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International Journal of Pharma and Bio Sciences
RESEARCH ARTICLE
PHARMACOLOGY
STUDY OF THE RELATIONSHIP OF CONVENTIONAL RISK FACTORS AND MI
AMONG SOUTH INDIAN POPULATION.
AUXILIA HEMAMALINI TILAK*1 AND LAKSHMI.T
2
1
2
Faculty of Microbiology, Saveetha Dental College, Chennai-77
Faculty of Pharmacology, Saveetha Dental College, Chennai-77
AUXILIA HEMAMALINI TILAK
Faculty of Microbiology, Saveetha Dental College, Chennai-77
ABSTRACT
Cardiovascular disease (CVD) is a major global health problem reaching epidemic
proportions in the Indian population, accounting for 78% of all deaths. High risk of
CVD has been reported among South Asians. Presence of conventional risk factors
such as Obesity, Smoking, Diabetes mellitus, Hypertension and Dyslipidemia
are clearly associated with coronary artery disease. In contrast to conventional belief
we have proved in this preliminary study that the Indian population needs a totally
different set of risk factors for CAD. Our present study was undertaken to elicit the
pattern of selected risk factors for myocardial infarction (MI) among South Indians
belonging to low socio economic status and to emphasize the need to delve into
factors which lead to a pro-inflammatory state rather than be satisfied in identifying
such a state which culminates in MI and other related problems.
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KEY WORDS
Cardiovascular disease, Risk factors, Myocardial Infarction, Obesity, BMI.
INTRODUCTION
Obesity is generally defined as a condition in
which excess body fat has accumulated to an
extent that can negatively affect health.
Obesity is nowadays a major health problem in
developed countries and a growing one in the
developing world, becoming one of the most
serious public health threats.1, 2, 3 In 1998, the
World Health Organization4recognized obesity
as a major public health epidemic worldwide.5
The health impact and financial burdens of
obesity have been well documented. Excess
weight is associated with an increased
incidence of cardiovascular disease (CVD),
type
2
diabetes
mellitus,
smoking,
hypertension,
stroke,
dyslipidemia,
osteoarthritis,
and
some
cancers.6-9
Furthermore, obesity is believed to play a
central role in the development of the
'metabolic syndrome', a term given to the
clustering of CVD risk factors.10
In financial terms, conservative estimates place
the economic costs of obesity in developed
countries at 2–7% of total health costs, 11 and it
is anticipated that obesity-related diseases will
increasingly compete with infectious diseases
for health care resources in this century.12The
exact causes of obesity remain to be fully
elucidated, but lack of physical activity and
excessive energy intake are known to be major
determinants.
As populations become more urbanized, and
as lifestyles shift towards reduced physical
activity and increased food consumption, the
prevalence of obesity is expected to rise. High
total and low-density lipoprotein (LDL
cholesterol) levels and low HDL cholesterol
levels increase the risk of myocardial infarction
Cholesterol levels can be lowered with
dietary/lifestyle modifications such as exercise
or medications.
Different methods are used for the
measurement of obesity and these include: (a)
the estimation of the body mass index; (b)
measurement of skin fold thickness or waist hip
ratio;13 (c) measurement of fat cell size and
number;14 and (d) measurement of body
density.15
BODY MASS INDEX
Height and weight were assessed at baseline
and weight was updated on each subsequent
questionnaire in each cohort. We calculated
body mass index (BMI) as the weight in
kilograms divided by the height in meters
squared. BMI was classified into five
categories based on NHLBI guidelines,16 with
normal weight split into two categories in order
to facilitate comparison with other studies; the
categories used were: normal (<23 kg/m2 and
23-24.9 kg/m2), overweight (25-27.9 kg/m2 and
28-29.9 kg/m2) and obese ( 30 kg/m2).
MATERIALS AND METHODS
STUDY GROUP
The first group were 56 men admitted to a
General Hospital ICU in Chennai during March
and April 2009 with acute MI and belonging to
the lower socioeconomic group, with a median
age of 40(between 21 and 60). They were
enrolled in this study after obtaining informed
consent.
The second group consisted of 56 healthy
volunteers with a median age of 40(21-60) who
are volunteers donating blood at the blood
bank of the General hospital in Chennai. They
were enrolled in this study after obtaining their
consent.
