(Stroke. 2004;35:2782.)
© 2004 American Heart Association, Inc.
Original Contributions |
From the Section of Cardiovascular Medicine, University of Wisconsin Medical School (J.H.S., P.S.D.), Madison, Wis; Tulane Center for Cardiovascular Health and Department of Epidemiology (S.R.S., S.L., W.C., G.S.B.), Tulane University Health Sciences Center, New Orleans, La; Division of Vascular Ultrasound Research (M.G.B., R.T.), Wake Forest University School of Medicine, Winston-Salem, NC.
Correspondence to Dr James H. Stein, Department of Medicine, Section of Cardiovascular Medicine, University of Wisconsin Medical School, 600 Highland Avenue, G7/341 CSC (MC 3248), Madison, WI 53792. E-mail jhs{at}medicine.wisc.edu
| Abstract |
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Methods Age-, sex-, and race-specific CIMT percentile values and cross-sectional changes with age were estimated using B-mode carotid ultrasound images from 519 young adults (mean age 32 years, 61% female, 29% black). Nomograms of CIMT percentiles between the ages of 25 and 40 years are provided in 5-year increments.
Results CIMT was thickest in the carotid bulb and increased linearly with age, most rapidly in the bulb. With age, composite CIMT increased most slowly in white females and most rapidly in white males. Sample size estimates projected that 268 to 462 subjects are needed to detect CIMT changes
0.010 mm/year.
Conclusions These estimated CIMT distributions and percentiles can serve as reference values for assessment of subclinical atherosclerosis in young adults. The observed age-related differences in CIMT can be used to plan epidemiological and clinical trials investigating atherosclerosis and anti-atherosclerotic interventions.
Key Words: aging atherosclerosis cardiovascular diseases carotid arteries
| Introduction |
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| Materials and Methods |
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4 years younger (P<0.001).68 One subject (a white male) had experienced a myocardial infarction that was identified at the time of this survey.
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Study Procedures
Study-related protocols have been described previously.7,8 Images of the right and left common carotid (CCA), carotid bulb, and internal carotid (ICA) arterial segments were acquired using a Toshiba SonoLayer SSH 160A (Toshiba Medical) ultrasound system and a 7.5-MHz linear array transducer. Carotid arterial segments were imaged and measured following previously described protocols developed for the Atherosclerosis Risk in Communities studies (ARIC).8,9 A single certified reader conducted measurements using a semi-automated program.8,9 Fifty-four subjects underwent repeat CIMT examination within 10 to 12 days to determine repeatability. The mean absolute value of the difference of repeated measures was 0.06 [0.05] mm (median 0.04) for the mean CIMT of all 6 segments. There was a mean difference of <0.01 mm between replicate scans, indicating an absence of bias in repeat measurements.
Data Analysis
Analyses were performed using the SAS software package (SAS Systems). CIMT distributions for white males, white females, black males, and black females were described by means (standard deviations) and compared using the general linear model, after adjustments for height and weight. For each segment, the average of the right- and left-sided far wall measurements was used to define segmental CIMT. Composite CIMT was defined as the average of the segmental CIMT measurements. Missing data were handled conservatively by list-wise deletion, such that both right- and left-sided measurements were required to determine CCA, bulb, and ICA values.
Race- and sex-specific distributions of CIMT values for each segment were estimated using ordinary least-squares (OLS) regression for the 5th, 10th, 25th, 75th, 90th, and 95th percentiles across subject aged 25 to 40 years in 5-year increments. Age-specific percentiles were obtained using Ave Xp(n +1), which gives the common value of the median. The 100th percentile was computed as Zp=(1g)X[k1]+gX[k2], where k1 equals the integer part of p(n+1), k2=k1+1, g is the fractional part of p(n+1), and X[k] is the kth observation when the data are sorted from lowest to highest. Linear and nonlinear (quadratic, CIMT=ß0+ß1Age+ß2Age2) regression models were constructed for each race-, sex-, and segmental percentile across the age ranges.
Assessment of fit for linear and nonlinear percentile regression lines was evaluated by inspection of R2 changes and proportion of bias. Differences in R2 for composite and segmental CIMT models for each racesex group were low (all
R2
0.045). Proportion of bias was estimated as:
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where k=1, 2, ... K patient ages per race and sex, with y being the known age-specific percentile, and
being the regression estimated percentile. Biases for all composite CIMT percentiles in each racesex group were <1.4%, except for the 75th, 90th, and 95th percentiles in black males, for which biases were 2.6% to 5.3%. Biases for all CCA CIMT percentiles in each racesex group were <0.9%. For bulb CIMT, biases in all racesex groups were <1.2%, except for the 90th and 95th percentile in black males (biases <6.1%). In the ICA, all biases were <1.6%, except black males (biases 2.6 to 5.0%). Therefore, both assessments indicated little benefit for modeling percentile line curvature, so only linear percentiles are reported.
