Material and Methods: The patient files and records belonging to ones who underwent multi-detector computed tomography (MDCT) coronary angiography between 1 March 2014 and 1 February 2016 in our clinic were examined retrospectively. Those who had diabetes, hypertension, malignity, chronic disease and history of smoking were not included in the study. The patients were divided into five groups according to their body mass index (BMI). The coronary artery calcium (CAC) score of each patient was calculated according to Agatston's method. For the statistical analysis of the data, Oneway Anova was used for the differences between the groups, and regression analysis was used for the relationship between BMI and CAC scores.

Results: All of the patients were divided into five according to their BMI. The average calcium score was found as 0.62±0.15 for group 1, 21±3 for group 2, 126±25 for group 3, 340±17 for group 4, and 887±32 for group 5. There was a significant positive correlation between BMI and CAC scores value for the group 3, group 4 and group 5 (Group 3 r=0.34, Group 4 r=0.62, Group 5 r=0.53, p<0.05).

Conclusion: It was determined that there is a relationship between BMI and CAC scores indicating that as long as BMI increases, CAC scores increases prominently as well.

There is a close link between vessel wall calcification in coronary artery and atherosclerotic coronary artery disease. A lot of studies are conducted to determine The exact determination of body fat index takes long time and it is troublesome. In determining obesity, BMI is used, which is the ratio of human body weight to squared height.

WHO (World Health Organization), regards a BMI risk factors for atherosclerotic heart diseases. Body mass index (BMI) is an index which is used in many fields of medicine to determine obesity limit and its unit is kg/m^23-5.

Determining coronary artery calcium level to specify the level and distribution of coronary artery calcification is an important parameter for diagnosing cardiovascular risk in advance. Multidetector computed tomography (MDCT) is the candidate for the routine use as a sensitive method for detection of coronary calcium deposition^6-8.

under 18.5 kg/m² as underweight, 18.5 - 24.9 kg/m² as normal, 25 - 29.9 kg/m² as overweight, 30 - 39.9 kg/m² as obesity, and over 40 kg/m² as very morbid obesity^7-10. Between obesity and atherosclerotic coronary artery disease (CAD) is a close link, and American Heart Association (AHA) defines this as a major risk factor for coronary heart disease^8-11.

Determining coronary artery calcification level by using coronary artery calcium (CAC) scores is an important parameter in for diagnosing cardiovascular risk in advance. MDCT is used as a sensitive non-invasive method for diagnosing coronary calcium deposition and CAD^7,12-14.

In this study, we determined coronary artery calcium level and investigated the relationship between BMI and CAC scores using MDCT.

Patients Group
All of the patients were divided into five groups according to their BMI. The ones with a BMI under 18,5 kg/m² consisted the group 1 (underweight, n=40), those between 18,5 kg/m² and 24.9 kg/m² are the group 2 (normal, n=40), the ones between 25 kg/m² and 29.9 kg/m² made up the group 3 (over-weighted, n=40), the ones between 30 kg/m² and 39.9 kg/m² are the group 4 (obese n=40), and finally those over 40 kg/m² were named as the group 5 (very severely weighted, n=40). The data about the groups are presented in Table 1.

Click Here to Zoom

Table 1: Exploratory Data of the Groups According to BMI

Evaluation of Images
CAC scores of each patient was assessed retrospectively at workstation (VITAL, Vitrea 2, HP XW6400 Workstation, America). Using Agatston's calcium scoring method, CAC scores of the patients was calculated one by one. According to Agatston's calcium scoring system, the patients were divided into five groups.

Statistical Analysis
For the statistical analysis of the data, Oneway Anova was used for the differences between the groups, and fit gaussian analysis was used for the relationship between BMI and CAC scores, and p<0.05 was accepted as significant.

Click Here to Zoom

Figure 1: CAC scores between the groups which are formed according to BMI

The minimum calcium score was calculated as 0, while the maximum score was 1387. In the groups, which were created according to BMI, the distributions according to age, gender and calcium scores were presented in Table 1.

When the scores of CAC and BMI among the groups are compared statistically, no significant relationship between the groups 1 and 2 was found (p>0.05). Between the all other groups, there is statistically significant relationship (p<0.001). Moreover, it was found out that gender does not have an effect on CAC scores on its own, and gender and BMI together do not have a statically significant effect on CAC scores (p>0.05).

