Temperature-related mortality in France, a comparison between regions with different climates from the perspective of global warming.

This paper aims to explain the results of an observational population study that was carried out between 1991 and 1995 in six regions (departments) in France. The study was to assess the relationship between temperature and mortality in a few areas of France that offer widely varying climatic conditions and lifestyles, to determine their thermal optimum, defined as a 3 degrees C temperature band with the lowest mortality rate in each area, and then to compare the mortality rates from this baseline band with temperatures above and below the baseline. The study period was selected because it did not include extreme cold or hot events such as a heatwave. Data on daily deaths from each department were first used to examine the entire population and then to examine men, women, various age groups and various causes of death (respiratory disease, stroke, ischaemic heart disease, other disease of the circulatory system, and all other causes excluding violent deaths). Mean temperatures were provided by the National Weather Service. The results depicted an asymmetrical V- or U-shaped relationship between mortality and temperature, with a thermal optimum lower for the elderly, and generally lower for women than for men except in Paris. The relationship was also different depending on the cause of death. In all cases, more evidence was collected showing that cold weather was more deadly than hot weather, and it would now be interesting to enlarge the study to include years with cold spells and heatwaves. Furthermore, the results obtained could be of great use in estimating weather-related mortality as a consequence of future climate-change scenarios.

Ragweed in France: an invasive plant and its allergenic pollen.

BACKGROUND: Ragweed is an annual, herbaceous, wind-pollinated plant that is responsible for strong allergies. In France, it is mainly present in the region of Lyon, where it threatens the health of the population. OBJECTIVE: To analyze annual, daily, and bihourly pollen concentrations in the air to determine the characteristics of ragweed pollination and in particular its diurnal rhythm. METHODS: Ragweed pollens were sampled from 1987 to 2001 by a Hirst volumetric trap calibrated to handle a flow of 10 L/min of air, which roughly corresponds to a human breathing rhythm. Pollen counts were performed on a daily and bihourly basis, which is of particular importance in allergologic practice. RESULTS: Ragweed pollination occurs from the beginning of August to the end of September. Annual and daily levels of pollen have increased significantly since 1987. The pronounced diurnal periodicity shows a peak from 9 to 11 AM. Pollen counts increased from the early morning with temperature increase and relative humidity decrease. CONCLUSIONS: Daily pollen counts of this strongly allergic plant are above the allergic thresholds commonly defined, limiting the interest of eradication campaigns. Thus, prevention of ragweed allergy depends on informing and educating the public through reports and updates. Diurnal variations seem to be the most crucial part of such a report, allowing allergy patients to adapt their daily outdoor activities in respect to the pollen peaks and off-peaks.

Two statistical approaches to forecasting the start and duration of the pollen season of Ambrosia in the area of Lyon (France).

The aim of the present study was to forecast the start and duration of the pollen season of Ambrosia from meteorological data, in order to provide early information to allergists and allergic people. We used the airborne pollen data from Lyon (France), sampled using a Hirst trap from 1987 to 1999, and the meteorological data for the same period: air temperature (minimal, maximal, and average), rainfall, relative humidity, sunshine duration and soil temperature. Two forecasting models were used, one summing the temperatures and the other making use of a multiple regression on 10-day or monthly meteorological parameters. The start of the pollen season was predicted with both methods, results being more accurate with the regression (the errors between the predicted and the observed SDP ranging from 0 to 3 days). The duration of the pollen season was predicted by a regression model, errors ranging from 0 to 7 days. The models were later tested with satisfactory results from 2 additional years (2000 and 2001). Such forecasting models are helpful for allergic people, who have to begin their anti-allergic treatment before the start of the pollen season and not when the symptoms have appeared, since a preventive treatment is more efficient than a curative one. The regression allows predictions to be made 3-5 weeks in advance and so it is of particular interest. The forecasts will be broadcast on the Internet.