Cardiometabolic risk factors associated with coronary artery disease in Asian Indian population

Kaur S¹, Bhatti GK², Saini NK³, Vijayvergiya R⁴, Tewari R¹, Bhatti JS¹

1. Introduction

Cardiovascular diseases (CVD) have become a crucial social health problem in India and other developing countries [1, 2]. The facts show that these diseases are flourishing in these countries as compare to developed nations of Europe and North America [3, 4]. Coronary artery disease (CAD) being the major killer in developed countries is now promptly thriving in developing countries [5]. The South Asian Countries share most of the burden of cardiovascular diseases in comparison with any other region globally [6-8]. Recent estimates predicts that cardiovascular diseases will be the greatest cause of death and disability in India by 2020 [9]. Various studies have had suggested that age is a significant factor to which the risk factors of CVD are linked [10-12]. The cardiovascular risk for men and women, is known to escalate with age, smoking, hypertension, blood lipids and glucose levels, and central obesity [13]. The fact remains that the problems of high blood pressure and obesity, considered to be the major risk factors for CVD, are increasingly assuming global importance [14]. The major established cardiovascular risk factors include hypertension, smoking, hypercholesterolemia and type 2 diabetes mellitus [15, 16]. The majority of patients who develop CAD have at least one of these risk factors. The risk factors related to urban lifestyle such as unhealthy diet and sedentary lifestyle complement insulin resistance further ensuing cardiovascular risk. Many studies have been carried out in south Indians but data on north Indian population is scanty. So, this study was planned to determine the metabolic risk factors associated with the high prevalence of CAD in Asian Indian population.

2. Materials and Methods

Human subjects

The present study was commenced in year 2011 with the objective of identification of genetic and environmental risk factors associated with CAD in North Indian population. The study was verbally explained to all the participants and adequate opportunities were given for discussion with the interviewer. Informed written consent was then obtained from all the study subjects. All the protocols were approved by Institutional Ethics Committees of Panjab University, Chandigarh and Post Graduate Institute of Medical Education and Research, Chandigarh, India.

In this study, we included 1375 participants, among which 715 subjects were healthy controls and 660 subjects were angiographically confirmed CAD patients recruited from OPD of Advanced Cardiac Centre, PGIMER, Chandigarh. Potential participants identified were invited to participate in this study. After confirming eligibility, a full clinical examination was performed on each participant. The diagnosis of the occurrence of CAD was performed by cardiologist based on the clinical symptoms, characteristic ECG changes, cardiac enzyme levels, and the findings in coronary angiography and/or echocardiography. Other health conditions were documented based on self-reported history of diabetes, hypertension and related complications. Family history for all of the above conditions was also obtained. A detailed questionnaire was administered to each participant regarding their demographic and socioeconomic characteristics like participant’s self-reported age, sex, educational status, family history and individual’s smoking and alcohol use.

Inclusion/ Exclusion criteria

Individuals aged 25 years and above, irrespective of disease status were included in this study. Participants belonging to north Indian states only were included in this study.

Anthropometric measurements

Standard anthropometric measurements were performed including height, weight, waist and hip circumferences and blood pressure. Waist and Hip circumference was measured with a metal tape using standard protocols. Height was measured with a stature meter and weight with a portable balance beam scale. Blood pressure was measured by Omron blood pressure machine in sitting position from the left arm resting on the table, with legs uncrossed and feet flat.

Biochemical estimations

About 5 ml of blood sample of each patient was drawn in plain and EDTA coated vials. Quantitative lipid profile [total cholesterol (TC), triglycerides (TG), high density lipoprotein (HDL), and creatinine content were measured in serum by using standard kits (Roche Diagnostics, GmbH, Mannheim, Germany). Low-density lipoprotein (LDL) level was calculated by using Friedewald formula i.e. LDL-C = TC – [HDL-C – (TG in mg/dl/5)]. Fasting and random blood glucose levels were measured using a portable glucometer (Abbott OptiumXceed, USA). Calibration of the glucometer was routinely verified using test strips provided by the manufacturers. All the quantitative parameters were measured by following manufacturer’s instructions using biochemistry autoanalyzer.

Quantitative measures of obesity

Body Mass Index (BMI) was calculated according to Quetelet equation i.e. (BMI = weight in kilograms/height in meters squared). Waist to Hip Ratio (WHR) was calculated as ratio of abdomen to hip circumferences. Anthropometric measurements used for the establishment of abdominal obesity were according to the cut off values for Asian Indians. Body fat percentage (BF %) was calculated according to the method of Lean et al. [17] using following formulae; BF% for men = [(0.567 × waist circumference in cm) + (0.101 × age in years)] − 31.8; and BF% for women = [(0.438 × waist circumference in cm) + (0.221 × age in years)] − 9.4.

Phenotypic characteristics

The abdominal obesity was measured according to the new cut offs proposed for South Asian Indians [18] i.e. WHR >0.89 for men and > 0.81 for women. BMI <23 2 kg/m has been proposed for low risk, 23- 2 27.5 kg/m for increased risk and ≥27.5 kg/m2 for high risk for developing weight- related diseases in Asian populations. Dyslipidemia is the elevation of cholesterol (>200mg/dl), triglycerides (>150mg/dl) or both, or a low HDL level (<40 mg/dl in men and <50 mg/dl in women)that contributes to the development of atherosclerosis. Hypertension was defined as a persistent elevation of blood pressure ≥140/≥90 mmHg or use of any antihypertensive medication.

