Conflict in the Indian Kashmir Valley I: exposure to violence

ABSTRACT: BACKGROUND: India and Pakistan have disputed ownership of the Kashmir Valley region for many years, resulting in several conflicts since the end of partition in 1947. Very little is known about the prevalence of violence and insecurity in this population. METHODS: We undertook a two-stage cluster household survey in two districts (30 villages) of the Indian part of Kashmir to assess experiences with violence and mental health status among the conflict-affected Kashmiri population. The article presents our findings for confrontations with violence. Data were collected for recent events (last 3 months) and those occurring since the start of the conflict. Informed consent was obtained for all interviews. RESULTS: 510 interviews were completed. Respondents reported frequent direct confrontations with violence since the start of conflict, including exposure to crossfire (85.7%), round up raids (82.7%), the witnessing of torture (66.9%), rape (13.3%), and self-experience of forced labour (33.7%), arrests/kidnapping (16.9%), torture (12.9%), and sexual violence (11.6%). Males reported more confrontations with violence than females, and had an increased likelihood of having directly experienced physical/mental maltreatment (OR 3.9, CI: 2.7-5.7), violation of their modesty (OR 3.6, CI: 1.9-6.8) and injury (OR 3.5, CI: 1.4-8.7). Males also had high odds of self-being arrested/kidnapped (OR 8.0, CI: 4.1-15.5). CONCLUSION: The civilian population in Kashmir is exposed to high levels of violence, as demonstrated by the high frequency of deliberate events as detention, hostage, and torture. The reported violence may result in substantial health, including mental health problems. Males reported significantly more confrontations with almost all violent events; this can be explained by higher participation in outdoor activities

Exploring Multiple‐discreteness in Freight Transport. A Multiple Discrete Extreme Value Model Application for Grain Consolidators in Argentina

There are some examples where freight choices may be of a multiple discrete nature, especially the ones at more tactical levels of planning. Nevertheless, this has not been investigated in the literature, although several discrete-continuous models for mode/vehicle type and shipment size choice have been developed in freight transport. In this work, we propose that the decision of port and mode of the grain consolidators in Argentina is of a discrete-continuous nature, where they can choose more than one alternative and how much of their production to send by each mode. The Multiple Discrete Extreme Value Model (MDCEV) framework was applied to a stated preference data set with a response variable that allowed this multiple-discreteness. To our knowledge, this is the only application of the MDCEV in regional freight context. Free alongside ship price, freight transport cost, lead-time and travel time were included in the utility function and observed and random heterogeneity was captured by the interaction with the consolidator’s characteristics and random coefficients. In addition, different discrete choice models were used to compare the forecasting performance, willingness to pay measures and structure of the utility function against

Model-assisted predictions on prognosis in HNSCC: do we learn?

Dedicated software packages incorporating prognostic models are meant to aid physicians in making accurate predictions of prognosis. This study concerns 742 predictions of 5-year survival on consecutive newly diagnosed patients with head- and neck squamous cell carcinoma. The 5-year survival predictions made by the physicians are not compared with actual survival, but with a prediction made by OncologIQ, a dedicated software package. We used a linear regression and a linear mixed-effects model to look at absolute differences between both predictions and possible learning effects. Predictions made by the physicians were optimistic and inaccurate. Using the linear regression and linear mixed-effects models, the physicians’ learning effect showed little improvement per successive prediction. We conclude that prognostic predictions in general are imprecise. When given feedback on the model’s predicted survival, the accuracy increases, but only very modestly

The valuation of clean spread options: linking electricity, emissions and fuels

The purpose of the paper is to present a new pricing method for clean spread options, and to illustrate its main features on a set of numerical examples produced by a dedicated computer code. The novelty of the approach is embedded in the use of a structural model as opposed to reduced-form models which fail to capture properly the fundamental dependencies between the economic factors entering the production process

Parameter Reduction in Log-normal Chain-ladder Models

Multiplicative chain-ladder (CL) models are characterized by CL factors that explain the development of claims from one period to the next. In classical CL models every development period has its own CL factor. In the present paper we give a method describing how some of these CL factors can be modeled by a joint functional dependence. This joint functional form reduces the number of model parameters needed

Predicting a low cortisol response to adrenocorticotrophic hormone in the critically ill: a retrospective cohort study

Introduction: Identification of risk factors for diminished cortisol response to adrenocorticotrophic hormone (ACTH) in the critically ill could facilitate recognition of relative adrenal insufficiency in these patients. Therefore, we studied predictors of a low cortisol response to ACTH. Methods: A retrospective cohort study was conducted in a general intensive care unit of a university hospital over a three year period. The study included 405 critically ill patients, who underwent a 250 μg ACTH stimulation test because of prolonged hypotension or need for vasopressor/inotropic therapy. Plasma cortisol was measured before and 30 and 60 min after ACTH injection. A low adrenal response was defined as an increase in cortisol of less than 250 nmol/l or a peak cortisol level below 500 nmol/l. Various clinical variables were collected at admission and on the test day. Results: A low ACTH response occurred in 63% of patients. Predictors, in multivariate analysis, included sepsis at admission, low platelets, low pH and bicarbonate, low albumin levels, high Sequential Organ Failure Assessment score and absence of prior cardiac surgery, and these predictors were independent of baseline cortisol and intubation with etomidate. Baseline cortisol/albumin ratios, as an index of free cortisol, were directly related and increases in cortisol/albumin were inversely related to disease severity indicators such as the Simplified Acute Physiology Score II and Sequential Organ Failure Assessment score (Spearman r = -0.21; P < 0.0001). Conclusion: In critically ill patients, low pH/bicarbonate and platelet count, greater severity of disease and organ failure are predictors of a low adrenocortical response to ACTH, independent of baseline cortisol values and cortisol binding capacity in blood. These findings may help to delineate relative adrenal insufficiency and suggest that adrenocortical suppression occurs as a result of metabolic acidosis and coagulation disturbances

