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ISSN 0975-6299 Vol 3/Issue 1/Jan – Mar 2012 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. This article can be downloaded from www.ijpbs.net P - 123 ISSN 0975-6299 Vol 3/Issue 1/Jan – Mar 2012 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. This article can be downloaded from www.ijpbs.net P - 124 ISSN 0975-6299 Vol 3/Issue 1/Jan – Mar 2012 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 This article can be downloaded from www.ijpbs.net P - 125 ISSN 0975-6299 Vol 3/Issue 1/Jan – Mar 2012 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. This article can be downloaded from www.ijpbs.net P - 126 ISSN 0975-6299 Vol 3/Issue 1/Jan – Mar 2012 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 This article can be downloaded from www.ijpbs.net P - 127 ISSN 0975-6299 Vol 3/Issue 1/Jan – Mar 2012 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 This article can be downloaded from www.ijpbs.net P - 128 ISSN 0975-6299 Vol 3/Issue 1/Jan – Mar 2012 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 This article can be downloaded from www.ijpbs.net P - 129 ISSN 0975-6299 HT Smoking TGL Hs-CRP BMI LDL Vol 3/Issue 1/Jan – Mar 2012 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 This article can be downloaded from www.ijpbs.net P - 130 upper 1.336 1.336 1.89 3.549 154.261 1.055 2.076 1.411 ISSN 0975-6299 Vol 3/Issue 1/Jan – Mar 2012 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. 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