Yearly changes in CIMT were estimated from cross-sectional data using linear and nonlinear OLS regression models as a function of age. Age-related changes of CIMT were determined from the slope (B). Assuming that the residual values were normally distributed, tests of hypotheses about the rates of CIMT changes (determined from the slopes) were constructed. Specifically, an F-ratio was used to test the hypothesis that the yearly rate of CIMT change=0 versus the alternative hypothesis that the rate=B (B not 0). When the slope is zero, there is no linear relationship between CIMT and patient age. Because the values of each of the parameters
, ß,
2(y), N,
2(x), and the slope (B) can be determined from the others, ß error and, subsequently, power (1ß) were derived.10
| Results |
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CIMT values are presented in Table 2. In general, CIMT values in white females were lower than in white males, black males, and black females. CCA CIMT in white males was less than in black males (P=0.034). Estimates of segmental and composite CIMT and percentiles by age, sex, and race are presented in Table 3. Composite CIMT values are displayed graphically in Figure 1. In general, linear increases in composite CIMT were seen with aging; however, negative slopes in the 5th, 10th, and 25th percentiles for black males were seen because of small numbers. In general, linear increases in segmental CIMT also were seen with aging; however, negative slopes were seen in black males at the 5th and 10th percentiles for the bulb and at the 5th, 75th, 90th, and 95th percentiles for the ICA (data not shown). Other negative slopes for segmental CIMT were seen in white males at the 25th percentile for ICA, for white females at the 90th and 95th percentiles for ICA, and for black females at the 5th percentile for bulb and ICA (data not shown).
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Age-Related CIMT Changes
Cross-sectional age-related differences in CIMT are presented in Table 4. Significant age-related differences in CIMT between males and females were not observed; however, among males the yearly change in the CCA was faster in white than black subjects (P=0.030). Among females, significant differences were not seen between races. Significant differences between black and white subjects were not observed; however, among white subjects the yearly difference in composite CIMT tended to be greater among males than females (P=0.082). Among black subjects, differences were not seen between sexes.
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Cross-sectional age-related differences in CIMT were greater in the CCA than the ICA for white females (P=0.047). With age, yearly CIMT changes tended to be greater in the bulb than in the ICA for white males (P=0.010), white females (P=0.089), and black males (P=0.090). Age-related CIMT changes in the bulb were greater than in the ICA for white males (P=0.045) and white females (P=0.005). Between sexrace groups, composite CIMT age-related changes were smaller in white females than black males (P=0.043), and tended to be greater in white males than white females (P=0.082) and black females (P=0.073). White males had greater estimated CIMT changes in the CCA than black males (P=0.030) and tended to have greater changes in the CCA than black females (P=0.070). White females had greater estimated CIMT changes in the CCA (P<0.002) than black males.
Power Analyses
Power curves to detect composite CIMT changes of 0.010 mm/year (80% power) are in Figure 2. Sample size estimates to detect this difference in composite CIMT ranged from 268 white female to 462 white male subjects. In the CCA, sample size estimates ranged from 220 white female to 292 black female subjects (data not shown).
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| Discussion |
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Cross-sectional age-related changes in CIMT were not significantly different between sexes and races; however, comparison of group combinations of sex and race demonstrated some important differences. With age, composite CIMT increased most slowly in white females and most rapidly in white males. Bulb CIMT increased faster than CCA and ICA CIMT, and in white females age-related increases in CCA were greater than ICA CIMT. Compared with the middle-aged subjects, aging-related cross-sectional rates of CIMT change were quite similar, with differences in mean segmental CIMT change rate estimates that were <0.0033 mm/year for white males (except ICA), white females (except ICA), black males (except CCA), and black females.5 Mean differences of
0.010 mm/year were observed for white male ICA and black male CCA estimates. The sample size estimates provided in this data set represent reasonable targets for recruitment into epidemiological and clinical trials investigating atherosclerosis and interventions.
