Discriminatory Capacity of Anthropometric Indices for Cardiovascular Disease in Adults: A Systematic Review and Meta-Analysis
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INTRODUCTION: Obesity is one of the main risk factors for cardiovascular disease (CVD) and cardiometabolic disease (CMD). Many studies have developed cutoff points of anthropometric indices for predicting these diseases. The aim of this systematic review was to differentiate the screening potential of body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR) for adult CVD risk. METHODS: statistic and Cochran's Q test. RESULTS: This meta-analysis included 38 cross-sectional and 2 cohort studies with 105 to 137,256 participants aged 18 or older. The pooled area under the ROC curve (AUC) value for BMI was 0.66 (95% CI, 0.63-0.69) in both men and women. The pooled AUC values for WC were 0.69 (95% CI, 0.67-0.70) in men and 0.69 (95% CI, 0.64-0.74) in women, and the pooled AUC values for WHR were 0.69 (95% CI, 0.66-0.73) in men and 0.71 (95% CI, 0.68-0.73) in women. CONCLUSION: Our findings indicated a slight difference between AUC values of these anthropometric indices. However, indices of abdominal obesity, especially WHR, can better predict CVD occurrence.
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Obesity is a risk factor for multiple outcomes such as cardiovascular disease, diabetes, chronic orthopedic problems, accidents, collagen vascular diseases, lower quality of life, osteoarthritis, and autoimmune disorders.
“Healthcare providers and public health agencies alike recognize obesity to be a risk factor for multiple outcomes such as cardiovascular disease, diabetes, chronic orthopedic problems, accidents, collagen vascular diseases, lower quality of life, osteoarthritis, and autoimmune disorders [13,14].”
From Advantages and Limitations of the Body Mass Index (BMI) to Assess Adult Obesity (2024) · cites this paper as [13]
The Introduction identifies obesity as a CVD risk factor, and the Discussion links excess fat accumulation to features of diabetes. The supplied passages do not support the additional claims about orthopedic problems, accidents, collagen vascular diseases, lower quality of life, osteoarthritis, or autoimmune disorders. Page numbers are not provided in our copy. (LLM, conf=0.88)
Experimental — accuracy not yet measuredWaist-to-hip ratio may be a better predictor of cardiovascular disease occurrence than BMI.
“The waist-to-hip ratio uses waist and hip circumference measurements and may be a better predictor of cardiovascular disease occurrence than BMI [13].”
From Advantages and Limitations of the Body Mass Index (BMI) to Assess Adult Obesity (2024) · cites this paper as [13]
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von Elm, E., Altman, D. G., Egger, M., Pocock, S. J., Gøtzsche, P. C., Vandenbroucke, J. P., & Initiative, F. T. S. (2007) · PLoS Medicine · doi:10.1371/journal.pmed.0040296 · Cited by 23,020 · see citing works
Wildman, R. P., Gu, D., Reynolds, K., Duan, X., & He, J. (2004) · The American Journal of Clinical Nutrition · doi:10.1093/ajcn/80.5.1129 · Cited by 265 · see citing works
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Research works printed but not linked: 66
- [1]McClellan M, Brown N, Califf RM, Warner JJ. Call to action: urgent challenges in cardiovascular disease: a presidential advisory from the American Heart Association. Circulation 2019; 139(9): e44– 54. 10.1161/CIR.0000000000000652 30674212 · DOI
- [2]Meier T, Gräfe K, Senn F, Sur P, Stangl GI, Dawczynski C, Cardiovascular mortality attributable to dietary risk factors in 51 countries in the WHO European Region from 1990 to 2016: a systematic analysis of the Global Burden of Disease Study. Eur J Epidemiol 2019; 34(1): 37– 55. 10.1007/s10654-018-0473-x 30547256 PMC6325999 · DOI
