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Elwira Piszczek

Topic: Civilization diseases. Can the rural area protect? Methodological problems regarding the collection and interpretation of data


Different types of statistical data, analysis show “rural areas” usually as underdeveloped areas, as a place of life worse than “urban areas”. Such a picture emerges, among others, from public health data both at the local (regional) level as in the global perspective (eg WHO data). At the same time, the same data shows us differences in the intensity (and dynamics) of the apperance of many different so-called civilization diseases, which seems to concern urban residents rather than villages.

In my paper, I would like to try to answer the question whether  the “rural area” and “rural lifestyle” can play a protective role in relation to mental and physical health? To what extent? I would like to raise the question of the relationship between man and Nature as a (still dominant) element of rural life, which is crucial in the interpretation of so-called Nature Deficit Disorder.

This is directly related to the methodological problems that I would like to address. Public health is an extremely interesting but at the same time extremely difficult research area. On the one hand, we have extensive surveys. Due to the type of collected material, the benefits of a large range of research (often representative) are sometimes eclipsed by the limited possibilities of correlation analysis (cause-and-effect relationship).  Research on a small scale (local and regional) usually gives better opportunities for in-depth analysis (dependencies). Unfortunately, they are often accused of being unable to generalize. Similarly, experimental studies, despite statistically significant results, are often accused of being unable to generalize conclusions. Additional difficulties are the ethical aspects of constructing experiments. These problems are connected with the unresolved disputes about the nature of “urbanity” and “rurality”. This is obviously a big simplification, but showing important problems related to the collection, analysis and interpretation of data.

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