Department of Cardiology, Bangabandhu Sheikh Mujib Medical University (BSMMU), Dhaka, Bangladesh
Department of Community Medicine, Ibrahim Medical College, 122 Kazi Nazrul Islam Avenue Shahbag, Dhaka-1000.
Department of Internal Medicine, Bangabandhu Sheikh Mujib Medical University (BSMMU), Dhaka, Bangladesh
Department of Internal Medicine, Ibrahim Medical College, 122 Kazi Nazrul Islam Avenue Shahbag, Dhaka-1000.
The prevalence of cardiovascular diseases (CVD) are on the increase worldwide
and more in the developing countries. Coronary artery disease (CAD) constitutes
the major brunt of CVD. Despite the increasing morbidity and mortality,
Bangladesh has a few published data on CAD in rural population. This study
addressed the prevalence of CAD and its risk factors in rural population of
Sixteen villages were purposively selected in a rural area. A population census
was conducted in the selected area. The census yielded eligible participants,
who reached at least eighteen years of age. Those who willingly consented to
participate were enlisted. Each participant was interviewed regarding CAD risk
(age, sex, social class, occupation, illness, family history). Anthropometry (height,
weight, waist- and hip-girth) was recorded. Resting blood pressure (BP) was
measured. Blood sample was collected for fasting blood glucose (FBG), total cholesterol
(Chol), triglycerides (Tg), low density lipoproteins (LDL), very low density
lipoproteins (VLDL) and high density (HDL). All participants having
FBG>5.5mmol/l or systolic (SBP) ³135 or diastolic BP
(DBP) ³85mmHg underwent
electrocardiography (ECG). A team of cardiologists selected and accomplished
exercise tolerance test (ETT) and echocardiography (Echo).
Results: The prevalence of CAD
was 4.5% (95% CI: 3.85 – 5.15). Compared with the female (3.5%, CI,
2.76 – 4.24) the male participants had significantly higher prevalence of CAD
(6.0%, CI, 4.83 – 7.13). Comparison of characteristics between participants
with and without CAD showed that age, SBP, DBP and FBG were significantly
higher in CAD group. Bivariate analysis showed that age, sex, social class,
glycemic status, metabolic syndrome (MetS) and smoking were significantly
related to CAD. Stepwise logistic regression proved only male sex, rich social
class, hypertension and diabetes had independent risk of CAD; whereas, age,
obesity and dyslipidemia were proved not significant.
Conclusions: The study concludes that the prevalence of CAD in a Bangladeshi rural
population is comparable to other developed countries. The male sex, rich
social class, hypertension and diabetes were proved to have excess risk of CAD.
Neither obesity nor dyslipidemia were found significant for CAD. The younger
people had similar risk as the aged ones, which necessitate primordial and
primary prevention of CAD. Further study may be undertaken, which should
include and consider physical activity and diet; and if possible, C-reactive protein,
Vitamin D and homocysteine level.
IMC J Med Sci 2017; 11(2): 61-69
Correspondence: Prof. M. Abu Sayeed, Department of Community Medicine,
Ibrahim Medical College, 122 Kazi Nazrul Islam Avenue Shahbag, Dhaka-1000.
of atherosclerotic diseases is progressively
increasing . The projected deaths from cardiovascular diseases (CVD) in 2030 is estimated to reach 23.6 million
(34.8%) of the world population. Thus, it is clear that the clinical and
socioeconomic impact of CVD is considerable.
The World Health Organization (WHO) statistics of 2004 showed that CVD represents the number one cause of death
worldwide, approximating 30% of total mortality . Considering these facts,
WHO and its partners launched a new initiative “Global Hearts” on 22
September, 2016 . The initiative aimed to minimize the global threat of
cardiovascular disease, the world’s leading cause of death.
questions remained still unanswered how to minimize the global threat and how
to prevent morbidity and mortality of CVD. Though multiple risk factors like
adiposity and metabolic disorders have been identified, these are found
inconsistent in different studies. For example, some studies observed that
obesity is a significant risk for coronary artery disease (CAD) [3,4]. In
contrast, some studies reported that non-obese people also had risk for
cardiovascular deaths  and different populations with an obesity paradox by BMI showed
different risk .
regards Bangladesh, there are few published data that estimated the magnitude
of CVD and its related morbidity or mortality. Some investigators showed
several known risks (obesity, smoking, lipids) prevalent amongst the south
Asians (India, Pakistan, Bangladesh, Sri Lanka and Nepal) . But these risk factors
have not been studied in relation to CAD, and no study investigated which of
the risks and how much of it significantly related to CAD. This study aimed to
determine the prevalence of CAD in a rural community of Bangladesh.
