Prevalences and Risk Factors of Electrocardiographic Abnormalities in Chinese Adults: a cross-sectional study

Abstract

Background: Electrocardiogram (ECG) is widely used to screen cardiac diseases. To date, no large population study has provided estimates of the prevalences of ECG findings in China. We aim to investigate the prevalences and risk factors of ECG abnormalities in the general population of Chinese adults.

Methods: ECG data were obtained from 34965 participants in the 2007-2008 China National Diabetes and Metabolic Disorders Study. ECG abnormalities were classified according to the Minnesota coding (MC) criteria. Prevalences of variant ECG abnormalities were calculated. The associations between ECG abnormalities and gender, age and other risk factors for cardiovascular diseases (CVD) were analyzed by multivariate logistic regression test.

Results: The prevalences of major arrhythmias were 1.70%, 2.37% and 1.04% in the whole population, men and women, respectively. Atrial fibrillation/flutter was found in 0.35% of men and 0.20% of women. ST depression and T abnormalities accounted for 10.96%, 7.54% and 14.32% in the whole population, men and women, respectively. Independent of gender and other CVD risk factors, the older age significantly increased the risk of having atrial fibrillation/flutter, complete left bundle branch block, complete right bundle branch block, sinus tachycardia, atrial/junctional/ventricular premature beats, ST depression and T abnormalities, tall R wave left, left/right atrial hypertrophy, left axis deviation and low voltage. Hypertension, overweight, obesity and hypercholesterolemia all independently increased the odds ratios of having ST depression and T abnormalities. History of cardiovascular/cerebrovascular diseases was positively associated with major arrhythmias, ST depression and T abnormalities and tall R wave left.

Conclusions: This study provides estimates of the prevalences of ECG findings in a large population of Chinese adults. Gender, age, CVD risk factors and history of cardiovascular/cerebrovascular diseases had important impact on ECG abnormalities.

^# Liping Yu and Xiaojun Ye contributed equally to this work.

Background

The electrocardiogram (ECG) is an inexpensive and convenient tool which has been widely used to screen arrhythmias and cardiovascular diseases (CVDs). The prevalences of variant ECG abnormalities and their association with age and CVD risk factors have been reported in several large population studies conducted in North American, South American and European countries [1–3]. The prevalence of major ECG abnormalities has been reported to vary from 6.0–11.3% in men and from 4.3–12.9% in women in previous studies, with differences dependent on various racial backgrounds and targeted age groups [1–4]. Older age has been positively associated with the prevalences of major ECG abnormalities and several specific ECG findings [2, 3, 5]. A previous cross-sectional survey reported that arrhythmias accounted for 4.8% in men and 3.6% in women from 65 to 74 years old, while the prevalences of arrhythmias were less than 0.5% in both men and women under 45 years old [1]. Other CVD risk factors, such as hypertension and diabetes, increased the risk of having major ECG abnormalities and some specific ECG findings as well [1, 2].

Up to now, no large population study has provided estimates of the prevalences of ECG findings in different age groups in China. Most previous ECG studies performed in China were regional or focused on specific types of ECG findings [6, 7]. The ECG data presented in this study were obtained from 34965 participants in the China National Diabetes and Metabolic Disorders Study from June 2007 to May 2008. The objective of the present study was to investigate the prevalences of ECG findings in the general population of Chinese adults and determine the associations between ECG abnormalities and age, gender and other CVD risk factors.