When we examine the correlation between BMI and CAC scores in each group, there is a significant positive correlation in groups 3, 4 and 5. The scores were calculated as (R=0.34 p<0.05), (R=0.62 p<0.01), (R=0.53 p<0.01) for the groups 3, 4 and 5 respectively. Moreover, without making a distinction between the groups, when the correlation between BMI and CAC scores of everyone in the groups was examined, it is seen that in figure 2.

Click Here to Zoom

Figure 2: The relationship between BMI and CAC scores of all the groups.

For each group, there is no a statistically significant correlation between age and CAC scores.

Atherosclerosis, starting at an early age, is a multi- factor, systemic and progressive disease which affects arteries. Around the world, CAD is known to be the most important cause of mortality and morbidity. Considering systemic involvement of atherosclerosis, the same relation is expected to have a close link with coronary artery atherosclerosis^18,19.

Obesity is an established risk factor for cardiovascular disease, and it is increasing at an alarming rate worldwide. In a study, bodyweight is defined as a risk factor which has a moderate effect on CAD. In the studies carried out in western countries with coronary artery patients, half of the women and majority of men have been reported to be over excessive weight limit²⁰.

In another two studies, obesity is found to be an independent risk factor for CAD, and it is also stated that as long as BMI increases, there is a linear increase in risk of cardiovascular disease^21,22. In some studies, contrary to females; in males, there was found a stronger relationship between BMI and CAD in middle ages than in older ages^23,24. In another study, while in men over 70, a high level BMI was found as a coronary artery risk, there is not a significant risk in females²⁵. In a study in our country, it was found out that female coronary artery patients have higher BMI averages than males have²⁶.

Kronmal et al.²⁷ determined in their studies in which they carried out on 5756 multi-ethnic, asymptomatic patients to examine risk factors affecting progression at coronary artery calcification that the incidence of coronary artery calcification increases with aging. They also determined in this study, which they studied approximately 2.4 years on a group with no one known cardiovascular disease, that age, gender and BMI, which are all cardiovascular risk factors, are effective in the formation of coronary artery calcification.

Since the possibility of future cardiac events has a close link with atherosclerotic disease, determining the amount and distribution of coronary artery calcium is important for determining the risk of cardiovascular disease in advance. Coronary artery calcium scanning performed with computed tomography is considered the gold standard for the detection of coronary artery calcium and is a commonly used imaging method recently⁷.

In our study, according to statistics results, while there is no significant difference between the groups 1 and 2 for BMI and CAC scores, between the all other groups, there is statistically significant difference. The ones with a high BMI score were observed to have a high CAC score. As a result, there is significant relationship between BMI and CAC scores.

In conclusion; it cannot be strong relationship between body mass index and CAC scores, when presence of diabetes, hypertension, malignancy, chronic disease, and the smokers is not homogeneous between the groups. In the literature these studies are a few, and it is thought to be the studies show more clearly the effect of BMI and CAC scores with homogenous groups. In our study, diabetes, hypertension, malignancy, chronic disease, and smokers involved in the study and thus, have revealed a strong relationship between the BMI with CAC scores.

1) Scherbakov N, Anker SD, Doehner W. How to determine a metabolically healthy body composition in cardiovascular disease. J Am Coll Cardiol 2014; 64: 1182-3.

2) Rhee EJ, Seo MH, Kim JD, et al. Metabolic health is more closely associated with coronary artery calcification than obesity. PLoS One 2013; 8: e74564.

3) Eker E, Şahin M. Birinci basamakta obeziteye yaklaşım. Sürekli Tıp Eğitim Dergisi 2002; 11: 246.

4) Dietz WH, Bellizzi MC. Introduction: the use of body mass index to assess obesity in children. Am J Clin Nutr 1999; 70: 123-5.

5) Jones G, Scott FS. A Cross-sectional study of smoking and bone mineral density in premenopausal parous women: effect of body mass index, breastfeeding, and sports participation. J Bone Miner Res 1999; 14: 1628-33. 6. Efe D, Aygün F, Kuzgun A. Vücut kitle indeksi ile koroner arter kalsiyum skoru ve tıkayıcı koroner ar-ter hastalığı arasındaki muhtemel ilişki. Türk Göğüs Kalp Damar Cerrahisi Dergisi 2013; 21: 26-30.

7) Stanford W, Thompson BH. Imaging of coronary artery calcification: its importance in assessing atherosclerotic disease. Radiol Clin North Am 1999; 37: 257-72.

8) Eckel RH, Krauss RM. American heart association call to action: obesity as a major risk factor for coronary heart disease. Circulation 1998; 97: 2099-100.

