Índice de redondez corporal como indicador antropométrico para identificar riesgo de síndrome metabólico en médicos del hospital San Francisco del IESS, en la ciudad de Quito
DOI:
https://doi.org/10.29166/rfcmq.v43i2.2828Keywords:
Body mass index, metabolic syndrome, anthropometry, overweight, body roundness indexAbstract
Contex: Chronic non-communicable diseases are of interest to public health; some of them can be detected and predicted through basic studies such as anthropometry. The body mass index (BMI) assesses, stratifies and classifies the individual’s level of overweight as a risk factor for metabolic syndrome (MS), without discriminating between muscle mass and adiposity that can be elucidated by means of the body roundness index (BRI) and predict both body fat percentage and health status. Barazzoni and collaborators related both IRC and BRI with metabolic syndrome; about this relationship there are few studies, some controversial. Objective: to demonstrate the usefulness of the BRI to identify risk factors for metabolic syndrome and correlate it with the body mass index to establish clinical utility as an indicator of metabolic risk. Subjects and methods: Cross-sectional descriptive observational epidemiological study, in a sample of 90 doctors from the San Francisco Hostpital of Quito (Ecuadorian Social Security Institute). Main measurements: nutritional status according to weight, height, abdominal circumference; diagnosis of metabolic syndrome according to “guide for the treatment of dyslipidemias in adults” (Adult Treatment Panel III). Results: 16.67% (95% CI 10.37–25.69%) of subjects were diagnosed with MS demonstrating a similar result using BMI and BRI to establish the condition of MS according to diagnostic criteria of ATPIII (p <0.05). The accuracy of the BMI as a predictor of MS risk was 62% and 30% accuracy; for IRC, the accuracy was 42%, sensitivity 23% and 100% negative predictive value. Conclusions: The prevalence of metabolic syndrome in doctors is high. The BRI is useful for the diagnosis of MS, however, its greatest application is to rule out its diagnosis, compared to the BMI. New studies are recommended.
Downloads
Metrics
References
Ravasco P, Anderson H, Mardones F. Métodos de valoración del estado nutricional. Nutr Hosp. 2010;
(S3):57–66.
Moreno V, Gómez Gandoy JB, Antoranz González MJ, Gómez de la Cámara A. Concordancia entre
los porcentajes de grasa corporal estimados mediante el área adiposa del brazo, el pliegue del tríceps
y por impedanciometría brazo-brazo. Rev Esp Salud Pública. 2003; 77(3):347–61.
Martínez Roldán C, Veiga Herreros P, López de Andrés a, Cobo Sanz JM, Carbajal Azcona a. Nutritional status assessment in a group of university students by means of dietary parameters and body
composition. Nutr Hosp 2005; 20(3):197–203.
Arroyave, G, Brock, JF, Hegsted, DM, Jelliffe D et al. Expert Committee on Medical Assessment of Nutritional
Status, WHO Technical Report Series, No. 258. Organización Mundial de la Salud:Ginebra. 1963. pp 1–67.
Buffa R, Mereu E, Comandini O, Ibanez ME, Marini E. Bioelectrical impedance vector analysis (BIVA)
for the assessment of two-compartment body composition. Eur J Clin Nutr 2014; 68(11):1234–40.
Organización Mundial de la Salud. El estado físico: uso e interpretación de la antropometría. Comité
de expertos de la OMS. Serie de Informes Técnicos Número 854. Organización Mundial de la Salud:Ginebra. 1993. pp 5-26.
Gómez AB. Evaluación del estado nutricional del adulto mediante la antropometría. Rev Cuba Aliment Nutr 2002; 16(2):146–52.
Tian S, Zhang X, Xu Y, Dong H. Feasibility of body roundness index for identifying a clustering of
cardiometabolic abnormalities compared to BMI, waist circumference and other anthropometric indices. Medicine (Baltimore) 2016; 95(34):e4642.
Zalesin KC, Franklin BA, Miller WM, Peterson ED, Mccullough PA. Impact of obesity on cardiovascular disease. Med Clin N Am 2011; 95:919–37.
Hossain P, Kawar B. Obesity and diabetes in the developing world- a growing challenge. N Engl J Med
; 356(3):213–5.
Krakauer NY, Krakauer JC. A new body shape index predicts mortality hazard independently of body
mass index. PLoS One 2012l; 7(7):e39504. doi: 10.1371/journal.pone.0039504
World Health Organization. Fact sheets. Obesity and overweight. 2018. Disponible en https://www.
who.int/news-room/fact-sheets/detail/obesity-and-overweight
Gawrys W, Zyska A. Anthropometric indicators and their applications for assessing population’s
health condition. Hygeia Public Heal. 2017;52(1):41–7
Ng M, Fleming T, Robinson M, et al. Global, regional and national prevalence of overweight and obesity in children and adults 1980-2013: A systematic analysis. Lancet 2014; 384(9945):766–81.
Sánchez J, Montaluisa F, Correa F, Guamán W, Paz W, Vásquez M, et al. Hipertrigliceridemia asociada
a sobrepeso y obesidad en médicos del hospital San Francisco del IESS, en la ciudad de Quito: una
alerta para los profesionales médicos. Rev Fac Cien Med 2017; 42(2):104–13.
Organización Mundial de la Salud. Dieta, nutrición y prevención de enfermedades crónicas. Serie
Informes técnicos No916. Organización Mundial de la Salud:Ginebra. 2003. pp 13–21.
