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Journal of Clinical Endocrinology & Metabolism , doi:10.1210/jc.2007-2484
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The Journal of Clinical Endocrinology & Metabolism Vol. 93, No. 9 3325-3332
Copyright © 2008 by The Endocrine Society

Body Composition and Common Carotid Artery Remodeling in a Healthy Population

Michaela Kozakova, Carlo Palombo, Marco Paterni, Christian-Heinz Anderwald, Thomas Konrad, Mary-Paula Colgan, Allan Flyvbjerg, Jacqueline Dekker on behalf of the Relationship between Insulin Sensitivity Cardiovascular risk Investigators1

Department of Internal Medicine (M.K., C.P.), University of Pisa, 56126 Pisa, Italy; Department of Technosciences for Medical Application and Research (M.P.), Consiglio Nazionale delle Ricerche Institute of Clinical Physiology, 56124 Pisa, Italy; Division of Endocrinology and Metabolism (C.-H.A.), Department of Internal Medicine III, Medical University of Vienna, A-1090 Vienna, Austria; Institute fur Stoffwechselforschung (T.K.), D-60327 Frankfurt, Germany; St. James’s Hospital (M.-P.C.), Dublin, 8 Ireland; The Medical Research Laboratories (A.F.), Clinical Institute and Medical Department M (Diabetes and Endocrinology), Aarhus University Hospital, DK-8000 Aarhus, Denmark; and Institute for Research in Extramural Medicine Institute (J.D.), Vrije University, 1081 BT Amsterdam, The Netherlands

Address all correspondence and requests for reprints to: Michaela Kozakova, M.D., Ph.D., Department of Internal Medicine, University of Pisa, Via Roma 67, 56126 Pisa, Italy. E-mail: m.kozakova{at}int.med.unipi.it.


   Abstract
Top
 Abstract
Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
Context: An independent association between obesity and preclinical carotid atherosclerosis has been demonstrated, however, the pathophysiological links were not clearly established. Body composition (BC) influences systemic hemodynamics and may participate in the remodeling of common carotid artery (CCA), independently of risk factors.

Objective: This study evaluated the association between CCA structure and BC in a large population of healthy subjects.

Design: This was a cross-sectional study.

Settings: The study was conducted at 19 European centers.

Subjects: The study included 627 healthy subjects (252 men, age 30–60 yr, body mass index 17–40 kg/m2).

Main Outcome Measures: CCA luminal diameter and intima-media thickness were measured on digitized ultrasound images. Acoustic properties of CCA wall were evaluated by digital densitometric analysis and described in terms of mean gray level. BC was assessed by electrical bioimpedance. Insulin sensitivity (euglycemic hyperinsulinemic clamp) and plasma adiponectin levels were measured. Associations between CCA structure, age, BC, and metabolic and atherosclerotic risk factors were analyzed by multivariate regression models.

Results: Independent factors affecting CCA diameter were fat-free mass and waist girth (standardized r = 0.44 and 0.12; P < 0.01 and < 0.0001; R2 = 0.35); independent correlates of intima-media thickness were age, CCA diameter, systolic blood pressure, and low-density lipoprotein-cholesterol (standardized r = 0.39, 0.25, 0.10, and 0.14; P < 0.005–0.0001; R2 = 0.40). The mean gray level of carotid wall was independently associated with age and waist girth (standardized r = 0.23 and 0.12; P < 0.0001 and = 0.001; R2 = 0.30).

Conclusions: Findings of this cross-sectional study suggest that BC modulates CCA diameter, and may induce adaptive changes in carotid wall thickness, independently of metabolic and atherosclerotic factors. Central adiposity modifies the acoustic properties of carotid wall.


   Introduction
Top
 Abstract
 Introduction
Subjects and Methods
 Results
 Discussion
 References
 
An increase in intima-media thickness (IMT) of the common carotid artery (CCA) is considered a surrogate marker of subclinical atherosclerosis because relationships between IMT, traditional cardiovascular risk factors, and clinically manifest cardiovascular disease (CVD) have been clearly demonstrated (1, 2). However, a growing body of evidence indicates that CCA IMT below certain levels (3) may not reflect atherosclerotic disease, but vascular aging (4, 5) and adaptive response to hemodynamic changes leading to alterations in shear and/or tensile stress (3, 6, 7). Shear and tensile stresses are interrelated, and the geometrical characteristics of arterial remodeling depend on the type of hemodynamic stimuli applied on the vessel (6, 8).

Previous clinical observations have shown independent associations of obesity and abdominal adiposity with carotid IMT (9, 10, 11). The mechanisms by which the obesity is linked to early carotid atherosclerosis are not clearly established, even though the role of metabolic factors, like insulin resistance (12, 13), and altered plasma adiponectin levels (10, 13) have been proposed. Yet, body composition and fat distribution may influence systemic hemodynamics, both systemic blood pressure (BP) (11) and total blood volume. Several studies have demonstrated that total blood volume, stroke volume, and cardiac output increase with body size (14, 15, 16), central fat distribution (16, 17), and, above all, with metabolically active fat-free mass (FFM) (14, 15, 16) that may account for as much as 50% of stroke volume variance (15). Chronic increase in stroke volume results in a proportional increase in systolic flow and flow velocity in large arteries (such as CCA), and can be expected to induce a relative increase in their luminal diameter (6, 7) aimed to restore the shear stress to normal levels (6). At a given BP, an increase in luminal diameter may be followed by an increase in wall thickness, i.e. IMT, meant to normalize tensile stress that is directly proportional to intra-arterial pressure and arterial diameter, and inversely to arterial wall thickness (3, 7, 8).

