An assessment of PM1 levels based on indicative PM1 measurements and relationships with PM10 and PM2.5 concentrations, for the analysis of hospital admissions and mortality in the Moravian region.

BACKGROUND: Particulate matter (PM) air pollution is a serious concern in the city of Ostrava. Thus, in 2018, a project entitled "Validation of the relationships between PM10, PM2.5 and PM1 concentrations, and morbidity and mortality, in the heavily polluted region in the Czech Republic," was launched. The relationship between hospital admissions and mortality in the said region is based primarily on short-term PM10 and PM2.5 concentrations and indicative PM1 measurement. The analysis of spatiotemporal variations and the relationship between PM10, PM2.5 and PM1 data from 3 measurement sites within the city of Ostrava is presented. MATERIAL AND METHODS: The analysis was based on the daily average PM concentrations for 5 and 6 months at 2 sites, and on the annual average values (2018-2019) at the baseline station. The correlations of and variability between PM fractions, seasonal differences and explanation of the differences found were the objectives of a detailed analysis. Especially, the potential PM1 variability and its causes were analyzed with respect to the location of the site. RESULTS: The study findings confirmed good correlations between the PM fractions. Compared to PM10, PM2.5 concentrations were more predictive for PM1 concentrations. The annual means of PM10, PM2.5 and PM1 reached 37.5, 29.9 and 27.1 µg/m3 in 2018, respectively, and 25.8, 19.9 and 17.9 µg/m3 in 2019, respectively. The concentration levels in the non-heating season were significantly lower than in the heating season in the 2 years under consideration. The levels of PM10, PM2.5 and PM1 were significantly correlated (the correlation coefficient, r > 0.96). The levels of PM2.5 represented about 0.82-0.86 of PM10, and the levels of PM1 about 0.92-0.93 of PM2.5. These ratios were found to differ in the heating and non-heating seasons, with the PM2.5-PM10 ratio ranging 0.61-0.63 in the non-heating seasons. CONCLUSIONS: The correlations found will be used for indicative PM1 measurements in other areas of the region. Seasonal variability should be taken into account as well. Med Pr. 2021;72(3):249-58.

PM10 Air Pollution and Acute Hospital Admissions for Cardiovascular and Respiratory Causes in Ostrava.

BACKGROUND AND AIM: The city of Ostrava and its surroundings belong to the most long-therm polluted areas in the Czech Republic and Europe. For identification of health risk, the World Health Organization recommends a theoretical estimation of increased short-term PM10 concentrations effect on hospital admissions for cardiac complaints based on a 0.6% increase per 10 µg.m-3 PM10 and 1.14% increase for respiratory causes. The goal of the present study is to verify the percentage increase of morbidity due to cardiovascular and respiratory causes, as per WHO recommendations for health risk assessment, in the population of Ostrava. METHOD: The input data include data on PM10 air pollution, meteorological data, the absolute number of hospital admissions for acute cardiovascular and respiratory diseases in the period 2010-2012. To examine the association between air pollution and health outcomes the time series Poisson regression adjusted for covariates was used. RESULTS: A significant relationship was found between the cardiovascular hospital admissions (percentage increase of 1.24% per 10 µg.m-3) and values of PM10 less than 150 µg.m-3 in the basic model, although after adjustment for other factors, this relationship was no longer significant. A significant relationship was also observed for respiratory causes of hospital admissions in the basic model. Contrary to cardiovascular hospitalization, the relationship between respiratory hospital admissions and PM10 values below 150 µg.m-3 (percentage increase of 1.52%) remained statistically significant after adjustment for other factors. CONCLUSIONS: The observed significant relationship between hospital admissions for respiratory causes was consistent with the results of large European and American studies.

A Summary of Environmental Health Studies in the City of Ostrava and the Surrounding Region in the Czech Republic.

AIM: This study is concerned with environmental health studies conducted in Ostrava (Czech Republic) and the surrounding region since the early nineties. METHODS: Various databases, journals and reports, including internal or unpublished reports, were reviewed to assess the individual publications. A brief description of the studies and main results were collated. RESULTS: The city of Ostrava and the surrounding region is an important industrial centre in the Czech Republic with a long-term heavy environmental and occupational disease burden. In spite of the theoretically assessed decline of health risks related to decreasing concentrations of compounds in the environment in recent years, it still poses a disproportionally high risk for the city residents. There are a number of studies suggesting supportive evidence, but they are highly variable in their approach to this topic resulting in a high uncertainty of observed associations and consistency of results. Most of the studies were focused on specific contexts, without any relation to environmental factors. CONCLUSIONS: A more systematic approach is needed to assess environmental health burden of diseases especially in relation to air pollution, based on the prospective cohort study, that would lead to sufficient new evidence for accurate and updated description of the environmental health burden in Ostrava.

Czech socio-economic deprivation index and its correlation with mortality data.

OBJECTIVES: The aim of the study was to create an index of socio-economic deprivation (SESDI) and to analyse correlation between SESDI and mortality data. METHODS: The SESDI components were selected from the census data (2001) at enumeration district and district level. Two methods were used for creating the SESDI: 1/ a sum of Z-scores of specific components (INDEX1); and 2/ standardized score - average values of specific components were divided by a maximum value of the specific component at the corresponding geographical level (INDEX2). Pearson's correlation coefficient was used for assessing the relationship between indices, and between indices and mortality data (SMR). RESULTS: The final indices were applied to districts in the Czech Republic (N = 77). The correlation of INDEX1 and INDEX2 was high (r = 0.99). Analysis of relationships between degree of deprivation and total and selected specific SMR in the Czech Republic confirmed that mortality was associated with degree of deprivation. CONCLUSION: The use of socio-economic deprivation indices in analysis of routinely collected mortality data in public health might help to explain health inequalities.