Browse Subject Areas

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Impact of Cardiovascular Risk Factors on Carotid Intima-Media Thickness and Degree of Severity: A Cross-Sectional Study

  • Lijie Ren ,

    Contributed equally to this work with: Lijie Ren, Jingjing Cai

    Affiliations Departments of Shenzhen Second People′s Hospital, clinical medicine college of Anhui Medical University, Shenzhen, Guangdong Province, China, Department of neurology, Shenzhen Second People's Hospital, Shenzhen, Guangdong Province, China

  • Jingjing Cai ,

    Contributed equally to this work with: Lijie Ren, Jingjing Cai

    Affiliations Departments of Shenzhen Second People′s Hospital, clinical medicine college of Anhui Medical University, Shenzhen, Guangdong Province, China, Department of neurology, Shenzhen Second People's Hospital, Shenzhen, Guangdong Province, China

  • Jie Liang,

    Affiliations Department of neurology, Shenzhen Second People's Hospital, Shenzhen, Guangdong Province, China, Departments of Shenzhen Second People′s Hospital, clinical medicine college of Guangzhou Medical University, Shenzhen, Guangdong Province, China

  • Weiping Li ,

    Affiliation Department of neurosurgery, Shenzhen Second People's Hospital, Shenzhen, Guangdong Province, China

  • Zhonghua Sun

    Affiliation Department of Medical Radiation Sciences, Curtin University, Perth, Western Australia, Australia

Impact of Cardiovascular Risk Factors on Carotid Intima-Media Thickness and Degree of Severity: A Cross-Sectional Study

  • Lijie Ren, 
  • Jingjing Cai, 
  • Jie Liang, 
  • Weiping Li, 
  • Zhonghua Sun



Age, hypertension, dyslipidemia and diabetes are common cardiovascular risk factors (CVRFs) that contribute to the development of atherosclerosis in cardiovascular system including carotid artery disease. However, the impact of these risk factors on the increased carotid intima-media thickness (cIMT) and degree of carotid severity remains to be further clarified. This study aims to evaluate the relationship between CVRFs and degree of carotid severity and cIMT in high-risk subjects.


Four thousand and three hundred ninety-four subjects with one or more risk factors were retrospectively reviewed in this study. Patients were divided into different groups based on age, the type and quantity of CVRFs. cIMT and degree of carotid artery stenosis were measured and analyzed based on carotid ultrasound imaging with findings compared to the CVRFs to determine the correlation between these variables.


Aging was significantly associated with degree of severity (P < 0.05) and cIMT was significantly increased with age (P < 0.05). Individual CVRF analysis shows that hypertension was more related to the degree of severity than dyslipidemia and diabetes with corresponding abnormal cIMT rates being 79.39%, 72.98% and 32.37%, respectively. The prevalence of carotid atherosclerosis were 20.06%, 22.88% and 28.63%, respectively corresponding to patients with zero, one and more than one chronic diseases. The percentage of abnormal cIMT in hypertensive patient group with dyslipidemia is significantly higher than the other groups (P< 0.05).


This study shows a direct correlation between the degree of carotid severity and cIMT and cardiovascular risk factors, especially with age and hypertension. Carotid atherosclerosis is closely related to the number of cardiovascular risk factors.


Atherosclerosis constitutes one of the most common causes of stroke, due to embolism from a fissured or ruptured plaque [1]. It is the result of a combination of various physiological processes[2]. Plaque formation is a chronic process which is caused or accelerated by age, hypertension, diabetes and high blood cholesterol [36]. Carotid artery intima-media thickness (cIMT) is a measure of subclinical atherosclerosis associated with cardiovascular risk factors (CVRFs) and is predictive of stroke incident [711]. Combined cIMT and plaque assessment was considered to be better than either measure alone [12]. Thus, it is clinically important to examine the effects of risk factors on progression of cIMT and atherosclerosis, therefore, achieving the goal of reducing the mortality associated with cerebrovascular events.

Hypertension, diabetes and blood lipid play different role in the formation of plaque and development of cardiovascular disease. Atherosclerosis was caused by a combination of dysfunction of the endothelium of the vessels, oxidative stress and inflammation [2, 13, 14]. A previous study indicated that the cIMT was positively correlated with blood pressure variability in patients with hypertension [15]. A prospective study reported the association of both total serum cholesterol levels and the differences in cholesterol homeostasis with cIMT [16]. In diabetic patients, the latest evidence-based medicine data show a significant increase in IMT [17].

