Journal articles on the topic 'Death – Causes – Econometric models'
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Bett, Nicholas, Juma Kasozi, and Daniel Ruturwa. "Temporal Clustering of the Causes of Death for Mortality Modelling." Risks 10, no. 5 (May 6, 2022): 99. http://dx.doi.org/10.3390/risks10050099.
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Actuaries utilize demographic features such as mortality and longevity rates for pricing, valuation, and reserving life insurance and pension contracts. Capturing accurate mortality estimates requires factual mortality assumptions in mortality models. However, the dynamic and uncertain nature of mortality improvements and deteriorations necessitates better approaches in tracking mortality changes, for instance, using the causes of deaths features. This paper aims to determine temporal homogeneous clusters using unsupervised learning, a clustering approach to group causes of death based on (dis)similarity measures to set representative clusters in detection and monitoring death trends. The causes of death dataset were derived from the World Health Organization, Global Health Estimates for males and females, from 2000 to 2019, for Kenya. A hierarchical agglomerative clustering technique was implemented with modified Dynamic Time Warping distance criteria. Between 6 and 14 clusters were optimally achieved for both males and females. Using visualisations, principal clusters were detected. Over time, the causes of death trends of these clusters have demonstrated a correlated association with mortality and longevity rates, rationalizing why insurance and pension offices may include this approach as a preliminary step to undertake mortality and longevity modelling.
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Zittersteyn, Geert, and Jennifer Alonso-García. "Common Factor Cause-Specific Mortality Model." Risks 9, no. 12 (December 3, 2021): 221. http://dx.doi.org/10.3390/risks9120221.
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Recent pension reforms in Europe have implemented a link between retirement age and life expectancy. The accurate forecast of life tables and life expectancy is hence paramount for governmental policy and financial institutions. We developed a multi-population mortality model which includes a cause-specific environment using Archimedean copulae to model dependence between various groups of causes of death. For this, Dutch data on cause-of-death mortality and cause-specific mortality data from 14 comparable European countries were used. We find that the inclusion of a common factor to a cause-specific mortality context increases the robustness of the forecast and we underline that cause-specific mortality forecasts foresee a more pessimistic mortality future than general mortality models. Overall, we find that this non-trivial extension is robust to the copula specification for commonly chosen dependence parameters.
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Stepanov, Vladimir S. "Assessing SARS-CoV-2-related mortality rate in Russian regions, based on the econometric model." Russian Journal of Infection and Immunity 12, no. 4 (September 9, 2022): 783–89. http://dx.doi.org/10.15789/2220-7619-asr-1846.
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The objects of the study were the daily data on the population morbidity and mortality due to coronavirus disease 2019 (COVID-19) in Russian regions, as well as regional medical, demographic and environmental data recorded in recent years. COVID-19 is a contagious disease caused by the novel coronavirus (SARS-CoV-2). The mathematical methods consist of correlation and regression analysis, methods of testing statistical hypotheses. First, a multiple Variable Structure Regression should be specified. The intercept in the model differs from region to region, depending on the combination of values for dummy variables. The role of the dependent variable Y t was chosen as the cumulative mortality published by the operational headquarters for the regions that has been linked to day t, so that COVID-19 was considered the main cause of death. The complex of explanatory variables included two factorial variables that changed daily, and had a lag relative to t value. Also, this complex included a number of variables that did not change with the growth of t: the explanatory variable with the regions availability with doctors of certain specialties; and four dummy variables. One of them coded the regions belonging to the two southern Russian Federal Districts. Three other variables characterized the increased air pollution in settlements recorded in recent years, as well as the level of radiation pollution of the regions territory and the population health estimated for 10 classes of diseases (for the circulatory system, endocrine system, etc.). The values of such dummy variables were obtained from open data from the Federal State Statistics Service (Rosstat) etc. The model parameters were estimated by the least squares method using the training table, which included 40 Russias regions, the t parameter for variable Y t was assessed starting from November, 1, 2021. As a result, a statistical model was built with an approximation error equal to 3%. For regions of the regions examined this error was 1.94 (1.5)% for the value Y t that has been fixed on the 1st Nov. The plots show daily prediction for mortality rate due to COVID-19 in the first half of November for seven Russian regions compared with actual data. The model can be useful in development of medical and demographic policy in geographic regions, as well as generating adjusted compartment models that based on systems of differential equations (SEIRF, SIRD, etc.).
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Babashova, Sakina. "Predicting the Dynamics of Covid-19 Propagation in Azerbaijan based on Time Series Models." WSEAS TRANSACTIONS ON ENVIRONMENT AND DEVELOPMENT 18 (July 28, 2022): 1036–48. http://dx.doi.org/10.37394/232015.2022.18.99.
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The study is dedicated to developing an econometric model that can be used to make medium-term forecasts about the dynamics of the spread of the coronavirus in different countries, including Azerbaijan. We examine the number of COVID-19 cases and deaths worldwide to understand the data's intricacies better and make reliable predictions. Though it’s essential to quickly obtain an acceptable (although not perfect) prediction that shows the critical trends based on incomplete and inaccurate data, it is practically impossible to use standard SIR models of the epidemic spread. At the same time the similarity of the dynamics in different countries, including those which were several weeks ahead of Azerbaijan in the epidemic situation, and the possibility of including the heterogeneity factors into the model allowed as early as March 2020 to develop the extrapolation working relatively well on the medium-term horizon. The SARS-CoV-2 virus, which causes COVID-19, has affected societies worldwide, but the experiences have been vastly different. Countries' health-care and economic systems differ significantly, making policy responses such as testing, intermittent lockdowns, quarantine, contact tracing, mask-wearing, and social distancing. The study presented in this paper is based on the Exponential Growth Model method, which is used in statistical analysis, forecasting, and decision-making in public health and epidemiology. This model was created to forecast coronavirus spread dynamics under uncertainty over the medium term. The model predicts future values of the percentage increase in new cases for 1–2 months. Data from previous periods in the United States, Italy, Spain, France, Germany, and Azerbaijan were used. The simulation results confirmed that the proposed approach could be used to create medium-term forecasts of coronavirus spread dynamics. The main finding of this study is that using the proposed approach for Azerbaijan, the deviation of the predicted total number of confirmed cases from the actual number was within 3-10 percent. Based on March statistics on the spread of the coronavirus in the US, 4 European countries: Italy, Spain, France, Germany (most susceptible to the epidemic), and Azerbaijan, it was shown how the trajectory would deviate exponentially from a shape; a trial was carried out to identify and assess the key factors that characterize countries. One of the unexpected results was the impact of quarantine restrictions on the number of people infected. We also used the medium-term forecast set by the local government to assess the adequacy of health systems.
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Lambrecht, Stéphane. "Altruistic bequests and non-negative savings." Recherches économiques de Louvain 69, no. 4 (2003): 349–69. http://dx.doi.org/10.1017/s0770451800007910.
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SummaryThis paper builds on the class of models studying the game interaction between an altruistic benefactor and a selfish recipient. An altruistic parent's bequest is transferred to his selfish son after the former's death and we assume that it is not a valid collateral for bank loans. This is equivalent to adding a non-negativity constraint on savings to the standard bequest model. A crucial mechanism at work is that the son's choice of a level of action can seriously dwarf his budget set. When Becker's result holds, the credit constraint places an upper bound on the strategic savings of the Samaritan's dilemma type. But the constraint on savings also causes the shrinkage of the validity domain of the Rotten Kid Theorem because it may lead both poor and rich heirs to behave unoptimally from the family point of view.
