Prevalencia de las combinaciones de componentes del síndrome metabólico en el municipio San Cristóbal, Táchira, Venezuela
Introducción: El síndrome metabólico (SM) se define como un conjunto de factores de riesgo que aumentan la probabilidad del desarrollo de Diabetes Mellitus y enfermedades cardiovasculares. Sin embargo, en nuestra localidad no se ha estudiado el comportamiento de las combinatorias de criterios del SM...
- Autores:
-
Mata, Katy R.
Bermúdez, Valmore
Villalobos, Edimar
Guerrero, Ybrain
Añez, Roberto J.
Rojas, Joselyn
- Tipo de recurso:
- Fecha de publicación:
- 2017
- Institución:
- Universidad Simón Bolívar
- Repositorio:
- Repositorio Digital USB
- Idioma:
- spa
- OAI Identifier:
- oai:bonga.unisimon.edu.co:20.500.12442/1843
- Acceso en línea:
- http://hdl.handle.net/20.500.12442/1843
- Palabra clave:
- Síndrome Metabólico
Criterios diagnósticos
Resistencia a la insulina
Factores de riesgo
Enfermedad cardiovascular
Metabolic syndrome
Diagnostic criteria
Insulin resistance
Risk factors
Cardiovascular disease
- Rights
- License
- Licencia de Creative Commons Reconocimiento-NoComercial-CompartirIgual 4.0 Internacional
| id |
USIMONBOL2_6c944df44c5ed80c1e1f99b70a91670f |
|---|---|
| oai_identifier_str |
oai:bonga.unisimon.edu.co:20.500.12442/1843 |
| network_acronym_str |
USIMONBOL2 |
| network_name_str |
Repositorio Digital USB |
| repository_id_str |
|
| dc.title.spa.fl_str_mv |
Prevalencia de las combinaciones de componentes del síndrome metabólico en el municipio San Cristóbal, Táchira, Venezuela |
| dc.title.alternative.eng.fl_str_mv |
Prevalence of combinations of metabolic syndrome components in the municipality of San Cristóbal, Táchira, Venezuela |
| title |
Prevalencia de las combinaciones de componentes del síndrome metabólico en el municipio San Cristóbal, Táchira, Venezuela |
| spellingShingle |
Prevalencia de las combinaciones de componentes del síndrome metabólico en el municipio San Cristóbal, Táchira, Venezuela Síndrome Metabólico Criterios diagnósticos Resistencia a la insulina Factores de riesgo Enfermedad cardiovascular Metabolic syndrome Diagnostic criteria Insulin resistance Risk factors Cardiovascular disease |
| title_short |
Prevalencia de las combinaciones de componentes del síndrome metabólico en el municipio San Cristóbal, Táchira, Venezuela |
| title_full |
Prevalencia de las combinaciones de componentes del síndrome metabólico en el municipio San Cristóbal, Táchira, Venezuela |
| title_fullStr |
Prevalencia de las combinaciones de componentes del síndrome metabólico en el municipio San Cristóbal, Táchira, Venezuela |
| title_full_unstemmed |
Prevalencia de las combinaciones de componentes del síndrome metabólico en el municipio San Cristóbal, Táchira, Venezuela |
| title_sort |
Prevalencia de las combinaciones de componentes del síndrome metabólico en el municipio San Cristóbal, Táchira, Venezuela |
| dc.creator.fl_str_mv |
Mata, Katy R. Bermúdez, Valmore Villalobos, Edimar Guerrero, Ybrain Añez, Roberto J. Rojas, Joselyn |
| dc.contributor.author.none.fl_str_mv |
Mata, Katy R. Bermúdez, Valmore Villalobos, Edimar Guerrero, Ybrain Añez, Roberto J. Rojas, Joselyn |
| dc.subject.spa.fl_str_mv |
Síndrome Metabólico Criterios diagnósticos Resistencia a la insulina Factores de riesgo Enfermedad cardiovascular |
| topic |
