Development of land use regression models for particle composition in twenty study areas in Europe

Land Use Regression (LUR) models have been used to describe and model spatial variability of annual mean concentrations of traffic related pollutants such as nitrogen dioxide (NO2), nitrogen oxides (NOx) and particulate matter (PM). No models have yet been published of elemental composition. As part of the ESCAPE project, we measured the elemental composition in both the PM10 and PM2.5 fraction sizes at 20 sites in each of 20 study areas across Europe. LUR models for eight a priori selected elements (copper (Cu), iron (Fe), potassium (K), nickel (Ni), sulfur (S), silicon (Si), vanadium (V), and zinc (Zn)) were developed. Good models were developed for Cu, Fe, and Zn in both fractions (PM10 and PM2.5) explaining on average between 67 and 79% of the concentration variance (R(2)) with a large variability between areas. Traffic variables were the dominant predictors, reflecting nontailpipe emissions. Models for V and S in the PM10 and PM2.5 fractions and Si, Ni, and K in the PM10 fraction performed moderately with R(2) ranging from 50 to 61%. Si, NI, and K models for PM2.5 performed poorest with R(2) under 50%. The LUR models are used to estimate exposures to elemental composition in the health studies involved in ESCAPE.

Development of Land Use Regression models for PM(2.5), PM(2.5) absorbance, PM(10) and PM(coarse) in 20 European study areas; results of the ESCAPE project

Land Use Regression (LUR) models have been used increasingly for modeling small-scale spatial variation in air pollution concentrations and estimating individual exposure for participants of cohort studies. Within the ESCAPE project, concentrations of PM(2.5), PM(2.5) absorbance, PM(10), and PM(coarse) were measured in 20 European study areas at 20 sites per area. GIS-derived predictor variables (e.g., traffic intensity, population, and land-use) were evaluated to model spatial variation of annual average concentrations for each study area. The median model explained variance (R(2)) was 71% for PM(2.5) (range across study areas 35-94%). Model R(2) was higher for PM(2.5) absorbance (median 89%, range 56-97%) and lower for PM(coarse) (median 68%, range 32- 81%). Models included between two and five predictor variables, with various traffic indicators as the most common predictors. Lower R(2) was related to small concentration variability or limited availability of predictor variables, especially traffic intensity. Cross validation R(2) results were on average 8-11% lower than model R(2). Careful selection of monitoring sites, examination of influential observations and skewed variable distributions were essential for developing stable LUR models. The final LUR models are used to estimate air pollution concentrations at the home addresses of participants in the health studies involved in ESCAPE.

Development of Land Use Regression models for PM(2.5), PM(2.5) absorbance, PM(10) and PM(coarse) in 20 European study areas; results of the ESCAPE project

Land Use Regression (LUR) models have been used increasingly for modeling small-scale spatial variation in air pollution concentrations and estimating individual exposure for participants of cohort studies. Within the ESCAPE project, concentrations of PM(2.5), PM(2.5) absorbance, PM(10), and PM(coarse) were measured in 20 European study areas at 20 sites per area. GIS-derived predictor variables (e.g., traffic intensity, population, and land-use) were evaluated to model spatial variation of annual average concentrations for each study area. The median model explained variance (R(2)) was 71% for PM(2.5) (range across study areas 35-94%). Model R(2) was higher for PM(2.5) absorbance (median 89%, range 56-97%) and lower for PM(coarse) (median 68%, range 32- 81%). Models included between two and five predictor variables, with various traffic indicators as the most common predictors. Lower R(2) was related to small concentration variability or limited availability of predictor variables, especially traffic intensity. Cross validation R(2) results were on average 8-11% lower than model R(2). Careful selection of monitoring sites, examination of influential observations and skewed variable distributions were essential for developing stable LUR models. The final LUR models are used to estimate air pollution concentrations at the home addresses of participants in the health studies involved in ESCAPE.

[Regional differences of mortality from malignancies in Hungary]

INTRODUCTION

The mortality of the Hungarian population is very unfavourable in relation to other European countries. Mortality from malignant diseases is the second most frequent cause of death in both sexes. The most frequent localisation of cancer is that of the bronchi and the lungs, followed by colorectal, breast and oral cavity cancers.

AIM

Of the publication was to demonstrate the spatial distribution of mortality from malignant diseases of all sites, bronchi and the lungs, as well as mortality from cancer of the thyroid gland and leukaemias, and to evaluate the possible impact of the Chernobyl nuclear accident on the frequency of cancer mortality.

