CV Risk Factors in South Asians of Canada
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CV Risk Factors in South Asians of Canada
Sonia AnandMcMaster University
Feb 21, 2013
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North America
Australia
Africa
AsiaEurope
Middle East
South and Central America
Excess Coronary Heart Disease in South Asian Migrants
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Mortality for CHD and CancerAge 35 – 74(1979-1993)
0
20
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60
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120
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CH
D &
Can
cer M
orta
lity
.. Ra
te/1
00,0
00
South Asian Chinese European
CHDCancer
Sheth T et al, CMAJ 1999
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South Asian 7%
Black 4%
Other 9%
White 75%Statistics Canada, 2006
Ethnic Profile in Ontario
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Changes in Risk Factors with Migration
51.6
19.4
9.3
1.8
13.5 16.8
6.6
23.519
1
19.1
25.226.3
0
5
10
15
20
25
30
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20
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40
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60
Rurual India Urban India Canada
BMI
% R
isk
Fact
or
Smoke
DM
HTN
BMI
36 lbs42 lbs
n=972 n=342n=775
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1. Weight gain 2. pre-Diabetes 3. Diabetes 4. Heart Disease
Evolution of risk factors in South Asians
• Lipids• Blood Pressure
5.? Some Cancers
6
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Metabolic Syndrome Phenotype: A Cluster of Metabolic Abnormalities
• Abdominal Adiposity
• Dysglycemia• HDL Cholesterol• Triglycerides• +/- Elevated BP
Associated with a significant increase in type 2 diabetes and CHD
Visceral Adipose Tissue
Subcutaneous Adipose Tissue
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Age-Adjusted Prevalence of Metabolic Syndrome in Canada
45.4
26.8
15.9
28.8 28.325.2
14.37.1
41.3
23.4
05
101520253035404550
Overall Chinese Euro SouthAsian
Aboriginal
WomenMen
Age-AdjustedAnand et al Circulation 2003
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0.5 1 2 4 8 16OR (99% CI)
INTERHEART: MS and MI by Region
Region % Contr OR (99% CI) PAR (99% CI)
Overall 26.1 2.69 (2.48,2.92) 29.2 ( 27.1, 31.3)
W Europe 16.7 3.86 (2.61,5.70) 36.0 ( 27.5, 45.4)
C/E Europe 32.0 1.82 (1.46,2.26) 20.4 ( 14.3, 28.2)
Middle E/Egypt 35.7 2.53 (2.08,3.08) 34.8 ( 29.1, 41.1)
Africa 24.6 4.02 (2.76,5.86) 41.7 ( 32.6, 51.4)South Asia 26.9 2.72 (2.18,3.39) 31.6 ( 25.9, 37.9)
China /H.K. 13.9 2.27 (1.89,2.73) 15.1 ( 12.1, 18.7)
S.E. Asia/Japan 22.4 5.59 (4.22,7.41) 50.0 ( 43.5, 56.6)
Aust/N. Z. 26.4 2.20 (1.30,3.72) 22.0 ( 10.5, 40.3)
South Am./Mex. 36.3 2.74 (2.18,3.44) 40.3 ( 33.1, 47.9)
North Am 27.4 2.30 (0.97,5.47) 21.5 ( 5.5, 56.3)
Mente et al JACC
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Summary of Risk Factors
• 1) Increased body fat• 2) Tendancy toward central adiposity• 3) Visceral Fat excess• 4) Fatty liver• 5) Low HDL, High LDL, High TRGS• 6) Increased Diabetes• 7) Smoking is lower
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Summary of Presentation, Diagnosis, and Treatment
• Presentation time to hospital with chest pain symptoms is later in SA
• Management of acute coronary syndromes is similar
• Case fatality rate is similar • Long-term morbidity, mortality appears
similar• Lower attendance at Cardiac Rehab
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Pregnancy and Early Childhood
Adult Metabolic Syndrome
Interventions to Change Health
Behaviours
Individual
Community Level
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SouTh Asian BiRth CohorTEarly Life Determinants
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“Thin-fat” baby
• Newborns, relatively small at birth (BW < 2.9 kg) reported to have greater subscapular skin fold thickness, which is shown to correlate well with truncal obesity
• This adiposity tracks to 4 years of age• An increase of BMI of 1 SD from 2 to 12
years of age, increased the odds ratio for disease (IGT / DM) by 1.36. in young adults
Krishnaveni GV, Hill JC, Veena SR, Fall CHD. Indian Pediatr 2005; 42: 527-538New Eng J Med 2004; 350: 865-875.
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LBW persists in South Asian babies in UK
• X- sectional data record linkage 2005 – 2006 n=861,654 births of white, or South Asians
• 1st generation: Born in Indian subcontinent
• 2nd generation: Born in England/Wales
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Singleton Birth Weights
N = 772,128 1st Generation 2nd Generation
White Mean = 3457g
Bangladesh Mean = 3074g 13,261Mean = 3084g
3,015Mean = 3026g
Indian Mean = 3089g 15,733Mean = 3105g
11,368Mean = 3062g
Pakistani Mean = 3130g 28,566Mean = 3148g
17,583Mean = 3097g
Leon, J Epidemiol Community Health 2012;66:544-61
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Birth Weight by Maternal Region of Birth (Canada and South Asia only). Ontario, 2002-2006 Combined
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Risk of Gestational Diabetes Mellitus in Association with Maternal Place of Birth
Canad
ian-B
orn
Indus
trializ
ed N
ation
s
Sub S
ahara
n Afric
a
Carribe
an
East A
sia
South
Asia0
1
2
3
4 Country of Birth
a Odds ratios were adjusted for maternal age (continuous in years), number of livebirths, multifetal pregnancy, place of residence, neighborhood income quintile, and fiscal year of delivery. b Reference category.
Epidemiology: November 2011 – Volume 22 – Issue 6 – pp 879-880.
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Rel
ativ
e R
isk
of
DM
, obe
sity
, CVD
Low HighBirth Weight Higher Risk with
LOW Birth Weight
Higher Risk with HIGH Birth
Weight
• Placental insufficiency • Maternal undernutrition• Hypoxia (smoking, anemia,
altitude) • Genetics
• Maternal diabetes • Obesity• Excess gestational
weight gain • Genetics
Both low birth weight and high birth are associated with long-term metabolic disease risk for offspring
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Diverse Environments
250 Mothers/Babies
250 Mothers/Babies
1000 Mothers/Babies
Rural India Urban India Urban Canada
DIETARY DIFFERENCES (WEIGHT GAIN)
ACCESS to PRIMARY CARE
PSYCHSOCIAL SRESS, SOCIAL SUPPORT
GENETIC/EPIGENETIC FACTORS20
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Birthweight among GA > 37 weeks
START FAMILY (EC)3.15
3.2
3.25
3.3
3.35
3.4
3.45
3.5
3.55
3.6
Series 1
In singleton newborns with a gestational age >=37 weeks
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START: Is thin fat phenotype Observed in Canada?
South Asian FAMILY (EC)2.6
2.7
2.8
2.9
3
3.1
3.2
3.3
3.4
%fat/kg BW
%fat/kg BW
In singleton newborns with a gestational age >=37 weeks
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Epigenetic
• Maternal Exposures linked to DNA methylation in offspring:– Smoking– Depression– Under or over nutrition
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Regions of Genome associated with Birth Weight
• Development and morphagenesis • Cell Cycle/Cell division• Metabolism and biosynthesis• Not imprinted regions or housekeeping
genes• 60% methylation discordance between
heavy and light birth weight babies
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Explanations
• 1) Genetic- Transgenerational, DNA inherited
• 2) EpiGenetic – Transgenerational, inherited, non-DNA
• 3) Cultural: Diet deficiency or imbalance• 4) Other: Brown fat, telomere length
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What can we do to prevent Metabolic Syndrome in about the South Asian population in Canada?
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SAHARA Project
A multi-media based intervention aiming to provide culturally tailored health messaging and feedback to participants with the goal of reducing their cardiac risk score over a 6-month period.
http://www.youtube.com/watch?v=SwZdUSmWBpo
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Screening Cohort• 320 Men and women of South Asian ancestry • Permanent residents of Ontario/BC• ≥30 years• Access to email, cell phone with text messaging
capability, or a smart phone• No previous MI, CABG, Stroke
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Study Outcomes
• Primary outcome: change in IHRS after 1 year• Secondary outcomes:
• Change in components of risk score - blood pressure, HbA1c, waist to hip ratio, and apolipoproteins B and A
• Difference in clinical events between the intervention and control groups at the end of the study
• Rate of change in IHRS over time
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INTERHEART Modifiable Risk Score Report
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Genetic Risk Score Report
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Community or Contextual Factors and Future Interventions
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Social Networks
• 12,000 people tracked for 32 yrs• Social networks play a powerful role in
determining weight gain• If spouse or brother is overweight –1.40x
would be overweight• Friends had the most powerful influence 1.5-
2.0x - “kind of social contagion” • Think about typical S. Asian social networks-
centered around eating, not around moving• Older cultural beliefs must change to prevent
weight gain
Kristakis NEJM 2007
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Social Networks 2008; 30: 330-342.
Obesity in a Facebook Network
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Population & high risk individualized strategy for the Prevention of CVD
GOAL
Type of Strategy
Examples
Determinants of Risk Behaviours in a
Population
Interventions with a Socio-Economic &
Political Focus
• Taxing Tobacco• Subsidizing healthy
foods• Health Education• Promote Physical
Activity
Individuals with Risk Factors for
CVD
Interventions with a
Preventive Focus
• Identifying & treating individuals with high cholesterol or hypertension
• Smoking cessation in a smoker
Individuals with Manifest CVD
Interventions with a Clinical
Focus
• Lipid Lowering• Aspirin• Beta blockers• ACE-inhibitors• Appropriate revascularization
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October 30, 2008
A PolyPill for all?
AspirinStatinThiazideBBACE - I