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Mur, Jesús, Ana M. Angulo, and Fernando A. López. "Looking for the Causes of Instability in Spatial Econometric Models." International Regional Science Review 35, no. 3 (June 15, 2012): 303–38. http://dx.doi.org/10.1177/0160017611415265.
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Doszyń, Mariusz. "Determination of Impact of Propensities by Means of Residuals of Econometric Models for Spatial Data." Folia Oeconomica Stetinensia 8, no. 1 (January 1, 2009): 49–56. http://dx.doi.org/10.2478/v10031-009-0023-5.
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Determination of Impact of Propensities by Means of Residuals of Econometric Models for Spatial Data It is important to be aware that economic occurrences depend also on subjective (psychological and sociological) factors. In many cases these causes could be identified with propensities. Propensities could be understood as a generalized psychological and sociological causes that make probabilities of certain events higher in given objective circumstances. In the article proposition of determining impact of propensities on economic phenomena by means of residuals of econometric models for spatial data was discussed. Econometric consequences of omitting subjective factors (propensities) while analyzing socio-economic regularities were presented. Such kind of residuals as OLS, predictive, studentized, recursive and BLUS residuals were described. Econometric properties of mentioned residuals were also pointed out. In the empirical example all types of residuals were used to analyze impact of propensity to consume in chosen European countries in 2006.
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Wan Yaacob, Wan Fairos, and Wan Zakiyatussariroh Wan Husin. "Modelling Malaysian Road Accident Deaths : An Econometric Approach." Social and Management Research Journal 3, no. 1 (June 1, 2006): 99. http://dx.doi.org/10.24191/smrj.v3i1.5105.
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A number of methods have been proposed for dealing with road accident death model. This paper uses econometric regression models to develop the road accident death model. By using this approach, this paper attempts to establish a statistical model to describe the relationship between the total road accident deaths and a range ofexplanatory macroeconomic variables. The macroeconomic factors used in the model include population, the number of registered vehicles, road length, technique of data coverage, system of data recording and Gross Domestic Product. The results suggest that the POp, ROADL, VEH and DR do not have any impact on road accident deaths. In contrast, the GDP and Technique of data Coverage were found to be highly significant (P < 0.05) in explaining the road accident deaths.
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Lazarides, Themistokles, Evaggelos Drimpetas, and George Kyriazopoulosr. "Mergers, liquidations and bankruptcies in the European banking sector." Risk Governance and Control: Financial Markets and Institutions 5, no. 2 (2015): 52–70. http://dx.doi.org/10.22495/rgcv5i2art6.
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The inactivity of banks may be the result of a number of events, such as merger & acquisition (M&A), liquidation, default-bankruptcy, etc. All these phenomena of inactivity contribute to the same result, the reform of the European banking sector and they may have the same causes. The paper will address the issue of inactivity and will try to detect its causes using econometric models. Six groups of indicators are examined: performance, size, ownership, corporate governance, capital adequacy or capital structure and loan growth. Three econometric methods (Probit, Logit, OLS) have been used to create a system that predicts inactivity. The results of the econometric models show that from the six groups of indicators, four have been found to be statistically important (performance, size, ownership, corporate governance). Two have a negative impact (ownership, corporate governance) on the probability of inactivity and two positive (performance, size). The paper’s value and innovation is that it has given a systemic approach to find indicators of inactivity and it has excluded two groups of indicators as non-statistically important (capital adequacy or capital structure and growth).
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Sandoval-Pineda, Alejandro, Cesar Pedraza, and Aquiles E. Darghan. "Macroscopic Spatial Analysis of the Impact of Socioeconomic, Land Use and Mobility Factors on the Frequency of Traffic Accidents in Bogotá." Computers 11, no. 12 (December 8, 2022): 180. http://dx.doi.org/10.3390/computers11120180.
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The urban structure of a city, defined by its inhabitants, daily movements, and land use, has become an environmental factor of interest that is related to traffic accidents. Traditionally, macro modeling is usually implemented using spatial econometric methods; however, techniques such as support vector regression have proven to be efficient in identifying the relationships between factors at the zonal level and the frequency associated with these events when considering the autocorrelation between spatial units. As a result of this, the main objective of this study was to evaluate the impact of socioeconomical, land use, and mobility variables on the frequency of traffic accidents through the analysis of area data using spatial and vector support regression models. The spatial weighting matrix term was incorporated into the support vector regression models to compare the results against those that ignore it. The urban land of Bogotá, disaggregated into the territorial units of mobility analysis, was delimited as a study area. Two response variables were used: the traffic accidents index on the road perimeter and the traffic accidents index with deaths on the road perimeter, to analyze the total number of traffic accidents and the deaths caused by them. The results indicated that the rate of trips per person by taxi and motorcycle had the greatest impact on the increase in total accidents and deaths caused by them. Support vector regression models that incorporate the spatial structure allowed the modeling of the spatial dependency between spatial units with a better fit than the spatial regression models.
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Banerjee, Swagata “Ban”, and Babatunde A. Obembe. "Econometric Forecasting of Irrigation Water Demand Conserves a Valuable Natural Resource." Journal of Agricultural and Applied Economics 45, no. 3 (August 2013): 557–68. http://dx.doi.org/10.1017/s107407080000506x.
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Natural causes (such as droughts), non-natural causes (such as competing uses), and government policies limit the supply of water for agriculture in general and irrigating crops in particular. Under such reduced water supply scenarios, existing physical models reduce irrigation proportionally among crops in the farmer's portfolio, disregarding temporal changes in economic and/or institutional conditions. Hence, changes in crop mix resulting from expectations about risks and returns are ignored. A method is developed that considers those changes and accounts for economic substitution and expansion effects. Forecasting studies based on this method with surface water in Georgia and Alabama demonstrate the relative strength of econometric modeling vis-à-vis physical methods. Results from a study using this method for ground water in Mississippi verify the robustness of those findings. Results from policy-induced simulation scenarios indicate water savings of 12% to 27% using the innovative method developed. Although better irrigation water demand forecasting in crop production was the key objective of this pilot project, conservation of a valuable natural resource (water) has turned out to be a key consequence.
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Paquet-Durand, François, Stefanie M. Hauck, Theo van Veen, Marius Ueffing, and Per Ekström. "PKG activity causes photoreceptor cell death in two retinitis pigmentosa models." Journal of Neurochemistry 108, no. 3 (February 2009): 796–810. http://dx.doi.org/10.1111/j.1471-4159.2008.05822.x.
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Gerasimov, Aleksey N., Evgeny I. Gromov, Yury S. Skripnichenko, Oksana P. Grigoryeva, and Victoria Yu Skripnichenko. "Models and Forecasts of the Export Potential of the Regional Economic System." REGIONOLOGY 30, no. 4 (December 30, 2022): 762–82. http://dx.doi.org/10.15507/2413-1407.121.030.202204.762-782.