Methods

Study-outcome Definitions

The design and methods of the China National Diabetes and Metabolic Disorders Study were reported previously [8, 9]. Briefly speaking, interviews and fulfill of standard questionnaires were conducted to obtain the information about demographical characteristics, lifestyle risk factors, personal medical history, treatment of diseases and family disease history. Fasting blood samples were collected from the participants to test liver function, renal function and lipid levels. ECGs and measurements of blood pressure, waist circumference, height and weight were conducted for participants after an overnight fast by well-trained clinical staffs. Participants then received a standard oral glucose tolerance test. Diabetes mellitus was defined as fasting plasma glucose ≥ 7.00 mmol/L, 2-hour plasma glucose ≥ 11.10 mmol/L or using glucose-lowering medications with a history of diabetes. Prediabetes was defined as fasting plasma glucose 6.10–6.99 mmol/L or 2-hour plasma glucose 7.80-11.09 mmol/L without any evidence of diagnosis of diabetes. Hypercholesterolemia was defined as total cholesterol ≥ 6.22 mmol/L, LDL cholesterol ≥ 4.14 mmol/L or using cholesterol-lowering medications with a history of hypercholesterolemia. Hypertension was defined as systolic blood pressure ≥ 140 mmHg, diastolic blood pressure ≥ 90 mmHg or using hypotensive medications with a history of hypertension. Obese was defined as BMI ≥ 28 kg/m^2, while overweight was defined as BMI 24-27.9 kg/m^2 according to the criteria adopted by the Chinese Society of Endocrinology. The definition of smoking history was having smoked at least 100 cigarettes in the past.

Twelve-lead ECGs were conducted with the subject in the supine position. ECGs were read and recorded by two trained physicians in each subcenter. ECG data were classified based on the Minnesota coding (MC) criteria [1, 2, 5]. Major arrhythmias included atrial fibrillation or flutter (MC 8 − 3), complete left bundle branch block (LBBB, MC 7 − 1), complete right bundle branch block (RBBB, MC 7 − 2), nonspecific intraventricular conduction delay (IVCD, MC 7 − 4), Mobitz Type II or III atrial-ventricular (AV) conduction defects (MC 6 − 1, 6 − 2), supraventricular or ventricular rhythm/tachycardia (MC 8-4-1, 8-4-2, 8-2-2, 8-2-3), Wolff-Parkinson-White (WPW, MC 6 − 4) and artificial pacemaker (MC 6–8). Minor arrhythmias mainly included sinus bradycardia (MC 8–8), sinus tachycardia (MC 8 − 7), atrial or junctional or ventricular premature beats (MC 8-1-1, 8-1-2, 8-1-3), incomplete RBBB (MC 7 − 3), Mobitz Type I AV conduction defect (MC 6 − 3) and short PR interval (MC 6 − 5). Other types of ECG abnormalities were classified and analyzed as well, including ST depression and T abnormalities (MC 4 − 1, 4 − 2, 4 − 3, 4–4, 5 − 1, 5 − 2, 5 − 3 or 5 − 4), Q wave abnormalities (MC 1–1, 1–2), Q wave abnormalities plus ischemic ST-T abnormalities (MC ‘1–1 or 1–2’ plus ‘4 − 1, 4 − 2, 4 − 3, 4–4, 5 − 1, 5 − 2, 5 − 3 or 5 − 4’), ST elevation (MC 9 − 2), tall R wave left (MC 3 − 1 or 3–3), tall R wave right (MC 3 − 2), left/right atrial hypertrophy (MC 9 − 3 or 9 − 6), left axis deviation (MC 2 − 1), right axis deviation (MC 2–2) and low voltage (MC 9 − 1).

Statistical Methods

The prevalence calculation and significance evaluation, performed using SUDAAN software (version 10, Research Triangle Institute) in this study, were weighted to represent the population of Chinese adults (≥ 20 years old) based on the Chinese population distribution data in 2006 [8]. The age- and gender- standardized prevalences of ECG abnormalities were calculated for the whole population, for males and females, and for different age groups. Multivariate logistic regression analysis was conducted using SUDAAN software (version 10, Research Triangle Institute) to investigate associations of gender, age, metabolic factors and rural/urban areas with the odds of ECG abnormalities.

Results

This study contained 34965 participants (40% men and 60% women). The baseline characteristics of the participants are summarized in Table 1. The mean ages of men and women were both 44.8 years old. There were no significant differences comparing the age between men and women. Men had significantly higher prevalences of overweight, obese, presence of smoking history, hypertension, diabetes and presence of one or more CVD risk factors (Table 1).

