OBJECTIVES: Health state utility values (HSUVs) for comorbid health conditions (CHC) are frequently estimated using data from single health conditions but there is no consensus on the most appropriate method.  The objective of the study is to comparing five techniques in a single dataset. METHODS: We use EQ-5D data from the Health Survey for England to compare results generated using the: additive, multiplicative and minimum methods, the adjusted decrement estimator (ADE), and a linear regression model; a baseline of perfect health and an adjusted baseline obtained from individuals who indicate they have no chronic health condition.  Results are compared using mean errors (ME), root mean squared errors (RMSE) and the proportion of values estimated within |0.05|. RESULTS: Using an age adjusted baseline, we found the additive (and multiplicative) methods underestimate the majority of HSUVs (ME:0.0781(0.0254); RMSE:0.1012(0.0651); 26%(56%)