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Original Research

Evaluation of Anthropometric Indices and Lipid Parameters to Predict Metabolic Syndrome Among Adults in Mexico

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Pages 691-701 | Published online: 16 Feb 2021

References

  • Forouzanfar MH , Afshin A , Alexander LT , et al. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet . 2016;388(10053):1659–1724.27733284
  • de Salud S ; Instituto Nacional de Salud Pública, Instituto Nacional de Estadística y Geografía. Encuesta Nacional de Salud y Nutrición (ENSANUT) 2018. Presentación De Resultados . 2018.
  • Alberti K , Eckel RH , Grundy SM . International diabetes federation task force on epidemiology and prevention; national heart, lung, and blood institute; American heart association; world heart federation; international atherosclerosis society; international association for the study of obesity: 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;120:1640–1645. doi:10.1161/CIRCULATIONAHA.109.192644 19805654
  • Bozkurt B , Aguilar D , Deswal A , et al. Contributory risk and management of comorbidities of hypertension, obesity, diabetes mellitus, hyperlipidemia, and metabolic syndrome in chronic heart failure: a scientific statement from the American Heart Association. Circulation . 2016;134(23):e535–e578. doi:10.1161/CIR.0000000000000450 27799274
  • Adejumo EN , Adejumo AO , Azenabor A , et al. Anthropometric parameter that best predict metabolic syndrome in South west Nigeria. Diabetes Metab Syndr . 2019;13(1):48–54. doi:10.1016/j.dsx.2018.08.009 30641748
  • Wang H , Liu A , Zhao T , 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):e016062. doi:10.1136/bmjopen-2017-016062
  • Elsayed EF , Sarnak MJ , Tighiouart H , et al. Waist-to-hip ratio, body mass index, and subsequent kidney disease and death. Am J Kidney Dis . 2008;52(1):29–38. doi:10.1053/j.ajkd.2008.02.363 18511168
  • Nimmanapalli HD , Kasi AD , Devapatla P , Nuttakki V . Lipid ratios, atherogenic coefficient and atherogenic index of plasma as parameters in assessing cardiovascular risk in type 2 diabetes mellitus. Int J Res Med Sci . 2016;4(7):2863–2869. doi:10.18203/2320-6012.ijrms20161966
  • Aguilar-Morales I , Colin-Ramirez E , Rivera-Mancía S , Vallejo M , Vázquez-Antona C . Performance of waist-to-height ratio, waist circumference, and body mass index in discriminating cardio-metabolic risk factors in a sample of school-aged Mexican children. Nutrients . 2018;10(12):1850. doi:10.3390/nu10121850
  • Gnatiuc L , Alegre-Díaz J , Wade R , et al. General and abdominal adiposity and mortality in Mexico City: a prospective study of 150 000 adults. Ann Intern Med . 2019;171(6):397–405. doi:10.7326/M18-3502 31404923
  • Wei M , Gaskill SP , Haffner SM , Stern MP . Waist circumference as the best predictor of Noninsulin Dependent Diabetes Mellitus (NIDDM) compared to body mass index, waist/hip ratio and other anthropometric measurements in Mexican Americans—a 7-year prospective study. Obes Res . 1997;5(1):16–23. doi:10.1002/j.1550-8528.1997.tb00278.x 9061711
  • Rodea-Montero ER , Evia-Viscarra ML , Apolinar-Jiménez E . Waist-to-height ratio is a better anthropometric index than waist circumference and BMI in predicting metabolic syndrome among obese mexican adolescents. Int J Endocrinol . 2014;2014:195407. doi:10.1155/2014/195407 25574166
  • Xia C , Li R , Zhang S , et al. Lipid accumulation product is a powerful index for recognizing insulin resistance in non-diabetic individuals. Eur J Clin Nutr . 2012;66(9):1035–1038. doi:10.1038/ejcn.2012.83 22781025
  • Wakabayashi I , Daimon T . The “cardiometabolic index” as a new marker determined by adiposity and blood lipids for discrimination of diabetes mellitus. Clin Chim Acta . 2015;438:274–278. doi:10.1016/j.cca.2014.08.042 25199852
  • Bhardwaj S , Bhattacharjee J , Bhatnagar M , Tyagi S . Atherogenic index of plasma, castelli risk index and atherogenic coefficient-new parameters in assessing cardiovascular risk. Int J Pharm Biol Sci . 2013;3(3):359–364.
