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American Journal of Clinical Nutrition, Vol. 84, No. 4, 748-755, October 2006
© 2006 American Society for Nutrition

ORIGINAL RESEARCH COMMUNICATION

Dietary intakes of fat and antioxidant vitamins are predictors of subclinical inflammation in overweight Swiss children1,2,3

Isabelle Aeberli, Luciano Molinari, Giatgen Spinas, Roger Lehmann, Dagmar l'Allemand and Michael B Zimmermann

1 From the Human Nutrition Laboratory, Institute of Food Science and Nutrition, Swiss Federal Institute of Technology, Zurich, Switzerland (IA and MBZ); the Department for Growth and Development, University Children's Hospital, Zurich, Switzerland (LM); the Clinic for Endocrinology and Diabetes, University Hospital Zurich, Zurich, Switzerland (GS and RL); and the Children's Hospital of Eastern Switzerland, St Gallen, Switzerland (Dl'A)

2 Supported by the Swiss Diabetes Foundation (Steinhausen, Switzerland), the Swiss Ministry of Health (Bern, Switzerland), and the Swiss Federal Institute of Technology (Zurich, Switzerland).

3 Reprints not available. Address correspondence to MB Zimmermann, Institute of Food Science and Nutrition, Human Nutrition Laboratory, ETH Zurich, LFV E19, Schmelzbergstrasse 7, 8092 Zürich, Switzerland. E-mail: michael.zimmermann{at}ilw.agrl.ethz.ch.


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Background: In obese children, subclinical inflammation is often present and is correlated with the metabolic syndrome. Dietary factors, such as fatty acids and antioxidants, potentially modulate the association between adiposity and subclinical inflammation, but few data are available in children.

Objective: The aim of the study was to determine whether dietary fat or antioxidant intakes influence circulating tumor necrosis factor {alpha} (TNF-{alpha}), interleukin 6 (IL-6), C-reactive protein (CRP), and leptin concentrations in overweight children.

Design: In a cross-sectional study of 6–14-y-old normal-weight (n = 33), overweight (n = 19), and obese (n = 27) Swiss children, nutritional intakes were assessed from two 24-h dietary recalls and a 1-d dietary record. Percentage body fat from skinfold thicknesses, waist-hip ratio, and blood pressure were measured. Fasting blood samples were collected for the measurement of insulin, glucose, HDL-cholesterol, triacylglycerol, CRP, IL-6, TNF-{alpha}, and leptin concentrations.

Results: CRP, IL-6, and leptin increased significantly (P < 0.02) with increasing adiposity, independent of age; TNF-{alpha} did not increase. Total dietary fat and the percentage of energy from fat were significant predictors of CRP concentration, independent of body mass index (P < 0.05). Meat intake was a significant predictor of IL-6 and leptin, independent of body mass index (P < 0.05). Intakes of antioxidant vitamins (vitamins E and C and ß-carotene) were significant predictors of leptin (P < 0.05) but not of CRP, IL-6, or TNF-{alpha}.

Conclusions: Overweight Swiss children as young as 6 y have elevated concentrations of inflammatory markers. Intakes of total fat and antioxidant vitamins are determinants of subclinical inflammation in this age group.

Key Words: Children • obesity • inflammation • diet • C-reactive protein • interleukin 6 • leptin • tumor necrosis factor {alpha} • fat • antioxidants


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
The prevalence of pediatric obesity is increasing globally at an alarming rate (1, 2). Many of the cardiovascular and metabolic complications of excess body fat are already detectable in overweight children (3). Childhood obesity is a significant early risk factor for adult cardiovascular disease and diabetes (4, 5). In obesity, adipocytes produce proinflammatory cytokines, including tumor necrosis factor {alpha} (TNF-{alpha}) and interleukin 6 (IL-6) (6, 7). IL-6 stimulates the hepatic synthesis of C-reactive protein (CRP), an inflammatory marker. In addition, leptin, which is elevated in obese subjects, has been shown to be proinflammatory (8). Subclinical inflammation in adults is associated with a greater risk of type 2 diabetes and cardiovascular disease (9-11). In obese older children and adolescents, elevated concentrations of CRP and IL-6 correlate with components of the metabolic syndrome (12), including elevated body mass index (BMI), high triacylglycerol concentrations, low HDL-cholesterol concentrations, elevated systolic blood pressure, and impaired glucose tolerance (12-17). Subclinical inflammation also correlates with markers of oxidative stress (18). In obesity, CRP concentrations predict 8-iso-prostaglandin F2{alpha} (8-iso-PGF2{alpha}) excretion (a marker of lipid peroxidation) independently of insulin and leptin concentrations (19). In adults, increased oxidative stress in adipose tissue may be a mechanism of obesity-associated insulin resistance and the metabolic syndrome (20, 21).

Dietary factors, such as fatty acids (22, 23) and antioxidants (24), potentially modulate the association between adiposity and subclinical inflammation (25). Both the type and total amount of dietary fat can influence plasma and tissue fatty acid composition (26, 27), which, in turn, can modify inflammation (28, 29) and inflammation-mediated disease (30). Overweight adolescents with elevated CRP and IL-6 concentrations have higher plasma concentrations of saturated fatty acids and lower concentrations of n–3 polyunsaturated fatty acids (31). Dietary antioxidants can influence the expression of proinflammatory cytokines (32). Low antioxidant vitamin concentrations and reduced antioxidant capacity are common in obese children (33-37). Therefore, the aim of the present study was to investigate the dietary determinants of subclinical inflammation in overweight young children. Specifically, we examined whether dietary fat or antioxidant intakes influence TNF-{alpha}, IL-6, CRP, and leptin concentrations in overweight Swiss children.