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Introduction. The export potential of the regional agricultural market causes great interest from both the scientific community and government agencies. Many scientific studies are devoted to the search for methods to increase the export potential in order to ensure the sustainable development of regional economic systems. The article proposes and tests the original author’s algorithm for creating a dynamic econometric model for forecasting the volumes of production, sales and exports of the main types of livestock products at the regional level. The purpose of the article is to assess the export potential of the main products of the regional agricultural market based on the built dynamic econometric models. Materials and Methods. The research is based on a set of empirical data of result and input variables characterizing the production, sales and export of the main livestock products in the region for the period 2010–2020. Research methods include dynamic analysis, econometric modeling and forecasting. The dynamic analysis carried out made it possible to assess the change in the production, sale and export of the main agricultural products in the region, to assess the current trends. Based on the constructed econometric models, the most significant factors influencing the resulting variables were identified, the specifications and verification of the models were carried out. The method of extrapolation of the identified trends made it possible to evaluate the predicted values of the resulting variables for the medium term. Results. Based on the selected input variables, models of production, sale and export of milk, wool and eggs by agricultural producers in the region were built. From a variety of alternative models, models with the best statistical quality characteristics were selected. The high level of quality of the obtained models made it possible to use them for predictive calculations of the levels of resulting variables for the period 2021–2026. Comparison of the results of the forecasts made it possible to identify the types of livestock products that already have a high level of exportability. In addition, types of products with a low level of exportability were identified, which have a high potential for increase. Discussion and Conclusion. As a result of using econometric modeling methods, dynamic models were obtained that made it possible to obtain a forecast for the development of livestock in a region with a high export potential in the near future. The practical significance of this article lies in the possibility of influencing the production, sale and export of livestock products in the region through a change in the corresponding set of factor variables of the models. Thus, the resulting dynamic models can be used both by agricultural producers for planning economic activities, and by regional authorities when drawing up regional development programs.
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Galvin, Angeline, Svetlana Ukraintseva, Konstantin Arbeev, Mary Feitosa, Anne Newman, and Kaare Christensen. "END-OF-LIFE EVENTS AND CAUSES OF DEATH IN DANISH LONG-LIVED FEMALE SIBLINGS." Innovation in Aging 6, Supplement_1 (November 1, 2022): 395. http://dx.doi.org/10.1093/geroni/igac059.1555.
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Abstract Long-lived siblings have better health and survival compared to “sporadic” long-lived individuals, but it is unknown whether they also differ in end-of-life events and causes of death. Deceased Danish long-lived female siblings (n=833, mean age at death=95.6) were identified through national health registers compared to controls matched on sex, year-of-birth, and year-of-death. End-of-life events (hospitalizations, emergency room visits, medication within the five years before death) and causes of death were analyzed using linear models with fixed effects and multinomial logistic models, respectively. End-of-life events and causes of death were not statistically significantly different between long-lived female siblings and “sporadic” long-lived individuals. However, long-lived female siblings presented non-significant higher risk of ischemic heart disease and cancer – and lower risk of mental diseases and accidents. The analyses will be extended to include men, a longer follow-up, and focus on dementia in the last years of life.
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Oura, Yoshihito, Machiko Nakamura, Tohru Takigawa, Yoko Fukushima, Taku Wakabayashi, Motokazu Tsujikawa, and Kohji Nishida. "High-Temperature Requirement A 1 Causes Photoreceptor Cell Death in Zebrafish Disease Models." American Journal of Pathology 188, no. 12 (December 2018): 2729–44. http://dx.doi.org/10.1016/j.ajpath.2018.08.012.
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Badea, Mădălina Andreea, Mihaela Balas, Daniela Ioniță, and Anca Dinischiotu. "Cytotoxic Effects of Carbon Nanotubes and Cisplatin Conjugates on 3D Breast Cancer Cellular Models." Proceedings 29, no. 1 (October 9, 2019): 6. http://dx.doi.org/10.3390/proceedings2019029006.
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Gu, Jiafeng, Tiyan Shen, and Jiadong Zhang. "Can Financial Shortages in China’s Education Be Contagious?" Journal of Systems Science and Information 3, no. 3 (June 25, 2015): 193–213. http://dx.doi.org/10.1515/jssi-2015-0193.
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AbstractThe full models are estimated by spatial econometric models using county-level data from 1513 Chinese counties. The results indicate the existence of spatial contagion effects among local governments with respect to spending on local education. Financial shortages in education tend to be contagious; they affect counties or regions in geographic proximity. Contagion occurs due to three different fundamental causes: Intergovernmental competition, political economy and neighborhood watch. The possibility of contagion depends strongly on education investment, financial and economic conditions, cultural diversity, urban/rural distribution, and population structure. Poor counties are much more likely to become “infected” by neighboring financial behavior in education. The empirical evidence suggests that the speed of contagion is faster in economically underdeveloped areas than in economically developed areas.
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Ng, Ta-Chou, Wei-Cheng Lo, Chu-Chang Ku, Tsung-Hsueh Lu, and Hsien-Ho Lin. "Improving the Use of Mortality Data in Public Health: A Comparison of Garbage Code Redistribution Models." American Journal of Public Health 110, no. 2 (February 2020): 222–29. http://dx.doi.org/10.2105/ajph.2019.305439.
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Objectives. To describe and compare 3 garbage code (GC) redistribution models: naïve Bayes classifier (NB), coarsened exact matching (CEM), and multinomial logistic regression (MLR). Methods. We analyzed Taiwan Vital Registration data (2008–2016) using a 2-step approach. First, we used non-GC death records to evaluate 3 different prediction models (NB, CEM, and MLR), incorporating individual-level information on multiple causes of death (MCDs) and demographic characteristics. Second, we applied the best-performing model to GC death records to predict the underlying causes of death. We conducted additional simulation analyses for evaluating the predictive performance of models. Results. When we did not account for MCDs, all 3 models presented high average misclassification rates in GC assignment (NB, 81%; CEM, 86%; MLR, 81%). In the presence of MCD information, NB and MLR exhibited significant improvement in assignment accuracy (19% and 17% misclassification rate, respectively). Furthermore, CEM without a variable selection procedure resulted in a substantially higher misclassification rate (40%). Conclusions. Comparing potential GC redistribution approaches provides guidance for obtaining better estimates of cause-of-death distribution and highlights the significance of MCD information for vital registration system reform.
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Jiménez de Bagüés, María P., Safia Ouahrani‐Bettache, Juan F. Quintana, Olga Mitjana, Nabil Hanna, Stéphanie Bessoles, Françoise Sanchez, et al. "The New SpeciesBrucella microtiReplicates in Macrophages and Causes Death in Murine Models of Infection." Journal of Infectious Diseases 202, no. 1 (July 2010): 3–10. http://dx.doi.org/10.1086/653084.
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Salomon, Joshua A., and Christopher J. L. Murray. "The Epidemiologic Transition Revisited: Compositional Models for Causes of Death by Age and Sex." Population and Development Review 28, no. 2 (June 2002): 205–28. http://dx.doi.org/10.1111/j.1728-4457.2002.00205.x.
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Ibrahim, Joseph Elias, Chebiwot Kipsaina, Cathy Martin, David Leo Ranson, and Lyndal Bugeja. "Variations in death notification of nursing home residents to Australian Coroners." Injury Prevention 25, no. 5 (July 9, 2018): 357–63. http://dx.doi.org/10.1136/injuryprev-2017-042689.