Statistical Analysis

Results were expressed as mean ± SD. Chisquare analysis was applied to test the significance of differences in frequencies. Group comparisons were done using unpaired t-tests. All the p-values <0.05 (two-tailed) were considered as significant difference. Logistic regression analysis were performed to correlate various clinical parameters with disease and to calculate odds ratios (ORs) and 95% CIs for each risk factor. Statistical

analysis was performed using IBM-SPSS for Windows, version 20 (SPSS, Inc., Chicago, IL).

3. Result and Discussion

Among 1375 participants, 715 subjects were healthy controls (307 Men and 408 Women) and 660 subjects were CAD patients (525 Men and 135 Women). During this study, 166 subjects were diagnosed with CAD after their first visit to the hospital as they were showing symptoms of CAD earlier. The disease status of all these newly diagnosed CAD patients was confirmed after undergoing angiography procedures.

The demographic and socioeconomic characteristics of study participants are summarized in Table 1. Most of the participants originated from Chandigarh followed by Punjab, Haryana, Himachal and other parts of North India and belonged to Hindu (51.9%) and Sikh communities (46%). Only 2% belong to Muslim and Christian communities. A significant difference was observed between CAD patients and control subjects in respect of socio-economic status and eating habits. Alcohol consumption was significantly higher in CAD patients and may increase the risk of CAD in this population (OR, with 95% CI; 2.9 (2.22-3.89) P=0.000). The physical activity was significantly lower in CAD patients than controls. Due to religious belief, Sikhs and most of the Indian women don’t smoke.

However, smoking emerged as a major risk factor for developing CAD in this population (OR, with 95% CI; 5.2 (3.34-8.09) p=0.000). Unlike Western populations, the frequency of non-vegetarian diet among all the participants (38.8%), in general, was very low (once a week or once a month) with the exception of <3.1% of individuals who were regularly following a non-vegetarian diet. Also, consumption of hydrogenated oil (trans fat) and mixed oils used in daily cooking may increase the risk of CAD many folds in our study (OR, with 95% CI; 4.782 (2.817-8.119), p=0.000 and 3.03 (2.298- 3.995, p=0.000), respectively.

Age specific prevalence of CAD is shown in the Figure 1. Present data demonstrated that prevalence of CAD increased with age especially after 55 years and has the strongest age associated risk for CAD among Asian Indians. One-third CAD patients developed this disease at a mean age of 58 years having the duration of 1-6

The maximum number of CAD patients were in the age range of 51-70 years. Logistic regression analysis of the data established that our population has the strongest age associated risk for developing CAD in the age interval of 55-65 years (OR with 95% CI is 5.387 (3.821-7.594); p=0.000) and >65 years age group (OR; 8.101 (5.417-12.11); P=0.000).

Table 2 shows the anthropometric measurements in the study subjects. A significance difference in the mean age of the CAD patients (58.6±11.2 years) and healthy controls (49.5±10.8 years) was observed (p=0.000). Most of the CAD patients develop this condition in the most productive years of their life which is 10-15 years earlier and remain undiagnosed for many years. A majority of the CAD patients were suffering from hypertension and were taking anti-hypertensive drugs to limit their blood pressure levels to normal.

Abdominal obesity reflected by higher waist circumference was predicted as one of the major risk factor for the development of CAD in our study (Figure 2). Pragmatically, the control subjects were found to be at a high risk of developing metabolic disorders, due to their significantly higher BMI as

However, CAD patients had marked abdominal adiposity as reflected by their significantly higher WHR when compared with control subjects. Following stratification of the data, taking BMI cutoffs into account by WHO Expert Consultation, 2004, we observed pronounced central obesity in both CAD patients and controls (Figure 3), even at the lowest BMI values 2 (<23kg/m ). Present study demonstrated that 68.8% of controls and 64.8% of CAD patients fall under the higher limits of waist

SBP, Systolic Blood Pressure; DBP, Diastolic Blood Pressure; WHR, Waist to Hip ratio; BMI, Body Mass WC, Waist Circumference; HC, Hip Circumference; Index circumference recommended for Asian Indians, reflecting a strong predisposition to cardiometabolic abnormalities in our population. Body fat percent was significantly higher in control subjects than CAD patients (p=0.000). Also significantly higher body fat was observed in women CAD patients (43.8±5.9) than their male

Table 3 shows the clinical characteristics in the CAD patients and healthy control subjects. The mean glucose level was significantly higher in CAD patients than in control subjects. The influence of dyslipidemia in the progression of CAD is well established. Our study demonstrated significantly higher levels of TC, TG, LDL and VLDL in control subjects than CAD patients, the reason being most of the CAD patients were taking lipid lowering drugs. Also CAD patients are very regular in taking prescribed medicines along with daily exercises/sports. Present data also revealed that the males have slightly higher HDL level than normal but all female subjects were having below normal value of HDL- cholesterol. The reduced HDL-cholesterol and elevated creatinine values observed in CAD patients may have contributed to the pathophysiology of CAD and renal dysfunctioning in this study. In an attempt to optimize the predictive capacity of the lipid profile, atherogenic indices have been defined. The TC/HDL ratio and the LDL/HDL cholesterol ratio are two important components and indicators of vascular risk, the predictive value of which is greater than the isolated parameters. These ratios can provide information on risk factors difficult to quantify by routine analysis and could be a better representation of the metabolic and clinical interactions between lipid fractions. In the control subjects, 33.2% and 26.9% individuals have significantly greater primary cardiovascular risk as demonstrated by atherogenic indices i.e. TC/HDL and LDL/HDL ratios owing to the imbalance between the cholesterol carried by atherogenic and protective lipoproteins.

