Background: Socioeconomic analysis is currently used in the Europe Union as part of the regulatory process in Regulation Registration, Evaluation and Authorisation of Chemicals (REACH), with the aim of assessing and managing risks from dangerous chemicals. The political impact of the socio-economic analysis is potentially high in the authorisation and restriction procedures, however, current socio-economic analysis dossiers submitted under REACH are very heterogeneous in terms of methodology used and quality. Furthermore, the economic literature is not very helpful for regulatory purposes, as most published calculations of health costs associated with chemical exposures use epidemiological studies as input data, but such studies are rarely available for most substances. The quasi-totality of the data used in the REACH dossiers comes from toxicological studies. Methods: This paper assesses the use of the integrated probabilistic risk assessment, based on toxicological data, for the calculation of health costs associated with endocrine disrupting effects of triclosan. The results are compared with those obtained using the population attributable fraction, based on epidemiological data. Results: The results based on the integrated probabilistic risk assessment indicated that 4894 men could have reproductive deficits based on the decreased vas deferens weights observed in rats, 0 cases of changed T3 levels, and 0 cases of girls with early pubertal development. The results obtained with the Population Attributable Fraction method showed 7,199,228 cases of obesity per year, 281,923 girls per year with early pubertal development and 88,957 to 303,759 cases per year with increased total T3 hormone levels. The economic costs associated with increased BMI due to TCS exposure could be calculated. Direct health costs were estimated at €5.8 billion per year. Conclusions:The two methods give very different results for the same effects. The choice of a toxicological-based or an epidemiological-based method in the socio-economic analysis will therefore significantly impact the estimated health costs and consequently the political risk management decision. Additional work should be done for understanding the reasons of these significant differences.