Additionally, the study attempted to investigate some known risk factors
attributed to CAD.
study proposal was approved by the Ethical Review Committee of Bangladesh
Diabetic Samity (BADAS).
to protocol, sixteen villages were purposively selected in a rural area - located
north-east of Dhaka city and inhabited mostly by the population involved in
agrarian occupation. The area is connected to Dhaka city by110 km of paved and
10 km of non-paved road. A census was conducted in these villages. The census
included socio-demographic information (age, sex, education, occupation and
family income). It also included family history of non-communicable diseases
(NCD). Individual equal to or greater than 18 years of age was considered eligible.
The eligible participants (≥18years) were randomized. The eligible participants
were detailed (objectives, methods) about the study. Those who consented to
volunteer the study were invited for stepwise investigations.
Interviewing - In the morning, the participant was interviewed about occupation,
education, income, illness (present or past) and medication. Interviewing on
family-history included diabetes, hypertension (HTN), stroke, coronary heart
diseases (CHD), peripheral vascular disease (PVD), foot-ulcer and leg
amputation. The information was recorded based on medical reports
(investigation, prescription) and verbal autopsy.
Anthropometric and blood pressure (BP) measurements: Height, weight, waist- and hip-girth were measured. Body mass index
(BMI = weight in kg / height in met sq.), waist-to-hip ratio (WHR = waist /
hip) and waist-to-height ratio (WHtR =Waist / height) were calculated. Blood
pressure was taken after 10 minutes of rest.
Collection of blood
sample: Five milliliter of fasting blood sample was
collected aseptically for estimation of fasting blood glucose (FBG mmol/l) and
lipids (total cholesterol, triglycerides, low-density lipoprotein, high-density
and very high density lipoproteins). While collecting blood sample a drop of
blood was taken on a finger strip for rapid assessment of FBG. The participants, who showed SBP /
DBP ≥ 135 / 85 mmHg and/ or FBG ≥5.6 mmol/l were referred to electrocardiography
A team of cardiologists examined all ECG
tracings. According to the need of the cardiologists the ECG was repeated and
for confirmation the participants were referred to the Department of Cardiology,
Bangabandhu Sheikh Mujib Medical University (BSMMU) in Dhaka for ehocardiography
(Echo) and exercise tolerance tests (ETT). Diagnosis of CAD was based on - a) history of angina plus ischemic change in
ECG either at rest or on stress; b) post-myocardial infarction (MI) with Q-wave
MI or non-QMI.
of the study
Note: SBP, DBP – systolic, diastolic
blood pressure in mmHg; FBG – fasting blood glucose in mmol/l; CAD – coronary
artery disease; ECG – electrocardiography; Echo – echocardiography; ETT –
exercise tolerance test;
Statistical analyses: Prevalence rates were
given in percentages. Student’s t-tests were used for comparison of variables
between groups (men vs. women, non-CAD vs.CAD) with mean and standard deviation
(Mean ± SD). To find out associations
between different qualitative variables we used Chi sq (c2) test. The
quantitative variables were transformed into quartiles (Q) for determining the trend of CAD prevalence from
lowest (Q1) to the highest quartile (Q4). Stepwise logistic regression analysis
quantified the risk variables as independent and CAD as a dependent variable. The
findings were expressed as Odds ratio (OR) with 95% confidence interval (CI). In
each test the level of significance was accepted if p<0.05. For all these
analyses SPSS/PC+ was used.
mentioned, the census in 16 villages yielded 22863 persons of all ages in 6823
households (Figure 1). The observed age groups were: 4.6%, 37.1% and 58.3% in
<2, 2-17 and ≥18years of age, respectively (Table 1). Of the eligible group
for CAD (≥18y: n = 13724), an estimated sample of 5000 were randomly selected
for investigations (Figure 1). Of them, 3928 (m / f = 1590 / 2338) volunteered.
