Introduction

Metabolic syndrome is increasing globally, Nigeria inclusive with obesity and increasing sedentary lifestyle being the main epidemic drivers.(1, 2) Prevalence as much as 40% for this condition has been reported in some Western country while in Nigeria it is about 30%.(3, 4)  

 Each of the components produces complications which impose various electrocardiographic (ECG) changes. Previous studies in other population have reported metabolic syndrome to have high prevalence of ECG abnormalities.(5-7) These are associated with adverse cardiovascular outcome among this population group. There is paucity of studies in Nigeria examining these features among metabolic syndrome patients.

The study determined the ECG patterns in a cohort of patient aged above 18years in Ibadan who had metabolic syndrome and accessed the predictors of the abnormalities seen.

Methods

A total of 615 patients with cardiovascular risks presenting to the outpatient unit of cardiology department, University College Hospital, Ibadan for the first time were recruited into the Cardiovascular Risk Prediction Registry (CRP). Basic demographic & clinical profiles and ECG findings were determined and    found to have metabolic syndrome based on the definition below were selected for this study.

Definition of metabolic syndrome

Metabolic syndrome was defined based on International Diabetic Federation (IDF) criteria using waist circumference(?94cm (men), ?80cm (female),or two or more  of the following i.  Fasting triglyceride >150g/dL, or specific treatment for this lipid abnormality, ii HDL cholesterol > 40mg/dL(men), >50mg/dL(women) or specific treatment for this lipid abnormality  iii. Blood pressure >130mmHg (systolic), >90mmHg (diastolic) or on antihypertensive treatment. iv. ?100mg/dL or previously diagnosed diabetes mellitus.

Assessment of anthropometric measurement

Weight and height were taken by trained research staff. Weight was taken after the participants have removed clothing to the barest minimum and the height without shoes or head gear. The weight was measured to the nearest 0.1 kg while height was to the nearest 0.5cm. Waist circumference was taken midpoint of the distance of last palpable rib and the top of the iliac crest using an anthropometric measuring tape while hip circumference was at the  widest portion of the buttocks using the same tape.

The basic, clinical and ECG profiles of those with metabolic syndrome were compared with those with metabolic syndrome.

Assessment of blood pressure

 

Electrocardiography

All participants for this study had resting  ECG using a commercially availableDA1  CONTEC® Workstation Model CONTEC EC8000G, ECG machine (Made in China) at 25 mm/s and 1mV/cm calibration. The entire ECG tracing used were inspected visually by the technicians in the team to detect technical errors, missing leads, and inadequate quality of tracings. Defective ones are repeated before extraction of data.

Various parameters such as heart rate, PR interval, QRS duration, QTc interval, P wave axis, QRS axis, T wave axis were extracted. These are in addition to standard determination of rhythm & conduction abnormalities, chamber enlargement and right or left ventricular hypertrophy. Cornell product was determined by (RaVL + SV3) + 8mm for women x QRS duration ? 2440 mm while Sokolow-Lyon voltage was determined by sum of the amplitudes of S wave in V1 and R wave in V5 or V6 ?3.5 mV.

Data management and statistical analysis

The data was extracted from the case reporting form and stored safe and secure location using excel spreadsheet and data base pass worded and access  only be  available to the research team.

The qualitative data were summarized as frequency and percentage. Quantitative variables would be summarized as means, standard deviations and percentages. Categorical data were analyzed using chi square with Yates correction  and confidence interval determined.        

Multiple linear regression would be used to model for the influence of socio demographic and clinical variables of the participants on various ECG findings.

The data was analyzed using Statistical Package for Social Sciences (SPSS), version 16.0 (Spss Inc, Chicago, IL, USA).

 

Ethical considerations

Ethical approval was granted for the study by UI/UCH ethical committee and all patients that participated in the study gave informed consent.

Results

Dummy tables

Table 1: Basic demographic and clinical profile of participants

 

Total

Men

Women

P value

Age(mean)

 

 

 

 

Ethnicity

 

 

 

 

Marital status(Married)

 

 

 

 

Educational background(None)

 

 

 

 

Occupation(Unemployed)

 

 

 

 

smoking

 

 

 

 

Alcohol

 

 

 

 

BMI(mean)

 

 

 

 

Weight (Kg)

 

 

 

 

Height(cm)

 

 

 

 

Waist circumference(cm)

 

 

 

 

WHtR

 

 

 

 

Systolic blood pressure(mean)

 

 

 

 

Diastolic blood pressure(mean)

 

 

 

 

 

 

 

metabolic syndrome

Without metabolic syndrome

P value

Heart rate

 

 

 

PR interval

 

 

 

QRS duration

 

 

 

QT interval

 

 

 

QTc interval

 

 

 

P wave axis

 

 

 

QRS axis

 

 

 

T wave axis

 

 

 

 

Table 2: Various ECG abnomalities

 

metabolic syndrome

Without metabolic syndrome

P value

Presence of any ECG abnomalities

 

 

 

Sinus rhythm(Yes)

 

 

 

Sinus arrthymia(Yes)

 

