Asociación entre síndrome metabólico, nivel socioeconómico y calidad de vida en mexicanos
##plugins.themes.themeEleven.article.main##
Keywords
Síndrome Metabólico, Factores Socioeconómicos, Calidad de Vida, México
Resumen
Introducción: en México existe escasa información respecto al vínculo entre el síndrome metabólico (MetS), el nivel socioeconómico (NSE) y la calidad de vida (CdV) de la población.
Objetivo: evaluar la asociación entre sujetos que tienen alto riesgo de desarrollar MetS con NSE y CdV.
Material y métodos: se invitó a participar a pacientes de la UMF-2 del IMSS y del Centro Urbano-SSA Clínica-1. Se recolectaron medidas antropométricas y se aplicaron los cuestionarios AMAI, SF12 y ESF-I para NSE, CdV y MetS, respectivamente. La asociación se determinó calculando rho de Spearman. El riesgo se evaluó mediante regresión logística (razon de momios e intervalo de confianza del 95%).
Resultados: la diferencia entre NSE (193 ± 53 frente a 124 ± 50) y CdV (86.3 ± 14.8 frente a 56.0 ± 25.4) fue significativa entre los grupos de bajo y alto riesgo, respectivamente (p < 0.001). Hubo una fuerte correlación negativa entre las puntuaciones de la ESF-I y NSE (rho = -0.623, p < 0.001) así como con la CdV (rho = -0.719, p < 0.001). El riesgo de MetS aumentó al disminuir el NSE (C+: OR = 6.4, IC95%: 3.2 - 13.0; D: OR = 66.1, IC95%: 23.2 - 188.3), mientras que el aumento de la CdV lo atenuó (OR = 0.93, IC95%: 0.91 - 0.94).
Conclusión: Una menor CdV y NSE aumentan el riesgo de MetS en la región centro de México; sin embargo, el aumento en la CdV podría disminuir el efecto que tiene el NSE en el desarrollo de MetS.
Referencias
Biggs TW, Anderson WG, Pombo OA. Concrete and poverty, vegetation and wealth? A counterexample from remote sensing of socioeconomic indicators on the US– Mexico border. Prof Geogr. 2015;67(2):166-79. doi: 10.1080/ 00330124.2014.905161.
Gwynne RN. Industrialization and urbanization in latin america. 1st ed. London, UK: Routledge Taylor & Francis Group; 2018.
INEGI. Regiones Socioeconómicas de México 2018. Disponible en: https://sc.inegi.org.mx/niveles/index.jsp.
OECD. Panorama económico de México: OECD Economic Surveys: Mexico 2017; 2019. Available from: www.oecd.org/ eco/surveys/economic-survey-mexico.htm.
Yusuf S, Joseph P, Rangarajan S, Islam S, Mente A, Hystad P, et al. Modifiable risk factors, cardiovascular disease, and mortality in 155 722 individuals from 21 high-income, middle-income, and low-income countries (PURE): a prospective cohort study. Lancet. 2020;395(10226):795-808. doi: 10.1016/ S0140-6736(19)32008-2.
Wang X, Strizich G, Hua S, Sotres-Alvarez D, Buelna C, Gallo LC, et al. Objectively measured sedentary time and cardiovascular risk factor control in US Hispanics/Latinos with diabetes mellitus: results from the Hispanic community health study/study of Latinos (HCHS/SOL). J Am Heart Assoc. 2017;6(6):e004324. doi: 10.1161/JAHA.116.004324.
Morales LS, Lara M, Kington RS, Valdez RO, Escarce JJ. Socioeconomic, cultural, and behavioral factors affecting Hispanic health outcomes. J Health Care Poor Underserved. 2002;13(4):477. doi: 10.1177/104920802237532.
Mendenhall E, Kohrt BA, Norris SA, Ndetei D, Prabhakaran D. Non-communicable disease syndemics: poverty, depression, and diabetes among low-income populations. Lancet. 2017; 389(10072):951-63. doi: 10.1016/S0140-6736(17)30402-6.
AMAI. Nivel Socio Económico AMAI 2018: Comité de Niveles Socioeconómicos AMAI; 2018. Disponible en: http://www. amai.org/nse/wp-content/uploads/2018/04/Nota-Metodolo% CC%81gico-NSE-2018-v3.pdf.
INEGI. Educacion, Escolaridad 2020 [cited 2020 10 January]. Disponible en: http://cuentame.inegi.org.mx/monografias/ informacion/pue/poblacion/educacion.aspx?tema=me&e=21.