A new scoring system in Cystic Fibrosis: statistical tools for database analysis – a preliminary report

<p>Abstract</p> <p>Background</p> <p>Cystic fibrosis is the most common fatal genetic disorder in the Caucasian population. Scoring systems for assessment of Cystic fibrosis disease severity have been used for almost 50 years, without being adapted to the milder phenotype of the disease in the 21^stcentury. The aim of this current project is to develop a new scoring system using a database and employing various statistical tools. This study protocol reports the development of the statistical tools in order to create such a scoring system.</p> <p>Methods</p> <p>The evaluation is based on the Cystic Fibrosis database from the cohort at the Royal Children's Hospital in Melbourne. Initially, unsupervised clustering of the all data records was performed using a range of clustering algorithms. In particular incremental clustering algorithms were used. The clusters obtained were characterised using rules from decision trees and the results examined by clinicians. In order to obtain a clearer definition of classes expert opinion of each individual's clinical severity was sought. After data preparation including expert-opinion of an individual's clinical severity on a 3 point-scale (mild, moderate and severe disease), two multivariate techniques were used throughout the analysis to establish a method that would have a better success in feature selection and model derivation: 'Canonical Analysis of Principal Coordinates' and 'Linear Discriminant Analysis'. A 3-step procedure was performed with (1) selection of features, (2) extracting 5 severity classes out of a 3 severity class as defined per expert-opinion and (3) establishment of calibration datasets.</p> <p>Results</p> <p>(1) Feature selection: CAP has a more effective "modelling" focus than DA.</p> <p>(2) Extraction of 5 severity classes: after variables were identified as important in discriminating contiguous CF severity groups on the 3-point scale as mild/moderate and moderate/severe, Discriminant Function (DF) was used to determine the new groups mild, intermediate moderate, moderate, intermediate severe and severe disease. (3) Generated confusion tables showed a misclassification rate of 19.1% for males and 16.5% for females, with a majority of misallocations into adjacent severity classes particularly for males.</p> <p>Conclusion</p> <p>Our preliminary data show that using CAP for detection of selection features and Linear DA to derive the actual model in a CF database might be helpful in developing a scoring system. However, there are several limitations, particularly more data entry points are needed to finalize a score and the statistical tools have further to be refined and validated, with re-running the statistical methods in the larger dataset.</p

Loneliness of Older Immigrant Groups in Canada: Effects of Ethnic-Cultural Background

This study aimed to explore the loneliness of several groups of older immigrants in Canadacompared to native-born older adults. Data from the Canadian General Social Survey, Cycle 22 (Nolder adults = 3,692) were used. The dependent variable is the 6 item De Jong Gierveld lonelinessscale. Determinants of loneliness included country of birth, ethnic background (cultural context);belongingness (community context) and social networks (social context). Results showed that onlysome immigrant groups are significantly lonelier than older adults born in Canada. Immigrants withsimilar language and culture are not lonelier; while those from countries that differ in nativelanguage/culture are significantly higher on loneliness. Multivariate analyses showed the importanceof cultural background, of composition of the network of relatives and friends, and of localparticipation and feelings of belonging to the Canadian society in explaining loneliness of olderimmigrants

The trauma of ongoing conflict and displacement in Chechnya: quantitative assessment of living conditions, and psychosocial and general health status among war displaced in Chechnya and Ingushetia

BACKGROUND: Conflict in Chechnya has resulted in over a decade of violence, human rights abuses, criminality and poverty, and a steady flow of displaced seeking refuge throughout the region. At the beginning of 2004 MSF undertook quantitative surveys among the displaced populations in Chechnya and neighbouring Ingushetia. METHODS: Surveys were carried out in Ingushetia (January 2004) and Chechnya (February 2004) through systematic sampling. Various conflict-related factors contributing to ill health were researched to obtain information on displacement history, living conditions, and psychosocial and general health status. RESULTS: The average length of displacement was five years. Conditions in both locations were poor, and people in both locations indicated food shortages (Chechnya (C): 13.3%, Ingushetia (I): 11.3%), and there was a high degree of dependency on outside help (C: 95.4%, I: 94.3%). Most people (C: 94%, I: 98%) were confronted with violence in the past. Many respondents had witnessed the killing of people (C: 22.7%, I: 24.1%) and nearly half of people interviewed witnessed arrests (C: 53.1%, I: 48.4%) and maltreatment (C: 56.2%, I: 44.5%). Approximately one third of those interviewed had directly experienced war-related violence. A substantial number of people interviewed – one third in Ingushetia (37.5%) and two-thirds in Chechnya (66.8%) – rarely felt safe. The violence was ongoing, with respondents reporting violence in the month before the survey (C: 12.5%, I: 4.6%). Results of the general health questionnaire (GHQ 28) showed that nearly all internally displaced persons interviewed were suffering from health complaints such as somatic complaints, anxiety/insomnia, depressive feelings or social dysfunction (C: 201, 78.5%, CI: 73.0% – 83.4%; I: 230, 81.3%, CI: 76.2% – 85.6%). Poor health status was reflected in other survey questions, but health services were difficult to access for around half the population (C: 54.3%, I: 46.6%). DISCUSSION: The study demonstrates that the health needs of internally displaced in both locations are similarly high and equally unaddressed. The high levels of past confrontation with violence and ongoing exposure in both locations is likely to contribute to a further deterioration of the health status of internally displaced. As of March 2007, concerns remain about how the return process is being managed by the authorities