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. Author manuscript; available in PMC: 2020 Apr 1.
Published in final edited form as: Nutr Metab Cardiovasc Dis. 2019 Feb 2;29(4):378–382. doi: 10.1016/j.numecd.2019.01.013

Racial Differences in Myocardial Deformation in Obese Children: Significance of Inflammatory State

TJ Popp 1, MH Henshaw 1, J Carter 1, TN Thomas 1, SM Chowdhury 1
PMCID: PMC6492271  NIHMSID: NIHMS1523302  PMID: 30850223

Abstract

Background and Aims

The association between racial differences in myocardial deformation and cardiometabolic risk factors is unknown in obese children. Our objective was to: 1) investigate for racial differences in myocardial deformation between white and black obese children and 2) identify biomarkers associated with these observed racial differences. We hypothesized that decreased myocardial deformation observed in black obese children could be accounted for by the differences in the markers of metabolic syndrome between the groups.

Methods and Results

Obese children were recruited prospectively. All clinical and laboratory tests for the metabolic syndrome were conducted during a single assessment using a standardized protocol. Speckle-tracking echocardiography was performed to obtain longitudinal and circumferential measures of deformation. 310 patients were included in the analysis; 158 (51%) white and 152 (49%) black. The median age was 11.3 years (IQR 5.9). Blacks demonstrated worse longitudinal strain (−14.7 ± 2.7% vs. −15.4 ± 2.9%, p = 0.04). There was no difference in circumferential strain between the groups. Multivariable linear regression showed a significant relationship between longitudinal strain and hsCRP (β = 0.16, p = 0.03) and HOMA-IR (β = 0.15, p = 0.04); there was no independent association between longitudinal strain and race.

Conclusion

Black subjects demonstrated worse longitudinal strain than whites. Only hsCRP and HOMA-IR levels, not race, had an independent association with longitudinal strain, suggesting that the observed racial differences in longitudinal strain may be secondary to differences in inflammation and insulin resistance between the groups.

Keywords: obesity, pediatrics, longitudinal strain, metabolic syndrome, race

Introduction

Cardiovascular disease outcomes are worse for black adults than white adults[14]. Obesity is one of the known major risk factors for cardiovascular disease [5] and is similarly more prevalent in black adults than white adults [6]. There is increasing evidence that childhood obesity is a risk factor for cardiovascular disease as an adult. However, specific modifiable risk factors in childhood that contribute to the racial differences seen in adults cardiovascular disease are not entirely clear. [7]

Racial differences in cardiovascular risk have been observed in the pediatric population. Black adolescents are more likely to be obese, hypertensive, and have higher carotid intima-media thickness (cIMT) and aortic stiffness than whites [811]. However, the effect of obesity and the consequences of the metabolic syndrome on cardiac function have been incompletely described in children. Moreover, evaluations for racial differences in cardiac function and the metabolic drivers that contribute to these differences have not been studied. The use of speckle-tracking echocardiography to evaluate pre-clinical evidence of cardiovascular dysfunction allows such investigations to now be performed in children.

Our objectives were to: 1) investigate for racial differences in myocardial deformation between white and black obese children and 2) identify biomarkers of the metabolic syndrome that are associated with these observed racial differences. We hypothesized that black children would have poorer myocardial deformation compared to whites and that markers of the metabolic syndrome would be associated with the racial differences observed.

Methods

This was a secondary analysis of a prospective single-institution cross-sectional study whose aim was to assess for racial differences in biomarkers of the metabolic syndrome. [10, 12, 13] Demographic, echocardiographic, and laboratory data was obtained at our institution from September 2009 through June 2015. This study was approved by the institutional review board of the Medical University of South Carolina. At the time of the original study, informed consent was obtained from patients ≥ 18 years old or from parents or legal guardians for patients < 18 years old with simultaneous assent obtained from the patient if they were ≥ 12 years old.

