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Journal of Diabetes Research
Volume 2013 (2013), Article ID 241347, 9 pages
Research Article

Predicting Changes in Cardiovascular Risk Factors in Type 2 Diabetes in the Post-UKPDS Era: Longitudinal Analysis of the Swedish National Diabetes Register

1Division of Health Economics, Department of Clinical Sciences, Malmö University Hospital, Lund University, 20502 Malmö, Sweden
2Health Economics & Management, Institute of Economic Research, Lund University, 22007 Lund, Sweden
3Department of Health Management and Economics, School of Public Health, Tehran University of Medical Sciences, Tehran 141556447, Iran
4School of Public Health, University of Sydney, Sydney, NSW 2006, Australia
5Department of Economics, Lund University, 22363 Lund, Sweden
6Department of Clinical Sciences, Malmö University Hospital, Lund University, 20502 Malmö, Sweden
7Department of Medicine, Sahlgrenska University Hospital, University of Gothenburg, 41345 Göteborg, Sweden

Received 24 August 2012; Accepted 31 January 2013

Academic Editor: T. S. Kern

Copyright © 2013 Aliasghar Ahmad Kiadaliri et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The aim of the current study was to provide updated time-path equations for risk factors of type-2-diabetes-related cardiovascular complications for application in risk calculators and health economic models. Observational data from the Swedish National Diabetes Register were analysed using Generalized Method of Moments estimation for dynamic panel models ( , aged 25–70 years at diagnosis in 2001–2004). Validation was performed using persons diagnosed in 2005 ( ). Results were compared with the UKPDS outcome model. The value of the risk factor in the previous year was the main predictor of the current value of the risk factor. People with high (low) values of risk factor in the year of diagnosis experienced a decreasing (increasing) trend over time. BMI was associated with elevations in all risk factors, while older age at diagnosis and being female generally corresponded to lower levels of risk factors. Updated time-path equations predicted risk factors more precisely than UKPDS outcome model equations in a Swedish population. Findings indicate new time paths for cardiovascular risk factors in the post-UKPDS era. The validation analysis confirmed the importance of updating the equations as new data become available; otherwise, the results of health economic analyses may be biased.