Overall, the response rate was 78.6%.
Table-1: Distribution of age and sex according to
crude prevalence of CAD was 4.5% with 95% CI 3.85 – 5.15. Compared to female
(3.5%, CI, 2.76 – 4.24), the male participants had significantly higher
prevalence of CAD (6.0%, CI, 4.83 – 7.13) [Table 2]. Similarly, compared to
people in lower socio-economic class, the higher class had significantly higher
prevalence of CAD (p <0.001) [Table-2]. The diabetic participants had significantly
higher prevalence (10.3%: CI 8.17 – 12.43) than those with normal or impaired
fasting glucose levels (p<0.001) [Table 2]. Similarly, smoking habit
(p=0.02) and metabolic syndrome were significantly (p<0.05) associated with
prevalence of CAD showed an increasing trend (Pearson Chi Sq) with increasing
quartiles of age (p=0.004), SBP (p=0.008), DBP (p=0.047) and cholesterol
(p=0.016) [Figure-2]. It may be noted that quartiles of BMI, WHR, WHtR, TG, LDL
and VLDL were also estimated for similar trend but were not found significant
(data not shown).
characteristics of men and women were compared in Table-3. Though mean (SD) of
age, DBP, TG, and VLDL were significantly higher in male than female
participants, the obesity related variables (BMI, WHR) and FBG did not differ
[Table 3] except WHtR, which was significantly higher in female.
Table-2: Prevalence (%) of coronary artery disease
(CAD) according to sex, social class, glycemic status, smoking habit and
comparison of quantitative variables were made between participants with and
without CAD [Table -4]. Most of the (risk) variables did not differ between
them except age (p<0.001), SBP (p = 0.002), DBP (p=0.001) and FBG (p=0.003).
Evidently, none of the obesity related variables (BMI, WHR, WHtR) differ between
CAD and non-CAD nor did the lipids (Chol, Tg, LDL and VLDL). Thus, these
findings were found inconsistent and inconclusive. So, these risk variables
were quantified by logistic regression.
Prevalence of CAD according to quartiles
(Q1, Q2, Q3, Q4) of age, systolic blood pressure (SBP), diastolic blood
pressure (DBP) and total cholesterol (Chol). The trend (Pearson Chi Sq.) for
Age (p=0.004), BPS (p=0.008), BPD (p=0.047) and Chol (p=0.016)
logistic regression (forward stepwise) estimated different risk factors as
independent and CAD as a dependent variable in four different models (Table-5).
In model 1, we included sex (f=1, m=2), social class (poor=1, rich=2),
age-quartile (Q1 through Q2) and metabolic syndrome (no=1, yes=2). In model-2,
glycemic levels were added to model-1. In subsequent models, the quartiles of
SBP (model-3) and chol (model-4) were added. Finally, four risk factors
retained their significance (male sex, rich class, diabetes and Q4 of SBP). The
odds ratio (with 95% CI) for men was 1.83 (CI, 1.30 – 2.56); the rich class
1.74 (CI, 1.11 – 2.73); diabetes 1.97 (CI, 1.15 – 3.36) and Q4 of SBP 1.85 (CI,
1.22 – 2.80). The other risk variables (age, metabolic syndrome, chol, TG, HDL,
LDL, VLDL) entered stepwise into the logistic equation but these were proved
Table-3: Comparison of characteristics
between men and women
Table-4: Comparison of
characteristics between participants with coronary artery disease (CAD) and
without CAD (Non-CAD)
Table-5: Binary logistic
regression taking CAD as a dependent variable
is a population based study and appears to be unique considering its
commencement with a census of the study communities that included all possible
socio-demographic information. Most of the studies reported the prevalence of
CAD and its risk factors separately. Very few studies investigated which risk
and how much that is attributable to CAD and why the prevalence and the risks differ
across communities, classes and countries [2-5].
study emphasized not only the prevalence of CAD in a rural population, which
comprises almost 70%  of the country, but also included the background
information (census) related to known risk factors (family income, education,
occupation, smoking, family history). Other known risks (obesity, blood
pressure, glycemia, lipids) were also investigated. Additionally, we quantified
each specific risk whether or not contributing for developing CAD.
