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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Am J Cardiol. Author manuscript; available in PMC 2010 August 15.
Published in final edited form as:
PMCID: PMC2723724

Relation of Subcutaneous and Visceral Adipose Tissue to Coronary and Abdominal Aortic Calcium (From the Framingham Heart Study)


Body fat distribution may be differentially associated with subclinical cardiovascular disease. We sought to examine whether body mass index (BMI), waist circumference (WC), subcutaneous (SAT) and visceral (VAT) adipose tissue are associated with either prevalence of coronary (CAC) or abdominal aortic calcium (AAC) in the Framingham Heart Study. Participants (n=3130, mean age 52 years, 49% women) free of clinical cardiovascular disease from the Framingham Heart Study underwent multidetector computed tomography assessment for quantification of subcutaneous and visceral fat volume and coronary and abdominal aortic calcification. Coronary artery calcification (CAC) and abdominal aortic calcification (AAC) were examined in relation to BMI, WC, SAT, and VAT in age- sex- and multivariable-adjusted models. All measures of adiposity were associated with CAC in age-sex adjusted models (all p-values<0.008). All relations were attenuated in multivariable models (all p-value>0.14). BMI, WC, and VAT (but not SAT) were associated with abdominal aortic calcification in age- sex-adjusted models (all p-values<0.012). However, all relations were attenuated in multivariable models (all p-values>0.23). Similar findings were observed in quartile-based analyses. In conclusion, general measures of obesity and measures of central abdominal fat are related to CAC and AAC. However, these cross-sectional associations are attenuated by cardiovascular disease risk factors, possibly because they may mediate the association between adiposity measures and subclinical cardiovascular disease.

Keywords: visceral fat, subcutaneous fat, obesity, calcification, epidemiology, risk factors


Obesity and associated metabolic risk factors are associated with cardiovascular disease.1 Obesity is also associated with coronary artery calcium (CAC),2-5 a marker for atherosclerotic burden, which is positively associated with coronary heart disease and cardiovascular disease events.6-8 Because abdominal adiposity may be more atherogenic than generalized adiposity,9, 10 measures of central obesity, particularly visceral abdominal tissue (VAT) may be more strongly associated with CAC. Prior studies that have examined this question were conducted in small, selected samples, limiting the generalizability of their findings.4, 11 The purpose of this analysis is to comprehensively evaluate the association between body fat depots and prevalence of coronary and abdominal aortic calcification (AAC) in a community-based sample.


Study participants were from the Framingham Heart Study Multi-detector Computed Tomography (MDCT) Study, a sub-study derived from the Framingham Heart Study Offspring and Third Generation cohorts. The study design has been described elsewhere.12-14 From June 2002 to April 2005, 3529 participants (2111 Third Generation, 1418 Offspring participants) underwent MDCT for assessment of aortic and coronary calcium. Study inclusion was weighted towards participants who resided in the Greater New England area, and those from larger Framingham Heart Study families; additional details regarding study exclusions have been described previously.9 Of the 3529 participants who underwent imaging, 3495 had interpretable coronary and aortic calcium measures, 3338 additionally had interpretable SAT and VAT measures, 3143 were free of clinical cardiovascular disease, 3143 attended a contemporaneous examination, and 3130 of whom had a complete covariate profile, resulting in a final sample size of 3130 participants.

The study was approved by the institutional review boards of the Boston University Medical Center and Massachusetts General Hospital. All subjects provided written informed consent. The authors had full access to and take full responsibility for the integrity of the data. All authors have read and agree to the manuscript as written.

Participants underwent eight-slice multi-detector computed tomography imaging of the chest and abdomen as previously described (LightSpeed Ultra, General Electric, Milwaukee, WI).15 Subcutaneous and visceral adipose tissue volumes (SAT and VAT) were assessed using an Aquarius 3D Workstation (TeraRecon Inc., San Mateo, CA) via fat pixel identification (image display window width of -195 to -45 Hounsfield Units (HU); window center of -120 HU). Inter-class correlations for inter-reader comparisons were 0.992 for VAT and 0.997 for SAT.15

To image the heart, on average forty-eight 2.5 mm contiguous slices were obtained using a prospectively EKG triggered scanning protocol; image acquisition was initiated at 70% of the cardiac cycle (120 kVp, 400 mA, temporal resolution 330 ms) using a procedure has been previously described.16 MDCT scans were quantified for both the presence and quantity of AAC and CAC by an experienced reader using a dedicated offline workstation (Aquarius, Terarecon, San Mateo, CA).17 CAC or AAC (present/absent) was based on age- and sex-specific 90th percentile cutpoints derived from a healthy referent sample.18