- [3]Roth GA, Johnson CO, Abate KH, Abd-Allah F, Ahmed M, Alam K,; Global Burden of Cardiovascular Diseases Collaboration. The burden of cardiovascular diseases among US states, 1990–2016. JAMA Cardiol 2018; 3(5): 375– 89. 10.1001/jamacardio.2018.0385 29641820 PMC6145754 · DOI
- [4]Adejumo EN, Adejumo AO, Azenabor A, Ekun AO, Enitan SS, Adebola OK, Anthropometric parameter that best predict metabolic syndrome in South west Nigeria. Diabetes Metab Syndr 2019; 13(1): 48– 54. 10.1016/j.dsx.2018.08.009 30641748 · DOI
- [5]Gupta N, Lteif A, Creo A, Iqbal AM, Pittock S, Tebben PJ,. Improved utilization of waist-to-height ratio in cardiometabolic risk counselling in children: application of DMAIC strategy. J Eval Clin Pract 2019; 25(2): 300– 5. 30378218
- [6]Weiler Miralles CS, Wollinger LM, Marin D, Genro JP, Contini V, Morelo Dal Bosco S. Waist-to-height ratio (WHtR) and triglyceride to HDL-C ratio (TG/HDL-c) as predictors of cardiometabolic risk. Nutr Hosp 2015; 31(5): 2115– 21. 25929382
- [7]Ouyang X, Lou Q, Gu L, Ko GT, Mo Y, Wu H, Anthropometric parameters and their associations with cardio-metabolic risk in Chinese working population. Diabetol Metab Syndr 2015; 7(1): 37. 10.1186/s13098-015-0032-5 25960779 PMC4424518 · DOI
- [8]Darbandi M, Najafi F, Pasdar Y, Rezaeian S. Structural equation model analysis for the evaluation of factors associated with overweight and obesity in menopausal women in RaNCD cohort study. Menopause 2020; 27(2): 208– 15. 10.1097/GME.0000000000001452 31895176 · DOI
- [9]Li SS, Pan S, Ma YT, Yang YN, Ma X, Li XM, Optimal cutoff of the waist-to-hip ratio for detecting cardiovascular risk factors among Han adults in Xinjiang. BMC Cardiovasc Disord 2014; 14(1): 93. 10.1186/1471-2261-14-93 25074400 PMC4122671 · DOI
- [10]Adab P, Pallan M, Whincup PH. Is BMI the best measure of obesity? BMJ 2018; 360: k1274. 10.1136/bmj.k1274 29599212 · DOI
- [11]Staiano AE, Bouchard C, Katzmarzyk PT. BMI-specific waist circumference thresholds to discriminate elevated cardiometabolic risk in White and African American adults. Obes Facts 2013; 6(4): 317– 24. 10.1159/000354712 23970141 PMC4343283 · DOI
- [13]Guan X, Sun G, Zheng L, Hu W, Li W, Sun Y. Associations between metabolic risk factors and body mass index, waist circumference, waist-to-height ratio and waist-to-hip ratio in a Chinese rural population. J Diabetes Investig 2016; 7(4): 601– 6. 10.1111/jdi.12442 27181937 PMC4931212 · DOI
- [14]Kim SH, Choi H, Won CW, Kim BS. Optimal cutoff points of anthropometric parameters to identify high coronary heart disease risk in Korean adults. J Korean Med Sci 2016; 31(1): 61– 6. 10.3346/jkms.2016.31.1.61 26770039 PMC4712581 · DOI
- [15]WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 2004; 363(9403): 157– 63. 10.1016/S0140-6736(03)15268-3 14726171 · DOI · Paper page
- [16]Ko KP, Oh DK, Min H, Kim CS, Park JK, Kim Y, Prospective study of optimal obesity index cutoffs for predicting development of multiple metabolic risk factors: the Korean genome and epidemiology study. J Epidemiol 2012; 22(5): 433– 9. 10.2188/jea.JE20110164 22955044 PMC3798638 · DOI
- [17]Moher D, Liberati A, Tetzlaff J, Altman DG; PRISMA Group. Preferred Reporting Items for Systematic Reviews and Meta-Analyses: the PRISMA statement. Ann Intern Med 2009; 151(4): 264– 9, W64. 10.7326/0003-4819-151-4-200908180-00135 19622511 · DOI · Paper page
- [18]Fisher M. Cardiometabolic disease: the new challenge? Pract Diabetes Int 2006; 23(3): 95– 7. 10.1002/pdi.909 · DOI
- [20]Bamber D. The area above the ordinal dominance graph and the area below the receiver operating characteristic graph. J Math Psychol 1975; 12(4): 387– 415. 10.1016/0022-2496(75)90001-2 · DOI
- [21]Hanley JA, McNeil BJ. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 1982; 143(1): 29– 36. 10.1148/radiology.143.1.7063747 7063747 · DOI · Paper page
- [22]Glaser A. High-yield biostatics, epidemiology and public health. 4th Edition. Philadelphia (PA): Lippincott, Williams & Wilkins; 2013.
