Cadi > Topic > Risk Stratification > Underestimation of Risk in Asian Indians

Underestimation of Risk in Asian Indians

Underestimation of Heart Disease Risk in Asian Indians 

  • Although the classical risk factors of high blood pressure, an abnormal lipid profile, diabetes, and obesity do increase the risk of developing CVD in Indians, the slopes of these risk factors appear to be steeper among South Asians relative to white populations.  Indians tend to develop CVD at lower levels of the classical risk factors relative to whites.1-4  For instance, South Asians have been found to manifest CVD at lower levels of total cholesterol relative to other ethnic groups.1 Similarly, Indians have been shown to have elevated risk of developing CVD risk factors at lower BMI (body mass index)   and waist circumference (WC) levels.5-8
  • In addition, some of the variables identified as risk factors for CVD seem to be more important for Indians than for other populations. For instance, for any given level of total or low-density lipoprotein cholesterol, Indians have been found to have higher triglyceride levels, higher lipoprotein(a) levels, increased ratios of apolipoprotein B to apolipoprotein A-1 (apoB/apoA-1), smaller high-density lipoprotein (HDL) and low-density lipoprotein particle size, and lower levels of HDL.9-13
  • Similarly, in the INTERHEART study, a global case-control study of the risk factors of acute myocardial infarction, elevated apoB/apoA-1 ratios were found to have the highest attributable risk among South Asians. 14, 15 Thus, just looking at the total and HDL ratio, as is done in the Framingham risk score, might not be enough to ascertain the 10-year absolute risk of developing CVD among Indians, and in fact, many even lead to an underestimation of risk. 15
  • CAD risk estimation tools are a simple means of identifying those at high risk in a community and hence a potentially cost-effective strategy for CAD prevention in resource-poor countries. The Asian Indians develop CAD at a very young age and Framingham Risk Score (FRS) markedly underestimate the risk as shown in Table 022. At any given level of FRS factors, CAD risk varies at least 3-fold with Chinese and Caribbeans having the lowest and South Asians having the highest.

  • Brindle and colleagues used two community-based surveys of more than 8000 individuals to calculate the ethnic- and sex-specific 10-year risks of CAD and cerebrovascular disease (CBVD) from the product of the incidence rate in the general population and the prevalence rates for each ethnic group.16 They  found the 10-year risk of CAD and CVD was highest for men of Pakistani and Bangladeshi origin and lowest for Chinese women.
  • In the Seven Countries Study, the coronary artery disease (CAD) mortality varied more than 5-fold among populations with the Japanese having the lowest and Finns having the highest mortality.17 Further analysis of the data has demonstrated that compared to Americans, the CAD risk is 50% lower among southern Europeans but 50% higher among northern Europeans18 at any given level of conventional risk factors. For example, the risk of hard CAD events (such as heart attack, cardiac death, coronary angioplasty, stent, and bypass surgery) among northern Europeans with a cholesterol level of 160 mg/dL is similar to southern Europeans with a cholesterol level of 240 mg/dL even when adjustments were made for the differences in  smoking and high blood pressure.18
  • It appears that at any given level and/or combination of conventional risk factors, the risk of CAD among Asian Indians is the highest ─ higher than in northern Europeans, double that of Americans and several-fold higher than other Asians.19  Some have argued Indian ethnicity to be a risk factor by itself.20 21
  • Asian Indians have a 2-6 –fold higher risk of diabetes and diabetes carries a 3-4-fold risk of heart disease compared to Europids. Asian Indians also have higher prevalence of metabolic abnormalities and metabolic syndrome. The excess of diabetes and metabolic syndrome among Asian Indians worldwide has led many investigators to erroneously attribute virtually all the excess of CAD in this population to these entities.22, 23

