Clinical Chemistry Link to Randox Laboratories Web Site
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

Clinical Chemistry 53: 456-464, 2007. First published January 26, 2007; 10.1373/clinchem.2006.073668
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
clinchem.2006.073668v1
53/3/456    most recent
Right arrow Submit an electronic Letter to
the Editor about this paper
Right arrow Alert me when this article is cited
Right arrow Alert me when eLetters are posted
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via ISI Web of Science (6)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Kelishadi, R.
Right arrow Articles by Adeli, K.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Kelishadi, R.
Right arrow Articles by Adeli, K.
Related Collections
Right arrow Lipids, Lipoproteins, and Cardiovascular Risk Factors
(Clinical Chemistry. 2007;53:456-464.)
© 2007 American Association for Clinical Chemistry, Inc.

Lipids, Lipoproteins, and Cardiovascular Risk Factors

Relationship Between C-Reactive Protein and Atherosclerotic Risk Factors and Oxidative Stress Markers Among Young Persons 10–18 Years Old

Roya Kelishadi1,a, Mohsen Sharifi2, Alireza Khosravi1 and Khosrow Adeli3

1 Isfahan Cardiovascular Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.
2 Isfahan University of Medical Sciences, Isfahan, Iran.
3 Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada.

aAddress correspondence to this author at: Preventive Pediatric Cardiology Department, Isfahan Cardiovascular Research Centre, Isfahan University of Medical Sciences, PO Box 81465-1148, Isfahan, Iran. Fax 98-311-3373435; e-mail kroya{at}aap.net or Kelishadi{at}med.mui.ac.ir


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Background: This study was undertaken to determine the association of serum C-reactive protein (CRP) with generalized and abdominal obesity, body fat composition, the metabolic syndrome, and oxidative stress markers among young people.

Methods: We conducted a population-based study of 512 young people, aged 10–18 years. We obtained anthropometric and blood pressure measurements. Fasting blood sugar, total cholesterol (TC), HDL-cholesterol, triglycerides, CRP, malondialdehyde (MDA), and conjugated diene (CDE) were quantified. LDL-cholesterol (LDL-C) was calculated for samples with TG ≤4.52 mmol/L

Results: Mean triglycerides, waist and hip circumferences, percentage body fat, subcutaneous fat, and systolic blood pressure increased significantly with increasing body mass index (BMI). In contrast, the mean LDL and TC were higher in underweight than normal weight individuals, and then increased significantly from normal to higher BMI categories. Mean HDL cholesterol significantly decreased with increasing BMI. Overall, CRP, MDA, and CDE were significantly correlated with measures of abdominal obesity. Serum CRP, MDA, and CDE significantly increased in the upper quartiles of waist circumference. Study participants with higher CRP concentrations were more likely to have metabolic syndrome and high oxidative stress markers.

Conclusion: We found a significant positive association between CRP and oxidative stress markers in healthy young people, as well as an increase in these markers in the upper quartiles of waist circumference, but not BMI. Oxidative stress and CRP may interact in the early inflammatory processes of atherosclerosis.


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
The relationship between inflammatory factors and coronary heart disease (CHD)1 suggests that subclinical chronic inflammation may have a major role in the development of atherosclerosis (1). It is now well established that atherosclerosis originates in early life, and that its risk factors track to adulthood. Although the relationship between C-reactive protein (CRP) and the risk of CHD has been shown in adults (2), limited studies have been conducted among young people. Some studies documented a correlation between serum CRP and white blood cell count and some CHD risk factors among youths (3).

The serum concentration of CRP is known to be an independent risk factor and a predictor for CHD (1)(2). Studies performed among different ethnic groups showed diverse results, but all these studies confirmed a relationship between serum CRP and both generalized and abdominal obesity (4). Oxidative stress may have proinflammatory effects, but limited data exist on its relationship with CRP in healthy individuals. In our previous study, we found a higher level of oxidative stress in offspring of parents with premature myocardial infarction than in controls (5). Oxidative stress may be a determinant of CRP concentrations, and promotes the proatherosclerotic inflammatory process (6). To the best of our knowledge, no previous study has evaluated the relationship of CRP with oxidative stress markers among youths.

The current study was conducted to investigate the association of serum CRP with generalized and abdominal obesity, as well as body fat composition, blood pressure (BP), lipid profile, and the oxidative stress markers malondialdehyde (MDA) and conjugated diene (CDE) among a representative sample of children and adolescents.


