Printer Friendly

Coronary heart disease in Indians: implications of the INTERHEART study.

Introduction

India is undergoing a rapid health transition with rising burden of coronary heart disease (CHD) (1). Among adults over 20 yr of age, the estimated prevalence of CHD is around 3-4 per cent in rural areas and 8-10 per cent in urban areas, representing a two-fold rise in rural areas and a six-fold rise in urban areas between the years 1960 and 2000 (2). Studies among Indian migrants in various parts of the world have documented an increased susceptibility to CHD in comparison to the native population studied (3,4). In Britain, comparisons of age adjusted mortality statistics have shown a 40-60 per cent excess in South Asian migrants (comprising Indian) in comparison to the population of England and Wales (5). Several factors such as genetic, metabolic, early-life, conventional and non-conventional risk factors were suspected to cause high CHD morbidity and mortality rates among Indians. However, the results from the INTERHEART study conclusively established the role of behavioural and conventional risk factors in the prediction of CHD risk among Indians (6). In this report we summarize the results of the INTERHEART study and discuss its implications for India.

The INTERHEART study

The INTERHEART study, an international case-control study, carried out in 52 countries involving 15152 cases of incident acute myocardial infarction (AMI) and 14820 controls, estimated the hazard ratios and population-attributable fractions for multiple well-established physiological and behavioural risk factors for incident myocardial infarction in several regions of the world (6). This study concluded that abnormal lipids, smoking, hypertension, diabetes, abdominal obesity, psychosocial stress, decreased consumption of fruits and vegetables, moderate consumption of alcohol, and physical activity accounted for most of the risk of myocardial infarction worldwide. Collectively, these nine risk factors accounted for 90 per cent of the population attributable risk (PAR) in men and 94 per cent in women. The risk of heart attacks imposed by these risk factors was similar in both sexes, for all the population groups studied at all ages in all regions emphasizing the role of environmental origin of cardiovascular risk factors for all the ethnicities of the world. The key results from the South Asian Component of the INTERHEART study are shown in the Table. The only difference observed for South Asian population was the earlier occurrence of AMI (6). But this was explained by the higher level of risk factors particularly smoking and diabetes among Asians.

General remarks on the implications of INTERHEART

The results of INTERHEART dispelled several myths that were prevailing prior to the study. Studies in the earlier 70's, such as the North Karelia Projects, estimated that only 50 per cent of the risk for myocardial infarction could be explained by conventional risk factors (7). Subsequently it was estimated that 75 per cent of the population attributable risk could be explained by such risk factors (8). Further, simple conventional risk factors were considered to be unimportant in a number of developing countries particularly in South Asians. This was largely because of the early occurrence of CHD and excess deaths among south Asians in a relatively younger population. Therefore it was believed that non-conventional risk factors and genetic factors may play a pivotal role in determining the risk of CHD among south Asians. However, the results of INTERHEART study when considered with the results of a modelled data from cohort studies dispel this notion (9). One important observation in the INTERHEART study was the high level of risk factors even among controls who were less than sixty years of age. This observation of a larger role for conventional risk factors in increasing the risk for AMI, has important implications for Indians.

Implications for India

Epidemiological studies (largely cross-sectional surveys) 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 (10-12). Further, the long-term case fatality following acute coronary syndrome is considerably higher among Indians as compared to other populations (13). In addition, a reversal of socio-economic gradients for CHD risk factors has emerged in the Indian population (14,15). This combined with lack of support mechanisms for evidence based treatment and follow up for AMI, results in almost 49.1 per cent higher mortality among the poor as compared to richest (16). All these factors in combination lead to a large economic loss to India. The WHO has estimated that India lost 9 billion USD in national income from premature deaths due to heart disease, stroke and diabetes in the year 2005 (17). These losses are expected to cumulatively lead to 237 billion USD over the next 10 years17. These estimates highlight the need for aggressive strategies for the prevention and control of CHD in India. In this context, findings from the south Asian component of INTERHEART study convey important messages to the health care providers and policy makers in the country as all these conventional risk factors for CHD are potentially modifiable and are good starting points for prevention (18).