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STUDY DESIGN
a) PATIENTS WITH ACUTE MYOCARDIAL
INFARCTION (n=56)
INCLUSION CRITERIA
Patients aged 21-60 reporting to the
cardiology OP with acute MI is enrolled in this
study. All subjects filled out a standardized
questionnaire containing socio demographic
information, smoking history and other relevant
medical history, including the previous history
of diabetes mellitus, hypertension, and family
history of related events. Their Complete blood
counts, lipid profile, hs-CRP levels, ECG,
Fasting and post prandial blood sugars are
obtained
EXCLUSION CRITERIA
Subjects with malignancy, terminally ill, chronic
pulmonary diseases like bronchitis and asthma,
old cases of pulmonary tuberculosis and
previous MI
b) HEALTHY POPULATION (n=56)
INCLUSION CRITERIA
Volunteers aged 21-60 years, matched for age
with the patient population. All subjects verified
with blood counts, regular screening for
infectious diseases as routinely done in a blood
bank, lipid profile, fasting and post prandial
sugar, hs-CRP levels, ECG and a clinical
examination
EXCLUSION CRITERIA
Previous history of cardiac events including
previous MI, cardiac surgeries, and negative
for infectious diseases by routine blood bank
screening were the exclusion criteria
UNDER TAKING OF HISTORY AND
PHYSICAL EXAMINATION
A thorough undertaking of history was done
which includes socioeconomic status, marital
status, monthly income, routine food habits,
smoking, and alcoholism, past history of
medical problems which included DM and HT,
family history and history of presenting illness.
A clinical examination was done including vitals,
height, weight, abdominal girth and systems
examination. The ECG report was utilized from
that of the hospital records
CLINICAL SPECIMEN
BLOOD: 5 ml of blood was collected twice
from the patients in a BD vacutainer for CBC,
lipid profile, hs-CRP levels, fasting and
postprandial sugar in the patient population
and once from the healthy volunteers.
RESULT AND DISCUSSION
Myocardial infarction is multi factorial and
numerous risk factors are known to the
common man. What is not known that the
South Asian community is unique with respect
to the risk factors that are documented and
often quoted.
Obesity is a major risk factor for
cardiovascular disease and obesity has been
conventionally defined as a BMI of 30 and
above. Waist-to-hip ratio shows a graded and
highly significant association with myocardial
infarction risk17 worldwide and has been
argued to be better marker of obesity than BMI.
On the other hand in the interheart study18
researchers have argued that overweight (BMI
25-30) and obesity (above 30) are as valuable
risk factors for myocardial infarction as waist to
hip ratio. Obesity has been proven to have an
independent association with acute coronary
syndrome19. Obese patients (body mass index
[BMI] >30) with AM1 were significantly younger
than patients with AM1 in the overweight (BMI
25-30) and normal-weight (BMI <25) groups as
proven by Jasim etal20.
South Asians have levels of LDL
cholesterol comparable to other populations
but the LDL particle size tends to be smaller. 23
These small LDL particles through increased
susceptibility to oxidation are more atherogenic
than larger particles. HDL particle size also is
an important predictor of CAD risk in addition
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to the actual level of HDL cholesterol. South
Asians not only have lower HDL levels(less
than 35 in males) but also have a higher
concentration of small, less-protective HDL
particles 24 it has also been noted that even at
normal HDL levels Asian Indian males have a
higher prevalence of low HDL2b than non-Asian
Indians, which suggests impaired reverse
cholesterol transport. All this is genetically
predetermined and lifestyle modifications and
therapeutic interventions are possible to
prevent adverse effects due to this.
Inflammation plays a major role in
atherothrombosis, and measurement of
inflammatory markers such as high-sensitivity
C-reactive protein (hs-CRP) may help in
identifying individuals with a high risk of
developing MI. It has proven to be a global risk
marker. Several large-scale prospective
studies demonstrate that hs-CRP is a strong
independent predictor of future myocardial
infarction among apparently healthy men and
women as proven by Ridker and his colleagues
21, 22, 23
. Nevertheless it is an inflammatory
marker and it reveals the fact that the
inflammatory process has begun in other
words damage has already been done. It gives
no indication as to the etiology.
