early cardiovascular risk factors disclosures in south asians … · p ar tm en of mdic i ,s j h...

MINTU TURAKHIA, MD MAS

Instructor of Medicine, Stanford UniversityDirector of Cardiac Electrophysiology, Palo Alto VAResearch Chair, South Asian Heart Center

[email protected]

Early cardiovascular risk factors in South Asians

Disclosures

! Research support:! VA HSR&D Career Development Award! AHA National Scientist Development Grant! VA MERIT Award IIR04-248! El Camino Hospital Foundation

! No other financial disclosures

2

Objectives

! Scope and burden of CVD in South Asians! Screening and risk assessment program at

SAHC! SAHC clinical findings! Future avenues for research

3

Case

! 33-year old nonsmoking engineer presents with chest pain, anterior ST elevation, tachycardia, and rales

! Angiography demonstrated 3-vessel disease with proximal LAD occlusion

! EF 40%! Total cholesterol 234, LDL 156, HDL 32,

triglycerides 45! BMI 25 kg/m2

! Fasting blood sugar: 187

4

5

! India, Pakistan, Sri Lanka, Bangladesh

! 20% of global population! 2.5 million on United

States! Heterogeneous

(language, diet, culture, lifestyle)

South Asia = Indian subcontinent Epidemiology

! South Asians have a four-fold higher risk of MI and cardiovascular death compared to Caucasians

International prevalence of CV disease(SHARE study, Lancet 2000)

! South Asians: 10.7%! Europeans 5.4%! Chinese 2.4%

6

7

1461

743926

11231175

1592

2034

2584

619

849

1108

556500

1000

1500

2000

2500

1990 2000 2010 2020

MenWomenTotal

Ghaffar et al. BMJ 2004; 328:807-10

CHD mortality in India

2.5 M

2.0 M

1.5 M

1.0 M

0.5 M

(# in thousands)

By 2010, India will bear 60% of the

world’s CAD burden

Epidemiology! Younger

! Prone to have MI at earlier age (< 40 years in men)! 25% of MIs before age 40; 33% before age 45! Three-fold higher risk of second MI compared to Caucasians

! Sicker! Anterior infarction! More left main and multivessel disease at time of cath! Present later in the course! Higher post-MI mortality! Younger at first heart failure hospitalization! Die earlier

! Traditional risk factors do not entirely account for this discrepancy

8

Why are South Asians at high risk?

! Three possibilities1. Excess burden of conventional risk factors

2. Greater susceptibility to similar burden of risk factors

3. Unrecognized (“emerging”) risk factors

! May be genetic, environmental, or both

9

Framingham Risk Factors

! Smoking! Hypertension! High total cholesterol or LDL! Low HDL! Diabetes Mellitus! Age! Gender

10

11

0

5

10

15

20

25

30

35

Smoking HTN LDL > 160 TG > 250

Framingham Offspring StudyAsian Indians

(Enas, Indian Heart J, 1996)

Prevalence of Framingham risk

10-year risk of 33-year old male with anterior MI and 3VD: 1 percent

ORIGINAL CONTRIBUTION

Risk Factors for Early Myocardial Infarctionin South Asians Compared With Individualsin Other CountriesPrashant Joshi, MDShofiqul Islam, MScPrem Pais, MDSrinath Reddy, MDPrabhakaran Dorairaj, MDKhawar Kazmi, MBBSMrigendra Raj Pandey, MBBSSirajul Haque, MBBSShanthi Mendis, MDSumathy Rangarajan, MScSalim Yusuf, MD, DPhil

THE SOUTH ASIAN COUNTRIES OFIndia, Pakistan, Bangladesh, SriLanka, and Nepal account forabout a quarter of the world’s

population and contribute the highestproportion of the burden of cardiovas-cular diseases compared with any otherregion globally.1-3 South Asian mi-grants living in several countries havehigher death rates from coronary heartdisease (CHD) at younger ages com-pared with the local population de-spite apparently lower levels of con-ventional risk factors.4-8 Deaths relatedto cardiovascular disease also occur 5to 10 years earlier in South Asian coun-tries than they do in Western coun-tries.9,10 This has raised the possibilitythat South Asians exhibit a special sus-ceptibility for acute myocardial infarc-tion (AMI) that is not explained by tra-ditional risk factors.

AmongindividualslivingintheUnitedKingdom,theearlieronsetofCHDamong

Author Affiliations: Department of Medicine, Gov-ernment Medical College, Nagpur, India (Dr Joshi);Population Health Research Institute, McMaster Uni-versity and Hamilton Health Sciences, Hamilton, On-tario (Mr Islam, Ms Rangarajan, and Dr Yusuf ); De-partment of Medicine, St John’s Medical College,Bangalore, India (Dr Pais); All India Institute of Medi-cal Sciences, New Delhi, India (Drs Reddy and Dorai-raj); Department of Cardiology, Aga Khan Univer-

sity, Karachi, Pakistan (Dr Kazmi); Nepal Hyperten-sion Society, Nepal (Dr Pandey); Department of Car-diology, Bangabandhu Sheikh Medical University,Bangladesh (Dr Haque); and World Health Organi-zation, Geneva, Switzerland (Dr Mendis).Corresponding Author: Salim Yusuf, DPhil, PopulationHealthResearchInstitute,SecondFloor,McMasterClinic,Hamilton General Hospital, 237 Barton St E, Hamilton,Ontario, Canada L8L 2X2 ([email protected]).

Context South Asians have high rates of acute myocardial infarction (AMI) at youngerages compared with individuals from other countries but the reasons for this are unclear.

Objective To evaluate the association of risk factors for AMI in native South Asians,especially at younger ages, compared with individuals from other countries.

Design, Setting, and Participants Standardized case-control study of 1732 caseswith first AMI and 2204 controls matched by age and sex from 15 medical centers in5 South Asian countries and 10 728 cases and 12 431 controls from other countries.Individuals were recruited to the study between February 1999 and March 2003.

Main Outcome Measure Association of risk factors for AMI.

Results The mean (SD) age for first AMI was lower in South Asian countries (53.0 [11.4]years) than in other countries (58.8 [12.2] years; P!.001). Protective factors were lowerin South Asian controls than in controls from other countries (moderate- or high-intensityexercise, 6.1% vs 21.6%; daily intake of fruits and vegetables, 26.5% vs 45.2%; alcoholconsumption "once/wk, 10.7% vs 26.9%). However, some harmful factors were morecommon in native South Asians than in individuals from other countries (elevated apoli-poproteinB100/apolipoproteinA-Iratio,43.8%vs31.8%;historyofdiabetes,9.5%vs7.2%).Similar relative associations were found in South Asians compared with individuals fromother countries for the risk factors of current and former smoking, apolipoprotein B100/apolipoprotein A-I ratio for the top vs lowest tertile, waist-to-hip ratio for the top vs lowesttertile, history of hypertension, history of diabetes, psychosocial factors such as depressionand stress at work or home, regular moderate- or high-intensity exercise, and daily intakeof fruits and vegetables. Alcohol consumption was not found to be a risk factor for AMI inSouthAsians.Thecombinedoddsratio forall9 risk factorswassimilar inSouthAsians (123.3;95% confidence interval [CI], 38.7-400.2] and in individuals from other countries (125.7;95% CI, 88.5-178.4). The similarities in the odds ratios for the risk factors explained a highand similar degree of population attributable risk in both groups (85.8% [95% CI, 78.0%-93.7%] vs 88.2% [95% CI, 86.3%-89.9%], respectively). When stratified by age, SouthAsians had more risk factors at ages younger than 60 years. After adjusting for all 9 riskfactors, thepredictiveprobabilityof classifyinganAMIcaseasbeingyounger than40yearswas similar in individuals from South Asian countries and those from other countries.