Importantly, the risk of developing atherosclerosis is greatly increased by presence of multiple factors[18]. Epidemiologic studies have stressed the important impact of multiple risk factor profiles on the prediction and prevention of coronary artery disease [19]. Early studies reported the deleterious influence of multiple risk factors on the cIMT in children and young adults [20, 21]. Recently, several studies have confirmed the greater impact of multiple risk factors on cIMT than individual CVRFs on different population groups [2224], but these studies were limited by a small sample size. Therefore, we conducted this study comprising 4394 subjects with high risk of cardiovascular disease. The aim of this study is to investigate the cIMT in different age groups and explore the relationship between two or more risk factors. It was hypothesized that multiple risk factors have greater impact on cIMT and degree of stenosis, with results providing guidance to clinicians for prevention of carotid atherosclerosis.


Population and Study design

The study was composed of 6 community health centers in Futian District, Shenzhen, China. From November 2012 to March 2013, a total of 14270 residents over 40 years old underwent physical and biochemical examinations as part of their clinical diagnosis of chronic cardiovascular diseases. Exclusion criteria were as follows: (1) subjects with no risk factors; (2) subjects did not agree to have the carotid ultrasonography examination; (3) the examination data was incomplete or missing. Researchers selected the appropriate subjects in the screening process according to inclusion and exclusion criteria. Finally, 4394 subjects met the selection criteria and were included in the analysis. The following details for each patient were collected: age, gender, blood pressure, body mass index (BMI), fasting plasma glucose (FPG), total cholesterol (TC), low density lipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol (HDL-C) and triglyceride (TG). Informed consent forms were obtained from all subjects.

Definition of risk factors

Definition criterion of risk factors were guided by Adult Treatment Panel III and the World Health Organization [25, 26]. Blood pressure was measured at left arm brachial artery in resting state. Blood pressure was measured by Yuyue mercury sphygmomanometer and NISSEI DS-500 blood pressure monitor. Hypertension was defined as resting systolic blood pressure (SBP) ≥ 140 mmHg, and /or diastolic blood pressure (DBP) ≥ 90 mmHg, or use of antihypertensive drugs. Blood lipid was measured with morning fasting blood, and all the subjects were examined by Cardiochek Portable blood detector. Dyslipidemia was defined as taking antilipemic drugs or having one or more of the following: TC≥5.2 mmol/L, LDL-C≥3.4 mmol/L, HDL-C≤1.0 mmol/L, or TG≥1.70 mmol/L. FPG was detected with morning fasting fingertip blood by Abbott Optium glucose meters. Diabetes mellitus was defined as FPG ≥ 7.0 mmol/L, or use of medication for diabetes. Hypertension, dyslipidemia and diabetes were the major chronic cardiovascular diseases which were associated with increasing the risk of stroke, therefore, comprising the main content of this study.

Carotid ultrasonography

The carotid ultrasound scan was carried out in the same period of 6 community health centers, with each patient performed by experienced sonographers with more than ten years of experience in ultrasound imaging by using high-resolution ultrasound Doppler system (SSI6000, Kai-Li ultrasound, China). During the data collection, researchers measured the degree of severity and cIMT again based on the ultrasound images. When there was discrepancy in the measurement of degree of severity or cIMT difference was greater than 0.2mm between the two assessors, a third assessor was asked to perform the measurements, and the averaged results of the similar findings were used. All the subjects were measured in a supine position. The scanning was performed on bilateral common carotid arteries, carotid bulb, carotid bifurcation and the origin of the internal carotid artery, with each providing proximal and distal wall data for the right and left carotid arteries. In addition, the scanning was examined at different angles of insonation. IMT was measured from multiple segments of carotid artery with the maximum IMT value used as the final result. When a carotid plaque was present on the artery wall, the maximum value is defined as the maximum height of the plaque. Thus, mean maximum measures represent the plaque burden. The mean maximum values of the common cIMT in the distal wall of the left and right carotid arteries were used as the dependent variables. The presence of plaques and degree of stenosis are characterized according to the Mannheim Consensus 2006 [27]. Carotid artery disease was classified into 4 categories based on the degree of severity (grade 1: IMT <0.9 mm, grade 2: IMT > 0.9 mm, grade 3: presence of carotid plaques with stenosis <50% and grade 4: presence of carotid plaques with stenosis >50%). Carotid IMT <0.9 mm (Grade 1) was regard as normal, while carotid IMT >0.9 mm was regarded as abnormal.