WHO. Primary health care systems (PRIMASYS): case study from Mexico, 2017 Licence: CC BY-NC-SA 3.0 IGO. Geneva: World Health Organization2017 [cited 2020 21 February]. Disponible en: https://www.who.int/alliance-hpsr/projects/ alliancehpsr_mexico_abridgedprimasys2018.pdf?ua=1.
Cohen-Carneiro F, Souza-Santos R, Rebelo MAB. Quality of life related to oral health: contribution from social factors. Ciência & Saúde Coletiva. 2011;16:1007-15. doi: 10.1590/ s1413-81232011000700033.
Javed S, Javed S, Khan A. Effect of education on quality of life and well being. Int J Indian Psychol. 2016;3(3):119-28. doi: 10.25215/0304.053.
Jabbour G, Mathieu M-E, Beliveau L, Brochu M. Importance of Tangible Physical Changes for Quality of Life Improvements of Type 2 Diabetic and at Risk Individuals Involved in Exercise Intervention: A Quasi-Experimental Design. J Med Liban. 2016;103(4007):1-6. doi: 10.12816/0033792.
Sitlinger A, Zafar SY. Health-Related Quality of Life: The Impact on Morbidity and Mortality. Surg Oncol Clin N Am. 2018;27(4): 675-84. doi: 10.1016/j.soc.2018.05.008.
Zhang Y-B, Chen C, Pan X-F, Guo J, Li Y, Franco OH, et al. Associations of healthy lifestyle and socioeconomic status with mortality and incident cardiovascular disease: two prospective cohort studies. BMJ. 2021;373. doi: 10.1136/bmj.n604.
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.
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. doi: 10.1177/1753944717711379.
Dragsbæk K, Neergaard JS, Laursen JM, Hansen HB, Christiansen C, Beck-Nielsen H, et al. Metabolic syndrome and subsequent risk of type 2 diabetes and cardiovascular disease in elderly women: challenging the current definition. Medicine. 2016;95(36):e4806. doi: 10.1155/2014/943162.
Shah CH, Brown JD. Reliability and Validity of the Short-Form 12 Item Version 2 (SF-12v2) Health-Related Quality of Life Survey and Disutilities Associated with Relevant Conditions in the U.S. Older Adult Population. J Clin Med. 2020;9(3). doi: 10.3390/jcm9030661.
Porchia LM, Lara-Solis B, Torres-Rasgado E, Gonzalez-Mejia M, Ruiz-Vivanco G, Pérez-Fuentes R. Validation of a non-laboratorial questionnaire to identify Metabolic Syndrome among a population in central Mexico. Rev Panam Salud Publica. 2019;43:e9. doi: 10.26633/RPSP.2019.9.
Campos Vázquez RM, Monroy-Gómez-Franco LA. La relación entre crecimiento económico y pobreza en México. Invest Económ. 2016;75(298):77-113. doi: 10.1016/j. inveco.2016.11.003.
CDC. Health-Related Quality of Life (HRQOL) 2018. Disponible en: https://www.cdc.gov/hrqol/wellbeing.htm.
Saboya PP, Bodanese LC, Zimmermann PR, Gustavo AD, Assumpcao CM, Londero F. Metabolic syndrome and quality of life: a systematic review. Rev Lat-Am Enferm. 2016;24: e2848. doi: 10.1590/1518-8345.1573.2848.
Pathak R, Agarwalla R, Pathania D. Assessment of metabolic syndrome and health related quality of life in community dwellers: A cross sectional study from North India. Indian J Med Spec. 2018;9(1):15-9. doi: 10.1016/j.injms.2018.01.001.
OECD. Education at a Glance 2020: OECD Indicators. OECD Publishing, Paris2020. Disponible en: https://doi.org/ 10.1787/69096873-en.
Cho KI, Kim BH, Je HG, Jang JS, Park YH. Gender-Specific Associations between Socioeconomic Status and Psychological Factors and Metabolic Syndrome in the Korean Population: Findings from the 2013 Korean National Health and Nutrition Examination Survey. Biomed Res Int. 2016; 2016:3973197. doi: 10.1155/2016/3973197.
Matute I, Burgos S, Alfaro T. Socioeconomic status and perceived health-related quality of life in Chile. MEDICC Review. 2017;19:51-6.
Uppala S, Thangellapally SS, Vatipelli M. A prospective observational study on health related quality of life and socioeconomic status among chronic disease patients. Int J Curr Res. 2017;9(5):51312-5.
Pechey R, Monsivais P. Socioeconomic inequalities in the healthiness of food choices: Exploring the contributions of food expenditures. Prev Med. 2016;88:203-9. doi: 10.1016/j. ypmed.2016.04.012: 10.1016/j.ypmed.2016.04.012.