Policy implications

The positive impact of policy measures on chronic diseases is unequivocal (19). INTERHEART study results highlight the need for policies to promote primordial prevention strategies in India such as regulation against tobacco use and promotion of protective lifestyle factors such as leisure time physical activity and regular intake of fruits and vegetables which are markedly lower among South Asians compared to western population.

Considering the size of this public health challenge, the interventions can only be addressed through policy measures by means of legislation and regulatory approaches on agriculture and food industry (production, pricing, labelling) or tobacco (production, sale, advertising) or physical activity (a conducive transport policy which favours urban cycle lanes, walking paths with curbs on private vehicular transport, facilities for leisure time exercise in community playgrounds and emphasising the importance of physical activity in school curriculum and at worksites) that have large impact on the mean level CHD risk factors at the population level. For example, in low and middle income countries, a 10 per cent increase in the price of tobacco products reduces the number of smokers by 37.6 million (9.3 million deaths averted) as compared to 18.6 million (4.4 million deaths averted) with other tobacco control measures (20). By contrast, in high income countries, a similar intervention will reduce the number of smokers by 4.1 million (1 million deaths averted) as compared with 4.0 million (0.9 million deaths averted) by non-price measures (20). Therefore, active health policy measures are likely to have a larger impact in developing countries such as India.

Implications for the community

Public health education programmes focussing on promotion of a health promoting diet (calories appropriate to the level of physical activity; moderation in the intake of saturated fat, salt, and refined sugar; high intake of fresh fruit and vegetables; fish in preference to red meat in non-vegetarian diets), and (ii) adequate physical activity and regular exercise are required. Similarly anti-tobacco messages are a major public health imperative which will provide the largest benefit for CHD prevention. These messages need to be reinforced to change individual, family, and community behaviours throughout the country. Such measures bring about benefits not only for CHD prevention but also for a wide range of chronic diseases such as stroke, diabetes and some cancers. The success of such population based interventions, addressing multiple risk factors for CHDs, through lifestyle linked community programmes was demonstrated initially in North Karelia study (21). However, a meta-analysis questioned its utility (22). In this meta-analysis Ebrahim et al suggested that the benefits by such interventions are very minimal and there may be small reduction in blood pressure, blood glucose and lipids. They questioned the validity of such small reduction in risk factors. However, as argued by the authors, the reasons for such miniscule reductions are several. These include strong secular trends, limitations of implementing interventions at community level, greater availability of highly cost-effective drugs to control high blood pressure and lower blood cholesterol (making high risk intervention strategies more effective as opposed to health promotion), difficulty of measuring population-level changes, methodological and statistical flaws and lack of a conceptual model.

We, however, believe that in developing countries such as India such measures may indeed work due to several reasons. First, the risk factor levels are high among Indians conferring a higher risk. Interventions are likely to have a higher impact on high risk population. Further, most studies carried out in western population were conducted in a background of declining trend of CVD, thereby negating the expected benefits (Fig.). Evidence from other developing countries suggests that public health interventions in developing countries are successful (23). For example, the 'Healthy lifestyle programmes' in Mauritius had a positive impact on mean population cholesterol level, hypertension prevalence, tobacco and alcohol use (24). In addition, we have recently demonstrated the utility of such programmes in Indian Industrial population (24). Given that just two simple factors (tobacco and Apo B/Apo A-I ratio) explain more than two third of risk, targeting tobacco, diet and physical activity may have huge implications for the Indian population.

[FIGURE OMITTED]

Implication for the health system

In the coming years, the Indian health system has to device CHD prevention and control strategies, as a priority, to address the growing epidemic of CHD. Deriving inputs from the INTERHEART results, the principal functions of such strategies would be: (i) to provide information and an enabling environment for increasing awareness and adoption of health living habits by the community; (ii) early detection of persons with risk factors and cost-effective interventions for reducing risk; and (iii) early detection of persons with clinical disease and cost-effective secondary prevention measures to prevent complications.