Discussion

There has been an alarming increase in the prevalence of cardiovascular mortality in India and other south Asian countries [19- 21]. CVD is a multifactorial disease in which both environmental and genetic factors interplay [22]. In the present study, we have identified various cardiometabolic risk factors such as low SES, smoking, alcohol consumption, low physical activity alongwith bad combination of cooking media, which are associated with high prevalence to CVD in Indian population. Our results are inconsistent with other studies carried out in Asian Indians [19-21, 23, 24]. Indian economy growing at a rapid pace has induced inequities in education, incomes and socioeconomic status [25], resulting poor health status [26]. In addition, a reversal of socio-economic gradients for CAD risk factors has emerged in the Indian population [27, 28]. In developed countries where the epidemic has been there for many decades, high incidence of CAD first occurred in high socio-economic group followed by a reversal of the trend. Studies in India over the past half century have

TC, Total Cholesterol; TG, Triglycerides; HDL, High Density Lipoprotein; LDL, Low Density Lipoprotein; VLDL, Very Low Density Lipoprotein

status

Mean SD

Control 92.44 11.57

Glucose

(mg/dl)

CAD Patient 100.28 15.18 Control 188.69 45.66 TC

(mg/dl)

CAD Patient 151.34 43.37 Control 164.60 81.67 TG

(mg/dl)

CAD Patient 148.59 66.53 Control 45.30 7.18

HDL(mg/dl)

CAD Patient 42.90 5.96 Control 110.47 42.89

LDL(mg/dl)

CAD Patient 78.72 41.77 Control 32.92 16.33

VLDL(mg/dl)

CAD Patient 29.72 13.31 Control 545.51 156.05

Total Lipids (mg/dl)

CAD Patient 451.26 123.03 Control 4.28 1.31

TC/HDL ratio

CAD Patient 3.60 1.19 Control 2.49 1.18

LDL/HDL

ratio

CAD Patient 1.88 1.06 Control 0.95 1.05

Creatinine (mg/dl)

CAD Patient 1.09 0.91

p Mean SD p Mean SD p

92.44 10.72 92.44 11.07 0.000 0.000 0.000 97.52 13.47 99.67 14.85 195.89 42.96 192.83 44.24 0.000 0.000 0.000 162.68 47.45 153.79 44.48 145.22 62.28 153.46 71.76 0.005 0.542 0.107 141.26 54.36 147.00 64.11 46.17 8.22 45.80 7.80 0.000 0.039 0.000 44.37 7.93 43.22 6.46 120.68 41.91 116.34 42.60 0.000 0.000 0.000 90.06 42.87 81.17 42.23 29.04 12.46 30.69 14.35 0.005 0.542 0.107 28.25 10.87 29.40 12.82 537.00 121.01 540.62 136.96 0.000 0.000 0.000 466.63 132.10 454.59 125.08 4.37 1.24 4.33 1.27 0.000 0.000 0.000 3.79 1.47 3.64 1.26 2.72 1.13 2.62 1.16 0.000 0.000 0.000 2.12 1.23 1.93 1.10 0.75 0.41 0.83 0.76 0.102 0.001 0.000 0.90 0.37 1.04 0.81 revealed a similar trend towards a progressive reversal of the social gradient for CAD. The prevalence of CAD has also risen substantially in India [29, 30] and was reported to be higher in urban than in rural areas [31]. Our study showed that alcohol consumption and smoking increased the risk of developing CAD among study population. Smoking was also shown to predispose to CAD through a variety of mechanisms [32]. Our findings that highand middle-income groups had a significant risk of having CAD are consistent with the previous studies done in north India [33]. Highly educated persons and those belonging to the most affluent class had significantly greater consumption of calories, polyunsaturated fats, fruits, vegetables and fibers as compared to the most deprived men and women.

Our study demonstrated the enhanced risk of CAD with use of hydrogenated oil and mixed oils on daily basis. Amongst Asian Indian vegetarians, the lipoprotein levels are not different from non-vegetarians [34, 35]. This trend is due to contaminated vegetarianism, where vegetarians consume profuse amounts of dairy, butter, ghee, cheese and bakery products, all of them are major sources of saturated fat and/or trans unsaturated fatty acid [34]. A research study signifies that a diet very low in fat and very high in carbohydrate can intensify dyslipidemia by increasing triglycerides and decreasing HDL levels [36].

Epidemiological studies from various parts of India have reported the rising trends and a high burden in the levels of conventional risk factors such as diabetes, hypertension and metabolic syndrome which are largely determined by urbanization as evident from the urban-rural difference in the risk factors observed in India [37-39]. The major established cardiovascular risk factors include hypertension, smoking, hypercholesterolemia and type 2 diabetes mellitus [16, 40]. Various explanations have been anticipated for this extreme vascular risk including variation in access to healthcare, risk factor burden and clustering and socioeconomic variables [41]. While the exact aetiology of this predisposition to CVD among Indians is still debated, rapid transition in diet and lifestyles with urbanization are identified as the major contributors to this epidemic [6]. Elevated blood pressure is a significant risk factor for the progression of CVD [42].