   SUBJECTS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
The subjects for this study were 6–14 y-old children (n = 79) living in northern Switzerland. The children were a convenience sample recruited through letters to primary schools and pediatric clinics. Children recruited from the pediatric clinics were otherwise healthy overweight children presenting to the clinic for the first time for weight-loss counseling. Our intent was to enroll 25 normal-weight, 25 overweight, and 25 obese children for the study. Informed written consent was obtained from the parents, and informed oral assent was obtained from the children. Ethical approval for the study was obtained from the ethics committee of the Swiss Federal Institute of Technology in Zürich.

Well-trained female interviewers assessed the dietary intakes of each child using two 24-h dietary recalls and one 1-d weighed food record in the family home. Each child was visited 3 times by the same interviewer within 3 wk. The 24-h dietary recalls were done at the first and second visits, and, at the second visit, the interviewer gave instructions and guidelines for the 1-d weighed food record. At the third visit, the 1-d food record was carefully reviewed, and a questionnaire on usual dietary habits was completed with the child. The questionnaire included queries on food and beverage preferences, including sweets, baked goods, and snacks, and frequency and temporal patterns of snacking.

Volumes and portion sizes for the 24-h dietary recalls were estimated by using measuring cups and spoons, photographs of food portions, and graduated food samples of cheese and bread. The combination of 24-h dietary recalls and a food record provides a good overview of a child's habitual diet; this approach has been validated in children as young as 8 y of age (38). An appointment was scheduled at the hospital clinic, at the parents' convenience, usually within 1–2 wk of the dietary assessment.

The children arrived at the hospital clinic in the morning after a 12-h overnight fast. Twelve milliliters of blood (2 mL into EDTA-containing tubes) was collected by venipuncture. Height was measured to the nearest 0.5 cm and weight to the nearest 100 g with a digital balance (BF 18; Beurer, Ulm, Germany). Pubertal staging was done. Waist and hip circumferences were measured with a nonstretchable measuring tape. Skinfold thicknesses were measured at the triceps and subscapular sites with a Harpenden Skinfold Caliper (HSK-BI; British Indicators, West Sussex, United Kingdom) with a constant spring pressure of 10 g/mm2 and a resolution of 0.2 mm. A single experienced observer (IA) performed all of the measurements of waist and hip circumferences and skinfold thicknesses. After a 15-min rest, supine resting blood pressure was measured by auscultation.

Data analysis
Dietary data obtained from the 3 records were checked carefully and entered by the lead interviewer (IA) into a nutrition software system (EBISpro for Windows 4.0; Dr J Erhardt, University of Hohenheim, Germany). This system translates the amount of food eaten into individual nutrients and assigns consumed foods into 22 food groups. The program is based on the German Food and Nutrition Data Base BLS 2.3 (Federal Health Department, Berlin, Germany), and, for foods specific to Switzerland, incorporates values from the Swiss Food Composition Database (39). Energy and nutrient data were averaged across the 3 d to obtain a mean daily energy and nutrient intake for each child. The reference values for nutrient intakes for Germany, Austria, and Switzerland—the D-A-CH references (40)—were used for comparison of the actual intakes with the recommended intakes for the respective age groups.

The BMIs of the children were calculated as weight (kg)/height squared (m). BMI SD scores (BMI-SDS = individual BMI value – reference mean BMI value ÷ SD, to scale the data for comparison across ages and sex) were calculated and used in the analysis. Age- and sex-specific criteria from the US Centers for Disease Control and Prevention (41) were used to classify children as normal weight, overweight (above the 85th percentile), or obese (above the 95th percentile). These criteria were previously validated in Swiss children at this age (42). Percentage body fat (%BF) was calculated by using the equation of Lohman (43). Fat-free body mass (FFB) was determined as follows:

For boys:

Formula 1(1)

For girls:

Formula 2(2)

Formula 3(3)

Laboratory analysis
The blood samples were centrifuged for 15 min at 1000 x g (2500 rpm). Glucose was measured immediately on EDTA-plasma with the use of reflection photometry (Reflotron Sprint, Roche, Rotkreuz, Switzerland). HDL-cholesterol and triacylglycerol concentrations were measured in fresh serum with a Hitachi 917 (TriglycerideGPO-PAP and HDL cholesterol plus 2nd generation; Roche). Serum was stored at –20 °C for later measurement of insulin by radioimmunoassay (Schering AG, Baar, Switzerland), IL-6 by high-sensitivity enzyme-linked immunosorbent assay (Quantikine HS Human IL-6 Immunoassay; R&D Systems, Minneapolis, MN), leptin by enzyme-linked immunosorbent assay (BioVender; Alexis Biochemicals, Lausen, Switzerland), and high-sensitivity CRP and TNF-{alpha} by chemiluminescent immunometry (IMMULITE; Bühlmann Laboratories AG, Allschwil, Switzerland). The quantitative insulin sensitivity check index (QUICKI), was calculated as follows (44):

Formula 4(4)