Data collection.

Each subject has a unique serial number as an identification code. The physical and biochemical examination results and carotid ultrasound measurement data were entered according to the subject’s serial number by a third party (Shenzhen New Element Medical company). To ensure data consistency, two staff members as a group, with one responsible for data entry, another one for the data entry check. All the information was input into Shenzhen Second People′s Hospital stroke screening platform information system.

Statistical analysis.

Data were analyzed using the software Statistical Package for the Social Sciences (SPSS, version 12.0, USA). To confirm the significance of CVRFs, the models were constructed including the individual risk factors and the possible interactions among these risk factors. To demonstrate the relationship between age and degree of severity, subjects were divided into four groups and the proportion of each grade was calculated. The effect of chronic cardiovascular diseases on atherosclerosis was examined by comparing the grade of severity and mean cIMT values of individuals with 0, 1, 2, and 3 chronic diseases. Risk comparison of continuous variables between groups was performed using x2 test. P < 0.05 was considered statistically significant.


Table 1 shows the patient’s demographic characteristics. There were 2134 males (48.57%) and 2260 females (51.42%) with the mean age 61.21±10.32 years.

Table 2 lists the different age groups with carotid ultrasound results. The results showed that cIMT were <0.9 mm in 1711 patients (38.94%), and >0.9 mm in the remaining patients (61.06%). Forty-eight patients were scored with grade 4 consisting of 34 subjects with moderate stenosis, 6 with severe stenosis and 8 with occlusion. In the age group of 40–50 years, abnormal percentage (26.67%) was significantly lower than the other groups (P<0.05). In the age group older than 70 years, 36.04% had arterial plaque formation or stenosis. Fig 1 is an example showing normal carotid endometrium, intimal thickening and carotid plaque. Fig 2A)is the box plot demonstrating the relationship between age and cIMT, with the trend showing that the mean cIMT was increased by age.

Table 2. Carotid ultrasound results based on different age groups.

Note: * Due to the presence of the desired frequency <5, the use of Fisher's exact test.

Fig 1. Carotid ultrasound image.

*Representing thickening or plaque of carotid artery. (A) Normal carotid intima; (B) Carotid intimal thickening; (C) Carotid artery plaque.

Fig 2. The relation between cIMT and CVRFs.

A shows the cIMT by the age. Box 1: age 40–50 years; Box 2: age 50–60 years; Box 3: age 60–70 years; Box 4: >70 years. B demonstrates the cIMT by the types of chronic disease. Box 1:hypertension; Box 2: dyslipidemia; Box 3: diabetes. C shows the cIMT by the number of chronic cardiovascular diseases. Box 0:without chronic cardiovascular disease; Box 1:1 type of chroinc cardiovascular disease; Box 2: 2 types of chronic cardiovascular diseases; Box 3:3 types of chronic cardiovascular diseases. D shows the cIMT by two different chronic cardiovascular diseases. Box 1: Combination of hypertension with diabetes; Box 2: combination of dyslipidemia with diabetes; Box 3: combination of hypertension with dyslipidemia.

Table 3 shows the relationship between different chronic cardiovascular diseases and carotid ultrasound analysis. The number of subjects with hypertension accounted for 60.28% of the total population. In the hypertension group, the number of abnormal cIMT patients (79.39%) was higher than the other groups (72.98% and32.37%). In the dyslipidemia group, the subjects of grade 2 and grade 3 were greater than the diabetic group. Fig 2B shows the relationship between different chronic cardiovascular diseases and cIMT, with the mean cIMT measurement highest in the hypertension group.

Table 3. The relationship between different chronic cardiovascular diseases and degrees of severity.

Note: * Due to the presence of the desired frequency <5, the use of Fisher's exact test.Table 4 shows the relationship between number of chronic cardiovascular diseases and degree of severity. In the group with no chronic disease, cIMT was normal in more than half of the subjects. With the increasing number of chronic cardiovascular disease, the exposure rate of subject’s intimal thickening, plaque formation and moderate carotid stenosis increased. Fig 2C shows the cIMT in subjects with different numbers of chronic cardiovascular diseases with significant difference noticed between groups (p<0.05).