  • Scheaffer RL , Mendenhall W , Ott RL , Gerow KG . Elementary survey sampling. Cengage Learn . 2011.
  • WHO. Physical status: the use of and interpretation of anthropometry, Report of a WHO Expert Committee. 1995.
  • Pickering TG , Hall JE , Appel LJ , et al. Recommendations for blood pressure measurement in humans and experimental animals: part 1: blood pressure measurement in humans: a statement for professionals from the Subcommittee of Professional and Public Education of the American Heart Association Council on high blood pressure research. Circulation . 2005;111(5):697–716. doi:10.1161/01.CIR.0000154900.76284.F6 15699287
  • Gutiérrez-Solis AL , Datta Banik S , Méndez-González RM . Prevalence of metabolic syndrome in mexico: a systematic review and meta-analysis. Metab Syndr Relat Disord . 2018;16(8):395–405. doi:10.1089/met.2017.0157 30063173
  • Isordia-Salas I , Santiago-Germán D , Rodrìguez-Navarro H , et al. Prevalence of metabolic syndrome components in an urban Mexican sample: comparison between two classifications. Exp Diabetes Res . 2011;2012:2012. doi:10.1155/2012/202540
  • van Vliet-ostaptchouk JV , Nuotio M-L , Slagter SN , et al. The prevalence of metabolic syndrome and metabolically healthy obesity in Europe: a collaborative analysis of ten large cohort studies. BMC Endocr Disord . 2014;14(1):9. doi:10.1186/1472-6823-14-9 24484869
  • Sigit F , Tahapary D , Sartono E , et al. The prevalence of metabolic syndrome and its association with body fat distribution in a Dutch and Indonesian population. Atherosclerosis . 2019;287:e135–e136. doi:10.1016/j.atherosclerosis.2019.06.400
  • Lee EY , Han K , Kim DH , et al. Exposure-weighted scoring for metabolic syndrome and the risk of myocardial infarction and stroke: a nationwide population-based study. Cardiovasc Diabetol . 2020;19(1):1–12. doi:10.1186/s12933-020-01129-x 31910850
  • Banik SD , Cardoza RH , González RMM , Solis ALG . Fasting plasma glucose, lipid ratios, and atherogenic coefficient are the risk factors for hypertension in chronic kidney disease patients on hemodialysis: a report from the Regional High Speciality Hospital of Peninsular Yucatan, Mexico. Anthropol Rev . 2020;83(3):251–260. doi:10.2478/anre-2020-0019
  • Gurka MJ , Filipp SL , DeBoer MD . Geographical variation in the prevalence of obesity, metabolic syndrome, and diabetes among US adults. Nutr Diabetes . 2018;8(1):1–8. doi:10.1038/s41387-018-0024-2 29330446
  • Murguía-Romero M , Jiménez-Flores JR , Sigrist-Flores SC , et al. Prevalence of metabolic syndrome in young Mexicans: a sensitivity analysis on its components. Nutr Hosp . 2015;32(1):189–195. doi:10.3305/nh.2015.32.1.9031 26262716
  • Rojas R , Aguilar-Salinas CA , Jiménez-Corona A , et al. Metabolic syndrome in Mexican adults: results from the National Health and Nutrition Survey 2006. Salud Publica Mex . 2010;52(Suppl 1):S11–18. doi:10.1590/S0036-36342010000700004 20585723
  • Castro-Sansores Carlos JH-EV , Arjona-Villicaña R . Prevalencia de Síndrome Metabólico en sujetos adultos que viven en Mérida, Yucatán, México. Rev Biomed . 2011;22:49–58.
  • Grundy SM , Brewer HB , Cleeman JI , Smith SC , 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):433–438. doi:10.1161/01.CIR.0000111245.75752.C6 14744958
  • Llinás MG , Janer PE , Agudo SG , Casquero RG , González IC . Utilidad en enfermería de diferentes índices antropométricos y analíticos para valorar la existencia de síndrome metabólico con los criterios NCEP ATPIII e IDF en población mediterránea española. Medicina Balear . 2017;32(1):26–34.
