Tourism, through its components, can be found in all areas that relate to sustainable development principles. Although it should be encouraged due to the multiplier effect that it has in the development of a region, it creates pressure on the surrounding environment like any other economic activity in the process of specific potential capitalization. This paper is aimed at determining the degree of tourism pressure, its trend and impact on tourism’s sustainable development and the Romanian economy. When this pressure exceeds the ecological support capacity, negative effects occur, both on the landscape in general, and on certain tourist objectives, in particular. The assessment of this pressure and its most accurate quantification imply the use, calculation, correlation and interpolation of indicators that may summarize certain aspects related to the density of tourist fittings, tourist traffic intensity and capitalization level. Hence, the approach would be considered regionally and in terms of tourism pressure dynamics, depending on the structure of available statistical data, as well as to get a clearer picture. The authors used methods specific to geography, as well as statistical and econometric methods. The interdependence between tourism, tourism pressure and sustainability is described in the Central region. The results and observations determined with reference to the factors and indicators shown underlie the coordination of the tourism activity in the other regions according to the processes of sustainability and tourism pressure mitigation.

Quality of life studies are numerous and of great interest. Beyond their practical utility, are also heavily publicized. The methodologies used are highly heterogeneous, relying on various statistical data and indicators, comparisons and correlations its difficult to make. This study aims a combined analysis of data and statistical indicators with questionnaires applied in the field in order to introduce an qualitative aspect - self-perception. The obtained results have been interpreted, compared, validated through correlation coefficient calculation and predictively analysed through linear regression. The analysis allowed identification trends and the formulation of some conclusions regarding important aspects of quality of life.