Conclusion The earlier age of AMI in South Asians can be largely explained by higherrisk factor levels at younger ages.JAMA. 2007;297:286-294 www.jama.com

286 JAMA, January 17, 2007—Vol 297, No. 3 (Reprinted) ©2007 American Medical Association. All rights reserved.

at UCSF/Library, on January 18, 2007 www.jama.comDownloaded from

ORIGINAL CONTRIBUTION

Risk Factors for Early Myocardial Infarctionin South Asians Compared With Individualsin Other CountriesPrashant Joshi, MDShofiqul Islam, MScPrem Pais, MDSrinath Reddy, MDPrabhakaran Dorairaj, MDKhawar Kazmi, MBBSMrigendra Raj Pandey, MBBSSirajul Haque, MBBSShanthi Mendis, MDSumathy Rangarajan, MScSalim Yusuf, MD, DPhil

THE SOUTH ASIAN COUNTRIES OFIndia, Pakistan, Bangladesh, SriLanka, and Nepal account forabout a quarter of the world’s

population and contribute the highestproportion of the burden of cardiovas-cular diseases compared with any otherregion globally.1-3 South Asian mi-grants living in several countries havehigher death rates from coronary heartdisease (CHD) at younger ages com-pared with the local population de-spite apparently lower levels of con-ventional risk factors.4-8 Deaths relatedto cardiovascular disease also occur 5to 10 years earlier in South Asian coun-tries than they do in Western coun-tries.9,10 This has raised the possibilitythat South Asians exhibit a special sus-ceptibility for acute myocardial infarc-tion (AMI) that is not explained by tra-ditional risk factors.

AmongindividualslivingintheUnitedKingdom,theearlieronsetofCHDamong

Author Affiliations: Department of Medicine, Gov-ernment Medical College, Nagpur, India (Dr Joshi);Population Health Research Institute, McMaster Uni-versity and Hamilton Health Sciences, Hamilton, On-tario (Mr Islam, Ms Rangarajan, and Dr Yusuf ); De-partment of Medicine, St John’s Medical College,Bangalore, India (Dr Pais); All India Institute of Medi-cal Sciences, New Delhi, India (Drs Reddy and Dorai-raj); Department of Cardiology, Aga Khan Univer-

sity, Karachi, Pakistan (Dr Kazmi); Nepal Hyperten-sion Society, Nepal (Dr Pandey); Department of Car-diology, Bangabandhu Sheikh Medical University,Bangladesh (Dr Haque); and World Health Organi-zation, Geneva, Switzerland (Dr Mendis).Corresponding Author: Salim Yusuf, DPhil, PopulationHealthResearchInstitute,SecondFloor,McMasterClinic,Hamilton General Hospital, 237 Barton St E, Hamilton,Ontario, Canada L8L 2X2 ([email protected]).

Context South Asians have high rates of acute myocardial infarction (AMI) at youngerages compared with individuals from other countries but the reasons for this are unclear.

Objective To evaluate the association of risk factors for AMI in native South Asians,especially at younger ages, compared with individuals from other countries.

Design, Setting, and Participants Standardized case-control study of 1732 caseswith first AMI and 2204 controls matched by age and sex from 15 medical centers in5 South Asian countries and 10 728 cases and 12 431 controls from other countries.Individuals were recruited to the study between February 1999 and March 2003.

Main Outcome Measure Association of risk factors for AMI.

Results The mean (SD) age for first AMI was lower in South Asian countries (53.0 [11.4]years) than in other countries (58.8 [12.2] years; P!.001). Protective factors were lowerin South Asian controls than in controls from other countries (moderate- or high-intensityexercise, 6.1% vs 21.6%; daily intake of fruits and vegetables, 26.5% vs 45.2%; alcoholconsumption "once/wk, 10.7% vs 26.9%). However, some harmful factors were morecommon in native South Asians than in individuals from other countries (elevated apoli-poproteinB100/apolipoproteinA-Iratio,43.8%vs31.8%;historyofdiabetes,9.5%vs7.2%).Similar relative associations were found in South Asians compared with individuals fromother countries for the risk factors of current and former smoking, apolipoprotein B100/apolipoprotein A-I ratio for the top vs lowest tertile, waist-to-hip ratio for the top vs lowesttertile, history of hypertension, history of diabetes, psychosocial factors such as depressionand stress at work or home, regular moderate- or high-intensity exercise, and daily intakeof fruits and vegetables. Alcohol consumption was not found to be a risk factor for AMI inSouthAsians.Thecombinedoddsratio forall9 risk factorswassimilar inSouthAsians (123.3;95% confidence interval [CI], 38.7-400.2] and in individuals from other countries (125.7;95% CI, 88.5-178.4). The similarities in the odds ratios for the risk factors explained a highand similar degree of population attributable risk in both groups (85.8% [95% CI, 78.0%-93.7%] vs 88.2% [95% CI, 86.3%-89.9%], respectively). When stratified by age, SouthAsians had more risk factors at ages younger than 60 years. After adjusting for all 9 riskfactors, thepredictiveprobabilityof classifyinganAMIcaseasbeingyounger than40yearswas similar in individuals from South Asian countries and those from other countries.

Conclusion The earlier age of AMI in South Asians can be largely explained by higherrisk factor levels at younger ages.JAMA. 2007;297:286-294 www.jama.com

286 JAMA, January 17, 2007—Vol 297, No. 3 (Reprinted) ©2007 American Medical Association. All rights reserved.

at UCSF/Library, on January 18, 2007 www.jama.comDownloaded from

Joshi, et al with Yusuf (JAMA 2007)

! International case-control study; includes 5 South Asian countries

! Cases: 1700 pts of South Asian origin after first MI

! Controls:! Non South Asian with MI ! South Asians without MI

Interheart study

! Protective factors lower in South Asians! Exercise 6% v. 21%! Daily fruits and vegetables 26% v. 45%! Alcohol !"once/week 11% v. 27%

! Some harmful factors more common! Diabetes 10% v. 7%! High ApoB100 /Apo A-I (LDL:HDL) ratio 44% v. 32%

! Lower mean age of MI (53 vs 59 yrs)! Higher levels of risk factors at younger age (< 60

and < 40)! 9 conventional risk factors accounted for 86% of

population-attributable risk of early MI

13

Limitations

! Few South Asian subjects drawn from Europe or North America

! 14% unmeasured attributable risk in model; could misclassify 1 out of 6 South Asians

! Possible added prognostic value of lipid subparticles, insulin resistance, and additional biomarkers

! Epidemiology in United States not well characterized

14

15

Hospitalization Rates for CAD in California

0

1

2

3

4

5

1.0

3.8

0.6

1.1 1.2

White Asian Indian Chinese Japanese Filipino

Like

lihoo

d of

hos

pita

lizat

ion

(vs.