Based on these observations, a hypothesis can be raised that carotid remodeling and a certain degree of intima-media thickening can represent a physiological adaptation to hemodynamic pattern related to body composition. To test this hypothesis, we examined the associations between CCA structure (luminal diameter and IMT), body composition, and metabolic factors (including insulin sensitivity measured by a euglycemic hyperinsulinemic clamp and plasma adiponectin levels) in a large population of healthy subjects with low to average cardiovascular risk, without plaques in extracranial carotid arteries and with CCA IMT less than or equal to 0.9 mm, i.e. below the value that is considered indicative for atherosclerotic disease (3). Such a selected study group, though not representative of the general population, allows evaluating the effect of body composition on carotid remodeling without influences of confounding variables. In addition, acoustic properties of the carotid wall, which are supposed to reflect the structural composition of the vessel (18, 19), were evaluated by digital densitometric analysis (18, 20).


   Subjects and Methods
Top
 Abstract
 Introduction
 Subjects and Methods
Results
 Discussion
 References
 
The study population is a part of the Relationship between Insulin Sensitivity and Cardiovascular risk (RISC) study cohort (www.egir.org). The design of the RISC study has been reported elsewhere (21). Briefly, between June 2002 and July 2004, more than 1400 apparently healthy Caucasian subjects were recruited in 19 centers in 14 European countries. All recruited subjects were between 30 and 60 yr, and their BP (<140/<90 mm Hg), plasma cholesterol (<7.8 mmol/liter), triglycerides (<4.6 mmol/liter), and fasting and 2-h glucose (<7.0 and 11.1 mmol/liter, respectively) were within normal limits. Exclusion criteria were the presence of chronic diseases, overt CVD, weight change of 5 kg or more in the last 6 months, carotid stenosis more than 40%, and treatment for hypertension, obesity, diabetes, or dyslipidemia. Local ethics committee approval was obtained by each center, and written consent was obtained from all participants.

Protocol

All participants underwent a standardized examination that included interviews, BP measurements, resting electrocardiogram, anthropometry, a fasting blood draw, an oral glucose tolerance test (OGTT), a euglycemic hyperinsulinemic clamp and high-resolution ultrasound of extracranial carotid arteries. Information regarding medical history, drug use, and alcohol and cigarette consumption was collected using a standardized questionnaire. Menopause was defined as menses cessation for at least 12 consecutive months. Clinical CVD was excluded on the basis of medical history and resting electrocardiogram. Brachial BP and resting heart rate were measured three times with a digital electronic tensiometer (model 705CP; Omron, Kyoto, Japan; regular or large adult cuffs were used according to arm circumference) and with the subject seated for at least 10 min. The mean value was used in statistical analysis.

Body composition assessment

Height was measured on a clinic stadiometer. Body weight and FFM were measured by electrical bioimpedance using a Body Composition Analyzer Model TB-300 (Tanita Corp., Tokyo, Japan) (22); fat mass was then obtained as the difference between body weight and FFM. Waist circumference was measured as the narrowest circumference between the lower rib margin and anterior superior iliac crest.

OGTT

After 3 d of a 250-g carbohydrate diet and after an overnight fast, glucose tolerance was assessed by a 2-h, 75-g OGTT. At baseline and at 30-min intervals thereafter, blood samples were obtained for glucose and insulin determination. Areas under OGTT time-concentration curves were calculated by the trapezoidal rule.

Insulin sensitivity

On a separate day (within 1 wk of the OGTT), a euglycemic hyperinsulinemic clamp was performed in all subjects following a previously described procedure standardized across centers (21). Insulin sensitivity was expressed as the ratio of the M value (averaged over the final 40 min of the 2-h clamp and normalized by FFM) to the mean plasma insulin concentration measured during the same interval [index of insulin sensitivity (M/I), µmol/min/kgffm/nM] (23).

Analytical procedures

Plasma glucose was measured by the glucose oxidase technique (Glucose Analyzer; Beckman Coulter, Inc., Fullerton, CA). Serum concentrations of insulin were measured by RIA using a kit specific for human insulin (LINCO Research, Inc., St. Louis, MO). Serum total and high-density lipoprotein (HDL)-cholesterol and triglycerides were assayed by standard methods. Total adiponectin was measured in plasma using a validated in-house time-resolved immunofluorimetric assay, as previously described (24).

Carotid artery ultrasound imaging

High-resolution B-mode ultrasound of extracranial carotid arteries was performed bilaterally, according to a previously described protocol (1). In the RISC study, the carotid images were obtained in each recruiting center by trained and certified technicians following a standardized protocol (21) and using high-resolution ultrasound scanners, all with a 7.5 or 10.0 MHz linear-array transducer.