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
We conducted this population-based study in 2004–2005 among a representative sample of students aged 10–18 years in Isfahan, the second largest city in Iran. A total of 512 individuals (age 10–18 years) participated in the study. Based on power calculations, this sample was deemed large enough to test our hypothesis.

Students were selected by multistage-random cluster sampling from urban and rural areas. Initially, we randomly selected census blocks based on data from the Ministry of Health, and then randomly selected the schools and the students. Schools were stratified according to location (urban/rural) and the socioeconomic character of their enrollment area, with consideration to the proportion of the different types of schools (public/private) to avoid socioeconomic bias. From each stratum we selected a proportional, 2-stage cluster sample of students. Students who had chronic disease, long-term medication use, or a history of acute infectious diseases in the past 2 weeks were excluded from the study.

The Ethics Committee of the Isfahan Cardiovascular Research Center (NIH member) approved the study. Written informed consent was obtained from parents and oral assent from students. Participants were asked to come to the Pediatric Metabolic Syndrome Clinic of the Preventive Pediatric Cardiology Department, Isfahan Cardiovascular Research Center (WHO-collaborating center).

The same physician and nurse examined all study participants and recorded their age and birth date. Height and weight were measured twice to ±0.2 cm and to ±0.2 kg, respectively, while the study participants were barefoot and lightly dressed; the averages of these measurements were recorded. Body mass index (BMI) (weight in kilograms divided by the square of height in meters) was calculated. Waist and hip circumferences (WC and HiC, respectively) were measured to the nearest 0.5 cm. Next, waist-to-hip ratio (WHR) and the waist-to-stature ratio (WSR) were computed by dividing the WC by the HiC and height, respectively. We defined BMI categories on the basis of a z score; the subjects were then classified as underweight (z score <–2.0), normal weight (z score –2.0 to 2.0), overweight (z score 2.0 to 2.5) or obese (z score >2.5).

A series of 3 BP measurements was performed on each participant. The procedure was explained to the students and the cuff inflated and deflated once; this measurement was not used in the analysis of this study. Then, duplicate BP measurements were performed on the right arm using mercury sphygmomanometers. The readings at the 1st and the 5th Korotkoff phase were taken as systolic and diastolic BP (SBP and DBP), respectively. The average of the 2 BP measurements was recorded and included in the analysis (7). Subcutaneous fat in the bicep and tricep muscles was measured with a skinfold caliper (Mojtahedi), and the percentage of body fat was determined by bioelectrical impedance using a Body Fat Monitor (Omron HBF-300).

We instructed the participants to fast for 12 h before blood collection, and testing compliance was determined by interview on the morning of the physical examination. Blood samples were obtained from the antecubital vein between 0800 and 0930. Blood samples were centrifuged for 10 min at 906g within 30 min of collection. Sera were analyzed in the central laboratory at Isfahan Cardiovascular Research Center. This laboratory meets the standards of the National Reference Laboratory (WHOCollaborating Center), and is also under the quality control of the Centers for Disease Prevention and Control, U S A, and the Department of Epidemiology, St. Rafael University, Leuven, Belgium. Fasting blood sugar (FBS), total cholesterol (TC), HDL-Cholesterol (HDL-C) and triglycerides (TG) were measured enzymatically (Pars Azmoun) on Elan2000 autoanalyzers (Eppendorf). HDL-C was determined after dextran sulfate-magnesium chloride precipitation of non-HDL-C. LDL-cholesterol (LDL-C) was calculated in serum samples with TG ≤4.52 mmol/L, according to the Friedewald equation (8).

CRP was measured with the same autoanalyzer. The assay (Pars Azmoun) had a limit of detection <0.05 mg/L and an upper limit of 160 mg/L. The intraassay and interassay CVs were 0.8%–1.3% and 1.0%–1.5%, respectively. The measurement of CDE and MDA was performed as described by Chajes et al. (9) and Eslerdauer et al.(10). CRP, MDA, and CDE were categorized to age- and sex-specific quartiles.

Because no universally accepted definition of the metabolic syndrome (MetS) exists for children, we used a definition similar to that used by de Ferranti et al. (11), which is defined as ≥3 of the following: fasting TG ≥1.1 mmol/L, HDL-C <1.3 mmol/L, (except in boys aged 15–19 years, for whom the cutoff was <1.17 mmol/L), WC >75th percentile for age and sex in the population studied; SBP/DBP >90th percentile for sex, age, and height from the National Heart, Lung, and Blood Institute’s recommended cutoff point (7); and FBS ≥5.5 mmol/L. It should be noted that de Ferranti et al. used the cutoff of FBS >6.1 mmol/L (11), but we used the recent recommendation of the American Diabetes Association (12).