Patient Selection

All participants were recruited through our institution’s Heart Health program, a pediatric obesity management program. Subjects consisted of obese (body mass index [BMI] > 95th percentile) children and young adults aged 4 to 21 years and of non-Hispanic white or black race. Patients who were pregnant, insulin dependent, or taking chronic oral steroids (for a duration> two weeks) were excluded in this analysis.

Study procedures

All tests were conducted during a single outpatient visit using a standardized protocol. Study visits were rescheduled in case of fever within 72 hours of planned study date. Fasting status was confirmed prior to phlebotomy. Age, sex, race, height, weight, blood pressure (DINAMAP automatic cuff, GE Healthcare), fasting insulin, glucose, lipid panel, and high sensitivity c-reactive protein (hsCRP), and body composition by dual-energy x-ray absorptiometry (DXA) were obtained. Body mass index was calculated as weight (kg)/height (m)2. Insulin resistance was determined by calculating the homeostatic model assessment of insulin resistance (HOMA-IR): [glucose (mg/dL) × insulin (mIU/mL)]/405.

Echocardiographic Analysis

A single cardiac sonographer performed transthoracic echocardiography in accordance with the guidelines and standards for pediatric echocardiograms by the American Society of Echocardiography using a Philips iE33 ultrasound system (Andover, MA [14]). Echocardiograms were retrospectively obtained from the clinical server (Xcelera, Philips Medical Systems, Andover, Mass) and analyzed by a single blinded reviewer. Speckle-tracking echocardiography was performed using Cardiac Performance Analysis v. 3.0 (Tomtec, Munich, Germany) on DICOM images to obtain longitudinal and circumferential measures of deformation. All measurements were done on the left ventricle (LV). Longitudinal measurements were obtained by manually tracing the endocardium from the mitral valve annulus from the lateral side down to the apex and back to the septal side of the annulus in systole in a four chamber apical view. The area of interest was divided by the software into six segments that were then averaged to estimate the longitudinal strain (LS). A sample analysis of LV LS is shown in Figure 1. Similarly, the circumferential measurements were obtained by manually tracing the endocardium in a parasternal short axis view and then using the software to calculate the circumferential strain (CS). If two or more segments could not be tracked due to poor acoustic windows, the calculations for that patient were excluded from analysis. Only patients with less than two untrackable segments for LS were included in the analysis.

Figure 1: Assessment of longitudinal strain.

Figure 1:

Speckle-tracking analysis to determine longitudinal strain (bottom strain curves) using Cardiac Performance Analysis v. 3.0 (Tomtec Imaging Systems, Unterschleissheim, Germany).

Statistical Analysis

The Shapiro-Wilk test was utilized to determine whether data was parametric versus nonparametric. Independent t-tests were used for parametric data, and Mann-Whitney U tests were used for non-parametric data. Statistics are reported using mean and standard deviation for normally distributed data and median and interquartile range for non-normally distributed data. Pearson’s or Spearman’s correlation were performed as appropriate to determine univariable associations between strain measurements and independent variables which included age, sex, race, blood pressure, BMI Z-score, HOMA-IR, lipid results, and hsCRP. Stepwise multivariable linear regression was then performed to assess the relationship of myocardial measures of deformation to independent variables. Independent variables were initially considered for the regression model if p < 0.20 on univariable analysis (or if p < 0.20 when comparing strain between two categorical variables, like sex or race) and were included in the final model if p > 0.10 and inclusion increased the explanatory power of the model by 0.03. Intra- and inter-observer variability was assessed using intraclass correlation coefficients measuring absolute agreement to the mean. Statistics were performed using SPSS v24 (IBM Corp., Armonk, NY).

