Библиотека курортолога → «Современные тенденции и перспективы развития курортного дела в Российской Федерации» → A CLIMATOTHERAPY REFERENCE MODEL BASED ON ANALYSIS OF TWO EMERGENCY ROOM DATA BANK
A CLIMATOTHERAPY REFERENCE MODEL BASED ON ANALYSIS OF TWO EMERGENCY ROOM DATA BANKV. Condemi1, U. Solimene, R. Meco1 1Centre for Research on Medical Bioclimatology, Biotechnologies, and Natural Medicines of the Milan State University The study of urban medical bioclimatology is of particular interest due to the by-now irreversible gradual concentration of man’s activities in densely inhabited areas. A combination of data on the slow and constant rise of the old age index and of the mean age of residents observed primarily in developed Countries highlighted the healthcare, environmental, and climatotherapic management models on which focus should be made, mainly known as geriatric oriented models (medical geronto-bioclimatology). This was the baseline consideration for this paper, which considers certain climate-sensitive diseases, as such of climatotherapic interest. The starting point was a reference to the Report on the Health Status of Italy, which analyzed a variety of public health issues and provided useful guidelines, directing works towards climate and environment sensitive diseases basically referred to weak groups, and a variey of disorders affecting both the respiratory system and the cardiocirculatory and cerebrovascular system. This paper focuses on emergency morbidity, a powerful public health indicator where 13000 ER diseases are described according to the international codes. Two Emergency Room (ER) data bases were considered, built in two different environments. The first ER data base was created by the San Carlo Hospital in Milan, with a potential patient base close to 400000 units and 80000 recorded accesses per year; the second data base was set up by four specific ER Units in the Valtellina region (Sondrio, Sondalo, Morbegno, and Chiavenna), operated by Azienda Ospedaliera della Valtellina e della Valchiavenna, with a patient base close to 200000 units and fed by significant seasonal tourist flows (both in summer and in winter), which increased pressure on the ERs. The selected data and the relevant method satisfy the need to compare two different geographies and climates. The first ER is a significant example of an urban bioclimatic model, while the latter is a typical example of a wide Alpine valley, with a 3212 sq. km. surface in the north-western part of the Lombardy Region. The data base analysis was primarily focused on two age groups considered as weak, with individuals requiring emergency services (< 14 and > 65). All the respiratory disorders admitted to the ER were analyzed, with special focus on some that showed significant potential developments, also in perspective. The comparison and the analysis based on certain environmental profiles were possible for two polluting agents, PM10 and NO2, measured in the Verziere district for the city of Milan and in the urban areas of Sondrio and Bormio for Valtellina (ARPAL data). The average daily figure per month of PM10 points out to a 3 times greater variability in the urban environment compared to the valley and compared to the seasonal average. Similar trends are observed for NO2. It was further decided to match the measurements in Sondrio with the series collected in Bormio as a comparison within the Alpine valley. Finally the weather data collected in Milan and in Valtellina were reviewed to obtain a more comprehensive picture of the different climate conditions in Milan and of the geographic areas that refer to the ERs in Valtellina. After processing and grouping the data according to homogeneous disease classes and to a well defined time frame, the The number of patients referring to the ER in the city shows a greater variability compared to the valley: the extent of the monthly data range is greater both for children and for the middle-age groups, except for the elderly people, who show the same value as the average. This phenomenon was observed after defining the representativeness of both population samples, performing an analysis on the seasonal access of non-resident users and defining consistency schemes comparing the composition of the age groups of both resident populations. The ER data pointed out to a significantly diversified concentration of polluting agents between the urban context and the hill-mountain context, expressed in terms of broad variability of references to the respective ERs, and stressing a different proportion of criticalities in both geographies, thus suggesting preventive, environmental, and climatotherapic medicine approaches. |