Statistical Analysis.
Stored data were analyzed by the SPSS version 13.0 software. Because this study comprised a study population with a wide range of ages, and the factors under study might differ between early and late adolescence, the mean value of the variables were compared between the 2 age groups of 10–13.9 and 14–18 years. Biological and biochemical variables were compared by ANOVA and Tukey Post Hoc tests. Pearson correlation analyses and multiple linear regression were used to assess the relationships of CRP with physical and biochemical characteristics, adjusted for age and sex. The associations of CRP (age- and sex-specific upper quartile and other) with the MetS and upper quartiles of oxidative stress markers were examined with logistic regression analysis. The significance level was set at P <0.05.


   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
A total of 512 children and adolescents were studied. This study population included 254 boys and 258 girls, aged 10–18 years, with a mean (SD) age of 13.7 (2.2) years. Among boys, the mean weight, height, and BMI of those aged 10–13.9 years corresponded to the age- and sex-specific 50th percentile of CDC growth charts (13) (ranging between 10th–90th percentile), and for those aged 14–18 years the mean corresponded to the 25th percentile (ranging between 5th and 75th percentile). The corresponding figures for girls were 50th–75th percentile (25th–90th percentile) and 25th–50th percentile (5th–75th), respectively.

Serum CRP, HDL-C and oxidative stress markers were not significantly different between sexes (Table 1 ). TC, LDL-C, and TG were higher in girls than in boys. Anthropometric measures were not significantly different between sexes, but were higher in the upper than the lower age group. Girls aged 14–18 years had the highest percentage of body fat. The MetS was detected in 14.2% of participants, with a prevalence of 42% among overweight and 51% among obese youths.


View this table:
[in this window]
[in a new window]

  		Table 1. Baseline characteristics of subjects studied.

The mean values of physical and biochemical characteristics of study participants according to their BMI z score are shown in Table 2 . The mean TG, WC, HiC, percent body fat, subcutaneous fat, and SBP increased significantly with increasing BMI. In contrast, the mean TC and LDL-C was higher in underweight than in normal weight subjects (P = 0.02), and then it increased significantly from normal to higher BMI categories. The mean HDL-C significantly decreased with increasing BMI.


View this table:
[in this window]
[in a new window]

  		Table 2. Baseline characteristics of participants according to the category of BMI, before and after adjustment for age and sex.

The age and sex-adjusted correlations among biochemical variables and different obesity indices are presented in Table 3 . Overall, CRP, MDA, and CDE were significantly correlated with measures of abdominal obesity (WC, WSR, WHR), but not generalized obesity (BMI) or subcutaneous fat.


View this table:
[in this window]
[in a new window]

  		Table 3. Age and sex-adjusted Pearson correlation coefficients of biochemical variables and different obesity indices.

The linear regression predictors of CRP concentration before and after adjustment for age and sex (Table 4 ) shows that the correlation of CRP and BMI was significant only after adjustment for age and sex, but its correlation with measures of abdominal obesity was significant both before and after adjustment for age and sex.


View this table:
[in this window]
[in a new window]

  		Table 4. Linear regression predictors of CRP among children and adolescents.

Serum CRP, MDA, and CDE did not differ among various categories of BMI, but significantly increased in the higher quartiles of WC (Fig. 1 ).


Figure 1
View larger version (17K):
[in this window]
[in a new window]

  		Figure 1. Serum CRP and oxidative stress markers according to the categories of the BMI and quartiles of the WC in children and adolescents.

Study participants with upper quartiles of CRP were more likely to have the MetS, abnormal lipid profile, and higher quartiles of oxidative stress markers (Table 5 ).


View this table:
[in this window]
[in a new window]

  		Table 5. Logistic regression of abnormal biochemical factors and CRP ≥75th percentile among children and adolescents.


   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
We found a significant correlation between CRP and oxidative stress markers (MDA, CDE) in healthy children and adolescents, as well as between CRP, MDA, and CDE with abdominal obesity, but not with generalized obesity. These biochemical factors increased significantly with a rise in measures of abdominal obesity, but not with BMI.

