Aymeric Ung

The mortality impacts of fine particles in France

INTRODUCTION Worldwide, air pollution has become a main environmental cause of premature mortality. This burden is largely due to fine particles. Recent cohort studies have confirmed the health risks associated with chronic exposure to PM2.5 for European and French populations. We assessed the mortality impact of PM2.5 in continental France using these new results. METHODS Based on a meta-analysis of French and European cohorts, we computed a shrunken estimate of PM2.5-mortality relationship for the French population (RR 1.15 [1.05:1.25] for a 10μg/m(3) increase in PM2.5). This RR was applied to PM2.5 annual concentrations estimated at a fine spatial scale, using a classical health impacts assessment method. The health benefits associated with alternative scenarios of improving air quality were computed for 36,219 French municipalities for 2007-2008. RESULTS 9% of the total mortality in continental France is attributable to anthropogenic PM2.5. This represents >48,000 deaths per year, and 950,000years of life lost per year, more than half occurring in urban areas larger than 100,000 inhabitants. If none of the municipalities exceeded the World Health Organization guideline value for PM2.5 (10μg/m(3)), the total mortality could be decreased by 3%, corresponding to 400,000years of life saved per year. CONCLUSION Results were consistent with previous estimates of the long-term mortality impacts of fine particles in France. These findings show that further actions to improve air quality in France would substantially improve health.

How to use near real-time health indicators to support decision-making during a heat wave: the example of the French heat wave warning system

Introduction The French warning system for heat waves is based on meteorological forecasts. Near real-time health indicators are used to support decision-making, e.g. to extend the warning period, or to choose the most appropriate preventive measures. They must be analysed rapidly to provide decision-makers useful and in-time information. The objective of the study was to evaluate such health indicators. Methods A literature review identified a range of possible mortality and morbidity indicators. A reduced number were selected, based on several criteria including sensitivity to heat, reactivity, representativity and data quality. Two methods were proposed to identify indicator-based statistical alarms: historical limits or control charts, depending on data availability. The use of the indicators was examined using the 2006 and 2009 heat waves. Results Out of 25 possible indicators, 5 were selected: total mortality, total emergency calls, total emergency visits, emergency visits for people aged 75 and over and emergency visits for causes linked to heat. In 2006 and 2009, no clear increases were observed during the heat waves. The analyses of real-time health indicators showed there was no need to modify warning proposals based on meteorological parameters. Discussion These findings suggest that forecasted temperatures can be used to anticipate heat waves and promote preventive actions. Health indicators may not be needed to issue a heat wave alert, but daily surveillance of health indicators may be useful for decision-makers to adapt prevention measures.

Heat and cold related-mortality in 18 French cities

OBJECTIVES Understanding the dynamics of the temperature-mortality relationship is an asset to support public health interventions. We investigated the lag structure of the mortality response to cold and warm temperatures in 18 French cities between 2000 and 2010. METHODS A distributed lag non-linear generalized model using a quasi-Poisson distribution and controlling for classical confounding factors was built in each city. A fitted meta-analytical model combined the city-specific models to derive the best linear unbiased prediction of the association, and a meta-regression explored the influence of background characteristics of the cities. The fraction of mortality attributable to cold and heat was estimated with reference to the minimum mortality temperature. RESULTS Between 2000 and 2010, 3.9% [CI 95% 3.2:4.6] of the total mortality was attributed to cold, and 1.2% [1.1:1.2] to heat. The immediate increase in mortality following high temperatures was partly compensated by a harvesting effect when temperatures were below the 99.2 percentiles of the mean temperature distributions. DISCUSSION Cold represents a significant public health burden, mostly driven by moderate temperatures (between percentiles 2.5 and 25). The population is better adapted to warm temperatures, up to a certain intensity when heat becomes an acute environmental health emergency (above percentile 99). The rapid increase in mortality risk at very high temperatures percentiles calls for an active adaptation in a context of climate change.