Whi

te)

(Palaniappan, L, Ann Epid 2004)

PMR =

16

% of deaths from CAD in ethnic group

% of deaths from CAD in whole population

(Palaniappan, L, Ann Epid 2004)

17

tery interventions, history of dialysis, hypercholester-olemia, and stroke showed significant associationswith the presence of diabetes mellitus (Table 3). Morethan 1 in 2 diabetics reported a family history ofdiabetes, and this was significantly higher than innondiabetics. Forward logistic regression showed thata family history of diabetes was the strongest inde-pendent predicting factor for diabetes (Table 4). Age,male gender, myocardial infarction, and hypertensionwere also independent predictive factors for diabetes.So far, no studies have examined the prevalence of

diabetes mellitus in Asian Indian immigrants in theUnited States. The National Health and Nutrition Exam-ination Survey (NHANES III)5,6 reported the prevalenceof diabetes in whites, blacks, and Hispanics living in theUnited States. Asian Indians were not categorized sepa-rately in this study. The NHANES III showed an overallcrude diabetes prevalence of 5.3% in persons living inthe United States aged !20 years of age. They found ahigher prevalence of diabetes in Hispanics (9.3%) andblacks (8.2%) compared with whites (4.8%) in the !20years age group. The prevalence of diabetes in AsianIndian immigrants !20 years of age in our study wasalmost twice that of Hispanics and 4 times that of whites,as reported by NHANES III.In the elderly population, NHANES III reported that

the prevalence of diabetes mellitus in the 60- to 74-yearage group was 24.4% in Hispanics and 20.9% in blacks,which is similar to the prevalence of diabetes in AsianIndians in the same age group in our study (24.8%). Incontrast, the prevalence of diabetes in whites in the 60- to74-year age group in the previously mentioned study wasonly 11.3%. Another study, which examined the preva-lence of diabetes in elderly Hispanics and blacks, alsoreported a high prevalence of diabetes among this pop-ulation in the !65-year age group.7 Bastida et al8 sur-

veyed a sample of 849 Hispanic men and women aged!45 years in south Texas and reported a 25.9% preva-lence of diabetes. They also showed a progressive in-crease in the prevalence of diabetes in Hispanics from 41years of age through 70 years of age, similar to ourresults (Figure 1).

• • •

In our study, the overall prevalence of diabetes inAsian Indians !20 years was higher than all otherracial groups in the United States. However, in theelderly age group, the prevalence of diabetes in AsianIndians was similar to the prevalence of diabetes inelderly Hispanics and elderly blacks.The prevalence of diabetes mellitus in Asian Indi-

ans !20 years of age in our study is much higher thanin Asian Indian immigrants in the United Kingdom,Singapore, Mauritius, Fiji, and South Africa.2,9–14 Inthese countries, the prevalence of diabetes in Asian-Indian immigrants has ranged from 6% to 15%. Theprevalence of diabetes in migrant Asian Indians in thepreviously mentioned studies was much higher than inthe other racial groups in their host countries,2 whichis similar to the results seen in our study. A studyperformed by the Indian Council of Medical Researchshowed the overall prevalence of diabetes in India tobe 1.73%; however, the prevalence varied from 2% inrural areas to up to 33% in urban areas.2,15 A studydone by Ramachandran et al1 by sampling urban In-dians aged!20 years in 6 major cities showed that theprevalence of diabetes in urban areas was 13.9% witha maximum prevalence seen in subjects aged between60 and 69 years of age (29.1%). Our study alsoshowed a high prevalence of diabetes in the 60 to 69years age group (32%) (Figure 1). The overall preva-lence of diabetes in Asian Indians in our study appearssimilar to the prevalence seen in urban India, support-ing the view that populations undergoing acculturationchanges from a traditional to a modern lifestyle havea higher prevalence of type 2 diabetes mellitus.

1. Ramachandran A, Snehalatha C, Kapur A, Vijay V, Mohan V, Das AK. Highprevalence of diabetes and impaired glucose tolerance in India: national urban

diabetes survey. Diabetologia 2001;44:1094–1101.

2. Ramaiya KL, Kodali VRR, Alberti KGMM. Epidemiology of diabetes inAsians of the Indian subcontinent. Diabetes/Metab Rev 1990;6:125–146.

3. U.S. Census Bureau, Census 2000, Special tabulations.4. Baweja G, Nanda NC, Parikh N, Bhatia V, Venkataraman R. Prevalence ofstroke and associated risk factors in Asian Indians living in the state of Georgia,

United States of America. Am J Cardiol 2004;93:267–269.

5. Harris MI, Flegal KM, Cowie CC, Eberhardt MS, Goldstein DE, Little RR,Wiedmeyer HM, Byrd-Holt DD. Prevalence of diabetes, impaired fasting glu-

cose, and impaired glucose tolerance in U.S. adults: the Third National Health

and Nutrition Examination Survey, 1988-1994. Diabetes Care 1998;21:518–524.

6. Mokdad AH, Ford ES, Bowman BA, Nelson DE, Engelgau MM, Vinicor F,Marks JS. Diabetes trends in the U.S.:1990-1998: The Third National Health and

Nutrition Examination Survey, 1988-1994. Diabetes Care 2000;23:1278–1283.

7. Black SA, Ray LA, Markides KS. The prevalence and health burden ofself-reported diabetes in older Mexican Americans: findings from the Hispanic

established populations for epidemiologic studies of the elderly. Am J Public

Health 1999;89:546–552.

8. Bastida E, Cu’ellar I, Villas P. Prevalence of diabetes mellitus and relatedconditions in a south Texas Mexican American sample. Commun Health Nurs

2001;18:75–84.

9. Beckles GLA, Miller GJ, Kirkwood BR, Alexis SD, Carson DC, Byam NTA.High total and cardiovascular mortality in adults of Indian descent in Trinidad

unexplained by major coronary risk factors. Lancet 1986;i:1298–1300.

TABLE 4 Multiple Logistic Regression Analysis

Co-morbid ConditionAdjusted Odds Ratio

(95% CI) p Value

Age 1.02 (1.009–1.36) "0.001Men 1.7 (1.2–2.5) 0.004Family history of diabetes 5.9 (4.1–8.4) "0.0001Hypertension 2.7 (1.9–3.9) "0.0001Myocardial infarction 3.9 (2.2–2.7) "0.001

CI # confidence interval.

FIGURE 1. Prevalence of diabetes in men and women in ourstudy sample.