It was shown that, among adults, there are strong associations between CRP and measures of generalized and abdominal obesity (14). Some previous studies among youths found similar associations. A study in Asian Indians showed a significant correlation of CRP with BMI and WC in adolescents and young adults (15). In addition, it was found that CRP concentrations correlated significantly with BMI, percent body fat, WC, WHR, and skinfold thickness of adolescents (16).

It has been demonstrated that fat accumulation correlates with the markers of systemic oxidative stress in humans and mice (17). A recent population-based study among adults confirmed that abdominal fat accumulation is associated with oxidative stress (18). Among healthy adults, oxidative stress markers were significantly associated with higher CRP concentrations, independent of BMI and other CRP determinants. These data suggest that oxidative stress may be a determinant of CRP concentrations, promoting proatherosclerotic inflammatory processes at the earliest stages of CHD development (6). Interestingly, recent studies showed that serum CRP is independently associated with advanced atherosclerosis in young persons, which suggests a potential direct prooxidant role for CRP (19)(20). To the best of our knowledge, no previous study has evaluated the relationships between CRP and oxidative stress markers among healthy children and adolescents; however, such an association has been documented in children with chronic and end stage renal failure (21).

Little is known about oxidative stress in childhood obesity and insulin resistance. Atabek et al. first showed that peroxy radical concentrations are high in obese children. They suggested that increased SBP associated with hyperlipidemia may independently contribute to increased oxidative stress in childhood obesity (22). More recently, this same group documented the presence of protein oxidation in obese children, and suggested that insulin resistance may play an important role as a source of oxidative stress in the development of other diseases later in life (23). Erdeve et al. have also shown the induction of oxidative stress in obesity and related antioxidative response, even in the pediatric age group (24). In a previous study, we also showed higher values of MDA, and an increased susceptibility of LDL-C to oxidation, in children with high family risk for premature CHD (5). In the present study, we found higher concentrations of CDE and MDA in youth with abdominal obesity. Interestingly, Engler et al. (25) demonstrated that antioxidant vitamin therapy improves endothelial function, and affects biomarkers for oxidative stress and inflammation in hyperlipidemic children. This clearly suggests that interventions, notably dietary modifications, might be effective in diminishing the obesity-related oxidative stress from childhood.

A number of new biomarkers for assessing oxidative stress have been developed, including isoprostanes, 8-hydroxyguanine, 3-nitrotyrosine, oxidized lowdensity lipoprotein, plasma antioxidants, and redox transition metals. Among these, oxidized low-density lipoprotein and isoprostanes have been suggested as emerging plasma biomarkers that hold promise for cardiovascular risk prediction (26). The correlation between these new biomarkers and pediatric obesity has not been investigated, but they are likely to correlate with the changes observed in CRP, MDA, and CDE in the present study.

In addition, in the current study we found that total- and LDL-C were not only higher in obese children, but also in underweight compared with normal weight children. Consistent with the current study, a number of studies have found abnormal lipid values in obese compared with non-obese children (2). However, other studies that have compared underweight, normal weight, and obese youth for CHD risk factors did not document a significant difference in mean serum cholesterol and LDL-C (27). A study among hemodialysis patients revealed a higher prevalence of atherosclerosis in underweight and obese patients compared with normal and overweight patients, and documented a U-shaped association of BMI with inflammation and atherosclerosis (28). Although different adaptive mechanisms to dietary cholesterol in lean and obese subjects are known (29), a coexistence of underweight and lower physical activity levels in low socioeconomic children (30) should be considered as well. Our previous study indicated that the improper quality of the consumed fat that is rich in saturated and trans-fatty acids was correlated with the high prevalence of dyslipidemia in Iranian youths (31). These observations point out the need for new public health policies in developing appropriate intervention strategies to efficiently identify and counteract these health and social risk factors early in life.

