Medidas antropométricas de obesidad general y central y capacidad discriminativa sobre el riesgo cardiovascular: estudio RICARTO
Tài liệu tham khảo
WHO. Obesity and overweight. WHO [consultado 7 Abr 2016]. Disponible en: http://www.who.int/mediacentre/factsheets/fs311/en/
2002, 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) final report, Circulation., 106, 3143, 10.1161/circ.106.25.3143
Cornier, 2011, Assessing adiposity: A scientific statement from the American Heart Association, Circulation., 124, 1996, 10.1161/CIR.0b013e318233bc6a
Goh, 2014, Anthropometric measurements of general and central obesity and the prediction of cardiovascular disease risk in women: A cross-sectional study, BMJ Open., 4
Sims, 2001, Are there persons who are obese, but metabolically healthy?, Metabolism., 50, 1499, 10.1053/meta.2001.27213
Blüher, 2010, The distinction of metabolically “healthy” from “unhealthy” obese individuals, Curr Opin Lipidol., 21, 38, 10.1097/MOL.0b013e3283346ccc
Ruderman, 1998, The metabolically obese, normal-weight individual revisited, Diabetes., 47, 699, 10.2337/diabetes.47.5.699
Romero-Corral, 2010, Normal weight obesity: A risk factor for cardiometabolic dysregulation and cardiovascular mortality, Eur Heart J., 31, 737, 10.1093/eurheartj/ehp487
De Lorenzo, 2007, Normal-weight obese syndrome: Early inflammation?, Am J Clin Nutr., 85, 40, 10.1093/ajcn/85.1.40
Schneider, 2007, Accuracy of anthropometric indicators of obesity to predict cardiovascular risk, J Clin Endocrinol Metab., 92, 589, 10.1210/jc.2006-0254
Gallagher, 1996, How useful is body mass index for comparison of body fatness across age, sex, and ethnic groups?, Am J Epidemiol., 143, 228, 10.1093/oxfordjournals.aje.a008733
Fernández, 2003, Is percentage body fat differentially related to body mass index in Hispanic Americans, African Americans, and European Americans?, Am J Clin Nutr., 77, 71, 10.1093/ajcn/77.1.71
De Koning, 2007, Waist circumference and waist-to-hip ratio as predictors of cardiovascular events: Meta-regression analysis of prospective studies, Eur Heart J., 28, 850, 10.1093/eurheartj/ehm026
Mason, 2009, Effect of the site of measurement of waist circumference on the prevalence of the metabolic syndrome, Am J Cardiol., 103, 1716, 10.1016/j.amjcard.2009.02.018
Wang, 2003, Comparisons of waist circumferences measured at 4 sites, Am J Clin Nutr., 77, 379, 10.1093/ajcn/77.2.379
Lee, 2008, Indices of abdominal obesity are better discriminators of cardiovascular risk factors than BMI: A meta-analysis, J Clin Epidemiol., 61, 646, 10.1016/j.jclinepi.2007.08.012
Motamed, 2015, Conicity index and waist-to-hip ratio are superior obesity indices in predicting 10-year cardiovascular risk among men and women, Clin Cardiol., 38, 527, 10.1002/clc.22437
Ohrvall, 2000, Sagittal abdominal diameter compared with other anthropometric measurements in relation to cardiovascular risk, Int J Obes Relat Metab Disord J Int Assoc Study Obes., 24, 497, 10.1038/sj.ijo.0801186
Mukuddem-Petersen, 2006, Sagittal abdominal diameter: No advantage compared with other anthropometric measures as a correlate of components of the metabolic syndrome in elderly from the Hoorn Study, Am J Clin Nutr., 84, 995, 10.1093/ajcn/84.5.995
Jensen, 2014, 2013 AHA/ACC/TOS guideline for the management of overweight and obesity in adults: A report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and The Obesity Society, Circulation., 129, S102
Rodríguez-Roca, 2018, Justificación, objetivos y diseño metodológico del estudio RICARTO (RIesgo CARdiovascular y eventos cardiovasculares en la población general del área sanitaria de TOledo), Semergen., 44, 107, 10.1016/j.semerg.2017.04.007
Panagiotakos, 2006, Dietary patterns: A Mediterranean diet score and its relation to clinical and biological markers of cardiovascular disease risk, Nutr Metab Cardiovasc Dis., 16, 559, 10.1016/j.numecd.2005.08.006
Valdez, 1991, A simple model-based index of abdominal adiposity, J Clin Epidemiol., 44, 955, 10.1016/0895-4356(91)90059-I
2017, Standards of Medical Care in Diabetes-2017: Summary of Revisions, Diabetes Care., 40, S4