Infection as a cause for the proinflammatory
state has leading to MI been discussed again
by the investigators 25, 26 who had partial
success. Jianhui Zhu et al26 have done a
prospective study and have evaluated IgG
antibodies to cytomegalovirus (CMV), hepatitis
A virus (HAV), herpes simplex virus type 1
(HSV1), HSV type 2 (HSV2), Chlamydia
pneumoniae and Helicobacter pylori, and Creactive protein (CRP) levels in baseline blood
samples from 890 patients who had significant
CAD on angiography. The mean follow-up
period was 3 years. They demonstrated that
adjusted relative hazards of MI or death
associated with pathogen burden were
significant among individuals independent of
the CRP levels. Again the study was not in the
Indian population and baseline IgG titres in
different areas have to be studied in a huge
population for all these infections before we
tabulate risk factors. Numerous studies have
linked infectious diseases and MI27, 28
In our study (Table 8), though there is a
27% correlation between diabetes within the
case group (p=0.007), it is considered as poor
correlation. When we try to predict myocardial
infarction in this case group with diabetics it
shows not significant. There is 27% correlation
between hypertension within case group
(p=0.007). In this also even though it shows
relationship it is considered as poor correlation.
When we tried to predict myocardial infarction
it proved to be not significant. There is 43%
correlation between smoking with case group.
(P=0.000), it shows relationship; it is
considered as positive correlation. When we try
to predict myocardial infarction it shows to be
insignificant. The reason is that voluntary blood
donors (controls) are routinely screened for
diabetes and hypertension and they all
happened to be non smokers. There is 68.4 %
correlation between hs-CRP within the case
group. (p=0.000) it shows good relationship, it
is considered as positive correlation. When we
try to predict myocardial infarction it shows
significance. There is a significant correlation
only between hs-CRP and MI but there is no
significant correlation between MI and other
traditional risk factors such as diabetes,
hypertension, obesity and overweight in this
population. There is 26.4 % correlation
between diabetes with hs-CRP (P=0.009).
Even though it shows relationship it is
considered as poor correlation. There is 26.4
% correlation between HT with hs-CRP
(P=0.009) even though it shows relationship it
is considered as poor correlation. There is
22.7% correlation between smoking with hsCRP. (P=0.02). Even though it shows
relationship it is considered as poor correlation.
There is 20.5 % correlation between TGL with
HSCRP. P=0.05. Even though it shows
relationship it is considered as poor correlation.
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TABLE 1
DIABETES
DIABETES
Group
Control No
Case
No
Yes
Total
Frequency
40
47
9
56
Percent
100
83.9
16.1
100
TABLE 2
HYPERTENSION
HYPERTENSION
Group
Frequency
Control No
40
Case
No
47
Yes
9
Total
56
Percent
100
83.9
16.1
100
TABLE 3
SMOKING
Group
Control No
Case
No
yes
Total
SMOKING
Frequency
40
36
20
56
Percent
100
64.285714
35.714286
100
TABLE 4
BMI
Group
control
Case
<30
<30
>=30
BMI
Frequency
40
55
1
Percent
100
98.2
1.8
Total
56
100
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ABLE 5: Hs-CRP
Group
control
Case
Hs-CRP
Frequency
37
3
40
13
43
56
<3
>=3
Total
<3
>=3
Total
Percent
92.5
7.5
100
23.214286
76.785714
100
TABLE 6
TRIGLYCERIDE
TRIGLYCERIDE
Frequency
Group
Control <150
>=150
Total
Case
<150
>=150
Total
25
15
40
29
27
56
Percent
62.5
37.5
100
51.785714
48.214286
100
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TABLE 7
LDL
LDL
Group
Control
Case
<100
>=100
Total
<100
>=100
Total
Frequency
22
18
40
32
24
56
In our study (Table 9), When we compare the
diabetes between case and control group it
shows some significant difference (chi sq =
7.094, p= 0.009). The odds of having MI is 1.19
times more in diabetes group when compare to
the person without diabetes the 95% CI is
1.062 – 1.336. When we compare the
hypertension with case and control group it
shows some significant difference (chi sq =
7.094, p= 0.009). The odds of having MI are
1.19 times more in HT group when compare to
normal person. The 95% CI is 1.062 – 1.336.