Risk factors were obtained at offspring examination cycle 7 or the first examination of the Third Generation. BMI was defined as weight (kilograms) divided by height-squared (meters). Waist circumference was measured using a tape measure at the level of the umbilicus. Fasting samples were used to measure plasma glucose, total and HDL cholesterol, and triglycerides. Diabetes was defined as follows: fasting plasma glucose ≥126 mg/dL at a Framingham Heart Study examination or current treatment with either a hypoglycemic agent or insulin. Participants who smoked at least one cigarette/day for the past year were defined as current smokers. Physician-administered questions were used to quantify alcohol use; drinks per week were dichotomized using the following cut-points: >14 drinks/week (men) or >7 drinks/week (women). Hypertension was defined as a systolic blood pressure ≥140 mm Hg, or a diastolic blood pressure ≥90 mm Hg, or the use of anti-hypertension therapy.

All measures of adiposity were standardized to a mean of 0 and standard deviation of 1. We examined the relation between quartiles of each adiposity variable and the presence of CAC or AAC, as well as continuous measures of adiposity and the presence of CAC or AAC using generalized estimating equations to account for familial relations in our study sample. Models were age-sex and multivariable adjusted (age, sex, systolic blood pressure, hypertension treatment, total/HDL cholesterol, triglycerides, lipid treatment, diabetes).


Study sample characteristics are presented in Table 1. Overall, the mean age was 52 years, nearly half the participants were women. Fifteen percent (n=457) of the individuals had CAC and 19% had AAC.

Table 1
Study Sample Characteristics; data represent means (standard deviation) or n (percents)

In age- sex-adjusted models, participants with BMI, WC, SAT, and VAT in the fourth quartile had a higher prevalence of CAC (all p<0.05; Table 2). For example, individuals in the fourth quartile of VAT had a 1.56-fold increased odds of CAC (OR 1.56, 95% CI 1.15-2.10, p=0.004). After multivariable adjustment, all relations were attenuated (all p-values>0.11).

Table 2
Association between different measures of Adiposity and Coronary Artery Calcium. Data represents odds ratio for each quartile* of coronary artery calcium with 95% confidence intervals.

When each measure of adiposity was modeled continuously (Table 3), BMI, WC, SAT, and VAT were all associated with CAC in age-sex adjusted models (all p-values<0.008). Upon multivariable adjustment, all relations were attenuated (p-value>0.14).

Table 3
Association between different measures of Adiposity and Coronary Artery Calcium and Abdominal Aortic Calcium. Data represents odds ratio and 95% confidence intervals of being coronary artery calcium or abdominal aortic calcium above 90% relative to per ...

For AAC, we found that in an age- sex-adjusted model only those participants with BMI, WC, and VAT in the fourth quartile had a higher prevalence of AAC (all p-values<0.008; Table 4). All relations were attenuated after multivariable adjustment (all p-values<0.98).

Table 4
Association between different measures of Adiposity and Abdominal Aortic Calcium. Data represents odds ratio per quartile* of abdominal aortic calcium with 95% confidence intervals.

When BMI, WC, SAT, and VAT were modeled continuously (Table 3), body mass index, waist-circumference and visceral abdominal fat were significantly associated with AAC in an age- sex-adjusted model (all p-values<0.012). After multivariable adjustment, all associations were rendered statistically non-significant (all p-values>0.14).


We found significant associations between all measures of adiposity and CAC in age- sex-adjusted models. However, all relations were attenuated upon multivariable adjustment. Similarly for AAC, we observed associations between most measures of adiposity (excluding SAT) in age- sex-adjusted models, which were attenuated upon multivariable adjustment. These findings suggest that shared risk factors between adipose tissue and CAC explain most of our observations.

In early work, Mahoney at al found that higher BMI in childhood, and higher BMI and waist-hip-ratio in young adulthood was associated with the early presence of CAC among participants from the Muscatine Study.3 Among 2951 black and white adults from the CARDIA study, Lee et al observed an association between waist girth and CAC in models adjusted for demographics.5 Similar to our findings, after adjustment for traditional cardiovascular disease risk factors, the associations were no longer significant. In contrast, among 443 cardiovascular disease-free individuals without diabetes, Cassidy et al found a positive association between WC and CAC among low-risk, but not high-risk individuals after adjusting for age, sex, hypertension, and cholesterol.2 However, these studies did not use a direct measure of VAT, and instead relied upon waist circumference as a proxy.