Table 4. Relationship between the number of chronic disease and degrees of severity.

Note: * Due to the presence of the desired frequency <5, the use of Fisher's exact test.

Table 5 lists the relationship between two different chronic cardiovascular disease and degree of severity. A total of 2146 subjects suffered from two types of chronic cardiovascular diseases at the same time. Subjects with hypertension and dyslipidemia accounted for 79.40% of the total abnormal cases. Fig 2D shows the box plot of two different chronic cardiovascular diseases and cIMT. Findings suggested that the collective effect of hypertension and dyslipidemia should be underscored. Two different chronic cardiovascular diseases and ultrasound results were statistically significant different between the combined groups consisting of different chronic cardiovascular diseases (p <0.05).

Table 5. Relationship between two different chronic cardiovascular diseases and degrees of severity.

Note: * Due to the presence of the desired frequency <5, the use of Fisher's exact test.


The present study shows that middle-aged and older adults with CVRFs display increased cIMT and higher grade of severity than the younger age groups. In addition, this study shows age, blood pressure, blood lipid and fasting plasma glucose are independent predictors of carotid atherosclerosis. Carotid IMT measurements have been applied in the study of cardiovascular disease for more than 2 decades [28]. Ultrasound measurements of cIMT and carotid plaque have been widely accepted as a noninvasive method to assess the extent of cerebrovascular disease [8, 9, 29]. Assessment of carotid artery vessels is increasingly used as the focus of carotid artery ultrasound imaging for cardiovascular risk prediction [12]. In this study, the ultrasound results of the carotid arteries were evaluated and correlated with the CVRFs for atherosclerosis. Carotid IMT was tested and degrees of severity were divided into four grades to enable us perform a comprehensive analysis of the cardiovascular risk factors in relation to the carotid dimensional changes. Results of this study further clarified the relationship between conventional risk factors (age, hypertension, dyslipidemia and diabetes) and cIMT in a large number of middle-age and older Chinese populations.

Total cholesterol, smoking and systolic blood pressure has been proved to be strong long-term predictors of total plaque area [30]. Individual components of CVRFs play a different role in the formation of plaque. Koskinen et al. evaluated the 6-year progression of cIMT in 1809 subjects aged 27–35 years, and the study found that conventional risk factors predicted cIMT progression in young adults [31]. This finding indicates that atherosclerotic change to the carotid artery already exists in an early stage, which is a preclinical phase of the disease. The proportion of older residents is accompanied by a significant increase in chronic cardiovascular disease, and this may lead to increased cIMT. However, Lee et al. considered vascular aging was an independent risk factor for cardiovascular disease and aging was a major determinant of arterial stiffness and IMT [32]. Sun et al. suggested that vascular aging itself is an independent risk factor for atherosclerosis [33]. Results of this study are consistent with these findings, further highlight that aging is an independent risk factor of atherosclerosis.

Hypertension was found to be associated with an increased risk of neurological events, according to an early report [34]. Waldstein et al. found in combination with other risk factors, hypertension results in higher risk of stroke [35]. Rundek et al. demonstrated a larger cIMT in adolescents suffering from hypertension than healthy controls [36]. The mechanisms of association between hypertension and atherosclerosis may be linked with angiotensin II, which was a pro-inflammatory and pro-oxidant stimulus[37]. The results are consistent with the INTERHEART study [38], which reported that the population attributable risks (PAR) of hypertension is 17.9% higher than diabetes (PAR 9.9%). Atherosclerosis has been shown to be associated with high cholesterol level [39]. The mean serum cholesterol among Chinese population is lower than that of Western standards [40], however, serum cholesterol was directly related to coronary heart disease mortality even at relatively low levels [41]. Our research and previous studies both indicate dyslipidemia is still a risk factor of arteriosclerosis among the Chinese people.

Diabetes is one of the major risk factors associated with carotid atherosclerosis [42]. It has been reported that patients with obesity or diabetes tend to have thicker and stiffer carotid arteries and are more likely to suffer from cerebrovascular events [43]. Although our study shows the influence of diabetes is lower than hypertension and dyslipidemia, a cross-sectional population study proved glycemic status was associated with all grades of carotid atherosclerosis [44]. Thus, patients with diabetes should receive preventive interventions to reduce the stroke risk.