  • A recent prospective study involving 1,515 European and 1,420 South Asian men 40-49 years of age has convincingly demonstrated that diabetes and metabolic syndrome cannot fully explain the excess burden of CAD.19 In this study, there were 34 CAD deaths among South Asians and 20 deaths among Europeans during a median follow-up of 17 years. The age-adjusted relative risk (RR) for CAD death in Asian Indians was 2.0, which increased to 3.1 after adjusting for the lower rates of smoking and cholesterol level. Adjusting for glucose intolerance and diabetes reduced this RR to 2.4. Further adjustments for insulin level, waist to hip ratio, body mass index, hypertension, fasting triglycerides, HDL-C, metabolic syndrome, and socioeconomic status failed to reduce this RR any further.19 Figure 030.
  • These results underscore the need for studying emerging risk factors such as Lp(a) (that are currently underway. The underestimation of the risk results in undertreatment of CAD that led many national and international organizations to make modifications to treatment guidelines in several countries.19, 24-26
  • Indians have been shown to manifest CVD at lower levels of risk factors than other populations.1-4  For this reason, the established cutoffs for CVD risk factors cannot be neatly applied to Indians.
  • Measures of overweight and obesity exemplify this problem. Several scientific bodies have advocated specific lower cutoffs from the existing ones that have been developed from studies conducted in white populations and a new consensus has now emerged.4, 7, 25, 27-30
  • All of them advocate for lowering the cutoffs from the existing ones that have been developed from studies conducted in Europid populations, and a new consensus is emerging.7, 25
  • A modified Framingham risk score called “ETHRISK” has been developed for ethnic groups in the United Kingdom, which takes into account an individual’s ethnicity(Indian  Pakistani/Bangladeshi/Chinese/Black Caribbean/Black African/Irish) in addition to their sex, age, systolic blood pressure, total and HDL cholesterol, and smoking status16 Although this might be more applicable to Indians relative to the original Framingham score, it would be a useful exercise to follow the FHS framework to develop an India specific risk calculator.1

Recalibration of Framingham Risk for in India 

  • The sex-specific Framingham CHD prediction functions perform well among whites and blacks in different settings and can be applied to other ethnic groups after recalibration for differing prevalences of risk factors and underlying rates of CAD events.31
  • Since India has few local data upon which to develop such Risk prediction tool  de novo,  a Framingham risk equation has been recalibrated to estimate CAD risks in a population from rural India. The proportion of a rural Indian population at high risk of CAD using three risk estimation equations was estimated. The first a published version of the Framingham risk equation, the second a recalibrated equation using local mortality surveillance data and local risk factor data, and the third a recalibrated equation using national mortality data and local risk factor data. 32
  •  The mean 10-year probability of CAD for adults >30 years was 10% for men and 5% for women using the Framingham equation; 11% for men and 4 %  for women using the local recalibration; and 19%  for men and 8% for  women using the national recalibration. 32
  • These findings indicate that in India, equations recalibrated to summary national data are unlikely to be relevant to all regions of India and demonstrate the importance of local data collection to enable development of relevant CHD risk tools.32
  • Conventional approaches to treatment and prevention are based on trials performed in white Caucasian populations and may underestimate risk in south Asians and result in undertreatment.  New approaches to management that incorporate the specific needs of south Asian communities are required.33

Sources

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2. Mohan V, Deepa R, Shanthi Rani S, 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(3):682-687.

3. Goel  PK, Bharti BB, Pandey CM, et al. A tertiary care hospital-based study of conventional risk factors including lipid profile in proven coronary artery disease. Indian Heart J. May-Jun 2003;55(3):234-240.

4. Razak F, Anand SS, Shannon H, et al. Defining obesity cut points in a multiethnic population. Circulation. Apr 24 2007;115(16):2111-2118.

5. Deurenberg-Yap M, Chew SK, Lin VF, Tan BY, van Staveren WA, Deurenberg P. Relationships between indices of obesity and its co-morbidities in multi-ethnic Singapore. Int J Obes Relat Metab Disord. 2001;25(10):1554-1562.

6. Deurenberg P, Deurenberg-Yap M, Guricci S. Asians are different from Caucasians and from each other in their body mass index/body fat per cent relationship. Obes Rev. 2002;3(3):141-146.

7. Misra A , Chowbey P, Makkar B. Consensus statement for diagnosis of obesity, abdominal obesity, and metabolic syndrome, for Asian Indians and recomendations for physical activity, medical and surgical management. JAPI. 2009;57:163-170.

8. Misra A, Singhal N, Khurana L. Obesity, the metabolic syndrome, and type 2 diabetes in developing countries: role of dietary fats and oils. J Am Coll Nutr. Jun 2010;29(3 Suppl):289S-301S.

9. McKeigue PM, Shah B, Marmot MG. Relation of central obesity and insulin resistance with high diabetes prevalence and cardiovascular risk in South Asians. Lancet. 1991;337(8738):382-386.

10. Bhalodkar NC, Blum S, Rana T, et al. Comparison of levels of large and small high-density lipoprotein cholesterol in Asian Indian men compared with Caucasian men in the Framingham Offspring Study. Am J Cardiol. Dec 15 2004;94(12):1561-1563.

11. Bhalodkar NC, Blum S, Rana T, Kitchappa R, Bhalodkar AN, Enas EA. Comparison of high-density and low-density lipoprotein cholesterol subclasses and sizes in Asian Indian women with Caucasian women from the Framingham Offspring Study. Clin Cardiol. May 2005;28(5):247-251.