Carotid artery ultrasound analysis

Carotid images were analyzed in a centralized reading center (Pisa), by a single reader (M.K.) blinded to clinical data, using a high-resolution video recorder (Panasonic AG-MD830; Matsushita Electric Industrial Co., Ltd., Osaka, Japan) coupled with the computer-driven image analysis system Medical Image Processing (Institute of Clinical Physiology, Consiglio Nazionale delle Ricerche, Pisa, Italy) (20). For the purpose of this study, end-diastolic unzoomed frames of the left CCA in longitudinal projection with well-defined intima-media complex of the near and far wall were selected. Selected images were digitized with a resolution of 576 x 768 pixels and 256-degree gray scale per pixel. In the digitized image, a segment of adequate length (~20 mm) was selected before the flow divider. In this CCA segment, the following measurements and analyses were performed: 1) the far-wall IMT, 2) the luminal diameter, and 3) a digital densitometry of the far-wall intima-media complex. The far-wall IMT was measured manually at five measurement points; the value used for statistical analysis represents an average of five measurements. The minimum luminal diameter was measured manually as the distance between the lumen-intima interfaces of the near and far wall (3) at five measurement points; the diameter used for statistical analysis represents an average of five measurements. The wall tensile stress in CCA at end diastole was estimated by the product between diastolic BP (DBP) and the ratio of lumen radius (r = diameter/2) and wall thickness (wall tensile stress = DBP r/IMT, kPa) (25).

Digital densitometric analysis was performed by specifically developed and validated software (Institute of Clinical Physiology, Consiglio Nazionale delle Ricerche, Pisa, Italy) (20). A region of interest (ROI), including the intima-media complex of the far wall, was selected. Within the ROI, digitized images were analyzed by first-order statistical analysis that generates a histogram representing the frequency distribution of gray levels of pixels by plotting the gray values on the abscissa and the frequency of the occurrence on the ordinate. The histogram was described in terms of average pixel intensity, i.e. mean gray level (MGL). To adjust for different ultrasound attenuation and different gain settings in different study subjects, two calibration steps were introduced into the analysis of each subject. The effect of gain setting was restrained by calibrating the gray level amplitude of the ROI against vessel lumen (blood) taken as the blank (mean gray value = 0), whereas the effects of imaging depth and attenuation were minimized by calibration against an internal reference represented by the adventitia (MGL = 160) (20, 26). Densitometric analysis used in this study was previously validated against histological analysis of intimal lesions (20) and against integrated backscatter analysis of the carotid wall (27).

Intraobserver variability of all measurements was tested in 60 randomly chosen scans. The mean differences between two readings were 4.4 ± 2.6%, 3.7 ± 2.1%, and 6.8 ± 4.3% for CCA IMT, luminal diameter, and MGL, respectively.

Stroke volume assessment

To address the contribution of stroke volume to vascular remodeling, a complete transthoracic Doppler echocardiography was performed for the participants of the recruitment center in Pisa (n = 75), and stroke volume was calculated as the product of aortic valve cross-sectional area and trans-aortic flow velocity-time integral (16). Trans-aortic flow was obtained in the apical projection, aortic valve opening was measured in the long-axis view, and aortic valve area was calculated by circular geometry. A single reader (M.K.) performed all measurements, and values used for calculation represent an average of five consecutive cardiac beats. Intraobserver variability of stroke volume measurement (tested in 30 randomly selected recordings) was 4.7 ± 3.1%.

Statistical analysis

Quantitative data are expressed as mean ± SD and categorical data as percentages. Skewed variables are given as median and (interquartile range), and were log transformed for statistical analyses. Relations among the outcome variables (CCA diameter, IMT, and MGL) and continuous variables were evaluated by univariate Pearson correlation coefficients. Multiple regression (or multiple logistical regression) analysis with center adjustment was then used to study the independence of the association of continuous variables (or nominal variables) with variables that did not exhibit excessive colinearity with each other. Statistical significance was set at a value of P < 0.05. Statistical analysis was performed by JMP software, version 3.1 (SAS Institute Inc., Cary, NC).


   Results
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
Discussion
 References
 
Characteristics of study population

In the present study, we selected 627 subjects who met the following criteria: 1) an individual 10-yr coronary heart disease (CHD) risk, estimated from the Framingham Heart Study prediction score sheet, not higher than average as indicated for the corresponding sex and age (28); 2) IMT of the left CCA 0.90 mm or less and IMT in any carotid segment less than 2.0 mm; and 3) left CCA near- and far-wall intima-media complex clearly visualized over the segment of adequate length (~20 mm). Clinical characteristics and CCA parameters for the whole study population and for men and women are shown in Table 1Go. The 10-yr CHD risk as estimated from the Framingham prediction score sheet was low, below average, and average in 77, 18, and 5% of the study population, respectively.


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  		TABLE 1. Characteristics of the study population

 
CCA ultrasound measures, age, body composition, BP, and metabolic parameters

Univariate correlates between CCA ultrasound measures and age, body composition, BP, and metabolic parameters are shown in Table 2Go. No relationships were observed between CCA diameter and post-load plasma glucose or insulin concentrations (at any time point during the OGTT or as areas under the respective OGTT curves). CCA IMT increased only with glucose OGTT area (r = 0.15; P < 0.001). Table 2Go also shows the relationships among body composition, BP, and metabolic parameters.


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  		TABLE 2. Matrix of univariate correlations between CCA structural characteristics and age, office BP, body composition, and metabolic parameters

 
To assess whether any of the variables that showed a significant association with CCA measures in univariate analysis contributed independently to the variability of these measures, multiple regression analyses were performed, entering standardized diameter, IMT, and MGL as dependent variables and their significant correlates (Table 2Go) as independent variables. All analyses were adjusted for center, sex, and smoking habit, and in women for menopausal status. Independent correlates of CCA diameter were FFM and waist girth, together explaining 35% of diameter variability (Table 3Go). The inclusion of sex, which correlated highly with FFM (r = 0.87; P < 0.0001), did not cancel anthropometric measures in the regression model (β ± SE for sex, FFM and waist = 29 ± 7, 17 ± 7 and 15 ± 5; P < 0.05–0.0001; R2=0.36). Neither body mass index (BMI) nor any metabolic parameter improved the regression model or replaced/canceled FFM in the model. When divided according to sex, independent predictors of CCA diameter were age, FFM, and waist girth in men, and menopausal status and FFM in women.