Although the relationship between individual risk factors and cIMT has been proved, the interaction of two or more risk factors cannot be ignored. In this study, we found that two or more different risk factors are independent of individual factors that have an impact on cIMT (Tables 4 and 5). This reminds us of underscoring the interactions between multiple CVRFs. Chuang et al. concluded that hypertension and dyslipidemia with type 2 diabetes have cumulative effects on the burden of carotid plaque[45]. In a study of 518 subjects of the same age-race-gender distribution, Urbina et al. examined the healthy young adults, and their results showed the trend of increasing cIMT at different carotid segments with increasing number of risk factors [20]. Paul et al. found the odds ratio for patients with >3 risk factors versus no risk factors having cIMT in the top fifth percentile was 4.7 (p = 0.01) [46]. Lili et al. in their comparative study concluded that three or more CVRFs have a greater impact on cIMT and elasticity than two or less CVRFs [23], but the cIMT data were taken from only left common carotid artery, thus their results may underestimate the relationships between multiple CVRFs. The mechanism of combined effect of two risk factors and interaction of multiple risk factors needs to be confirmed in future studies.

In addition to the influence of conventional risk factors on carotid atherosclerosis, the impact of other risk factors is attracting attention in the literature. Accumulating evidence indicates that psychological factors contribute to morbidity and mortality in cardiovascular disease. The INTERHEART study shows PAR of psychosocial factor is 32.5% even higher than hypertension [38]. Previous studies have shown depression or anxiety was associated with an increased cIMT and subclinical arteriosclerosis [4749]. A meta-analysis has provided strong evidence that depression is a significant risk factor for stroke[50]. Our study did not include the psychological factors, and a further study will explore the relationship between cIMT and psychological factors. Tatjana et al. found vascular risk factors explain only 11% of variance in cIMT [51], this study emphasizes the importance of novel genetic and environmental factors in underlying unexplained subclinical atherosclerosis. There are still some controversies in the risk factors of increased cIMT, thus, further research requires multiple corners, population-based and large number subjects to verify these early results.

This study verifies several findings. First, the study indicates that high-risk middle-aged and older population has a high proportion of carotid atherosclerosis. Second, aging was significantly associated with increased cIMT. Third, hypertension, dyslipidemia and diabetes plays an important role in the process of developing atherosclerosis and the impact of hypertension on cIMT is higher than dyslipidemia and diabetes. Fourth, the more risk factors and more chronic cardiovascular diseases that patients have, the higher risk of developing atherosclerosis.

Some limitations exist in this study that should be addressed. The study design involved four traditional CVRFs: age, hypertension, diabetes and dyslipidemia. It did not include smoking, homocysteine, psychological factors and other CVRFs. Therefore, further research is needed to allow robust conclusion to be drawn. In addition, our study divided the groups according to age, the type of CVRFs and the quantity of CVRFs. We did not stratify risk factors based on biochemical outcomes. This might underestimate the impact of individual risk factors.


In conclusion, this study shows that age, hypertension, dyslipidemia and diabetes plays a different role in the formation of plaque and the combination effect is increased with the burden of atherosclerosis. Among these factors, hypertension shows the highest impact on cIMT compared to dyslipidemia and diabetes. The degree of carotid severity and cIMT is increased with the number of chronic cardiovascular disease. This finding indicates the need for prevention and control of atherosclerosis with a focus on hypertension and multiple CVRFs.


This work was supported in part by Shenzhen Development and Reform Commission project "Shenzhen stroke screening and prevention public service platform" (2012110), the Shenzhen-based chronic disease tracking and monitoring and control of public service platform cloud platform (20120830145119425), Guangdong Province Science and Technology Project (2013B021800102), Shenzhen Knowledge Innovation Program (20130322131035) and Shenzhen-based research project (JCYJ20140414170821262).

Author Contributions

Conceived and designed the experiments: LR WL JC. Performed the experiments: LR JC JL. Analyzed the data: JC JL. Contributed reagents/materials/analysis tools: LR WL. Wrote the paper: LR JC. Revised and polished all the writing: ZS.


