| Summary: | 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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