Síndrome Metabólico Criterios diagnósticos Resistencia a la insulina Factores de riesgo Enfermedad cardiovascular Metabolic syndrome Diagnostic criteria Insulin resistance Risk factors Cardiovascular disease |
| dc.subject.eng.fl_str_mv |
Metabolic syndrome Diagnostic criteria Insulin resistance Risk factors Cardiovascular disease |
| description |
Introducción: El síndrome metabólico (SM) se define como un conjunto de factores de riesgo que aumentan la probabilidad del desarrollo de Diabetes Mellitus y enfermedades cardiovasculares. Sin embargo, en nuestra localidad no se ha estudiado el comportamiento de las combinatorias de criterios del SM, por lo que el objetivo de este estudio fue determinar la prevalencia de las combinaciones de componentes del SM en el municipio San Cristóbal, Venezuela. Materiales y Métodos: Se realizó un estudio transversal, con muestreo aleatorio y multietápico en 362 individuos de ambos sexos, a quienes se les determinaron los componentes del SM según IDF/AHA/NHLBI/WHF/IAS/IASO (2009). La presencia de insulinorresistencia (IR) fue evaluada mediante el HOMA2-IR. Resultados: La prevalencia de SM fue de 51,4% (n=186) para la población general. La combinatoria de SM más frecuente fue la que incluyó a todos los criterios con un 16,1% (n=30); seguido de la presencia de las combinatorias CPHT (C: obesidad abdominal, P: presión arterial elevada ó HTA, H: HDL-C bajas y T: TAG elevados) con un 12,4% (n=23). La combinatoria CPGT fue la que presentó mayor frecuencia de IR con un 60,0% seguido por CPHT que presentó 43,48% de IR y seguido de Todos los criterios con una prevalencia de IR similar de 43,33%. Conclusiones: El SM presentó una alta prevalencia en nuestra población. Las combinatorias más frecuentes fueron las que presentaron el criterio de circunferencia abdominal elevada, mientras que las menos frecuentes carecieron de éste. De manera similar las combinaciones con obesidad abdominal fueron las que mostraron una mayor insulinorresistencia. |
| publishDate |
2017 |
| dc.date.issued.none.fl_str_mv |
2017 |
| dc.date.accessioned.none.fl_str_mv |
2018-03-09T21:58:04Z |
| dc.date.available.none.fl_str_mv |
2018-03-09T21:58:04Z |
| dc.type.spa.fl_str_mv |
article |
| dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_6501 |
| dc.identifier.issn.none.fl_str_mv |
18564550 |
| dc.identifier.uri.none.fl_str_mv |
http://hdl.handle.net/20.500.12442/1843 |
| identifier_str_mv |
18564550 |
| url |
http://hdl.handle.net/20.500.12442/1843 |
| dc.language.iso.spa.fl_str_mv |
spa |
| language |
spa |
| dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
| dc.rights.license.spa.fl_str_mv |
Licencia de Creative Commons Reconocimiento-NoComercial-CompartirIgual 4.0 Internacional |
| rights_invalid_str_mv |
Licencia de Creative Commons Reconocimiento-NoComercial-CompartirIgual 4.0 Internacional http://purl.org/coar/access_right/c_abf2 |
| dc.publisher.spa.fl_str_mv |
Cooperativa servicios y suministros 212518 RS |
| dc.source.spa.fl_str_mv |
Revista Latinoamericana de Hipertensión Vol. 12, No.4 (2017) |
| institution |
Universidad Simón Bolívar |
| dc.source.uri.none.fl_str_mv |
https://www.redalyc.org/articulo.oa?id=170253258003 |
| bitstream.url.fl_str_mv |
https://bonga.unisimon.edu.co/bitstreams/6b9cb007-4fa9-4bc0-ad9f-e60af489eb26/download |
| bitstream.checksum.fl_str_mv |
8a4605be74aa9ea9d79846c1fba20a33 |
| bitstream.checksumAlgorithm.fl_str_mv |
MD5 |
