia
 No 35,674 64.5 (64.0, 65.0) 13,685 55.2 (54.4, 55.9) 21,989 74.3 (73.7, 74.9)
 Yes 19,320 35.5 (35.0, 36.0) 10,871 44.8 (44.1, 45.6) 8,449 25.7 (25.1, 26.3)
Metabolic syndrome
 No (<3) 36,160 68.9 (68.4, 69.4) 15,707 66.3 (65.6, 67.0) 20,453 71.6 (70.9, 72.2)
 Yes (≥3) 18,834 31.1 (30.6, 31.6) 8,849 33.7 (33.0, 34.4) 9,985 28.4 (27.8, 29.1)
CKD (with ACR)1
 Low risk 30,639 92.1 (91.7, 92.4) 13,663 92.4 (91.8, 92.8) 16,976 91.8 (91.3, 92.3)
 Moderate to high risk 3,082 7.5 (7.1, 7.9) 1,440 7.2 (6.8, 7.7) 1,642 7.8 (7.3, 8.3)
 Very high risk 194 0.4 (0.4, 0.5) 106 0.4 (0.3, 0.5) 88 0.4 (0.3, 0.6)
CKD (with Upro 1+)2
 Low risk 52,606 96.5 (96.3, 96.7) 23,195 96 (95.7, 96.2) 29,411 97 (96.8, 97.2)
 Moderate to high risk 2,203 3.3 (3.1, 3.4) 1,257 3.7 (3.5, 4.0) 946 2.8 (2.6, 3.0)
 Very high risk 185 0.3 (0.2, 0.3) 104 0.3 (0.2, 0.4) 81 0.2 (0.2, 0.3)
CKD (with Upro 2++)3
 Low risk 52,606 96.5 (96.3, 96.7) 23,195 96 (95.7, 96.2) 29,411 97 (96.8, 97.2)
 Moderate to high risk 2,110 3.1 (3.0, 3.3) 1,193 3.5 (3.3, 3.8) 917 2.7 (2.5, 2.9)
 Very high risk 278 0.4 (0.3, 0.4) 168 0.5 (0.4, 0.6) 110 0.3 (0.2, 0.4)
Self-reported CVD
 No 52,319 96.5 (96.3, 96.6) 23,097 96 (95.8, 96.3) 29,222 96.9 (96.7, 97.1)
 Yes 2,675 3.5 (3.4, 3.7) 1,459 4 (3.7, 4.2) 1,216 3.1 (2.9, 3.3)
CKM syndrome
 Stage 0 12,014 25.2 (24.7, 25.8) 3,904 19.4 (18.7, 20.0) 8,110 31.4 (30.7, 32.1)
 Stage 1 10,309 19.3 (18.9, 19.7) 3,899 16.9 (16.3, 17.5) 6,410 21.8 (21.2, 22.4)
 Stage 2 29,771 51.6 (51.1, 52.2) 15,160 59.4 (58.7, 60.2) 14,611 43.4 (42.7, 44.2)
 Stage 3-4 2,900 3.9 (3.7, 4.0) 1,593 4.3 (4.1, 4.6) 1,307 3.4 (3.1, 3.6)
CKM syndrome (Asian BMI)
 Stage 0 9,755 20.2 (19.7, 20.7) 2,682 13.2 (12.7, 13.8) 7,073 27.5 (26.8, 28.2)
 Stage 1 12,568 24.3 (23.9, 24.8) 5,121 23 (22.4, 23.7) 7,447 25.7 (25.1, 26.3)
 Stage 2 29,771 51.6 (51.1, 52.2) 51,160 59.4 (58.7, 60.2) 14,611 43.4 (42.7, 44.2)
 Stage 3-4 2,900 3.9 (3.7, 4.0) 1,593 4.3 (4.1, 4.6) 1,307 3.4 (3.1, 3.6)

CI, confidence interval; BMI, body mass index; WC, waist circumstance; CKD, chronic kidney disease; CVD, cardiovascular disease; CKM, cardiovascular-kidney-metabolic; eGFR, estimated glomerular filtration rate; ACR, albumin-to-creatinine ratio.

1 2015-2018 data excluded (total: 33,195, men: 15,209, women: 18,706).

2 Upro1+: individuals with an eGFR category of G3a who were positive for proteinuria were defined as “moderate to high risk.”

