Quality healthcare system is a priority for citizens of any country. Citizens' health is also a core EU priority. The objective of this article is application of multidimensional statistical techniques as a tool for information value added on health outcomes data in European countries and their further comparison. To achieve this objective, factor analysis and multidimensional comparison methods have been applied to the matrix of 16 healthcare indicators on 25 selected European countries. The synthetic variable allows transforming the countries described by a variety of healthcare indicators into one-dimensional space that considerably simplify monitoring of healthcare inequalities. The obtained results are compared with the results on the self-perceived health status provided by the citizens of the same countries. The results of this comparison have demonstrated significant similarity between self-reported statuses and objectively measured healthcare statuses. The results are presented in a visual form using tables and graphs.
Osteoporose in einer Population aus Bratislavaaltersabhängige KnochendichteänderungenZusammenfassung. Wir haben bei 498 Frauen aus Bratislava im Alter zwischen 21 und 90 Jahren die Knochendichte im proximalen Bereich des Femurs gemessen (in den "Regions of interest" ROI 1 -neck, ROI 2 -Ward's area, ROI 3 -Trochanter). Auf Grund der empirischen Häu-figkeitsverteilung der T-Werte haben wir mit dem χ 2 -test (Chi-square goodness-of-fit statistics) in der Grundgruppe der Population die Häufigkeitsverteilung festgestellt. Die entsprechend der T-Werte festgestellte Häufigkeit der Osteoporose betrug in ROI 1 2,40 %, in ROI 2 16,34 % und in ROI 3 3,83 %.Die Patientinnen wurden nach dem Alter in 10-Jahres-Gruppen eingeteilt. In jeder Gruppe wurde die Zahl der Osteoporosepatientinnen in Prozent (%) berechnet. Es hat uns interessiert, welcher ROI für die Feststellung der Altersabhängigkeit der Knochendichte am besten geeignet ist. Obwohl die Werte von ROI 2 (Ward's), entsprechend der WHO, nicht zur diagnostischen Sicherstellungen der Osteoporose zugelassen sind, zeigte ROI 2 die Altersabhängigkeit der Knochendichte am besten. Gegenüber ROI 1 und ROI 3 wird in der ROI 2 überwiegend trabekulärer Knochen gemessen. Die geringere Altersabhän-gigkeit der Knochendichte in ROI 1 und ROI 3 dürfte durch osteoarthrotische Veränderungen bedingt sein. Bei der Streuungsanalyse hat sich gezeigt, dass die Alterskategorie 9,6 % der Ganzvariabilität der T-Werte für ROI 1 , 24,7 % für ROI 2 und 11,7 % für ROI 3 erklärt. Im Fisher-Test wurde die statistische Relevanz (α = 0,05) der Altersabhängig-keit der Knochendichtewerte in ROI 1 , ROI 2 , ROI 3 unabhängig von anderen Risikofaktoren aufgezeigt. Um den Störfaktor der Osteoarthrose auszuschließen, ist die Entwicklung und Anwendung von neuen densitometrischen Methoden, die getrennt kortikalen and trabekularen Knochen messen, notwendig.Schlüsselwörter: Knochendichte, der proximale Bereich des Femurs, Osteoporose, Frauen, epidemiologische Studie.Summary. Patients and methods: We analysed 498 women (n = 498) in a Bratislava (BA) population aged 21 to 90. We measured bone mineral density (BMD) in the proximal femur with one densitometric instrument (DXA Osteocore II, France; dual energy X-ray absorptiometry), applying BMD and T-score values in three standard regions of interest: Neck (ROI 1 ), Ward's area (ROI 2 ), Trochanter (ROI 3 ). Results: Measured values of T-score in ROI 1, ROI 2 had normal distribution and a lognormal distribution of frequency in ROI 3 . Using χ 2 -test (chi-square goodness-of-fit statistics), we determined the distribution of the frequency of T-score values and the percentage of osteoporosis incidence in the Bratislava female population. The osteoporosis incidence, according to T-score values measured in ROI 1 was 2.40%, in ROI 2 16.34% and in ROI 3 3.83%. Following the division of women into ten-year intervals, the statistically significant sample averages of T-score values were decreasing in relation to age only for ROI 2 . Osteoporosis incidence in age intervals was ri...
The article offers the results of statistical analysis of data on the highest wages of employees in the Slovak Republic in 2020. Descriptive analysis of sample data is supplemented by generalizing the results to the population of all employees whose salary exceeds the 99th percentile of the sample, by selected methods of statistical inference, which are probability models of the highest wages and analysis of variance. The analysis focuses on assessing the significance of the impact of selected demographic and social factors on the highest salaries of employees in SR in 2020 and their differences. The investigated factors there are gender, level of education, region of residence, the label of occupation, and age category. The article also focuses on inequalities in the number of employees at different levels of the monitored factors. The obtained results of the analysis are compared with the results of similar analysis from 2010.
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