The weighted prevalences of arrhythmias in men, women and all participants with different ages are summarized in Table 2. Major arrhythmias accounted for 1.70% of all participants. The weighted prevalence of major arrhythmias in men was higher than in women (2.37% vs 1.04% in men vs women) (Table 2). The weighted prevalences of major arrhythmias in the young (20–44 years old), middle (45–59 years old) and older age (≥ 60 years old) groups were 1.30%, 2.37% and 5.56% in men, and 0.58%, 1.06% and 2.38% in women, respectively. Specifically, atrial fibrillation/flutter (MC 8 − 3) accounted for 0.28%, 0.35% and 0.20% in the whole population, men and women respectively. Complete RBBB (MC 7 − 2) had the highest prevalence among all major arrhythmias, with the weighted prevalence of 0.85%, 1.16% and 0.55% in the whole population, men and women respectively. Minor arrhythmias accounted for 9.92% in all participants. In the young, middle and older age groups, the weighted prevalences of minor arrhythmia were 11.05%, 10.82% and 14.26% in men, and 6.58%, 7.85% and 14.17% in women, respectively. Individuals in the older age group had higher prevalences of atrial fibrillation/flutter, complete RBBB and atrial/junctional/ventricular premature beats in both men and women, compared with those in the young age group. In addition, gender had an important impact on some specific types of arrhythmia. Complete LBBB, complete RBBB, nonspecific IVCD, sinus bradycardia, incomplete RBBB and Mobitz type I AV conduction defect were more common in men than in women, while sinus tachycardia was more frequent in women than in men (Table 2).

With respect to other ECG abnormalities except arrhythmias, ST depression and T abnormalities and tall R wave left had higher prevalences than other specific ECG types (Table 3). The ST depression and T abnormalities accounted for 10.96%, 7.54% and 14.32% in the whole population, men and women respectively. Tall R wave left accounted for 4.42%, 5.83% and 3.05% in the whole population, men and women respectively. Participants in the older group had higher prevalences of ST depression and T abnormalities, tall R wave left and left axis deviation, compared with those in the young group. In addition, gender played an important role in these ECG abnormalities as well. Compared with women, men had significantly higher prevalences of Q wave abnormalities, ST elevation, tall R wave left, left axis deviation and right axis deviation. Women had higher prevalences of ST depression and T abnormalities and low voltage, compared with men (Table 3).

Figures 1A, 1B, 1C and 1D indicated the odds ratios for the effects of multiple factors on major arrhythmias, minor arrhythmias, ST depression and T abnormalities and tall R wave left, respectively, by multivariate logistic regression analysis. Male gender, older age and living in rural area were positively associated with major arrhythmias. It is worth noting that the likelihood of having major arrhythmias in the 60-year-older group was nearly 4 times higher than that in the reference group (20–44 years old). The risk of having minor arrhythmias was significantly higher in males, the middle age group, the older age group, the smoking group, hypertensive participants, and residents living in rural area. Factors independently influenced the odds ratios of having ST depression and T abnormalities included female gender, older age, hypertension, overweight, obesity and hypercholesterolemia. In addition, male gender, older age and hypertension significantly increased the odds ratios of having tall R wave left.

To identify the factors that influence each arrhythmia ECG type, multivariate logistic regression analysis was conducted, and the results are displayed in Table 4. Older age (at least 60 years old) significantly increased the risk of having atrial fibrillation/flutter, complete LBBB, complete RBBB, nonspecific IVCD, sinus tachycardia, atrial/junctional/ventricular premature beats and Mobitz Type I AV conduction defect. Smoking was positively associated with supraventricular or ventricular rhythm/tachycardia and incomplete RBBB. Hypertension increased the risk of having sinus tachycardia and Mobitz Type I AV conduction defect. Diabetes, obesity and hypercholesterolemia were not positively associated with any arrhythmia ECG type. Residents living in rural area had higher risk of obtaining complete LBBB, nonspecific IVCD, sinus bradycardia and incomplete RBBB, compared to those living in urban area (Table 4).

With regard for the factors influencing other ECG abnormal types except arrhythmias, the results of multivariate logistic regression analysis are displayed in Table 5. Older age (at least 60 years old) was positively associated with ST depression and T abnormalities, tall R wave left, left/right atrial hypertrophy, left axis deviation and low voltage. Smoking was positively associated with Q wave abnormalities, tall R wave right and low voltage. Hypertension significantly increased the risk of having ST depression and T abnormalities, Q wave abnormalities, tall R wave left and left axis deviation. Obesity significantly contributed to ST depression and T abnormalities and left axis deviation. Hypercholesterolemia was positively associated with ST depression and T abnormalities (Table 5).

