Food allergy is associated with higher health care costs. Severity of allergic symptoms is a key explanatory factor.

IntroductionThe quality of life (QoL) experienced by cancer patients depends both on their state of health and on sociodemographic factors. Tumours in the head and neck region have a particularly adverse effect on patients psychologically and on their social functioning.Material and methodsThe study involved 121 patients receiving radiotherapy treatment for head and neck cancers. They included 72 urban and 49 rural residents. QoL was assessed using the questionnaires EORTC-QLQ-C30 and QLQ-H&N35. The data were analysed using statistical methods: a χ2 test for independence and a multinomial logit model.ResultsThe evaluation of QoL showed a strong, statistically significant, positive dependence on state of health, and a weak dependence on sociodemographic factors and place of residence. Evaluations of financial situation and living conditions were similar for rural and urban residents. Patients from urban areas had the greatest anxiety about deterioration of their state of health. Rural respondents were more often anxious about a worsening of their financial situation, and expressed a fear of loneliness.ConclusionsStudying the QoL of patients with head and neck cancer provides information concerning the areas in which the disease inhibits their lives, and the extent to which it does so. It indicates conditions for the adaptation of treatment and care methods in the healthcare system which might improve the QoL of such patients. A multinomial logit model identifies the factors determining the patients’ health assessment and defines the probable values of such assessment.

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Usage of the economic analysis in the study of the performance of health care system does not surprise anyone nowadays. Trends that are drawn over the years fluctuate from the technology assessment of health programs – in terms of efficiency, costs or utility for patients, through methods to establishing copayment for health services and the demand for medical services. Much of the interest is devoted to analysis of the shape of the health care system: the amount of contributions to the National Health Fund, the managing the system, both at the micro and macro level, or restructuring. Any method that allows to show dependencies, identify weaknesses/strengths of the health care system is appreciated by health policy makers. The aim of this article is an attempt of the use of models of input-output type in the analysis of the performance of the health care sector in Poland. The construction of input-output model is based on the observed data for the specified, variously defined area – it may concern: country, region, municipality, etc., hence with the appropriate designed database, it may be possible to examine the flow of health benefits – for example, expressed in zlotys. Part of the article is dedicated to theoretical aspects of the input-output models and the problems this usage can cause.

With the evolution of information and communication systems it is possible to speed up the flow of information. These processes have occurred and continue to occur in different areas of social and economic life, and concern both households and the enterprises. Consequently the possibility of building a knowledge-based economy has arisen. Additionally, the demand for ever more advanced digital technology is constantly increasing, which lays the foundation for the information society to function.The aim of the paper is a multi-dimensional approach to analysing the development of modern telecommunication infrastructure in Poland. The research issues are presented in regional terms, since digital networks have started expanding at this level. It was assumed that there were significant disproportions in interregional development of the ICT sector in Poland. That assumption was verified using appropriate taxonomic methods, including synthetic measure of development in standarised terms and cluster analysis. On the basis of the designated ICT indices, regions were classified and homogenously grouped according to the state and performance of the ICT sector. The analyses were carried out in the period 2003–2014.