Mills, 2016, Global disparities of hypertension prevalence and control. Clinical perspective, Circulation., 134, 441, 10.1161/CIRCULATIONAHA.115.018912
Levey, 2009, A new equation to estimate glomerular filtration rate, Ann Intern Med., 150, 604, 10.7326/0003-4819-150-9-200905050-00006
D’Agostino, 2008, General cardiovascular risk profile for use in primary care: The Framingham Heart Study, Circulation., 117, 743, 10.1161/CIRCULATIONAHA.107.699579
Hanley, 1983, A method of comparing the areas under receiver operating characteristic curves derived from the same cases, Radiology., 148, 839, 10.1148/radiology.148.3.6878708
Heston, 2011, Standardizing predictive values in diagnostic imaging research, J Magn Reson Imaging., 33, 10.1002/jmri.22466
Altman, 1994, Statistics notes: Diagnostic tests 2: Predictive values, BMJ., 309, 102, 10.1136/bmj.309.6947.102
Glas, 2003, The diagnostic odds ratio: A single indicator of test performance, J Clin Epidemiol., 56, 1129, 10.1016/S0895-4356(03)00177-X
2015, Estudios de exactitud diagnóstica: Herramientas para su interpretación, Rev Chil Radiol., 21, 158
Kim, 2016, Optimal cut-off points of anthropometric parameters to identify high coronary heart disease risk in Korean adults, J Korean Med Sci., 31, 61, 10.3346/jkms.2016.31.1.61
Chen, 2007, Anthropometric measures and absolute cardiovascular risk estimates in the Australian Diabetes, Obesity and Lifestyle (AusDiab) Study, Eur J Cardiovasc Prev Rehabil., 14, 740, 10.1097/HJR.0b013e32816f7739
Al-Lawati, 2008, Optimal cut-points for body mass index, waist circumference and waist-to-hip ratio using the Framingham coronary heart disease risk score in an Arab population of the Middle East, Diab Vasc Dis Res., 5, 304, 10.3132/dvdr.2008.044
Gu, 2018, Body mass index, waist circumference, and waist-to-height ratio for prediction of multiple metabolic risk factors in Chinese elderly population, Sci Rep., 8, 10.1038/s41598-017-18854-1
Seo, 2017, 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., 97, 100, 10.1016/j.ypmed.2017.01.012
Yang, 2017, Waist-to-height ratio is better than body mass index and waist circumference as a screening criterion for metabolic syndrome in Han Chinese adults, Med U S., 96
Luz, 2016, Waist circumference, body mass index and waist-height ratio: Are two indices better than one for identifying hypertension risk in older adults?, Prev Med., 93, 76, 10.1016/j.ypmed.2016.09.024
Vidal Martins, 2015, Anthropometric indicators of obesity as predictors of cardiovascular risk in the elderly, Nutr Hosp., 31, 2583
Ashwell, 2005, Six reasons why the waist-to-height ratio is a rapid and effective global indicator for health risks of obesity and how its use could simplify the international public health message on obesity, Int J Food Sci Nutr., 56, 303, 10.1080/09637480500195066
Berg, 2005, Adipose tissue, inflammation, and cardiovascular disease, Circ Res., 96, 939, 10.1161/01.RES.0000163635.62927.34
Romero-Corral, 2008, Accuracy of body mass index in diagnosing obesity in the adult general population, Int J Obes 2005, 32, 959
Sangrós, 2018, Asociación de obesidad general y abdominal con hipertensión, dislipemia y presencia de prediabetes en el estudio PREDAPS, Rev Esp Cardiol., 71, 170, 10.1016/j.recesp.2017.04.010
Wormser, 2011, Separate and combined associations of body-mass index and abdominal adiposity with cardiovascular disease: Collaborative analysis of 58 prospective studies, Lancet., 377, 1085, 10.1016/S0140-6736(11)60105-0
Van Dis, 2009, Body mass index and waist circumference predict both 10-year nonfatal and fatal cardiovascular disease risk: Study conducted in 20,000 Dutch men and women aged 20-65years, Eur J Cardiovasc Prev Rehabil., 16, 729, 10.1097/HJR.0b013e328331dfc0
Hartwig, 2016, Anthropometric markers and their association with incident type2 diabetes mellitus: Which marker is best for prediction? Pooled analysis of four German population-based cohort studies and comparison with a nationwide cohort study, BMJ Open., 6, e009266, 10.1136/bmjopen-2015-009266