Some metabolic abnormalities were more prevalent among Asian Indians, including high triglyceride, type 2 diabetes mellitus, and central or visceral obesity [43, 44]. The present study demonstrated low physical activity, abdominal obesity and dyslipidemia as major cardiometabolic risk factors in predisposition of CAD among study subjects. The typical “Asian Indian phenotype” refers to a blend of clinical, biochemical and metabolic abnormalities that are more common in individuals of South Asian origin and thus tendency of this group for developing diabetes and premature CAD [45, 46]. Previous studies showed lower physical activity as a major risk among the CAD patients [23, 47, 48]. About 12% of the global burden of myocardial infarction is because of sedentary lifestyle [49]. The waist circumference, glucose and insulin levels, BMI, were inversely related with levels of physical activity in South Asians [50].

Various studies have quoted that age is the main factor to which the CVD risk factors are related [10]. CVD results in substantial number of deaths in working age group in India as it manifests here almost 10 year prior on an average than other countries in the world [51]. This demographic transition has brought most people to the age group where the CVDs perceive. Thus, a larger population of liable adults in India confers to the CVD inflicted population. Lower physical activity scores have been reported in South Asians compared with white populations [50, 52, 53]. Levels of physical activity were inversely associated with BMI, waist circumference, glucose and insulin levels in South Asians [50]. The data showing physical activity suggested that those leading a sedentary lifestyle developed CAD and other metabolic diseases more frequently than those with an occupation or routine life involving more physical work. Consistently, South Asians and Asian Indians have been shown to be less physically active when compared with other ethnic groups [24].

Prevalence of overweight and obesity was highest in southern and northern Indian states and lowest in central Indian states [54]. Although possessing lower prevalence of obesity as defined by BMI, Asian Indians are predisposed to have greater waist circumference and waist-to-hip ratios, contributing to greater degree of central obesity. Our study depicted similar results with majority of the study subjects having greater waist circumference. Also, the BMI<25 was observed in the CAD patients. The traditional cut-off point of BMI of 25 might not define overweight and obesity optimally in Asian Indians as they have higher percentage of body fat compared to whites [55]. Among CAD patients, women tend to have significantly more body fat percent as compared to men. Asian Indians have more total abdominal and visceral fat for any given BMI, and for any given body fat they have increased insulin resistance [56, 57]. The higher incidence of CVD events in obese patients seems to be associated to endothelial dysfunction and subclinical inflammation in addition to the worsening of CVD risk factors [58] Present finding concurs with an Indian study [59] which showed that only 8.2% of patients with angiographically proven CAD had a BMI >27 kg/m2 but contrasts with western studies which have shown a strong association of BMI with hyperglycaemia and dyslipidaemia [60, 61]. High BMI is associated with the development of cardiovascular (CV) risk factors such as hypertension, dyslipidemia, insulin resistance, and diabetes mellitus leading to cardiovascular diseases such as coronary heart disease (CHD) and ischemic stroke [62-64]. The development of these co morbidities is proportionate to the BMI and obesity is considered as an independent risk factor for CVD [65, 66]. Several studies have documented that a high BMI is significantly associated, in both men and women, with manifestations of CVD such as angina, myocardial infarction (MI), heart failure and sudden death [67, 68]. The higher incidence of CVD events in obese patients seems to be related to endothelial dysfunction and subclinical inflammation in addition to the worsening of CVD risk factors.[58] Despite having lower prevalence of obesity as defined by BMI, Asian Indians tend to have greater waist circumference and waist-tohip ratios, thus having a greater degree of central obesity. Again, Asian Indians have more total abdominal and visceral fat for any given BMI, and for any given body fat they have increased insulin resistance [56, 57]. The body fat (%) is a measure of physical fitness. Women tend to have greater essential fat than men because of child bearing and hormonal functions. In our study, central obesity reflected by higher waist circumference and WHR may contribute a major cardiometabolic risk in Asian Indians. A study in 52 countries showed that more than 80% of the global burden of CAD could be attributed to these main established risk factors and to a lack of exercise [49].

