Funding sources: The work was funded by a UK MRC project grant on Disease Modelling (Grant ID: 87386)
THE EFFECT OF DIABETES COMPLICATIONS ON HEALTH-RELATED QUALITY OF LIFE: THE IMPORTANCE OF LONGITUDINAL DATA TO ADDRESS PATIENT HETEROGENEITY
Article first published online: 11 JUL 2013
© 2013 The Authors. Health Economics Published by John Wiley & Sons Ltd.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Volume 23, Issue 4, pages 487–500, April 2014
How to Cite
Alva, M., Gray, A., Mihaylova, B. and Clarke, P. (2014), THE EFFECT OF DIABETES COMPLICATIONS ON HEALTH-RELATED QUALITY OF LIFE: THE IMPORTANCE OF LONGITUDINAL DATA TO ADDRESS PATIENT HETEROGENEITY. Health Econ., 23: 487–500. doi: 10.1002/hec.2930
Disclosure: None of the authors of this paper has a conflict of interest that might prejudice the results.
The copyright line for this article was changed on 5 August 2015 after original online publication.
- Issue published online: 4 MAR 2014
- Article first published online: 11 JUL 2013
- Manuscript Accepted: 19 MAR 2013
- Manuscript Revised: 6 MAR 2013
- Manuscript Received: 1 FEB 2012
- UK Medical Research Council. Grant Number: 87386
- Quality of life;
- diabetes-related complications;
- fixed effects
We estimate the impact of six diabetes-related complications (myocardial infarction, ischaemic heart disease, stroke, heart failure, amputation and visual acuity) on quality of life, using seven rounds of EQ-5D questionnaires administered between 1997 and 2007 in the UK Prospective Diabetes Study. The use of cross-sectional data to make such estimates is widespread in the literature, being less expensive and easier to collect than repeated-measures data. However, analysis of this dataset suggests that cross-sectional analysis could produce biased estimates of the effect of complications on QoL. Using fixed effects estimators, we show that variation in the quality of life between patients is strongly influenced by time-invariant patient characteristics. Our results highlight the importance of studying quality-of-life changes over time to distinguish between time-invariant determinants of QoL and the effect on QoL of specific events such as diabetes complications. © 2013 The Authors. Health Economics Published by John Wiley & Sons Ltd.