12. Superko HR, Enas EA, Kotha P, Bhat NK, Garrett B. High-density lipoprotein subclass distribution in individuals of asian Indian descent: the National Asian Indian Heart Disease Project. Prev Cardiol. Spring 2005;8(2):81-86.

13. Enas EA, Chacko V, Pazhoor SG, Chennikkara H, Devarapalli HP. Dyslipidemia in South Asian patients. Curr Atheroscler Rep. Nov 2007;9(5):367-374.

14. Joshi P, Islam S, Pais P, et al. Risk factors for early myocardial infarction in South Asians compared with individuals in other countries. Jama. Jan 17 2007;297(3):286-294.

15. Parish S, Peto R, Palmer A, et al. The joint effects of apolipoprotein B, apolipoprotein A1, LDL cholesterol, and HDL cholesterol on risk: 3510 cases of acute myocardial infarction and 9805 controls. Eur Heart J. Sep 2009;30(17):2137-2146.

16. Brindle P, May M, Gill P, et al. Primary prevention of cardiovascular disease: a web-based risk score for seven British black and minority ethnic groups. Heart. Nov 2006;92(11):1595-1602.

17. Verschuren WMM, Jacobs D, Bloemberg B, et al. Serum total cholesterol and long-term coronary heart disease mortality in different cultures: Twenty-five year follow-up of the Seven Countries Study. JAMA. 1995;274:131-136.

18. Menotti A, Lanti M, Puddu PE, Kromhout D. Coronary heart disease incidence in northern and southern European populations: A reanalysis of the Seven Countries Study for a European coronary risk chart. Heart. 2000;84(3):238-244.

19. Forouhi N, McKeigue P. How far can risk factors account for excess coronary mortality in South Asians? Can J Cardiol. 1997;13(suppl B):47B.

20. Anand SS, Yusuf S, Vuksan V, 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(9226):279-284.

21. Gupta M, Brister S. Is South Asian ethnicity an independent cardiovascular risk factor? Can J Cardiol. Mar 1 2006;22(3):193-197.

22. 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(1):152-161.

23. Tan CE, Emmanuel SC, Tan BY, Tai ES, Chew SK. Diabetes mellitus abolishes ethnic differences in cardiovascular risk factors: Lessons from a multi-ethnic population. Atherosclerosis. 2001;155(1):179-186.

24. Enas EA, Jacob ST. Emerging noninvasive biochemical measures: Potential explanation for ethnic differences in cardiovascular risk. Arch Intern Med. 1999;159:1812-1813.

25. Enas  EA, Singh V, Gupta R, Patel R, et al. Recommendations of the Second Indo-US Health Summit for the prevention and control of cardiovascular disease among Asian Indians. Indian heart journal. 2009;61:265-74.

26. Graham I, Atar D, Borch-Johnsen K, Boysen G, Durrington PN. European guidelines on cardiovascular disease prevention in clinical practice: executive summary: Fourth Joint Task Force of the European Society of Cardiology and Other Societies on Cardiovascular Disease Prevention in Clinical Practice (Constituted by representatives of nine societies and by invited experts). Eur Heart J. Oct 2007;28(19):2375-2414.

27. Dudeja V, Misra A, Pandey RM, Devina G, Kumar G, Vikram NK. BMI does not accurately predict overweight in Asian Indians in northern India. Br J Nutr. 2001;86(1):105-112.

28. Misra A., Khurana L. Obesity-related non-communicable diseases: South Asians vs White Caucasians. Int J Obes (Lond). Jul 20 2010.

29. Snehalatha C, Viswanathan V, Ramachandran A. Cutoff values for normal anthropometric variables in Asian Indian adults. Diabetes Care. 2003;26(5):1380-1384.

30. WHO/IASO/ITO. Asia  Pacific Perspective:Redefing obesity and its treatment   World Health Organization, Western Pacific  Region;2000.

31. D’Agostino RB Sr, Grundy S, Sullivan LM, Wilson P. Validation of the Framingham coronary heart disease prediction scores: results of a multiple ethnic groups investigation. Jama. 2001;286(2):180-187.

32. Chow C K, Joshi R, Celermajer DS, Patel A, Neal BC. Recalibration of a Framingham risk equation for a rural population in India. J Epidemiol Community Health. May 2009;63(5):379-385.

33. Barnett AH, Dixon AN, Bellary S, et al. Type 2 diabetes and cardiovascular risk in the UK south Asian community. Diabetologia. Oct 2006;49(10):2234-2246.

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