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  		TABLE 3. Independent correlates of CCA diameter, wall thickness, and acoustic characteristics in the whole study population (n = 627): multivariate analyses

 
Independent factors affecting far-wall IMT were age, luminal diameter, low-density lipoprotein (LDL)-cholesterol, and systolic BP accounting for 40% of IMT variance (Table 3Go, model 1). When diameter was not included in the model, independent correlates of IMT were age, FFM, LDL-cholesterol, and systolic BP (Table 3Go, model 2). BMI, fat mass, and waist girth did not replace/cancel FFM in the model. When multivariate analyses were performed separately for men and women, luminal diameter, but not FFM, was independently related to CCA IMT.

In the whole study population and in women, MGL of carotid wall was independently related to age and waist girth, whereas in men MGL was related only to age (Table 3Go). IMT was not an independent predictor of carotid wall MGL.

To minimize the effect of the statistical distribution of variables, the associations between CCA diameter or wall thickness and age, body composition, BP, and metabolic variables were also assessed by logistical regression using the highest quartile of CCA luminal diameter (≥6.1 mm, mean 6.58) or IMT (≥660 µm, mean 726) as dependent variables. The models yielded a similar set of predictors, with age, FFM and mean BP significantly associated with a CCA diameter value in the upper quartile of the population (R2 = 0.27) (Fig. 1Go), and with age, luminal diameter, systolic BP, and LDL-cholesterol significantly associated with an IMT value in the upper quartile of distribution (R2 = 0.29).


Figure 1
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  		FIG. 1. A, Multiple logistical model for the dependence of CCA luminal diameter (as upper quartile of its distribution) on age, FFM, and mean BP. Odds ratios are calculated for 1 SD of the independent variables. B, Multiple logistical model for the dependence of CCA IMT (as upper quartile of its distribution) on age, CCA diameter, systolic BP, and LDL-cholesterol. Odds ratios are calculated for 1 SD of the independent variables.

 
Figure 2Go shows the distribution of CCA wall tensile stress by quartiles of luminal diameter. After adjustment for sex and age, significant differences in tensile stress were observed between the quartiles of diameter. The percent increase in tensile stress between the first and fourth quartiles was 27%.


Figure 2
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  		FIG. 2. Distribution of CCA wall tensile stress by increasing quartiles (from left to right) of CCA diameter. Values are mean (SD). *, P < 0.001; {dagger}, P < 0.0001.

 
In a subgroup of 75 subjects with Doppler echocardiography (37 men, mean age = 44 ± 8 yr, BMI = 26.5 ± 4.6 kg/m2, FFM = 54.8 ± 11.7 kg, fat mass = 22.7 ± 9.8 kg, waist girth = 89.3 ± 12.9 cm, and LDL-cholesterol = 2.93 ± 0.72 mmol/liter), stroke volume (77 ± 12 ml) was directly related to BMI, FFM, and waist girth (r = 0.34, 0.57, and 0.45, P at least <0.005), but not to fat mass. By multivariate analysis, independent predictors of stroke volume were age, FFM, and heart rate accounting for 44% of stroke volume variability (Table 4Go). Independent predictors of CCA luminal diameter (5.67 ± 0.53 mm) were stroke volume, waist girth, and mean BP (Table 4Go, model 1), explaining 52% of diameter variance. When stroke volume was not included in the model, independent predictors of diameter were FFM, waist girth, and mean BP (model 2). Independent correlates of CCA wall thickness (637 ± 88 µm) were similar as those in the whole study population (Tables 3Go and 4Go).


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  		TABLE 4. Independent correlates of stroke volume, CCA diameter, and wall thickness in the subgroup with Doppler echocardiography (n = 75): multivariate analysis

 

   Discussion
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
References
 
The results of this cross-sectional study suggest that in a healthy population with low to average cardiovascular risk, body composition, mainly FFM, may influence CCA luminal diameter and consequently also IMT, independently of age, established atherosclerotic risk factors, and metabolic factors, like insulin resistance and plasma adiponectin levels. Furthermore, central adiposity seems to alter the acoustic properties of carotid wall.

In our healthy subjects, FFM and waist girth were the only independent correlates of carotid diameter, and FFM remained independently related to luminal diameter when multivariate analysis was performed separately for men and women. Furthermore, in a subgroup of subjects who also underwent Doppler echocardiography (12% of study population), FFM was the strongest determinant of stroke volume, which together with waist girth was independently related to CCA diameter. Altogether these findings support the hypothesis that body composition modulates carotid luminal diameter through changes in stroke volume, and suggest that differences in body composition may contribute to well-known differences in CCA diameter between men and women (29). It is also noteworthy that in our healthy middle-aged population, an independent effect of age on carotid luminal diameter was observed only in men, but not women. Age-dependent increase in carotid diameter can reflect age-associated changes in carotid wall structure (alterations in the content and integrity of the structural matrix proteins, namely elastin and collagen) (30) that might be influenced by endogenous estrogen levels (31). Indeed, a high percentage of our women (82%) were in the reproductive phase, and menopause was independently and positively related to CCA diameter.