Dyslipidemia is more prominent in Asian Indians and poses a major threat for the development of CAD in our population. Once diagnosed with CAD, regular use of lipid lowering drugs by CAD patients limits the lipid profile to near normal values. High LDL-C levels considered as bad cholesterol leads to the formation of plaque in the artery, hence causing CAD. Previous studies showed that this LDL-particle phenotype represented an independent risk factor for CAD [69, 70]. Many studies have reported that Asians have higher prevalence of lipid abnormalities compared with non-Asians [71, 72]. Our study showed higher TC, TG and LDL-cholesterol among the control subjects when compared with CAD patients. The probable reason for this pattern may be the regular intake of lipid lowering drugs by CAD patients. Lipid lowering drugs such as statins inhibit 3-hydroxy-methylglutaryl coenzyme A (HMG-CoA) reductase enzyme which is responsible for the reduction in the serum low-density lipoprotein (LDL)- cholesterol level. The statins also have demonstrated efficacy in patients with a broad range of initial cholesterol levels but without coronary artery disease and in patients with average cholesterol levels and coronary artery disease. Intensive lipidlowering therapy with statins not only improves survival rates and clinical outcomes but also reduces the progression of atherosclerosis [73-76]. The study also showed decreased HDL and increased creatinine levels among CAD patients. Low levels of HDL cholesterol have been shown to be a powerful risk factor for CAD [77]. Classic cardiovascular risk factors such as age, gender, smoking, type 2 diabetes, hypertension, high LDL and low HDL cholesterol levels have been widely established as independent cardiovascular risk factors [78]. Furthermore, the TC/HDL and LDL/HDL ratios are of great interest as major predictors of cardiovascular disease. Previous studies suggested TC/HDL ratio as a powerful coronary risk predictor than independently used total cholesterol, LDL cholesterol and HDL cholesterol [79, 80] Insulin resistance was shown to increase the risk of both T2DM [81, 82] and CVD [83]. The increased prevalence of insulin resistance and T2DM in South Asians appears to be a major contributor to the observed elevated vascular risk. The hyperinsulinemia in these patients accelerates the atherosclerotic process in the coronary arteries. Hyperinsulinemia, insulin resistance, and the higher rate of prevalence of metabolic syndrome in people with type-2 diabetes were attributed to high coronary risk in south Asians [39, 84-89]. In conclusion, present study established the major cardiometabolic risk factors in north Indian population. We observed an early progression to CAD which, in part, is due to the physiologic attributes, such as upperbody adiposity as evident by a high WHR, body fat percent, physical inactivity, hypertension and low HDL-Cholesterol. Large studies need to be conducted to determine whether a genetic predisposition can be one of the contributing factors in the pathogenesis of CAD in this population.

Acknowledgments

Support for this study was provided by University Grant Commission, India. We would like to thank all the participants and volunteers for support.

Conflict of Interest: None declared.