3 Upro2++: individuals with an eGFR category of G3a who were positive for proteinuria were defined as “very high risk.”

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      Prevalence of cardiovascular-kidney-metabolic syndrome in Korea: Korea National Health and Nutrition Examination Survey 2011-2021
      Image Image Image Image Image Image
      Figure 1. Flowchart of participation selection. KNHANES, Korean National Health and Nutrition Examination Survey; CKM, cardiovascular-kidney-metabolic; SES, socioeconomic status.
      Figure 2. Cardiovascular-kidney-metabolic (CKM) syndrome and component prevalence stratified by gender. CKM syndrome stages in (A) all participants, (B) men, and (C) women. Each component of CKM syndrome in (D) all participants, (E) men, and (F) women. CKD, chronic kidney disease; CVD, cardiovascular disease.
      Figure 3. Trends in the prevalence of cardiovascular-kidney-metabolic (CKM) syndrome in (A) all participants, (B) men, and (C) women.
      Figure 4. Socioeconomic status and prevalence of cardiovascular-kidney-metabolic (CKM) syndrome stratified by age group (before 50 years and after 50 years) by (A) residential area, (B) education level, and (C) household income. *p<0.05.
      Figure 5. Comparison of overall cardiovascular-kidney-metabolic (CKM) syndrome prevalence before and during the pandemic in (A) all participants, (B) men, and (C) women. Prevalence of each CKM syndrome component in (D) all participants, (E) men, and (F) women. CKD, chronic kidney disease; CVD, cardiovascular disease. *p<0.05.
      Graphical abstract

      Figure 1.

      Figure 2.

      Figure 3.

      Figure 4.

      Figure 5.