Results

Of 359 patients eligible for this study, 49 (14%) were excluded due to poor windows precluding speckle-tracking analysis of LS. A total of 310 obese pediatric patients were included in the analysis; 158 (51%) patients were white and 152 (49%) were black. Patient characteristics including demographic, anthropomorphic, laboratory, and echocardiographic data are detailed in Table 1. Black obese children demonstrated worse (less negative) longitudinal strain (−14.7 ± 2.7 vs. −15.4 ± 2.9, p = 0.04). There was no difference in circumferential measures of deformation between races. Males displayed worse strain compared to females (−14.5 ± 2.9% versus −15.4 ± 2.7%, p = 0.004). There was no difference in circumferential measures of deformation between sexes. Intra- and inter-observer variability were r = 0.90 and 0.79, respectively.

Table 1:

Patient Characteristics

White (n = 158) Black (n = 152) p-value
Age (years) 11.1 ± 13.7 11.7 ± 8.7 0.42
Female, n (%) 90 (57%) 84 (55%) 0.56
Height (cm) 153 ± 19 153 ± 16 0.89
Weight (kg) 71.5 ± 28.5 84.0 ± 33.0 < 0.01
BMI Z-score 1.7 ± 1.1 2.3 ± 0.5 < 0.01
SBP (mm Hg) 109 ± 14 112 ± 15 0.17
DBP (mm Hg) 63 ± 9 62 ± 9 0.90
% body fat 38.8 (9.0) 40.9 (7.2) 0.02
Insulin (gIU/mL) 25.0 (19.8) 31.1 (18.0) < 0.01
Glucose (mg/dL) 92 ± 11 93 ± 7 0.30
Cholesterol 166 ± 31 161 ± 27 0.15
HDL (mg/dL) 47 ± 12 45 ± 10 0.13
Triglycerides (mg/dL) 101 (70) 69 (35) < 0.01
LDL (mg/dL) 99 ± 27 102 ± 25 0.21
VLDL (mg/dL) 20 ± 12 14 ± 6 < 0.01
Cholesterol/HDL 3.5 (1.3) 3.6 (1.3) 0.50
Triglycerides/HDL 1.8 (1.9) 1.5 (1.0) <0.01
HOMA-IR 5.9 (4.4) 7.2 (4.8) <0.01
hsCRP (mg/dL) 0.27 (0.35) 0.50 (0.65) <0.01
LV LS (%) −15.4 ± 2.9 −14.7 ± 2.7 0.04
LV CS (%) −21.9 ± 4.2 −21.8 ± 4.1 0.89

Values reported as mean ± standard deviation or median (interquartile range). BMI = body mass index. CRP = c-reactive protein. CS = circumferential strain. DBP = diastolic blood pressure. HDL = high density lipoprotein. HOMA-IR = Homeostatic model assessment - insulin resistance. LDL = low density lipoprotein. LS = longitudinal strain. LV = left ventricle. SBP = systolic blood pressure. VLDL = very low density lipoprotein.

Univariable analysis

There was a statistically significant correlation between LV LS and BMI Z-score (r = 0.16, p = 0.008). The associations of LV LS and age (r = 0.08, p = 0.16), systolic blood pressure (r = 0.10, p = 0.16), hsCRP (r = 0.13, p = 0.06), and HOMA-IR (r = 0.12, p = 0.06) all approached statistical significance. Diastolic blood pressure, total cholesterol, triglycerides, HDL, LDL, VLDL, glucose level, total cholesterol:HDL, and triglycerides:HDL had no association with LV LS.

Multivariable analysis

Stepwise multivariable linear regression was performed to assess the relationship of longitudinal strain to age, sex, race, systolic blood pressure, BMI Z-score, HOMA-IR, and hsCRP. The only measures found to have a significant independent association with longitudinal strain were hsCRP (B = 0.94, SE = 0.42, β = 0.16, p = 0.03) and HOMA-IR (B = 0.08, SE = 0.04, β = 0.15, p = 0.04). Race and sex were not independently associated with longitudinal strain after hsCRP and HOMA-IR were accounted for.

Discussion

The main finding of this study is that black obese children had worse myocardial deformation measured by speckle-tracking echocardiography than white obese children. These differences were no longer significant when systemic inflammation and insulin resistance were accounted for. This suggests that the differences in myocardial deformation between white and black children may be driven by the differences in inflammation and insulin resistance between groups.

