# Empirical Evidences for Urban Influences on Public Health in Hamburg
## 4 Discussion  
Only few studies have thus far used EQVAS as dependent variables. Most commonly, EQVAS is used as an easily accessible predictor of mortality within an (elderly) population [96; 97]. [PERSON] et al. provided one of the few research designs that intended to predict EQVAS [98], and were able to show that EQVAS is suitable as a dependent variable. Although the model and data used are hardly comparable to our study, one should note that their model only explained 9% of the variance of SRH. Therefore, our model's explanation of 27% (or 12% for the urban variables) of the variance can be seen as a satisfying result in comparison. On the other hand, there are many studies that use their own measuring instruments for SRH. SRH is often measured in five/six-fold Likert scales or only in binary form [99; 100]. The data are therefore not comparable with the dependent variable used here (EQVAS) because no standardized measuring instrument was used. In addition, most datasets are not georeferenced, which makes an analysis of environmental and place effects very difficult. Consequently, the statistical models developed are also more complex [101]. In this line of research, it is shown successfully that natural environments improve health and are protective against diseases. [PERSON] provided a similar modelling approach to UrbWellth, yet came up with different explanans from his study [102]. He determines the following factors as crucial for a salutogenic effect on urban health: \"Availability of green and open spaces [...]: general protection of urban residential neighbourhoods from noise and other urban exposures; improvement of the perception of public safety [...]; increased maintenance of urban and residential spaces; and adequate access to (public) transportation opportunities to avoid 'disconnection' of urban districts\" [102]. These results thus strengthen--even more clearly than our own results--the importance of salutogenetic approaches to health research. In addition, this approach is supported by the results of [PERSON] and [PERSON] who have shown that \"connection to nature\" is an important predictor of subjective well-being [103]. In this sense, in our study, rating of one's social context (SOC) and rating of neighborhood air quality (QCA) in particular are related to a salutogenetic perspective. Here, the double role of the three confounding variables must also be addressed. In an (epidemiological) study of the urban impact on health, they cannot only be regarded as confounding factors, for all three variables exhibit a clear bias in a comparison of rural and urban areas: city dwellers tend to smoke more [104], are younger [105], and the average income in cities is usually above that of the rural population [106]. Therefore, the influence of these variables may well be regarded as an urban influence. After having carried out the regression analysis, noise stress was excluded from the group of main impact variables although it had been expected to have a relevant impact [77]. However, the perception of noise stress (NWE) is clearly correlated with the assessment of air quality (QCA), showing a coefficient of 0.44 (\(p<0.01\)). Therefore, it can be assumed that the variable of air quality is a proxy for noise stress, too. A well rated Social Context (SOC) is known to have protective influence [107], a fact supported by public health research in different contexts [108; 109; 110]. Heat or cold stress have been heavily researched in climate impact research [69; 111]. Therefore, it can be assumed that our results are reproducible, even using a different research layout. Unfortunately, the confounding effect of body mass index (BMI) cannot be calculated with the present data set. This effect has been shown to influence heat or cold stress in other studies [112; 113], and the influence of cold stress inside (CNI) and heat stress outside (HDO) on EQVAS must therefore also be considered as a possible proxy for BMI.