The association between metabolic syndrome and anthropometric measurements in Iranian professional drivers: a cross-sectional analysis from shahroud drivers cohort study (SDCS)

Alberti K, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, 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):1640–5.

PubMed  CAS  Google Scholar 

Cameron AJSJ, Zimmet PZ. Prevalence in worldwide populations. Endocrinology and metabolism clinics of North America. Metabolic Syndrome. 2004;33(2):351–75.

Google Scholar 

Chen X, He C, Ma Y, Yang Y, Liu F, Ma X, et al. Association of metabolic syndrome with various anthropometric and atherogenic parameters in the Kazakh population in China. Lipids Health Dis. 2016;15(1):1–7.

Google Scholar 

Cheong KC, Ghazali SM, Hock LK, Yusoff AF, Selvarajah S, Haniff J, et al. 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.

PubMed  Google Scholar 

Ouyang X, Lou Q, Gu L, Ko GT, Mo Y, Wu H, et al. Anthropometric parameters and their associations with cardio-metabolic risk in Chinese working population. Diabetol Metab Syndr. 2015;7(1):1–7.

CAS  Google Scholar 

Vanita P, Jhansi K. Metabolic syndrome in endocrine system. J Diabetes Metab. 2011;2(163):2.

Google Scholar 

Mazloomzadeh S, Khazaghi ZR, Mousavinasab N. The prevalence of metabolic syndrome in iran: a systematic review and meta-analysis. Iran J Public Health. 2018;47(4):473.

PubMed  PubMed Central  Google Scholar 

Guize L, Pannier B, Thomas F, Bean K, Jégo B, Benetos A. Recent advances in metabolic syndrome and cardiovascular disease. Arch Cardiovasc Dis. 2008;101(9):577–83.

PubMed  Google Scholar 

Hanley A, Karter A, Williams K, Festa A, D′ Agostino RB Jr, Wagenknecht LE, et al. Prediction of type 2 diabetes mellitus with alternative definitions of the metabolic syndrome: the insulin resistance atherosclerosis study. Circulation. 2005;112:3713–21.

PubMed  Google Scholar 

Grundy SM, Brewer HB Jr, Cleeman JI, Smith SC Jr, Lenfant C. Definition of metabolic syndrome: report of the National Heart, Lung, and Blood Institute/American Heart Association conference on scientific issues related to definition. Circulation. 2004;109(3):433-8.

Hirata RP, Sampaio LMM, Leitao Filho FSS, Braghiroli A, Balbi B, Romano S et al. General characteristics and risk factors of cardiovascular disease among interstate bus drivers. The Scientific World Journal. 2012;2012.

Pozo-Hernández CE, Delgado-Santos NY, Guamialamá-Arévalo SA, Lomas-Males DM. Factores de Riesgo asociados a síndrome metabólico En Choferes profesionales [Risk factors associated with metabolic syndrome in professional drivers]. Sanitas Revista Arbitrada De Ciencias De La Salud. 2024;3(especial):25–33.

Google Scholar 

Ebrahimi MH, Delvarianzadeh M, Saadat SJD, Research MSC, Reviews. Prevalence of metabolic syndrome among Iranian occupational drivers. 2016;10(1):S46–51.

Bener A, Yousafzai MT, Darwish S, Al-Hamaq AO, Nasralla EA, Abdul-Ghani M. Obesity index that better predict metabolic syndrome: body mass index, waist circumference, waist hip ratio, or waist height ratio. Journal of obesity. 2013;2013.

Obeidat AA, Ahmad MN, Haddad FH, Azzeh FS. Evaluation of several anthropometric indices of obesity as predictors of metabolic syndrome in Jordanian adults. Nutr Hosp. 2015;32(2):667–77.

PubMed  Google Scholar 

Rajput R, Rajput M, Bairwa M, Singh J, Saini O, Shankar V. Waist height ratio: A universal screening tool for prediction of metabolic syndrome in urban and rural population of Haryana. Indian J Endocrinol Metabol. 2014;18(3):394.

Google Scholar 

Shabazian H, Latifi SM, Pipelzadeh MH. Efficiency of anthropometric indices in predicting metabolic syndrome among adult population of Ahvaz. Iran Age. 2015;44(142):405–135.

Google Scholar 

Hamzeh B, Bagheri A, Pasdar Y, Darbandi M, Rezaeian S, Najafi F, et al. Predicting metabolic syndrome by anthropometric measures among adults 35–65 years in the West of iran; a cross sectional study from an Iranian RaNCD cohort data. Diabetes Metabolic Syndrome: Clin Res Reviews. 2020;14(5):1293–8.

Google Scholar 

Molarius A, Seidell J. Selection of anthropometric indicators for classification of abdominal fatness—a critical review. Int J Obes. 1998;22(8):719–27.

CAS  Google Scholar 

Lysen L, Israel D. Nutrition in weight management. Krause’s food and the nutrition care process. 2012;13:462– 88.

Caballero B. Encyclopedia of human nutrition. Elsevier; 2005.

Eaton–Evans J, iEoHNSE. 2005. NUTRITIONAL ASSESSMENT| Anthropometry.

Ahbab S, Ataoğlu HE, Tuna M, Karasulu L, Çetin F, Temiz LÜ, et al. Neck circumference, metabolic syndrome and obstructive sleep apnea syndrome; evaluation of possible linkage. Med Sci Monitor: Int Med J Experimental Clin Res. 2013;19:111.

