Exploring the small-scale spatial distribution of hypertension and its association to area deprivation based on health insurance claims in Northeastern Germany

Abstract Background Hypertension is one of the most frequently diagnosed chronic conditions in Germany. Targeted prevention strategies and allocation of general practitioners where they are needed most are necessary to prevent severe complications arising from high blood pressure. However, data on chronic diseases in Germany are mostly available through survey data, which do not only underestimate the actual prevalence but are also only available on coarse spatial scales. The discussion of including area deprivation for planning of healthcare is still relatively young in Germany, although previous studies have shown that area deprivation is associated with adverse health outcomes, irrespective of individual characteristics. The aim of this study is therefore to analyze the spatial distribution of hypertension at very fine geographic scales and to assess location-specific associations between hypertension, socio-demographic population characteristics and area deprivation based on health insurance claims of the AOK Nordost. Methods To visualize the spatial distribution of hypertension prevalence at very fine geographic scales, we used the conditional autoregressive Besag–York–Mollié (BYM) model. Geographically weighted regression modelling (GWR) was applied to analyze the location-specific association of hypertension to area deprivation and further socio-demographic population characteristics. Results The sex- and age-adjusted prevalence of hypertension was 33.1% in 2012 and varied widely across northeastern Germany. The main risk factors for hypertension were proportions of insurants aged 45–64, 65 and older, area deprivation and proportion of persons commuting to work outside their residential municipality. The GWR model revealed important regional variations in the strength of the examined associations. Conclusion Area deprivation has only a significant and therefore direct influence in large parts of Mecklenburg-West Pomerania. However, the spatially varying strength of the association between demographic variables and hypertension indicates that there also exists an indirect effect of area deprivation on the prevalence of hypertension. It can therefore be expected that persons ageing in deprived areas will be at greater risk of hypertension, irrespective of their individual characteristics. The future planning and allocation of primary healthcare in northeastern Germany would therefore greatly benefit from considering the effect of area deprivation

Distribution of lymphocytes in intermingled skin grafts

Chinese intermingled skin grafts of allogenic material interspersed with small autogenic islets heal permanently with no signs of a rejection reaction. A study of the T-helper and T-suppressor cells in the region of the autogenic islets and the remaining allodermis revealed a distinctly greater frequency of these cells in the islets, with marked massing of the cells between the autoepithelium and the autodermis. Histologically it could be shown, that the Langerhans' cells grow over the allodermis together with the epithelium, although compared with the autogenic islets their number in the newly formed epidermis remained reduced

The Spatial Distribution of Hepatitis C Virus Infections and Associated Determinants - An Application of a Geographically Weighted Poisson Regression for Evidence-Based Screening Interventions in Hotspots

Background Hepatitis C Virus (HCV) infections are a major cause for liver diseases. A large proportion of these infections remain hidden to care due to its mostly asymptomatic nature. Population-based screening and screening targeted on behavioural risk groups had not proven to be effective in revealing these hidden infections. Therefore, more practically applicable approaches to target screenings are necessary. Geographic Information Systems (GIS) and spatial epidemiological methods may provide a more feasible basis for screening interventions through the identification of hotspots as well as demographic and socio-economic determinants. Methods Analysed data included all HCV tests (n = 23,800) performed in the southern area of the Netherlands between 2002-2008. HCV positivity was defined as a positive immunoblot or polymerase chain reaction test. Population data were matched to the geocoded HCV test data. The spatial scan statistic was applied to detect areas with elevated HCV risk. We applied global regression models to determine associations between population-based determinants and HCV risk. Geographically weighted Poisson regression models were then constructed to determine local differences of the association between HCV risk and population-based determinants. Results HCV prevalence varied geographically and clustered in urban areas. The main population at risk were middle-aged males, non-western immigrants and divorced persons. Socio-economic determinants consisted of one-person households, persons with low income and mean property value. However, the association between HCV risk and demographic as well as socio-economic determinants displayed strong regional and intra-urban differences. Discussion The detection of local hotspots in our study may serve as a basis for prioritization of areas for future targeted interventions. Demographic and socio-economic determinants associated with HCV risk show regional differences underlining that a one-size-fits-all approach even within small geographic areas may not be appropriate. Future screening interventions need to consider the spatially varying association between HCV risk and associated demographic and socio-economic determinants

Anwendungsgebiete und Limitierungen der amtlichen Statistik für die regionale Versorgungsforschung. Ein Diskussionsbeitrag der AOK Nordost am Beispiel der koronaren Herzkrankheit.