  1. 1. Sztajzel R, Ultrasonographic assessment of the morphological characteristics of the carotid plaque. Swiss Med Wkly. 2005; 135: 635–643. pmid:16380850
  2. 2. van Rooy MJ and Pretorius E, Obesity, hypertension and hypercholesterolemia as risk factors for atherosclerosis leading to ischemic events. Curr Med Chem. 2014; 21: 2121–2129. pmid:24372218
  3. 3. Mozaffarian D, Benjamin EJ, Go AS, Arnett DK, Blaha MJ, Cushman M, et al., Heart disease and stroke statistics—2015 update: a report from the American Heart Association. Circulation. 2015; 131: e29–322. pmid:25520374
  4. 4. Meschia JF, Bushnell C, Boden-Albala B, Braun LT, Bravata DM, Chaturvedi S, et al., Guidelines for the primary prevention of stroke: a statement for healthcare professionals from the American Heart Association/American Stroke Association. Stroke. 2014; 45: 3754–3832. pmid:25355838
  5. 5. O'Donnell MJ, Xavier D, Liu L, Zhang H, Chin SL, Rao-Melacini P, et al., Risk factors for ischaemic and intracerebral haemorrhagic stroke in 22 countries (the INTERSTROKE study): a case-control study. Lancet. 2010; 376: 112–123. pmid:20561675
  6. 6. Rothwell PM, Villagra R, Gibson R, Donders RC, and Warlow CP, Evidence of a chronic systemic cause of instability of atherosclerotic plaques. Lancet. 2000; 355: 19–24. pmid:10615886
  7. 7. Tattersall MC, Gassett A, Korcarz CE, Gepner AD, Kaufman JD, Liu KJ, et al., Predictors of carotid thickness and plaque progression during a decade: the Multi-Ethnic Study of Atherosclerosis. Stroke. 2014; 45: 3257–3262. pmid:25213342
  8. 8. Talelli P, Terzis G, Katsoulas G, Chrisanthopoulou A, and Ellul J, Recurrent stroke: the role of common carotid artery intima-media thickness. J Clin Neurosci. 2007; 14: 1067–1072. pmid:17804241
  9. 9. Polak JF, Pencina MJ, O'Leary DH, and D'Agostino RB, Common carotid artery intima-media thickness progression as a predictor of stroke in multi-ethnic study of atherosclerosis. Stroke. 2011; 42: 3017–3021. pmid:21885840
  10. 10. Lorenz MW, von Kegler S, Steinmetz H, Markus HS, and Sitzer M, Carotid intima-media thickening indicates a higher vascular risk across a wide age range: prospective data from the Carotid Atherosclerosis Progression Study (CAPS). Stroke. 2006; 37: 87–92. pmid:16339465
  11. 11. Tsivgoulis G, Vemmos K, Papamichael C, Spengos K, Manios E, Stamatelopoulos K, et al., Common carotid artery intima-media thickness and the risk of stroke recurrence. Stroke. 2006; 37: 1913–1916. pmid:16728693
  12. 12. Naqvi TZ and Lee MS, Carotid intima-media thickness and plaque in cardiovascular risk assessment. JACC Cardiovasc Imaging. 2014; 7: 1025–1038. pmid:25051948
  13. 13. Lusis AJ, Atherosclerosis. Nature. 2000; 407: 233–241. pmid:11001066
  14. 14. Libby P, Ridker PM, and Hansson GK, Progress and challenges in translating the biology of atherosclerosis. Nature. 2011; 473: 317–325. pmid:21593864
  15. 15. Mancia G, Parati G, Hennig M, Flatau B, Omboni S, Glavina F, et al., Relation between blood pressure variability and carotid artery damage in hypertension: baseline data from the European Lacidipine Study on Atherosclerosis (ELSA). J Hypertens. 2001; 19: 1981–1989. pmid:11677363
  16. 16. Weingartner O, Pinsdorf T, Rogacev KS, Blomer L, Grenner Y, Graber S, et al., The relationships of markers of cholesterol homeostasis with carotid intima-media thickness. PLoS One. 2010; 5: e13467. pmid:20976107
  17. 17. Yapei Y, Xiaoyan R, Sha Z, Li P, Xiao M, Shuangfeng C, et al., Clinical Significance of Arterial Stiffness and Thickness Biomarkers in Type 2 Diabetes Mellitus: An Up-To-Date Meta-Analysis. Med Sci Monit. 2015; 21: 2467–2475. pmid:26295503