In our study, as well as in several other studies (3, 25), a positive independent association was demonstrated between CCA luminal diameter and IMT. This association indicates the mutual adaptation between luminal diameter and wall thickness, and suggests that the FFM-related CCA luminal enlargement might induce a certain degree of wall thickening. However, it seems that an increase in wall thickness was not sufficient to maintain wall tensile stress constant because tensile stress increased with increasing luminal diameter (Fig. 2Go). Interestingly, the increase in tensile stress between the first and fourth quartiles of diameter (27%) was similar to that observed by Chironi et al. (25) in 394 normotensive subjects (28%).

Besides the luminal diameter, independent predictors of CCA IMT were age, LDL-cholesterol, and systolic BP, an observation implying that carotid wall thickness represents a product of vascular aging, physiological adaptation to hemodynamic stimuli, and early atherosclerotic alterations. Therefore, the growing evidence showing the relationship between IMT and obesity (9, 10, 11, 32) does not merely indicate early atherosclerosis but may also reflect an adaptive arterial remodeling, as in obese individuals with increasing weight increases BP (11) and FFM, which may account for 20–40% of the weight excess (16, 33).

Remodeling of carotid arteries is accompanied by changes in the wall composition (7) that modify the interaction between propagating ultrasound beam and arterial wall, leading to changes in tissue acoustic reflectivity. Acoustic properties of tissues can be quantitatively evaluated by digital densitometric analysis, which has identified the predominant cellular composition of atherosclerotic lesions (18, 20). We have previously demonstrated (using the same densitometric analysis as in this study) (20) that MGL (or acoustic reflectivity) of initial atherosclerotic lesions is positively related to the smooth muscle cell content. In the present study, the MGL of the intima-media complex increased with age and waist girth. A positive association between age and acoustic reflectivity of carotid wall has been described by other authors (19, 34), and is supposed to mirror the age-related increase in smooth muscle cells (35) and collagen fibers within carotid media (19). A positive association between intima-media MGL and waist girth may be related to the endocrine activity of adipose tissue (36), which expresses (together with other bioactive peptides) angiotensin II. Angiotensin II plays an important role in vascular remodeling because it enhances vascular protein synthesis and stimulates smooth muscle cell growth (37). Furthermore, in elastic-type arteries like the aorta, angiotensin II induces a shift of vascular smooth muscle cells to synthetic phenotype, increases the deposition of fibrillar collagen in tunica media (38), and modulates the expression and regulation of matrix metalloproteinases (39). These changes can be expected to modify the acoustic properties of vascular wall, and indeed, the collagen content in carotid media has influenced its acoustic reflectivity (19).

Study limitations

The design of the RISC study, a multicenter European study, allows investigations in a large and well-characterized healthy population. However, due to the large number of recruiting centers, only standard B-mode ultrasound scanners were used for carotid imaging, which brought about several limitations. First, carotid diameter was measured in conventional B-mode images and not by a radio frequency-based wall-tracking system that has higher temporal and spatial resolution, and, thus, may determine the end-diastolic diameter with higher accuracy (6, 32). Second, carotid flow velocity by Doppler was not recorded, and carotid shear rate could not be estimated (6). Third, ultrasound tissue characterization was not performed by backscatter signal analysis but by digital densitometric analysis of standard ultrasound images that are more influenced by ultrasound attenuation and gain settings. To restrict this limitation, two calibration steps were introduced into the analysis of each subject (see Subjects and Methods). Fourth, BP values used in multivariate models were obtained at the brachial artery and do not represent an accurate estimate of local carotid pressure. Due to the pressure amplification phenomenon, systolic BP and pulse pressure are higher in brachial artery than in carotid artery, and the difference between the two measurement sides decreases with age (40).

Finally, the relationships between body composition and stroke volume and between stroke volume and arterial diameter were evaluated only in a small subgroup (12% of the whole population) recruited in a single center where Doppler echocardiography was performed. This subgroup had slightly higher FFM, waist girth, and CCA IMT, however, the independent correlates of both luminal diameter and wall thickness were similar to those observed in the whole study population, suggesting that this subgroup can be considered a representative sample.

Conclusions

The results of this cross-sectional study raise the possibility that in healthy subjects without increased cardiovascular risk, body composition-related changes in systemic hemodynamics may modulate the luminal diameter of CCA and induce adaptive changes in IMT due to a mutual adjustment between carotid diameter and wall thickness. Central adiposity seems to increase the acoustic reflectivity of the carotid wall. Further longitudinal studies are needed to establish clearly the temporal sequences of changes in the carotid structure.


   Footnotes
 
This study is supported by European Union Grant QLG1-CT-2001-01252. Additional support has been provided by AstraZeneca (Sweden). The European Group for the Study of Insulin Resistance is supported by Merck Santé, France.