The weighted prevalences of major arrhythmias in participants with none, one, two and at least three CVD risk factors were 1.19%, 1.76%, 1.95% and 2.17% respectively (Table 6). The presence of CVD risk factors significantly increased the risk of obtaining ST depression and T abnormalities, Q wave abnormalities and tall R wave left, after gender and age were adjusted (Table 6). A history of cardiovascular/cerebrovascular diseases significantly increased the risk of having major arrhythmias, atrial fibrillation/flutter, atrial/junctional/ventricular premature beats, ST depression and T abnormalities, Q wave abnormalities, tall R wave left and left axis deviation, with gender and age adjusted (Table 6). The weighted prevalence of major arrhythmias in participants with a history of cardiovascular/cerebrovascular diseases was as high as 5.72%, while the prevalence in those without the history was only 1.61% (Table 6).

Discussion

ECG is a widely used and cheap examination applied to screen for cardiac diseases. Previous prospective studies have found that baseline major and minor ECG abnormalities are associated with coronary heart disease (CHD) and CVD events [4, 5, 10–14]. Several cross-sectional studies have been conducted to determine the prevalence of ECG abnormalities in North American, South American, and European populations [1–4]. Currently, no population-based estimation of the prevalence of ECG abnormalities has been reported in China. The ECG data contained in the present study were obtained from a large population in a cross-sectional study. The present data provide overall estimates of the prevalence of ECG findings in Chinese adults (aged ≥ 20 years old) and the relationships between ECG abnormalities and gender, age and CVD risk factors.

Age and ethnics, especially age, are factors affecting the prevalences of ECG findings, thus we compared our study results with previous population-based studies which had similar age range with us. The prevalences of some arrhythmias in our study were close to the results in the study of American Hispanics/Latinos aged 18–74 years old and another study of Belgians aged 25–74 years old [1, 2]. In these two foreign studies, atrial fibrillation or flutter accounted for 0.30–0.55% in men and 0.04–0.33% in women [1, 2]. In our study, the weighted prevalences of atrial fibrillation or flutter were 0.35% and 0.20% in men and women respectively, which were between the ranges of these two previous studies. Complete RBBB was the most prevalent arrhythmia type in the American Hispanics/Latinos study and the Belgian study, as well as in our study [1, 2]. In our study, complete RBBB accounted for 1.16% and 0.55% in men and women respectively, which were also between the ranges reported in these two previous studies [1, 2]. However, we had higher prevalences of WPW, Mobitz Type II or III AV conduction defects and supraventricular or ventricular rhythm/tachycardia, but lower prevalences of nonspecific IVCD and artificial pacemaker, compared with the American Hispanics/Latinos study [2]. With regard to ST-T abnormalities, because some subcenters in our study recorded the ST depression and T wave abnormalities together and didn’t differentiate the major and minor ST-T abnormalities, we eventually calculated the prevalence of the major and minor ST-T abnormalities together as ‘ST depression and T abnormalities’ in the population. ST depression and T abnormalities accounted for 7.54% and 14.32% in men and women respectively in our study, while the prevalences of major and minor ST-T abnormalities were approximately 8% and 10% in men and women respectively in the American Hispanics/Latinos study [2].

The weighted prevalences of several ECG abnormalities increased with age in both men and women in our study, confirming the age-related increase in the prevalence of these ECG abnormalities reported in previous studies [1–3, 15, 16]. The likelihoods of having atrial fibrillation/flutter, complete LBBB and complete RBBB in the 60-year-older group were all more than 4 times higher than those in the reference group (20–44 years old) in our study. It is noticeable that CVD risk factors except age and gender did not affect major arrhythmias much, although age had tremendous impact on major arrhythmias in our study (Table 4 and Table 6). However, CVD risk factor had much effect on ST-T abnormalities in our study which is in accordance with previous studies [1–3, 17].