CAS  Google Scholar 

Hoebel S, Malan L, De Ridder JH. Determining cut-off values for neck circumference as a measure of the metabolic syndrome amongst a South African cohort: the SABPA study. Endocrine. 2012;42(2):335–42.

PubMed  CAS  Google Scholar 

Obirikorang C, Obirikorang Y, Acheampong E, Anto EO, Toboh E, Asamoah EA et al. Association of wrist circumference and waist-to-height ratio with cardiometabolic risk factors among type II diabetics in a Ghanaian population. 2018;2018.

Capizzi M, Leto G, Petrone A, Zampetti S, Papa RE, Osimani M, et al. Wrist circumference is a clinical marker of insulin resistance in overweight and obese children and adolescents. Circulation. 2011;123(16):1757–62.

PubMed  Google Scholar 

Jahangiri Noudeh Y, Hadaegh F, Vatankhah N, Momenan AA, Saadat N, Khalili D, et al. Wrist circumference as a novel predictor of diabetes and prediabetes: results of cross-sectional and 8.8-year follow-up studies. J Clin Endocrinol Metabolism. 2013;98(2):777–84.

Google Scholar 

Namazi N, Djalalinia S, Mahdavi-Gorabi A, Asayesh H, Mansourian M, Noroozi M, et al. Association of wrist circumference with cardio-metabolic risk factors: a systematic review and meta-analysis. Eat Weight Disorders-Studies Anorexia Bulimia Obes. 2020;25(1):151–61.

Google Scholar 

Alberti KGMM, Zimmet P, Shaw J. Metabolic syndrome—a new world-wide definition. A consensus statement from the international diabetes federation. Diabet Med. 2006;23(5):469–80.

PubMed  CAS  Google Scholar 

Delvarianzadeh M, Abbasian M, Khosravi F, Ebrahimi H, Ebrahimi MH, Fazli M. Appropriate anthropometric indices of obesity and overweight for diagnosis of metabolic syndrome and its relationship with oxidative stress. Diabetes & Metabolic Syndrome: Clinical Research & Reviews. 2017;11:S907-S11.

Mabry JE, Hosig K, Hanowski R, Zedalis D, Gregg J, Herbert WG. Prevalence of metabolic syndrome in commercial truck drivers: a review. J Transp Health. 2016;3(3):413–21.

Google Scholar 

Fan S, Yang B, Zhi X, He J, Ma P, Yu L, et al. Neck circumference associated with arterial blood pressures and hypertension: A cross-sectional community-based study in Northern Han Chinese. Sci Rep. 2017;7(1):1–8.

Google Scholar 

Guan X, Sun G, Zheng L, Hu W, Li W, Sun YJJ. 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. 2016;7(4):601–6.

Parker ED, Pereira MA, Stevens J, Folsom ARJA. Association of hip circumference with incident diabetes and coronary heart disease: the atherosclerosis risk in communities study. 2009;169(7):837–47.

Molina-Luque R, Romero-Saldaña M, Álvarez-Fernández C, Rodríguez-Guerrero E, Hernández-Reyes A. Molina-Recio gjsr. Waist to height ratio and metabolic syndrome as lung dysfunction predictors. 2020;10(1):1–8.

He Y-H, Chen Y-C, Jiang G-X, Huang H-E, Li R, Li X-Y, et al. Evaluation of anthropometric indices for metabolic syndrome in Chinese adults aged 40 years and over. Eur J Nutr. 2012;51(1):81–7.

PubMed  Google Scholar 

Rochlani Y, Pothineni NV, Kovelamudi S, Mehta JL. Metabolic syndrome: pathophysiology, management, and modulation by natural compounds. Ther Adv Cardiovasc Dis. 2017;11(8):215–25.

PubMed  PubMed Central  CAS  Google Scholar 

Bowers LJ. Assessment of nutritional status. In: Mootz RDVH, editor. Best practices in clinical chiropractic. USA: ASPEN Publication; 1999. p. 70.

Google Scholar 

Lagua RT, Claudio VS, Richardson PJAJCN. Nutr Diet Therapy Ref Dict. 1996;64(1):124.

Google Scholar 

Millar SRPI, Phillips CM. doi: 10.1186/s13098-015-0069-5. eCollection. 2015. Assessing cardio metabolic risk in middle-aged adults using body mass index and waist-height ratio: are two indices better than one? A cross-sectional study. Diabetol Metab Syndr. 2015;7:73.

Karakaş P, Bozkır MG. Anthropometric indices in relation to overweight and obesity among Turkish medical students. Archives Med Science: AMS. 2012;8(2):209.

PubMed Central  Google Scholar 

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.

PubMed  CAS  Google Scholar 

Lin W, Lee L, Chen C, Lo H, Hsia H, Liu I et al. Optimal cut-off values for obesity: using simple anthropometric indices to predict cardiovascular risk factors in Taiwan. 2002;26(9):1232–8.

Tian T, Zhang J, Zhu Q, Xie W, Wang Y, Dai Y. Predicting value of five anthropometric measures in metabolic syndrome among Jiangsu province, China. BMC Public Health. 2020;20(1):1–9.

Google Scholar 

Vazquez G, Duval S, Jacobs DR Jr, Silventoinen K. Comparison of body mass index, waist circumference, and waist/hip ratio in predicting incident diabetes: a meta-analysis. Epidemiol Rev. 2007;29(1):115–28.

PubMed  Google Scholar 

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