Concordance between five criteria of metabolic syndrome in teenagers from a Peruvian high andes region

Authors

DOI:

https://doi.org/10.17843/rpmesp.2023.402.12546

Keywords:

Metabolic Syndrome, Adolescent, Diagnosis, Peru

Abstract

Objective. To determine the concordance between five diagnostic criteria for metabolic syndrome (MS) among teenagers from a Peruvian high Andes region. Materials and methods. A cross-sectional study was carried out with secondary data from an intervention study in two public schools in 2019. We included 397 teenagers who lived in the city of Cajamarca, in the Andean region of Peru. We applied the criteria from the Adult Treatment Panel III (ATP-III) modified by Cook, the International Diabetes Federation (IDF), the American Heart Association (AHA), Ferranti, and the World Health Organization (WHO). The point prevalence and interval prevalence were estimated with the five criteria. The Kappa concordance coefficient with an 95% confidence interval (95%CI) was estimated. Results. The Ferranti criterion identified 17.1% (95%CI: 13.4 to 20.8) of teenagers with MS, followed by the ATP-III criterion with 4.3% (95%CI: 2.3 to 6.3); the other criteria identified a lower frequency. The best concordance was found between the AHA and ATP-III criteria (k = 0.905); the WHO and IDF criteria had a coefficient of 0.628. The five criteria coincided in classifying six adolescents (1.5%) as MS. Conclusions. The AHA and ATP-III criteria modified by Cook had almost perfect concordance, which was also found for both sexes. The ATP-III, Ferranti, IDF, AHA and WHO criteria agree in less than 2% when identifying MS in the same group of adolescents.

 

Downloads

Download data is not yet available.

References

Noubiap JJ, Nansseu JR, Lontchi-Yimagou E, Nkeck JR, Nyaga UF, Ngouo AT, et al. Global, regional, and country estimates of metabolic

syndrome burden in children and adolescents in 2020: a systematic review and modelling analysis. Lancet Child Adolesc Health.

;6(3):158–70. doi: 10.1016/S2352-4642(21)00374-6.

Serbis A, Giapros V, Galli-Tsinopoulou A, Siomou E. Metabolic Syndrome in Children and Adolescents: Is There a Universally

Accepted Definition? Does it Matter? Metab Syndr Relat Disord. 2020;18(10):462–70. doi: 10.1089/met.2020.0076.

Ninatanta-Ortiz JA, Núñez-Zambrano LA, García-Flores SA, Romaní-Romaní F. Frecuencia de síndrome metabólico en residentes

de una región andina del Perú. Rev Peru Med Exp Salud Pública. 2016;33(4):640. doi: 10.17843/rpmesp.2016.334.2546.

García SA, Ninatanta-Ortiz JA, Abanto Villar MV, Pérez Cieza KM, Chávez Farro RR, Palacios Sánchez SE, et al. Intervención educativa

basada en estilos de vida para incrementar la proporción de adolescentes libres de componentes del síndrome metabólico en

una región altoandina del Perú. Rev Peru Med Exp Salud Pública. 2022;39(1):36–46. doi: 10.17843/rpmesp.2022.391.9986.

Cornejo-Monthedoro A, Negreiros-Sánchez I, Del Águila C, Ysla-Marquillo M, Mayta-Tristán P. Association between dietary glycemic load and metabolic syndrome in obese children and adolescents. Arch Argent Pediatr. 2017;115(4):323-330. doi: 10.5546/aap.2017.eng.323.

Villegas-Abrill CB, Vidal-Espinoza R, Gomez-Campos R, Ibañez-Quispe V, Mendoza-Mollocondo C, Cuentas-Yupanqui SR, et al.

Diagnostic Criteria for Metabolic Syndrome in High-Altitude Regions: A Systematic Review. Medicina (Mex). 2022;58(3):451. doi: 10.3390/

medicina58030451.

Bitew ZW, Alemu A, Ayele EG, Tenaw Z, Alebel A, Worku T. Metabolic syndrome among children and adolescents in low and middle income countries: a systematic review and meta-analysis. Diabetol Metab Syndr. 2020;12(1):93. doi: 10.1186/s13098-020-00601-8.

Reisinger C, Nkeh-Chungag BN, Fredriksen PM, Goswami N. The prevalence of pediatric metabolic syndrome—a critical look on the

discrepancies between definitions and its clinical importance. Int J Obes. 2021;45(1):12–24. doi: 10.1038/s41366-020-00713-1.