References

References

1. Gaziano TA: Cardiovascular disease in the developing world and its cost-effective management. Circulation 2005; 112:3547- 3553.
2. Joshi SR, Parikh RM: India--diabetes capital of the world: now heading towards hypertension. J Assoc Physicians India
3. Gaziano T, Reddy KS, Paccaud F, Horton S, Chaturvedi V: Cardiovascular Disease. In Disease Control Priorities in Developing Countries. 2nd edition. Edited by Jamison DT, Breman JG, Measham AR, Alleyne G, Claeson M, Evans DB, Jha P, Mills A, Musgrove P. Washington (DC); 2006
4. Murray CJ, Lopez AD: Alternative projections of mortality and disability by cause 1990-2020: Global Burden of Disease Study. Lancet 1997; 349:1498- 1504.
5. Ortega FB, Lavie CJ, Blair SN: Obesity and Cardiovascular Disease. Circ Res 2016;
6. Reddy KS, Yusuf S: Emerging epidemic of cardiovascular disease in developing countries. Circulation 1998; 97:596-601.
7. Yusuf S, Reddy S, Ounpuu S, Anand S: Global burden of cardiovascular diseases: part I: general considerations, the epidemiologic transition, risk factors, and impact of urbanization. Circulation 2001;
8. Reddy KS: Cardiovascular disease in nonWestern countries. N Engl J Med 2004;
9. WHO: The World Health Report 2002. Geneva, Switzerland 2002.
10. Eisenmann JC, Malina RM: Age-related changes in subcutaneous adipose tissue of adolescent distance runners and association with blood lipoproteins. Ann Hum Biol 2002; 29:389-397.
11. Ali MK, Bhaskarapillai B, Shivashankar R, Mohan D, Fatmi ZA, Pradeepa R, Masood Kadir M, Mohan V, Tandon N, Venkat Narayan KM, Prabhakaran D: Socioeconomic status and cardiovascular risk in urban South Asia: The CARRS Study. Eur J Prev Cardiol 2015.
12. Gupta R, Misra A, Vikram NK, Kondal D, Gupta SS, Agrawal A, Pandey RM: Younger age of escalation of cardiovascular risk factors in Asian Indian subjects. BMC Cardiovasc Disord 2009; 9:28.
13. WHO: Cardiovascular Diseases (CVDs).WHO Fact Sheet. 2011.
14. WHO: Obesity: Preventing and managing the global epidemic. In WHO Technical Series 894. Geneva: WHO; 2000.
15. Greenland P, Knoll MD, Stamler J, Neaton JD, Dyer AR, Garside DB, Wilson PW: Major risk factors as antecedents of fatal and nonfatal coronary heart disease events. JAMA 2003; 290:891-897.
16. Khot UN, Khot MB, Bajzer CT, Sapp SK, Ohman EM, Brener SJ, Ellis SG, Lincoff AM, Topol EJ: Prevalence of conventional risk factors in patients with coronary heart disease. JAMA 2003; 290:898-904.
17. Lean ME, Han TS, Bush H, Anderson AS, Bradby H, Williams R: Ethnic differences in anthropometric and lifestyle measures related to coronary heart disease risk between South Asian, Italian and generalpopulation British women living in the west of Scotland. Int J Obes Relat Metab Disord 2001; 25:1800-1805.
18. Snehalatha C, Viswanathan V, Ramachandran A: Cutoff values for normal anthropometric variables in asian Indian adults. Diabetes Care 2003; 26:1380- 1384.
19. Gupta R, Joshi P, Mohan V, Reddy KS, Yusuf S: Epidemiology and causation of coronary heart disease and stroke in India. Heart 2008; 94:16-26.
20. Ramaraj R, Chellappa P: Cardiovascular risk in South Asians. Postgrad Med J 2008;
21. Nag T, Ghosh A: Cardiovascular disease risk factors in Asian Indian population: A systematic review. J Cardiovasc Dis Res
22. Raj R, Bhatti JS, Badada SK, Ramteke PW: Genetic basis of dyslipidemia in disease precipitation of coronary artery disease (CAD) associated type 2 diabetes mellitus (T2DM). Diabetes Metab Res Rev 2014.
23. Prasad DS, Das BC: Physical inactivity: a cardiovascular risk factor. Indian J Med Sci
24. Jepson R, Harris FM, Bowes A, Robertson R, Avan G, Sheikh A: Physical activity in South Asians: an in-depth qualitative study to explore motivations and facilitators. PLoS One 2012; 7:e45333.
25. Panagariya A: India: The emerging giant. Oxford University Press; 2008.
26. Marmot M: Health in an unequal world: social circumstances, biology and disease. 2006.
27. Ajay V, Prabhakaran D, Jeemon P, Thankappan K, Mohan V, Ramakrishnan L, Joshi P, Ahmed F, Mohan B, Chaturvedi V: Prevalence and determinants of diabetes mellitus in the Indian industrial population. Diabetic Medicine 2008;
28. Reddy KS, Prabhakaran D, Jeemon P, Thankappan K, Joshi P, Chaturvedi V, Ramakrishnan L, Ahmed F: Educational status and cardiovascular risk profile in Indians. Proceedings of the National Academy of Sciences 2007; 104:16263- 16268.
29. Mohan V, Deepa R, Rani SS, Premalatha G: Prevalence of coronary artery disease and its relationship to lipids in a selected population in South India: The Chennai Urban Population Study (CUPS No. 5). J Am Coll Cardiol 2001; 38:682-687.
30. Ghaffar A, Reddy KS, Singhi M: Burden of non-communicable diseases in South Asia. BMJ 2004; 328:807-810.
31. Ahmad N, Bhopal R: Is coronary heart disease rising in India? A systematic review based on ECG defined coronary heart disease. Heart 2005; 91:719-725.
32. Tsiara S, Elisaf M, Mikhailidis DP: Influence of smoking on predictors of vascular disease. Angiology 2003; 54:507-
34. Gupta R, Gupta VP, Sarna M, Bhatnagar S, Thanvi J, Sharma V, Singh AK, Gupta JB, Kaul V: Prevalence of coronary heart disease and risk factors in an urban Indian population: Jaipur Heart Watch-2. Indian Heart J 2002; 54:59-66.
35. Yagalla MV, Hoerr SL, Song WO, Enas E, Garg A: Relationship of diet, abdominal obesity, and physical activity to plasma lipoprotein levels in Asian Indian physicians residing in the United States. J Am Diet Assoc 1996; 96:257-261.
36. Enas EA, Garg A, Davidson MA, Nair VM, Huet BA, Yusuf S: Coronary heart disease and its risk factors in first-generation immigrant Asian Indians to the United States of America. Indian Heart J 1996;