- [23]Lalkhen AG, McCluskey A. Statistics V: introduction to clinical trials and systematic reviews. Contin Educ Anaesth Crit Care Pain 2008; 8(4): 143– 6. 10.1093/bjaceaccp/mkn023 · DOI
- [24]Tompuri TT, Lakka TA, Hakulinen M, Lindi V, Laaksonen DE, Kilpeläinen TO, Assessment of body composition by dual-energy X-ray absorptiometry, bioimpedance analysis and anthropometrics in children: the Physical Activity and Nutrition in Children study. Clin Physiol Funct Imaging 2015; 35(1): 21– 33. 10.1111/cpf.12118 24325400 · DOI
- [25]Jahanlou AS, Kouzekanani K. Appropriate cutoff points for body mass index and waist-to-hip ratio for a large sample of adult in Bandar Abbas, Iran. Zahedan J Res Med Sci 2016; 18(8). 10.17795/zjrms-7934 · DOI
- [26]Rashiti P, Elezi S, Behluli I, Mucaj S. Relationship of plasma adiponectin and waist-hip ratio with coronary artery disease. Med Arch 2016; 70(6): 413– 8. 10.5455/medarh.2016.70.413-418 28210011 PMC5292226 · DOI
- [27]Schlecht I, Fischer B, Behrens G, Leitzmann MF. Relations of visceral and abdominal subcutaneous adipose tissue, body mass index, and waist circumference to serum concentrations of parameters of chronic inflammation. Obes Facts 2016; 9(3): 144– 57. 10.1159/000443691 27241125 PMC5644901 · DOI
- [28]Neeland IJ, Ayers CR, Rohatgi AK, Turer AT, Berry JD, Das SR, Associations of visceral and abdominal subcutaneous adipose tissue with markers of cardiac and metabolic risk in obese adults. Obesity (Silver Spring) 2013; 21(9): E439– 47. 10.1002/oby.20135 23687099 PMC3751977 · DOI · Paper page
- [29]Monti V, Carlson JJ, Hunt SC, Adams TD. Relationship of ghrelin and leptin hormones with body mass index and waist circumference in a random sample of adults. J Am Diet Assoc 2006; 106(6): 822– 8, quiz 829–30. 10.1016/j.jada.2006.03.015 16720123 · DOI
- [30]Mazor R, Friedmann-Morvinski D, Alsaigh T, Kleifeld O, Kistler EB, Rousso-Noori L,. Cleavage of the leptin receptor by matrix metalloproteinase-2 promotes leptin resistance and obesity in mice. Sci Translat Med 2018; 10(455): 6324. PMC9678493 30135249
- [31]Cheong KC, Ghazali SM, Hock LK, Yusoff AF, Selvarajah S, Haniff J, Optimal waist circumference cut-off values for predicting cardiovascular risk factors in a multi-ethnic Malaysian population. Obes Res Clin Pract 2014; 8(2): e154– 62. 10.1016/j.orcp.2013.03.004 24743011 · DOI
- [32]Foucan L, Hanley J, Deloumeaux J, Suissa S. Body mass index (BMI) and waist circumference (WC) as screening tools for cardiovascular risk factors in Guadeloupean women. J Clin Epidemiol 2002; 55(10): 990– 6. 10.1016/S0895-4356(02)00430-4 12464375 · DOI
- [33]Hadaegh F, Zabetian A, Sarbakhsh P, Khalili D, James WPT, Azizi F. Appropriate cutoff values of anthropometric variables to predict cardiovascular outcomes: 7.6 years follow-up in an Iranian population. Int J Obes (Lond) 2009; 33(12): 1437– 45. 10.1038/ijo.2009.180 19752876 · DOI
- [34]Han TS, van Leer EM, Seidell JC, Lean ME. Waist circumference as a screening tool for cardiovascular risk factors: evaluation of receiver operating characteristics (ROC). Obes Res 1996; 4(6): 533– 47. 10.1002/j.1550-8528.1996.tb00267.x 8946438 · DOI
- [35]Haun DR, Pitanga FJG, Lessa I. [Waist-height ratio compared to other anthropometric indicators of obesity as predictors of high coronary risk]. Rev Assoc Med Bras (1992) 2009; 55(6): 705– 11. 10.1590/S0104-42302009000600015 20191225 · DOI