Some studies have suggested a possible role of subclinical inflammation in insulin resistance and glucose intolerance that only partly explained the link between obesity and impaired glucose homeostasis (32). It has also been documented that chronic, subclinical inflammation, as indicated by increased circulating CRP concentrations, is more strongly associated with postchallenge glycemia than with fasting glucose in nondiabetic adults. This association is partially independent of body fat and insulin resistance (33). The independent relation between CRP concentrations and insulin resistance among women has been reported in other studies as well (34). A study among adults showed a relationship between increased CRP concentrations and the presence of the MetS, especially in women (35). Some studies have shown that CRP concentrations are higher in adolescents with the MetS than in those without it (36), that acute-phase reaction is correlated with the MetS in obese youth, and that the cluster of these proatherogenic factors may contribute to the accelerated atherosclerosis in obese children (37). However, other investigators found that, after adjustment for adiposity in adolescents, CRP was not significantly associated with the MetS and its components. These authors suggested that the MetS may precede the development of CRP elevation (38). Ford et al.(36) showed an independent association between abdominal obesity and CRP concentrations. In the current study, we found significant associations of abdominal obesity and the MetS with CRP and oxidative stress markers. In this study, the mean weight and BMI of subjects aged 10–13.9 years corresponded to the higher percentiles of CDC growth charts (17), which might reflect the growing problem of obesity in Iranian youths. Similar to many reports from Western countries, in our previous national study, which was the first study of its kind in Asia, we found close correlations between abdominal obesity and cardiovascular risk factors among youths, and found that WC was one of the best predictive indices for these risk factors. These findings emphasize the importance of abdominal obesity during childhood (39). The findings of the current study suggest that the metabolic complications of abdominal obesity and body fat distribution, as well as low-grade systemic inflammation, are detectable early in life. Regarding study limitations, we should acknowledge that the associations found in the current study should be interpreted with caution, given the cross-sectional nature of the associations. In addition, this study could not show the temporal ordering of the association between oxidative stress markers and CRP. Further longitudinal investigations are needed to confirm these associations.


   Acknowledgments
 
The study was funded by Isfahan Cardiovascular Research Center, Isfahan University of Medical Sciences.


   Footnotes
 
1 Nonstandard abbreviations: CHD, coronary heart disease; CRP, C-reactive protein; BP, blood pressure; MDA, malondialdehyde; CDE, conjugated diene; BMI, body mass index; WC, waist circumference; HiC, hip circumference; WHR, waist-to-hip ratio; WSR, waist-to-stature ratio; SBP, systolic blood pressure; DBP, diastolic blood pressure; FBS, fasting blood sugar; TC, total cholesterol, HDL-C, HDL cholesterol; TG, triglycerides; LDL-C, LDL cholesterol; and MetS, metabolic syndrome.