Regionale Analysen chronischer Erkrankungen in Abrechnungsdaten von Krankenkassen können einen entscheidenden Beitrag dazu leisten, zukünftige Versorgungsstrukturen bedarfsgerecht zu planen. Hierbei sind neben den Abrechnungsdaten selbst auch die Daten der amtlichen Statistik von zentraler Bedeutung: Erst die Analyse des Zusammenhangs zwischen Erkrankungslast und der demografischen und sozio-ökonomischen Zusammensetzung des Wohnortes erlaubt Rückschlüsse darüber, wie sich die Erkrankungslast in Zukunft entwickeln wird. Derzeit können die Daten der amtlichen Statistik allerdings aufgrund der maximalen räumlichen Gliederungstiefe bis zur Gemeindeebene nicht ihr volles Potenzial entfalten. Dieser Beitrag verfolgt mehrere Ziele: (i) Am Beispiel der koronaren Herzkrankheit unter den Versicherten der AOK Nordost in den Ländern Berlin, Brandenburg und Mecklenburg- Vorpommern soll die Verwendung von Daten der amtlichen Statistik beispielhaft vorgestellt werden, (ii) die daraus entstehenden Implikationen für die zukünftige Bedarfsplanung sollen erläutert werden und (iii) die derzeitigen Limitierungen von Daten der amtlichen Statistik sollen diskutiert und Anforderungen an diese Daten aus Sicht der Versorgungsforschung vorgestellt werden

Estimating the spatial distribution of acute undifferentiated fever (AUF) and associated risk factors using emergency call data in India. A symptom-based approach for public health surveillance

The System for Early-warning based on Emergency Data (SEED) is a pilot project to evaluate the use of emergency call data with the main complaint acute undifferentiated fever (AUF) for syndromic surveillance in India. While spatio-temporal methods provide signals to detect potential disease outbreaks, additional information about socio-ecological exposure factors and the main population at risk is necessary for evidence-based public health interventions and future preparedness strategies. The goal of this study is to investigate whether a spatial epidemiological analysis at the ecological level provides information on urban-rural inequalities, socio-ecological exposure factors and the main population at risk for AUF. Our results displayed higher risks in rural areas with strong local variation. Household industries and proximity to forests were the main socio-ecological exposure factors and scheduled tribes were the main population at risk for AUF. These results provide additional information for syndromic surveillance and could be used for evidence-based public health interventions and future preparedness strategies

A concept for routine emergency-care data-based syndromic surveillance in Europe

Ziemann A, Rosenkoetter N, Riesgo LG-C, et al. A concept for routine emergency-care data-based syndromic surveillance in Europe. Epidemiology and Infection. 2014;142(11):2433-2446.We developed a syndromic surveillance (SyS) concept using emergency dispatch, ambulance and emergency-department data from different European countries. Based on an inventory of sub-national emergency data availability in 12 countries, we propose framework definitions for specific syndromes and a SyS system design. We tested the concept by retrospectively applying cumulative sum and spatio-temporal cluster analyses for the detection of local gastrointestinal outbreaks in four countries and comparing the results with notifiable disease reporting. Routine emergency data was available daily and electronically in 11 regions, following a common structure. We identified two gastrointestinal outbreaks in two countries; one was confirmed as a norovirus outbreak. We detected 1/147 notified outbreaks. Emergency-care data-based SyS can supplement local surveillance with near real-time information on gastrointestinal patients, especially in special circumstances, e. g. foreign tourists. It most likely cannot detect the majority of local gastrointestinal outbreaks with few, mild or dispersed cases