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ObjectivesTo examine the impact of changes to the reporting requirements in coronial legislation on the nature and frequency of nursing home resident deaths reported to Coroners.DesignNational retrospective study of a population cohort of nursing home resident deaths.SettingAccredited Australian nursing homes between July 2000 and June 2013.ParticipantsResidents who died in nursing homes accredited by the Aged Care Standards and Accreditation Agency reported to Coroners.Main outcome measuresWe explored three death-reporting models in the nursing home setting: comprehensive model, selective ‘mechanism of death’ model and selective ‘age of death’ model. These models were examined by manner of death subgroups: natural, falls-related and other external causes using the outcome measure of deaths notified to the Coroner per 1000 residents. We used an interrupted time series analysis using generalised linear regression with a negative binomial probability distribution and a log link function.ResultsThe comprehensive model showed the proportion of reportable deaths due to natural causes far exceeded those from falls and other external cause. In contrast, the selective notification models reduced the total number of reportable deaths. Similarly, the selective ‘age of death’ model showed a decline in the reportable external cause deaths.ConclusionsVariation in the causes, locations and ages of persons whose deaths are legally required to be notified to Coroners impacts the frequency and nature of deaths of nursing home residents investigated by Coroners. This demonstrates that legislation needs to be carefully framed and applied to ensure that the prevention mandate of Coroners in Australia is to be achieved.
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Guziejewska, Beata, Anna Majdzińska, and Agata Żółtaszek. "The Flypaper Effect and Desirable Legislative Changes to Local Government Financing Systems." Lex localis - Journal of Local Self-Government 19, no. 3 (July 22, 2021): 587–608. http://dx.doi.org/10.4335/19.3.587-608(2021).
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A substantial portion of local government funding in Poland comes from intergovernmental transfers. It may lead to the flypaper effect, which means that external revenues contribute to greater local government spending than locally-collected revenues. This study analyses how different revenue categories influenced local government spending in Poland between 2009 and 2018. Panel econometric models are used to test a hypothesis about whether the flypaper effect occurred in that period and to identify the potential causes. The results confirm to some extent that all three levels of local government were affected by the flypaper effect, and they point to intergovernmental transfers (general grants, specific grants, and shares of corporate income tax revenue) as the main causes. The research findings can be of use in reforming local government funding legislation in Poland and other countries, especially when the size of the public sector and public spending need to be reduced.
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Polo, Sara M. T. "How Terrorism Spreads: Emulation and the Diffusion of Ethnic and Ethnoreligious Terrorism." Journal of Conflict Resolution 64, no. 10 (June 10, 2020): 1916–42. http://dx.doi.org/10.1177/0022002720930811.
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Previous research on the causes of domestic terrorism has tended to focus on domestic determinants. Although this approach can be helpful to understand many causes of terrorism, it implicitly disregards how the tactical choices made by similar nonstate actors elsewhere influence a group’s decision to resort to terrorist tactics. This study argues that the adoption of terrorism among ethnic and ethnoreligious groups results from a process of conditional emulation. Groups are more likely to emulate the terrorist choice of others with whom they are connected by shared political grievances and spatial networks. The theory is tested on a new and original group-level data set of ethnic and ethnoreligious terrorism (1970 to 2009) using geospatial analysis and spatial econometric models. The results provide strong support for the hypothesized mechanism leading to the diffusion of terrorism and suggest that emulation—more than domestic and contextual factors—substantially influences dissidents’ tactic choice.
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GANESH, SANTHI K., AUSTIN G. STACK, NATHAN W. LEVIN, TEMPIE HULBERT-SHEARON, and FRIEDRICH K. PORT. "Association of Elevated Serum PO4, Ca × PO4Product, and Parathyroid Hormone with Cardiac Mortality Risk in Chronic Hemodialysis Patients." Journal of the American Society of Nephrology 12, no. 10 (October 2001): 2131–38. http://dx.doi.org/10.1681/asn.v12102131.
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Abstract. Hyperphosphatemia is highly prevalent among patients with end-stage renal disease (ESRD) and is associated with increased mortality risk in hemodialysis (HD) patients. The mechanism through which this mortality risk is mediated is unclear. Data from two national random samples of HD patients (n= 12,833) was used to test the hypothesis that elevated serum PO4contributes mainly to cardiac causes of death. During a 2-yr follow-up, the cause-specific relative risk (RR) of death for patients was analyzed separately for several categories of cause of death, including coronary artery disease (CAD), sudden death, and other cardiac causes, cerebrovascular and infection. Cox regression models were fit for each of the eight cause of death categories, adjusting for patient demographics and non-cardiovascular comorbid conditions. Time at risk for each cause-specific model was censored at death that resulted from any of the other causes. Higher mortality risk was seen for patients in the high PO4group (>6.5mg/dl) compared with the lower PO4group (≤6.5mg/dl) for death resulting from CAD (RR 1.41;P< 0.0005), sudden death (RR 1.20;P< 0.01), infection (RR 1.20;P< 0.05), and unknown causes (RR 1.25;P< 0.05). Patients in the high PO4group also had non-significantly increased RR of death from other cardiac and cerebrovascular causes of death. The RR of sudden death was also strongly associated with elevated Ca × PO4product (RR 1.07 per 10 mg2/dl2;P< 0.005) and serum parathyroid hormone levels greater than 495 pg/ml (RR 1.25;P< 0.05). This study identifies strong relationships between elevated serum PO4, Ca × PO4product, and parathyroid hormone and cardiac causes of death in HD patients, especially deaths resulting from CAD and sudden death. More vigorous measures to reduce the prevalence of these factors in HD patients may result in improved survival.
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Meier-Kriesche, Herwig-Ulf, Julie A. Arndorfer, and Bruce Kaplan. "Association of Antibody Induction with Short- and Long-Term Cause-Specific Mortality in Renal Transplant Recipients." Journal of the American Society of Nephrology 13, no. 3 (March 2002): 769–72. http://dx.doi.org/10.1681/asn.v133769.
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ABSTRACT. A total of 73,707 primary renal transplants reported to the USRDS between 1988 and 1997 were examined to investigate the cause-specific risk for patient death associated with anti-lymphocyte antibody induction therapy (ABI). Cox proportional hazard models were used to estimate the relative risk of the use of ABI and patient death. All Cox models were corrected for potential confounding variables, such as age, gender, race, HLA mismatch, panel reactive antibody, delayed graft function, cold ischemia time, time since start of dialysis, etiology of end-stage renal disease, cytomegalovirus risk group, donor source (living or cadaveric), era effect, and immunosuppressive therapy. Primary study end points were patient death with functioning graft (DWFG) and overall patient death, including death after graft loss. Early patient death (deaths within the first 6 mo after renal transplantation) and late death (deaths after 6 mo post–renal transplantation) were investigated separately. Additionally, specific causes of death were investigated. ABI was associated with a significant risk for late death after renal transplantation (relative risk [RR] = 1.1; P < 0.001) but not for DWFG (RR = 0.94; P = 0.10). ABI conferred the highest RR for late malignancy–related death (RR = 1.35; P < 0.001). ABI was significantly associated with early deaths due to infection and cardiovascular causes (RR = 1.32 [P < 0.001] and RR = 1.27 [P < 0.001], respectively). Kaplan Meier plots confirmed that the risk of ABI for patient death secondary to infectious complications was increased predominately early after transplantation as opposed to late for malignancy-related death. ABI was associated with a significant relative risk for patient death secondary to cardiovascular causes and infectious complications early in the posttransplant period. In addition, ABI was associated with a significant risk for long-term malignancy-related death. The risk of ABI should be taken in context with potential benefits of this therapy.