 

 

Atrial fibrillation(Yes)

 

 

 

Atrial flutter

 

 

 

Presence of arrthymia

 

 

 

PVC

 

 

 

PVC and PSVC

 

 

 

Ventricular tachycardia

 

 

 

Supraventricular tachycardia

 

 

 

 

 

 

 

No conduction abnormalities

 

 

 

First degree AV block

 

 

 

Second degree AV block

 

 

 

Complete AV block

 

 

 

RBBB

 

 

 

LBBB

 

 

 

LAH

 

 

 

LPH

 

 

 

Bifascicular block

 

 

 

Trifascicular block

 

 

 

Indeterminate interventricular block

 

 

 

 

 

 

 

No chamber enlargement

 

 

 

Right atrial enlargement

 

 

 

Left atrial enlargement

 

 

 

Biatrial enlargement

 

 

 

LVH

 

 

 

LVH with strain

 

 

 

RV hypertrophy

 

 

 

 

Table 3: Assessment of gender difference of  ECG abnormalities in metabolic syndrome

 

Male with metabolic syndrome

Female with metabolic syndrome

P value

Presence of any ECG abnormalities

 

 

 

Sinus rhythm(Yes)

 

 

 

Sinus arrthymia(Yes)

 

 

 

Atrial fibrillation(Yes)

 

 

 

Atrial flutter

 

 

 

Presence of arrthymia

 

 

 

PVC

 

 

 

PVC and PSVC

 

 

 

Ventricular tachycardia

 

 

 

Supraventricular tachycardia

 

 

 

 

 

 

 

No conduction abnormalities

 

 

 

First degree AV block

 

 

 

Second degree AV block

 

 

 

Complete AV block

 

 

 

RBBB

 

 

 

LBBB

 

 

 

LAH

 

 

 

LPH

 

 

 

Bifascicular block

 

 

 

Trifascicular block

 

 

 

Indeterminate interventricular block

 

 

 

 

 

 

 

No chamber enlargement

 

 

 

Right atrial enlargement

 

 

 

Left atrial enlargement

 

 

 

Biatrial enlargement

 

 

 

LVH

 

 

 

LVH with strain

 

 

 

RV hypertrophy

 

 

 

 

 

Table 4: Associations with different ECG abnomalities

 

 

All abnormalities

Rhythm abnormalities

Conduction abnormalities

Chamber enlargement/Wall abnomalities

 QT changes

Age

 

 

 

 

 

 

Gender

 

 

 

 

 

 

Smoking status

 

 

 

 

 

 

 

Non-smoker

 

 

 

 

 

 

Former smoker

 

 

 

 

 

 

Light smoker(<10/day)             Moderate smoker(10-19/day)             Heavy smoker(?20)           Alcohol intake(Yes)             Duration of hypertension               (5-10years)             >10years

 

 

 

 

 

Family history of hypertension(Yes)

 

 

 

 

 

 

Family history of DM(Yes)

 

 

 

 

 

 

Family history of coronary heart disease(Yes)

 

 

 

 

 

 

Diagnosis of hypertension

 

 

 

 

 

 

Diagnosis of DM

 

 

 

 

 

 

Diagnosis of lipid abnormality

 

 

 

 

 

 

Albuminuria

 

 

 

 

 

 

Presence of urine protein

 

 

 

 

 

 

Urea(mean)

 

 

 

 

 

 

 

 

 

References

1.            Eckel RH, Grundy SM, Zimmet PZ. The metabolic syndrome. Lancet. 2005;365(9468):1415-28.

2.            Misra A, Khurana L. Obesity and the Metabolic Syndrome in Developing Countries. The Journal of Clinical Endocrinology & Metabolism.93, Issue 11_(11 supplement_1, 1 ):s9–s30.

3.            Grundy SM. Metabolic syndrome pandemic. Arteriosclerosis, thrombosis, and vascular biology. 2008;28(4):629-36.

4.            Oguoma VM, Nwose EU, Richards RS. Prevalence of cardio-metabolic syndrome in Nigeria: a systematic review. Public Health.129(5):413-23.

5.            Kim H-K, Kim C-H, Ko K-H, Park S-W, Park J-Y, Lee K-U. Variable Association between Components of the Metabolic Syndrome and Electrocardiographic Abnormalities in Korean Adults. The Korean Journal of Internal Medicine. 2010;25(2):174-80.

6.            Ebong IA, Bertoni AG, Soliman EZ, Guo M, Sibley CT, Chen YD, et al. Electrocardiographic abnormalities associated with the metabolic syndrome and its components: the multi-ethnic study of atherosclerosis. Metabolic syndrome and related disorders. 2012;10(2):92-7.

7.            Ajayi EA, Ajayi OA, Adeoti OA. Metabolic syndrome: prevalence and association with electrocardiographic abnormalities in Nigerian hypertensive patients. Metabolic syndrome and related disorders. 2014;12(8):437-42.

 DA1ECG acquisition box  Model MGY-S3, Made in Germany

 

CONTEC® Workstation Model CONTEC EC8000G, Made in China