  18. 18. Conner WT, Multiple cardiovascular risk factors in young people were associated with marked increase in coronary atherosclerosis. Evid Based Cardiovasc Med. 1998; 2: 71. pmid:16379827
  19. 19. Kannel WB, Contributions of the Framingham Study to the conquest of coronary artery disease. Am J Cardiol. 1988; 62: 1109–1112. pmid:3189175
  20. 20. Urbina EM, Srinivasan SR, Tang R, Bond MG, Kieltyka L, Berenson GS, et al., 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: 953–958. pmid:12398961
  21. 21. Berenson GS, Srinivasan SR, Bao W, Newman WP 3rd, Tracy RE, and Wattigney WA, Association between multiple cardiovascular risk factors and atherosclerosis in children and young adults. The Bogalusa Heart Study. N Engl J Med. 1998; 338: 1650–1656. pmid:9614255
  22. 22. Zhang F, Feng L, Chen Y, Geng Z, and Xu X, Relationship between carotid artery intima-media thickness and cardiovascular risk factors in Chinese Uygur population. Int J Clin Exp Med. 2014; 7: 5412–5420. pmid:25664050
  23. 23. Niu L, Zhang Y, Qian M, Meng L, Xiao Y, Wang Y, et al., Impact of multiple cardiovascular risk factors on carotid intima-media thickness and elasticity. PLoS One. 2013; 8: e67809. pmid:23844099
  24. 24. Liang Y, Yan Z, Sun B, Cai C, Jiang H, Song A, et al., Cardiovascular risk factor profiles for peripheral artery disease and carotid atherosclerosis among Chinese older people: a population-based study. PLoS One. 2014; 9: e85927. pmid:24465793
  25. 25. Expert Panel on Detection E and Treatment of High Blood Cholesterol in A, Executive Summary of The Third Report of The National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, And Treatment of High Blood Cholesterol In Adults (Adult Treatment Panel III). JAMA. 2001; 285: 2486–2497. pmid:11368702
  26. 26. Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al., Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation. 2009; 120: 1640–1645. pmid:19805654
  27. 27. Touboul PJ, Hennerici MG, Meairs S, Adams H, Amarenco P, Bornstein N, et al., Mannheim carotid intima-media thickness and plaque consensus (2004-2006-2011). An update on behalf of the advisory board of the 3rd, 4th and 5th watching the risk symposia, at the 13th, 15th and 20th European Stroke Conferences, Mannheim, Germany, 2004, Brussels, Belgium, 2006, and Hamburg, Germany, 2011. Cerebrovasc Dis. 2012; 34: 290–296. pmid:23128470
  28. 28. Bots ML and Sutton-Tyrrell K, Lessons from the past and promises for the future for carotid intima-media thickness. J Am Coll Cardiol. 2012; 60: 1599–1604. pmid:22999720
  29. 29. Lorenz MW, Markus HS, Bots ML, Rosvall M, and Sitzer M, Prediction of clinical cardiovascular events with carotid intima-media thickness: a systematic review and meta-analysis. Circulation. 2007; 115: 459–467. pmid:17242284
  30. 30. Herder M, Johnsen SH, Arntzen KA, and Mathiesen EB, Risk factors for progression of carotid intima-media thickness and total plaque area: a 13-year follow-up study: the Tromso Study. Stroke. 2012; 43: 1818–1823. pmid:22550052
  31. 31. Koskinen J, Kahonen M, Viikari JS, Taittonen L, Laitinen T, Ronnemaa T, et al., Conventional cardiovascular risk factors and metabolic syndrome in predicting carotid intima-media thickness progression in young adults: the cardiovascular risk in young Finns study. Circulation. 2009; 120: 229–236. pmid:19581494
  32. 32. Lee HY and Oh BH, Aging and arterial stiffness. Circ J. 2010; 74: 2257–2262. pmid:20962429
  33. 33. Sun Z, Aging, arterial stiffness, and hypertension. Hypertension. 2015; 65: 252–256. pmid:25368028
  34. 34. Liapis CD, Kakisis JD, and Kostakis AG, Carotid stenosis: factors affecting symptomatology. Stroke. 2001; 32: 2782–2786. pmid:11739973
