Health, Wellness and Tourism: healthy tourists, healthy business ...

However, according to Table 1, it appears that inhabitants of settlements involved in
"tourism" or "wellness tourism" do not differ significantly from the national average in
assessing their personal happiness (53% of subjects in our sample were living at a settlement
involved in tourism; 23% lived at a wellness tourism destination). This appears to
demonstrate that micro-habitat factors affect the individual's subjective well-being more than
their macro-habitat.
Defining the indicator of “objective welfare of settlement”
Beyond a simple analysis of the available database, we are trying to determine the factors that
impact (individual) perception of happiness. Since our ultimate goal is to set up a ranking
among settlements in Hungary in terms of happiness of their inhabitants, we must first
determine the range of variables that influence subjective well-being. In order to do the same
for objective well-being, we must define those indices that will clearly have an impact on
subjective well-being at the individual level as well as at the municipal level. In other words,
if we find, for example, that moving into a new home has a positive impact on the individual's
subjective well-being, then our municipal level indicator measuring the construction of new
housing will receive a higher weight in our index for objective well-being.
Table 2 summarises the indicators used as explanatory variables in our model.
Number Dimensions affecting perceived Indicators affecting perceived
subjective well-being
subjective well-being
1. Socio-demographic indicators Age
2. Marital status
3. Highest level of education
4. Economic activity
5. Urban characteristics (facilities) Railway station
6. Long-distance bus station
7. Post Office/P.O.B, postal agencies
8. Bank
9. Market
10. Pharmacy
11. Old persons’ home
12. GP
13. Kindergarten
14. Primary school
15. Library
16. Tourism exists in the settlement
17. City status
Note: socio-demographic characteristics are from HCSO Time Use Survey 1999/2000, source
of local settlement features from database TSTAR CSO 2002
The dependent variable of our logistic regression model is a binary variable that is created
from a previous model, which had earlier been prepared to measure "happiness" on a fourlevel
scale 52 .
52 This was a question in the questionnaire: values of the dependent variable were created by aggregation. 1=
happy; 0=unhappy