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Pereira, José, Mário Basto, and Amélia Silva. "Comparing logit model with discriminant analysis for predicting bankruptcy in Portuguese hospitality sector." European Journal of Tourism Research 16 (July 1, 2017): 276–80. http://dx.doi.org/10.54055/ejtr.v16i.289.
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Portugal’s tourism sector is on permanent expansion and contributes significantly to the Portuguese economy. However, it has been facing the problem of business failure. The main goal of this paper is to develop an econometric and a multivariate model for forecasting business failure in the hospitality industry using logit and discriminant analysis. The present paper does not explore the causes of business failure but rather aims to propose a model that may help anticipate failure, so that decision makers can minimize the negative effects of this phenomenon. The results confirm that the models for forecasting business failure contribute positively to setting macroeconomic policies and tourism development support programs and are relevant for investors, stockholders, and decision makers.
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Umapathi, Priya, Olurotimi O. Mesubi, Partha S. Banerjee, Neha Abrol, Qinchuan Wang, Elizabeth D. Luczak, Yuejin Wu, et al. "Excessive O -GlcNAcylation Causes Heart Failure and Sudden Death." Circulation 143, no. 17 (April 27, 2021): 1687–703. http://dx.doi.org/10.1161/circulationaha.120.051911.
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Background: Heart failure is a leading cause of death worldwide and is associated with the rising prevalence of obesity, hypertension, and diabetes. O -GlcNAcylation (the attachment of O -linked β-N-acetylglucosamine [ O -GlcNAc] moieties to cytoplasmic, nuclear, and mitochondrial proteins) is a posttranslational modification of intracellular proteins and serves as a metabolic rheostat for cellular stress. Total levels of O -GlcNAcylation are determined by nutrient and metabolic flux, in addition to the net activity of 2 enzymes: O -GlcNAc transferase (OGT) and O -GlcNAcase (OGA). Failing myocardium is marked by increased O -GlcNAcylation, but whether excessive O -GlcNAcylation contributes to cardiomyopathy and heart failure is unknown. Methods: We developed 2 new transgenic mouse models with myocardial overexpression of OGT and OGA to control O -GlcNAcylation independent of pathologic stress. Results: We found that OGT transgenic hearts showed increased O -GlcNAcylation and developed severe dilated cardiomyopathy, ventricular arrhythmias, and premature death. In contrast, OGA transgenic hearts had lower O -GlcNAcylation but identical cardiac function to wild-type littermate controls. OGA transgenic hearts were resistant to pathologic stress induced by pressure overload with attenuated myocardial O -GlcNAcylation levels after stress and decreased pathologic hypertrophy compared with wild-type controls. Interbreeding OGT with OGA transgenic mice rescued cardiomyopathy and premature death, despite persistent elevation of myocardial OGT. Transcriptomic and functional studies revealed disrupted mitochondrial energetics with impairment of complex I activity in hearts from OGT transgenic mice. Complex I activity was rescued by OGA transgenic interbreeding, suggesting an important role for mitochondrial complex I in O -GlcNAc–mediated cardiac pathology. Conclusions: Our data provide evidence that excessive O -GlcNAcylation causes cardiomyopathy, at least in part, attributable to defective energetics. Enhanced OGA activity is well tolerated and attenuation of O -GlcNAcylation is beneficial against pressure overload–induced pathologic remodeling and heart failure. These findings suggest that attenuation of excessive O -GlcNAcylation may represent a novel therapeutic approach for cardiomyopathy.
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Kuropka, Ireneusz, and Joanna Krupowicz. "Spatial convergence of mortality in Poland." Bulletin of Geography. Socio-economic Series 54, no. 54 (November 10, 2021): 7–20. http://dx.doi.org/10.2478/bog-2021-0029.
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Abstract Aim The aim is to observe whether there is a territorial similarity of changes in mortality due to selected causes in Poland in the years 2002–2017. Convergence models were used to verify the hypothesis that, since Poland's accession to the EU, the country has seen a spatial convergence of mortality due to major causes of death. Results and conclusion The country's provinces have been homogenising in terms of death intensity levels evening out for the majority of examined groups of causes. This is indicated by the confirmed absolute beta-convergence for most variables, including the two major causes of death: I00–I99 and C00–D48. However, a confirmation of beta-convergence does not always apply to both a broader and a narrower group of causes. In turn, sigma-divergence of mortality due to most of the examined causes in Poland's provinces indicates increasing variation in the years 2002–2017, which means that the provinces were not becoming similar. Such findings indicate that the formulated hypothesis has not been confirmed.
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Cesare, Mariachiara Di, and Mike Murphy. "Forecasting Mortality, Different Approaches for Different Cause of Deaths? The Cases of Lung Cancer; Influenza, Pneumonia, and Bronchitis; and Motor Vehicle Accidents." British Actuarial Journal 15, S1 (2009): 185–211. http://dx.doi.org/10.1017/s1357321700005560.
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ABSTRACTMost of the methods of mortality forecasting have been assessed using performance on overall mortality, and few studies address the issue of identifying the appropriate forecasting models for specific causes of deaths. This study analyses trends and forecasts mortality rates for three major causes of death — lung cancer, influenza-pneumonia-bronchitis, and motor vehicle accidents — using Lee–Carter, Booth–Maindonald–Smith, Age-Period-Cohort, and Bayesian models, to assess how far different causes of death need different forecasting methods. Using data from the Twentieth and Twenty-First Century Mortality databases for England and Wales, results show major differences among the different forecasting techniques. In particular, when linearity is the main driver of past trends, Lee–Carter-based approaches are preferred due to their straightforward assumptions and limited need for subjective judgment. When a clear cohort pattern is detectable, such as with lung cancer, the Age-Period-Cohort model shows the best outcome. When complete and reliable historical trends are available the Bayesian model does not produce better results than the other models.
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Tomlinson, I. P., and W. F. Bodmer. "Failure of programmed cell death and differentiation as causes of tumors: some simple mathematical models." Proceedings of the National Academy of Sciences 92, no. 24 (November 21, 1995): 11130–34. http://dx.doi.org/10.1073/pnas.92.24.11130.
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DeFina, Robert, and Lance Hannon. "De-unionization and Drug Death Rates." Social Currents 6, no. 1 (October 7, 2018): 4–13. http://dx.doi.org/10.1177/2329496518804555.
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Drug death rates in the United States have risen dramatically in recent years, sparking urgent discussions about causes. Most of these discussions have centered on supply-side issues, such as doctors overprescribing pain killers. However, there is increasing recognition of the need to go beyond proximate causes and to consider larger social forces that bear on the demand for pain-relieving drugs. Informed by sociological research linking labor unions to community health, we empirically examined the relationship between union density and drug death rates for the years 1999 to 2016. We found that states experiencing greater declines in unionization also tended to experience greater increases in drug deaths. Estimates from our fixed-effects models suggested that a one standard deviation decrease in union density was associated with a 42 percent increase in drug death rates over the period. Although the incorporation of a variety of statistical controls reduced this association, it remained negative and significant. Beyond variation in the availability of substances to misuse, our findings underscore the importance of considering institutional decline and broader social conditions as deeply relevant for contemporary drug death trends.