Statistical analysis
Statistical analysis was performed with the statistical package SPSS 13.0 for WINDOWS (SPSS Inc, Chicago, IL). Non-normally distributed variables were log transformed for comparisons. One-way analysis of variance (ANOVA) with a post hoc Bonferroni test was used to compare means. To investigate relations between dietary factors and BMI, Pearson's correlation coefficients were calculated. Multiple regression and analysis of covariance (ANCOVA) were used to study the effect of nutrients and metabolic and personal covariates on metabolic variables. All equations were checked for confounding by BMI, age, pubertal stage, sex, and their quadratic polynomials; they were added as covariates if they were significant predictors and were specified in the data presentation.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
Anthropometric and metabolic data of the children, by weight classification, are shown in Table 1Go. %BF, waist-hip ratio, fasting insulin, insulin resistance as defined by QUICKI, triacylglycerols, and systolic blood pressure increased significantly with increasing adiposity (P < 0.01), whereas HDL-cholesterol concentrations were lower with increasing adiposity (P < 0.01). Increasing adiposity was associated with significantly higher circulating concentrations of CRP (P < 0.02), IL-6 (P < 0.02), and leptin (P < 0.01) but not of TNF-{alpha}.


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  		TABLE 1. Anthropometric and metabolic data for 6- to 14-y-old Swiss children by weight classification1

 
Daily intakes of energy, total fat, types of fat, protein, and antioxidant vitamins, by weight classification, are shown in Table 2Go. The only significant differences were in intakes of meat and protein (P < 0.05) between normal-weight and obese children and in percentages of energy as protein (P < 0.05) between normal-weight and overweight and between normal-weight and obese children; intakes increased with increasing adiposity. To further investigate the relation between dietary factors and BMI as continuous variables, the following correlations were calculated: energy intake (r = 0.053, P = 0.644), fat intake (r = –0.036, P = 0.750), saturated fatty acid intake (r = –0.089, P = 0.435), polyunsaturated fatty acid intake (r = 0.061, P = 0.593), monounsaturated fatty acid intake (r = –0.025, P = 0.825), protein intake (r = 0.326, P = 0.003), and meat intake (r = 0.388, P < 0.001). Again, the only dietary factors significantly correlated with BMI-SDS were protein and meat intakes.


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  		TABLE 2. Nutritional intakes of 6- to 14-y-old Swiss children by weight classification1

 
The results of the univariate regressions of CRP, IL-6, TNF-{alpha}, and leptin as dependent variables on BMI, %BF, waist-hip ratio, age, and sex as predictors are shown in Table 3Go. BMI, %BF, and waist-hip ratio were significant predictors of circulating CRP, IL-6, and leptin but not of TNF-{alpha}. Sex was not a significant predictor, with the exception of leptin, for which values were significantly higher in girls (P < 0.01). Age was a significant predictor of TNF-{alpha} (P < 0.01), but not of the other inflammatory markers.


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  		TABLE 3. Associations of C-reactive protein (CRP), interleukin 6 (IL-6), tumor necrosis factor {alpha} (TNF-{alpha}), and leptin with BMI, percentage body fat (%BF), waist-hip ratio, age, and sex in 6- to 14-y-old Swiss children in univariate regression models1

 
Associations of the 4 inflammatory markers with individual components of the metabolic syndrome, in univariate regressions and after control for BMI-SDS, are shown in Table 4Go. For CRP, IL-6, and TNF-{alpha}, no significant associations with components of the metabolic syndrome remained after control for BMI-SDS. In contrast, associations of leptin with fasting insulin, QUICKI, systolic blood pressure, and triacylglycerols remained significant after control for adiposity.


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  		TABLE 4. Associations of inflammatory markers with individual components of the metabolic syndrome in 6- to 14-y-old Swiss children in multivariate regression models1

 
Regressions of dietary factors on CRP, IL-6, and leptin, after control for BMI-SDS and age, are shown in Table 5Go. Total fat intake, percentage of energy as fat, plant oils, saturated fatty acid, polyunsaturated fatty acid, and monounsaturated fatty acid were all significant predictors of CRP. Vitamin C, vitamin E, and ß-carotene intakes were significant negative predictors of leptin concentrations (P = 0.05), and meat intake was a significant predictor of IL-6 (P = 0.032). None of the dietary factors shown in Table 5Go were significant predictors of TNF-{alpha} after adjustment for BMI-SDS and age (data not shown).


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  		TABLE 5. Associations of nutritional factors with C-reactive protein (CRP), interleukin 6 (IL-6), and leptin concentrations in 6- to 14-y-old Swiss children in multivariate regression models1

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
In Swiss children as young as 6 y, measures of adiposity (BMI, %BF, and waist-hip ratio) were significant predictors of 3 inflammatory markers: IL-6, CRP, and leptin. Although data from younger children is scarce, and most studies measured only CRP (12, 13, 15, 16), our findings are consistent with previous studies, which showed increased subclinical inflammation in obese prepubertal children (3). In our sample, no association of serum TNF-{alpha} with adiposity was observed. Some studies have found elevated circulating TNF-{alpha} concentrations in obese children (45, 46), whereas others have not (47). It appears that TNF-{alpha} acts primarily via its transmembrane form in an autocrine-paracrine fashion in adipocytes (6, 48, 49). Thus, although TNF-{alpha} expression is increased in adipose tissue, circulating TNF-{alpha} concentrations in obese animals and humans are often not detectable or only mildly elevated (49).

