Correlación del índice cintura-altura con otros parámetros antropométricos asociados al riesgo cardiometabólico en individuos aparentemente sanos con factores de riesgo de enfermedad cardiometabólica
DOI:
https://doi.org/10.62827/eb.v23i3.4014Palabras clave:
Síndrome metabólico; obesidad; ejercicio físico; estilo de vida; atención primaria de salud.Resumen
Introducción: Uno de los criterios para estratificar el riesgo cardiometabólico (ICC) es el índice cintura-talla (ICC). Objetivo: correlacionar el ICC con otros parámetros antropométricos y de composición corporal en individuos aparentemente sanos o con factores de riesgo de enfermedad cardiometabólica. Métodos: 193 hombres/220 mujeres (18-74 años). Se aplicó la prueba de Mann Whitney para las comparaciones entre WHtR-CC y WHtR-CAB y los resultados se presentaron como mediana y rango intercuartílico. Se realizaron correlaciones de Pearson para evaluar la correlación entre las variables WC, CAB e IMC en relación con el WHtR. El nivel de significancia adoptado fue (p<0.05) y los análisis se realizaron con el software SigmaPlot para Windows versión 11.0, copyright© 2008 System Software, Inc. Resultados: Las variables RCE-CC y RCE-CAB mostraron diferencia significativa cuando comparados en su totalidad (p=0,001) con valores para WHR-CC de 0,49 (0,45-0,54) y para WHR-CAB de 0,52 (0,47-0,58). Lo mismo ocurrió en las comparaciones por subgrupo tanto para hombres como para mujeres (p=0,001), (p=0,020), respectivamente y los valores presentados fueron para ICT-CC de 0,49 (0,45-0,55) y para ICT-CAB de 0,51. (0,46-0,56) en hombres y para mujeres para ICT-CC de 0,49 (0,44-0,54) y para ICT-CAB de 0,53 (0,48-0,60). Las correlaciones entre la variable RCC con relación al índice de masa corporal, CC y CAB fueron respectivamente; (p<0,0001) (r=0,904), (p<0,0001) (r=0,922), (p<0,0001) (r=0,924). Conclusión: WHtR tiene una correlación muy fuerte con IMC, CC y CAB. Sin embargo, CC y CAB no deben aplicarse a la fórmula CER con el mismo objetivo.
Referencias
Chaves TO, Reis MS. Abdominal Circumference or Waist Circumference? IJCS. 2019;32(3):290-2. doi: 10.5935/2359-4802.20180080.
Mbanya VN, Kengne AP, Mbanya JC, Akhtar H. Body mass index, waist circumference, waist-hip-ratio and waist-height-ratio: which is the better discriminator of prevalent screen-detected diabetes in Cameroonian population? Diabetes Res Clin Pract. 2015;108(1):23-30. doi: 10.1016/j.diabres.2015.01.032.
Masoud M, Khajeh M. Comparison of anthropometric indices (body mass index, waist circumference, waist to hip ratio and waist to height ratio) in predicting risk of type II diabetes in the population of Yazd, Iran. Diabetes Metab Syndr. 2018;12(5):677-82. doi: 10.1016/j.dsx.2018.04.026.
Correa MM, Thumé E, Oliveira ER, Tomasi E. Performance of the waist-to-height ratio in identifying obesity and predicting non-communicable diseases in the elderly population: A systematic literature review. Arch Gerontol Geriatr. 2016;65:174-82. doi: 10.1016/j.archger.2016.03.021.
Lee DH, Keum N, Hu FB, Orav EJ, Rim EB, Willett WC, et al. Comparison of the association of predicted fat mass, body mass index, and other obesity indicators with type 2 diabetes risk: two large prospective studies in US men and women. European journal of epidemiology. 2018;33(11): 1113-23. doi: 10.1007/s10654-018-0433-5.
Ross R, Neeland IJ, Yamashita S, Shai I, Seidell J, Magni P, et al. Waist circumference as a vital sign in clinical practice: a Consensus Statement from the IAS and ICCR Working Group on Visceral Obesity. Nat Rev Endocrinol . 2020; 16(3):177-89. doi: 10.1038/s41574-019-0310-7.
Munckhof IC, Holewijn S, Rutten JG, Rutten JH. Sex differences in fat distribution influence the association between BMI and arterial stiffness. J Hypertens. 2017; 35(6):1219-25. doi: 10.1097/HJH.0000000000001297.
Dhana K, Kavousi M, Ikram MA, Tiemeier HW, Hofman A, Franco OH. Body shape index in comparison with other anthropometric measures in prediction of total and cause-specific mortality. J Epidemiol Community Health. 2016;70(1):90-6. doi: 10.1136/jech-2014-205257.