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Khan, Muhammad Mahroof, and Afshan Azam. "Root Causes of Terrorism." Journal of Interdisciplinary Studies 20, no. 1 (2008): 65–86. http://dx.doi.org/10.5840/jis2008201/24.
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Serious study of terrorism requires a proper understanding of why individuals turn extremism md what motivates them to join terrorist organizations. This essay analyzes socio-economic, cultural, religious, and psychological dimensions in a comprehensive framework gauging the "root causes" of terrorism The analysis is based on data collected from Pakistan-based organtations serving as allies of Al-Qaeda. The results indicate that almost all sample resporuients involved in terrorism were unmarried males exposed to fundamentalist teachings of the Qur'an. All believed that if they sacrificed themselves for the sake of their religion, they would be blessed with paradise in life after death. The essay employs relevant models in order to identify empirically the effects of education, an individual's age, household income, and rural or urban residence. The resulting evidence on the individual level suggests that both higher standards of living and education are negatively associated with participation in terrorist activities.
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Li, Xing, Liang Wang, and Bang Yuan Wu. "Research on Efficiency of Physical Capital and Human Capital in China's Economic Growth." Advanced Materials Research 468-471 (February 2012): 2970–73. http://dx.doi.org/10.4028/www.scientific.net/amr.468-471.2970.
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Research on economic growth in the past concerns only with physical capital and human capital in the absolute amount of effects at the expense of the efficiency of the present situation, we use the 1981-2008 China's annual time-series data, with uniform measurement to build econometric models to study China's economic growth in the efficiency of physical capital and human capital. Our research results indicate that in the long term, human capital is of much higher output efficiency than physical capital; In the short term, increased input ratio of human capital causes average labour output to grow sustainably, and increased input ratio of physical capital only between the 1th and 2nd period dues to rapid increase in average labour output and then declined rapidly.
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Lô, Serigne N., Jun Ma, Maurizio Manuguerra, Margarita Moreno-Betancur, Richard A. Scolyer, and John F. Thompson. "Competing risks analysis with missing cause-of-failure—penalized likelihood estimation of cause-specific Cox models." Statistical Methods in Medical Research 31, no. 5 (January 17, 2022): 978–94. http://dx.doi.org/10.1177/09622802211070254.
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Competing risks models are attractive tools to analyze time-to-event data where several causes of an event are competing. However, a complexity may arise when, for instance, some subjects experience the event of interest but the causes are not known. Assuming that unknown causes of events are missing at random, we developed a novel constrained maximum penalized likelihood method for fitting semi-parametric cause-specific Cox regression models. Here, penalty functions were used to smooth the baseline hazards. An appealing feature of this approach is that all the relevant estimands in competing risks models are estimated including cause-specific hazard ratios, cause-specific baseline hazards, and cumulative incidence functions. Asymptotic results for these estimators were also developed, allowing for direct inferences. The proposed method was compared with some existing methods through a simulation study. A real data example was analyzed using the new method to evaluate the association of age at diagnosis with melanoma-death and non-melanoma-death in patients diagnosed with thin melanoma (tumour thickness [Formula: see text]1.0 mm). An R function for our proposed method is currently available on GitHub and will be included in the R package "survivalMPL" at CRAN.
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Goodyear, Michael DE. "Death or Taxes? An Examination of Recent Changes in Tobacco Taxation Policy in Canada." Canadian Respiratory Journal 1, no. 2 (1994): 95–103. http://dx.doi.org/10.1155/1994/860903.
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Manipulation of the price of tobacco products has proven to be one of the most effective tools in tobacco control. However, a strategy relying predominantly on tampering with free-market conditions by raising prices independently of the quantity available is unlikely to be successful over the long term, unless balanced by equal efforts to reduce demand. Canada has a number of unique factors which combined to create a contraband market that eventually led to political pressure for action at a national level. Although presented with a number of policy alternatives, the federal government based its strategy on reducing tobacco taxes to compete with the contraband product. Provision of an effective comprehensive national strategy to combat tobacco has yet to be realized. Econometric models predict significant changes in consumption from drastic tax reductions that effectively halved the retail price in a large part of Canada. The medical profession and public health authorities will need to combat these effects, not only by working for restoration of fiscal pressures but also for sweeping measures to restrict overall demand if increases in long term morbidity and mortality are to be prevented.
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FINKELSTEIN, M. S. "ON SOME RELIABILITY APPROACHES TO HUMAN AGING." International Journal of Reliability, Quality and Safety Engineering 12, no. 04 (August 2005): 337–46. http://dx.doi.org/10.1142/s0218539305001860.
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Deceleration in mortality rates for old ages is explained via the concept of population heterogeneity. Two simple probabilistic models of biological aging are considered. The first one assumes that some random resource is acquired by an organism at birth. Death occurs when the accumulated wear exceeds the initial random resource. In the second model death occurs as the consequence of a harmful event. A non-homogeneous Poisson and doubly stochastic Poisson processes of harmful events are considered. These models describe possible causes of population heterogeneity.
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Fernández-García, Alberto, Mónica Pérez-Ríos, Alberto Fernández-Villar, Gael Naveira, Cristina Candal-Pedreira, María Isolina Santiago-Pérez, Cristina Represas-Represas, Alberto Malvar-Pintos, Sara Cerdeira-Caramés, and Alberto Ruano-Raviña. "Four Decades of COPD Mortality Trends: Analysis of Trends and Multiple Causes of Death." Journal of Clinical Medicine 10, no. 5 (March 7, 2021): 1117. http://dx.doi.org/10.3390/jcm10051117.
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There is little information on chronic obstructive pulmonary disease (COPD) mortality trends, age of death, or male:female ratio. This study therefore sought to analyze time trends in mortality with COPD recorded as the underlying cause of death from 1980 through 2017, and with COPD recorded other than as the underlying cause of death. We conducted an analysis of COPD deaths in Galicia (Spain) from 1980 through 2017, including those in which COPD was recorded other than as the underlying cause of death from 2015 through 2017. We calculated the crude and standardized rates, and analyzed mortality trends using joinpoint regression models. There were 43,234 COPD deaths, with a male:female ratio of 2.4. Median age of death was 82 years. A change point in the mortality trend was detected in 1996 with a significant decrease across the sexes, reflected by an annual percentage change of −3.8%. Taking deaths into account in which COPD participated or contributed without being the underlying cause led to an overall 42% increase in the mortality burden. The most frequent causes of death when COPD was not considered to be the underlying cause were bronchopulmonary neoplasms and cardiovascular diseases. COPD mortality has decreased steadily across the sexes in Galicia since 1996, and age of death has also gradually increased. Multiple-cause death analysis may help prevent the underestimation of COPD mortality.
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Lima, Everton Emanuel Campos de, and Bernardo Lanza Queiroz. "Evolution of the deaths registry system in Brazil: associations with changes in the mortality profile, under-registration of death counts, and ill-defined causes of death." Cadernos de Saúde Pública 30, no. 8 (August 2014): 1721–30. http://dx.doi.org/10.1590/0102-311x00131113.