Among the ECG abnormalities, atrial fibrillation/flutter, ST-T abnormalities and left ventricular hypertrophy were broadly studied before. Atrial fibrillation/flutter, well known as a critical risk factor for stroke, was also indicated as an independent risk factor of ventricular fibrillation in a population-based case-control study [18]. In a cross-sectional study of participants aged at least 35 years old in China, the prevalences of atrial fibrillation were 0.78% and 0.76% in men and women, respectively [7]. The inclusion of a history of atrial fibrillation in addition to ECG records and the older age of the participants could have contributed to the higher prevalence of atrial fibrillation observed in this previous study than in our study [7]. The factors that contributed to atrial fibrillation/flutter were mainly older age and the history of cardiovascular/cerebrovascular diseases (Table 4 and Table 6). Compared to the reference group (20–44 years old), in the 60 years old or older group, the odds ratio of having atrial fibrillation or flutter was as high as 9.39. However, in conflict with previously reported studies, we found that smoking history, hypertension, diabetes, obesity and hypercholesterolemia were not significantly related with atrial fibrillation [7, 19]. The odds ratios of having ischemic ST-T abnormalities significantly increased with older age, hypertension, overweight, obesity and hypercholesterolemia, confirming the association between CVD risk factors and ischemic ECG abnormalities [1, 2]. High R wave left is a main ECG manifestation of left ventricular hypertrophy. Our study and previous studies all presented that hypertension was a key risk factor for left ventricular hypertrophy or high R wave left [20, 21]. Another previous study followed up hypertensive patients for a mean time of about 10 years and found that left ventricular hypertrophy was independently associated with CVD events [22]. Thus, it is crucial to identify left ventricular hypertrophy in hypertensive patients, while ECG provides a convenient way to identify it. Meanwhile, blood pressure control in hypertensive patients can prevent the development of left ventricular hypertrophy [23].

Our study had some limitations. First, the original design of the ECG recording didn’t include PR, QRS, QT and QTc interval durations and heart rates. Second, some subcenters recorded the ST depression and T wave abnormalities together, thus the major ST-T abnormalities could not be differentiated with the minor ST-T abnormalities. Third, we didn’t follow up these participants to investigate the progression of ECG findings and metabolic characteristics.

Conclusions

Our study provides estimates of the prevalences of ECG findings in Chinese adults. Gender, age, CVD risk factors and history of cardiovascular/cerebrovascular diseases had important impact on ECG abnormalities.

Abbreviations

ECG, Electrocardiogram; MC, Minnesota coding; CVD, cardiovascular diseases; LBBB, left bundle branch block; RBBB, right bundle branch block; IVCD, intraventricular conduction delay; AV, atrial-ventricular; WPW, Wolff-Parkinson-White; CHD, coronary heart disease

Declarations

Ethics Approval And Consent To Participate

This study was approved by the institutional review board and the ethics committee of local institutions.

Consent For Publication

Not applicable.

Availability of Data and Materials

All data associated with the findings of this article are included in this published article. The datasets used and/or analyzed in the current study are available from the corresponding author upon reasonable request.

Competing interests

The authors have no competing interests.

Funding

The analysis and interpretation of the data in this study were supported by the National Natural Science Foundation of China (grant number: 2017YFC1309705, Beijing, China). The design of the study and data collection of the survey were supported by the Chinese Medical Association Foundation and Chinese Diabetes Society.

Authors' contributions

Liping Yu, Xiaojun Ye and Bo Zhang analyzed and interpreted the ECG data. Zhaojun Yang helped with the analysis of the data. Liping Yu wrote the draft of the manuscript. Xiaojun Ye and Bo Zhang revised the manuscript carefully. Zhaojun Yang and Wenying Yang provided suggestions for the revision of the manuscript. Wenying Yang designed the China National Diabetes and Metabolic Disorders Study. All authors have read and approved the final version of the manuscript.

Acknowledgements

We acknowledge the China National Diabetes and Metabolic Disorders Study Group. We are grateful for all the colleagues who contributed in the China National Diabetes and Metabolic Disorders Study. We thank all the participants in this study.

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