| repository.name.fl_str_mv |
DSpace UniSimon |
| repository.mail.fl_str_mv |
bibliotecas@biteca.com |
| _version_ |
1812100469741322240 |
| spelling |
Licencia de Creative Commons Reconocimiento-NoComercial-CompartirIgual 4.0 Internacionalhttp://purl.org/coar/access_right/c_abf2Mata, Katy R.7d91f318-6703-4073-8df2-0c81cb23d07e-1Bermúdez, Valmore29f9aa18-16a4-4fd3-8ce5-ed94a0b8663a-1Villalobos, Edimar413f23f3-8346-48ab-ba07-5d28d7dbec58-1Guerrero, Ybrain3ad7d46d-aa99-4411-8232-5e07a6831b8e-1Añez, Roberto J.a0889cd6-db0e-409f-8ab0-9ad32833b9ae-1Rojas, Joselyn2aa91570-0516-424d-8f76-25cd7b39be6e-12018-03-09T21:58:04Z2018-03-09T21:58:04Z201718564550http://hdl.handle.net/20.500.12442/1843Introducción: El síndrome metabólico (SM) se define como un conjunto de factores de riesgo que aumentan la probabilidad del desarrollo de Diabetes Mellitus y enfermedades cardiovasculares. Sin embargo, en nuestra localidad no se ha estudiado el comportamiento de las combinatorias de criterios del SM, por lo que el objetivo de este estudio fue determinar la prevalencia de las combinaciones de componentes del SM en el municipio San Cristóbal, Venezuela. Materiales y Métodos: Se realizó un estudio transversal, con muestreo aleatorio y multietápico en 362 individuos de ambos sexos, a quienes se les determinaron los componentes del SM según IDF/AHA/NHLBI/WHF/IAS/IASO (2009). La presencia de insulinorresistencia (IR) fue evaluada mediante el HOMA2-IR. Resultados: La prevalencia de SM fue de 51,4% (n=186) para la población general. La combinatoria de SM más frecuente fue la que incluyó a todos los criterios con un 16,1% (n=30); seguido de la presencia de las combinatorias CPHT (C: obesidad abdominal, P: presión arterial elevada ó HTA, H: HDL-C bajas y T: TAG elevados) con un 12,4% (n=23). La combinatoria CPGT fue la que presentó mayor frecuencia de IR con un 60,0% seguido por CPHT que presentó 43,48% de IR y seguido de Todos los criterios con una prevalencia de IR similar de 43,33%. Conclusiones: El SM presentó una alta prevalencia en nuestra población. Las combinatorias más frecuentes fueron las que presentaron el criterio de circunferencia abdominal elevada, mientras que las menos frecuentes carecieron de éste. De manera similar las combinaciones con obesidad abdominal fueron las que mostraron una mayor insulinorresistencia.Introduction: Metabolic syndrome (MS) is defined as a set of risk factors that increase the likelihood of developing type 2 diabetes mellitus (T2DM) and cardiovascular disease. However, in our town not studied the behavior of combinatorial criteria for MS, so the aim of this study was to determine the prevalence of combinations of components of MS in the municipality of San Cristobal, Venezuela. Materials and methods: This was a cross-sectional study with a multistage and randomized sampling on 362 individuals of both sexes, who were identified as components MS by IDF/AHA/NHLBI/WHF/IAS/IASO (2009) criteria’s. The presence of insulin resistance (IR) was assessed by HOMA2-IR. Results: The prevalence of MS was 51,4% (n=186) for the general population. The most frequent MS cluster was that included all the criteria 16,1% (n=30); followed by the presence of AO-HBP-LowH-ET (AO: abdominal obesity, HBP: High blood pressure or hypertension, Low-H: low HDL-C and ET: Elevated TAG) combinatorial 12,4% (n=23). The combinatorial AO-HBP-HG-ET (AO: abdominal obesity, HBP: High blood pressure or hypertension, HG: Hyperglycemia or T2DM: Elevated TAG) was the one with higher frequency of IR with 60,0% followed by AOHBP- LowH-ET presented 43,48% of IR and followed by all criteria with a prevalence similar IR of 43.33%. Conclusions: The MS showed a high prevalence in our population. Combinatorial frequently were the criteria presented elevated waist circumference, while less frequent lacked it. Similarly combinations with abdominal obesity were those that showed increased insulin resistance.spaCooperativa servicios y suministros 212518 RSRevista Latinoamericana de HipertensiónVol. 12, No.4 (2017)https://www.redalyc.org/articulo.oa?id=170253258003Síndrome MetabólicoCriterios diagnósticosResistencia a la insulinaFactores de riesgoEnfermedad cardiovascularMetabolic syndromeDiagnostic criteriaInsulin resistanceRisk factorsCardiovascular diseasePrevalencia de las combinaciones de componentes del síndrome metabólico en el municipio San Cristóbal, Táchira, VenezuelaPrevalence of combinations of metabolic syndrome components in the municipality of San Cristóbal, Táchira, Venezuelaarticlehttp://purl.org/coar/resource_type/c_6501Cornier MA, Dabelea D, Hernandez TL, et al. The metabolic syndrome. Endocr Rev. 2008; 29(7):777-822.Reaven GM. Banting lecture 1988. Role of insulin resistance in human disease. Diabetes. 1988; 37:1595–607.Souza MR, Diniz Mde F, Medeiros-Filho JE, Araújo MS. Metabolic syndrome and risk factors for non-alcoholic fatty liver disease. Arq Gastroenterol 2012; 49:89-96.Guerra F, Mancinelli L, Buglioni A, Pierini V, Rappelli A, at al. Microalbuminuria and left ventricular mass in overweight and obese hypertensive patients: role of the metabolic syndrome. High Blood Press Cardiovasc Prev 2011; 18:195-201.Aso Y, Wakabayashi S, Yamamoto R, Matsutomo R, Takebayashi K, Inukai T. Metabolic syndrome accompanied by hypercholesterolemia is strongly associated with proinflammatory state and impairement of fibrinolysis in patients with type 2 diabetes: synergistic effects of plasminogen activator inhibitor-1 and thrombinactivatable fibrinolysis inhibitor. Diabetes Care 2005; 28:2211-6.Gluszak O, Stopinska-Gluszak U, Glinicki P, Kapuscinska R, Snochowska H, et al. Phenotype and metabolic disorders in polycystic ovary syndrome. ISRN Endocrinol 2012; 2012:569862.Rask Madsen C, Kahn CR. Tissue-specific insulin signaling, metabolic syndrome, and cardiovascular disease. Arterioscler Thromb Vasc Biol 2012; 32(9):2052-9.Schmidt AM. Insulin resistance and metabolic syndrome: mechanisms and consequences. Arterioscler Thromb Vasc Biol 2012; 32(8):1753.Ruderman NB, Carling D, Prentki M, Cacicedo JM. AMPK, insulin resistance, and the metabolic syndrome. J Clin Invest. 2013; 123(7): 2764-72Ferrannini E. Metabolic syndrome: a solution in search of a problem. J Clin Endocrinol Metab 2007; 92:396-8Klein-Platat C, Drai J, Oujaa M, Schlienger JL, Simon C. Plasma fatty acid composition is associated with the metabolic syndrome and low-grade inflammation in overweight adolescents. Am J Clin Nutr 2005; 82:1178-84Matsuzawa Y, Funahashi T, Nakamura T. The concept of metabolic syndrome: contribution of visceral fat accumulation and its molecular mechanism. J Atheroscler Thromb 2011; 18:629-39.Yki-Järvinen H. Ectopic fat accumulation: an important cause of insulin resistance in humans. Journal of the Royal Society of Medicine 2002; 95(42):39-45.Heilbronn LK, Campbell LV. Adipose tissue macrophages, low grade inflammation and insulin resistance in human obesity. Curr Pharm Des 2008; 14(2): 1225-30.Herder C, Schneitler S, Rathmann W, Haastert B, Schneitler H, Winkler H, et al. Low-grade inflammation, obesity, and insulin resistance in adolescents. J Clin Endocrinol Metab. 