Although dietary studies in obese children have focused mainly on the metabolic syndrome and dyslipidemia (50, 51), diet may also modulate the association between adiposity and subclinical inflammation (22, 24, 25). Differences in total fat intake and specific fatty acids can modulate the inflammatory response (22, 23). High concentrations of plasma free fatty acids (FFAs)—due to high fat intakes, increased lipolysis, or both—are found in overweight adults with the metabolic syndrome (52). High concentrations of FFAs, especially saturated fatty acids, impair glucose and lipid metabolism (52) and induce expression of proinflammatory cytokines in adipocytes (53), but this may not be a generalized effect of all saturated fatty acids. Palmitate, but not laurate or docosahexaenoic acid, induces IL-6 in adipocytes (53), skeletal muscle cells (54), and endothelial cells (55). Palmitate, but not other plasma FFAs, correlates in vivo with IL-6 concentrations, independent of body fat mass (55). Conjugated linoleic acid (18:2; with a conjugated double bond) may also increase production of IL-6 and other proinflammatory cytokines in adipose tissue (56). In contrast, n–3 polyunsaturated fatty acids may ameliorate the inflammatory response (57, 58). Supplementation with n–3 polyunsaturated fatty acids modified phospholipid fatty acid composition and decreased production of TNF-{alpha} and IL-6 by monocytes (59), when compared with palmitic acid (60). Diets high in {alpha}-linolenic acid (ALA,18:3n-3) tend to reduce inflammation (61-63). In dyslipidemic adults, daily supplementation with ALA for 3 mo decreased concentrations of CRP and IL-6 by 38% and 11%, respectively (64).

Overweight adolescents with elevated CRP and IL-6 concentrations have higher plasma saturated fatty acid and lower n–3 polyunsaturated fatty acid concentrations than do normal-weight control subjects (31). It has been suggested that high dietary intakes of saturated fatty acids may stimulate IL-6 secretion, and, conversely, high intakes of n–3 polyunsaturated fatty acids may inhibit low-grade inflammation (31, 65). However, in our study, total fat intake and percentage of energy from fat—and not specific types of dietary fat—predicted subclinical inflammation, independent of BMI. Also, intake of food groups high in saturated fats, such as meat and milk products, did not predict subclinical inflammation after control for adiposity, with the exception of a significant association between meat intake and IL-6 and leptin. In adults, a diet pattern high in processed meats correlated with inflammatory markers, including IL-6 (66).

Oxidative stress may play a central role in the pathogenesis of various disease states, including diabetes and insulin resistance (21, 67). Obesity per se may induce systemic oxidative stress (20), which may contribute to the dysregulation of adipocytokines and to the development of the metabolic syndrome (68, 69). In obese adults, subclinical inflammation correlates with markers of oxidative stress (18), and CRP concentrations predict 8-iso- PGF2{alpha} excretion independently of insulin and leptin concentrations (19). Obesity in adults may be associated with lower concentrations of {alpha}-tocopherol and ß-carotene (18, 70).

Decreased antioxidant vitamin concentrations and reduced antioxidant capacity also appear to be characteristic of obese children (33, 34, 36). In prepubertal obese children, vitamin E concentrations are significantly lower and malondialdehyde concentrations are significantly higher than those of normal-weight children, and these abnormalities are improved by a dietary restriction weight-loss program (35). In 6–19-y-old children in the second National Health and Nutrition Examination Survey (NHANES III), obese children had low serum concentrations of {alpha}-tocopherol and ß-carotene (37). However, in NHANES III, no significant differences in intakes of ß-carotene, {alpha}-tocopherol, fruit, or vegetables were observed between obese and nonobese children, as assessed by 24-h dietary recall and food-frequency questionnaires (37). Similarly, we found that adiposity did not predict antioxidant vitamin intakes. Intakes of vitamin C, vitamin E, and ß-carotene did not predict subclinical inflammation, as measured by IL-6 and CRP, but did predict leptin.

CRP is significantly associated with adiposity and components of the metabolic syndrome in adults (16, 71-74). CRP also is a predictor of insulin resistance in adults (16, 71-74), but the relation is variably attenuated after adjustment for adiposity (71, 72). In children, data are more limited, but CRP has also been correlated with components of the metabolic syndrome (12-17). However, studies suggest that increases in CRP, independent of adiposity, are associated with dyslipidemia but are not strongly associated with other components of the metabolic syndrome in children. Similarly, in our study, univariate analyses found correlations between IL-6, CRP, leptin, and several components of the metabolic syndrome (Table 4Go). However, after control for BMI, the associations with CRP and IL-6 were no longer significant. In contrast, leptin remained a significant predictor of fasting insulin, QUICKI, systolic blood pressure, and triacylglycerols, even after control for BMI.

In adults, stronger associations between adiposity and CRP have been reported for women than for with men (75, 76). In children, the data are unclear. In Quebec, CRP concentrations were higher in 9- and 16-y-old girls than in boys of the same age (15). In UK children aged 9–11 y, CRP concentrations were 47% higher in girls than in boys (13). In adolescents in the 1999–2000 US NHANES (14), females had higher CRP concentrations than did males only at 16–19 y of age. In contrast, CRP concentrations were similar by sex in a study in children in Taipei (17). In our sample, no significant age or sex effect on IL-6 or CRP was observed, whereas female sex was a significant predictor of leptin concentrations.