37. Abbasi F, McLaughlin T, Lamendola C, Kim HS, Tanaka A, Wang T, Nakajima K, Reaven GM: High carbohydrate diets, triglyceriderich lipoproteins, and coronary heart disease risk. Am J Cardiol 2000; 85:45-48.
38. Prabhakaran D, Chaturvedi V, Shah P, Manhapra A, Jeemon P, Shah B, Reddy KS: Differences in the prevalence of metabolic syndrome in urban and rural India: A problem of urbanization. Chronic Illness 2007.
39. Gupta R: Trends in hypertension epidemiology in India. J Hum Hypertens 2004, 18:73-78.
40. Mohan V, Sandeep S, Deepa R, Shah B, Varghese C: Epidemiology of type 2 diabetes: Indian scenario. Indian J Med Res 2007, 125:217-230.
41. Greenland P, Knoll MD, Stamler J, Neaton JD, Dyer AR, Garside DB, Wilson PW: Major risk factors as antecedents of fatal and nonfatal coronary heart disease events. JAMA 2003; 290:891-897.
42. Albert MA, Ridker PM: C-reactive protein as a risk predictor: do race/ethnicity and gender make a difference? Circulation 2006; 114:e67-74.
43. Dasgupta K, Padwal R, Poirier L, Quinn RR, Bacon S, Feldman RD, Hackam DG, Herman RJ, Khan N, Rabi DM, et al: Managing hypertension: evidence supporting the 2013/2014 recommendations of the Canadian Hypertension Education Program. CMAJ
44. Ghosh A, Bose K, Chaudhuri ABD: Association of food patterns, central obesity measures and metabolic risk factors for coronary heart disease (CHD) in middle aged Bengalee Hindu men, Calcutta, India. Asia Pacific journal of clinical nutrition 2003; 12:166-171.
45. Bhatti GK, Bhadada SK, Vijayvergiya R, Mastana SS, Bhatti JS: Metabolic syndrome and risk of major coronary events among the urban diabetic patients: North Indian Diabetes and Cardiovascular Disease Study-NIDCVD-2. J Diabetes Complications
46. Ali MK, Narayan KM, Tandon N: Diabetes & coronary heart disease: current perspectives. Indian J Med Res 2010;
47. Mohan V, Venkatraman JV, Pradeepa R: Epidemiology of cardiovascular disease in type 2 diabetes: the Indian scenario. J Diabetes Sci Technol 2010; 4:158-170.
48. 47. Shah B, Mathur P: Surveillance of cardiovascular disease risk factors in India: the need & scope. Indian J Med Res
49. Gupta R, Deedwania PC, Sharma K, Gupta A, Guptha S, Achari V, Asirvatham AJ, Bhansali A, Gupta B, Gupta S, et al: Association of educational, occupational and socioeconomic status with cardiovascular risk factors in Asian Indians: a cross-sectional study. PLoS One 2012; 7:e44098.
50. Yusuf S, Hawken S, Ounpuu S, Dans T, Avezum A, Lanas F, McQueen M, Budaj A, Pais P, Varigos J, Lisheng L: Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. Lancet 2004; 364:937-
52. Hayes L, White M, Unwin N, Bhopal R, Fischbacher C, Harland J, Alberti KG: Patterns of physical activity and relationship with risk markers for cardiovascular disease and diabetes in Indian, Pakistani, Bangladeshi and European adults in a UK population. J Public Health Med 2002; 24:170-178.
53. Gupta R: Burden of coronary heart disease in India. Indian Heart J 2005; 57:632-638.
54. Fischbacher CM, Hunt S, Alexander L: How physically active are South Asians in the United Kingdom? A literature review. J Public Health (Oxf) 2004; 26:250-258.
55. McKeigue PM, Pierpoint T, Ferrie JE, Marmot MG: Relationship of glucose intolerance and hyperinsulinaemia to body fat pattern in south Asians and Europeans. Diabetologia 1992; 35:785-
57. Wang Y, Chen HJ, Shaikh S, Mathur P: Is obesity becoming a public health problem in India? Examine the shift from under- to overnutrition problems over time. Obes Rev 2009; 10:456-474.
58. Joshi PP: Why is coronary heart diseases increasing in Indians? Cardiovascular risk factors in the Indian scenario. South Asian J Prev Cardiol 2003; 7:4.
59. Reddy KK, Rao AP, Reddy TP: Socioeconomic status and the prevalence of coronary heart disease risk factors. Asia Pac J Clin Nutr 2002; 11:98-103.
60. Misra A, Chowbey P, Makkar BM, Vikram NK, Wasir JS, Chadha D, Joshi SR, Sadikot S, Gupta R, Gulati S, et al: Consensus statement for diagnosis of obesity, abdominal obesity and the metabolic syndrome for Asian Indians and recommendations for physical activity, medical and surgical management. J Assoc Physicians India 2009; 57:163-170.
61. Rossi R, Iaccarino D, Nuzzo A, Chiurlia E, Bacco L, Venturelli A, Modena MG: Influence of body mass index on extent of coronary atherosclerosis and cardiac events in a cohort of patients at risk of coronary artery disease. Nutr Metab Cardiovasc Dis 2011; 21:86-93.
62. Thomas CS, Krishnaswami S: Distribution of Body Mass Index in Indian patients with coronary artery disease. Indian Heart J
63. Tavani A, Bertuzzi M, Gallus S, Negri E, La Vecchia C: Diabetes mellitus as a contributor to the risk of acute myocardial infarction. J Clin Epidemiol 2002;
64. Brown CD, Higgins M, Donato KA, Rohde FC, Garrison R, Obarzanek E, Ernst ND, Horan M: Body mass index and the prevalence of hypertension and dyslipidemia. Obes Res 2000; 8:605-619.
65. Wilkins K, Campbell NR, Joffres MR, McAlister FA, Nichol M, Quach S, Johansen HL, Tremblay MS: Blood pressure in Canadian adults. Health Rep 2010; 21:37-
67. Poirier P, Giles TD, Bray GA, Hong Y, Stern JS, Pi-Sunyer FX, Eckel RH: Obesity and cardiovascular disease: pathophysiology, evaluation, and effect of weight loss: an update of the 1997 American Heart Association Scientific Statement on Obesity and Heart Disease from the Obesity Committee of the Council on Nutrition, Physical Activity, and Metabolism. Circulation 2006; 113:898-