Among studies that have used a direct measure of VAT, findings were similar. Allison et al examined 3028 self-referred individuals and found that VAT was associated with CAC in men, but not women.19 These findings are in our contrast to our work, and may be due to the selected nature of the sample (ie self-referral sample), and the use of self-reported covariates, which may underestimate the true risk factor burden. In contrast, among 220 women and 190 men age 55-80 years old from the Rancho Bernardo Study, Kim et al observed no association between VAT and CAC in multivariable models.11 However, we cannot compare these findings directly with the results of the present study, as no age- sex-adjusted model was presented in the paper.

Fewer published reports exist looking at the relation between adiposity, in particular central obesity, and AAC. Among 168 men, AAC severity as measured on lateral radiographs was correlated with truncal fat mass (an indirect measure of VAT) quantified by dual energy Xray absorptiometry,20 but similar effects in post-menopausal women were not observed.21 Among 148 patients with peripheral artery disease, Golledge et al found a 6-fold increase in the odds of AAC in the upper as compared to the lower tertile of the VAT compartment (measured as the transverse diameter of the abdominal cavity) in models adjusted for age, sex, hypertension, diabetes, smoking, and cholesterol.22 While intriguing, these findings are limited with the small sample size with all with peripheral arterial disease with a likely distribution of AAC far exceeding that of a population-based sample, very wide confidence limits, and an indirect measure of VAT.

These findings highlight the strong association between measures of adiposity and subclinical disease, as well as the mediation of these associations by cardiovascular disease risk factors that are likely in the causal pathway from adiposity to subclinical disease.

The large sample size, the community-based setting, the volumetric assessment of visceral and subcutaneous fat with CT are strengths of our investigation. Limitations include the cross-sectional design of the study, so that causality cannot be inferred. Further, the Framingham Offspring Study is comprised of primarily white participants, limiting the generalizability of our findings to other ethnic groups. Lastly, we did not assess progression of arterial calcification; it is possible that measures of adiposity may be associated with progression of CAC or AAC.


This work was supported by the National Heart, Lung and Blood Institute's Framingham Heart Study (N01-HC-25195). Dr. Vasan is supported in part by 2K24HL04334 (NHLBI/NIH) and R01-DK-080739.