Limitations
Although this study was one of the largest cross-sectional studies of CIMT in young adults to date, the number of subjects was relatively small given the number of ageracesex combinations analyzed. The relatively small number of black males and the relatively increased number of ICA segments that were not visualized or measurable led to small cell sizes in certain racesexsegment percentiles, which may have been sensitive to outlier values. This was manifested by increased variability at extreme percentiles of some segments and some of the negative slopes for CIMT distribution percentiles. The relatively low number of black male and females subjects led to nearly identical regression lines for the 5th and 10th percentiles and 90th and 95th percentiles for composite CIMT in both groups.
To not miss possible associations between cross-sectional and age-related changes in CIMT, the alpha of 0.05 was not adjusted for multiple comparisons, and trends (P=0.05 to 0.10) were reported. These associations should be considered exploratory and interpreted in the context of the strength of the associations and the sizes of the subgroups. The general associations between age, sex, race, and CIMT are similar to those reported in larger studies of middle-aged and older adults, and in smaller studies of young adults, suggesting that the associations identified in this study are likely to be accurate.4,5,1113
The conservative approach to handling missing data could have introduced some bias into the percentile estimates; however, the occurrences of missing data were relatively similar between racesex groups, and alternatives such as imputing missing values also could introduce biases. Eliminating missing data points from determinations of segmental and composite CIMT values may have decreased cell sizes and increased variability; however, the biases in the models remained small. Although only far-wall CIMT was measured, far-wall CIMT predicts prevalent and incident cardiovascular disease.2,3 Because this study was cross-sectional, the accuracy of the predicted age-related changes in CIMT need to be validated longitudinally. Also, because of the very small number of cardiovascular events in the Bogalusa Heart Study, the ability of CIMT values to predict events is not yet known.
| Conclusions |
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| Acknowledgments |
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Received May 17, 2004; revision received August 31, 2004; accepted September 13, 2004.
| References |
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3. Chambless LE, Heiss G, Folsom AR, Rosamond W, Szklo M, Sharrett AR, Clegg LX. Association of coronary heart disease incidence with carotid arterial wall thickness and major risk factors: the Atherosclerosis Risk in Communities (ARIC) Study, 19871993. Am J Epidemiol. 1997; 146: 483494.
4. OLeary D, Polak J, Kronmal R, Manolio T, Burke G, Wolfson S Jr. Carotid-artery intima and media thickness as a risk factor for myocardial infarction and stroke in older adults: Cardiovascular Health Study. N Engl J Med. 1999; 340: 1422.
5. Howard G, Sharrett A, Heiss G, Evans G, Chambless L, Riley W, Burke G, for the ARIC Investigators. Carotid artery intimal-medial thickness distribution in general populations as evaluated by B-mode ultrasound. Stroke. 1993; 24: 12971304.
6. Krishnan P, Balamurugan A, Urbina E, Srinivasan SR, Bond G, Tang R, Berenson GS. Cardiovascular risk profile of asymptomatic healthy young adults with increased carotid artery intima-media thickness: the Bogalusa Heart Study. J La State Med Soc. 2003; 155: 165169.[Medline] [Order article via Infotrieve]
7. Li S, Chen W, Srinivasan SR, Bond MG, Tang R, Urbina EM, Berenson GS. Childhood cardiovascular risk factors and carotid vascular changes in adulthood: the Bogalusa Heart Study. JAMA. 2003; 290: 22712276.
8. Urbina EM, Srinivasan SR, Tang R, Bond MG, Kieltyka L, Berenson GS. Impact of multiple coronary risk factors on the intima-media thickness of different segments of carotid artery in healthy young adults (the Bogalusa Heart Study). Am J Cardiol. 2002; 90: 953958.[CrossRef][Medline] [Order article via Infotrieve]
9. Bond M, Barnes R, Riley W, Wilmoth S, Chambless L, Howard G, Owens B, ARIC Study Group. High-resolution B-mode ultrasound scanning methods in the Atherosclerosis Risk in Communities Study (ARIC). J Neuroimaging. 1991; 1: 6873.[Medline] [Order article via Infotrieve]
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11. Gariepy J, Salomon J, Denarie N, Laskri F, Megnien JL, Levenson J, Simon A. Sex and topographic differences in associations between large-artery wall thickness and coronary risk profile in a French working cohort: the AXA Study. Arterioscler Thromb Vasc Biol. 1998; 18: 584590.
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13. Davis PH, Dawson JD, Mahoney LT, Lauer RM. Increased carotid intimal-medial thickness and coronary calcification are related in young and middle-aged adults. The Muscatine Study. Circulation. 1999; 100: 838842.
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