2007;92:4569-74Ford ES. The metabolic syndrome and mortality from cardiovascular disease and all-causes: findings from the National Health and Nutrition Examination Survey II Mortality Study. Atherosclerosis. 2004; 173(2):309-14.Dutra ES, de Carvalho KM, Miyazaki E, Hamann EM, Ito MK. Metabolic syndrome in central Brazil: prevalence and correlates in the adult population. Diabetol Metab Syndr. 2012;4(1):20.Oliveira EP, Souza MLA, Lima MDA. Prevalência de syndrome metabólica em uma área rural do semi-árido baiano [Prevalence of metabolic syndrome in a semi-arid rural area in Bahia]. Arq Bras Endocrinol Metabol. 2006;50(3):456-65.Gregory CO, Dai J, Ramirez Zea M, Stein AD. Occupation is more important than rural or urban residence in explaining the prevalence of metabolic and cardiovascular disease risk in Guatemalan adults. J Nutr. 2007;137(5):1314-9Kim TN, Kim JM, Won JC, et al. A decision tree based approach for identifying urban-rural differences in metabolic syndrome risk factors in the adult Korean population. J Endocrinol Invest. 2012; 35(9):847-52.Lawes CM, Vander Hoorn S, Rodgers A, International Society of Hypertension. Global burden of blood-pressure-related disease, 2001. Lancet. 2008; 371(9623):1513-8.Wild S, Roglic G, Green A, Sicree R, King H. Global prevalence of diabetes: estimates for the year 2000 and projections for 2030. Diabetes Care. 2004; 27(5):1047-53.Kahn R, Buse J, Ferrannini E, et al. The metabolic syndrome: time for a critical appraisal: joint statement from the American Diabetes Association and the European Association for the Study of Diabetes. Diabetes Care. 2005; 28(9):2289-304.Reaven GM. The metabolic syndrome: is this diagnosis necessary? Am J Clin Nutr. 2006;83(6):1237-47.Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Executive Summary of The Third Report of The National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, And Treatment of High Blood Cholesterol In Adults (Adult Treatment Panel III). JAMA. 2001; 285(19):2486-97.Kuk JL, Ardern CI. Age and sex differences in the clustering of metabolic syndrome factors: association with mortality risk. Diabetes Care. 2010;33(11):2457-61.Grundy SM, Cleeman JI, Daniels SR, et al. Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation. 2005; 112(17):2735-52.Alberti K, Eckel RH, Grundy SM, et al. Harmonizing the metabolic syndrome: a joint interim statement of the international diabetes federation task force on epidemiology and prevention; national heart, lung, and blood institute; american heart association; world heart federation; international atherosclerosis society; and international association for the study of obesity. Circulation 2009, 120(16):1640–1645.Alberti KG, Zimmet P, Shaw J; IDF Epidemiology Task Force Consensus Group. The metabolic syndrome: a new worldwide definition. Lancet. 