The Canadian Cardiovascular Society IS IT AND WHAT SHOULD ...
Cardiovascular Disease from the Canadian and International Perspectives
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Cardiovascular Disease from the Canadian and International
Perspectives
Dr. Sonia Anand MD, PhD
Professor of Medicine
McMaster University
Canadian Heart Health Strategic –Action Plan
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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
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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
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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
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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
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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
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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
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Comparing Ethnic Groups
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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
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Other
Immigrants
Aboriginal
74%
24%
ImmigrantsAboriginal
• 922,000 Chinese
•723,000 South Asians
•1,100,000 + Aboriginal people
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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
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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
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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
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↑ 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
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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
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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
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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
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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*
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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
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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
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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
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EVOLUTION OF RISK FACTORS IN URBAN MIGRANTS
• Calories
• Activity
• Cultural Stressors
• Diabetes
• Hypertension
• Dyslipidemia
CVD
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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
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Risk Factor Frequency Varies
Are the same risk factors important in all ethnic groups, age groups, and
women and men?
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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
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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%
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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
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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)
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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
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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)
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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)
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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
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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)
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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
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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%
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Risk factors the same, Frequency Varies
Risk factors for MI are the same for all ethnic groups, young and old, and women and men.
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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
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Prevention and Treatment of Risk Factors/CVD
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-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
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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
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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%
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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
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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?
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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
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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
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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
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Swimming Upstream
Fast Food
Energy Saving Devices
Tobacco Advertising
Simple Lifestyle Intervention
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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
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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
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Intervening on the causes of CV risk factors
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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
%%
%
%
%
%
%
%
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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%
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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
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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
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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)
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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