Relationship between Insulin Sensitivity and Cardiovascular risk investigators: Amsterdam, The Netherlands: R. J. Heine, J. Dekker, S. de Rooij, G. Nijpels, and W. Boorsma; Athens, Greece: A. Mitrakou, S. Tournis, K. Kyriakopoulou, and P. Thomakos Belgrade; Serbia and Montenegro: N. Lalic, K. Lalic, A. Jotic, L. Lukic, and M. Civcic; Dublin, Ireland: J. Nolan, T. P. Yeow, M. Murphy, C. DeLong, G. Neary, M. P. Colgan, and M. Hatunic; Frankfurt, Germany: T. Konrad, H. Böhles, S. Fuellert, F. Baer, and H. Zuchhold; Geneva, Switzerland: A. Golay, E. Harsch Bobbioni,V. Barthassat, V. Makoundou, T. N. O. Lehmann, and T. Merminod; Glasgow, Scotland, United Kingdom: J. R. Petrie (now Dundee), C. Perry, F. Neary, C. MacDougall, K. Shields, and L. Malcolm; Kuopio, Finland: M. Laakso, U. Salmenniemi, A. Aura, R. Raisanen, U. Ruotsalainen, T. Sistonen, M. Laitinen, and H. Saloranta; London, United Kingdom: S. W. Coppack, N. McIntosh, J. Ross, L. Pettersson, and P. Khadobaksh; Lyon, France: M. Laville, F. Bonnet, A. Brac de la Perriere, C. Louche-Pelissier, C. Maitrepierre, J. Peyrat, S. Beltran, and A. Serusclat; Madrid, Spain: R. Gabriel, E. M. Sánchez, R. Carraro, A. Friera, and B. Novella; Malmö, Sweden (1): P. Nilsson, M. Persson, G. Östling, and (2): O. Melander, and P. Burri; Milan, Italy: P. M. Piatti, L. D. Monti, E. Setola, E. Galluccio, F. Minicucci, and A. Colleluori; Newcastle-upon-Tyne, United Kingdom: M. Walker, I. M. Ibrahim, M. Jayapaul, D. Carman, C. Ryan, K. Short, Y. McGrady, and D. Richardson; Odense, Denmark: H. Beck-Nielsen, P. Staehr, K. Hojlund, V. Vestergaard, C. Olsen, and L. Hansen; Perugia, Italy: G. B. Bolli, F. Porcellati, C. Fanelli, P. Lucidi, F. Calcinaro, and A. Saturni; Pisa, Italy: E. Ferrannini, A. Natali, E. Muscelli, S. Pinnola, and M. Kozakova; Rome, Italy: G. Mingrone, C. Guidone, A. Favuzzi, and P. Di Rocco; Vienna, Austria: C. Anderwald, M. Bischof, M. Promintzer, M. Krebs, M. Mandl, A. Hofer, A. Luger, W. Waldhäusl, and M. Roden.

Project Management Board: B. Balkau (Villejuif, France); S. W. Coppack (London, United Kingdom); J. M. Dekker (Amsterdam, The Netherlands); E. Ferrannini (Pisa, Italy); A. Mari (Padova, Italy); A. Natali (Pisa, Italy); and M. Walker (Newcastle, United Kingdom).

Core laboratories and reading centers: lipids, Dublin, Ireland: P. Gaffney, J. Nolan, and G. Boran; hormones, Odense, Denmark: C. Olsen, L. Hansen, and H. Beck-Nielsen; albumin-creatinine, Amsterdam, The Netherlands: A. Kok and J. Dekker; genetics, Newcastle-upon-Tyne, United Kingdom: S. Patel and M. Walker; and Stable isotope laboratory, Pisa, Italy: A. Gastaldelli and D. Ciociaro.

Ultrasound reading center: Pisa, Italy: M. Kozakova; electrocardiogram reading, Villejuif, France: M. T. Guillanneuf; data management, Villejuif, France: B. Balkau and L. Mhamdi; mathematical modeling and web site management, Padova, Italy: A. Mari, G. Pacini, and C. Cavaggion; coordinating office, Pisa, Italy: S. A. Hills, L. Landucci, and L. Mota.

Further information on the Relationship between Insulin Sensitivity and Cardiovascular risk Study and participating centers can be found at www.egir.org.

Disclosure Summary: M.K., C.P., M.P., C.-H.A., T.K., M.P.C., and J.D. have nothing to declare. A.F. consulted for Hoffmann-La Roche and Merck Santé, and lectured for Novo Nordisk and GlaxoSmithKline.

First Published Online July 1, 2008

1 For a list of members of the Relationship between Insulin Sensitivity and Cardiovascular risk Investigators, see Acknowledgments. Back

Abbreviations: BMI, Body mass index; BP, blood pressure; CCA, common carotid artery; CHD, coronary heart disease; CVD, cardiovascular disease; DBP, diastolic blood pressure; FFM, fat-free mass; HDL, high-density lipoprotein; IMT, intima-media thickness; LDL, low-density lipoprotein; MGL, mean gray level; M/I, index of insulin sensitivity; OGTT, oral glucose tolerance test; RISC, Relationship between Insulin Sensitivity and Cardiovascular risk; ROI, region of interest.

Received November 8, 2007.

Accepted June 25, 2008.