Janssen I, Katzmarzyk PT, Ross R. Waist circumference and not body mass index explains obesity-related health risk. Am J Clin Nutr 2004; 79:379–84.
Pajunen P, Jousilahti P, Borodulin K, Harald K, Tuomilehto J. Body fat measured by a near-infrared
interactance device as a predictor of cardiovascular events: The FINRISK’92 Cohort. Obesity 2009;
(4):848–52.
Liu PJ, Ma F, Lou HP, Zhu YN. Body roundness index and body adiposity index: two new anthropometric indices to identify metabolic syndrome among Chinese postmenopausal women. Climacteric
; 19(5):433–9.
Carvajal CC. Síndrome metabólico: definiciones, epidemiología, etiología, componentes y tratamiento. Medicina Legal de Costa Rica 2017; 34(1):175-193.
Gómez I, González J. Dislipemia diabética, síndrome metabólico y riesgo cardiovascular. Rev Esp
Cardiol Supl 2006; 6(SG):13–23.
Duque P, Alonso O, Naranjo S, César J, Arias S, Carlos J, et al. Evaluación de la distribución de
los criterios diagnósticos para síndrome metabólico, en Pereira, Colombia. Investig. Andina 2013;
(27):746-743.
Thomas DM, Bredlau C, Bosy-Westphal A, Mueller M, Shen W, Gallagher D, et al. Relationships
between body roundness with body fat and visceral adipose tissue emerging from a new geometrical
model. Obesity. 2013; 21(11):2264–71.
Li G, Wu H, Wu X, Cao Z, Tu Y, Ma Y, et al. The feasibility of two anthropometric indices to identify
metabolic syndrome, insulin resistance and inflammatory factors in obese and overweight adults.
Nutrition 2019; 57:194–201.
Wang H, Liu A, Zhao T, Gong X, Pang T, Zhou Y, et al. Comparison of anthropometric indices for
predicting the risk of metabolic syndrome and its components in Chinese adults: a prospective, longitudinal study. BMJ Open 2017; 7(9):1–10.
Gómez-Ambrosi J, Silva C, Galofré JC, Escalada J, Santos S, Millán D, et al. Body mass index classification misses subjects with increased cardiometabolic risk factors related to elevated adiposity. Int J
Obes 2012; 36(2):286–94.
Bray GA, Smith SR, de Jonge L, Xie H, Rood J, Martin CK, et al. Effect of dietary protein content on
weight gain, energy expenditure, and body composition during overeating: a randomized controlled
trial. Jama 2012; 307(1):47–55.
Organización Mundial de la Salud. Obesity: preventing and managing the global epidemic. Serie
Informes Técnicos No 894. Organización Mundial de la Salud:Ginebra. 2000. pp 2-12.
Barazzoni R, Gortan Cappellari G, Semolic A, Ius M, Zanetti M, Gabrielli A, et al. Central adiposity
markers, plasma lipid profile and cardiometabolic risk prediction in overweight-obese individuals.
Clin Nutr 2018; 38(3):1–9.
World health statistics 2018: monitoring health for the SDGs, sustainable development goals. Geneva: World Health Organization; 2018. Licence: CC BY-NC-SA 3.0 IGO.pp 18-20
Liu PJ, Ma F, Lou HP, Zhu YN. Comparison of the ability to identify cardio metabolic risk factors
between two new body indices and waist-to-height ratio among Chinese adults with normal BMI and
waist circumference. Public Health Nutr 2017; 20(6):984–91.
Moreno C, Cabrerizo L, Rubio Montañés M. Guías para el tratamiento de las dislipemias en el adulto:
Adult Treatment Panel III (ATP-III). Endocrinología y Nutrición 2004; 51(5):254-266.
Freire de Freitas R, Moura de Araújo M, Gueiros Gaspar M, Garcia Lira Neto J, Parente Garcia Alencar
A, Zanetti M, Coelho Damasceno M. Comparison of three criteria for metabolic syndrome among
Brazilian university students. Nutrition & Food Science 2017; 47(4):543-552.
Gil Llinás M, Janer PE, Agudo SG, Casquero RG, González IC. Usefulness in nursing of different anthropometric and analytical indices to assess the existence of metabolic syndrome with
the NCEP ATP III and IDF criteria in Spanish Mediterranean population. Med Balear 2017;
(1):26–34.
Correa LF, Sánchez JM, Montaluisa FG, Guamán WM, Paz WR. EL síndrome metabólico en aumento en médicos del hospital San Francisco del IESS, de la ciudad de Quito. Revista de la Facultad de
Ciencias Médicas Quito 2016; 41(1):103–12.
Zhao Q, Zhang K, Li Y, Zhen Q, Shi J, Yu Y, et al. Capacity of a body shape index and body roundness
index to identify diabetes mellitus in Han Chinese people in Northeast China: a cross-sectional study.
Diabet Med 2018; 35(11):1580-1587.
Zhang J, Fang L, Qiu L, Huang L, Zhu W, Yu Y. Comparison of the ability to identify arterial stiffness
between two new anthropometric indices and classical obesity indices in Chinese adults. Atherosclerosis 2017; 263:263–71.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2018 Sebastián Vallejo Espinoza, Jorge Sánchez Sánchez, Washington Paz Cevallos, William Guamán Gualpa, Fabián Montaluisa Vivas, Fabricio Correa, Marco Vásquez
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
