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BackgroundThis methodological paper describes the integration of the ‘European Health Interview Survey wave 2’ (EHIS 2) into the ‘German Health Update’ 2014/2015 (GEDA 2014/2015-EHIS).MethodsGEDA 2014/2015-EHIS is a cross-sectional health survey. A two-stage stratified cluster sampling approach was used to recruit persons aged 15 years and older with permanent residence in Germany. Two different modes of data collection were used, self-administered web questionnaire and self-administered paper questionnaire. The survey instrument implemented the EHIS 2 modules on health status, health care use, health determinants and social background variables and additional national questions. Data processing was conducted according to the quality and validation rules specified by Eurostat. ResultsIn total, 24,824 questionnaires were completed. The response rate was 27.6%. The two-stage cluster sample method seems to have been successful in achieving a sample with high representativeness. The final micro data file was inspected, approved and certified by Eurostat. Access to micro data of the EHIS 2 can be provided by Eurostat via research contract and to the GEDA 2014/2015-EHIS public use file by the Research Data Centre of the Robert Koch Institute. First EHIS 2 results are available at the Eurostat website.ConclusionsIntegrating a multinational health survey into an existing national health monitoring system was a challenge in Germany. The national survey methodology for conducting the survey had to be further developed in order to meet the overarching goal of harmonizing the health information from national statistical offices and public health research institutes across the European Union. The harmonized EHIS 2 data source will profoundly impact international public health research in the near future. The next EHIS wave 3 will be conducted around 2019.

A steep rise in Hepatitis E diagnoses is currently being observed in Germany and other European countries. The objective of this study was (i) to assess whether this trend mirrors an increase in infection pressure or is caused by increased attention and testing and (ii) estimate individual and population-based Hepatitis E Virus (HEV) seroconversion and seroreversion rates for Germany. We measured anti-HEV IgG prevalence in 10 407 adults participating in two linked, population-representative serosurveys (total n = 12 971) conducted in 1998 and 2010. In this period, we found a moderate but statistically significant decline of overall anti-HEV IgG prevalence from 18.6% to 15.3%. At both time points, seroprevalence increased with age and peaked in persons born between 1935 and 1959 suggesting a past period of increased infection pressure. Paired samples of individuals participating in 1998 and 2010 (n = 2564) revealed respective seroconversion and seroreversion rates of 6.2% and 22.6% among seronegative and seropositive individuals during 12 years, or 5.2 and 2.9 per 1000 inhabitants per year. This corresponds to a total of 417 242 [95%CI: 344 363-495 971] new seroconversions per year in the German population. While anti-HEV seroprevalence has decreased in the last decade, infection pressure and seroincidence remains high in Germany. Continuously rising numbers of Hepatitis E diagnoses in Europe are likely due to an increased awareness of clinicians and indicate that still there is a gap between incident and diagnosed cases. Studies on the true burden of the disease, specific risk factors and sources of autochthonous infections as well as targeted prevention measures are urgently needed.

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This article is about modeling count data with zero truncation. A parametric count density family is considered. The truncated mixture of densities from this family is different from the mixture of truncated densities from the same family. Whereas the former model is more natural to formulate and to interpret, the latter model is theoretically easier to treat. It is shown that for any mixing distribution leading to a truncated mixture, a (usually different) mixing distribution can be found so that the associated mixture of truncated densities equals the truncated mixture, and vice versa. This implies that the likelihood surfaces for both situations agree, and in this sense both models are equivalent. Zero-truncated count data models are used frequently in the capture-recapture setting to estimate population size, and it can be shown that the two Horvitz-Thompson estimators, associated with the two models, agree. In particular, it is possible to achieve strong results for mixtures of truncated Poisson densities, including reliable, global construction of the unique NPMLE (nonparametric maximum likelihood estimator) of the mixing distribution, implying a unique estimator for the population size. The benefit of these results lies in the fact that it is valid to work with the mixture of truncated count densities, which is less appealing for the practitioner but theoretically easier. Mixtures of truncated count densities form a convex linear model, for which a developed theory exists, including global maximum likelihood theory as well as algorithmic approaches. Once the problem has been solved in this class, it might readily be transformed back to the original problem by means of an explicitly given mapping. Applications of these ideas are given, particularly in the case of the truncated Poisson family.

The cardiometabolic risk profile of the German adult population as a whole improved over a period of 20 years. Further in-depth analyses are now planned.

The self-controlled case series method (SCCS) was developed to analyze the association between a time-varying exposure and an outcome event. We consider penta- or hexavalent vaccination as the exposure and unexplained sudden unexpected death (uSUD) as the event. The special situation of multiple exposures and a terminal event requires adaptation of the standard SCCS method. This paper proposes a new adaptation, in which observation periods are truncated according to the vaccination schedule. The new method exploits known minimum spacings between successive vaccine doses. Its advantage is that it is very much simpler to apply than the method for censored, perturbed or curtailed post-event exposures recently introduced. This paper presents a comparison of these two SCCS methods by simulation studies and an application to a real data set. In the simulation studies, the age distribution and the assumed vaccination schedule were based on real data. Only small differences between the two SCCS methods were observed, although 50 per cent of cases could not be included in the analysis with the SCCS method with truncated observation periods. By means of a study including 300 uSUD, a 16-fold risk increase after the 4th dose could be detected with a power of at least 90 per cent. A general 2-fold risk increase after vaccination could be detected with a power of 80 per cent. Reanalysis of data from cases of the German case-control study on sudden infant death (GeSID) resulted in slightly higher point estimates using the SCCS methods than the odds ratio obtained by the case-control analysis.