Dietary assessment is challenging, particularly in children. Children's abilities to record or remember their diet, as well as their knowledge of food and food preparation, is limited (77, 78). Different assessment tools have strengths and weaknesses. A dietary record, considered the "gold standard," provides an accurate quantitative account of a person's diet, but it is demanding and time consuming and requires motivated and literate subjects. In contrast, a 24-h dietary recall provides only a snapshot of a person's diet on the day before the interview, but it requires less motivation to perform and the subject does not have to be literate. Because of the wide variation in daily diets, a single day assessment by a 24-h dietary recall is unlikely to yield an accurate picture of a subject's diet (78-80). Lytle et al (38) validated a 24-h dietary recall in children, supplemented with food records done by the children's parents. Because this combination of interviewing both children and their parents showed good results, and because 24-h dietary recalls and a diet record are complementary (38), we chose to combine two 24-h dietary recalls with a 1-d dietary record in the present study. This method aimed to minimize time demands on the children and their families while trying to ensure an accurate overview of their diet.

This study had several limitations. Because it was cross-sectional, the directionality of the reported associations cannot be established. The use of a single fasting measurement of CRP, IL-6, TNF-{alpha}, or leptin may not necessarily reflect chronic inflammatory status; the biological variability of CRP in adults has been estimated at 22% (81). Finally, the sample size may have been insufficient to detect weak associations. However, studies of the early mechanisms of subclinical inflammation in young children are valuable because they are not confounded by chronic inflammatory conditions, atheromatous disease, smoking, or alcohol consumption.


   ACKNOWLEDGMENTS
 
We thank the participating children and their families. Special thanks go to MT Achermann and S Jacob (University Hospital Zurich); RF Hurrell, K Hotz, and C Zeder (ETH Zurich); I Hutter (Children's Hospital, St Gallen); and the staff of the Children's Hospitals in Biel and Basel.

IA, MBZ, GS, and DA performed the fieldwork and the data collection. IA, MBZ, and GS supervised the laboratory analysis and completed the data analysis. IA, MBZ, and LM conducted the statistical analysis. IA and MBZ wrote the first draft of the manuscript. All authors contributed to the study design and edited the manuscript. None of the authors had a financial or personal conflict of interest in regard to this study.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