Many of these activities can be performed in primary care settings through the multi-purpose health workers (MPWs) and other non-physician health workers. MPW cadre can be trained to promote simple messages on promoting fruits and vegetable intake, physical activity and tobacco cessation. Further, simple screening tool for diabetes and CHD can be used identifying early detection of high risk individuals. For example, we and others have devised screening systems for using non-biochemical, simple measures for identifying individuals with diabetes (25-27). Such risk scores can be used for targeted screening of individuals. Such tools can be easily employed by lay persons in the community enabling self-referral.

Addition of fasting values of blood fats and blood sugar to the above tools will substantially improve their specificity and can be employed at the secondary health care level. Additionally, the WHO STEPwise approach to surveillance methodology can be adopted for surveillance of risk factors which is adapted for low resource settings (28). Thus, the recently launched National Programme for Prevention and Control of Diabetes, Cardio-vascular Diseases and Stroke (NPCDS) can derive substantial inputs from the INTERHEART study while devising its strategies. Community-based programmes targeting multiple risk factors impact blood pressure much more than other risk factors (29). If a comprehensive risk factor survey is not possible, even prevention programmes aimed at controlling high blood pressure could be a starting point because of its significant effect on death rates from heart disease and stroke and complications among diabetic cases.

Implications for physicians

For primary care physicians and cardiologists, INTERHEART study provides ample evidence to give simple messages on the role of conventional risk factors in the causation of heart attacks and convincing the patients on the need for adopting healthy lifestyle for primary and secondary prevention of heart attack has become straight forward. Above all, INTERHEART provides answer for the quest for a single reliable biomarker, the Apo B/ApoA 1 ratio that can predict the future CHD risk relieving physicians from the complexities of monitoring various fractions of blood fats and other conventional and unconventional risk factors. Aggressive management of coronary risk factors in South Asians entails vigorous lipid control, and dietary and lifestyle modifications. The evidence from INTERHEART provides rationale for developing treatment algorithms and treatment guidelines for CHD at various levels of health care. Further, this approach improves quality of care and ensures equity as the intervention tools do not involve complex and costly therapeutic procedures.

Unanswered questions

While explaining the role of conventional risk factors in the aetiology of myocardial infarction, INTERHEART study also opens up several unanswered questions such as:

* Why do Indians have higher levels of risk factors even at a younger age?

* Why is that CHD/ diabetes occurs at younger ages and at a lower level of risk factors?

* Are these factors a result of gene-environment interaction? For example, is there a gene-diet interaction in the Indian population?

* What is the role of macro- and micronutrients in Indian Diet?

* Do rural-urban migrants have increased diabetes and obesity?

* Does the pattern of migration influence risk?

* What are the potential interventions to reduce the risk?

* Finally, is there an evolutionary basis for the increased risk of diabetes30.

How to answer these questions: The need for research and capacity development

The answer to these questions lies in trans-disciplinary research involving basic science, epidemiology, health systems, health economics and health policy disciplines. More importantly, operational research to implement the evidence based strategies generated from INTERHEART is critical in providing access to rural communities with poor referral linkages. Emphasis on upstream interventions such as policy level changes and research to identify barriers in prevention are other research priorities.

Considering higher levels of risk factors in Indians even among younger ages, developing innovative strategies incorporating both high-risk and population-wide strategies are crucial to prevention. Therefore, trials investigating the effects of a fixed-dose, combination therapy (Polypill) in various population groups in India and estimating its cost-effectiveness is highly justified.

Conclusion

INTERHEART study results highlight the role of potentially modifiable risk factors in causation of acute myocardial infarction. These results suggest the feasibility of low cost prevention strategies to address the growing threat of chronic diseases in India.

Declaration of competing interests: None.

Received April 30, 2009

References

(1.) Reddy KS, Shah B, Varghese C, Ramadoss A. Responding to the threat of chronic diseases in India. Lancet 2005; 366 : 1744-9.

(2.) 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.

(3.) McKeigue PM, Miller GJ, Marmot MG. Coronary heart disease in South Asians: a review. Clin Epidemiol 1989; 42 : 579-609.

(4.) Tuomilehto J, Ram P, Eseroma R, Taylor R, Zimmet P. Cardiovascular diseases in Fiji: analysis of mortality, morbidity and risk factors. Bull World Health Organ 1984; 62 : 133-43.