- [36]Samsen M, Hanchaiphiboolkul S, Puthkhao P, Tantirittisak T, Towanabut S. Appropriate body mass index and waist circumference cutoffs for middle and older age group in Thailand: data of 19,621 participants from Thai epidemiologic stroke (TES) study. J Med Assoc Thai 2012; 95(9): 1156– 66. 23140032
- [37]Siren R, Eriksson JG, Vanhanen H. Waist circumference a good indicator of future risk for type 2 diabetes and cardiovascular disease. BMC Public Health 2012; 12(1): 631. 10.1186/1471-2458-12-631 22877354 PMC3490795 · DOI
- [38]Talaei M, Thomas GN, Marshall T, Sadeghi M, Iranipour R, Oveisgharan S, Appropriate cut-off values of waist circumference to predict cardiovascular outcomes: 7-year follow-up in an Iranian population. Intern Med 2012; 51(2): 139– 46. 10.2169/internalmedicine.51.6132 22246480 · DOI
- [40]Lu Q, Xie Z, Zhang H, Ren J. Evaluation of the appropriate diagnostic threshold of waist circumference for the cardiometabolic syndrome in Chinese Uygur adults. J Cardiometab Syndr 2009; 4(2): 120– 5. 10.1111/j.1559-4572.2008.00045.x 19614800 · DOI
- [41]Mason C, Katzmarzyk PT. Waist circumference thresholds for the prediction of cardiometabolic risk: is measurement site important? Eur J Clin Nutr 2010; 64(8): 862– 7. 10.1038/ejcn.2010.82 20502472 · DOI
- [42]Pitanga FJ, Lessa I. Indicadores antropométricos de obesidade como instrumento de triagem para risco coronariano elevado em adultos na cidade de Salvador — Bahia. Arq Bras Cardiol 2005; 85(1): 26– 31. 10.1590/S0066-782X2005001400006 16041451 · DOI
- [43]Czernichow S, Kengne AP, Stamatakis E, Hamer M, Batty GD. Body mass index, waist circumference and waist-hip ratio: which is the better discriminator of cardiovascular disease mortality risk? Evidence from an individual-participant meta-analysis of 82,864 participants from nine cohort studies. Obes Rev 2011; 12(9): 680– 7. 10.1111/j.1467-789X.2011.00879.x 21521449 PMC4170776 · DOI
- [44]Lee CMY, Huxley RR, Wildman RP, Woodward M. Indices of abdominal obesity are better discriminators of cardiovascular risk factors than BMI: a meta-analysis. J Clin Epidemiol 2008; 61(7): 646– 53. 10.1016/j.jclinepi.2007.08.012 18359190 · DOI · Paper page
- [45]van Dijk SB, Takken T, Prinsen EC, Wittink H. Different anthropometric adiposity measures and their association with cardiovascular disease risk factors: a meta-analysis. Neth Heart J 2012; 20(5): 208– 18. 10.1007/s12471-011-0237-7 22231153 PMC3346869 · DOI
- [46]Cao Q, Yu S, Xiong W, Li Y, Li H, Li J, Waist-hip ratio as a predictor of myocardial infarction risk: a systematic review and meta-analysis. Medicine (Baltimore) 2018; 97(30): e11639. 10.1097/MD.0000000000011639 30045310 PMC6078643 · DOI
- [47]Cameron JD, Sigal RJ, Kenny GP, Alberga AS, Prud’homme D, Phillips P, Body composition and energy intake — skeletal muscle mass is the strongest predictor of food intake in obese adolescents: The HEARTY trial. Appl Physiol Nutr Metab 2016; 41(6): 611– 7. 10.1139/apnm-2015-0479 27111402 · DOI
- [48]Han TS, Al-Gindan YY, Govan L, Hankey CR, Lean MEJ. Associations of BMI, waist circumference, body fat, and skeletal muscle with type 2 diabetes in adults. Acta Diabetol 2019; 56(8): 947– 54. 10.1007/s00592-019-01328-3 30927105 PMC6597601 · DOI · Paper page
- [50]Takahashi MM, de Oliveira EP, Moreto F, Portero-McLellan KC, Burini RC. Association of dyslipidemia with intakes of fruit and vegetables and the body fat content of adults clinically selected for a lifestyle modification program. Arch Latinoam Nutr 2010; 60(2): 148– 54. 21425719