BRIEF REPORTS 979

(Venkataraman, Am J Cardiol 2004)

The high prevalence of infection withH. pylori in ourpopulation could be a result of the high mean age of ourstudy population. Elderly patients have a higher risk tobe infected with these bacteria because hygiene statuswas lower in their youth. A reason for the protectiveeffect of infection with H. pylori on vitamin B12 defi-ciency in cardiovascular patients could be the waythe bacteria works on the gastric mucosa. Appar-ently, more gastric acid is produced as a reaction ofthe stomach in the presence of the bacteria. There-fore, more vitamin B12 could be released from itsprotein binding in the patient’s diet. This leads tohigher amounts of free vitamin B12, and all avail-able intrinsic factors will come into play in thissituation.Our study population used a lot of concomitant

medication, which could lead to confounding in theassociations that we studied. Nonsteroidal anti-inflam-matory drugs are known to cause similar damage tothe stomach as acetylsalicylic acid.13 The Dutch el-derly population frequently used vitamin preparations,which resulted in a maximum daily vitamin in-take.14,15 With use of a vitamin B preparation, a lowdaily dietary intake of vitamin B12 can be compen-sated.16,17 However, the number of patients using non-steroidal anti-inflammatory drugs or vitamin prepara-tions did not differ between vitamin B12 deficient andnondeficient patients.

1. Ranganath LR, Baines M, Roberts NB. Homocysteine and thiol metabolites invitamin B12 deficiency. Clin Sci (Lond) 2001;100:111–116.

2. Hankey GJ, Eikelboom JW. Homocysteine and vascular disease. Lancet

1999;354:407–413.

3. Peterson JC, Spence JD. Vitamins and progression of atherosclerosis inhyper-homocyst(e)inaemia. Lancet 1998;351:263.

4. Verheugt FWA, Gersh BJ. Aspirin beyond platelet inhibition. Am J Cardiol

2002;90:39–41.

5. Verheugt FWA. Aspirin, the poor man’s statin. Lancet 1998;351:227–228.6. Verheugt FWA. In search of a super-aspirin for the heart. Lancet 1997;349:1409–1410.

7. Petty GW, Brown RD, Whisnant JP, Sicks JD, O’Fallon WM, Wiebers DO.Frequency of major complications of aspirin, warfarin, and intravenous heparin

for secondary stroke prevention. Ann Intern Med 1999;130:14–22.

8. Lanas A, Serrano P, Bajador E, Esteva F, Benito R, Sainz R. Evidence ofaspirin use in both upper and lower gastrointestinal perforation. Gastroenterology

1997;112:683–689.

9. Weil J, Colin-Jones D, Langman M, Lawson D, Logan R, Murphy M, RawlinsM, Vessey MP, Wainwhright P. Prophylactic aspirin and risk of peptic ulcer

bleeding. BMJ 1995;310:827–830.

10. Willems FF, Aengevaeren WRM, Boers GHJ, Blom HJ, Verheugt FWA.

Coronary endothelial function in hyperhomocysteinemia: improvement after

treatment with folic acid and cobalamin in patients with coronary artery disease.

J Am Coll Cardiol 2002;40:766–772.

11. Laheij RJF, van Oijen MGH, Paloheimo LI, Jansen JBMJ. Vitamin B12deficiency and gastric functioning in patients with cardiovascular disease (abstr).

Gut 2002;51(suppl III):A152.

12. Van Asselt DZB, de Groot LCPGM, van Staveren WA, Blom HJ, Wevers

RA, Biemond I, Hoefnagels WH. The role of cobalamin intake and atrophic

gastritis in mild cobalamin deficiency in older Dutch subjects. Am J Clin Nutr

1998;68:328–334.

13. Day RO, Henry DA, Muirden KD, Yeomans ND, Brooks PM, Stiel D,Prichard PJ. Non-steriodal anti-inflammatory drug (NSAID) induced upper gas-

trointestinal haemorrhage and bleeding. Med J Aust 1992;157:810–812.

14. Carmel R. Mild cobalamin deficiency in older Dutch subjects. Am J Clin Nutr

1999;69:738–739.

15. Naurath HJ, Joosten E, Riezler R, Stabler SP, Allen RH, Lindenbaum J.

Effects of vitamin B12, folate, and vitamin B6 in elderly people with normal

serum concentrations. Lancet 1995;346:85–89.

16. Seal EC, Metz J, Flicker L, Melny J. A randomized, double-blind, placebo-controlled study of oral vitamin B12 supplementation in older patients with

subnormal or borderline serum vitamin B12 concentrations. J Am Geriatr Soc

2002;50:146–151.

17. Loew D, Wanitschke R, Schroedter A. Studies on vitamin B12 status in theelderly—prophylactic and therapeutic consequences. Int J Vitam Nutr Res

1999;69:228–233.

Prevalence of Diabetes Mellitus and RelatedConditions in Asian Indians Living in the United States

Rajesh Venkataraman, MD, MPH, Navin C. Nanda, MD, Gurpreet Baweja, MD,Naresh Parikh, MD, and Vishal Bhatia, MD

This study is the first attempt to evaluate the prev-alence of diabetes mellitus and related conditionsin Asian Indians living in the United States. A com-munity-based survey of 1,046 Asian Indian immi-grants living in and around the Atlanta metro areaof Georgia was conducted and found an overallprevalence of diabetes mellitus of 18.3% (22.5% inmen and 13.6% in women). This prevalence ofdiabetes mellitus in Asian Indians is much higherthan in whites, blacks, and Hispanics living in the

United States. !2004 by Excerpta Medica, Inc.(Am J Cardiol 2004;94:977–980)

Many studies have reported that Asian Indianshave an unusually high prevalence of diabetes

mellitus.1,2 This high prevalence of diabetes in mi-grant Asian Indians has been shown to be much higherthan the population residing in India and is also higherthan the other racial groups in the host countries.2

Asian Indians now constitute 1% (1.9 million) of theUnited States population3 and are one of the fastestgrowing minority groups. No study has examined andcompared the prevalence of diabetes mellitus in AsianIndians with other racial groups in the United States.This study examined the prevalence of diabetes mel-litus and its association with other co-morbid medicalconditions in Asian Indians living in Atlanta, Georgia.

• • •

From the Division of Cardiovascular Disease, The University ofAlabama at Birmingham, Birmingham, Alabama. Dr. Nanda’s ad-dress is: The University of Alabama at Birmingham, Heart Station/Echocardiography Laboratories, 619 South 19th Street, SW-S102,Birmingham, Alabama 35249. E-mail: [email protected]. Manuscriptreceived April 2, 2004; revised manuscript received and acceptedJune 16, 2004.