2005;366:1059 –1062.Guize L, Thomas F, Pannier B, Bean K, Jego B, Benetos A. All-cause mortality asso ciated with specific combinations of the metabolic syndrome according to recent definitions. Diabetes Care 2007;30:2381– 2387Qiao Q, Laatikainen T, Zethelius B, Stegmayr B, Eliasson M, Jousilahti P, Tuomilehto J. Comparison of definitions of metabolic syndrome in relation to the risk of developing stroke and coronary heart disease in Finnish and Swedish cohorts. Stroke 2009;40:337–343Hong Y, Jin X, Mo J, Lin HM, Duan Y, Pu M, Wolbrette DL, Liao D. Metabolic syndrome, its preeminent clusters, incident coronary heart disease and all-cause mortality— results of prospective analysis for the Atherosclerosis Risk in Communities study. J Intern Med 2007; 262: 113–122.Ford ES, Li C, Zhao G: Prevalence and correlates of metabolic syndrome based on a harmonious definition among adults in the US. J Diabetes 2010; 2:180-193.Gu D, Reynolds K, Wu X, Chen J, Duan X, Reynolds RF, Whelton PK, He J: Prevalence of the metabolic syndrome and overweight among adults in China. Lancet 2005, 365:1398-1405.Das M, Pal S, Ghosh A: Rural urban differences of cardiovascular disease risk factors in adult Asian Indians. Am J Hum Biol 2008, 20:440-445.Rojas J, Bermúdez V, Añez R, Salazar J, Humberto Sánchez H, Castellanos B, Bello L, Toledo A, Yaquelin Torres Y, Diego Fuenmayor D, Apruzzese V, Chacín M, Aguirre M, Villalobos M. Comportamiento Epidemiológico del síndrome metabólico en el municipio Maracaibo-Venezuela. Síndrome Cardiometabólico 2013; 3(2):31-42.Instituto nacional de estadística. XIV censo nacional de población y vivienda. Resultados por entidad federal y municipio del estado Táchira-Venezuela. (2013). Disponible en: http://www.ine.gov.ve/documentos/Demografia/CensodePoblacionyVivienda/ pdf/tachira.pdfSierra Bravo, M. Técnicas de investigación social: teoría y ejercicios. (1991). 7ma Edición. Madrid. Paraninfo.Méndez-Castellano H, De Méndez MC. Estratificación social y biología humana: método de Graffar modificado. Arch Ven Pueric Pediatr. 1986; 49:93–104.Health Statistics. NHANES III reference manuals and reports (CDROM). Hyattsville, MD: Centers for Disease Control and Prevention, 1996. Available at: http://www. cdc.gov/nchs/data/nhanes/nhanes3/cdrom/NCHS/MANUALS/ANTHRO.PDF.Friedewald WT., Levy R., Fredrickson DS. Estimation of plasma low-density lipoprotein without the use of a preparative ultracentrifugation. Clin Chem 1978; 18:499–502.Saely ChH, Koch L, Schmid F, Marte T, Aczel S, Langer P, et al. Adult Treatment Panel III 2001 but not International Diabetes Federation 2005 criteria of the metabolic syndrome predict clinical cardiovascular events in subjects who underwent coronary angiography. Diabetes Care 2006;29(4): 901- 7.Nigam A, Bourassa MG, Fortier A, Guertin MC, Tardif JC. The metabolic syndrome and its components and the longterm risk of death in patients with coronary heart disease. Am Heart J 2006;151:514-21.Tillin T, Forouhi NG, McKeigue PM, Chaturvedi N. The role of diabetes and components of the metabolic syndrome in stroke and coronary heart disease mortality in U.K. white and African-Caribbean populations. Diabetes Care 2006;29:2127- 9.Kadota A, Hozawa A, Okamura T, Kadowak T, Nakmaura K, Murakami Y, et al, for the NIPPON DATA research group. Relationship between metabolic risk factor clustering and cardiovascular mortality stratified by high blood glucose and obesity. Diabetes Care 2007;30:1533-8.Rosengren A, Hawken S, Ounpuu S, Sliwa K, Zubaid M, Almahmeed WA, et