- [51]Zeng Q, He Y, Dong S, Zhao X, Chen Z, Song Z, Optimal cut-off values of BMI, waist circumference and waist:height ratio for defining obesity in Chinese adults. Br J Nutr 2014; 112(10): 1735– 44. 10.1017/S0007114514002657 25300318 · DOI
- [52]Lin WY, Lee LT, Chen CY, Lo H, Hsia HH, Liu IL, Optimal cut-off values for obesity: using simple anthropometric indices to predict cardiovascular risk factors in Taiwan. Int J Obes Relat Metab Disord 2002; 26(9): 1232– 8. 10.1038/sj.ijo.0802040 12187401 · DOI
- [53]Ho SY, Lam TH, Janus ED; Hong Kong Cardiovascular Risk Factor Prevalence Study Steering Committee. Waist to stature ratio is more strongly associated with cardiovascular risk factors than other simple anthropometric indices. Ann Epidemiol 2003; 13(10): 683– 91. 10.1016/S1047-2797(03)00067-X 14599732 · DOI
- [54]Mirmiran P, Esmaillzadeh A, Azizi F. Detection of cardiovascular risk factors by anthropometric measures in Tehranian adults: receiver operating characteristic (ROC) curve analysis. Eur J Clin Nutr 2004; 58(8): 1110– 8. 10.1038/sj.ejcn.1601936 15280905 · DOI
- [55]Pua YH, Ong PH. Anthropometric indices as screening tools for cardiovascular risk factors in Singaporeans: receiver operating characteristic curves analysis. Ann Acad Med Singapore 2004; 33(5, Suppl): S28– 30. 15651194
- [57]Mozumdar A, Roy SK. Validity of an alternative anthropometric trait as cardiovascular diseases risk factor: example from individuals with traumatic lower extremity amputation. Eur J Clin Nutr 2006; 60(10): 1180– 8. 10.1038/sj.ejcn.1602434 16708069 · DOI
- [58]Al-Lawati JA, Barakat NM, Al-Lawati AM, Mohammed AJ. 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 2008; 5(4): 304– 9. 10.3132/dvdr.2008.044 18958841 · DOI
- [59]Narisawa S, Nakamura K, Kato K, Yamada K, Sasaki J, Yamamoto M. Appropriate waist circumference cutoff values for persons with multiple cardiovascular risk factors in Japan: a large cross-sectional study. J Epidemiol 2008; 18(1): 37– 42. 10.2188/jea.18.37 18305365 PMC4771601 · DOI
- [60]de Almeida RT, Almeida MM, Araújo TM. Abdominal obesity and cardiovascular risk: performance of anthropometric indexes in women. Arq Bras Cardiol 2009; 92(5): 345– 50, 362–7, 375–80. 19629289
- [61]Yoshida D, Toyomura K, Fukumoto J, Ueda N, Ohnaka K, Adachi M, Waist circumference and cardiovascular risk factors in Japanese men and women. J Atheroscler Thromb 2009; 16(4): 431– 41. 10.5551/jat.No539 19672029 · DOI
- [62]Lee JS, Kawakubo K, Mori K, Akabayashi A. BMI specific waist circumference for detecting clusters of cardiovascular risk factors in a Japanese population. J Atheroscler Thromb 2010; 17(5): 468– 75. 10.5551/jat.3145 20057171 · DOI
- [63]Satoh H, Kishi R, Tsutsui H. Body mass index can similarly predict the presence of multiple cardiovascular risk factors in middle-aged Japanese subjects as waist circumference. Intern Med 2010; 49(11): 977– 82. 10.2169/internalmedicine.49.3006 20519812 · DOI
- [64]Katulanda P, Jayawardena MAR, Sheriff MH, Matthews DR. Derivation of anthropometric cut-off levels to define CVD risk in Sri Lankan adults. Br J Nutr 2011; 105(7): 1084– 90. 10.1017/S0007114510004563 21205381 · DOI
- [65]Suka M, Miwa Y, Ono Y, Yanagisawa H. BMI, waist circumference, and clustering of cardiovascular risk factors in Japanese adults. Environ Health Prev Med 2011; 16(2): 90– 6. 10.1007/s12199-010-0169-7 21432223 PMC3047660 · DOI