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This paper examines the spatial pattern of ill-defined causes of death across Brazilian regions, and its relationship with the evolution of completeness of the deaths registry and changes in the mortality age profile. We make use of the Brazilian Health Informatics Department mortality database and population censuses from 1980 to 2010. We applied demographic methods to evaluate the quality of mortality data for 137 small areas and correct for under-registration of death counts when necessary. The second part of the analysis uses linear regression models to investigate the relationship between, on the one hand, changes in death counts coverage and age profile of mortality, and on the other, changes in the reporting of ill-defined causes of death. The completeness of death counts coverage increases from about 80% in 1980-1991 to over 95% in 2000-2010 at the same time the percentage of ill-defined causes of deaths reduced about 53% in the country. The analysis suggests that the government’s efforts to improve data quality are proving successful, and they will allow for a better understanding of the dynamics of health and the mortality transition.
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Mitratza, Marianna, Anton E. Kunst, and Jan W. P. F. Kardaun. "Detecting Mortality Trends in the Netherlands Across 625 Causes of Death." International Journal of Environmental Research and Public Health 16, no. 21 (October 28, 2019): 4150. http://dx.doi.org/10.3390/ijerph16214150.
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Cause of death (COD) data are essential to public health monitoring and policy. This study aims to determine the proportion of CODs, at ICD-10 three-position level, for which a long-term or short-term trend can be identified, and to examine how much the likelihood of identifying trends varies with COD size. We calculated annual age-standardized counts of deaths from Statistics Netherlands for the period 1996–2015 for 625 CODs. We applied linear regression models to estimate long-term trends, and outlier analysis to detect short-term changes. The association of the likelihood of a long-term trend with COD size was analyzed with multinomial logistic regression. No long-term trend could be demonstrated for 216 CODs (34.5%). For the remaining 409 causes, a trend could be detected, following a linear (211, 33.8%), quadratic (126, 20.2%) or cubic model (72, 11.5%). The probability of detecting a long-term trend increased from about 50% at six mean annual deaths, to 65% at 22 deaths and 75% at 60 deaths. An exceptionally high or low number of deaths in a single year was found for 16 CODs. When monitoring long-term mortality trends, one could consider a much broader range of causes of death, including ones with a relatively low number of annual deaths, than commonly used in condensed lists.
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Soares Filho, Adauto Martins, Elisabeth Duarte, Tim Adair, Ximena Pamela Díaz Bermúdez, and Edgar Merchan-Hamann. "Mortality surveillance in Brazil: factors associated with certification of unspecified external cause of death." Ciência & Saúde Coletiva 27, no. 4 (April 2022): 1289–300. http://dx.doi.org/10.1590/1413-81232022274.10422021.
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Abstract This article aims to analyze the association between characteristics of death - type of certifier and place of death - and the odds of an external cause death being certified as unspecified in Brazil. Cross-sectional study of deaths due to external causes from the Mortality Information System, 2017. Unspecified external cause (UEC) is the outcome variable in the models. Type of certifier physician, place of death and the interaction of these variables were the explanatory variables. Confounders were controlled by multiple logistic regression. UEC were the initial underlying cause for 22% of the 159,720 deaths from external causes in Brazil and 31% of hospital deaths issued by coroners. After adjustment for confounders, the odds of UEC in a hospital death certified by a coroner was 98% greater (OR=1.98; 95%CI: 1.53; 2.56) than in a home/street death issued by another certifier. This was greater than the odds for certifications by coroners (OR=1.23; 95%CI: 1.14; 1.33) and hospital deaths (OR=1.44; 95%CI: 1.32; 1.58). External causes certified by coroners and/or occurring in hospitals have a higher presence of UEC than other deaths; and indicate the need for coordinated initiatives by the health and public security sectors.
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Stroustrup, Nicholas. "HOW MANY MOLECULAR MECHANISMS MUST BE ALTERED SIMULTANEOUSLY TO SLOW AGING AND EXTEND LIFESPAN?" Innovation in Aging 3, Supplement_1 (November 2019): S207—S208. http://dx.doi.org/10.1093/geroni/igz038.754.
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Abstract Most anti-aging therapeutics are designed to target single molecules, single molecular mechanisms, or single cell types. Yet, to produce a substantial lifespan extension, these interventions would need to act promiscuously and delay the onset of many or all causes of death. In invertebrate models, several molecular-level interventions are known to act this way, yet their downstream action on multiple causes of death remains poorly understood. Recently, we identified a strong mathematical constraint in the way that many different interventions in aging alter all-cause mortality in the nematode Caenorhabditis elegans. Interventions including suppression of IGF/insulin signaling, disruption of the hsf-1 heat shock factor and the hif-1 hypoxia-inducible factor, as well as changes in diet and body temperature, all produce a temporal scaling of lifespan. This temporal scaling suggests a common physiologic path through which diverse, evolutionary-conserved, molecular mechanisms can simultaneously influence all causes of death.
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Kedzierski, W., S. Nusinowitz, D. Birch, G. Clarke, R. R. McInnes, D. Bok, and G. H. Travis. "Deficiency of rds/peripherin causes photoreceptor death in mouse models of digenic and dominant retinitis pigmentosa." Proceedings of the National Academy of Sciences 98, no. 14 (June 26, 2001): 7718–23. http://dx.doi.org/10.1073/pnas.141124198.
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Lambert, P. C., P. W. Dickman, C. P. Nelson, and P. Royston. "Estimating the crude probability of death due to cancer and other causes using relative survival models." Statistics in Medicine 29, no. 7-8 (March 8, 2010): 885–95. http://dx.doi.org/10.1002/sim.3762.
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Caliaperumal, Jayalakshmi, Sonia Brodie, Yonglie Ma, and Frederick Colbourne. "Thrombin Causes Neuronal Atrophy and Acute but not Chronic Cell Death." Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques 41, no. 6 (November 2014): 714–20. http://dx.doi.org/10.1017/cjn.2014.105.
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AbstractBackground: Brain injury after intracerebral hemorrhage (ICH) arises from numerous contributors, of which some also play essential roles. Notably, thrombin production, needed to stop bleeding, also causes acute cell death and edema. In some rodent models of ICH, peri-hematoma neurons die over weeks. Hence we evaluated whether thrombin is responsible for this chronic degeneration. Functional impairments after ICH also result from sub-lethal damage to neurons, especially the loss of dendrites. Thus, we evaluated whether thrombin infusion alone, a reductionist model of ICH, causes similar injury. Methods: Adult rats had a modest intra-striatal infusion of thrombin (1 U) or saline followed by a behavioral test, to verify impairment, 7 days later. After this they were euthanized and tissue stained with Golgi-Cox solution to allow the assessment of dendritic morphology in striatal neurons. In a second experiment, rats survived 7 or 60 days after thrombin infusion in order to histologically determine lesion volume. Results: Thrombin caused early cell death and considerable atrophy in surviving peri-lesion neurons, which had less than half of their usual numbers of branches. However, total tissue loss was comparable at 7 (24.1 mm3) and 60 days (25.6 mm3). Conclusion: Thrombin infusion causes early cell death and neuronal atrophy in nearby surviving striatal neurons but thrombin does not cause chronic tissue loss. Thus, the chronic degeneration found after ICH in rats is not simply and solely due to acute thrombin production. Nonetheless, thrombin is an important contributor to behavioral dysfunction because it causes cell death and substantial dendritic injury.