      Graphical abstract

      Prevalence of cardiovascular-kidney-metabolic syndrome in Korea: Korea National Health and Nutrition Examination Survey 2011-2021
      CKM syndrome stage Definition
      Stage 0 Normal BMI, WC, normoglycemia, normotension, normal lipid profile, no evidence of CKD, no subclinical and clinical CVD
       No CKM risk factors
      Stage 1 BMI≥25.0 kg/m2 OR
       Excess/dysfunctional adipose tissue  WC≥80/90 cm in women/men OR
       Prediabetes (FG: 100-125 mg/dL or HbA1c: 5.7-6.4%)
      Stage 2 Hypertriglyceridemia (TG≥135 mg/dL) OR
       Metabolic risk factors and CKD  Hypertension (SBP≥140 mmHg or DBP≥90 mmHg or self-reported diagnosis of hypertension or taking medicine) OR
       MetS1≥3 OR
       Diabetes (FG≥126 mg/dL or HbA1c≥6.5% or self-reported diagnosis of diabetes or taking medication or insulin) OR
       CKD (moderate to high risk)
      Stage 3-4 Very high-risk CKD OR
       Subclinical or clinical CVD in CKM syndrome  Clinical CVD (stroke, angina pectoris, myocardial infraction)
      Characteristics Total (n=54,994, 100%)
      		 Men (n=24,556, 51.2%)
      		 Women (n=30,438, 48.8%)
      Unweighted (n) Weighted % (95% CI) Unweighted (n) Weighted % (95% CI) Unweighted (n) Weighted % (95% CI)
      Age (yr)
       20-29 6,055 16.8 (16.3, 17.4) 2,987 18.5 (17.8, 19.3) 3,068 15.1 (14.5, 15.6)
       30-39 8,525 18.4 (17.9, 19.0) 3,877 19.5 (18.8, 20.3) 4,648 17.3 (16.7, 18.0)
       40-49 10,017 20.9 (20.3, 21.4) 4,481 21.3 (20.6, 22.0) 5,536 20.4 (19.8, 21.0)
       50-59 11,118 20.6 (20.1, 21.1) 4,680 19.9 (19.3, 20.5) 6,438 21.3 (20.7, 21.9)
       60-69 10,301 13.3 (13.0, 13.7) 4,586 12.7 (12.2, 13.1) 5,715 14.1 (13.6, 14.5)
       70-79 7,261 7.9 (7.6, 8.2) 3,239 6.6 (6.3, 7.0) 4,022 9.2 (8.9, 9.6)
       80-89 1,717 2.0 (1.9, 2.1) 706 1.4 (1.3, 1.6) 1,011 2.6 (2.4, 2.8)
      Area of residence
       Dong 44,654 83.7 (82.1, 85.1) 19,773 83.3 (81.7, 84.8) 24,881 84.1 (82.6, 85.5)
       Eup/Myeon 10,782 16.3 (14.9, 17.9) 4,964 16.7 (15.2, 18.3) 5,818 15.9 (14.5, 17.4)
      Type of house
       General 26,603 49.2 (48.4, 50.0) 12,016 49.6 (48.6, 50.5) 14,587 48.8 (47.9, 49.7)
       Apartment 28,833 50.8 (50.0, 51.6) 12,721 50.4 (49.5, 51.4) 16,112 51.2 (50.3, 52.1)
      Individual income
       Low 13,229 24.5 (23.9, 25.2) 5,885 24.5 (23.7, 25.3) 7,344 24.6 (23.8, 25.3)
       Lower middle 13,886 25.3 (24.7, 25.9) 6,197 25.4 (24.6, 26.2) 7,689 25.2 (24.6, 25.9)
       Higher middle 13,954 25.2 (24.6, 25.8) 6,228 25.2 (24.5, 25.9) 7,726 25.1 (24.5, 25.8)
       High 14,118 25.0 (24.2, 25.8) 6,318 24.9 (24.0, 25.8) 7,800 25.0 (24.2, 25.9)
      Household income
       Low 10,164 14.4 (13.9, 15.0) 4,004 12.3 (11.7, 12.9) 6,160 16.6 (15.9, 17.3)
       Lower middle 13,676 24.2 (23.6, 24.9) 6,034 23.6 (22.9, 24.4) 7,642 24.8 (24.1, 25.6)
       Higher middle 15,153 29.6 (29.0, 30.3) 6,968 30.6 (29.8, 31.4) 8,185 28.7 (27.9, 29.4)
       High 16,194 31.7 (30.8, 32.7) 7,622 33.5 (32.5, 34.5) 8,572 29.9 (28.9, 30.9)
      Education level
       Middle school or lower 17,575 23.7 (23.0, 24.3) 6,169 17.8 (17.1, 18.4) 11,406 29.9 (29.0, 30.7)
       High school 18,111 36.5 (35.9, 37.1) 8,720 38.8 (38.0, 39.6) 9,391 34.1 (33.3, 34.8)
       College or higher 19,549 39.8 (39.0, 40.7) 9,774 43.4 (42.5, 44.4) 9,775 36.1 (35.2, 37.0)
      BMI (kg/m2)
       Underweight (<18.5) 2,055 4.0 (3.8, 4.2) 531 2.4 (2.2, 2.7) 1,464 5.7 (5.3, 6.0)
       Normal (18.5-22.9) 33,861 61.0 (60.5, 61.5) 14,148 56.6 (55.8, 57.3) 19,713 65.6 (64.9, 66.2)
       Overweight/obesity (≥23.0) 19,078 35.0 (34.5, 35.5) 3,817 41.0 (40.2, 41.7) 9,261 28.7 (28.1, 29.4)
      BMI (Asia criteria) (kg/m2)
       Underweight (<18.5) 2,055 4 (3.8, 4.2) 591 2.4 (2.2, 2.7) 1,464 5.7 (5.3, 6.0)
       Normal (18.5-24.9) 20,875 37.9 (37.4, 38.4) 7,691 30.8 (30.1, 31.5) 13,184 45.4 (44.7, 46.1)
       Overweight/obesity (≥25.0) 32,064 58.1 (57.6, 58.6) 16,274 66.8 (66.1, 67.5) 15,790 48.9 (48.2, 49.7)
      WC (women/men) (cm)
       Normal (<80/90) 32,684 62.6 (62.0, 63.2) 16,309 67.3 (66.6, 68.1) 16,375 57.6 (56.8, 58.4)
       Abdominal obesity (≥80/90) 22,310 37.4 (36.8, 38.0) 8,247 32.7 (31.9, 33.4) 14,063 42.4 (41.6, 43.2)
      Glycemic status
       Normoglycemia 25,039 50.7 (50.1, 51.3) 10,176 47.4 (46.5, 48.2) 14,863 54.2 (53.4, 54.9)
       Prediabetes 22,046 37.4 (36.9, 38.0) 10,321 39.5 (38.7, 40.3) 11,725 35.3 (34.6, 35.9)
       Diabetes 7,909 11.9 (11.5, 12.2) 4,059 13.1 (12.7, 13.6) 3,850 10.6 (10.2, 11.0)
      Hypertension
       No 36,724 72.2 (71.6, 72.7) 15,618 69.6 (68.9, 70.3) 21,106 74.9 (74.2, 75.5)
       Yes 18,270 27.8 (27.3, 28.4) 8,938 30.4 (29.7, 31.1) 9,332 25.1 (24.5, 25.8)
      Hypertriglyceridemia
       No 35,674 64.5 (64.0, 65.0) 13,685 55.2 (54.4, 55.9) 21,989 74.3 (73.7, 74.9)
       Yes 19,320 35.5 (35.0, 36.0) 10,871 44.8 (44.1, 45.6) 8,449 25.7 (25.1, 26.3)
      Metabolic syndrome
       No (<3) 36,160 68.9 (68.4, 69.4) 15,707 66.3 (65.6, 67.0) 20,453 71.6 (70.9, 72.2)
       Yes (≥3) 18,834 31.1 (30.6, 31.6) 8,849 33.7 (33.0, 34.4) 9,985 28.4 (27.8, 29.1)
      CKD (with ACR)1
       Low risk 30,639 92.1 (91.7, 92.4) 13,663 92.4 (91.8, 92.8) 16,976 91.8 (91.3, 92.3)
       Moderate to high risk 3,082 7.5 (7.1, 7.9) 1,440 7.2 (6.8, 7.7) 1,642 7.8 (7.3, 8.3)
       Very high risk 194 0.4 (0.4, 0.5) 106 0.4 (0.3, 0.5) 88 0.4 (0.3, 0.6)
      CKD (with Upro 1+)2
       Low risk 52,606 96.5 (96.3, 96.7) 23,195 96 (95.7, 96.2) 29,411 97 (96.8, 97.2)
       Moderate to high risk 2,203 3.3 (3.1, 3.4) 1,257 3.7 (3.5, 4.0) 946 2.8 (2.6, 3.0)
       Very high risk 185 0.3 (0.2, 0.3) 104 0.3 (0.2, 0.4) 81 0.2 (0.2, 0.3)
      CKD (with Upro 2++)3
       Low risk 52,606 96.5 (96.3, 96.7) 23,195 96 (95.7, 96.2) 29,411 97 (96.8, 97.2)
       Moderate to high risk 2,110 3.1 (3.0, 3.3) 1,193 3.5 (3.3, 3.8) 917 2.7 (2.5, 2.9)
       Very high risk 278 0.4 (0.3, 0.4) 168 0.5 (0.4, 0.6) 110 0.3 (0.2, 0.4)
      Self-reported CVD
       No 52,319 96.5 (96.3, 96.6) 23,097 96 (95.8, 96.3) 29,222 96.9 (96.7, 97.1)
       Yes 2,675 3.5 (3.4, 3.7) 1,459 4 (3.7, 4.2) 1,216 3.1 (2.9, 3.3)
      CKM syndrome
       Stage 0 12,014 25.2 (24.7, 25.8) 3,904 19.4 (18.7, 20.0) 8,110 31.4 (30.7, 32.1)
       Stage 1 10,309 19.3 (18.9, 19.7) 3,899 16.9 (16.3, 17.5) 6,410 21.8 (21.2, 22.4)
       Stage 2 29,771 51.6 (51.1, 52.2) 15,160 59.4 (58.7, 60.2) 14,611 43.4 (42.7, 44.2)
       Stage 3-4 2,900 3.9 (3.7, 4.0) 1,593 4.3 (4.1, 4.6) 1,307 3.4 (3.1, 3.6)
      CKM syndrome (Asian BMI)
       Stage 0 9,755 20.2 (19.7, 20.7) 2,682 13.2 (12.7, 13.8) 7,073 27.5 (26.8, 28.2)
       Stage 1 12,568 24.3 (23.9, 24.8) 5,121 23 (22.4, 23.7) 7,447 25.7 (25.1, 26.3)
       Stage 2 29,771 51.6 (51.1, 52.2) 51,160 59.4 (58.7, 60.2) 14,611 43.4 (42.7, 44.2)
       Stage 3-4 2,900 3.9 (3.7, 4.0) 1,593 4.3 (4.1, 4.6) 1,307 3.4 (3.1, 3.6)
      Table 1. Definition of CKM syndrome in this study