CAD prevalence of this study (4.5% with 95% CI 3.85 – 5.15; m/ f =6.0 / 3.9%)
is lower than urban population of Rajasthan (m / f = 6.18 /10.12 %)  and Jaipur
(m / f = 9.2 / 11.7%) ; but consistent with findings of Scotland study (m /
f = 5.5 / 3.9%) . Again, the study findings are inconsistent regarding the
proportion of CAD in male and female groups. The urban female population had
more CAD than males [9, 10]; whereas, our finding and Scotland study  had male
known modifiable risks of CAD are obesity, dyslipidemia, smoking, hyperglycemia
and hypertension; and the non-modifiable major risks are age and inheritance
[2-4]. But these are not unequivocally proven risks as reported by others. For
example, though obesity is thought to be an important risk, obesity reduced CAD
as reported by Tsujimoto T  and De Shutter . It is interesting that some studies have observed
high CAD mortality among people with low body fat and /or low lean mass index;
and low mortality among the obese individuals [12,15,16]. Higher BMI, WHR and
WHtR in this study showed no significant association with CAD. Logistic regression
analyses proved obesity had neither excess nor reduced risk for CAD. Likewise, dyslipidemia
(high chol, Tg, LDL, VLDL and low HDL) were known risk for CAD [13,14]. On the
contrary, our study findings did not show excess risk of dyslipidemia for CAD.
prevalence of CAD increases with increasing age due to metabolic derangement
attributed to in ageing process (hyperglycemia, dyslipidemia, atherogenesis, hypertension).
The findings of this study did not show such effect of advancing age on CAD.
This means that even younger people bear the risk of CAD. This particular
finding is consistent with the study addressing ‘overweight risk paradox in
other risk variables were expected to contribute to CAD, but eventually, proved
not significant as CAD risk. Family history of diabetes, hypertension, CAD and
stroke was found not significant. Metabolic syndrome was also thought to be an
important CAD risk. Bivariate quantitative analysis showed that the
participants with MetS had almost six-fold higher CAD than those without MetS (Table-2:
25.0% vs 4.5%). But, logistic regression analysis disproved its effect on CAD. MetS
though associated with CAD, it has not been found consistent [17,18].
was found significant (Table-2: p=0.02) in bivariate analysis, but ultimately
was found insignificant.
study, however, unequivocally proved that the male participants, higher social
class, higher systolic blood pressure and hyperglycemia (FBG >7.0mmol/L) had
independent risk of CAD. These findings are very much consistent with other
there are some issues remained unexplained. If not obesity and dyslipidemia are
CAD risk, then what other risk factors are related to CAD? Why the younger people
had similar CAD risk as the aged?
could not investigate some simple but important risks like physical activity
and diet. This is the shortfall of this study. Additionally, it would have been
better if we could include C-reactive protein [19,20], Vitamin D  and
homocysteine level , which are considered CAD risk, directly or indirectly.
Though not very evident, it is also important to explore whether genetic
predisposition have any contribution to CAD [23,24].
may conclude that the prevalence of CAD in rural Bangladeshi people is not insignificant
and is comparable to other developed countries. The male sex, rich social
class, hypertension and diabetes were independent risk for CAD. Obesity and
dyslipidemia had no effect on CAD. Younger people had equal CAD risk as the
aged people. Thus it becomes imperative to initiate primordial and primary
prevention. It is also suggested that further study may be undertaken to
determine the role of physical activity and diet, and if possible, C reactive protein,
Vitamin D and homocysteine level in CAD.
We are grateful to Ministry of Science and
Technology, Government of the People’s Republic of Bangladesh, for funding the
project. We are also grateful to the Department of Cardiology, Bangabandhu
Sheikh Mujib Medical University for their active co-operation in making the
necessary investigations for confirmation of diagnosis. We are indebted to the
Department of Community Medicine, Ibrahim Medical College for taking the brunt
of all biochemical tests. We appreciate the help
extended by the Principal, Ibrahim Medical College, who kindly allowed his
teaching and technical staff to carry out the study from starting to the end.
Finally, we acknowledge the contributions made by the principals, headmasters,
teachers and students of the educational institutes; and local leaders and the
participants of the study sites, who actively volunteered.
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