Cardiovascular Disease from the Canadian and International

Perspectives

Dr. Sonia Anand MD, PhD

Professor of Medicine

McMaster University

Canadian Heart Health Strategic –Action Plan

Overview

• Global Burden of CVD

• Canadian Burden of CVD

• Ethnic Variations in Risk factors

• Association between Risk factors and CVD

• Strategies for Prevention

• Call for Action

CHANGE IN THE RANK ORDER OF DISEASE BURDEN FOR 10 LEADING CAUSES, WORLD, 1990-2020 (DALYS)

1. Lower resp infection2. Diarrh diseases3. Perinatal4, Major depression5. Coronary heart dis6. Stroke 7. TB8. Measles9. Traffic accidents10. Cong anomalies

1 Coronary heart disease2. Major depression3. Traffic accidents4. Stroke 5. COPD6. Lower resp infections7. TB8. War9. Diarrhoeal disease10. HIV

1990 2020

Reddy K. N Engl J Med 2004;350:2438-2440

Worldwide Deaths from Cardiovascular Causes

9

195

6

0

5

10

15

20

25

30

1990 2020

WesternCountries

Non-Western(developing)countries

Mil

lio

ns

of

De

ath

s

fro

m C

ard

iov

as

cu

lar

Dis

ea

se

Numbers with DM (Diagnosed)

0

50

100

150

200

250

300

350

400

N (

mil

lio

ns)

1995 2000 2030

Developed WorldDeveloping World

Whole World

Diabetes Care 2004:1047

Age-standardized mortality rates of CVD

and Cancer in Canada

150

160

170

180

190

200

210

220

230

240

1994 1995 1995 1996 1997

CVD

Cancer

Pe

r 10

0,0

00

Statistics CanadaCVD= IHD, CBVD, DM, ATH

Risk Factor Proportion of the Population

Aged 20-59 Years(%)

Tobacco Smoking (Daily) 25.7

Physical Inactivity 55.5

Overweight (BMI > 25.0) 47.5

Less than Recommended Consumption of Fruits and Vegetables

64.7

High Blood Pressure 8.3

Diabetes* 2.7

Source:   Statistics Canada, Canadian Community Health SurveyThe Growing Burden of Heart Disease and Stroke in Canada 2003

Canada’s Modifiable Risk Factors

Comparing Ethnic Groups

Mortality for CHD and Cancer Age 35 – 74(1979-1993)

0

20

40

60

80

100

120

140

160

CH

D &

Can

cer

Mo

rtali

ty .

.

Rate

/100,0

00

South Asian Chinese European

CHD

Cancer

Sheth et al, CMAJ 1999

Other

Immigrants

Aboriginal

74%

24%

ImmigrantsAboriginal

• 922,000 Chinese

•723,000 South Asians

•1,100,000 + Aboriginal people

SHARE: Study of Health Assessment and Risk in Ethnic Groups

Random Sample - Europeans, South Asians, Chinese, Aboriginal

Environmental

Factors•Lifestyle•Nutrition•Psychosocial•Cultural

Genetic Factors

Risk Markers

•Lipids

•Coagulation

•Glucose

•BP

•Antioxidants

•Homocysteine

Subclinical Disease

•Carotid

•Ankle Arm BP

•LVH

•Micro Alb.

Clinical

Events

•CAD

•Stroke

•PVD

Anand S et al Can J Cardiol 1998

22.70%16.70%

3.90%

12.50%

1.90%

9.60%

15.50%

2.30%

15.60%

Percent Distribution By Province ofRegistered Indian Population in Canada

Overweight and Abdominal Fat

0

10

20

30

40

50

60

Euro Chinese S Asian Aboriginal

Obese

Abdo Obese

Anand et al SHARE Lancet 2000/1

BMI ≥30; WHR > 0.85 (female)/1.0 (male)

%

Age and sex Adjusted

↑ Glucose: Dysglycemia

2.8

22

6.34.6

10.0

17

11.5 15.3

18.7

5.82.5

0

5

10

15

20

25

30

35

EURO CH S. ASIAN AP

%

Established DM New DM IGT

11

Anand et al SHARE

Relationship of Glucose Factor to Body Mass Index Among South Asians, Chinese, Aboriginals and Europeans

