The determination of an appropriate catchment area for a hospital providing highly specialized (i.e. tertiary) health care is typically a trade-off between ensuring adequate client volumes and maintaining reasonable accessibility for all potential clients. This may pose considerable challenges, especially in sparsely inhabited regions. In Finland, tertiary health care is concentrated in five university hospitals, which provide services in their dedicated catchment areas. This study utilizes Geographic Information Systems (GIS), together with grid-based population data and travel-time estimates, to assess the spatial accessibility of these hospitals. The current geographical configuration of the hospitals is compared to a normative assignment, with and without capacity constraints. The aim is to define optimal catchment areas for tertiary hospitals so that their spatial accessibility is as equal as possible. The results indicate that relatively modest improvements can be achieved in accessibility by using normative assignment to determine catchment areas.

A fair amount of research has been carried out on pathfinding problems in the context of transportation networks, whereas pathfinding in off-network space has received far less interest. In geographic information systems (GIS), the latter is usually associated with the cost surface method, which allows optimum paths to be calculated through rasters in which the value of each cell depicts the cost of traversal through that cell. One of the problems with this method is computational expense, which may be very high with large rasters. In this study, a pathfinding method called Hierarchical Pathfinding A* (HPA*), based on an abstraction strategy, is investigated as an alternative to the traditional approach. The aim of this study is to enhance the method to make it more suitable for calculating paths over cost rasters with nonuniform traversal cost. The method is implemented in GIS and tested with actual data. The results indicate that by taking into account the information embedded in the cost raster, paths of relatively good quality can be calculated while effecting significant savings in computational effort compared to the traditional, nonhierarchical approach.

There is accumulating evidence that prenatal exposure to air pollution disturbs fetal growth and development, but little is known about these effects in cold climates or their season-specific or joint effects. Our objective was to assess independent and joint effects of prenatal exposure to specific air pollutants on the risk of low birth weight (LBW). We utilized the 2568 children of the Espoo Cohort Study, born between 1984 and 1990 and living in the City of Espoo. We conducted stratified analyses for births during warm and cold seasons separately. We analyzed the effect estimates using multi-pollutant Poisson regression models with risk ratio (RR) as the measure of effect. The risk of LBW was related to exposure to CO (adjusted RR 1.44, 95% confidence interval [CI]: 1.04–2.00) and exposure to O₃ in the spring–summer season (1.82, 1.11–2.96). There was also evidence of synergistic effects between CO and O₃ (relative risk due to interaction (RERI), all year 1.08, 95% CI: 0.27–4.94, spring–summer 3.97, 2.17–25.85) and between PM_2.5 and O₃ (all year 0.72, −0.07–3.60, spring–summer 2.80, 1.36–19.88). We present new evidence of both independent and joint effects of prenatal exposure to low levels of air pollution in a cold climate on the risk of LBW.

Previous studies have suggested that living close to green spaces has protective health effects, but potential effects on asthma are contradictory. We investigated the association between the amount of greenness in the residential area during pregnancy and early life and development of asthma in the first 27 years of life. The study population included all 2568 members of the Espoo Cohort Study, Finland. We calculated individual-level exposure to green space measured as cumulative Normalized Difference Vegetation Index (cumNDVI in unit-months) within 300 m of the participant's residence during pregnancy and the first two years of life in both spring and summer seasons. The onset of asthma was assessed using information from the baseline and follow-up surveys. Exposure to residential greenness in the spring season during pregnancy was associated with an increased risk of asthma up to 6 years of age, with an adjusted hazard ratio (aHR) of 3.72 (95% confidence interval (CI): 1.11, 12.47) per 1 unit increase in cumNDVI. Increased greenness in the summer during pregnancy associated with asthma up to 6 years, with an aHR of 1.41 (95% CI: 0.85, 2.32). The effect was found to be related to increased greenness particularly during the third trimester of pregnancy, with an aHR of 2.37 (95% CI: 1.36, 4.14) per 1 unit increase of cumNDVI. These associations were weaker at the ages of 12 and 27 years. No association was found between NDVI in the first two years of life and the development of asthma. Our findings provide novel evidence that exposure to greenness during pregnancy increases the risk of developing asthma. The adverse effects were strongest for the prenatal greenness in the spring season and in the third trimester of pregnancy. Both the season and trimester of exposure to greenness are critical in the development of asthma.