9) Calle EE, Thun MJ, Petrelli JM, Rodriguez C, Heath CW Jr. Body-mass index and mortality in a prospective cohort of U.S. adults. N Engl J Med 1999; 341: 1097-105.

10) Rao SV, Donahue M, Pi-Sunyer FX, Fuster V. Results of expert meetings: obesity and cardiovascular disease. Obesity as a risk factor in coronary artery disease. Am Heart J 2001; 142: 1102.

11) Bolick LE, Blankenhorn DH. A quantitative study of coronary arterial calcification. Am J Pathol 1961; 39: 511-9.

12) Nieman K, van der Lugt A, Pattynama PM, de Feyter PJ. Noninvasive visualization of atherosclerotic plaque with electron beam and multislice spiral computed tomography. J Interv Cardiol 2003; 16: 123-8.

13) Jakobs TF, Wintersperger BJ, Herzog P, et al. Ultra-low-dose coronary artery calcium screening using multislice CT with retrospective ECG gating. Eur Radiol 2003; 13: 1923-30.

14) Taylor AJ, Bindeman J, Feuerstein I, Cao F, Brazaitis M, O’Malley PG. Coronary calcium independently predicts incident premature coronary heart disease over measured cardiovascular risk factors: mean three-year outcomes in the prospective army coronary calcium (PACC) project. J Am Coll Cardiol 2005; 46: 807-14.

15) Arad Y, Goodman KJ, Roth M, Newstein D, Guerci AD. Coronary calcification, coronary disease risk factors, c-reactive protein, and atherosclerotic cardiovascular disease events: the St. Francis heart study. J Am Coll Cardiol 2005; 46: 158-65.

16) Pletcher MJ, Tice JA, Pignone M, Browner WS. Using the coronary artery calcium score to predict coronary heart disease events: a systematic review and meta-analysis. Arch Intern Med 2004; 164: 1285-92.

17) Elkiran O, Yilmaz E, Koc M, Kamanli A, Ustundag B, Ilhan N. The association between intima media thickness, central obesity and diastolic blood pressure in obese and owerweight children: A crosssectional school-based study. Int J Cardiol 2013; 165: 528-32.

18) Onat A, Dursunoğlu D, Kahraman G ve ark. Türk erişkinlerinde ölüm ve koroner olaylar: TEKHARF Çalışması kohortunun 5-yıllık ta- kibi. Türk Kardiyoloji Derneği Arşivi 1996; 24: 8-15.

19) Ross R. Atherosclerosis; McGee J, Isaacson PG, Wright NA (eds): Oxford Textbook of Pathology. Oxford, Oxford University Press; 1992; 798-812.

20) Allen JK, Blumenthal RS. Risk factors in the offspring of women with premature coronary heart disease. Am Heart J 1998; 135: 428-34.

21) Hubert HB, Feinleib M, McNamara PM, Castelli WP. Obesity as an independent risk factor for cardiovascular disease: a 26-year follow-up of participants in the Framingham Heart Study. Circulation 1983; 67: 968-77.

22) Mhurchu CN, Rodgers A, Pan W, Gu D, Woodward M: Asia Pacific Cohort Studies Collaboration. Body mass index and cardiovascular disease in the asia-pacific region: an overview of 33 cohorts involving 310 000 participants. Int J Epidemiol 2004; 33: 751-8.

23) Rexrode KM, Carey VJ, Hennekens CH, et al. Abdominal adiposity and coronary heart disease in women. Jama 1998; 280: 1843-8.

24) Salonen R, Salonen JT. Progression of carotid atherosclerosis and its determinants: a population-based ultrasonography study. Atherosclerosis 1990; 81: 33-40.

25) Seeman T, de Leon CM, Berkman L, Ostfeld A. Risk factors for coronary heart disease among older men and women: a prospective study of community-dwelling elderly. Am J Epidemiol 1993; 138: 1037-49.

26) Çatalyürek H, Oto Ö, Örer A, Hazan E, Açıkel Ü. Farklı hasta gruplarında vücut kitle indekslerinin karşılaştırılması. Türk Göğüs Kalp Damar Cerrahisi Dergisi 1999; 7: 71-4.

27) Kronmal RA, McClelland RL, Detrano R, et al. Risk factors for the progression of coronary artery calcification in asymptomatic subjects results from the multi-ethnic study of atherosclerosis (MESA). Circulation 2007; 115: 2722-30.