977©2004 by Excerpta Medica, Inc. All rights reserved. 0002-9149/04/$–see front matterThe American Journal of Cardiology Vol. 94 October 1, 2004 doi:10.1016/j.amjcard.2004.06.048

Asian Indians living in Atlanta and nearby counties inGeorgia were surveyed during religious congregations atthe Bochasanwasi Shri Akshar Purushottam Swami-narayan Sanstha temple. Bochasanwasi Shri Akshar Pu-rushottam Sanstha is a prominent sect of Hindu religionand an international sociospiritual organization that con-ducts humanitarian work through a worldwide network.All participants were originally from the state of Gujarat,a state in the western part of India and are Hindus byreligion. Abstinence from alcohol, tobacco, and strictadherence to a vegetarian diet are the norm in this par-ticular community. Participants were asked to fill out aquestionnaire, which was designed by the authors. Thequestionnaire was composed of demographic character-istics, anthropometric profile (height, weight) and a “yes/

no” response for the presence of dia-betes mellitus and related co-morbidmedical conditions, including hyper-tension, hypercholesterolemia, myo-cardial infarction, coronary interven-tional procedures, history of dialysis,and stroke. We also elicited a similarresponse for a family history of diabe-tes mellitus, myocardial infarction, andstroke. The questionnaire itself wasworded in simple laymen’s languageand was also translated into the ver-nacular language spoken by the sur-veyed subjects (Gujarati). Diabetesand other co-morbid conditions wereself-reported by the subjects. Nonmed-ical personnel were trained by localphysicians to conduct the survey undertheir supervision. A 5% (n ! 10) ran-

dom sample of participants reporting diabetes were con-tacted, and their medical records were traced with theirconsent and were found to have type 2 diabetes mellitus.Analysis of this data for the prevalence of stroke in AsianIndians has been previously reported elsewhere.4

Data are reported as percent for discrete variablesand mean " SD for continuous variables. Descriptivestatistics were computed for all variables and com-pared between diabetics and nondiabetics with chi-square (discrete variables) and t tests (continuous vari-ables). We performed cross tabulations for diabeteswith other co-morbid medical conditions and reportedodds ratios. A multivariable logistic regression modelwas constructed with diabetes as the dependent vari-able and male sex, stroke, hypertension, hypercholes-terolemia, myocardial infarction, coronary artery in-terventions, history of dialysis, and family history ofdiabetes as independent variables. Statistical analyseswere done using SPSS version 11.1 (SPSS Inc., Chi-cago, Illinois) for Windows (Microsoft, Redmond,Washington). All tests were 2 tailed; a p value of#0.05 was considered statistically significant, and allconfidence intervals reported are 95%. A total numberof 1,046 subjects were surveyed (537 men and 509women). Mean age of the subjects was 52.8 " 11.3years (range 17 to 87).The overall prevalence of diabetes was 18.3% for

the total surveyed population. The mean age of par-ticipants reporting diabetes was significantly higherthan those without diabetes (Table 1). The prevalenceof diabetes in those !20 years of age was 18.1%, inthose $45 years of age was 21.6%, and in those !65years of age was 24.8%. There was no significantdifference in the body mass index (body weight inkilograms divided height in meters squared) betweenboth groups. The mean age of diabetic men andwomen was also significantly higher than nondiabet-ics. The prevalence of diabetes was higher in mencompared with women (p #0.001); however, amongdiabetic men and women, there were no significantdifferences in the prevalence of co-morbid conditions(Table 2).Myocardial infarction, hypertension, coronary ar-

TABLE 1 Baseline Characteristics of Participants

CharacteristicsTotal

(n ! 1,046)Diabetics(n ! 192)

Nondiabetics(n ! 854)

Men 51% 62.5% 51%Women 49% 37.5% 49%Mean age (yrs)* 52.8 " 11.3 57.2 " 9.5 51.9 " 11.4†

Mean body mass index (kg/m2)* 26.1 " 4.7 26.4 " 4.5 26.0 " 4.7Hypertension 23.7% 45.2% 18.9%†

Hypercholesterolemia 18.5% 27.3% 16.4%†

Myocardial infarction 6.5% 16.3% 4.3%†

Coronary artery intervention 10.7% 21% 8.4%†

History of dialysis 2.7% 8.4% 1.4%†

Stroke 2.9% 5.2% 2.2%‡

Family history of diabetes mellitus 22.7% 53.1% 14%†

*Figures are mean " SD.†p #0.001, independent sample t test between diabetic and nondiabetic groups.‡p #0.05, independent sample t test between diabetic and nondiabetic groups.

TABLE 2 Prevalence of Co-morbid Conditions in DiabeticMen and Women

Co-morbid ConditionMen

(n ! 120)Women(n ! 72) p Value

Hypertension 26.3% 21% NSHypercholesterolemia 20.7% 16.1% NSMyocardial infarction 8.2% 4.7% 0.07Coronary artery

intervention11.2% 10% NS

History of dialysis 3.7% 1.6% NSStroke 3.7% 1.7% NS

TABLE 3 Cross Tabulation of Diabetes and Co-morbidConditions

Co-morbid Condition Odds RatioConfidence

Interval p Value

Hypertension $3.5 2.5–4.9 #0.001Myocardial infarction 4.3 2.6–7.1 #0.001Hypercholesterolemia 1.9 1.3–2.7 #0.001Coronary artery

intervention2.9 1.9–4.4 #0.001

Stroke 2.4 1.1–5.9 0.029History of dialysis 6.5 3–13.9 #0.001Family history of diabetes

mellitus6 4.2–8.4 #0.001

978 THE AMERICAN JOURNAL OF CARDIOLOGY! VOL. 94 OCTOBER 1, 2004

(Venkataraman, Am J Cardiol 2004)

The high prevalence of infection withH. pylori in ourpopulation could be a result of the high mean age of ourstudy population. Elderly patients have a higher risk tobe infected with these bacteria because hygiene statuswas lower in their youth. A reason for the protectiveeffect of infection with H. pylori on vitamin B12 defi-ciency in cardiovascular patients could be the waythe bacteria works on the gastric mucosa. Appar-ently, more gastric acid is produced as a reaction ofthe stomach in the presence of the bacteria. There-fore, more vitamin B12 could be released from itsprotein binding in the patient’s diet. This leads tohigher amounts of free vitamin B12, and all avail-able intrinsic factors will come into play in thissituation.Our study population used a lot of concomitant

medication, which could lead to confounding in theassociations that we studied. Nonsteroidal anti-inflam-matory drugs are known to cause similar damage tothe stomach as acetylsalicylic acid.13 The Dutch el-derly population frequently used vitamin preparations,which resulted in a maximum daily vitamin in-take.14,15 With use of a vitamin B preparation, a lowdaily dietary intake of vitamin B12 can be compen-sated.16,17 However, the number of patients using non-steroidal anti-inflammatory drugs or vitamin prepara-tions did not differ between vitamin B12 deficient andnondeficient patients.

1. Ranganath LR, Baines M, Roberts NB. Homocysteine and thiol metabolites invitamin B12 deficiency. Clin Sci (Lond) 2001;100:111–116.

2. Hankey GJ, Eikelboom JW. Homocysteine and vascular disease. Lancet

1999;354:407–413.

3. Peterson JC, Spence JD. Vitamins and progression of atherosclerosis inhyper-homocyst(e)inaemia. Lancet 1998;351:263.

4. Verheugt FWA, Gersh BJ. Aspirin beyond platelet inhibition. Am J Cardiol

2002;90:39–41.

