These infections are underrecognized as a cause of death in the general population and high-risk groups.

BackgroundParkinson’s disease (PD) is 1.5 times more frequent in men than women. Whether age modifies this ratio is unclear. We examined whether male-to-female (M–F) ratios change with age through a French nationwide prevalence/incidence study (2010) and a meta-analysis of incidence studies.MethodsWe used French national drug claims databases to identify PD cases using a validated algorithm. We computed M–F prevalence/incidence ratios overall and by age using Poisson regression. Ratios were regressed on age to estimate their annual change. We identified all PD incidence studies with age/sex-specific data, and performed a meta-analysis of M–F ratios.ResultsOn the basis of 149 672 prevalent (50% women) and 25 438 incident (49% women) cases, age-standardised rates were higher in men (prevalence=2.865/1000; incidence=0.490/1000 person-years) than women (prevalence=1.934/1000; incidence=0.328/1000 person-years). The overall M–F ratio was 1.48 for prevalence and 1.49 for incidence. Prevalence and incidence M–F ratios increased by 0.05 and 0.14, respectively, per 10 years of age. Incidence was similar in men and women under 50 years (M–F ratio <1.2, p>0.20), and over 1.6 (p<0.001) times higher in men than women above 80 years (p trend <0.001). A meta-analysis of 22 incidence studies (14 126 cases, 46% women) confirmed that M– F ratios increased with age (0.26 per 10 years, p trend=0.005).ConclusionsAge-increasing M–F ratios suggest that PD aetiology changes with age. Sex-related risk/protective factors may play a different role across the continuum of age at onset. This finding may inform aetiological PD research.

A case-control study on respiratory cancers was conducted in New Caledonia (South Pacific), where a high incidence of malignant pleural mesothelioma had been observed. The disease pattern suggested an environmental exposure to asbestos. The first results showed that, in some areas, tremolite asbestos derived from local outcroppings was used as whitewash (locally named "pö"). All cases diagnosed between 1993 and 1995 (including 15 pleural mesotheliomas, 228 lung cancers, and 23 laryngeal cancers) and 305 controls were included in the study. Detailed information on past or present use of the whitewash, residential history, smoking, diet, and occupation was collected. The risk of mesothelioma was strongly associated with the use of the whitewash (odds ratio (OR) = 40.9; 95% confidence interval (CI): 5.15, 325). All Melanesian cases had been exposed. Among Melanesian women, exposure to the whitewash was associated with an increased risk of lung cancer (OR = 4.89; 95% CI: 1.13, 21.2), and smokers exposed to po had an approximately ninefold risk (OR = 9.26; 95% CI: 1.72, 49.7) compared with women who never smoked and had never used the whitewash. In contrast, no association was noted between exposure to pö and lung cancer risk among Melanesian men, probably because of lower exposure levels. Among non-Melanesians, the numbers of exposed subjects were too small to assess the effect of exposure to po. There was no indication of elevated risks for the other cancer sites.

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Recent public health crises have shown the need for readily available information allowing proper management by decision-makers. One way of obtaining early information is to involve data providers who already record routine data for their own use. We describe here the results of a pilot network carried out by the InVS (Institut national de veille sanitaire) which gathered data available in real time from hospital emergency departments and register offices. Emergency departments data were registered from patients' computerised medical files. Mortality data were received from the national institute of statistics (Insee). Data were transmitted automatically on a daily basis. Influenza data from outbreaks in 2004/05 and 2005/06 were compared with data from the sentinel network for the same periods. Environmental health data were compared with meteorological temperatures recorded in Paris between June and August 2006. A mortality analysis was conducted on a weekly basis. Correlation between influenza data from emergency departments and data from Sentiweb (sentinel network) was significant (p<0.001) for both outbreaks. In 2005 and 2006, the outbreaks were described similarly by both sources with identification of the start of the outbreaks by both systems during the same weeks. As for data related to heat, a significant correlation was observed between some diagnoses and temperature increases. For both types of phenomena, mortality increased significantly with one to two weeks lag. To our knowledge, this is the first time that a study using real time morbidity and mortality data is conducted. These initial results show how these data complement each other and how their simultaneous analysis in real time makes it possible to quickly measure the impact of a phenomenon.