Mortality and morbidity in the city of Bern, Switzerland, 1805-1815 with special emphasis on infant, child and maternal deaths

This article contributes to the research on demographics and public health of urban populations of preindustrial Europe. The key source is a burial register that contains information on the deceased, such as age and sex, residence and cause of death. This register is one of the earliest compilations of data sets of individuals with this high degree of completeness and consistency. Critical assessment of the register's origin, formation and upkeep promises high validity and reliability. Between 1805 and 1815, 4,390 deceased inhabitants were registered. Information concerning these individuals provides the basis for this study. Life tables of Bern's population were created using different models. The causes of death were classified and their frequency calculated. Furthermore, the susceptibility of age groups to certain causes of death was established. Special attention was given to causes of death and mortality of newborns, infants and birth-giving women. In comparison to other cities and regions in Central Europe, Bern's mortality structure shows low rates for infants (q0=0.144) and children (q1-4=0.068). This could have simply indicated better living conditions. Life expectancy at birth was 43 years. Mortality was high in winter and spring, and decreased in summer to a low level with a short rise in August. The study of the causes of death was inhibited by difficulties in translating early 19th century nomenclature into the modern medical system. Nonetheless, death from metabolic disorders, illnesses of the respiratory system, and debilitation were the most prominent causes in Bern. Apparently, the worst killer of infants up to 12 months was the "gichteren", an obsolete German term for lethal spasmodic convulsions. The exact modern identification of this disease remains unclear. Possibilities such as infant tetanus or infant epilepsy are discussed. The maternal death rate of 0.72% is comparable with values calculated from contemporaneous sources. Relevance of childbed fever in the early 1800s was low. Bern's data indicate that the extent of deaths related to childbirth in this period is overrated. This research has an explicit interdisciplinary value for various fields including both the humanities and natural sciences, since information reported here represents the complete age and sex structure of a deceased population. Physical anthropologists can use these data as a true reference group for their palaeodemographic studies of preindustrial Central Europe of the late 18th and early 19th century. It is a call to both historians and anthropologists to use our resources to a better effect through combination of methods and exchange of knowledge.

Tabulation of multiple responses

Although multiple-response questions are quite common in survey research, Stata’s official release does not provide much capability for an effective analysis of multiple-response variables. For example, in a study on drug addiction an interview question might be, “Which substances did you consume during the last four weeks?” The respondents just list all the drugs they took, if any; e.g., an answer could be “cannabis, cocaine, heroin” or “ecstasy, cannabis” or “none”, etc. Usually, the responses to such questions are stored as a set of variables and, therefore, cannot be easily tabulated. I will address this issue here and present a new module to compute one- and two-way tables of multiple responses. The module supports several types of data structure, provides significance tests, and offers various options to control the computation and display of the results. In addition, tools to create graphs of multiple-response distributions are presented.

Tabulation of multiple responses

Although multiple response questions are quite common in survey research, Stata's official release does not provide much possibility for an effective analysis of multiple response variables. For example, in a study on drug addiction an interview question might be, "Which substances did you consume during the last four weeks?" The respondents just list all the drugs they took if any, e.g., an answer could be "cannabis, cocaine, heroin" or "ecstasy, cannabis" or "none", etc. Usually, the responses to such questions are held as a set of variables and, therefore, cannot be easily tabulated. I will address this issue and present a new module to compute one- and two-way tables of multiple responses. The module supports several types of data structure, provides significance tests, and offers various options to control the computation and display of the results.

Sweat test in patients with glucose-6-phosphate-1-dehydrogenase deficiency

BACKGROUND: A false-positive sweat test in patients with deficiency of glucose-6-phosphate-1-dehydrogenase (EC 1.1.1.49; G6PD) is repeatedly reported. METHODS: Sweat chloride or conductivity was measured in 11 patients with G6PD deficiency. RESULTS: Mean (SD) chloride level (n = 8, median age 9.2 years, range 1.9-48.5) was 18.8 (9.6 mmol/l) and, mean (SD) sodium level was 26.0 (10.0 mmol/l), respectively, and mean (SD) conductivity (n = 3, median age 6.6 years, range 1.9-40.5) was 34.3 (6.5 mmol/l). CONCLUSION: In sweat of 11 patients with G6PD deficiency we did not find any abnormality. The reason for alleged false-positive sweat test in patients with G6PD deficiency is not known and we were unable to identify any original reference. It appears that tables of putative false-positive sweat tests in several disease states have been directly "copied and pasted" from one paper or textbook to another without verifying the original literature, a phenomenon one can call "chain citation".

Predictive Margins and Marginal Effects in Stata

Tables of estimated regression coefficients, usually accompanied by additional information such as standard errors, t-statistics, p-values, confidence intervals or significance stars, have long been the preferred way of communicating results from statistical models. In recent years, however, the limits of this form of exposition have been increasingly recognized. For example, interpretation of regression tables can be very challenging in the presence of complications such as interaction effects, categorical variables, or nonlinear functional forms. Furthermore, while these issues might still be manageable in the case of linear regression, interpretational difficulties can be overwhelming in nonlinear models such as logistic regression. To facilitate sensible interpretation of such models it is often necessary to compute additional results such as marginal effects, predictive margins, or contrasts. Moreover, smart graphical displays of results can be very valuable in making complex relations accessible. A number of helpful commands geared at supporting these tasks have been recently introduced in Stata, making elaborate interpretation and communication of regression results possible without much extra effort. Examples of such commands are -margins-, -contrasts-, and -marginsplot-. In my talk, I will discuss the capabilities of these commands and present a range of examples illustrating their use.