Ahrens W, Moreno LA, Mårild S, Molnár D, Siani A, De Henauw S, et al. Metabolic syndrome in young children: definitions and results

of the IDEFICS study. Int J Obes (Lond). 2014; 38 Suppl 2:S4-14. doi: 10.1038/ijo.2014.130.

Agudelo GM, Bedoya G, Estrada A, Patiño FA, Muñoz AM, Velásquez CM. Variations in the Prevalence of Metabolic Syndrome in Adolescents According to Different Criteria Used for Diagnosis: Which Definition Should Be Chosen for This Age Group? Metab Syndr Relat Disord. 2014;12(4):202–9. doi: 10.1089/met.2013.0127.

Gonçalves R, de Paula Símola RÁ, Oliveira Damasceno V, Alves Lamounier J, Mendes RC, Granjeiro PA. Prevalence of metabolic syndrome in Brazilian children using three different sets of international criteria. Nutr Hosp. 2021; 38(2):228-235. doi: 10.20960/nh.03224.

Guilherme FR, Nascimento MA do, Molena-Fernandes CA, Guilherme VR, Santos SR dos, Elias RGM, et al. Comparison of different criteria in the prevalence of metabolic syndrome in students from Paranavaí, Paraná. Rev Paul Pediatr. 2019;37(3):332–7. doi: 10.1590/1984-0462/;2019;37;3;00007.

Fernández‐Aparicio Á, Perona JS, Schmidt‐RioValle J, González‐Jiménez E. Concordance among diagnostic criteria for metabolic

syndrome is inconsistent in Spanish adolescents. Eur J Clin Invest. 2021;51(2). doi: 10.1111/eci.13384.

Vanlancker T, Schaubroeck E, Vyncke K, Cadenas-Sanchez C, Breidenassel C, González-Gross M, et al. Comparison of definitions for the metabolic syndrome in adolescents. The HELENA study. Eur J Pediatr. 2017;176(2):241–52. doi: 10.1007/s00431-016-2831-6.

Reuter CP, Burgos MS, Barbian CD, Renner JDP, Franke SIR, de Mello ED. Comparison between different criteria for metabolic

syndrome in schoolchildren from southern Brazil. Eur J Pediatr. 2018;177(10):1471–7. doi: 10.1007/s00431-018-3202-2.

Lopez-Pascual A, Arévalo J, Martínez JA, González-Muniesa P. Inverse Association Between Metabolic Syndrome and Altitude: A Cross-Sectional Study in an Adult Population of Ecuador. Front Endocrinol. 2018;9:658. doi: 10.3389/fendo.2018.00658.

Huang X, Hu Y, Du L, Lin X, Wu W, Fan L, et al. Metabolic syndrome in native populations living at high altitude: a cross-sectional survey in Derong, China. BMJ Open. 2020;10(1):e032840. doi: 10.1136/bmjopen-2019-032840.

Pérez-Galarza J, Baldeón L, Franco OH, Muka T, Drexhage HA, Voortman T, et al. Prevalence of overweight and metabolic syndrome,

and associated sociodemographic factors among adult Ecuadorian populations: the ENSANUT-ECU study. J Endocrinol Invest.

;44(1):63–74. doi: 10.1007/s40618-020-01267-9.

Zhao X, Li S, Ba S, He F, Li N, Ke L, et al. Prevalence, Awareness, Treatment, and Control of Hypertension Among Herdsmen Living at 4,300 m in Tibet. Am J Hypertens. 2012;25(5):583–9. doi: 10.1038/ajh.2012.9.

Woolcott OO, Gutierrez C, Castillo OA, Elashoff RM, Stefanovski D, Bergman RN. Inverse association between altitude and obesity: A

prevalence study among andean and low-altitude adult individuals of Peru: Altitude and Obesity. Obesity. 2016;24(4):929–37. doi: 10.1002/oby.21401.

Herrera-Enriquez K, Narvaez-Guerra O. Discordance of metabolic syndrome and abdominal obesity prevalence according to different

criteria in Andean highlanders: A community-based study. Diabetes Metab Syndr Clin Res Rev. 2017;11:S359–64. doi: 10.1016/j.dsx.2017.03.016.

Cook S, Weitzman M, Auinger P, Nguyen M, Dietz WH. Prevalence of a Metabolic Syndrome Phenotype in Adolescents: Findings From

the Third National Health and Nutrition Examination Survey, 1988-1994. Arch Pediatr Adolesc Med. 2003;157(8):821–7. doi: 10.1001/

archpedi.157.8.821.