5. Verheugt FWA. Aspirin, the poor man’s statin. Lancet 1998;351:227–228.6. Verheugt FWA. In search of a super-aspirin for the heart. Lancet 1997;349:1409–1410.

7. Petty GW, Brown RD, Whisnant JP, Sicks JD, O’Fallon WM, Wiebers DO.Frequency of major complications of aspirin, warfarin, and intravenous heparin

for secondary stroke prevention. Ann Intern Med 1999;130:14–22.

8. Lanas A, Serrano P, Bajador E, Esteva F, Benito R, Sainz R. Evidence ofaspirin use in both upper and lower gastrointestinal perforation. Gastroenterology

1997;112:683–689.

9. Weil J, Colin-Jones D, Langman M, Lawson D, Logan R, Murphy M, RawlinsM, Vessey MP, Wainwhright P. Prophylactic aspirin and risk of peptic ulcer

bleeding. BMJ 1995;310:827–830.

10. Willems FF, Aengevaeren WRM, Boers GHJ, Blom HJ, Verheugt FWA.

Coronary endothelial function in hyperhomocysteinemia: improvement after

treatment with folic acid and cobalamin in patients with coronary artery disease.

J Am Coll Cardiol 2002;40:766–772.

11. Laheij RJF, van Oijen MGH, Paloheimo LI, Jansen JBMJ. Vitamin B12deficiency and gastric functioning in patients with cardiovascular disease (abstr).

Gut 2002;51(suppl III):A152.

12. Van Asselt DZB, de Groot LCPGM, van Staveren WA, Blom HJ, Wevers

RA, Biemond I, Hoefnagels WH. The role of cobalamin intake and atrophic

gastritis in mild cobalamin deficiency in older Dutch subjects. Am J Clin Nutr

1998;68:328–334.

13. Day RO, Henry DA, Muirden KD, Yeomans ND, Brooks PM, Stiel D,Prichard PJ. Non-steriodal anti-inflammatory drug (NSAID) induced upper gas-

trointestinal haemorrhage and bleeding. Med J Aust 1992;157:810–812.

14. Carmel R. Mild cobalamin deficiency in older Dutch subjects. Am J Clin Nutr

1999;69:738–739.

15. Naurath HJ, Joosten E, Riezler R, Stabler SP, Allen RH, Lindenbaum J.

Effects of vitamin B12, folate, and vitamin B6 in elderly people with normal

serum concentrations. Lancet 1995;346:85–89.

16. Seal EC, Metz J, Flicker L, Melny J. A randomized, double-blind, placebo-controlled study of oral vitamin B12 supplementation in older patients with

subnormal or borderline serum vitamin B12 concentrations. J Am Geriatr Soc

2002;50:146–151.

17. Loew D, Wanitschke R, Schroedter A. Studies on vitamin B12 status in theelderly—prophylactic and therapeutic consequences. Int J Vitam Nutr Res

1999;69:228–233.

Prevalence of Diabetes Mellitus and RelatedConditions in Asian Indians Living in the United States

Rajesh Venkataraman, MD, MPH, Navin C. Nanda, MD, Gurpreet Baweja, MD,Naresh Parikh, MD, and Vishal Bhatia, MD

This study is the first attempt to evaluate the prev-alence of diabetes mellitus and related conditionsin Asian Indians living in the United States. A com-munity-based survey of 1,046 Asian Indian immi-grants living in and around the Atlanta metro areaof Georgia was conducted and found an overallprevalence of diabetes mellitus of 18.3% (22.5% inmen and 13.6% in women). This prevalence ofdiabetes mellitus in Asian Indians is much higherthan in whites, blacks, and Hispanics living in the

United States. !2004 by Excerpta Medica, Inc.(Am J Cardiol 2004;94:977–980)

Many studies have reported that Asian Indianshave an unusually high prevalence of diabetes

mellitus.1,2 This high prevalence of diabetes in mi-grant Asian Indians has been shown to be much higherthan the population residing in India and is also higherthan the other racial groups in the host countries.2

Asian Indians now constitute 1% (1.9 million) of theUnited States population3 and are one of the fastestgrowing minority groups. No study has examined andcompared the prevalence of diabetes mellitus in AsianIndians with other racial groups in the United States.This study examined the prevalence of diabetes mel-litus and its association with other co-morbid medicalconditions in Asian Indians living in Atlanta, Georgia.

• • •

From the Division of Cardiovascular Disease, The University ofAlabama at Birmingham, Birmingham, Alabama. Dr. Nanda’s ad-dress is: The University of Alabama at Birmingham, Heart Station/Echocardiography Laboratories, 619 South 19th Street, SW-S102,Birmingham, Alabama 35249. E-mail: [email protected]. Manuscriptreceived April 2, 2004; revised manuscript received and acceptedJune 16, 2004.

977©2004 by Excerpta Medica, Inc. All rights reserved. 0002-9149/04/$–see front matterThe American Journal of Cardiology Vol. 94 October 1, 2004 doi:10.1016/j.amjcard.2004.06.048

Where is the unmet need?

! More South Asians have CAD & present at an earlier age! Conventional risk factors, novel risk factors, or both?! Treated or untreated?! When does it start?! Role of socioeconomic status and access to care?! Where are the high-risk people? How can we get to

them?

19

Barriers to care

! Lack of physician awareness of need for early screening and aggressive treatment in South Asians

! Patients don’t know to ask! No focused resource center for clients and

physicians

! 2005: Creation of South Asian Heart Center

20

21

“The mission of the South Asian Heart Center is to reduce the high incidence of coronary disease among South Asians through a comprehensive, culturally-appropriate program incorporating education, advanced screening, lifestyle changes, and case management.”

Prevention Program Methodology

! Easy sign-up at website for advanced screening! ASSESSMENT:

Guided heart-heath risk assessmentAdvanced labBrief physical exam

! IDENTIFICATION: Detailed risk & risk factor stratification

! MANAGEMENT: Customized risk-factor mgmt. plan & follow-

through

Results consultation with nurse practitionerNutrition consultations with registered dieticianFrequent follow-up over 1 year with heart health coachesRetest tracking, facilitation, communicating results

22

Metabolic Evaluation

23

Metabolic Syndrome & Risk Marker Evaluation

24

SAHC evaluation process

! Sign up online! 30-40 minute risk assessment by phone! Lab tests (12-hour fasting)! 30-40 min appointment to discuss results and

recommendations (not prescription)! Medication, exercise, diet, stress reduction! Sent back to referring MD for interventions (MD emailed all

reports and recommendations as well)

! Nutrition appointment! Follow-up

! Did you see your doctor?! Are you doing the things that were recommended?

