LOGIN TO YOUR ACCOUNT

Username
Password
Remember Me
Or use your Academic/Social account:

CREATE AN ACCOUNT

Or use your Academic/Social account:

Congratulations!

You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.

Important!

Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message

CREATE AN ACCOUNT

Name:
Username:
Password:
Verify Password:
E-mail:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Buchan, DS; Boddy, LM; Despres, JP; Grace, FM; Sculthorpe, N; Mahoney, C; Baker, JS
Publisher: Wiley: 12 months
Languages: English
Types: Article
Subjects: RC1200
Background: It is unclear whether the Hypertriglyceridemic Waist Phenotype can be used to identify those at most risk of cardiometabolic disorders.\ud \ud Objectives: The utility of the Hypertriglyceridemic Waist Phenotype (HTWP) as a useful predictor of cardiometabolic risk in youth stratified by body mass index (BMI) was assessed.\ud \ud Methods: Three hundred and eighty seven children (12-17.5 years) were used within this cross-sectional study. Participants were classified as normal weight or overweight/obese according to the IOTF criteria. The HTWP phenotype was defined as having a waist circumference ≥ 90th percentile for age and gender with concomitant triglyceride concentrations ≥ 1.24 mmol/L. Cardiometabolic risk profiles were compared using MANCOVA.\ud \ud Results: Normal weight participants with the HTWP had significantly higher levels of C-reactive protein 2.6 ± 0.4 vs. 1.6 ± 0.3 mg/L (P < 0.05) and cardiometabolic risk scores (1.3 ± 0.3 vs. -0.7 ± 0.2 and 2.1 ± 0.4 vs. -0.5 ± 0.2; both P < 0.05) compared to those of a normal weight without the HTWP. Overweight/obese participants with the HTWP had significantly higher C-reactive protein levels (3.5 ± 0.6 vs. 2.6 ± 0.5; P < 0.05) as well as both cardiometabolic risk scores (1.6 ± 0.6 vs. 0.9 ± 0.2 and 2.2 ± 0.6 vs. 0.8 ± 0.2; both P < 0.001) when compared to overweight/obese participants without the HTWP.\ud \ud Conclusions:\ud The HTWP may serve as a simple and clinically useful approach to identify youth at increased cardiometabolic risk.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • 1. Khoury M, Manlhiot C, McCrindle BW. Role of the waist/height ratio in the cardiometabolic risk assessment of children classified by body mass index. J Am Coll Cardiol 2013;62:742-51.
    • 2. Lemieux I, Pascot A, Couillard C, et al. Hypertriglyceridemic waist: A marker of the atherogenic metabolic triad (hyperinsulinemia; hyperapolipoprotein B; small, dense LDL) in men? Circulation 2000;102:179-84.
    • 3. Bailey DP, Savory LA, Denton SJ, Davies BR, Kerr CJ. The hypertriglyceridemic waist, waist-toheight ratio, and cardiometabolic risk. J Pediatr 2013;162:746-52.
    • 4. Hobkirk JP, King RF, Gately P, et al. The predictive ability of triglycerides and waist (hypertriglyceridemic waist) in assessing metabolic triad change in obese children and adolescents. Metab Syndr Relat Disord 2013;11:336-42.
    • 5. Esmaillzadeh A, Mirmiran P, Azizi F. Clustering of metabolic abnormalities in adolescents with the hypertriglyceridemic waist phenotype. Am J Clin Nutr 2006;83:36-46; quiz 183-4.
    • 6. Pirkola J, Tammelin T, Bloigu A, et al. Prevalence of metabolic syndrome at age 16 using the International Diabetes Federation paediatric definition. Arch Dis Child 2008;93:945-51.
    • 7. Esmaillzadeh A, Mirmiran P, Azadbakht L, Azizi F. Prevalence of the hypertriglyceridemic waist phenotype in Iranian adolescents. Am J Prev Med 2006;30:52-8.
    • 8. 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.
    • 9. Anderssen SA, Cooper AR, Riddoch C, et al. Low cardiorespiratory fitness is a strong predictor for clustering of cardiovascular disease risk factors in children independent of country, age and sex. Eur J Cardiovasc Prev Rehabil 2007;14:526-31.
    • 10. Thomas NE, Cooper SM, Williams SP, Baker JS, Davies B. Relationship of fitness, fatness, and coronary-heart-disease risk factors in 12- to 13-year-olds. Pediatr Exerc Sci 2007;19:93-101.