  1. Hedley AA, Ogden CL, Johnson CL, Carroll MD, Curtin LR, Flegal KM. Prevalence of overweight and obesity among US children, adolescents, and adults, 1999–2002. JAMA 2004;291:2847–50.[Abstract/Free Full Text]
  2. Seidell JC. Obesity: a growing problem. Acta Paediatr Suppl 1999;88:46–50.[Medline]
  3. Weiss R, Caprio S. The metabolic consequences of childhood obesity. Best Pract Res Clin Endocrinol Metab 2005;19:405–19.[Medline]
  4. Dietz WH. Health consequences of obesity in youth: childhood predictors of adult disease. Pediatrics 1998;101:518–25.[Abstract/Free Full Text]
  5. Rosenbloom AL, Joe JR, Young RS, Winter WE. Emerging epidemic of type 2 diabetes in youth. Diabetes Care 1999;22:345–54.[Abstract/Free Full Text]
  6. Mohamed-Ali V, Goodrick S, Rawesh A, et al. Subcutaneous adipose tissue releases interleukin-6, but not tumor necrosis factor-alpha, in vivo. J Clin Endocrinol Metab 1997;82:4196–200.[Abstract/Free Full Text]
  7. Wellen KE, Hotamisligil GS. Obesity-induced inflammatory changes in adipose tissue. J Clin Invest 2003;112:1785–8.[Medline]
  8. Canavan B, Salem RO, Schurgin S, et al. Effects of physiologic leptin administration on markers of inflammation, platelet activation, and platelet aggregation during caloric deprivation. J Clin Endocrinol Metab 2005;90:5779–85.[Abstract/Free Full Text]
  9. Pearson TA, Mensah GA, Alexander RW, et al. Markers of inflammation and cardiovascular disease: application to clinical and public health practice: a statement for healthcare professionals from the Centers for Disease Control and Prevention and the American Heart Association. Circulation 2003;107:499–511.[Free Full Text]
  10. Plutzky J. Inflammation in atherosclerosis and diabetes mellitus. Rev Endocr Metab Disord 2004;5:255–9.[Medline]
  11. Pradhan AD, Manson JE, Rifai N, Buring JE, Ridker PM. C-reactive protein, interleukin 6, and risk of developing type 2 diabetes mellitus. JAMA 2001;286:327–34.[Abstract/Free Full Text]
  12. Weiss R, Dziura J, Burgert TS, et al. Obesity and the metabolic syndrome in children and adolescents. N Engl J Med 2004;350:2362–74.[Abstract/Free Full Text]
  13. Cook DG, Mendall MA, Whincup PH, et al. C-reactive protein concentration in children: relationship to adiposity and other cardiovascular risk factors. Atherosclerosis 2000;149:139–50.[Medline]
  14. Ford ES. C-reactive protein concentration and cardiovascular disease risk factors in children: findings from the National Health and Nutrition Examination Survey 1999–2000. Circulation 2003;108:1053–8.[Abstract/Free Full Text]
  15. Lambert M, Delvin EE, Paradis G, O'Loughlin J, Hanley JA, Levy E. C-reactive protein and features of the metabolic syndrome in a population-based sample of children and adolescents. Clin Chem 2004;50:1762–8.[Abstract/Free Full Text]
  16. Visser M, Bouter LM, McQuillan GM, Wener MH, Harris TB. Low-grade inflammation in overweight children. Pediatrics 2001;107:E13–8.
  17. Wu DM, Chu NF, Shen MH, Chang JB. Plasma C-reactive protein levels and their relationship to anthropometric and lipid characteristics among children. J Clin Epidemiol 2003;56:94–100.[Medline]
  18. Helmersson J, Vessby B, Larsson A, Basu S. Association of type 2 diabetes with cyclooxygenase-mediated inflammation and oxidative stress in an elderly population. Circulation 2004;109:1729–34.[Abstract/Free Full Text]
  19. Davi G, Guagnano MT, Ciabattoni G, et al. Platelet activation in obese women: role of inflammation and oxidant stress. JAMA 2002;288:2008–14.[Abstract/Free Full Text]
  20. Furukawa S, Fujita T, Shimabukuro M, et al. Increased oxidative stress in obesity and its impact on metabolic syndrome. J Clin Invest 2004;114:1752–61.[Medline]
  21. Urakawa H, Katsuki A, Sumida Y, et al. Oxidative stress is associated with adiposity and insulin resistance in men. J Clin Endocrinol Metab 2003;88:4673–6.[Abstract/Free Full Text]
  22. Bray GA, Lovejoy JC, Smith SR, et al. The influence of different fats and fatty acids on obesity, insulin resistance and inflammation. J Nutr 2002;132:2488–91.[Abstract/Free Full Text]
  23. Kelley DS. Modulation of human immune and inflammatory responses by dietary fatty acids. Nutrition 2001;17:669–73.[Medline]
  24. Cunningham-Rundles S, McNeeley DF, Moon A. Mechanisms of nutrient modulation of the immune response. J Allergy Clin Immunol 2005;115:1119–28.[Medline]
  25. Browning LM, Jebb SA. Nutritional influences on inflammation and type 2 diabetes risk. Diabetes Technol Ther 2006;8:45–54.[Medline]
  26. Ma J, Folsom AR, Shahar E, Eckfeldt JH. Plasma fatty acid composition as an indicator of habitual dietary fat intake in middle-aged adults. The Atherosclerosis Risk in Communities (ARIC) Study Investigators. Am J Clin Nutr 1995;62:564–71.[Abstract/Free Full Text]
  27. Salo P, Viikari J, Hamalainen M, et al. Fatty acid composition of serum cholesterol esters as a reflector of low-saturated-fat, low-cholesterol diet in young children: the STRIP project. The Special Turku Coronary Risk Factor Intervention Project. Acta Paediatr 2000;89:399–405.[Medline]
  28. Fernandez-Real JM, Broch M, Vendrell J, Ricart W. Insulin resistance, inflammation, and serum fatty acid composition. Diabetes Care 2003;26:1362–8.[Abstract/Free Full Text]
  29. Lee TH, Hoover RL, Williams JD, et al. Effect of dietary enrichment with eicosapentaenoic and docosahexaenoic acids on in vitro neutrophil and monocyte leukotriene generation and neutrophil function. N Engl J Med 1985;312:1217–24.[Abstract]