   References
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 

  1. O'Leary DH, Polak JF, Kronmal RA, Manolio TA, Burke GL, Wolfson Jr SK 1999 Carotid-artery intima and media thickness as a risk factor for myocardial infarction and stroke in older adults. Cardiovascular Health Study Collaborative Research Group. N Engl J Med 340:14–22[Abstract/Free Full Text]
  2. Chambless LE, Heiss G, Folsom AR, Rosamond W, Szklo M, Sharett AR, Clegg LX 1997 Association of coronary heart disease incidence with carotid arterial wall thickness and major risk factors: the Atherosclerosis Risk in Communities (ARIC) Study, 1987–1993. Am J Epidemiol 146:483–494[Abstract/Free Full Text]
  3. Bots ML, Hofman A, Grobbee DE 1997 Increased common carotid intima-media thickness. Adaptive response or a reflection of atherosclerosis? Findings from the Rotterdam Study. Stroke 28:2442–2447[Abstract/Free Full Text]
  4. Tanaka H, Dinenno FA, Monahan KD, DeSouza CA, Seals D 2001 Carotid artery wall hypertrophy with age is related to local systolic blood pressure in healthy men. Arterioscler Thromb Vasc Biol 21:82–87[Abstract/Free Full Text]
  5. Schmidt-Trucksäss A, Grathwohl D, Schmid A, Boragk R, Upmeier C, Keul J, Huonker M 1999 Structural, functional and hemodynamic changes of the common carotid artery with age in male subjects. Arterioscler Thromb Vasc Biol 19:1091–1097[Abstract/Free Full Text]
  6. Girerd X, London G, Boutouyrie P, Mourad JJ, Safar M, Laurent S 1996 Remodeling of the radial artery in response to chronic increase in shear stress. Hypertension 27:799–803[Abstract/Free Full Text]
  7. Unthank JL, Fath SW, Burkhart HM, Miller SC, Dalsing MC 1996 Wall remodeling during luminal expansion of mesenteric arterial collaterals in rat. Circ Res 79:1015–1023[Abstract/Free Full Text]
  8. Glagov S, Vito R, Giddens DP, Zarins CK 1992 Micro-architecture and composition of artery walls: relationship to location, diameter and the distribution of mechanical stress. J Hypertens Suppl 10:S101–S104
  9. De Michele M, Panico S, Iannuzzi A, Celentano E, Ciardullo AV, Galasso R, Sacchetti L, Zarrilli F, Bond GM, Rubba P 2002 Association of obesity and central fat distribution with carotid artery wall thickening in middle-aged women. Stroke 33:2923–2928[Abstract/Free Full Text]
  10. Lo J, Dolan SE, Kanter JR, Hemphill LC, Connelly JM, Lees RS, Grinspoon SK 2006 Effects of obesity, body composition, and adiponectin on carotid intima-media thickness in healthy women. J Clin Endocrinol Metab 91:1677–1682[Abstract/Free Full Text]
  11. Burke GL, Bertoni G, Shea S, Tracy R, Watson K, Blumenthal RS, Chung H, Carnethon MR 2008 The impact of obesity on cardiovascular risk factors on subclinical vascular disease: the Multi-Ethnic Study of Atherosclerosis. Arch Intern Med 168:928–935[Abstract/Free Full Text]
  12. Hassinen M, Komulainen P, Lakka TA, Väisänen SB, Haapala I, Gylling H, Alen M, Schmidt-Trucksäss A, Nissinen A, Rauramaa R 2006 Metabolic syndrome and progression of carotid intima-media thickness in elderly women. Ann Intern Med 166:444–449[CrossRef]
  13. Nilsson PM, Engström G, Hedblad B, Frystyk J, Persson MM, Berglund G, Flyvbjerg A 2006 Plasma adiponectin levels in relation to carotid intima media thickness and markers of insulin resistance. Arterioscler Thromb Vasc Biol 26:2758–2762[Abstract/Free Full Text]
  14. Davy KP, Seals DR 1994 Total blood volume in healthy young and older men. J Appl Physiol 76:2059–2062[Abstract/Free Full Text]
  15. Hunt BE, Davy KP, Jones PP, DeSouza C, Van Pelt ER, Tanaka H, Seals DR 1998 Role of central circulatory factors in the fat-free mass-maximal aerobic capacity relation across age. Am J Physiol 275(4 Pt 2):H1178–H1182
  16. Collis T, Devereux RB, Roman MJ, de Simone G, Yeh JL, Horward BV, Fabsitz RR, Welty TK 2001 Relations of stroke volume and cardiac output to body composition: the strong heart study. Circulation 103:820–825[Abstract/Free Full Text]
  17. de Simone G, Devereux RB, Kizer JR, Chinali M, Bella JN, Oberman A, Kitzman DW, Hopkins PN, Rao DC, Arnett DK 2005 Body composition and fat distribution influence systemic hemodynamics in the absence of obesity: the HyperGEN Study. Am J Clin Nutr 81:757–761[Abstract/Free Full Text]
  18. Beletsky VY, Kelley RE, Fowler M, Phifer T 1996 Ultrasound densitometric analysis of carotid plaque composition. Pathoanatomic correlation. Stroke 27:2173–2177[Abstract/Free Full Text]
  19. Kawasaki M, Ito Y, Yokoyama H, Arai M, Takemura G, Hara A, Ichiki Y, Takatsu H, Minatoguchi S, Fujiwara H 2005 Assessment of arterial medial characteristics in human carotid arteries using integrated backscatter ultrasound and its histological implications. Atherosclerosis 180:145–154[Medline]
  20. Puato M, Faggin E, Rattazzi M, Paterni M, Kozakova M, Palombo C, Pauletto P, Study Group on Arterial Wall Structure 2003 In vivo noninvasive identification of cell composition of intimal lesions: a combined approach with ultrasonography and immunocytochemistry. J Vasc Surg 38:1390–1395[CrossRef][Medline]