      CKM, cardiovascular-kidney-metabolic; CKD, chronic kidney disease; CVD, cardiovascular disease; BMI, body mass index; WC, waist circumference; FG, fasting blood glucose; HbA1c, glycated hemoglobin; TG, total triglyceride; SBP, systolic blood pressure; DBP, diastolic blood pressure; MetS, metabolic syndrome.

      MetS: (1) WC≥80/90 cm in women/men, (2) high-density lipoprotein cholesterol<40/50 mg/dL in men/women, (3) TG≥150 mg/dL, (4) blood pressure≥130/80 mmHg, or taking medication, (5) FG≥100 mm/dL.

      Table 2. Characteristics of participants included in the analysis

      CI, confidence interval; BMI, body mass index; WC, waist circumstance; CKD, chronic kidney disease; CVD, cardiovascular disease; CKM, cardiovascular-kidney-metabolic; eGFR, estimated glomerular filtration rate; ACR, albumin-to-creatinine ratio.

      2015-2018 data excluded (total: 33,195, men: 15,209, women: 18,706).

      Upro1+: individuals with an eGFR category of G3a who were positive for proteinuria were defined as “moderate to high risk.”

      Upro2++: individuals with an eGFR category of G3a who were positive for proteinuria were defined as “very high risk.”

      Table 1.

      Table 2.

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