Speckle-tracking echocardiography has emerged as a tool to help identify early changes in myocardial function. An association between obesity and worse myocardial strain is well documented in children [1526]. However, to our knowledge, this is the first study to assess for potential racial differences in measures of myocardial deformation in children. Our findings are line with previous studies in adults. Kishi et al. performed a prospective study looking at sex and race differences in 3,499 American black and white adults. At 43 – 55 years of age, they found worse myocardial deformation in black males using speckle-tracking echocardiography [27]. Based on our findings, it appears these differences start early and can be detected in childhood.

The racial differences in inflammatory markers and insulin resistance between white and black obese patients are well known [28, 29]. The causes of these differences are currently being studied, with some groups positing that they may be secondary to differences in adipose tissue distribution (subcutaneous versus visceral) or genetic differences that cause inherent differences in beta cell function between races.[30, 31] The effect of these metabolic aberrations on myocardial contractility and stiffness are well studied.[32] Abnormal insulin resistance results in limited adaptive energy response when stress requires a change from free fatty acid metabolism to glucose oxidation. This results in increased oxygen consumption and decreased efficiency.[33] Chronic low-grade inflammation is known to be associated with increased afterload related to micro- and macro-vasculopathies.[34] These studies support the association found in this study between insulin resistance/inflammation and abnormal myocardial deformation.

Clinical Implications

An increasing body of evidence has demonstrated that elevated inflammatory markers and insulin resistance in obese individuals put them at an increased risk for cardiac events [3541]. Elevated CRP values in patients with atherosclerosis is associated with poor cardiovascular outcomes in adults [42]. Multiple studies have detected elevated CRP levels in obese children [2729, 31]. Our study found that these markers of the metabolic syndrome were associated with myocardial deformation. If future studies show that myocardial deformation in childhood is associated with cardiovascular outcomes in adulthood, speckle-tracking echocardiography may have the potential to be used as an imaging biomarker to detect children at risk for heart disease in adulthood.

Limitations

The primary limitation of our study lies in its nature as a retrospective review. While useful for identifying associations between the studied variables, a causative relationship cannot be ascertained. For example, though we found that racial differences in markers of the metabolic syndrome are associated with differences in myocardial deformation between the groups, we cannot determine if these findings are associated with the known differences in cardiovascular disease outcomes between white and black patients in adulthood. We also faced the challenge of the limited acoustic windows in obese children, which made measurements using speckle-tracking echocardiography more difficult and on occasion futile. The univariable and multivariable associations we found were weak. However, that is likely to be expected as the length of time our patients have been obese and the resultant metabolic derangements associated with obesity are low compared to adult studies.

Conclusion

Black obese pediatric subjects demonstrated worse longitudinal strain than whites. They were also found to have higher levels of systemic inflammation and insulin resistance than whites. Only hsCRP and HOMA-IR had an independent association with longitudinal strain; race did not. This suggests that the observed racial differences in longitudinal strain may be secondary to differences in inflammation between the two groups. Further investigations into the etiology of the effects on inflammation and insulin resistance on cardiac function in obese children are warranted. Future studies should assess whether decreased myocardial deformation in obese children is associated with worse cardiovascular outcomes in adulthood.

Highlights.

  • This study found that black obese children have worsened longitudinal strain than white obese children.

  • Black obese children were also found to have higher levels of systemic inflammation and insulin resistance than whites.

  • The observed racial differences in longitudinal strain in obese children may be secondary to differences in inflammation and insulin resistance between the two groups.

Acknowledgments

Funding Source: This project was supported by the South Carolina Clinical & Translational Research (SCTR) Institute, NIH/NCRR grants UL1 RR029882 and UL1 TR000062.