Information-Centric Networking in Mobile and Opportunistic Networks

Information Centric Networking (ICN) as an emerging paradigm for the Future Internet has initially been rather focusing on bandwidth savings in wired networks, but there might also be some significant potential to support communication in mobile wireless networks as well as opportunistic network scenarios, where end systems have spontaneous but time-limited contact to exchange data. This chapter addresses the reasoning why ICN has an important role in mobile and opportunistic networks by identifying several challenges in mobile and opportunistic Information-Centric Networks and discussing appropriate solutions for them. In particular, it discusses the issues of receiver and source mobility. Source mobility needs special attention. Solutions based on routing protocol extensions, indirection, and separation of name resolution and data transfer are discussed. Moreover, the chapter presents solutions for problems in opportunistic Information-Centric Networks. Among those are mechanisms for efficient content discovery in neighbour nodes, resume mechanisms to recover from intermittent connectivity disruptions, a novel agent delegation mechanisms to offload content discovery and delivery to mobile agent nodes, and the exploitation of overhearing to populate routing tables of mobile nodes. Some preliminary performance evaluation results of these developed mechanisms are provided.

Cadaver dogs--a study on detection of contaminated carpet squares

INTRODUCTION: Cadaver dogs are known as valuable forensic tools in crime scene investigations. Scientific research attempting to verify their value is largely lacking, specifically for scents associated with the early postmortem interval. The aim of our investigation was the comparative evaluation of the reliability, accuracy, and specificity of three cadaver dogs belonging to the Hamburg State Police in the detection of scents during the early postmortem interval. MATERIAL AND METHODS: Carpet squares were used as an odor transporting media after they had been contaminated with the scent of two recently deceased bodies (PMI<3h). The contamination occurred for 2 min as well as 10 min without any direct contact between the carpet and the corpse. Comparative searches by the dogs were performed over a time period of 65 days (10 min contamination) and 35 days (2 min contamination). RESULTS: The results of this study indicate that the well-trained cadaver dog is an outstanding tool for crime scene investigation displaying excellent sensitivity (75-100), specificity (91-100), and having a positive predictive value (90-100), negative predictive value (90-100) as well as accuracy (92-100).

Comparison of partial least squares regression and principal component regression for pelvic shape prediction.

This paper studied two different regression techniques for pelvic shape prediction, i.e., the partial least square regression (PLSR) and the principal component regression (PCR). Three different predictors such as surface landmarks, morphological parameters, or surface models of neighboring structures were used in a cross-validation study to predict the pelvic shape. Results obtained from applying these two different regression techniques were compared to the population mean model. In almost all the prediction experiments, both regression techniques unanimously generated better results than the population mean model, while the difference on prediction accuracy between these two regression methods is not statistically significant (α=0.01).

Pretreatment Tables Predicting Pathologic Stage of Locally Advanced Prostate Cancer

BACKGROUND Pretreatment tables for the prediction of pathologic stage have been published and validated for localized prostate cancer (PCa). No such tables are available for locally advanced (cT3a) PCa. OBJECTIVE To construct tables predicting pathologic outcome after radical prostatectomy (RP) for patients with cT3a PCa with the aim to help guide treatment decisions in clinical practice. DESIGN, SETTING, AND PARTICIPANTS This was a multicenter retrospective cohort study including 759 consecutive patients with cT3a PCa treated with RP between 1987 and 2010. INTERVENTION Retropubic RP and pelvic lymphadenectomy. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Patients were divided into pretreatment prostate-specific antigen (PSA) and biopsy Gleason score (GS) subgroups. These parameters were used to construct tables predicting pathologic outcome and the presence of positive lymph nodes (LNs) after RP for cT3a PCa using ordinal logistic regression. RESULTS AND LIMITATIONS In the model predicting pathologic outcome, the main effects of biopsy GS and pretreatment PSA were significant. A higher GS and/or higher PSA level was associated with a more unfavorable pathologic outcome. The validation procedure, using a repeated split-sample method, showed good predictive ability. Regression analysis also showed an increasing probability of positive LNs with increasing PSA levels and/or higher GS. Limitations of the study are the retrospective design and the long study period. CONCLUSIONS These novel tables predict pathologic stage after RP for patients with cT3a PCa based on pretreatment PSA level and biopsy GS. They can be used to guide decision making in men with locally advanced PCa. PATIENT SUMMARY Our study might provide physicians with a useful tool to predict pathologic stage in locally advanced prostate cancer that might help select patients who may need multimodal treatment.

MRTAB: Stata module to compute one- and two-way tables/graphs of multiple responses

mrtab tabulates multiple responses which are held as a set of indicator variables or as a set of polytomous response variables.