(5.) Balarajan R. Ethnic differences in mortality from ischaemic heart disease and cerebrovascular disease in England and Wales. BMJ 1991; 302 : 560-4.

(6.) Yusuf S, Hawken S, Ounpuu S, Dans T, Avezum A, Lanas F, et al; INTERHEART Study Investigators. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. Lancet2004; 364 : 937-52.

(7.) Magnus P, Beaglehole R. The real contribution of the major risk factors to the coronary epidemics: time to end the "only-50%" myth. Arch Intern Med 2001; 161 : 2657-60.

(8.) Beaglehole R, Magnus P. The search for new risk factors for coronary heart disease: occupational therapy for epidemiologists? Int J Epidemiol 2002; 31 : 1117-22.

(9.) Ezzati M, Vander Hoorn S, Rodgers A, Lopez AD, Mathers CD, Murrary CJL, et al. Estimates of global and regional health gains from reducing multiple major risk factors. Lancet 2003; 362 : 271-80.

(10.) Mohan V, Sandeep S, Deepa R, Shah B, Varghese C. Epidemiology of type 2 diabetes: Indian scenario. Indian J Med Res 2007; 125 : 217-30.

(11.) Gupta R. Trends in hypertension epidemiology in India. J Hum Hypertens 2004; 18 : 73-8.

(12.) Prabhakaran D, Chaturvedi V, Shah P, Manhapra A, Jeemon P, Shah B, et al. Differences in the prevalence of metabolic syndrome in urban and rural India: a problem of urbanization. Chronic Illness 2007; 3 : 8-19.

(13.) Prabhakaran D, Yusuf S, Mehta S, Pogue J, Avezum A, Budaj A, et al. Two-year outcomes in patients admitted with non-ST elevation acute coronary syndrome: results of the OASIS registry 1 and 2. Indian Heart J 2005; 57 : 217-25.

(14.) Reddy KS, Prabhakaran D, Jeemon P, Thankappan KR, Joshi P, Chaturvedi V, et al. Educational status and cardiovascular risk profile in Indians. Proc Natl Acad Sci USA 2007; 104 : 16263-8.

(15.) Ajay VS, Prabhakaran D, Jeemon P, Thankappan KR, Mohan V, Ramakrishnan L, et al. Prevalence and determinants of diabetes mellitus in the Indian Industrial population. Diabetic Med 2008; 25 : 1187-94.

(16.) Xavier D, Pais P, Devereaux PJ, Xie C, Prabhakaran D, Reddy KS, et al. CREATE registry investigators. Treatment and outcomes of acute coronary syndromes in India (CREATE): a prospective analysis of registry data. Lancet 2008; 371 : 1435-42.

(17.) WHO global report 2005--Preventing chronic diseases: a vital investment. Geneva: World Health Organization; 2005.

(18.) Joshi P, Islam S, Pais P, Reddy S, Dorairaj P, Kazmi K, et al. Risk factors for early myocardial infarction in South Asians compared with individuals in other countries. JAMA 2007; 297 : 286-94.

(19.) Gaziano TA, Galea G, Reddy KS. Scaling up interventions for chronic disease prevention: the evidence. Lancet 2007; 370 : 1939-46.

(20.) Ranson K, Jha P, Chaloupka FJ, Yurekli A. Effectiveness and cost-effectiveness of price increases and other tobacco control policies. In: Jha P, Chaloupka FJ, editors. Tobacco control in developing countries. Oxford: Oxford University Press; 2000. p. 427-47.

(21.) Puska P, Tuomilehto J, Aulikki N, Enkki V. The North Karelia Project. 20 years results and experiences. Helsinki: National Public Health Institute; 1995.

(22.) Ebrahim S, Smith GD. Systematic review of randomised controlled trials of multiple risk factor interventions for preventing coronary heart disease. BMJ 1997; 314 : 1666-74.

(23.) Dowse GK, Gareeboo H, Alberti KG, Zimmet P, Tuomilehto J, Purran A, et al. Changes in population cholesterol concentrations and other cardiovascular risk factor levels after five years of the non-communicable disease intervention programme in Mauritius. Mauritius Non-communicable Disease Study Group. BMJ 1995; 311 : 1255-9.