Abbreviations

BMI

body mass index

Cimt

carotid intima-media thickness

CS

circumferential strain

DXA

dual-energy x-ray absorptiometry

HOMA-IR

homeostatic model assessment of insulin resistance

hsCRP

high sensitivity c-reactive protein

LS

longitudinal strain

Footnotes

Potential Conflicts of Interest: The authors have no conflicts of interest relevant to this article to disclose

Financial Disclosure: The authors have no financial relationships relevant to this article to disclose

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Literature

  • 1.Li S, Fonarow GC, Mukamal KJ, Liang L, Schulte PJ, Smith EE, DeVore A, Hernandez AF, Peterson ED and Bhatt DL. Sex and Race/Ethnicity-Related Disparities in Care and Outcomes After Hospitalization for Coronary Artery Disease Among Older Adults. Circ Cardiovasc Qual Outcomes. 2016;9:S36–44. [DOI] [PubMed] [Google Scholar]
  • 2.Lu Y, Ezzati M, Rimm EB, Hajifathalian K, Ueda P and Danaei G. Sick Populations and Sick Subpopulations: Reducing Disparities in Cardiovascular Disease Between Blacks and Whites in the United States. Circulation. 2016;134:472–85. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Feinstein M, Ning H, Kang J, Bertoni A, Carnethon M and Lloyd-Jones DM. Racial differences in risks for first cardiovascular events and noncardiovascular death: the Atherosclerosis Risk in Communities study, the Cardiovascular Health Study, and the Multi-Ethnic Study of Atherosclerosis. Circulation. 2012;126:50–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Bibbins-Domingo K, Pletcher MJ, Lin F, Vittinghoff E, Gardin JM, Arynchyn A, Lewis CE, Williams OD and Hulley SB. Racial differences in incident heart failure among young adults. N Engl J Med. 2009;360:1179–90. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Ortega FB, Lavie CJ and Blair SN. Obesity and Cardiovascular Disease. Circ Res. 2016;118:1752–70. [DOI] [PubMed] [Google Scholar]
  • 6.Jackson CL, Szklo M, Yeh HC, Wang NY, Dray-Spira R, Thorpe R and Brancati FL. Black-white disparities in overweight and obesity trends by educational attainment in the United States, 1997–2008. J Obes. 2013;2013:140743. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Ajala O, Mold F, Boughton C, Cooke D and Whyte M. Childhood predictors of cardiovascular disease in adulthood. A systematic review and meta-analysis. Obes Rev. 2017;18:1061–1070. [DOI] [PubMed] [Google Scholar]
  • 8.Cheung EL, Bell CS, Samuel JP, Poffenbarger T, Redwine KM and Samuels JA. Race and Obesity in Adolescent Hypertension. Pediatrics. 2017;139. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Brady TM, Fivush B, Parekh RS and Flynn JT. Racial differences among children with primary hypertension. Pediatrics. 2010;126:931–7. [DOI] [PubMed] [Google Scholar]
  • 10.Chowdhury SM, Henshaw MH, Friedman B, Saul JP, Shirali GS, Carter J, Levitan BM and Hulsey T. Lean body mass may explain apparent racial differences in carotid intima-media thickness in obese children. J Am Soc Echocardiogr. 2014;27:561–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Lefferts WK, Augustine JA, Spartano NL, Atallah-Yunes NH, Heffernan KS and Gump BB. Racial Differences in Aortic Stiffness in Children. J Pediatr. 2017;180:62–67. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Jackson LB, Henshaw MH, Carter J and Chowdhury SM. Sex-specific lean body mass predictive equations are accurate in the obese paediatric population. Ann Hum Biol. 2015:1–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Palmieri VJ, Henshaw MH, Carter J and Chowdhury SM. Assessing truncal obesity in predicting cardiometabolic risk in children: clinical measures versus dual-energy X-ray absorptiometry. Acta Paediatr. 2018;107:1065–1069. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Lai WW, Geva T, Shirali GS, Frommelt PC, Humes RA, Brook MM, Pignatelli RH and Rychik J. Guidelines and standards for performance of a pediatric echocardiogram: a report from the Task Force of the Pediatric Council of the American Society of Echocardiography. J Am Soc Echocardiogr. 2006;19:1413–30. [DOI] [PubMed] [Google Scholar]