Feng RN, Zhao C, Wang C, Niu Y, Li K, Guo F, Li S, et al. BMI is strongly associated with hypertension, and waist circumference is strongly associated with type 2 diabetes and dyslipidemia, in northern Chinese adults. J Epidemiol . 2012;22(4):317-23. doi: 10.2188/jea.je20110120.
Rocha DR, Jorge AR, Braulio VB, Arbex AK, Marcadenti A. Visceral Adiposity Measurements, Metabolic and Inflammatory Profi le in Obese Patients with and Without Type 2 Diabetes Mellitus: A Crosssectional Analysis. Curr Diabetes Rev. 2017;13(1):11-8. doi: 10.2174/1573399812666151015115924.
Krakauer NY, Krakauer CJ. Untangling Waist Circumference and Hip Circumference from Body Mass Index with a Body Shape Index, Hip Index, and Anthropometric Risk Indicator. Metab Syndr Relat Disord . 2018;16(4):160-5. doi: 10.1089/met.2017.0166.
Sciomer S, Moscucci F, Salvioni E, Marchese G, Bussotti M, Corrà U, et al. Role of gender, age and BMI in prognosis of heart failure. Eur J Prev Cardiol. 2020;27(2_suppl):46-51. Doi: 10.1177/2047487320961980.
Xinyan BI, Loo YT, Henry CJ. Body fat measurements in Singaporean adults using four methods. Nutrients. 2018;10(3):303. doi: 10.3390/nu10030303.
Li R, Shi L, Jia J, Li Y, Yang Q, Ruan Y, et al. Differentiating the associations of waist circumference and body mass index with cardiovascular disease risk in a Chinese population. Asia-Pacific Journal of Public Health. 2015;27(2):457-67. doi: 10.1177/1010539512465306.
Stewart AD, Marfell-Jones MJ, Ridder JH. International standards for anthropometric assessment. Lower Hutt, New Zealand: International Society for the Advancement of Kinanthropometry - ISAK, 2011.
Hopkins WG. Measures of reliability in sports medicine and science. Sports Med. 2000;30(1);1-15. doi: 10.2165/00007256-200030010-00001.
Mancini MC. Associação Brasileira para o Estudo da Obesidade e da Síndrome Metabólica. Diretrizes brasileiras de obesidade 2016/ABESO - Associação Brasileira para o Estudo da Obesidade e da Síndrome Metabólica. - 4.ed. - São Paulo, SP, p:1-188.
Malachias MB, Souza WK, Plavnik FL, Rodrigues CI, Brandão AA, Neves MF, et al. Sociedade Brasileira de Cardiologia. 7ª Diretriz Brasileira de Hipertensão Arterial: Capítulo 14–Crise Hipertensiva. Arq Bras Cardiol. 2016;107(3):1-103.
Merrill RK, Kim JS, Leven DM, Kim JH, Meaike JJ, Bronheim RS, et al. Differences in fundamental sagittal pelvic parameters based on age, sex, and race. Clin Spine Surg. 2018;31(2):109-14. doi: 10.1097/BSD.0000000000000555.
Correa MM, Facchini LA, Thumé E, Oliveira ER, Tomasi E. The ability of waist-to-height ratio to identify health risk. Rev Saude Publica. 2019;53:66. doi: 10.11606/s1518-8787.2019053000895
Ashwell M, Gibson S. Waist-to-height ratio as an indicator of ‘early health risk’: simpler and more predictive than using a ‘matrix’ based on BMI and waist circumference. BMJ Open. 2016;63(3):e010159. doi: 10.1136/bmjopen-2015-010159.
Ashwell M, Gunn P, Gibson S. Waist-to-height ratio is a better screening tool than waist circumference and BMI for adult cardiometabolic risk factors: systematic review and meta-analysis. Obes Rev. 2012;13(3):275-86. doi: 10.1111/j.1467-789X.2011.00952.x.
Cai L, Liu A, Zhang Y, Wang P. Waist-to-height ratio and cardiovascular risk factors among Chinese adults in Beijing. PLoS One. 2013;8(7):e69298. doi: 10.1371/journal.pone.0069298.
Christofaro DG, Farah BQ, Vanderlei LC, Delfino LD, Tebar WR, Barros MV, et al. Analysis of different anthropometric indicators in the detection of high blood pressure in school adolescents: a cross-sectional study with 8295 adolescents. Braz J Phys Ther. 2018;22(1):49-54. doi: 10.1016/j.bjpt.2017.10.007.
