Technological interventions in metabolic syndrome: new paths for health professionals
DOI:
https://doi.org/10.15448/1980-6108.2016.3.25622Keywords:
metabolic syndrome X, information and communication technologies, risk factors.Abstract
In recent decades, changes in the epidemiological profile of populations and the development and improvement of new technologies have given rise to several strategies targeted at healthcare. In the prevention and management of metabolic syndrome, interdisciplinary interventions by health professionals have already yielded relevant results. Besides this, several technological resources now emerged as a staunch ally of professionals and patients in the quest for better quality of life and reduction of the adverse outcomes of this highly prevalent clinical condition. Notwithstanding, the present health technology scenario takes on additional challenges in terms of interdisciplinarity, as it involves heterogeneous fields of knowledge (health, computer science, and communication). So, the question is: are we prepared to handle these new forms of health intervention?
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References
Gami AS, Witt BJ, Howard DE, Erwin PJ, Gami LA, Somers VK, Montori VM. Metabolic syndrome and risk of incident cardiovascular events and death: a systematic review and meta-analysis of longitudinal studies. J Am Coll Cardiol. 2007 Jan 30;49(4):403-14. http://dx.doi.org/10.1016/j.jacc.2006.09.032
Valle Gottlieb MG, Mânica da Cruz IV, Bodanese LC. Origem da síndrome metabólica: aspectos genético-evolutivos e nutricionais. Sci Med. 2008;18(1):31-8.
Gustafsson PE, Hammarström A. Socioeconomic disadvantage in adolescent women and metabolic syndrome in mid-adulthood: an examination of pathways of embodiment in the Northern Swedish Cohort. Soc Sci Med. 2012 May;74(10):1630-8. http://dx.doi.org/10.1016/j.socscimed.2012.01.044
Ford ES, Li C, Zhao G. Prevalence and correlates of metabolic syndrome based on a harmonious definition among adults in the US. J Diabetes. 2010;2(3):180-93. http://dx.doi.org/10.1111/j.1753-0407.2010.00078.x
Onis M, Blössner M, Borghi E. Global prevalence and trends of overweight and obesity among preschool children. Am J Clin Nutr. 2010;92(5):1257-64. http://dx.doi.org/10.3945/ajcn.2010.29786
Afshin A, Babalola D, Mclean M, Yu Z, Ma W, Chen CY, Arabi M, Mozaffarian D.Information Technology and Lifestyle: A Systematic Evaluation of Internet and Mobile Interventions for Improving Diet, Physical Activity, Obesity, Tobacco, and Alcohol Use. J Am Heart Assoc. 2016 Aug 31;5(9). pii: e003058. http://dx.doi.org/10.1161/JAHA.115.003058
World Health Organization (WHO). Global Observatory for eHealth (GOe) [Internet]. [cited 2016 Oct 18]. Available from: http://www.who.int/goe/en/
Rubinstein A, Miranda JJ, Beratarrechea A, Diez-Canseco F, Kanter R, Gutierrez L, Bernabé-Ortiz A, Irazola V, Fernandez A, Letona P, Martínez H, Ramirez-Zea M; GISMAL group. Effectiveness of an mHealth intervention to improve the cardiometabolic profile of people with prehypertension in low-resource urban settings in Latin America: a randomised controlled trial. Lancet Diabetes Endocrinol. 2016 Jan;4(1):52-63. http://dx.doi.org/10.1016/S2213-8587(15)00381-2
Stuckey MI, Shapiro S, Gill DP, Petrella RJ. A lifestyle intervention supported by mobile health technologies to improve the cardiometabolic risk profile of individuals at risk for cardiovascular disease and type 2 diabetes:study rationale and protocol. BMC Public Health. 2013 Nov 7;13:1051. http://dx.doi.org/10.1186/1471-2458-13-1051
Free C, Phillips G, Galli L, Watson L, Felix L, Edwards P, Patel V, Haines A. The effectiveness of mobile-health technology-based health behaviour change or disease management interventions for health care consumers: a systematic review. PLoS Med. 2013;10(1):e1001362. http://dx.doi.org/10.1371/journal.pmed.1001362
Napolitano MA, Hayes S, Russo G, Muresu D, Giordano A, Foster GD. Using avatars to model weight loss behaviors: participant attitudes and technology development. J Diabetes Sci Technol. 2013 Jul 1;7(4):1057-65. http://dx.doi.org/10.1177/193229681300700430
Persky S. Application of virtual reality methods to obesity prevention and management research. J Diabetes Sci Technol. 2011 Mar 1;5(2):333-9. http://dx.doi.org/10.1177/193229681100500220
Neves Assis SAC, Bós AJG, Myskiw JC, Pinho MS, Silva Filho IG, Schwanke CHA, Izquierdo IA. Effects of video game training on cognition in the elderly: systematic review. Sci Med. 2015;25(3):ID21636. http://dx.doi.org/10.15448/1980-6108.2015.3.21636