-1.5

-1

-0.5

0

0.5

1

15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

BMI

Glu

co

se

Fa

cto

r

SA

CH

EC

AP

BMI = 20.6 in SA

BMI = 21.0 in CH

BMI = 30.0 in ECBMI = 21.5 in AP

Razak et al Circ 2005

BMI=21 BMI = 30

Relationship of Glucose Factor to BMI in Non-white ethnic groups

5.4

2.4

10.3

17.3

0

2

4

6

8

10

12

14

16

18

EURO Chinese South Asian Aboriginal

CVD Prevalence

Age and Sex Adjusted

CVD Prevalence comparing Ethnic Groups in Canada

Anand et al SHARE

SHARE- NutritionSouth Asians

Chinese Euro AP

N 173 167 185 92

Age 46.3 45.8 47.7 51.6

Calories/Day 1911 1898 2072 2242*

% Vegetarian 18.8* 2.1 0.6 1.2

Total Fat g/day 59.1 70.3* 61.8 69.8

Saturated Fat g/day 19.6 17.3* 21.6 25.7

Carbohydrates g/day 298.8* 240.7 269.5 256.7

Sugar g/day 11.2* 6.9 8.9 6.7

Protein g/day 70.1* 100.5* 78.0 82.1

Anand et al SHARE

SHARE- Fat Intake

South Asians

Chinese Euro

Fried Foods(# serv./week)

4.8 3.9 5.0

Total Fat g/day 59.1 70.3* 61.8

Saturated Fat g/day 19.6 17.3* 21.6

Trans Fats (g) 0.34 0.27 0.56*

SHARE- Fish

South Asian

Chinese Euro

Fish (# serv./week) 1.1 6.3* 1.6

Omega-3 FA 0.13 0.76 0.04

Omega-6 FA 0.37 0.42 0.31

Anand, S. S et al. Int. J. Epidemiol. 2006 35:1239-1245; doi:10.1093/ije/dyl163

Aboriginal and South Asian ♂

Aboriginal and South Asian ♀

Chinese ♂/ ♀

Risk of CVD and Social Disadvantage

Changes in Risk Factors with Migration

19.4

9.3

51.6

13.5 16.8

1.86.6

23.519

1

19.1

26.325.2

0

10

20

30

40

50

60

Rurual India Urban India Canada

% R

isk F

acto

r

0

5

10

15

20

25

30BMI

Smoke

DM

HTN

BMI

36 lbs42 lbs

n=972 n=342n=775

EVOLUTION OF RISK FACTORS IN URBAN MIGRANTS

• Calories

• Activity

• Cultural Stressors

• Diabetes

• Hypertension

• Dyslipidemia

CVD

INTERHEART: Design

Cases: First Acute Myocardial Infarction (n=15,152)

Controls: Matched to cases by age (+/-5 yr and sex) at each site (n=14,820)

Data collected from 262 sites in 52 countries

Coordinated by the Population Health Research Institute, McMaster University, Canada

Ounpuu S et al Am Heart J 2001

Risk Factor Frequency Varies

Are the same risk factors important in all ethnic groups, age groups, and

women and men?

INTERHEART: Design

Cases: First Acute Myocardial Infarction (n=15,152)

Controls: Matched to cases by age (+/-5 yr and sex) at each site (n=14,820)

Data collected from 262 sites in 52 countries

Coordinated by the Population Health Research Institute, McMaster University, Canada