  35. 35. Waldstein SR, Manuck SB, Ryan CM, and Muldoon MF, Neuropsychological correlates of hypertension: review and methodologic considerations. Psychol Bull. 1991; 110: 451–468. pmid:1758919
  36. 36. Pall D, Settakis G, Katona E, Csiba L, Kakuk G, Limburg M, et al., Increased common carotid artery intima media thickness in adolescent hypertension: results from the Debrecen Hypertension study. Cerebrovasc Dis. 2003; 15: 167–172. pmid:12646774
  37. 37. Libby P, Inflammation in atherosclerosis. Nature. 2002; 420: 868–874. pmid:12490960
  38. 38. Yusuf S, Hawken S, Ounpuu S, Dans T, Avezum A, Lanas F, et al., Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. Lancet. 2004; 364: 937–952. pmid:15364185
  39. 39. van der Meer IM, Iglesias del Sol A, Hak AE, Bots ML, Hofman A, and Witteman JC, Risk factors for progression of atherosclerosis measured at multiple sites in the arterial tree: the Rotterdam Study. Stroke. 2003; 34: 2374–2379. pmid:12947155
  40. 40. Yusuf S, Reddy S, Ounpuu S, and Anand S, Global burden of cardiovascular diseases: Part II: variations in cardiovascular disease by specific ethnic groups and geographic regions and prevention strategies. Circulation. 2001; 104: 2855–2864. pmid:11733407
  41. 41. Chen Z, Peto R, Collins R, MacMahon S, Lu J, and Li W, Serum cholesterol concentration and coronary heart disease in population with low cholesterol concentrations. BMJ. 1991; 303: 276–282. pmid:1888927
  42. 42. Beckman JA, Creager MA, and Libby P, Diabetes and atherosclerosis: epidemiology, pathophysiology, and management. JAMA. 2002; 287: 2570–2581.
  43. 43. Urbina EM, Kimball TR, McCoy CE, Khoury PR, Daniels SR, and Dolan LM, Youth with obesity and obesity-related type 2 diabetes mellitus demonstrate abnormalities in carotid structure and function. Circulation. 2009; 119: 2913–2919. pmid:19470890
  44. 44. Mostaza JM, Lahoz C, Salinero-Fort MA, de Burgos-Lunar C, Laguna F, Estirado E, et al., Carotid atherosclerosis severity in relation to glycemic status: A cross-sectional population study. Atherosclerosis. 2015; 242: 377–382. pmid:26275375
  45. 45. Yuan C, Lai CW, Chan LW, Chow M, Law HK, and Ying M, Cumulative effects of hypertension, dyslipidemia, and chronic kidney disease on carotid atherosclerosis in Chinese patients with type 2 diabetes mellitus. J Diabetes Res. 2014; 2014: 179686. pmid:24860832
  46. 46. Paul TK, Srinivasan SR, Chen W, Li S, Bond MG, Tang R, et al., Impact of multiple cardiovascular risk factors on femoral artery intima-media thickness in asymptomatic young adults (the Bogalusa Heart Study). Am J Cardiol. 2005; 95: 469–473. pmid:15695130
  47. 47. Santos IS, Goulart AC, Brunoni AR, Kemp AH, Lotufo PA, and Bensenor IM, Anxiety and depressive symptoms are associated with higher carotid intima-media thickness. Cross-sectional analysis from ELSA-Brasil baseline data. Atherosclerosis. 2015; 240: 529–534. pmid:25955192
  48. 48. Kabir AA, Srinivasan SR, Sultana A, Chen W, Wei CY, and Berenson GS, Association between depression and intima-media thickness of carotid bulb in asymptomatic young adults. Am J Med. 2009; 122: 1151 e1151–1158.
  49. 49. Chirinos DA, Medina-Lezama J, Salinas-Najarro B, Arguelles W, Llabre MM, Schneiderman N, et al., Depressive symptoms and carotid intima-media thickness in South American Hispanics: results from the PREVENCION study. J Behav Med. 2015; 38: 284–293. pmid:25267357
  50. 50. Pan A, Sun Q, Okereke OI, Rexrode KM, and Hu FB, Depression and risk of stroke morbidity and mortality: a meta-analysis and systematic review. JAMA. 2011; 306: 1241–1249. pmid:21934057
  51. 51. Rundek T, Blanton SH, Bartels S, Dong C, Raval A, Demmer RT, et al., Traditional risk factors are not major contributors to the variance in carotid intima-media thickness. Stroke. 2013; 44: 2101–2108. pmid:23704105