Elderly people are known to be more vulnerable than the general population to a range of weather-related hazards such as heat waves, icy conditions and cold periods. In the Nordic region, some of these hazards are projected to change their frequency and intensity in the future, while at the same time strong increases are projected in the proportion of elderly in the population. This paper reports results from three projects studying the potential impacts of climate change on elderly people in the Nordic region. An interactive web-based tool has been developed for mapping and combining indicators of climate change vulnerability of the elderly, by municipality, across three Nordic countries: Finland, Norway and Sweden. The tool can also be used for projecting temperature-related mortality in Finland under different projections of future climate. The approach to vulnerability mapping differs from most previous studies in which researchers selected the indicators to combine into an index. Here, while researchers compile data on indicators that can be accessed in the mapping tool, the onus is on the users of the tool to decide which indicators are of interest and whether to map them individually or as combined indices. Stakeholders with responsibility for the care and welfare of the elderly were engaged in the study through interviews and a workshop. They affirmed the usefulness of the prototype mapping tool for raising awareness about climate change as a potential risk factor for the elderly and offered suggestions on potential refinements, which have now been implemented. These included adding background information on possible adaptation measures for ameliorating the impacts of extreme temperatures, and improved representation of uncertainties in projections of future exposure and adaptive capacity.

Climate change is expected to increase heat-related and decrease cold-related mortality. The extent of acclimatization of the population to gradually-changing thermal conditions is not well understood. We aimed to define the relationship between mortality and temperature extremes in different age groups in the Helsinki-Uusimaa hospital district in Southern Finland, and changes in sensitivity of the population to temperature extremes over the period of 1972–2014. Time series of mortality were made stationary with a method that utilizes 365-day Gaussian smoothing, removes trends and seasonality, and gives relative mortality as the result. We used generalized additive models to examine the association of relative mortality to physiologically equivalent temperature (PET) and to air temperature in the 43-year study period and in two 21-year long sub-periods (1972–1992 and 1994–2014). We calculated the mean values of relative mortality in percentile-based categories of thermal indices. Relative mortality increases more in the hot than in the cold tail of the thermal distribution. The increase is strongest among those aged 75 years and older, but is somewhat elevated even among those younger than 65 years. Above the 99th percentile of the PET distribution, the all-aged relative mortality decreased in time from 18.3 to 8.6%. Among those ≥75 years old, the decrease in relative mortality between the sub-periods were found to be above the 90th percentile. The dependence of relative mortality on cold extremes was negligible, except among those ≥75 years old, in the latter period. Thus, heat-related mortality is also remarkable in Finland, but the sensitivity to heat stress has decreased over the decades.

Urbanization and ongoing climate change increase the exposure of the populations to heat stress, and the urban heat island (UHI) effect may magnify heat-related mortality, especially during heatwaves. We studied temperature-related mortality in the city of Helsinki—with urban and suburban land uses—and in the surrounding Helsinki-Uusimaa hospital district (HUS-H, excluding Helsinki)—with more rural types of land uses—in southern Finland for two decades, 2000–2018. Dependence of the risk of daily all-cause deaths (all-age and 75+ years) on daily mean temperature was modelled using the distributed lag nonlinear model (DLNM). The modelled relationships were applied in assessing deaths attributable to four intensive heatwaves during the study period. The results showed that the heat-related mortality risk was substantially higher in Helsinki than in HUS-H, and the mortality rates attributable to four intensive heatwaves (2003, 2010, 2014 and 2018) were about 2.5 times higher in Helsinki than in HUS-H. Among the elderly, heat-related risks were also higher in Helsinki, while cold-related risks were higher in the surrounding region. The temperature ranges recorded in the fairly coarse resolution gridded datasets were not distinctly different in the two considered regions. It is therefore probable that the modelling underestimated the actual exposure to the heat stress in Helsinki. We also studied the modifying, short-term impact of air quality on the modelled temperature-mortality association in Helsinki; this effect was found to be small. We discuss a need for higher resolution data and modelling the UHI effect, and regional differences in vulnerability to thermal stress.

Icy and snowy sidewalks are typical wintertime phenomena in Finland. Wintertime slipping injuries are common and lead to substantial economic costs to health care as well as losses to society due to long sick leaves. In Finland, almost every second person slips and falls outdoors annually, and around 70,000 persons are injured needing medical attention. Typically, the most slippery conditions are encountered when the daily average temperature is slightly below 0°C or temperature crosses 0°C and there is precipitation in some form. The Finnish Meteorological Institute (FMI) has developed a numerical weather model that simulates the level of slipperiness on the sidewalks. The model classifies the sidewalk slipperiness into three classes; normal, slippery and very slippery. The FMI issues warnings of hazardous sidewalk conditions to the general public. Pedestrians' road safety can be increased with sidewalk condition forecasts and warnings. When warned, people can choose proper footwear or use anti‐slip devices, change the route or mode of transport, postpone the journey or cancel it altogether. Precise and reliable weather and sidewalk condition forecasts enable targeted and more effective sidewalk maintenance activities that can improve the grip of sidewalks and thus reduce the risk of accidents and injuries. This study presents the sidewalk condition model RoadSurf‐Pedestrian, its physical principles and examples of model runs. There are some challenges in the modelling of the slipperiness but the model gives valuable information on the slipperiness for duty forecasters. Slipping injury statistics are also presented and used as verification data.

The aim of this study was to assess regional differences in temperature–mortality relationships across 21 hospital districts in Finland. The temperature dependence of the daily number of all-cause, all-aged deaths during 2000–2014 was studied in each hospital district by using daily mean temperatures, spatially averaged across each hospital district, to describe exposure to heat stress and cold stress. The relationships were modelled using distributed lag non-linear models (DLNM). In a simple model version, no delayed impacts of heat and cold on mortality were taken into account, whereas a more complex version included delayed impacts up to 25 days. A meta-analysis with selected climatic and sociodemographic covariates was conducted to study differences in the relationships between hospital districts. A pooled mortality-temperature relationship was produced to describe the average relationship in Finland. The simple DLNM model version without lag gave U-shaped dependencies of mortality on temperature almost without exception. The outputs of the model version with a 25-day lag were also U-shaped in most hospital districts. According to the meta-analysis, the differences in the temperature-mortality relationships between hospital districts were not statistically significant on the absolute temperature scale, meaning that the pooled mortality–temperature relationship can be applied to the whole country. However, on a relative temperature scale, heterogeneity was found, and the meta-regression suggested that morbidity index and population in the hospital districts might explain some of this heterogeneity. The pooled estimate for the relative risk (RR) of mortality at a daily mean temperature of 24 °C was 1.16 (95% CI 1.12–1.20) with reference at 14 °C, which is the minimum mortality temperature (MMT) of the pooled relationship. On the cold side, the RR at a daily mean temperature of −20 °C was 1.14 (95% CI 1.12–1.16). On a relative scale of daily mean temperature, the MMT was found at the 79th percentile.