Housing conditions vary widely across the EU and the fact that new member-states are lagging behind in this regard has even come onto the European policy agenda. This article examines housing conditions as an outcome of complex social developments and highlights specific reasons why housing conditions vary so much within the EU. Thus the specific impact is observed of factors which have been identified in the literature as characterising distinctive housing models: the eastern European housing model, the southern European housing model and the distinction between cost-renting and homeowning countries. Further, the impact of these factors, along with general socioeconomic development, is empirically assessed by a linear regression model based on the EQLS 2003 dataset. The results clearly support the thesis of economic development playing a decisive role, with it being the biggest single factor explaining variations in housing conditions across the EU, followed by the significant influence of policy choice and the incidence of family support.
COBISS.SI-ID: 30494301
OBJECTIVES: Self-rated health can be influenced by several characteristics of the social environment. The aim of this study was to evaluate the relationshipbetween self-rated health and self-assessed social class in Slovenian adult population. METHODS: The study was based on the Countrywide Integrated Non-communicable Diseases Intervention Health Monitor database. During 2004, 8,741/15,297 (57.1%) participants aged 25-64 years returned posted self-administered questionnaire. Logistic regression was used to determine unadjusted and adjusted estimates of association between poor self-rated health and self-assessed social class. RESULTS: Poor self-rated health was reported by 9.6% of participants with a decrease from lower to upper-middle/upper self-assessed social class (35.9 vs. 3.7%). Logistic regression showed significant association between self-rated health and all self-assessed social classes. In an adjusted model, poor self-rated health remained associated with self-assessed social class (odds ratio for lower vs. upper-middle/upper self-assessed social class 4.23, 95% confidence interval 2.46-7.25; P ( 0.001). CONCLUSIONS: Our study confirmed differences in the prevalence of poor self-rated health across self-assessed social classes. Participants from lower self-assessed social class reported poor self-rated health most often and should comprise the focus of multisectoral interventions.
COBISS.SI-ID: 26406873
We observe the situation in two ‘dysfunctional’ post WWII estates in two countries – Slovenia and the Netherlands. The differences in social capital and participation in neighbourhood improvement between the residents are analysed with multivariate modelling procedures. The empirical data is the 2004 RESTATE survey. The findings show that participation levels are similar in both case study areas. The conclusions underline that social capital influences participation. However, the different elements of social capital do have different impacts on participation in both countries.
COBISS.SI-ID: 28341341
Proportions of a total, including social network compositions (proportions of partner, family, friends, etc.) lie in a restricted space, which challenges statistical analysis. Network compositions can be both dependent and explanatory variables and are usually measured with error by survey instruments. Structural equation models make it possible to correct measurement error bias. Coenders et al. (2011) fitted a factor analysis model to transformed network compositions. In this article, we use another transformation called an isometric log-ratio and we extend the model to include predictors and outcomes. The findings and hypotheses in the literature can be reformulated with isometric log-ratios in a more interpretable manner. For instance, we find relationships of gender with partner support, of education and extraversion with friend support, and of family support with tie multiplexity and closeness.
COBISS.SI-ID: 31612253
Survey indicators of social networks usually measure a certain function of social networks, for example exchange of social support. Social support is a multidimensional construct. The most comprehensive definition distinguishes among sources of social support (social support networks), supportive acts and appraisal of given support. Generally, two main hypotheses can be given with regard to the role social support plays in quality of life of individuals: that social support is beneficial as such (main effects), or that social support is beneficial at occasions of stressful events (buffer effect). In this paper we are dealing with survey measurement of ego-centered social support networks. Three methods to social network measurement are compared: the name generator method, the role generator method and the event-related approach. In a meta-analysis of several studies done on convenient quota samples the effects of method, type of calculation, response format and limitation of support providers on network composition indicators are studied.
COBISS.SI-ID: 31355485