Caminha TC, Ferreira HS, Costa NS, Nakano RP, Carvalho RE, Xavier AF, et al. Waist-to-height ratio is the best anthropometric predictor of hypertension: A population-based study with women from a state of northeast of Brazil. Medicine (Baltimore). 2017;96(2):e5874. doi: 10.1097/MD.0000000000005874.
Oliveira A, Cocate PG, Hermsdorff HH, Bressan J, Silva MF, Rodrigues JA, et al. Waist circumference measures: cutoff analyses to detect obesity and cardiometabolic risk factors in a Southeast Brazilian middle-aged men population-a cross-sectional study. Lipids health Dis. 2014;13(141):1-8. doi: 10.1186/1476-511X-13-141
Wang J, Thornton JC, Bari S, Williamson B, Gallagher D, Heymsfield SB, et al. Comparisons of waist circumferences measured at 4 sites. Am J Clin Nutr. 2003;77(2):379-84. doi: 10.1093/ajcn/77.2.379.
Saklayen MG. The Global Epidemic of the Metabolic Syndrome. Current Hypertension Reports. 2018;20(2):1-8. doi: 10.1007/s11906-018-0812-z.
Dong-Chul S, Siyoung C, Mohammad RT. Is waist circumference ≥102/88cm better than body mass index ≥30 to predict hypertension and diabetes development regardless of gender, age group, and race/ethnicity? Meta-analysis. Prev Med. 2017;100(108):100-8. doi: 10.1016/j.ypmed.2017.01.012.
Perona JS, Rio-Valle JS, Ramírez-Vélez R, Correa-Rodríguez M, Fernández-Aparicio A, González-Jiménez E. Waist Circumference and Abdominal Volume Index Are the Strongest Anthropometric Discriminators of Metabolic Syndrome in Spanish Adolescents. Eur J Clin Invest. 2019;49(3):e13060. doi: 10.1111/eci.13060.
Sareban HM, Mirhosseini SJ, Mirzaei M, Namayandeh SM, Beiki O, Gannar F, et al. The Most Important Predictors of Metabolic Syndrome Persistence after 10-year Follow-Up: YHHP Study. Int Prev Med. 2020;27(33):11-33. doi: 10.4103/ijpvm.IJPVM_215_18
Chertow GM, Appel GB, Block GA, Chin MP, Coyne DW, Goldsberry A, et al. Effects of Bardoxolone Methyl on Body Weight, Waist Circumference and Glycemic Control in Obese Patients With Type 2 Diabetes Mellitus and Stage 4 Chronic Kidney Disease. J Diabetes Complications. 2018;32(12):1113-7. doi: 10.1016/j.jdiacomp.2018.09.005.
Correa-Burrows P, Blanco E, Gahagan S, Burrows R. Cardiometabolic health in adolescence and its association with educational outcomes. J Epidemiol Community Health. 2019;73(12):1071-7. doi: 10.1136/jech-2019-212256.
Buchmann N, Spira D, König M, Demuth I, Steinhagen-Thiessen E. Frailty and the Metabolic Syndrome - Results of the Berlin Aging Study II (BASE-II). J Frailty Aging. 2019;8(4):169-75. doi: 10.14283/jfa.2019.15.
Katsa ME, Loannidis A, Sachlas A, Dimopoulos L, Stylianos Chatzipanagiotou S, Gil AP. The roles of triglyceride/high-density lipoprotein cholesterol ratio and uric acid as predisposing factors for metabolic syndrome in healthy children. Ann Pediatr Endocrinol Metab. 2019;24(3):172-9. doi: 10.6065/apem.2019.24.3.172.
Malik MS, Qayyum W, Farooq A, Waqas A, Sukhera AB, Khalid MA, et al. Dietary Patterns, Exercise, and the Metabolic Syndrome Among Young People in Urban Pakistan (Lahore). 2020;18(1):56-64. doi: 10.1089/met.2019.0021.
Descargas
Publicado
Número
Sección
Licencia
Derechos de autor 2024 Tiago de Oliveira Chaves , Clóvis de Albuquerque Maurício, Michel Silva Reis (Autor)
Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.
Autores que publicam nesta revista concordam com os seguintes termos:
Autores mantém os direitos autorais e concedem à revista o direito de primeira publicação, com o trabalho simultaneamente licenciado sob a Licença Creative Commons Attribution 4.0 que permite o compartilhamento do trabalho com reconhecimento da autoria e publicação inicial nesta revista.
Autores têm autorização para distribuição não-exclusiva da versão do trabalho publicada nesta revista (ex.: publicar em repositório institucional ou como capítulo de livro), com reconhecimento de autoria e publicação inicial nesta revista.