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Reference List

1. Poirier P, Giles TD, Bray GA, Hong Y, Stern JS, Pi-Sunyer FX, Eckel RH. Obesity and cardiovascular disease: pathophysiology, evaluation, and effect of weight loss: an update of the 1997 American Heart Association Scientific Statement on Obesity and Heart Disease from the Obesity Committee of the Council on Nutrition, Physical Activity, and Metabolism. Circulation. 2006 February 14;113(6):898–918. [PubMed]
2. Cassidy AE, Bielak LF, Zhou Y, Sheedy PF, Turner ST, Breen JF, Araoz PA, Kullo IJ, Lin X, Peyser PA. Progression of subclinical coronary atherosclerosis: does obesity make a difference? Circulation. 2005 April 19;111(15):1877–1882. [PubMed]
3. Mahoney LT, Burns TL, Stanford W, Thompson BH, Witt JD, Rost CA, Lauer RM. Coronary risk factors measured in childhood and young adult life are associated with coronary artery calcification in young adults: the Muscatine Study. J Am Coll Cardiol. 1996 February;27(2):277–284. [PubMed]
4. Allison MA, Michael WC. Body morphology differentially predicts coronary calcium. Int J Obes Relat Metab Disord. 2004 March;28(3):396–401. [PubMed]
5. Lee CD, Jacobs DR, Jr., Schreiner PJ, Iribarren C, Hankinson A. Abdominal obesity and coronary artery calcification in young adults: the Coronary Artery Risk Development in Young Adults (CARDIA) Study. Am J Clin Nutr. 2007 July;86(1):48–54. [PubMed]
6. Wong ND, Hsu JC, Detrano RC, Diamond G, Eisenberg H, Gardin JM. Coronary artery calcium evaluation by electron beam computed tomography and its relation to new cardiovascular events. Am J Cardiol. 2000 September 1;86(5):495–498. [PubMed]
7. Arad Y, Spadaro LA, Goodman K, Lledo-Perez A, Sherman S, Lerner G, Guerci AD. Predictive value of electron beam computed tomography of the coronary arteries. 19-month follow-up of 1173 asymptomatic subjects. Circulation. 1996 June 1;93(11):1951–1953. [PubMed]
8. Detrano R, Guerci AD, Carr JJ, Bild DE, Burke G, Folsom AR, Liu K, Shea S, Szklo M, Bluemke DA, O'Leary DH, Tracy R, Watson K, Wong ND, Kronmal RA. Coronary calcium as a predictor of coronary events in four racial or ethnic groups. N Engl J Med. 2008 March 27;358(13):1336–1345. [PubMed]
9. Fox CS, Massaro JM, Hoffmann U, Pou KM, Maurovich-Horvat P, Liu CY, Vasan RS, Murabito JM, Meigs JB, Cupples LA, D'Agostino RB, Sr., O'Donnell CJ. Abdominal visceral and subcutaneous adipose tissue compartments: association with metabolic risk factors in the Framingham Heart Study. Circulation. 2007 July 3;116(1):39–48. [PubMed]
10. Zhang C, Rexrode KM, van Dam RM, Li TY, Hu FB. Abdominal obesity and the risk of all-cause, cardiovascular, and cancer mortality: sixteen years of follow-up in US women. Circulation. 2008 April 1;117(13):1658–1667. [PubMed]
11. Kim DJ, Bergstrom J, Barrett-Connor E, Laughlin GA. Visceral Adiposity and Subclinical Coronary Artery Disease in Elderly Adults: Rancho Bernardo Study. Obesity (Silver Spring) 2008 April;16(4):853–858. [PMC free article] [PubMed]
12. Dawber TR, Kannel WB, Lyell LP. An approach to longitudinal studies in a community: the Framingham Heart Study. Ann NY Acad Sci. 1963;107:539–556. [PubMed]
13. Shurtleff D. Some characteristics related to the incidence of cardiovascular disease and death: Framingham Study, 18-yea follow-up. Section 30. In: Kannel WB, Fordon T, editors. The Framingham Study: an epidemiological investigation of cardiovascular disease. Department of Health, Education, and Welfare; Washington, D.C.: 1973. (DHEW publication no. (NIH) 74-599).
14. Splansky GL, Corey D, Yang Q, Atwood LD, Cupples LA, Benjamin EJ, D'Agostino RB, Sr., Fox CS, Larson MG, Murabito JM, O'Donnell CJ, Vasan RS, Wolf PA, Levy D. The Third Generation Cohort of the National Heart, Lung, and Blood Institute's Framingham Heart Study: Design, Recruitment, and Initial Examination. Am J Epidemiol. 2007 March 19; [PubMed]
15. Maurovich-Horvat P, Massaro J, Fox CS, Moselewski F, O'Donnell CJ, Hoffmann U. Comparison of anthropometric, area- and volume-based assessment of abdominal subcutaneous and visceral adipose tissue volumes using multi-detector computed tomography. Int J Obes (Lond) 2007 March;31(3):500–506. [PubMed]
16. Rosito GA, Massaro JM, Hoffmann U, Ruberg FL, Mahabadi AA, Vasan RS, O'Donnell CJ, Fox CS. Pericardial Fat, Visceral Abdominal Fat, Cardiovascular Disease Risk Factors, and Vascular Calcification in a Community-Based Sample. The Framingham Heart Study. Circulation. 2008 Feb;117(5):605–13. [PubMed]
17. Hoffmann U, Siebert U, Bull-Stewart A, Achenbach S, Ferencik M, Moselewski F, Brady TJ, Massaro JM, O'Donnell CJ. Evidence for lower variability of coronary artery calcium mineral mass measurements by multi-detector computed tomography in a community-based cohort--consequences for progression studies. Eur J Radiol. 2006 March;57(3):396–402. [PubMed]
18. Hoffmann U, Massaro JM, Fox CS, Manders E, O'Donnell CJ. Defining normal distributions of coronary artery calcium in women and men (from the Framingham Heart Study) Am J Cardiol. 2008 November 1;102(9):1136–41. 1141. [PMC free article] [PubMed]
19. Allison MA, Michael WC. Body morphology differentially predicts coronary calcium. Int J Obes Relat Metab Disord. 2004 March;28(3):396–401. [PubMed]
20. Alexandersen P, Tanko LB, Bagger YZ, Jespersen J, Skouby SO, Christiansen C. Associations between aortic calcification and components of body composition in elderly men. Obesity (Silver Spring) 2006 September;14(9):1571–1578. [PubMed]
21. Tanko LB, Bagger YZ, Alexandersen P, Larsen PJ, Christiansen C. Central and peripheral fat mass have contrasting effect on the progression of aortic calcification in postmenopausal women. Eur Heart J. 2003 August;24(16):1531–1537. [PubMed]
22. Golledge J, Jayalath R, Oliver L, Parr A, Schurgers L, Clancy P. Relationship between CT anthropometric measurements, adipokines and abdominal aortic calcification. Atherosclerosis. 2008 March;197(1):428–434. [PMC free article] [PubMed]