When we compare the smoking with case and
control group it shows good significant
difference (chi sq = 18.05, p= 0.000). The odds
of having MI is 1.556 times more in smoking
group when compared to the nonsmoking
group the 95% CI is 1.28 – 1.89. When we
compare the hs-CRP with case and control
Percent
55
45
100
57.1
42.9
100
group it shows some significant difference (chi
sq = 44.88, p= 0.000). The odds of having MI
are 40.79 times more in >3 groups when
compared to those below 3 the 95% CI is
10.78-154.26.
In our study even though
Diabetes mellitus, Hypertension, Smoking
played some significant roles, it is not very
different between controls to case group. Only
because 27% of this risk factor present in case
group(patients with MI) but none in control
group(voluntary blood donors). Only hs-CRP
factor played a vital role with other variables as
well as case group. None of the variables
shows significant role in this study.
.
TABLE 8
KENDAL’S CORRELATION ANALYSIS
CORRELATIONS
Group
DM
Pearson
Correlation
Sig. (2tailed)
N
Pearson
Correlation
Sig. (2tailed)
N
DM
HT
smoking
TGL
Hs CRP
BMI
.272**
.272**
.434**
0.106
.684**
0.007
96
0.007
96
0
96
0.302
96
.632**
-0.077
0
96
0.456
96
0.087
LDL
0.021
HDL
0.169
0
96
0.401
96
0.837
96
0.099
96
0.005
.264**
-0.033
-0.14
-0.09
0.965
96
0.009
96
0.75
96
0.175
96
0.382
96
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HT
Smoking
TGL
Hs-CRP
BMI
LDL
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Pearson
Correlation
Sig. (2tailed)
N
Pearson
Correlation
Sig. (2tailed)
N
Pearson
Correlation
Sig. (2tailed)
N
Pearson
Correlation
Sig. (2tailed)
N
Pearson
Correlation
Sig. (2tailed)
N
Pearson
Correlation
Sig. (2tailed)
N
0.099
0.005
.264**
-0.033
0.068
-0.09
0.337
96
0.965
96
0.009
96
0.75
96
0.513
96
0.382
96
-0.09
.227*
-0.053
0.065
0.053
0.381
96
0.026
96
0.611
96
.205*
0.116
0.532
96
0.016
0.605
96
0.005
0.045
96
0.259
96
0.878
96
0.107
0.163
0.961
96
0.028
0.3
96
0.113
96
-0.09
0.381
96
0.784
96
0.029
0.781
96
0.086
0.406
96
**. Correlation is significant at the 0.01 level (2-tailed)
*. Correlation is significant at the 0.05 level (2-tailed)
TABLE 9
CHI SQUARE ANALYSIS.
VARIABLES
chi sq
p – value
OR
DM
HT
SMOKING
TGL
HSCRP
BMI
LDL
HDL
7.094
7.094
18.05
1.088
44.88
7.22
0.044
2.75
0.009
0.009
0.00
0.297
0.00
0.39
0.83
0.09
1.19
1.19
1.556
1.552
40.795
1.018
0.917
0.25
95% CI
Lower
1.062
1.062
1.28
0.678
10.788
0.983
0.405
0.048
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upper
1.336
1.336
1.89
3.549
154.261
1.055
2.076
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CONCLUSION
The South Indian population is unique in that
the traditional risk factors have a very minor
role to play in the causation of Myocardial
infarction. The only signification association
that could also be regarded as a screening test
to detect susceptible for MI is hs-CRP and this
is in turn only a marker that inflammatory
changes have taken place in the vessel wall.
The risk factor identification should be unique
in the Indian population and should include a
battery of tests for infectious diseases. In all
these, a huge representative population should
be tested for baseline titres for all the infections
that have shown some relationship with MI.
Then we should be in a position to say what
would be the cutoff titres in order to define a
rise in titre. Thirdly there should be trials to
focus on medical interventions to halt the
infections which lead up to inflammation in the
coronary vessels and MI. This is where our
primary focus needs to be.
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