25

SAHC Experience: Bay Area South Asian Study

! Started initial health screenings starting in 2006! 1 year ago: 800 participants! December 2008: 2100 participants! > 3500 patient encounters

! Anthropomorphic, demographic, and medical information collected

! Fasting blood specimen collected for cholesterol and metabolic profile screening

! DNA banked for a sub-cohort that consented

26

Research aims

! Define prevalence of metabolic syndrome and its components in cohort

! Define burden of CV risk factors and metabolic syndrome in youngest participants

27

SAHC MetS study

! From Jan 2006-Dec 2008: 1445 completed screening program including laboratory testing

! Lab testing: Berkeley Heart Lab panel! Fasting lipids! Glucose! Lipid subfractions! Inflammatory markers! Plasma insulin

28

(E Flowers, in press, 2010)

Metabolic Syndrome (NCEP ATP III)• Any 3 of the 5

–Abdominal obesity• > 102 cm for males and >88 cm for women

–Elevated Triglycerides• >150 mg/dL

– Low HDL cholesterol (<40 mg/dL for men, <50 mg/dL for women)

– Elevated Blood Pressure • (>130/85 mm Hg)

– Elevated fasting glucose• (>110 mg/dL)

• Shown to markedly underestimate prevalence of Metabolic Syndrome

Metabolic Syndrome (IDF)

• Waist Circumference(> 90 cm for men, >80 cm for women)

+Any two of following

–Elevated Fasting Glucose >100 mg/dL–Elevated Triglycerides (> 150 mg/dL)–Elevated Blood Pressure ( > 130/85 mm Hg)–Low HDL (<40 for men, <50 for women)

Table 1 Demographic and clinical characteristics (n=1445)

Characteristics Mean ± SD or n (%)

Men (n = 1012)

Women (n = 433)

p-value

Age (years) 43 ±10 43 ±10 43 ±11 0.6 Birth country (n = 849)

South Asia 763 (89) 526 (90) 237 (87) 0.6 United States 40 (5) 26 (4) 14 (5) 0.5

Married 1343 (93) 947 (94) 396 (91) 0.2 Education

Less than Bachelorʼs 52 (4) 21 (<1) 31 (7) <0.05 Bachelorʼs 326 (23) 175 (17) 151 (35) <0.05 Graduate/Masterʼs 932 (65) 707 (70) 225 (52) <0.05 PhD/post-grad 132 (9) 106 (11) 25 (6) <0.05

Behaviors Current smoking 54 (4) 49 (5) 5 (1) <0.05 Former smoking 187 (13) 177 (17) 10 (2) <0.05

Family history of CVD Parent 811 (56) 560 (55) 251 (58) 0.3 Sibling (n = 678) 274 (40) 181 (39) 93 (43) 0.5

Clinical variables TC (mg/dL) 190 ± 37 192 ± 37 185 ± 35 <0.05 LDL (mg/dL) 116 ± 31 118 ± 32 111 ± 29 <0.05 HDL (mg/dL) 45 ±12 42 ± 10 53 ± 13 <0.05 TG (mg/dL) 144 ± 93 159 ±100 110 ± 63 <0.05 Glucose (mg/dL) 90 ± 16 92 ± 18 87 ± 12 <0.05 Systolic blood pressure (mmHg) 118 ± 17 120 ± 17 113 ± 17 <0.05 Diastolic blood pressure (mmHg) 76 ± 11 78 ± 11 72 ± 11 <0.05 BMI (kg/m2) 25.7 ± 3.7 25.8 ± 3.5 25.6 ± 4.1 0.3 Waist circumference (cm) 88 ± 13 91 ± 12 82 ± 12 <0.05 Metabolic syndrome 387 (27) 315 (31) 72 (17) <0.05


Regional data among Indians

32

Region %

Northern 22%

Southern 40%

Eastern 5%

Western 27%

Central 3%



Men (n = 1012)

Women (n = 433)

p-value










Men (n = 1012)

Women (n = 433)

p-value









*adjusted for age, smoking, and education level

Characteristic Unadjusted OR (95% CI) Adjusted* OR (95% CI)

TC > 200mg/dl 0.6 (0.5, 0.8) 0.7 (0.5, 0.9)

LDL > 160mg/dl 0.4 (0.2, 0.6) 0.4 (0.2, 0.6)

HDL < 40mg/dl (men) < 50mg/dl (women)

1.1 (0.9, 1.3) 1.0 (0.8, 1.3)

TG > 200mg/dl 0.3 (0.2, 0.4) 0.3 (0.2, 0.4)

Glucose > 126 mg/dl 0.3 (0.1, 0.8) 0.3 (0.1, 0.7)

Blood pressure > 140/90 0.5 (0.3, 0.7) 0.5 (0.4, 0.8)

BMI > 25 0.7 (0.6, 0.9) 0.8 (0.6, 1.0)

WC > 90cm (men) >80cm (women)

1.2 (0.9, 1.5) 1.3 (1.0, 1.6)

Gender differences(for women compared to men)


Relationship of HDL and HDL2b (n=798; from 2008)

35

HDL 2b:> 20% desirable; < 10%: high risk;

Only 77% of variability of HDL-2b is explained by HDL-C

44 of 216 had low HDL2b with normal HDL1, HDL may be “normal” despite

impaired reverse cholesterol transport2. HDL-2b may add prognostic value, especially in borderline or low-normal HDL


Clinical characteristics

37

0

5

10

15

20

25

30

35

Smoking HTN LDL > 160 TG > 250

Framingham Offspring StudyAsian Indians

(Enas, Indian Heart J, 1996)

Framingham risk factors

38

0%

13%

26%

39%

0 1 2 3 4 5

0%

5%

17%

26%28%

27%

1%

6%

21%

28%27%

17%

Men Women

Metabolic syndrome: # criteria (ATP III)

# of metabolic risk factors

Waist > 40”M. 35”FHDL ! 40M, 45FHypertensionTG " 150Glu " 100

p < 0.001 between sexes

Metabolic Syndrome Phenotypesn(%)

n = 854

Men

n = 589

Women

n = 265

p-value*

WC only 212 (25) 106 (18) 106 (40) <0.003

WC + HTN 63 (7) 47 (8) 16 (6) 0.3

WC + HDL 102 (12) 59 (10) 43 (16) <0.003

WC + TG 65 (8) 47 (8) 18 (7) 0.5

WC + glu 30 (4) 19 (3) 11 (4) 0.5

WC + HTN + HDL 37 (4) 27 (5) 10 (4) 0.6

WC + HTN + TG 28 (3) 23 (4) 5 (2) 0.1

WC + HTN + glu 19 (2) 15 (3) 4 (2) 0.3

WC + HDL + TG 137 (16) 111 (19) 26 (10) <0.003

WC + HDL + glu 15 (2) 10 (2) 5 (2) 0.8

WC + TG + glu 22 (3) 16 (3) 6 (2) 0.7

WC + HTN + HDL + TG 55 (6) 46 (8) 9 (3) 0.02

WC + HTN + HDL + glu 10 (1) 9 (2) 1 (<1) 0.1

WC + HTN + TG + glu 13 (2) 12 (2) 1 (<1) 0.07

WC + HDL + TG + glu 22 (3) 20 (3) 2 (1) 0.02

WC + HTN + HDL +TG + glu 24 (3) 22 (4) 2 (1) 0.02

*Bonferroni corrected p-value for 16 comparisons is 0.003

Metabolic Syndrome Prevalence

*Population based sample **Convenience sample

Summary

! High prevalence of metabolic syndrome (31%M, 17%F)! Very high prevalence of increased waist circumference

based on IDF/WHO cutpoints (58%M, 62%F)! Prevalence of high TG much higher in men (23%M,

8%F)! Only 13% with elevated fasting glucose! HTN not as prevalent (16%M, 9%F)! Most common MetS phenotype was high WC + low

HDL + high TG! Obesity, dyslipidemia markedly out of proportion to

measurable insulin resistance

41

What about young South Asians?(When does it start?)