- [66]Wakabayashi I, Daimon T. Receiver-operated characteristics (ROCs) of the relationships between obesity indices and multiple risk factors (MRFs) for atherosclerosis at different ages in men and women. Arch Gerontol Geriatr 2012; 55(1): 96– 100. 10.1016/j.archger.2011.06.028 21871669 · DOI
- [67]Weng X, Liu Y, Ma J, Wang W, Yang G, Caballero B. Use of body mass index to identify obesity-related metabolic disorders in the Chinese population. Eur J Clin Nutr 2006; 60(8): 931– 7. 10.1038/sj.ejcn.1602396 16465198 · DOI
- [68]Matsushita Y, Tomita K, Yokoyama T, Mizoue T. Relations between waist circumference at four sites and metabolic risk factors. Obesity (Silver Spring) 2010; 18(12): 2374– 8. 10.1038/oby.2010.33 20186135 · DOI
- [69]Zandieh A, Esteghamati A, Morteza A, Noshad S, Khalilzadeh O, Gouya MM, Appropriate BMI cut-off values for identification of metabolic risk factors: third national surveillance of risk factors of non-communicable diseases in Iran (SuRFNCD-2007). Ann Hum Biol 2012; 39(6): 484– 9. 10.3109/03014460.2012.716860 22946480 · DOI
- [70]Aekplakorn W, Kosulwat V, Suriyawongpaisal P. Obesity indices and cardiovascular risk factors in Thai adults. Int J Obes (Lond) 2006; 30(12): 1782– 90. 10.1038/sj.ijo.0803346 16619055 · DOI
- [71]Yu J, Tao Y, Tao Y, Yang S, Yu Y, Li B, Optimal cut-off of obesity indices to predict cardiovascular disease risk factors and metabolic syndrome among adults in Northeast China. BMC Public Health 2016; 16(1): 1079. 10.1186/s12889-016-3694-5 27737656 PMC5062901 · DOI
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Advantages and Limitations of the Body Mass Index (BMI) to Assess Adult Obesity
Wu, Y., Li, D., & Vermund, S. H. (2024) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph21060757 · Cited by 332 · see citing works
“Healthcare providers and public health agencies alike recognize obesity to be a risk factor for multiple outcomes such as cardiovascular disease, diabetes, chronic orthopedic problems, accidents, collagen vascular diseases, lower quality of life, osteoarthritis, and autoimmune disorders [13,14].”
Background
- Authors
- Darbandi, M., Pasdar, Y., Moradi, S., Mohamed, H. J. J., Hamzeh, B., & Salimi, Y.
- Affiliations
- Kermanshah University of Medical Sciences (IR)
- Universiti Sains Malaysia (MY)
- Corresponding author
- Darbandi, Mitra
- Venue
- Preventing Chronic Disease
- Published
- 2020-10-22
- Volume
- 17
- Pages
- E131-E131
- ISSN
- 1545-1151 (ISSN-L)
- PMC
- PMC7587303
- OpenAlex
- W3093792159
- Cited by
- 76
- References
- 2
- Citations by year
- 2026: 13 · 2025: 19 · 2024: 16 · 2023: 10 · 2022: 9 · 2021: 8 · 2020: 1
- FWCI
- 1.07
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- public-domain
- Locations
- Preventing Chronic Disease (publishedVersion, public-domain)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- Kermanshah University of Medical Sciences
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
- Health Sciences › Medicine › Physiology › Body Composition Measurement Techniques
- Keywords
- cardiovascular disease, anthropometric indices, body mass index, waist circumference, waist-to-hip ratio, abdominal obesity, cardiovascular risk prediction, area under the ROC curve, cardiometabolic disease, obesity
- MeSH terms
- Cardiometabolic Risk Factors, Adult, Cardiovascular Diseases, Female, Humans, Male, Reference Standards, ROC Curve, Body Mass Index, Risk Assessment, Waist-Hip Ratio, Waist Circumference
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