Ounpuu S et al Am Heart J 2001

ArgentinaArgentina

AustraliaAustralia

BahrainBahrain

BangladeshBangladesh

BeninBenin

BotswanaBotswana

BrazilBrazil

CameroonCameroon

CanadaCanada

ChileChile

China/Hong KongChina/Hong Kong

ColombiaColombia

CroatiaCroatia

Czech RepCzech Rep

EgyptEgypt

GermanyGermany

GreeceGreece

GuatemalaGuatemala

HungaryHungary

IndiaIndia

IranIran

IsraelIsrael

ItalyItaly

JapanJapan

KenyaKenya

KuwaitKuwait

MalaysiaMalaysia

MexicoMexico

MozambiqueMozambique

NepalNepal

New ZealandNew Zealand

NetherlandsNetherlands

NigeriaNigeria

PakistanPakistan

PhilippinesPhilippines

PolandPoland

PortugalPortugal

QatarQatar

RussiaRussia

SeychellesSeychelles

SingaporeSingapore

S AfricaS Africa

SpainSpain

Sri LankaSri Lanka

Sultanate of OmanSultanate of Oman

SwedenSweden

ThailandThailand

UAEUAE

UKUK

USAUSA

ZimbabweZimbabwe

INTERHEART: > 27,000 Cases and Controls

Arab10%

Latin Am11%

Oth Asian6%

Col Afr2%

Other1%

Euro26%

Bl Afr2%

S Asian18%

Chinese24%

INTERHEART Global Case-Control Study: Nine Modifiable Risk Factors

• Smoking

• Elevated Lipids: ↑ ApoB/Apo A ratio

• Diabetes

• Hypertension

• Abdominal Obesity: ↑ Waist to Hip Ratio

• Physical Activity: > 4 hrs/week

• Alcohol: ≥ 3 drinks/week

• Fruit and Vegetable Consumption: Daily

• Psychosocial Stress: Work/home stress, depression, financial stress, locus of control

• >27,000 subjects• 52 Countries • 6000 women• > 12,000 > age 60 yrs

Risk of MI associated with Risk Factors in the Overall Population

Risk factor % Cont % Cases OR (99% CI)adj for all

PAR (99% CI)

ApoB/ApoA-1 (5 v 1) 20.0 33.5 3.25 (2.81, 3.76) 49.2 (43.8, 54.5)

Curr smoking 26.8 45.2 2.87 (2.58, 3.19) 35.7 (32.5,39.1)

Abd Obesity (3 v 1) 33.3 46.3 1.62 (1.45, 1.80) 20.1 (15.3, 26.0)

Hypertension 21.9 39.0 1.91 (1.74, 2.10) 17.9 (15.7, 20.4)

Diabetes 7.5 18.4 2.37 (2.07, 2.71) 9.9 (8.5, 11.5)

Psychosocial - - 2.67 (2.21, 3.22) 32.5 (25.1, 40.8)

Veg & fruits daily 42.4 35.8 0.70 (0.62, 0.79) 13.7 (9.9, 18.6)

Exercise 19.3 14.3 0.86 (0.76, 0.97) 12.2 (5.5, 25.1)

Alcohol Intake 24.5 24.0 0.91 (0.82, 1.02) 6.7 (2.0, 20.2)

All combined (extremes)

333.7 (230.2, 483.9) 90.4 (88.1, 92.4)

Risk Factors for Acute MI in the Overall Population

Risk factor % Cont % Cases PAR (99% CI)ApoB/ApoA-1(5 v 1) 20.0 33.5 49.2 (43.8, 54.5)

Current smoking 26.8 45.2 35.7,(32.5,39.1)

Psychosocial - - 32.5 (25.1, 40.8)Abd Obesity (3 v 1) 33.3 46.3 20.1 (15.3, 26.0)Hypertension 21.9 39.0 17.9 (15.7, 20.4)No Veg & fruits 42.4 35.8 13.7 (9.9, 18.6)Low Physical Activity 19.3 14.3 12.2 (5.5, 25.1)Diabetes 7.5 18.5 9.9 (8.5, 11.5)No Alcohol 24.5 24.0 6.7 (2.0, 20.2)Combined - - 90.4 (88.1, 92.4)

Over 90% of AMI are predicted by these nine risk factors

Lancet 2004

INTERHEART: Apolipoprotein B/A-1 and MI

Deciles: 1 2 3 4 5 6 7 8 9 10

Cont 1210 1206 1208 1207 1210 1209 1207 1208 1208 1209

Cases 435 496 610 720 790 893 1063 1196 1366 1757

Median 0.43 0.53 0.60 0.66 0.72 0.78 0.85 0.93 1.04 1.28

1

2

4

8

OR

(99

% C

I)

INTERHEART: Smoking and MI

1

2

4

8

16

Cont 7489 727 1031 446 1058 96 230 168 56Cases 4223 469 1021 623 1832 254 538 459 218OR 1 1.38 2.10 2.99 3.83 5.80 5.26 6.34 9.16

Never 1-5 6-10 11-15 16-20 21-25 26-30 31-40 41+

OR

(9

9%

CI)

Independent risk of MI associatedwith 2 markers of obesity

0

1

2

3

4

<20 20-23 23.1-25 25.1-27 27.1-30 >30 1st 2nd 3rd 4th 5th

OR

BMI

- adjusted for age, sex, smoking, region

…+ WHR

WHR

adjusted for age, sex, smoking, region

… + BMI

INTERHEART DIETARY ANALYSIS

• Methods– 6,530 cases and 10,792 controls– 19 items food groups questionnaire

• Dietary Patterns:– Prudent diet: raw and cooked vegetables, legumes and

fruits– Oriental diet: tofu, soy sauce and green leafy vegetables– Western diet: dairy, fried foods and meats (high in saturated fats)

