Physicians' Academy for Cardiovascular Education

Traditional risk factors only explain 11% of the variance in carotid intima media thickness

Literature - Rundek T, Blanton SH; Bartels S, et al. - Stroke. 2013;44:2101-2108


Traditional Risk Factors Are Not Major Contributors to the Variance in Carotid Intima-Media Thickness
 

Rundek T, Blanton SH; Bartels S, et al.
Stroke. 2013;44:2101-2108
 

Background

Carotid intima-media thickness (cIMT) has been a widely accepted imaging marker of subclinical atherosclerosis in the past [1-3]. It is now increasingly clear that IMT is a separate phenotype from a focal carotid plaque, possibly with different  biological and genetic underlying factors [4,5].
Traditional vascular risk factors such as hypertension, diabetes mellitus, dyslipidemia and smoking explain <50% of the variance of atherosclerotic plaque burden [6-9]. They may however not account for so much of the variance in IMT, especially in plaque-free location [5,10].
This study aimed to assess the contribution of traditional and less traditional vascular risk factors to the variance in cIMT and to identify individuals whose cIMT is not explained by these factors to serve as a resource for future genetic and environmental research. 1790 Stroke-free participants of the prospective population-based Northern Manhattan Study (NOMAS) and concurrently enrolled in the Oral Infections and Vascular Disease Study (INVEST) cohort were studied in the carotid imaging ancillary study.

 
Main results

  • After correction for age, significant associations with cIMT were seen for male sex, moderate alcohol intake, increase in waist-to-hip-ratio, pack-years of smoking, fasting glucose level, white blood cell count, and lower levels of adiponectin.
  • A step-wise multiple regression model including traditional risk factors identified the following factors as significant contributors to variance in cIMT: age (7%), male sex (3%), glucose (<1%), pack-years of smoking (<1%) and LDL-C (<1%), amounting to 11% in total.
  • A modified model that also included less traditional factors could explain 16% of the variance. This was the result of the contribution of age (9%), male sex (3%), LDL-C (0.9%), BMI (0.9%) and fasting glucose (0.7%). Furthermore, low but statistically significant contributions were seen for adiponectin (0.4%), pack-years of smoking (0.4%) and black race-ethnicity (0.3%).
  • Other less traditional risk factors such as homocysteine, cGFR and inflammatory markers did  not significantly explain the cIMT variance.
 

Conclusion

In this multiethnic, urban population, traditional vascular risk factors explained only 11% of the variance in cIMT, with the largest contribution of age and sex. Addition of other less traditional factors could explain a further 5% of the variance.  Thus, most of the cIMT variance is not explained by traditional vascular risk factors that are commonly investigated in cerebrovascular research or in preventive clinics.
 

References

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