   References
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

  1. Ridker PM, Buring JE, Cook NR, Rifai N. C-reactive protein, the metabolic syndrome, and risk of incident cardiovascular events: an 8-year follow-up of 14719 initially healthy American women. Circulation 2003;107:391-397.[Abstract/Free Full Text]
  2. Danesh J, Wheeler JG, Hirschfield GM, Eda S, Eiriksdottir G, Rumley A, et al. C-reactive protein and other circulating markers of inflammation in the prediction of coronary heart disease. N Engl J Med 2004;350:1387-1397.[Abstract/Free Full Text]
  3. Cook DG, Mendall MA, Whincup PH, Carey IM, Ballam L, Morris JE, et al. C-reactive protein concentration in children: relationship to adiposity and other cardiovascular risk factors. Atherosclerosis 2000;149:139-150.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  4. Barbeu P, Litaker MS, Woods KF, Lemmon CR, Humphries MC, Owen S, et al. Haemostatic and inflammatory markers in obese youths: effects of exercise and adiposity. J Pediatr 2002;141:415-420.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  5. Kelishadi R, Nadery GA, Asgary S. Oxidized LDL metabolites with high family risk for premature cardiovascular disease. Indian J Pediatr 2002;69:755-759.[Medline] [Order article via Infotrieve]
  6. Abramson JL, Hooper WC, Jones DP, Ashfaq S, Rhodes SD, Weintraub WS, et al. Association between novel oxidative stress markers and C-reactive protein among adults without clinical coronary heart disease. Atherosclerosis 2005;178:115-121.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  7. Update on the 1987 Task Force Report on High Blood Pressure in Children and Adolescents: a working group report from the National High Blood Pressure Education Program. National High Blood Pressure Education Program Working Group on Hypertension Control in Children and Adolescents. Pediatrics 1996;98:649-658.[Abstract/Free Full Text]
  8. Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem 1972;18:499-502.[Abstract]
  9. Chajes V, Sattlre W, Stultschnig M, Kostner G. Photometric evaluation of lipid peroxidation products in human plasma and copper oxidized low density lipoproteins: correlation of different oxidation parameters. Atherosclerosis 1996;121:193-203.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  10. Esterbauer H, Cheeseman KH. Determination of aldehydic lipid peroxidation products: malonaldehyde and 4 hydroxynonenal. Meth Enzymol 1990;186:407-421.[Medline] [Order article via Infotrieve]
  11. de Ferranti SD, Gauvreau K, Ludwig DS, Neufeld EJ, Newburger JW, Rifai N. Prevalence of the metabolic syndrome in American adolescents: findings from the Third National Health and Nutrition Examination Survey. Circulation 2004;110:2494-2497.[Abstract/Free Full Text]
  12. Genuth S, Alberti KG, Bennett P, Buse J, Defronzo R, Kahn R, et al. Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Follow-up report on the diagnosis of diabetes mellitus. Diabetes Care 2003;26:3160-3167.[Free Full Text]
  13. Kuczmarski RJ, Ogden CL, Grummer-Strawn LM. CDC growth charts: United States. Adv Data 2000;314:1-27.[Medline] [Order article via Infotrieve]
  14. Festa A, D’Agostino R, Jr, Howard G, Mykkanen L, Tracy RP, Haffner SM. Chronic subclinical inflammation as part of the insulin resistance syndrome: the Insulin Resistance Atherosclerosis Study (IRAS). Circulation 2000;102:42-47.[Abstract/Free Full Text]
  15. Vikram NK, Misra A, Dwivedi M, Sharma R, Pandey RM, Luthra K, et al. Correlations of C-reactive protein levels with anthropometric profile, percentage of body fat and lipids in healthy adolescents and young adult in urban North India. Atherosclerosis 2003;168:305-313.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  16. Vikram NK, Misra A, Pandey RM, Dwivedi M, Luthra K. Adiponectin, insulin resistance, and C-reactive protein in postpubertal Asian Indian adolescents. Metabolism 2004;53:1336-1341.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  17. Furukawa S, Fujita T, Shimabukuro M, Iwaki M, Yamada Y, Nakajima Y, et al. Increased oxidative stress in obesity and its impact on metabolic syndrome. J Clin Invest 2004;114:1752-1761.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  18. Suzuki K, Inoue T, Hioki R, Ochiai J, Kusuhara Y, Ichino N, et al. Association of abdominal obesity with decreased serum levels of carotenoids in a healthy Japanese population. Clin Nutr 2006;25:780-789.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  19. Zieske AW, Tracy RP, McMahan CA, Herderick EE, Homma S, Malcom GT, et al. Pathobiological Determinants of Atherosclerosis in Youth Research Group. Elevated serum C-reactive protein levels and advanced atherosclerosis in youth. Arterioscler Thromb Vasc Biol 2005;25:1237-1243.[Abstract/Free Full Text]
  20. Kobayashi S, Inoue N, Ohashi Y, Terashima M, Matsui K, Mori T, et al. Interaction of oxidative stress and inflammatory response in coronary plaque instability: important role of C-reactive protein. Arterioscler Thromb Vasc Biol 2003;23:1398-1404.[Abstract/Free Full Text]
  21. Ece A, Gurkan F, Kervancioglu M, Kocamaz H, Gunes A, Atamer Y, et al. Oxidative stress, inflammation and early cardiovascular damage in children with chronic renal failure. Pediatr Nephrol 2006;21:545-552.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  22. Atabek ME, Vatansev H, Erkul I. Oxidative stress in childhood obesity. J Pediatr Endocrinol Metab 2004;17:1063-1068.[ISI][Medline] [Order article via Infotrieve]
