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Conceptualizing type 2 diabetes and its management

Authors Tsasis P, Wu J, An A, Wong H, An X, Mei Z, Hains T

Received 16 May 2015

Accepted for publication 9 December 2015

Published 29 March 2016 Volume 2016:9 Pages 133—136


Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 5

Editor who approved publication: Dr Scott Fraser

Peter Tsasis,1 Jianhong Wu,2 Aijun An,3 Hannah J Wong,1 Xiandong An,3,4 Zhen Mei,4 Ted Hains4

1School of Health Policy and Management, York University, Toronto, ON, Canada; 2Centre for Disease Modelling, York University, Toronto, ON, Canada; 3Department of Electrical Engineering of Computer Science, York University, Toronto, ON, Canada; 4Manifold Data Mining Inc., Toronto, ON, Canada

Abstract: Type 2 diabetes is growing worldwide due to population growth, increased rates of obesity, unhealthy diet, and physical inactivity. Risk assessment methods can effectively evaluate the risk of diabetes, and a healthy lifestyle can significantly reduce risk or prevent complications of type 2 diabetes. However, risk assessment alone has not significantly improved poor adherence to recommended medical interventions and lifestyle changes. This paper focuses on the challenge of nonadherence and posits that improving adherence requires tailoring interventions that explicitly consider the social determinants of health.

Keywords: type 2 diabetes, nonadherence, tailored interventions, data mining and cluster analysis

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