  21. Hills SA, Balkau B, Coppack SW, Dekker JM, Mari A, Natali A, Walker M, Ferrannini E, EGIR-RISC Study Group 2004 The EGIR-RISC Study (The European group for the study of insulin resistance; relationship between insulin sensitivity and cardiovascular risk): I. Methodology and objectives. Diabetologia 47:566–570[CrossRef][Medline]
  22. Jebb SA, Cole TC, Doman D, Murgatroyd PR, Prentice AM 2000 Evaluation of the novel Tanita body-fat analyser to measure body composition by comparison with a four-compartment model. Br J Nutr 83:115–122[Medline]
  23. Ferrannini E, Balkau B, Coppack W, Dekker JM, Mari A, Nolan J, Walker M, Natala A, Beck-Nielsen H, RISC Investigators 2007 Insulin resistance, insulin response, and obesity as indicators of metabolic risk. J Clin Endocrinol Metab 92:2885–2892[Abstract/Free Full Text]
  24. Frystyk J, Tarnow L, Hansen TK, Parving HH, Flyvbjerg A 2005 Increased serum adiponectin levels in type 1 diabetic patients with microvascular complications. Diabetologia 48:1911–1918[CrossRef][Medline]
  25. Chironi G, Gariepy J, Denarie N, Balice M, Megnien JL, Levenson J, Simon A 2003 Influence of hypertension on early carotid artery remodeling. Arterioscler Thromb Vasc Biol 23:1460–1464[Abstract/Free Full Text]
  26. Takiuchi S, Rakugi H, Honda K, Masuyama T, Hirata N, Ito H, Sugimoto K, Yanagitani Y, Moriguchi K, Okamura A, Ogihara T 2000 Quantitative ultrasonic tissue characterization can identify high-risk atherosclerotic alteration in human carotid arteries. Circulation 102:766–770[Abstract/Free Full Text]
  27. Palombo C, Failla M, Maestroni S, Morizzo C, Kozakova M, Paterni M, Fantini E, Giannattasio C, Mancia G 2007 Comparison of videodensitometric analysis and integrated backscatter tissue characterization by ultrasound carotid arteries. J Hypertens 25(Suppl 2):S7 (Abstract 1B.8)
  28. Grundy SM, Pasternak R, Greenland P, Smith Jr S, Fuster V 1999 Assessment of cardiovascular risk by use of multiple-risk-factor assessment equations: a statement for healthcare professionals from the American Heart Association and the American College of Cardiology. Circulation 100:1481–1492[Free Full Text]
  29. Crouse JR, Goldbourt U, Evans G, Pinsky J, Sharrett AR, Sorlie P, Riley W, Heiss G 1994 Arterial enlargement in the atherosclerosis risk in communities (ARIC) cohort. In vivo quantification of carotid arterial enlargement. The ARIC Investigators. Stroke 25:1354–1359[Abstract]
  30. Najjar, SS, Scuteri A, Lakatta EG 2005 Arterial aging: is it an immutable cardiovascular risk factor? Hypertension 46:454–462[Abstract/Free Full Text]
  31. Fisher G, Swain M 1997 Effect of sex hormones on blood pressure and vascular connective tissue in castrated and noncastrated male rats. Am J Physiol 232:H617–H621
  32. Ferreira I, Twisk JW, van Mechelen W, Kemper HC, Seidell JC, Stehouwer CD 2004 Current and adolescent body fatness and fat distribution: relationship with carotid intima-media thickness and large artery stiffness at age 36. J Hypertens 22:145–155[CrossRef][Medline]
  33. Forbes GB 1999 Longitudinal changes in adult fat-free mass: influence of body weight. Am J Clin Nutr 70:1025–1031[Abstract/Free Full Text]
  34. Rossi M, Cuspidi A, Perrone L, Santoro G 2002 Carotid ultrasound backscatter analysis in hypertensive and in healthy subjects. Ultrasound Med Biol 28:1123–1128[CrossRef][Medline]
  35. Vazquez-Padron RI, Lasko D, Li S, Louis L, Pestana IA, Pang M, Liotta C, Fornoni A, Aitouche A, Pham SM 2004 Aging exacerbates neointimal formation, and increases proliferation and reduces susceptibility to apoptosis of vascular smooth muscle cells in mice. J Vasc Surg 40:1199–1207[CrossRef][Medline]
  36. Kershaw EE, Flier JS 2004 Adipose tissue as an endocrine organ. J Clin Endocrinol Metab 89:2548–2556[Abstract/Free Full Text]
  37. Daigle C, Martens FM, Girardot D, Dao HH, Touyz RM, Moreau P 2004 Signaling of angiotensin II-induced vascular protein synthesis in conduit and resistance arteries in vivo. BMC Cardiovasc Disord 4:6
  38. Rossi GP, Cavallin M, Belloni AS, Mazzocchi G, Nussdorfer GG, Pessina AC, Sartore S 2002 Aortic smooth muscle cell phenotypic modulation and fibrillar collagen deposition in angiotensin II-dependent hypertension. Cardiovasc Res 55:178–189[Abstract/Free Full Text]
  39. Castoldi G, Di Gioia CR, Pieruzzi F, D'Orlando C, Van De Greef VM, Busca G, Sperti G, Stella A 2003 Ang II increases TIMP-1 expression in rat aortic smooth muscle cells in vivo. Am J Physiol Heart Circ Physiol 284:H635–H643
  40. Verbeke F, Segers P, Heireman S, Vanholder R, Verdonck P, Van Bortel LM 2005 Noninvasive assessment of local pulse pressure: importance of brachial-to-radial pressure amplification. Hypertension 46:244–248[Abstract/Free Full Text]



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