Dietary Intake Varies by Ethnicity

Dietary Patterns:– Prudent diet: raw and cooked vegetables,

legumes and fruits– Oriental diet: tofu, soy sauce and green leafy

vegetables– Western diet: dairy, fried foods and meats (high in

saturated fats)

Iqbal et al 2006

0

0.2

0.4

0.6

0.8

1

1.2

1.4

Prudent Oriental Western

Lowest

Highest

Adjustment factorsAge, sex, region, BMI, WHR, physical activity, alcohol intake, smoking, apoB/apoA1, psycho-social factors, and education

Iqbal R et al 2006

INTERHEART: Relative Risk of MI by Dietary Type

↓ 24%

↑ 29%

Risk factors the same, Frequency Varies

Risk factors for MI are the same for all ethnic groups, young and old, and women and men.

Association between Risk factors and CHD is similar btwn ethnic groups

CHD

Dysglycemia

Smoking

Dyslipidemia

Risk Factors DiseaseDeterminants

Adiposity

Psychosocial Stress

Blood Pressure

Physical Inactivity

ETOH

Diet QualityPhysical activity

StressAir Pollution

Consistent btwn ethnic groups

Genetic Factors

Environment

Prevention and Treatment of Risk Factors/CVD

-500

0

500

1000

1500

2000

2500

3000

3500

4000

0 1 2 3 4 5 6 7 8 9

Controls

Cases

Frequency of INTERHEART RISK Factors in Cases and Controls

Number of Subjects

Number of Interheart Risk Factors

Risk Factors are Ubiquitous in the Population – We are all at Risk

• 80% of Canadians have 1 Risk Factor

• 30% of Canadians have 2 Risk Factors

• 11% have 3 or more Risk Factors

Source:    Statistics Canada, Canadian Community Health Survey

INTERHEART: Decreased Risk of AMI with Avoidance of Smoking; Daily Fruits/Veg, Reg

Phys Activity & Alcohol

0.35 0.70 0.86 0.91 0.24 0.21 0.19

0.125

0.25

0.5

1.0

no smk Frt/Veg Exer Alc Nosmk+fvg +Exer +Alc

OR

(99

% C

I)

All the “right” things reduce odds of AMI by 80%

RCT Evidence that Altering Risk Factors Lowers CHD

Risk Factor RCT Evidence Strong Alternative Evidence

Abnormal Lipids YesSmoking No Yes (36 % RR) ↑Blood Pressure Yes Diabetes Accumulating YesAbdominal Obesity Some YesPhysical Activity YesFruits and vegetable YesAlcoholAlcohol NoNo Yes (20% RR)Yes (20% RR)DepressionDepression NoNo YesYes

Iestra et al Circulation 2005

Can we prevent 90% of MI in young and middle age NOW?

NO

Can we prevent >90% of MI in young and middle age in the foreseeable future?

YES

How can we prevent the majority of premature CHD?

Prevention of Cardiovascular Disease - Individual Approach

GOAL

Type of Strategy

Examples

Determinants of Risk Determinants of Risk Behaviours in a Behaviours in a

Population Population

Interventions with a Interventions with a Socio-Economic & Socio-Economic &

Political FocusPolitical Focus

• Taxing TobaccoTaxing Tobacco

• Subsidizing healthy Subsidizing healthy foodsfoods

• Promote Physical Promote Physical Activity by improving Built Activity by improving Built EnvironmentEnvironment

Individuals with Risk Factors for

CVD

Interventions with a Preventive

Focus

Identifying & treating ↑ Cholesterol or HypertensionSmoking cessation

Individuals with CVD

Interventions with a Clinical Focus

• Lipid Lowering• Aspirin• Beta blockers• ACE-inhibitors• Appropriate revascularization

Risk Factor Detection and Control

Behavior Change

Policy and Environmental Change

Emergency Care or Acute Case Management

Rehabilitation or Long-term Case Management

End-of-Life Care

PREVENTION, 5% of Resources

High- Risk Treatment Intervention Approaches

TREATMENT, 95% of Resources

Greatest Gains in Preventing CVD: Population Approach

0 5 10 15 20 25 30 35 40

PopulationStrategy

High-RiskStrategy

10 Year Cardiovascular Disease Risk

% of Population

High Risk

Present Distribution

Optimal Distribution

Swimming Upstream

Fast Food

Energy Saving Devices

Tobacco Advertising

Simple Lifestyle Intervention

A Societal Pathophysiologic Pathway for COR HT DIS

RURAL LIFESTYLE

Proximal Determinants of Behaviour• urban structure & mechanization•Food & Tobacco policy•Cultural attitudes•Social/Education•Global influences