  • 15.Balderrabano N, Del Rio B, Navarrete E, Berber A and Mendez N. Evaluation of the left ventricle longitudinal deformity using myocardial-tracking signals in severely obese adolescents. Cardiol Young. 2016;26:749–53. [DOI] [PubMed] [Google Scholar]
  • 16.Barbosa JA, Mota CC, Simoes ESAC, Nunes Mdo C and Barbosa MM Assessing preclinical ventricular dysfunction in obese children and adolescents: the value of speckle tracking imaging. Eur Heart J Cardiovasc Imaging. 2013;14:882–9. [DOI] [PubMed] [Google Scholar]
  • 17.Binnetoglu FK, Yildirim S, Topaloglu N, Tekin M, Kaymaz N, Aylanc H and Karakurt H. Early detection of myocardial deformation by 2D speckle tracking echocardiography in normotensive obese children and adolescents. Anatol J Cardiol. 2015;15:151–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Colquitt JL and Pignatelli RH. Strain Imaging: The Emergence of Speckle Tracking Echocardiography into Clinical Pediatric Cardiology. Congenit Heart Dis. 2016;11:199–207. [DOI] [PubMed] [Google Scholar]
  • 19.Cote AT, Harris KC, Panagiotopoulos C, Sandor GG and Devlin AM. Childhood obesity and cardiovascular dysfunction. J Am Coll Cardiol. 2013;62:1309–19. [DOI] [PubMed] [Google Scholar]
  • 20.Kibar AE, Pac FA, Balli S, Oflaz MB, Ece I, Bas VN and Aycan Z. Early subclinical left-ventricular dysfunction in obese nonhypertensive children: a tissue Doppler imaging study. Pediatr Cardiol. 2013;34:1482–90. [DOI] [PubMed] [Google Scholar]
  • 21.Kibar AE, Pac FA, Ece I, Oflaz MB, Balli S, Bas VN and Aycan Z. Effect of obesity on left ventricular longitudinal myocardial strain by speckle tracking echocardiography in children and adolescents. Balkan Med J. 2015;32:56–63. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Koopman LP and Mertens LL. Impact of childhood obesity on cardiac structure and function. Curr Treat Options Cardiovasc Med. 2014;16:345. [DOI] [PubMed] [Google Scholar]
  • 23.Labombarda F, Zangl E, Dugue AE, Bougle D, Pellissier A, Ribault V, Maragnes P, Milliez P and Saloux E. Alterations of left ventricular myocardial strain in obese children. Eur Heart J Cardiovasc Imaging. 2013;14:668–76. [DOI] [PubMed] [Google Scholar]
  • 24.Mangner N, Scheuermann K, Winzer E, Wagner I, Hoellriegel R, Sandri M, Zimmer M, Mende M, Linke A, Kiess W, Schuler G, Korner A and Erbs S. Childhood obesity: impact on cardiac geometry and function. JACC Cardiovasc Imaging. 2014;7:1198–205. [DOI] [PubMed] [Google Scholar]
  • 25.Vitarelli A, Martino F, Capotosto L, Martino E, Colantoni C, Ashurov R, Ricci S, Conde Y, Maramao F, Vitarelli M, De Chiara S and Zanoni C. Early myocardial deformation changes in hypercholesterolemic and obese children and adolescents: a 2D and 3D speckle tracking echocardiography study. Medicine (Baltimore). 2014;93:e71. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Xie L, Man E, Cheung PT and Cheung YF. Myocardial Integrated Backscatter in Obese Adolescents: Associations with Measures of Adiposity and Left Ventricular Deformation. PLoS One. 2015;10:e0141149. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Kishi S, Reis JP, Venkatesh BA, Gidding SS, Armstrong AC, Jacobs DR Jr., Sidney S, Wu CO, Cook NL, Lewis CE, Schreiner PJ, Isogawa A, Liu K and Lima JA. Race-ethnic and sex differences in left ventricular structure and function: the Coronary Artery Risk Development in Young Adults (CARDIA) Study. J Am Heart Assoc. 