The heatwave in France during August 2003 was associated with a large increase in the number of deaths. The impact estimated using a time-series design was consistent with crude previous estimates of the impact of the heatwave. This finding suggests that neither air pollution nor long-term and seasonal trends confounded previous estimates. There was no evidence to suggest that the extras deaths associated with the heatwave were simply brought forward in time.

BackgroundDuring August 2003, record high temperatures were observed across Europe, and France was the country most affected. During this period, elevated ozone concentrations were measured all over the country. Questions were raised concerning the contribution of O3 to the health impact of the summer 2003 heat wave.MethodsWe used a time-series design to analyze short-term effects of temperature and O3 pollution on mortality. Counts of deaths were regressed on temperatures and O3 levels, controlling for possible confounders: long-term trends, season, influenza outbreaks, day of the week, and bank holiday effects. For comparison with previous results of the nine cities, we calculated pooled excess risk using a random effect approach and an empirical Bayes approach.FindingsFor the nine cities, the excess risk of death is significant (1.01%; 95% confidence interval, 0.58–1.44) for an increase of 10 μg/m3 in O3 level. For the 3–17 August 2003 period, the excess risk of deaths linked to O3 and temperatures together ranged from 10.6% in Le Havre to 174.7% in Paris. When we compared the relative contributions of O3 and temperature to this joint excess risk, the contribution of O3 varied according to the city, ranging from 2.5% in Bordeaux to 85.3% in Toulouse.InterpretationWe observed heterogeneity among the nine cities not only for the joint effect of O3 and temperatures, but also for the relative contribution of each factor. These results confirmed that in urban areas O3 levels have a non-negligible impact in terms of public health.

Long-term exposure to fine particles, nitrogen dioxide, sulfur dioxide and benzene is associated with an increased risk of non-accidental mortality in France. Our results strengthen existing evidence that outdoor air pollution is a significant environmental risk factor for mortality. Due to the limited sample size and the nature of our study (occupational), further investigations are needed in France with a larger representative population sample.

Background: A study was undertaken of deaths with an underlying or associated cause of chronic obstructive pulmonary disease (COPD), and trends in COPD mortality from 1979 to 2002 in France were analysed. Methods: Data were obtained from the Centre of Epidemiology on the Medical Causes of Death (CépiDc) for individuals aged 45 years and over. Owing to implementation of ICD-10 in 2000 for recording causes of death, two separate periods were analysed (1979-99 and 2000-2). Results: In 2000-2, COPD was the underlying cause of 1.4% of deaths (deaths from COPD) and was mentioned on the death certificate in 3.0% (deaths with COPD). The other main underlying causes in these cases were cardiovascular diseases (32.0%) and cancers (24.5%). In 1979-99, age standardised rates of death with COPD remained stable in men (20.01%/year) and increased in women (+1.7%/year). The mean annual rates of death with COPD per 100 000 were 84 for men and 19 for women in 2000-2. Conclusion: Multiple cause analysis improved the estimate of COPD related mortality. In 1979-99, COPD related mortality rates in France were stable in men but increased in women. Implementation of ICD-10 in 2000 introduced substantial discontinuities in mortality trends.

This work presents a brief overview of Markov models in cancer screening evaluation and focuses on two specific models. A three-state model was first proposed to estimate jointly the sensitivity of the screening procedure and the average duration in the preclinical phase, i.e. the period when the cancer is asymptomatic but detectable by screening. A five-state model, incorporating lymph node involvement as a prognostic factor, was later proposed combined with a survival analysis to predict the mortality reduction associated with screening. The strengths and limitations of these two models are illustrated using data from French breast cancer service screening programmes. The three-state model is a useful frame but parameter estimates should be interpreted with caution. They are highly correlated and depend heavily on the parametric assumptions of the model. Our results pointed out a serious limitation to the five-state model, due to implicit assumptions which are not always verified. Although it may still be useful, there is a need for more flexible models. Over-diagnosis is an important issue for both models and induces bias in parameter estimates. It can be addressed by adding a non-progressive state, but this may provide an uncertain estimation of over-diagnosis. When the primary goal is to avoid bias, rather than to estimate over-diagnosis, it may be more appropriate to correct for over-diagnosis assuming different levels in a sensitivity analysis. This would be particularly relevant in a perspective of mortality reduction estimation.