  • Sinaga M , Worku M , Yemane T , et al. Optimal cut-off for obesity and markers of metabolic syndrome for Ethiopian adults. Nutr J . 2018;17(1):109. doi:10.1186/s12937-018-0416-0 30466421
  • Hastuti J , Kagawa M , Byrne NM , Hills AP . Determination of new anthropometric cut-off values for obesity screening in Indonesian adults. Asia Pac J Clin Nutr . 2017;26(4):650–656. doi:10.6133/apjcn.072016.09 28582815
  • He J , Ma R , Liu J , et al. The optimal ethnic-specific waist-circumference cut-off points of metabolic syndrome among low-income rural Uyghur adults in Far western China and implications in preventive public health. Int J Environ Res . 2017;14(2):158.
  • Banik SD , Dickinson F . Waist circumference cut-off in relation to body mass index and percentage of body fat in adult women from Merida, Mexico. Anthropol Anz . 2015;72(4):369–383. doi:10.1127/anthranz/2015/0525 26425848
  • Domínguez-Reyes T , Quiroz-Vargas I , Salgado-Bernabé AB , Salgado-Goytia L , Muñoz-Valle JF , Parra-Rojas I . Las medidas antropométricas como indicadores predictivos de riesgo metabólico en una población mexicana. Nutr Hosp . 2017;34(1):96–101. doi:10.20960/nh.983 28244778
  • Hosseinpanah F , Barzin M , Mirbolouk M , Abtahi H , Cheraghi L , Azizi F . Lipid accumulation product and incident cardiovascular events in a normal weight population: Tehran Lipid and Glucose Study. Eur J Prev Cardiol . 2016;23(2):187–193. doi:10.1177/2047487314558771 25381336
  • Shi W-R , Wang H-Y , Chen S , Guo X-F , Li Z , Sun Y-X . Estimate of prevalent diabetes from cardiometabolic index in general Chinese population: a community-based study. Lipids Health Dis . 2018;17(1):236. doi:10.1186/s12944-018-0886-2 30314516
  • Biyik Z , Guney I . Lipid accumulation product and visceral adiposity index: two new indices to predict metabolic syndrome in chronic kidney disease. Eur Rev Med Pharmacol Sci . 2019;23(5):2167–2173. doi:10.26355/eurrev_201903_17262 30915762
  • Wang H-Y , Shi W-R , Yi X , Wang S-Z , Luan S-Y , Sun Y-X . Value of reduced glomerular filtration rate assessment with cardiometabolic index: insights from a population-based Chinese cohort. BMC Nephrol . 2018;19(1):294. doi:10.1186/s12882-018-1098-8 30359237
  • Kahn HS . The “lipid accumulation product” performs better than the body mass index for recognizing cardiovascular risk: a population-based comparison. BMC Cardiovasc Disord . 2005;5(1):26. doi:10.1186/1471-2261-5-26 16150143
  • Shin K-A , Kim Y-J . Usefulness of surrogate markers of body fat distribution for predicting metabolic syndrome in middle-aged and older Korean populations. Diabetes Metab Syndr Obes . 2019;12:2251. doi:10.2147/DMSO.S217628 31807040
  • Nascimento JXPT , da Costa Chein MB , de Sousa RML , Dos Santos Ferreira A , Navarro PA , Brito LMO . Importance of lipid accumulation product index as a marker of CVD risk in PCOS women. Lipids Health Dis . 2015;14(1):62. doi:10.1186/s12944-015-0061-y 26104466
  • Rivera-Mancía S , Colín-Ramírez E , Cartas-Rosado R , Infante O , Vargas-Barrón J , Vallejo M . Indicators of accumulated fat are stronger associated with prehypertension compared with indicators of circulating fat: a cross-sectional study. Medicine . 2018;97(34):e11869. doi:10.1097/MD.0000000000011869 30142781
  • Loria A , Arroyo P , Fernandez V , Pardio J , Laviada H . Prevalence of obesity and diabetes in the socioeconomic transition of rural Mayas of Yucatan from 1962 to 2000. Ethn Health . 2020;25(5):679–685. doi:10.1080/13557858.2018.1442560 29463112