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(16):2494–7. doi: 10.1161/01.CIR.0000145117.40114.C7.

Zimmet P, Alberti KGM, Kaufman F, Tajima N, Silink M, Arslanian S, et al. The metabolic syndrome in children and adolescents ? an

IDF consensus report. Pediatr Diabetes. 2007;8(5):299–306. doi: 10.1111/j.1399-5448.2007.00271.x.

Goodman E, Daniels SR, Meigs JB, Dolan LM. Instability in the Diagnosis of Metabolic Syndrome in Adolescents. Circulation.

;115(17):2316–22. doi: 10.1161/CIRCULATIONAHA.106.669994.

Aguilar L, Contreras M, Calle M del C. Guía técnica para la valoración nutricional antropométrica de la persona adolescente. Ministerio de Salud, Instituto Nacional de Salud. 2015. Disponible en: http://repositorio.ins.gob.pe/bitstream/ INS/214/1/CENAN-0056.pdf

Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. 1977;33(1):159–74.

Cook S, Auinger P, Huang TT-K. Growth Curves for Cardio-Metabolic Risk Factors in Children and Adolescents. J Pediatr. 2009;155(3):S6. e15-S6.e26. doi: 10.1016/j.jpeds.2009.04.051.

Villalobos M, Mederico M, Paoli de Valeri M, Briceño Y, Zerpa Y, Gómez-Pérez R, et al. Síndrome metabólico en escolares y adolescentes de la ciudad de Mérida-Venezuela: comparación de resultados utilizando valores de referencia locales e internacionales (estudio CREDEFAR). Endocrinol Nutr. 2014;61(9):474–85. doi: 10.1016/j.endonu.2014.03.009.

Galera-Martínez R. Prevalencia de síndrome metabólico en la población general. Nutr Hosp. 2015;(2):627–33. doi: 10.3305/

nh.2015.32.2.9278.

Prodam F, Ricotti R, Genoni G, Parlamento S, Petri A, Balossini C, et al. Comparison of two classifications of metabolic syndrome in

the pediatric population and the impact of cholesterol. J Endocrinol Invest. 2013;36(7):466-73. doi: 10.3275/8768.

Cook S, Auinger P, Li C, Ford ES. Metabolic Syndrome Rates in United States Adolescents, from the National Health and Nutrition

Examination Survey, 1999–2002. J Pediatr. 2008;152(2):165-170.e2. doi: 10.1016/j.jpeds.2007.06.004.

Mohanna S, Baracco R, Seclén S. Lipid Profile, Waist Circumference, and Body Mass Index in a High Altitude Population. High Alt Med

Biol. 2006;7(3):245–55. doi: 10.1089/ham.2006.7.245.

Sherpa LY, Deji, Stigum H, Chongsuvivatwong V, Luobu O, Thelle DS, et al. Lipid Profile and Its Association with Risk Factors for Coronary Heart Disease in the Highlanders of Lhasa, Tibet. High Alt Med Biol. 2011;12(1):57–63. doi: 10.1089/ham.2010.1050.

Gayà-Vidal M, Athanasiadis G, Carreras-Torres R, Via M, Esteban E, Villena M, et al. Apolipoprotein E/C1/C4/C2 Gene Cluster Diversity

in Two Native Andean Populations: Aymaras and Quechuas: APOE/C1/C4/C2 Gene Cluster Diversity in Andeans. Ann Hum Genet.

;76(4):283–95. doi: 10.1111/j.1469-1809.2012.00712.x.

Castillo O, Woolcott OO, Gonzales E, Tello V, Tello L, Villarreal C, et al. Residents at High Altitude Show a Lower Glucose Profile Than Sea-Level Residents Throughout 12-Hour Blood Continuous Monitoring. High Alt Med Biol. 2007;8(4):307–11. doi: 10.1089/ham.2007.8407.

Published

2023-06-30

Issue

Section

Original Article

How to Cite

1.
Romaní-Romaní FR, Pachacama Ramírez LF, Pichihua Grandez JD, Guevara Rodríguez DM, Cornejo Luyo V, Sheen Vargas CE, et al. Concordance between five criteria of metabolic syndrome in teenagers from a Peruvian high andes region. Rev Peru Med Exp Salud Publica [Internet]. 2023 Jun. 30 [cited 2024 Nov. 21];40(2):150-60. Available from: https://rpmesp.ins.gob.pe/index.php/rpmesp/article/view/12546

Most read articles by the same author(s)