For a few years, the littoral of the Gulf of Tunis has been subjected to agricultural activities, industrial, urban and tourist development and consequently submitted to the impact of many chemical and physical stressors. Sub-individual responses (biochemical biomarkers) in bivalves can be used as an early warning system for ecotoxicological risk assessment. However, the influence of many confounding factors such as ecological (e.g. temperature and salinity) or physiological (e.g. reproductive and nutritive status) parameters on biomarker responses must be taken carefully into account. The aim of the present study was to integrate into indices (Integrated Biomarker Response: IBR and Health Status Index: HSI) individual responses of biochemical biomarkers (acetylcholinesterase, catalase, glutathione-S-transferase, thiobarbituric acid reactive substance levels, lactate dehydrogenase and metallothionein-like proteins) and energy reserves (glycogen, lipid levels and total protein concentrations) at sub-individual level, and condition index at individual level in Donax trunculus originating from 4 sites contrasted by their level of contamination in the Gulf of Tunis. Integrated biomarkers indices have been revealed to be efficient and easy tools for environmental managers. Responses of IBR and HSI were compared and their strengths and weaknesses discussed. Results showed that HSI could be an easy tool for risk management whereas IBR results were more informative with regard to the temporal contribution of each biomarker considered in the battery used in the present work. In bivalves from the reference Sidi Jehmi site, the contribution of energy reserves and the condition index reflecting a good general health status clearly influenced the temporal variations of IBR whereas in bivalves from the multi-contaminated Radès Méliane site, temporal variations of IBR were induced mainly by the responses of pollution biomarkers. Previous investigations concerning other level of biological organization (population) are in accordance with the present data (Tlili et al., 2010, 2011).