! Of 2096 participants, 678 were below age 40 at time of screening

NCEP/ATP III MetS Components in SAHC cohort, age < 40

Component Total Men Women

Low HDL (<40 for women,<50 for men) 48.8% 47.9% 51.0%High Triglycerides (>150 mg/dL) 36.1% 46.6% 11.4%High Systolic BP(> 130mm Hg) 18.1% 20.7% 16.1%High Diastolic BP (>85 mm Hg) 16.1% 20.7% 5.5%High Waist Circumference(>102 cm for men and >88cm for women)

11.2% 10.1% 13.9%High glucose(>110mg/dL) 3.24% 3.99% 1.49%

Prevalence of # of Components of Metabolic Syndrome (NCEP)

Number Total Men Women

0 31.4% 26.7% 43.0%1 30.5% 27.9% 30.5%2 25.0% 28.8% 15.5%3 9.4% 12.2% 2.6%4 3.4% 4.0% 2.1%5 0.3% 0.4% 0%

Metabolic Syndrome: 13.1% of population; 16.6% of men and 4.7% of women

IDF MetS Components inSAHC cohort, age < 40

Total Men WomenHigh Waist Circumference+0 risk factors 31.0% 26.1% 42.6%High Waist Circumference + 1 risk factor 34.7% 30.7% 44.1%High Waist Circumference +2 risk factors 24.5% 30.5% 10.4%High Waist Circumference + 3 risk factors 8.11% 10.5% 2.5%High Waist Circumference+4 risk factors 1.78% 2.3% 0.50%

Prevalence of Metabolic Syndrome: 34.4% of population, 43.3% of men, 13.4% of women

Lp(a)

Total Men Women

Lp(a) >20 mg/dL43.4% 41.0% 50.0%

-2-3 x greater risk of MI-Primarily genetic-Associated with cardiovascular disease inhibit fibrinolysis increase LDL oxidation increase deposition of cholesterol-Lp(a) > 20 mg/dL considered abnormal

Average Total Men Women

Lp(a) (mg/dL) 29.2+32.2 26.1+28.4 37.7+39.7

Relationship of metabolic syndrome to dyslipidemia

47

# MetS criteria 0 1 2 3 4 5 p =

Total Chol

LDL

LDL iiia+b (%)

HDL

LDL:HDL

HDL2B (%)

TGs

196 196 187 199 191 220 NS

122 120 112 128 108 142 NS

15 19 25 27 27 34 <0.01

52 48 41 40 38 32 0.01

2.3 2.5 2.7 3.2 2.8 4.5 <0.01

18 14 11 11 9 8 <0.01

109 166 167 189 238 256 NS

Relationship of metabolic syndrome to inflammatory and thrombotic biomarkers

48

# MetS Criteria 0 1 2 3 4 5

Lp(a)

Homocysteine

CRP

Fibrinogen

41.4 38.6 32.5 31.7 23.9 10.5

11 10.6 12 12.7 12.5 13.5

2.1 1.5 2.4 2.4 2.6 7.8

321.7 336.3 339.2 345 385.6 410.5

• Adjusting for statin, niacin, folate, and B12 therapy, mean Lp(a) fell 3.39 mg/dL for each extra component of MetS, while mean homocysteine and CRP rose 0.35 umol/ml and 0.24 mg/L, respectively (for all, p < 0.001 for trend).

(Divakaruni M, accepted for ACC 2010)

Conclusions

! In this cohort of young- and middle-aged South Asian participants presenting for screening:! Large burden of traditional risk factors present at

an early age! Consistent with Interheart (Yusuf et al), Atlanta & SHARE

(Canada) studies! Occurs despite higher educational status and higher rates

of private insurance and access to care

! Abnormal waist circumference, LDL, HDL across all age ranges. Affected younger patients are more likely male

! High prevalence of metabolic syndrome components without hyperglycemia

49

Risk stratification and treatment of the Bay Area South Asian population is

an unmet clinical need

Recommendations

! Role of generalized advanced lipid and biomarker screening is controversial in all patients, including South Asians

! South Asians adults, even age 20-40, should have a waist circumference, lipid panel, and blood pressure performed

! Exercise, caloric restriction, weight loss! Lp(a) may be a useful adjunct, but prognosis

and management of isolated elevated Lp(a) is unclear

51

It’s in the genes...

! Beta-fibrinogen (455GA, 148CT)

! Factor VII (10bp promotor, R353Q; protective?)! ATP-binding cassette transporter (237indelG; 8994AG)

! Platelet glycoprotein IIIa (A2 variant)

! Apolipoprotein E (E3/E4 genotype)

! Thrombomodulin (Ala455Val in smokers)

! Endothelial nitric oxide synthase (Glu298Asp)! Tumor necrosis factor 2 (MM variant)

! PECAM-1 (Leu125Val)

! Cardiomyopathy (not CAD): Protein myosin binding chain PMBC3 (Nature Genetics, 2009)

52

Polymorphisms uniquely associated with CAD in South Asians:

Telomere shortening occurs in Asian Indian Type 2 diabetic patients.Adaikalakoteswari A, Balasubramanyam M, Mohan V.

METHODS: Measure of average telomere size, in leucocyte DNA. Type 2 diabetic patients without any diabetes-related complications (n = 40) and age- and sex-matched control non-diabetic subjects (n = 40) were selected from the Chennai Urban Rural Epidemiology Study (CURES).

RESULTS: Mean (+/- SE) TRF lengths of the Type 2 diabetic patients (6.01 +/- 0.2 kb) were significantly shorter than those of the control subjects (9.11 +/- 0.6 kb) (P = 0.0001). Among the biochemical parameters, only levels of TBARS showed a negative correlation with shortened telomeres in the diabetic subjects (r = -0.36; P = 0.02). However, telomere lengths were negatively correlated with insulin resistance (HOMA-IR) (r = -0.4; P = 0.01) and age (r = -0.3; P = 0.058) and positively correlated with HDL levels (r = 0.4; P = 0.01) in the control subjects. Multiple linear regression (MLR) analysis revealed diabetes to be significantly (P < 0.0001) associated with shortening of TRF lengths.

CONCLUSIONS: Telomere shortening occurs in Asian Indian Type 2 diabetic patients.

Diabet Med. 2005 Sep;22(9):1151-6.

Thank you

54

early cardiovascular risk factors disclosures in south asians … · p ar tm en of mdic i ,s j h...

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