The APHEA project as a turning point in modern environmental epidemiology: Current and future relevance.

In the late 80s and early 90s, it was unclear whether the observed levels of air pollution were related to health effects, with fragmented evidence based on a few single-city studies. The Air Pollution and Health: a European Approach (APHEA)-funded projects started in 1993 and continued until 2009 and, later, within the context of the APHENA collaboration with researchers from the United States and Canada. APHEA was among the first to introduce the multicity/multicountry approach, using standardized methods and specifically developed protocols, including examining exposure-response functions and investigating nonlinearity, as well as a two-stage analytical approach, with city-specific analysis followed by a meta-analysis and meta-regression to identify effect modifiers. This approach consolidated the time-series regression as a central design for studying health effects of short-term air pollution exposures, enabled extensions to other environmental exposures, specifically climate-related, and contributed to further methodological advances. Health-effects associations, thus, became more robust and easier to compare across locations, facilitating the consensus later reached on the importance of air pollution exposure for health, as well as the funding of multicenter cohort studies. The APHEA projects produced concentration-response functions that were used in health impact assessment and policies, e.g., setting the World Health Organization guidelines and legal standards for short period exposures. This can be particularly relevant, as the health burden of chronic exposures may be enhanced by short-term peaks that trigger health events that would not have otherwise happened for a long time. Although APHEA methods were developed for air pollution health effects, they are also particularly relevant for climate-change-related studies, where short-term exposures (such as temperature or other daily indices combining meteorological variables) are extremely important. Further advantages of time-series studies, making the design important for current and future research, include their relevance for episode-based risk communication and emergency response planning; their smaller susceptibility, compared with cohort studies, to the impact of measurement error leading to underestimating health effects; and their easier implementation, making them indispensable for an initial exploration of a hypothesis.