Model prevalence zdraví

In most developed countries of the world, the population lives at an older age. With increasing age, there is a greater probability of a certain health restriction, and the proportion and number of people with health restrictions, and disabilities increases. At the level of society, disability increases the demand for formal and informal care. Estimates of the future development of the number of people with health restrictions are in demand but rarely published. The health prevalence model is designed on individual anonymized data from the European health interview survey (EHIS) in 2008, 2014 and 2019 and enters selected socio-demographic indicators. The work is examined and described with mutual relations among the indicators of the Minimum European health module (MEHM): self-perceived health, chronic/long-term morbidity, and activity limitations (Global Activity Limiting Indicator). Within binary logistic regression, the influence of sex, age groups, marital status, education, presence of long-term illness and long-term limitation of activities on self-rated health has been examined. A statistically significant influence on self-rated health has been demonstrated in age, education, long-term illnesses, and long-term limitation of activities. As part of the sensitivity analysis, the assignment of the middle category (fair) of self-rated health is chosen for poor assessment of your health (bad, very bad). The thesis is designed by a new dichotomic variable called “healthy vs ill”, which can be further used to calculate the new population health indicator and compare it with life expectancy indicators based on MEHM. This new variable is unique it combines answers to subjective and objective health issues. The relationship between the new variable and gender, age groups, family status, education and year of investigation is examined using binary logistics regression. Statistically significant results were published here for independent variable age groups, education, and year of investigation. With the help of the Brass relational method, prevalence curves are modelled for the newly designed dichotomic variable and examined the potential trend of development over time, but it has not been clearly proven. The standard in the relational method is chosen a combination of three EHIS surveys in 2008, 2014 and 2019. Furthermore, the possible future development of health prevalence is outlined based on the Czech Statistical Office’s projection for the Czech Republic by 2100 by age groups and gender and modelled prevalence of the new variable “healthy vs. ill “from the EHIS 2019 for data transported on the population of 15 years and older.