al. Association of psychosocial risk factors with risk of acute myocardial infarction in 11119 cases and 13648 controls from 52 countries (the INTERHEART study): case-control study. Lancet 2004;364:953-62.Giampaoli S, Palmieri L, Donfrancesco C, Panico S, Vanuzzo D, Cesana G, et al, on behalf of Research Group of the Progetto CUORE. The metabolic syndrome: aetiology, identifying criteria, pathologic anatomy, utility for CVD risk prediction – data from the Progetto CUORE. Eur Heart J 2006,27(Suppl): 852.Lakka HM, Laaksonen DE, Lakka TA, Niskanen LK, Kumpusalo E, Tuomilehto J, et al. The metabolic syndrome and total and cardiovascular disease mortality in middle-aged men. JAMA 2002; 288(21):2709-16.Wichai Aekplakorn, Pattapong Kessomboon, Rassamee Sangthong, Suwat Chariyalertsak, Panwadee Putwatana, Rungkarn Inthawong, Wannee Nitiyanant, Surasak Taneepanichskul and The NHES IV study group. Urban and rural variation in clustering of metabolic syndrome components in the Thai population: results from the fourth National Health Examination Survey 2009. BMC Public Health 2011, 11:854.Crystal Man Ying Lee, Rachel R Huxley, Mark Woodward, Paul Zimmet, Jonathan Shaw, Nam H Cho, Hyung Rae Kim, Satu Viali, Makoto Tominaga, Dorte Vistisen, Knut Borch-Johnsen, Stephen Colagiuri. The metabolic syndrome identifies a heterogeneous group of metabolic component combinations in the Asia-Pacific region. Diabetes Res Clin Pract 2008 9; 81(3):377-80.Pimenta AM, Felisbino-Mendes MS, Velasquez-Melendez G. Clustering and combining pattern of metabolic syndrome components in a rural Brazilian adult population. Sao Paulo Med J. 2013; 131(4):213-9.Salazar MR, Carbajal HA, Espeche WG, Dulbecco CA, Aizpurúa M, MArillet AG, Echeverría RF, REaven GM. Relationships among insulin resistance, obesity, diagnosis of the metabolic syndrome and cardio-metabolic risk. Diabetes Vasc Dis Res 2011;8:109-116.Lee K. Usefulness of the metabolic syndrome criteria as predictors of insulin resistance among obese Korean women. Public Health Nutr 2010; 13:181-6.Kocelak P, Chudek J, Olszanecka-Glinianowicz M. Prevalence of metabolic syndrome and insulin resistance in overweight and obese women according to different diagnostic criteria. Minerva Endocrinol 2012; 37:247-54.Sandeep S, Gokulakrishnan K, Velmurugan K, Deepa M, Mohan V. Visceral and Subcutaneous abdominal fat in relation to insulin resistance and metabolic syndrome in non-diabetic south Indians. Indian J Med Res 2010; 131: 629-635Raúl Ignacio Coniglio, Jorge Nellem, Norberto Sibechi, Osvaldo Colombo. Síndrome metabólico: frecuencia de sus componentes y riesgo global de cardiopatía coronaria. Acta Bioquímica Clínica Latinoamericana 2011; 45 (3, 2011)413-421.Sigüencia W, Alvarado O, Fernández S, Piedra C, Carrera G, Torres M, Ortiz R, Villalobos M, Rojas J, Añez R Bermúdez V. Prevalencia del síndrome metabólico en individuos adultos de las parroquias urbanas de la ciudad de Cuenca, Ecuador. Síndrome Cardiometabólico 2013; 3 (3): 113-125.LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://bonga.unisimon.edu.co/bitstreams/6b9cb007-4fa9-4bc0-ad9f-e60af489eb26/download8a4605be74aa9ea9d79846c1fba20a33MD5220.500.12442/1843oai:bonga.unisimon.edu.co:20.500.12442/18432019-04-11 21:51:42.281metadata.onlyhttps://bonga.unisimon.edu.coDSpace UniSimonbibliotecas@biteca.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 |