The effect of diabetes complications on health-related quality of life: the importance of longitudinal data to address patient heterogeneity.

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.