2015;4:e001264. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Nazmi A and Victora CG. Socioeconomic and racial/ethnic differentials of C-reactive protein levels: a systematic review of population-based studies. BMC Public Health. 2007;7:212. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Clark DO, Unroe KT, Xu H, Keith NR, Callahan CM and Tu W. Sex and Race Differences in the Relationship between Obesity and C-Reactive Protein. Ethn Dis. 2016;26:197–204. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Hasson BR, Apovian C and Istfan N. Racial/Ethnic Differences in Insulin Resistance and Beta Cell Function: Relationship to Racial Disparities in Type 2 Diabetes among African Americans versus Caucasians. Curr Obes Rep. 2015;4:241–9. [DOI] [PubMed] [Google Scholar]
  • 31.Agrawal M, Kern PA and Nikolajczyk BS. The Immune System in Obesity: Developing Paradigms Amidst Inconvenient Truths. Curr Diab Rep. 2017;17:87. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Cauwenberghs N, Knez J, Thijs L, Haddad F, Vanassche T, Yang WY, Wei FF, Staessen JA and Kuznetsova T. Relation of Insulin Resistance to Longitudinal Changes in Left Ventricular Structure and Function in a General Population. Journal of the American Heart Association. 2018;7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Velez M, Kohli S and Sabbah HN. Animal models of insulin resistance and heart failure. Heart Fail Rev. 2014;19:1–13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Nishida K and Otsu K. Inflammation and metabolic cardiomyopathy. Cardiovasc Res. 2017;113:389–398. [DOI] [PubMed] [Google Scholar]
  • 35.Ghomari-Boukhatem H, Bouchouicha A, Mekki K, Chenni K, Belhadj M and Bouchenak M. Blood pressure, dyslipidemia and inflammatory factors are related to body mass index in scholar adolescents. Arch Med Sci. 2017;13:46–52. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Kapiotis S, Holzer G, Schaller G, Haumer M, Widhalm H, Weghuber D, Jilma B, Roggla G, Wolzt M, Widhalm K and Wagner OF. A proinflammatory state is detectable in obese children and is accompanied by functional and morphological vascular changes. Arterioscler Thromb Vasc Biol. 2006;26:2541–6. [DOI] [PubMed] [Google Scholar]
  • 37.Nishide R, Ando M, Funabashi H, Yoda Y, Nakano M and Shima M. Association of serum hs-CRP and lipids with obesity in school children in a 12-month follow-up study in Japan. Environ Health Prev Med. 2015;20:116–22. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Roh EJ, Lim JW, Ko KO and Cheon EJ. A useful predictor of early atherosclerosis in obese children: serum high-sensitivity C-reactive protein. J Korean Med Sci. 2007;22:192–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Singh R, Verma A, Aljabari S and Vasylyeva TL. Urinary biomarkers as indicator of chronic inflammation and endothelial dysfunction in obese adolescents. BMC Obes. 2017;4:11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Retnakaran R, Zinman B, Connelly PW, Harris SB and Hanley AJ. Nontraditional cardiovascular risk factors in pediatric metabolic syndrome. J Pediatr. 2006;148:176–82. [DOI] [PubMed] [Google Scholar]
  • 41.Norris AL, Steinberger J, Steffen LM, Metzig AM, Schwarzenberg SJ and Kelly AS. Circulating oxidized LDL and inflammation in extreme pediatric obesity. Obesity (Silver Spring). 2011;19:1415–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Pokharel Y, Sharma PP, Qintar M, Lu Y, Tang Y, Jones P, Dreyer RP and Spertus JA. High-sensitivity C-reactive protein levels and health status outcomes after myocardial infarction. Atherosclerosis. 2017;266:16–23. [DOI] [PMC free article] [PubMed] [Google Scholar]

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