  23. Atabek ME, Keskin M, Yazici C, Kendirci M, Hatipoglu N, Koklu E, et al. Protein oxidation in obesity and insulin resistance. Eur J Pediatr 2006;165:753-756.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  24. Erdeve O, Siklar Z, Kocaturk PA, Dallar Y, Kavas GO. Antioxidant superoxide dismutase activity in obese children. Biol Trace Elem Res 2004;98:219-228.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  25. Engler MM, Engler MB, Malloy MJ, Chiu EY, Schloetter MC, Paul SM, et al. Antioxidant vitamins C and E improve endothelial function in children with hyperlipidemia: Endothelial Assessment of Risk from Lipids in Youth (EARLY)Trial. Circulation 2003;108:1059-1063.[Abstract/Free Full Text]
  26. Tsimikas S. Measures of oxidative stress. Clin Lab Med 2006;26:571-590.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  27. Aziz J, Siddiqui NA, Siddiqui IA, Omair A. Relation of body mass index with lipid profile and blood pressure in young healthy students at Ziauddin Medical University. J Ayub Med Coll Abbottabad 2003;15:57-59.[Medline] [Order article via Infotrieve]
  28. Kahraman S, Yilmaz R, Akinci D, Arici M, Altun B, Erdem Y, et al. U-shaped association of body mass index with inflammation and atherosclerosis in hemodialysis patients. J Ren Nutr 2005;15:377-386.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  29. Klass DM, Buhrmann K, Sauter G, Del Puppo M, Scheibner J, Fuchs M, et al. Biliary lipids, cholesterol and bile synthesis: different adaptive mechanisms to dietary cholesterol in lean and obese subjects. Aliment Pharmacol Ther 2006;23:895-905.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  30. Manios Y, Dimitriou M, Moschonis G, Kocaoglu B, Sur H, Keskin Y, et al. Cardiovascular disease risk factors among children of different socioeconomic status in Istanbul, Turkey: directions for public health and nutrition policy. Lipids Health Dis 2004;3:11.[CrossRef][Medline] [Order article via Infotrieve]
  31. Kelishadi R, Pour MH, Zadegan NS, Kahbazi M, Sadry G, Amani A, et al. Fat intake and serum lipid profile in Iranian adolescents: IHHP-HHPC. Prev Med 2004;39:760-766.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  32. Nakanishi N, Shiraishi T, Wada M. Association between C-reactive protein and insulin resistance in a Japanese population: the Minoh Study. Intern Med 2005;44:542-547.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  33. Festa A, D’Agostino R, Jr, Tracy RP, Haffner SM. C-reactive protein is more strongly related to post-glucose load glucose than to fasting glucose in non-diabetic subjects; the Insulin Resistance Atherosclerosis Study. Diabet Med 2002;19:939-943.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  34. McLaughlin T, Abbasi F, Lamendola C, Liang L, Reaven G, Schaaf P, et al. Differentiation between obesity and insulin resistance in the association with C-reactive protein. Circulation 2002;106:2908-2912.[Abstract/Free Full Text]
  35. Florez H, Castillo-Florez S, Mendez A, Casanova-Romero P, Larreal-Urdaneta C, Lee D, et al. C-reactive protein is elevated in obese patients with the metabolic syndrome. Diabetes Res Clin Pract 2006;71:92-100.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  36. Ford ES, Ajani UA, Mokdad AH, . National Health and Nutrition Examination. The metabolic syndrome and concentrations of C-reactive protein among U. S. youth. Diabetes Care 2005;28:878-881.[Abstract/Free Full Text]
  37. Garanty-Bogacka B, Syrenicz M, Syrenicz A, Gebala A, Walczak M. Relation of acute-phase reaction and endothelial activation to insulin resistance and adiposity in obese children and adolescents. Neuro Endocrinol Lett 2005;26:473-479.[Medline] [Order article via Infotrieve]
  38. Moran A, Steffen LM, Jacobs DR, Jr, Steinberger J, Pankow JS, Hong CP, et al. Relation of C-reactive protein to insulin resistance and cardiovascular risk factors in youth. Diabetes Care 2005;28:1763-1768.[Abstract/Free Full Text]
  39. Kelishadi R, Gheiratmand R, Ardalan G, Adeli K, Mehdi Gouya M, Mohammad Razaghi E, et al; for the CASPIAN Study Group. Association of anthropometric indices with cardiovascular disease risk factors among children and adolescents: CASPIAN Study. Int J Cardiol. 2006 Jul 19; [Epub ahead of print].



The following articles in journals at HighWire Press have cited this article:


Home page
 Clin. Chem.Home page
R. Kelishadi, M. Hashemi, N. Mohammadifard, S. Asgary, and N. Khavarian
Association of Changes in Oxidative and Proinflammatory States with Changes in Vascular Function after a Lifestyle Modification Trial Among Obese Children
Clin. Chem., January 1, 2008; 54(1): 147 - 153.
[Abstract] [Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
clinchem.2006.073668v1
53/3/456    most recent
Right arrow Submit an electronic Letter to
the Editor about this paper
Right arrow Alert me when this article is cited
Right arrow Alert me when eLetters are posted
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via ISI Web of Science (6)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Kelishadi, R.
Right arrow Articles by Adeli, K.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Kelishadi, R.
Right arrow Articles by Adeli, K.
Related Collections
Right arrow Lipids, Lipoproteins, and Cardiovascular Risk Factors

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS