Persistent Pathogens Linking Socioeconomic Position and Cardiovascular Disease

1
Persistent Pathogens Linking Socioeconomic
Position and Cardiovascular Disease

• Amanda M. Simanek, MPH
• PhD pre-candidate
• University of Michigan-School of Public Health
• Department of Epidemiology
• Michigan Epidemiology Conference
• April 4th, 2008

PhD Advisor Dr. Allison Aiello
2
Outline

• Background
• Hypothesis
• Methods
• Results
• Discussion

3
Background

• Deaths from heart disease1
• Decreased by over 50 in the past 60 years
• Cardiovascular disease (CVD) is leading cause of
  death in U.S. and Michigan2
• Women and men
• 2004, 27 of all deaths nationally3
• 2005, 30,147 heart disease and stroke deaths in
  Michigan4
• Socioeconomic disparities in CVD persist 5-9
• Reported heart disease, ischemic heart disease,
  hypertension, and stroke inversely related to
  poverty status, education and income10

4
Background

• Risk Factors
• smoking
• physical inactivity
• higher body mass index (BMI)
• higher low-density lipoproteins levels
• However, studies have shown that not all of the
  variation in CVD, according to socioeconomic
  position (SEP) is explained by these traditional
  risk factors11,12

5
Background

• Alternative mechanisms?
• Biological Influences of Psychosocial Stress
• Inflammatory markers such as C-reactive protein
  and Interleukin-6 13-17
• - Reactivation of persistent infections
• Act as pro-inflammatory stimuli and contribute to
  chronic inflammation 18-21

6
Biological Pathways Between Infection and CVD
Chronic Infection/ Reactivation
Inflammatory Response
Endothelial Damage
Lipid/Debris Accumulation
Monocytes/ Macrophages/ Foam Cells
Intimal Thickening
Atherosclerosis
Fatty Streak
7
Background

• Studies have shown
• Association between SEP and infections22-26
• Cytomegalovirus (CMV),
• Herpes simplex 1 and 2 (HSV-1 and 2)
• Chlamydia pneumoniae
• Helicobacter pylori
• Others
• Associations between pathogens and CVD
  outcomes27-40
• Individual pathogens
• Various combinations of pathogens

8
Hypothesis
Socioeconomic Position
Cardiovascular Disease
Pathogens
Pathogens
b
a
ab indirect effect
Cardiovascular Disease
Socioeconomic Position
c direct effect
ab c total effect
Pathogens of Interest CMV, HSV-1, Both
9
Hypothesis

• CMV
• HSV-1
• Infections initially contracted at a young age
• High seroprevalence by age 50
• Persist in latent state with periodic
  reactivation over the life course
• Opportunity to cause chronic inflammation

10
Methods
11
Methods

• Study Population and Study Design
• National Health and Nutrition Examination Survey
  (NHANES) III (1988-1994)
• Cross-sectional study
• Age 45
• History of CVD
• Seropositivity CMV (N7866),  HSV-1 (N4156),
  and both pathogens (N4136)

12
Methods

• Measures
• Exposure
• SEP years of education
• Mediator
• Pathogens CMV and HSV-1 IgG antibody
  seroprevalence
• Pathogen burden total number of pathogens to
  which subjects were seropositive (range 0-2)
• Outcome
• CVD History reported history of one or more
  conditions
• congestive heart failure, stroke or heart attack
• Covariates
• Age, gender, race, smoking and diabetes

13
Methods

• Statistical Analyses
• SAS with SUDAAN (SAS Institute, Inc., Cary, NC).
• Weights and adjustments for strata and clustering
• Logistic regression
• Odds ratios and 95 percent confidence intervals
  (95 CI)
• Mediation
• Sobel Test Statistic
• compares the strength of the indirect effect of
  SEP on CVD (mediated by pathogen) to the null
  hypothesis that the indirect effect equals zero

14
Confounders
Age Gender Race Smoking Diabetes
Age Gender Race
Age Gender Race
Mediators
Pathogens
Cardiovascular Disease
Socioeconomic Position
Outcome
Exposure
15
Results
16
Relationship Between Covariates and History of
Cardiovascular Disease
17
Relationship Between Covariates and History of
Cardiovascular Disease
18
Seropositivity
19

• Mediation

20
Testing Mediation
CVD
SEP
Model 1 unadjusted (N8134) Model 2 adjusted
for age, gender and race (N8134) Significant at
plt0.05  
21
Testing Mediation
SEP Pathogens
Model with CMV adjusted for age, gender and race
(N7810) Models with HSV-1 (N4129) or both
pathogens (N4109) adjusted for age and race
Significant at plt0.05
22
Testing Mediation
Pathogens CVD, Controlling for
SEP
 
Model with CMV adjusted for age, gender,
diabetes and education (N7810) Model with HSV-1
adjusted for age, gender and education
(N4129) Model with both pathogens adjusted for
age, race, diabetes and education
(N4073) Significant at Plt0.05
23
Testing Mediation  
SEP CMV CVD
Model 1 adjusted for age and gender,
N7810. Model 2 adjusted for age, gender and CMV
seropositivity, N7810. Significant at plt0.05
24
Discussion

• After controlling for CMV, the odds of CVD
  history for those at the lowest education level
  compared to the highest were reduced by 7.5
• CMV was the only pathogen to partially mediate
  the relationship between SEP and CVD
• Seropositivity to HSV-1 and to both pathogens was
  not associated with CVD history in this sample
• Reactivation with CMV over the life course may
  have more detrimental effects on CVD than HSV-1
• CMV more consistently linked with CVD than
  HSV-142-45
• More likely to be found in the vasculature

25
Limitations

• Cross-sectional
• However, exposure to these herpes viruses
  generally occurs early in life
• Self-reported CVD history
• Measurement error

26
Conclusion

• Next step
• Examine how these infections mediate relationship
  between SEP and CVD incidence over time
• NHANES mortality data
• Implications
• Uncover social and biological mechanisms
  underlying SEP disparities in CVD
• Prevention of and/or vaccination against CMV
  infection could serve to ameliorate SEP
  disparities in CVD

27
Acknowledgements

• Allison E. Aiello, PhD
• Jennifer Beam Dowd, PhD
• Questions?

28
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32
Methods

• Sobel Test Statistic
• -compares the strength of the indirect effect of
  SEP on CVD (mediated by pathogen) to the null
  hypothesis that it equals zero
• ab
• Standard error of ab
• -yields a critical ratio (z-score)
• -usually compared with the critical value from
  the standard normal distribution
• -assumes large sample size