  30. Burr ML, Fehily AM, Gilbert JF, et al. Effects of changes in fat, fish, and fibre intakes on death and myocardial reinfarction: Diet and Reinfarction Trial (DART). Lancet 1989;2:757–61.[Medline]
  31. Klein-Platat C, Drai J, Oujaa M, Schlienger JL, Simon C. Plasma fatty acid composition is associated with the metabolic syndrome and low-grade inflammation in overweight adolescents. Am J Clin Nutr 2005;82:1178–84.[Abstract/Free Full Text]
  32. Hartel C, Strunk T, Bucsky P, Schultz C. Effects of vitamin C on intracytoplasmic cytokine production in human whole blood monocytes and lymphocytes. Cytokine 2004;27:101–6.[Medline]
  33. Decsi T, Molnar D, Koletzko B. Lipid corrected plasma alpha-tocopherol values are inversely related to fasting insulinaemia in obese children. Int J Obes Relat Metab Disord 1996;20:970–2.[Medline]
  34. Kuno T, Hozumi M, Morinobu T, Murata T, Mingci Z, Tamai H. Antioxidant vitamin levels in plasma and low density lipoprotein of obese girls. Free Radic Res 1998;28:81–6.[Medline]
  35. Mohn A, Catino M, Capanna R, Giannini C, Marcovecchio M, Chiarelli F. Increased oxidative stress in prepubertal severely obese children: effect of a dietary restriction-weight loss program. J Clin Endocrinol Metab 2005;90:2653–8.[Abstract/Free Full Text]
  36. Molnar D, Decsi T, Koletzko B. Reduced antioxidant status in obese children with multimetabolic syndrome. Int J Obes Relat Metab Disord 2004;28:1197–202.[Medline]
  37. Strauss RS. Comparison of serum concentrations of alpha-tocopherol and beta-carotene in a cross-sectional sample of obese and nonobese children (NHANES III). National Health and Nutrition Examination Survey. J Pediatr 1999;134:160–5.[Medline]
  38. Lytle LA, Nichaman MZ, Obarzanek E, et al. Validation of 24-hour recalls assisted by food records in third-grade children. The CATCH Collaborative Group. J Am Diet Assoc 1993;93:1431–6.[Medline]
  39. Infanger E. Schweizer Nährwerttabelle. (Swiss nutrient database.) Bern, Switzerland: Swiss Nutrition Society, Federal Office of PublicHealth, Swiss Federal Institute of Technology, 2005.
  40. D-A-CH. Referenzwerte für die Nährstoffzufuhr. (Reference values for nutrient intake.) Frankfurt am Main, Germany: Umschau/Braus, 2000 (in German).
  41. Ogden CL, Kuczmarski RJ, Flegal KM, et al. Centers for Disease Control and Prevention 2000 growth charts for the United States: improvements to the 1977 National Center for Health Statistics version. Pediatrics 2002;109:45–60.[Abstract/Free Full Text]
  42. Zimmermann MB, Gubeli C, Puntener C, Molinari L. Detection of overweight and obesity in a national sample of 6–12-y-old Swiss children: accuracy and validity of reference values for body mass index from the US Centers for Disease Control and Prevention and the International Obesity Task Force. Am J Clin Nutr 2004;79:838–43.[Abstract/Free Full Text]
  43. Lohman T. Advances in body composition assessment. Champaign, IL: Human Kinetics Publishers, 1992.
  44. Katz A, Nambi SS, Mather K, et al. Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans. J Clin Endocrinol Metab 2000;85:2402–10.[Abstract/Free Full Text]
  45. Halle M, Korsten-Reck U, Wolfarth B, Berg A. Low-grade systemic inflammation in overweight children: impact of physical fitness. Exerc Immunol Rev 2004;10:66–74.[Medline]
  46. Reinehr T, Stoffel-Wagner B, Roth CL, Andler W. High-sensitive C-reactive protein, tumor necrosis factor alpha, and cardiovascular risk factors before and after weight loss in obese children. Metabolism 2005;54:1155–61.[Medline]
  47. Gupta A, Ten S, Anhalt H. Serum levels of soluble tumor necrosis factor-alpha receptor 2 are linked to insulin resistance and glucose intolerance in children. J Pediatr Endocrinol Metab 2005;18:75–82.[Medline]
  48. Kern PA, Ranganathan S, Li C, Wood L, Ranganathan G. Adipose tissue tumor necrosis factor and interleukin-6 expression in human obesity and insulin resistance. Am J Physiol Endocrinol Metab 2001;280:E745–51.[Abstract/Free Full Text]
  49. Xu H, Uysal KT, Becherer JD, Arner P, Hotamisligil GS. Altered tumor necrosis factor-alpha (TNF-alpha) processing in adipocytes and increased expression of transmembrane TNF-alpha in obesity. Diabetes 2002;51:1876–83.[Abstract/Free Full Text]
  50. Gidding SS, Dennison BA, Birch LL, et al. Dietary recommendations for children and adolescents: a guide for practitioners: consensus statement from the American Heart Association. Circulation 2005;112:2061–75.[Abstract/Free Full Text]
  51. Steinbeck K. Childhood obesity. Treatment options. Best Pract Res Clin Endocrinol Metab 2005;19:455–69.[Medline]
  52. McGarry JD. Banting lecture 2001: dysregulation of fatty acid metabolism in the etiology of type 2 diabetes. Diabetes 2002;51:7–18.[Free Full Text]
  53. Ajuwon KM, Spurlock ME. Palmitate activates the NF-kappaB transcription factor and induces IL-6 and TNFalpha expression in 3T3–L1 adipocytes. J Nutr 2005;135:1841–6.[Abstract/Free Full Text]
  54. Jove M, Planavila A, Laguna JC, Vazquez-Carrera M. Palmitate-induced interleukin 6 production is mediated by protein kinase C and nuclear-factor kappaB activation and leads to glucose transporter 4 down-regulation in skeletal muscle cells. Endocrinology 2005;146:3087–95.[Abstract/Free Full Text]
  55. Staiger H, Staiger K, Stefan N, et al. Palmitate-induced interleukin-6 expression in human coronary artery endothelial cells. Diabetes 2004;53:3209–16.[Abstract/Free Full Text]