69. Wormser D, Kaptoge S, Di Angelantonio E, Wood AM, Pennells L, Thompson A, Sarwar N, Kizer JR, Lawlor DA, Nordestgaard BG, et al: Separate and combined associations of body-mass index and abdominal adiposity with cardiovascular disease: collaborative analysis of 58 prospective studies. Lancet
70. Poirier P, Giles TD, Bray GA, Hong Y, Stern JS, Pi-Sunyer FX, Eckel RH: Obesity and cardiovascular disease: pathophysiology, evaluation, and effect of weight loss. Arterioscler Thromb Vasc Biol 2006;
71. Poirier P, Eckel R: Obesity and cardiovascular disease. Curr Atheroscler Rep 2002, 4:448-453.
72. Rabkin SW, Mathewson FA, Hsu PH: Relation of body weight to development of ischemic heart disease in a cohort of young North American men after a 26 year observation period: the Manitoba Study. Am J Cardiol 1977; 39:452-458.
73. Hubert HB, Feinleib M, McNamara PM, Castelli WP: Obesity as an independent risk factor for cardiovascular disease: a 26-year follow-up of participants in the Framingham Heart Study. Circulation
74. Gazi IF, Tsimihodimos V, Tselepis AD, Elisaf M, Mikhailidis DP: Clinical importance and therapeutic modulation of small dense low-density lipoprotein particles. Expert Opin Biol Ther 2007; 7:53-72.
75. Lamarche B, Tchernof A, Moorjani S, Cantin B, Dagenais GR, Lupien PJ, Despres JP: Small, dense low-density lipoprotein particles as a predictor of the risk of ischemic heart disease in men. Prospective results from the Quebec Cardiovascular Study. Circulation 1997;
76. Karthikeyan G, Teo KK, Islam S, McQueen MJ, Pais P, Wang X, Sato H, Lang CC, SitthiAmorn C, Pandey MR, et al: Lipid profile, plasma apolipoproteins, and risk of a first myocardial infarction among Asians: an analysis from the INTERHEART Study. J Am Coll Cardiol 2009; 53:244-253.
77. Labreuche J, Touboul PJ, Amarenco P: Plasma triglyceride levels and risk of stroke and carotid atherosclerosis: a systematic review of the epidemiological studies. Atherosclerosis 2009; 203:331-
79. Jukema JW, Bruschke AV, van Boven AJ, Reiber JH, Bal ET, Zwinderman AH, Jansen H, Boerma GJ, van Rappard FM, Lie KI, et al.: Effects of lipid lowering by pravastatin on progression and regression of coronary artery disease in symptomatic men with normal to moderately elevated serum cholesterol levels. The Regression Growth Evaluation Statin Study (REGRESS). Circulation 1995, 91:2528-2540.
80. Nissen SE, Tuzcu EM, Schoenhagen P, Brown BG, Ganz P, Vogel RA, Crowe T, Howard G, Cooper CJ, Brodie B, et al: Effect of intensive compared with moderate lipid-lowering therapy on progression of coronary atherosclerosis: a randomized controlled trial. JAMA 2004; 291:1071- 1080.
81. Okazaki S, Yokoyama T, Miyauchi K, Shimada K, Kurata T, Sato H, Daida H: Early statin treatment in patients with acute coronary syndrome: demonstration of the beneficial effect on atherosclerotic lesions by serial volumetric intravascular ultrasound analysis during half a year after coronary event: the ESTABLISH Study. Circulation 2004; 110:1061-1068.
82. Nissen SE, Yock P: Intravascular ultrasound: novel pathophysiological insights and current clinical applications. Circulation 2001; 103:604-616.
83. Wilson PW, D'Agostino RB, Levy D, Belanger AM, Silbershatz H, Kannel WB: Prediction of coronary heart disease using risk factor categories. Circulation 1998,
84. Millan J, Pinto X, Munoz A, Zuniga M, Rubies-Prat J, Pallardo LF, Masana L, Mangas A, Hernandez-Mijares A, GonzalezSantos P, et al: Lipoprotein ratios: Physiological significance and clinical usefulness in cardiovascular prevention. Vasc Health Risk Manag 2009; 5:757-765.
85. Grover SA, Dorais M, Paradis G, Fodor JG, Frohlich JJ, McPherson R, Coupal L, Zowall H: Lipid screening to prevent coronary artery disease: a quantitative evaluation of evolving guidelines. CMAJ 2000;
86. Castelli WP, Garrison RJ, Wilson PW, Abbott RD, Kalousdian S, Kannel WB: Incidence of coronary heart disease and lipoprotein cholesterol levels. The Framingham Study. JAMA 1986; 256: 2835-2838.
87. Lillioja S, Mott DM, Spraul M, Ferraro R, Foley JE, Ravussin E, Knowler WC, Bennett PH, Bogardus C: Insulin resistance and insulin secretory dysfunction as precursors of non-insulin-dependent diabetes mellitus. Prospective studies of Pima Indians. N Engl J Med 1993;
88. Reaven GM: Banting lecture 1988. Role of insulin resistance in human disease. Diabetes 1988; 37:1595-1607.
89. Despres JP, Lamarche B, Mauriege P, Cantin B, Dagenais GR, Moorjani S, Lupien PJ: Hyperinsulinemia as an independent risk factor for ischemic heart disease. N Engl J Med 1996; 334:952-957.
90. McKeigue PM, Ferrie JE, Pierpoint T, Marmot MG: Association of early-onset coronary heart disease in South Asian men with glucose intolerance and hyperinsulinemia. Circulation 1993; 87: 152-161.
91. Anand SS, Yusuf S, Vuksan V, Devanesen S, Teo KK, Montague PA, Kelemen L, Yi C, Lonn E, Gerstein H, et al: Differences in risk factors, atherosclerosis, and cardiovascular disease between ethnic groups in Canada: the Study of Health Assessment and Risk in Ethnic groups (SHARE). Lancet 2000; 356:279-284.
92. Enas EA, Mohan V, Deepa M, Farooq S, Pazhoor S, Chennikkara H: The metabolic syndrome and dyslipidemia among Asian Indians: a population with high rates of diabetes and premature coronary artery disease. J Cardiometab Syndr 2007; 2:267-
94. Basit A, Shera AS: Prevalence of metabolic syndrome in Pakistan. Metab Syndr Relat Disord 2008; 6:171-175.
95. Misra A, Misra R, Wijesuriya M, Banerjee D: The metabolic syndrome in South Asians: continuing escalation & possible solutions. Indian J Med Res 2007;
96. Gerstein HC, Pais P, Pogue J, Yusuf S: Relationship of glucose and insulin levels to the risk of myocardial infarction: a casecontrol study. J Am Coll Cardiol 1999;