Conference Agenda

One substantial direct impact of climate change on human health and mortality stems from extreme temperatures. In this study, we explore the phenomenon known as the “harvesting effect”, expecting an effect modification of previous winter mortality on the relationship between temperature and mortality in the following summer and vice versa. We combine mortality data from the ISTAT with temperature data from E-OBS for Italy at the provincial level from 2011 to 2019. Poisson regression models are employed to estimate the effects of temperature extremes on mortality among individuals aged 60 and above. The results reveal that temperatures below and above the comfort zone are associated with an increased monthly mortality rate, with a more robust and pronounced effect size observed in the most extreme temperature bins. Considering the harvesting effect, the results suggest significantly lower effects of warm days and hot days following winters with higher mortality. Additionally, we observe the impact of hot days and in particular the described harvesting effect to be stronger for individuals aged 80+. The results highlight how the increase of vulnerable individuals due to low winter mortality could increase the impacts of heatwaves on the population and for individuals aged 80+.

Both non-optimal heat and cold are linked to increased mortality, with the highest burden attributed to moderate cold. However, the specific socioeconomic and climatic determinants of this relationship, particularly in cold climates, remain underexplored. This study aims to address this gap by examining the association between temperature and mortality across regions of Russia from 2004 to 2019. The analysis utilized a two-stage meta-analytic model to evaluate potential determinants of weekly temperature-mortality relationship. In the first stage, quasi-Poisson regression with DLNM was used to obtain region-specific estimates by four-year periods, controlling for trends, seasonality, and air pollution. In the second stage, these estimates were pooled in a multivariate multilevel meta-regression model, incorporating multiple metapredictors reflecting socioeconomic and geographic contexts. Findings indicate an increase in both heat- and cold-related mortality over the MMT of 17.2°C. RR associated with extreme cold was estimated at 1.23 (1.21–1.25), while for extreme heat, it comprised 1.07 (1.05–1.08). Socioeconomic variables related to income and education provided mixed results, whereas air conditioning adoption was associated with lower heat-related mortality. The climatic context, as indicated by average temperatures, suggests evidence of adaptation to frequently experienced temperature ranges.

Mortality patterns are often influenced by seasonal variations, with deaths often peaking during winter months due to respiratory and cardiovascular diseases. Understanding these seasonal trends is critical for assessing their impact on mortality and life expectancy. While most studies focus on annual data, our research aims to uncover cause-specific intra-annual mortality trends in Italy from 2004 to 2019.

We used monthly death counts by cause of death (ICD-10) from the Italian National Statistical Office (ISTAT), categorised into seventeen major cause groups. We estimated monthly age-standardized death rates (ASDR) by sex and cause, and its excess deaths by comparing observed rates to a baseline from the year’s lowest mortality months. Excess mortality and its ratio to baseline deaths were used to assess the relative impact of short-term mortality shocks across causes.

Most causes of death showed clear excess winter mortality, with the highest peaks observed for respiratory, cardiovascular, and cerebrovascular diseases. Interestingly, while overall mortality declined in the observed period, the impact of intra-annual excess mortality remained stable over time. Analysing the cause-specific contributions to intra-annual excess mortality is an essential aspect of understanding longevity trends and targeted public health interventions.

Europe may experience a disproportionately greater mortality burden due to its higher proportion of older populations and rising temperatures. To date, there has been limited work exploring the implications of climate change on mortality outcomes under different Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCP).

This study examines the impact of future extreme temperatures on mortality across 28 European countries at NUTS2 level. We use a combination of historical data (2014-2023), climate projections based on RCP and SSPs to describe potential future trajectories of European mortality related to temperature and global warming.

We employ a Poisson regression model with fixed effects to understand the temperature–mortality relationships, the SSP framework to assess future mortality accounting for population, and socioeconomic changes, and RCP to present projection on temperature.

We present three SSP-RCP scenarios at European NUTS2 regions, providing percentage changes in temperature-related mortality. Our findings suggest cold-related mortality will decline as winters become milder, but it will continue to surpass heat-related mortality in many regions, particularly in areas with moderate cold temperatures. Furthermore, heat-related deaths are expected to rise significantly, especially in southern Europe, due to more frequent extreme heat events.

Considering that improvements in life expectancy are mainly driven by older populations, understanding how historical contexts impact current life expectancy could contribute to elucidate the differences in this outcome.

This research focuses on the selection effect, which suggests that adverse early-life conditions may favour individuals with higher resilience, thus enhancing longevity. This mechanism implies that those who survive difficult early conditions contribute significantly to life expectancy as they age. For this purpose, we focus on Spain, a country which despite a historically low life expectancy (41.41 years in 1908) has emerged as a current leader in life expectancy worldwide.

This research aims to test if the long period of stress (1936-1960) in Spain led to a selection effect that positively influenced life expectancy. For this purpose, we first apply Age-Cohort-Period analysis and, second, decomposition methods to assess the contribution of different cohorts on life expectancy in this country.

Initial descriptive results point into the direction of this hypothesis. However, this must be confirmed and include comparisons with other Western countries with distinct recent historical contexts (Switzerland, France, Italy, Sweden, the UK, and USA) to assess the impact of historical stress on current mortality rates.