METHOD

The spatial distribution of mortality in the country is evaluated by computing standardized mortality ratio on settlement level, using geographical information system. In case of frequent mortality events a region analysis was carried out, in the opposite case--a cluster analysis.

RESULTS

Regarding the spatial distribution of mortality from all malignant diseases of 0-64 year-old males there are regions with excess mortality in almost each county. In case of women of this age group, there is a significantly higher mortality in Budapest, in three counties in the Eastern part of the country, and in some settlements in Transdanubia. Mortality from the cancer of the bronchi and the lungs significantly accumulates in both sexes in four counties in Eastern Hungary. Mortality from cancer of the thyroid gland and leukaemias does not show typical spatial accumulation as well.

CONCLUSIONS

The premature mortality from all malignant diseases and of cancer of the bronchi and lungs of the Hungarian male and female population shows an increasing tendency. Mortality from the latter cause shows a typical spatial accumulation, which causes should be investigated in analytical epidemiological studies. The potential causative role of the Chernobyl accident could not be proven in any case.

[Spatial accumulation of mortality and morbidity from cancer of the prostate (ICD-10:C61)]

The authors examined the spatial accumulation of mortality and morbidity of cancer of the prostate of the total as well as age stratified male population of Hungary. Using GIS, a descriptive epidemiological study was carried out examining the spatial differences of mortality on settlement level with 2000 inhabitants by calculating standardized mortality and morbidity ratios. The significance of the difference of mortality and morbidity from the national mean was tested by chi square probe. On the basis of the results a significant excess in mortality was detected in 11 regions of the country. The unfavourable regions cover 11.6% of the territory of the country where 25.6% of the male population live. A significant excess morbidity can be observed in 8 counties. A significant correlation was found between the unfavourable regions of mortality and morbidity (r=0.443, p<0.05). The age-specific analysis of morbidity revealed the highest excess in morbidity in the age group over 70 years accumulating in 3 counties of Transdanubia and in 6 counties of the Great Plain. On the basis of the results of mortality and morbidity analysis according to age and areas the unfavourable regions can be identified where mortality and morbidity from cancer of the prostate accumulates. These studies serve as a basis for intervention strategies.

[Spatial differences in mortality and morbidity from cancer of the lip, oral cavity and pharynx in Hungary]

In evaluating the health state of the population one of the most reliable parameter is mortality. The development of statistical and spatial analytical methods gave a tool for evaluating mortality and morbidity in small areas. GIS mapping helps in the assessment of health state of small areas, to investigate causal relationship and create plans of intervention. Within the frames of the National Environmental Health Action Programme (NEHAP, 1996) a spatial statistical information system was elaborated. By the help of this system, mortality from cancer of the lip, oral cavity and pharynx (ICD-X.: C00-C14) was analysed for 1986-1997 and morbidity for 1997-1999 by computing standardised mortality and morbidity ratio. Regions with unfavourable mortality and morbidity were defined, statistical significance was tested. After age and gender stratification, a cluster analysis was also carried out. An international comparison of mortality was done as well. According to our data, mortality - most frequent in both sexes according to the international comparison - as well as morbidity showed a typical spatial distribution. An excess in mortality and morbidity is observable in the central part of the country, as well as in the Northern part and in traditional wine producing areas. The spatial accumulation of mortality is very similar to that of mortality from chronic liver diseases (ICD-X.: K70). In the primary prevention of oral cancer smoking cessation and the decrease of alcohol consumption is of great importance. Screening activity of GPs and dental doctors is of major importance in secondary prevention.

[Hallervorden-Spatz disease]

Based on the history of a 5-year-old boy, the clinical picture and the natural history of Hallervorden-Spatz disease are reviewed. In the past, the diagnosis of Hallervorden-Spatz disease has usually been made only post mortem. In the T2 weighted MRI images "eye of the tiger" sign is seen. This is due to iron-accumulation in the pallidum and it makes the earlier, in vivo diagnosis of the disease possible.

Imported lyssa in Hungary

A 14 year old male lived for 5 years in Nigeria, 5 weeks after returning to Hungary he became ill and died within 3 days after a sudden cardiac arrest. Neuropathology revealed rabies. No contamination with animals or infected persons could be detected. The possibility of rabies related (Mokola) virus disease couldn't be excluded.