    • 11. Buchan DS, Young JD, Boddy LM, Baker JS. Independent associations between cardiorespiratory fitness, waist circumference, BMI, and clustered cardiometabolic risk in adolescents. Am J Hum Biol 2014;26:29-35.
    • 12. Ledoux M, Lambert J, Reeder BA, Despres JP. A comparative analysis of weight to height and waist to hip circumference indices as indicators of the presence of cardiovascular disease risk factors. Canadian Heart Health Surveys Research Group. CMAJ 1997;157 Suppl 1:S32-8.
    • 13. Buchan DS, Ollis S, Thomas NE, Baker JS. The influence of a high intensity physical activity intervention on a selection of health related outcomes: an ecological approach. BMC Public Health 2010;10:8.
    • 14. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985;28:412-9.
    • 15. Balagopal PB, de Ferranti SD, Cook S, et al. Nontraditional risk factors and biomarkers for cardiovascular disease: mechanistic, research, and clinical considerations for youth: a scientific statement from the American Heart Association. Circulation 2011;123:2749-69.
    • 16. Steinberger J, Daniels SR, Eckel RH, et al. Progress and challenges in metabolic syndrome in children and adolescents: a scientific statement from the American Heart Association Atherosclerosis, Hypertension, and Obesity in the Young Committee of the Council on Cardiovascular Disease in the Young; Council on Cardiovascular Nursing; and Council on Nutrition, Physical Activity, and Metabolism. Circulation 2009;119:628-47.
    • 17. Strong JP, Mc GH, Jr. The natural history of coronary atherosclerosis. Am J Pathol 1962;40:37-49.
    • 18. Balagopal PB, de Ferranti SD, Cook S, et al. Nontraditional risk factors and biomarkers for cardiovascular disease: mechanistic, research, and clinical considerations for youth: a scientific statement from the American Heart Association. Circulation 2011;123:2749-69.
    • 19. Buchan DS, Young JD, Boddy LM, Malina RM, Baker JS. Fitness and Adiposity Are Independently Associated with Cardiometabolic Risk in Youth. Biomed Res Int 2013;2013.
    • 20. Health UDo, Services H. Report of the Expert Panel on Blood Cholesterol Levels in Children and Adolescents (NIH Publication No. 91-2732). Washington, DC: US Department of Health and Human Services 1991.
    • 21. Zimmet P, Alberti KG, Kaufman F, et al. The metabolic syndrome in children and adolescents - an IDF consensus report. Pediatr Diabetes 2007;8:299-306.
    • 22. McCarthy HD, Jarrett KV, Crawley HF. The development of waist circumference percentiles in British children aged 5.0-16.9 y. Eur J Clin Nutr 2001;55:902-7.
    • 23. Cole TJ, Bellizzi MC, Flegal KM, Dietz WH. Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ 2000;320:1240-3.
    • 24. Bauer KW, Marcus MD, El Ghormli L, Ogden CL, Foster GD. Cardio-metabolic risk screening among adolescents: understanding the utility of body mass index, waist circumference and waist to height ratio. Pediatr Obes 2014.
    • 25. Graves L, Garnett SP, Cowell CT, et al. Waist-to-height ratio and cardiometabolic risk factors in adolescence: findings from a prospective birth cohort. Pediatr Obes 2014;9:327-38.
    • 26. Cornier M-A, Després J-P, Davis N, et al. Assessing Adiposity: A Scientific Statement From the American Heart Association. Circulation 2011;124:1996-2019.
    • 27. Kavey R, Simons-Morton D, de Jesus J. Expert Panel on Integrated Guidelines for Cardiovascular Health and Risk Reduction in Children and Adolescents: Summary Report. Pediatrics 2011;128:S213-S56.
    • 28. Wildman RP, Muntner P, Reynolds K, et al. The obese without cardiometabolic risk factor clustering and the normal weight with cardiometabolic risk factor clustering: prevalence and correlates of 2 phenotypes among the US population (NHANES 1999-2004). Arch Intern Med 2008;168:1617-24.
    • 29. Li S, Chen W, Srinivasan SR, Xu J, Berenson GS. Relation of childhood obesity/cardiometabolic phenotypes to adult cardiometabolic profile: the Bogalusa Heart Study. Am J Epidemiol 2012;176 Suppl 7:S142-9.
  • No related research data.
  • Discovered through pilot similarity algorithms. Send us your feedback.

Share - Bookmark

Cite this article