  56. Chung S, Brown JM, Provo JN, Hopkins R, McIntosh MK. Conjugated linoleic acid promotes human adipocyte insulin resistance through NFkappaB-dependent cytokine production. J Biol Chem 2005;280:38445–56.[Abstract/Free Full Text]
  57. Endres S, Ghorbani R, Kelley VE, et al. The effect of dietary supplementation with n–3 polyunsaturated fatty acids on the synthesis of interleukin-1 and tumor necrosis factor by mononuclear cells. N Engl J Med 1989;320:265–71.[Abstract]
  58. Kremer JM, Lawrence DA, Jubiz W, et al. Dietary fish oil and olive oil supplementation in patients with rheumatoid arthritis. Clinical and immunologic effects. Arthritis Rheum 1990;33:810–20.[Medline]
  59. Trebble T, Arden NK, Stroud MA, et al. Inhibition of tumour necrosis factor- and interleukin 6 production by mononuclear cells following dietary fish-oil supplementation in healthy men and response to antioxidant co-supplementation Br J Nutr 2003;90:405–12.[Medline]
  60. Zhao G, Etherton TD, Martin KR, et al. Anti-inflammatory effects of polyunsaturated fatty acids in THP-1 cells. Biochem Biophys Res Commun 2005;336:909–17.[Medline]
  61. Bemelmans WJ, Lefrandt JD, Feskens EJ, et al. Increased alpha-linolenic acid intake lowers C-reactive protein, but has no effect on markers of atherosclerosis. Eur J Clin Nutr 2004;58:1083–9.[Medline]
  62. Mantzioris E, Cleland LG, Gibson RA, Neumann MA, Demasi M, James MJ. Biochemical effects of a diet containing foods enriched with n–3 fatty acids. Am J Clin Nutr 2000;72:42–8.[Abstract/Free Full Text]
  63. Zhao G, Etherton TD, Martin KR, West SG, Gillies PJ, Kris-Etherton PM. Dietary alpha-linolenic acid reduces inflammatory and lipid cardiovascular risk factors in hypercholesterolemic men and women. J Nutr 2004;134:2991–7.[Abstract/Free Full Text]
  64. Rallidis LS, Paschos G, Liakos GK, Velissaridou AH, Anastasiadis G, Zampelas A. Dietary alpha-linolenic acid decreases C-reactive protein, serum amyloid A and interleukin-6 in dyslipidaemic patients. Atherosclerosis 2003;167:237–42.[Medline]
  65. Phinney SD. Fatty acids, inflammation, and the metabolic syndrome. Am J Clin Nutr 2005;82:1151–2.[Free Full Text]
  66. Schulze MB, Hoffmann K, Manson JE, et al. Dietary pattern, inflammation, and incidence of type 2 diabetes in women. Am J Clin Nutr 2005;82:675–84(quiz 714–5).[Abstract/Free Full Text]
  67. Brownlee M. Biochemistry and molecular cell biology of diabetic complications. Nature 2001;414:813–20.[Medline]
  68. Keaney JF Jr, Larson MG, Vasan RS, et al. Obesity and systemic oxidative stress: clinical correlates of oxidative stress in the Framingham Study. Arterioscler Thromb Vasc Biol 2003;23:434–9.[Abstract/Free Full Text]
  69. Olusi SO. Obesity is an independent risk factor for plasma lipid peroxidation and depletion of erythrocyte cytoprotective enzymes in humans. Int J Obes Relat Metab Disord 2002;26:1159–64.[Medline]
  70. Vogel S, Contois JH, Tucker KL, Wilson PW, Schaefer EJ, Lammi-Keefe CJ. Plasma retinol and plasma and lipoprotein tocopherol and carotenoid concentrations in healthy elderly participants of the Framingham Heart Study. Am J Clin Nutr 1997;66:950–8.[Abstract/Free Full Text]
  71. 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;102:42–7.[Abstract/Free Full Text]
  72. Lemieux I, Pascot A, Prud'homme D, et al. Elevated C-reactive protein: another component of the atherothrombotic profile of abdominal obesity. Arterioscler Thromb Vasc Biol 2001;21:961–7.[Abstract/Free Full Text]
  73. Pradhan AD, Cook NR, Buring JE, Manson JE, Ridker PM. C-reactive protein is independently associated with fasting insulin in nondiabetic women. Arterioscler Thromb Vasc Biol 2003;23:650–5.[Abstract/Free Full Text]
  74. Yudkin JS, Stehouwer CD, Emeis JJ, Coppack SW. C-reactive protein in healthy subjects: associations with obesity, insulin resistance, and endothelial dysfunction: a potential role for cytokines originating from adipose tissue? Arterioscler Thromb Vasc Biol 1999;19:972–8.[Abstract/Free Full Text]
  75. Festa A, D'Agostino R Jr, Williams K, et al. The relation of body fat mass and distribution to markers of chronic inflammation. Int J Obes Relat Metab Disord 2001;25:1407–15.[Medline]
  76. Visser M, Bouter LM, McQuillan GM, Wener MH, Harris TB. Oxidative stress is associated with adiposity and insulin resistance in men. J Clin Endocrinol Metab 1999;88:4673–6.
  77. Baranowski T, Domel SB. A cognitive model of children's reporting of food intake. Am J Clin Nutr 1994;59(suppl):212S–7S.[Abstract/Free Full Text]
  78. Rockett HR, Colditz GA. Assessing diets of children and adolescents. Am J Clin Nutr 1997;65(suppl):1116S–22S.[Abstract/Free Full Text]
  79. Biro G, Hulshof KF, Ovesen L, Amorim Cruz JA. Selection of methodology to assess food intake. Eur J Clin Nutr 2002;56(suppl):S25–32.
  80. Crawford PB, Obarzanek E, Morrison J, Sabry ZI. Comparative advantage of 3-day food records over 24-hour recall and 5-day food frequency validated by observation of 9- and 10-year-old girls. J Am Diet Assoc 1994;94:626–30.[Medline]
  81. Ockene IS, Matthews CE, Rifai N, Ridker PM, Reed G, Stanek E. Variability and classification accuracy of serial high-sensitivity C-reactive protein measurements in healthy adults. Clin Chem 2001;47:444–50.[Abstract/Free Full Text]
Received for publication April 5, 2006. Accepted for publication June 9, 2006.




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