(24.) Reddy KS, Prabhakaran D, Jeemon P, Goenka S, Ramakrishnan L, Thankappan KR, et al. Impact of population based primary prevention strategies on cardiovascular risk factors in India: A demonstration project in Indian industrial population. J Am Coll Cardiol 2007; 49 : 370A-70.

(25.) Chaturvedi V, Reddy KS, Prabhakaran D, Ramakrishnan L, Jeemon P, Shah P, et al. Development of a clinical risk score in predicting undiagnosed diabetes in urban Asian Indian adults: a population-based study. CVD Prev Control 2008; 3 : 14151.

(26.) Mohan V, Deepa R, Deepa M, Somannavar S, Datta M. A simplified Indian Diabetes Risk Score for screening for undiagnosed diabetic subjects. J Assoc Physicians India 2005; 53 : 759-63.

(27.) Ramachandran A, Snehalatha C, Vijay V, Wareham NJ, Colagiuri S. Derivation and validation of diabetes risk score for urban Asian Indians. Diabetes Res Clin Pract 2005; 70 : 63-70.

(28.) World Health Organization. The WHO STEPwise approach to Surveillance of chronic noncommunicable diseases risk factors. Available from: http://www.who.int/chp/steps/en, accessed on April 2, 2008.

(29.) Deborah E, Sellers L, Crawford KB, McKinlay JB. Understanding the variability in the effectiveness of community heart health programs: A meta-analysis. Soc Sci Med 1997; 44 : 1325-39.

(30.) Sniderman AD, Bhopal R, Prabhakaran D, Sarrafzadegan N, Tchernof A. Why might South Asians be so susceptible to central obesity and its atherogenic consequences? The adipose tissue overflow hypothesis. Int J Epidemiol 2007; 36 : 220-5.

Vamadevan S. Ajay & Dorairaj Prabhakaran Centre for Chronic Disease Control, New Delhi, India

Reprint requests: Dr Dorairaj Prabhakaran, Executive Director, Centre for Chronic Disease Control C-1/52, 2nd floor, Safdarjung Development Area, New Delhi 110 016, India e-mail: dprabhakaran@ccdcindia.org
Table. Key results of the South Asian component of the
INTERHEART study (17)

* Deaths due to acute myocardial infarction (AMI) in south
Asians occur at 5-10 years earlier than western population.

* South Asian men encountering AMI were 5.6 yr younger than
women.

* The higher risk for AMI in South Asians in their younger age
is largely determined by the higher levels of risk factors and
the nine conventional risk factors (abnormal lipids, smoking,
hypertension, diabetes, abdominal obesity, psychosocial
factors, consumption of fruits & vegetables, alcohol and
regular physical activity) collectively explain 86 per cent of
the AMI risk in south Asians.

* Abnormal Apo-B/ApoA-1 ratio and smoking are the most
important risk factors.

* Low education level is associated with increased risk of AMI
worldwide.

* Protective lifestyle factors such as leisure time physical activity
and regular intake of fruits and vegetables are markedly lower
among south Asians than western population, while harmful
risk factors such as elevated ApoB/Apo A-1 ratio are higher
in south Asians.

* South Asians have significantly higher population attributable
risk associated with waist-hip ratio.

* Higher level of risk factors in both cases and controls under
the age of sixty.

* Regular alcohol consumption is not protective for AMI in
south Asians (OR=1.06; 95% CI, 0.85-1.20).
COPYRIGHT 2010 Indian Council of Medical Research
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2010 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Author:Ajay, Vamadevan S.; Prabhakaran, Dorairaj
Publication:Indian Journal of Medical Research
Article Type:Clinical report
Geographic Code:9INDI
Date:Nov 1, 2010
Words:3482
Previous Article:Congestive heart failure in Indians: how do we improve diagnosis & management?
Next Article:Genomic approaches to coronary artery disease.
Topics:

Terms of use | Privacy policy | Copyright © 2021 Farlex, Inc. | Feedback | For webmasters |