URBAN LIFESTYLE

•Consumption of energy rich food•Sedentarines

s (in usual daily activities)•Psychosocial

factors

Obesity and other risk factors

Modifying influences:•Healthcare•Genes•Knowledge & Attitudes

Clinical Events

++

- -

Yusuf et al. Circ 2001

Prevention of Cardiovascular Disease: Population Approach

GOAL

Type of Strategy

Examples

Determinants of Risk Behaviours in a

Population

Interventions with a Socio-Economic &

Political Focus

• Taxing Tobacco

• Subsidizing healthy foods

• Promote Physical Activity by improving Built Environment

Individuals with Individuals with Risk Factors for Risk Factors for

CVDCVD

Interventions with Interventions with a Preventive a Preventive

FocusFocus

• Identifying & Identifying & treating treating ↑ ↑ CCholesterol or holesterol or HypertensionHypertension

•Smoking Smoking cessationcessation

Individuals with Individuals with CVDCVD

Interventions with Interventions with a Clinical Focusa Clinical Focus

• Lipid LoweringLipid Lowering• AspirinAspirin• Beta blockersBeta blockers• ACE-inhibitorsACE-inhibitors• Appropriate Appropriate revascularizationrevascularization

Intervening on the causes of CV risk factors

Change in commuting patterns in the US (from 1980 to 2000)

Commuting in America III - A Pisarski, American Highway Users Alliance: Census Bureau

2.9

4.6

12.2

75.7

5.6

6.2

19.7

64.4

Walking

Transit

Carpool

Driving Alone

1980

2000

%%

%

%

%

%

%

%

Leading risk factors for disease burden in 2000 by development category (% total DALYS)

Developed Countries Developing CountriesTobacco – 12.2% Underweight – 14.9%Blood pressure – 10.9% Unsafe Sex – 10.2Alcohol -9.2% Unsafe Water, Hygiene – 5.5%Cholesterol – 7.6% Indoor Smoke – 3.6%Overweight – 7.4% Zinc Deficiency – 3.2%Low Fruit and Vegetable Intake – 3.9%

Iron Deficiency – 3.1%

Physical Inactivity – 3.3% Vitamin A Deficiency – 3.0%Illicit Drugs – 1.8% Blood Pressure – 2.5%Unsafe Sex – 0.8% Tobacco – 2.0%Iron Deficiency - 0.7% Cholesterol – 1.9%

Finland’s Decline in CHD Mortality over 20 years

0100200300400500600700800900

1969

1970

1973

1975

1977

1980

1983

1985

1987

1990

1992

Ag

e s

tan

da

rdis

ed

mo

rta

lity

pe

r 1

00

,00

0

Men

Women

BMJ. 1994 Jul 2;309(6946):23-7National Strategy

↓ Dairy Product, ↑ Vegetables, ↓ Salt, ↓Animal fats

Decline in Risk Factors in men in Finland

0

10

20

30

40

50

60

1972 1977 1982 1987 1992

Dec

lin

e in

mo

rtal

ity

(%) Smoking

Blood Pressure

Cholesterol

Predicted (all riskfactors)

Observed (all riskfactors)

BMJ. 1994 Jul 2;309(6946):23-7

Men aged 35 – 63

How can we prevent 90% of MI by 2030?

1. Some “causal” risk factors that are modifiable [such as HDL (ApoA), abdominal obesity, hip size, diabetes] need to be changed and demonstrated to reduce CHD

2. LARGE reductions in multiple risk factors are needed

3. Practically ALL adults in Urbanized Societies have abnormalities of at least one risk factor.

• Treat all? (e.g. Polypill)• Prevent the development of risk factors (Societal

interventions - i.e. tobacco policy, community re-design, food supply)

Canadian Landscape

• Need for Public Health Programs to unite against CV Risk Factors (which overlap with Cancer RF’s)

• Partnerships at multiple policy levels (National, Provincial, Regional)

• Need for Target setting and Evaluation of Progress

Robinson et al 2007