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Botta, Laura, Gemma Gatta, Annalisa Trama, and Riccardo Capocaccia. "Excess risk of dying of other causes of cured cancer patients." Tumori Journal 105, no. 3 (March 25, 2019): 199–204. http://dx.doi.org/10.1177/0300891619837896.
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Background: The proportion of patients cured of cancer is usually estimated with cure models assuming they have the same death risk as the general population. These patients, even when cured, often maintain an extra death risk compared to the overall population. Our aims were to estimate this extra risk, and to take it into account in estimating cure proportions and relative survival (RS). Methods: We used RS mixture model with an additional parameter expressing the extra noncancer death risk of patients, assumed constant with age. We applied the model to the SEER registries survival data (1990–1994 diagnosed patients) with colorectal, breast, and lung cancers, and followed up to 2013. Results: The estimated relative risk of death for cured patients versus the general population was 1.11 for colorectal, 1.16 for breast, and 2.17 and 2.12, respectively, for female and male lung cancers. Taking this extra risk into account leads, for all cancers, to a higher estimated proportion of cured and a lower RS of uncured patients. In addition, it leads to a higher estimated RS for all patients aged >70 years, and for lung cancer patients aged >50 years, at diagnosis. Conclusions: Mortality of survivors not directly due to the diagnosed cancer was significantly higher than in the general population. It affected the estimates of cure proportions for all age classes and RS in the elderly.
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Ekpenyong, Emmanuel, and Iheanyi Emenike. "Analysis of deaths in a Nigerian hospital: the case of Federal Medical Centre (FMC), Umuahia." International Journal of Advanced Statistics and Probability 3, no. 1 (April 17, 2015): 64. http://dx.doi.org/10.14419/ijasp.v3i1.4032.
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<p>A Poisson regression model was fitted to the causes of death in Federal Medical Center (FMC), Umuahia. The basic violation of the model which is over-dispersion was confirmed absent with the use of a plot of residual against fitted values, the Pearson statistics and the comparison of the log-likelihoods of the Poisson regression and Negative Binomial regression models. Diseases affecting the excretory and neurological systems respectively were found to be insignificant in the model, while the rest of the other causes of deaths – were found to be significant in the model at 5% level of significance. The leading causes of death in the hospital were determined to be diseases affecting the digestive and circulatory system, injuries, endocrine and neonatal related diseases, and cancers.</p>
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Wright, Claire, Natacha Blake, Linda Glennie, Vinny Smith, Rose Bender, Hmwe Kyu, Han Yong Wunrow, et al. "The Global Burden of Meningitis in Children: Challenges with Interpreting Global Health Estimates." Microorganisms 9, no. 2 (February 13, 2021): 377. http://dx.doi.org/10.3390/microorganisms9020377.
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The World Health Organization (WHO) has developed a global roadmap to defeat meningitis by 2030. To advocate for and track progress of the roadmap, the burden of meningitis as a syndrome and by pathogen must be accurately defined. Three major global health models estimating meningitis mortality as a syndrome and/or by causative pathogen were identified and compared for the baseline year 2015. Two models, (1) the WHO and the Johns Hopkins Bloomberg School of Public Health’s Maternal and Child Epidemiology Estimation (MCEE) group’s Child Mortality Estimation (WHO-MCEE) and (2) the Institute for Health Metrics and Evaluation (IHME) Global Burden of Disease Study (GBD 2017), identified meningitis, encephalitis and neonatal sepsis, collectively, to be the second and third largest infectious killers of children under five years, respectively. Global meningitis/encephalitis and neonatal sepsis mortality estimates differed more substantially between models than mortality estimates for selected infectious causes of death and all causes of death combined. Estimates at national level and by pathogen also differed markedly between models. Aligning modelled estimates with additional data sources, such as national or sentinel surveillance, could more accurately define the global burden of meningitis and help track progress against the WHO roadmap.
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Gayawan, Ezra, and Everton Emanuel Campos de Lima. "A spatio-temporal analysis of cause-specific mortality in São Paulo State, Brazil." Ciência & Saúde Coletiva 27, no. 1 (January 2022): 287–98. http://dx.doi.org/10.1590/1413-81232022271.32472020.
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Abstract Using five cause-specific mortality data sourced by the Brazilian Ministry of Health, and over 17 years period, we applied Bayesian spatio-temporal models on 644 municipalities of the state of São Paulo, using logistic model to the binary outcome that specifies whether or not the death was from a specific cause. We modeled the temporal mortality effects using B-splines, while the spatial components were considered through Gaussian and Markov random field, and inference was based on Markov chain Monte Carlo simulation. The results demonstrate consistent downward trend in mortality from infectious and parasitic diseases and external causes, while those from neoplasms and respiratory are rising. Cardiovascular is the only cause-specific death that is kept constant in time. All the causes of death considered show heterogeneous spatial and temporal variations among the municipalities, which sometimes change considerably within successive years. Mortality from infectious diseases clustered around the Northwestern municipalities in 2000, but changes to the Southeastern part in 2016, a similar development as external death causes. The study identifies areas with increased and decreased odds mortality and could be useful in disease monitoring, especially if we consider small spatial units.
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Lunardi Baccetto, Sarah, and Christian Lehmann. "Microcirculatory Changes in Experimental Models of Stroke and CNS-Injury Induced Immunodepression." International Journal of Molecular Sciences 20, no. 20 (October 19, 2019): 5184. http://dx.doi.org/10.3390/ijms20205184.
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Stroke is the second-leading cause of death globally and the leading cause of disability in adults. Medical complications after stroke, especially infections such as pneumonia, are the leading cause of death in stroke survivors. Systemic immunodepression is considered to contribute to increased susceptibility to infections after stroke. Different experimental models have contributed significantly to the current knowledge of stroke pathophysiology and its consequences. Each model causes different changes in the cerebral microcirculation and local inflammatory responses after ischemia. The vast majority of studies which focused on the peripheral immune response to stroke employed the middle cerebral artery occlusion method. We review various experimental stroke models with regard to microcirculatory changes and discuss the impact on local and peripheral immune response for studies of CNS-injury (central nervous system injury) induced immunodepression.
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Agrawal, Gopal. "Health transition in India: does data on causes of death reveal trends, patterns and determinants?" International Journal of Human Rights in Healthcare 8, no. 2 (June 15, 2015): 92–109. http://dx.doi.org/10.1108/ijhrh-11-2014-0030.
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Purpose – Twenty-first century has dawned with substantial achievements in population health outcome indicators in India. However, very little is known on patterns in causes of death in India. The paper aims to discuss this issue. Design/methodology/approach – In this paper, data was drawn from two sources namely, National Family Health Survey (NFHS-1, 1992-1993 and NFHS-2, 1998-1999) and published reports of Survey of Cause of Death (Rural). Three-years moving average causes-of-death estimates were calculated based on World Health Organization classification of causes of death. Negative binomial regression models were fitted to capture the effect of socio-demographic and behavioural determinants of patterns in causes of death. Findings – The leading causes of death were heart diseases, tuberculosis, asthma, paralysis, prematurity and cancer. Three-fifth of the deaths to children under the age of ten was from communicable, maternal, perinatal and nutritional conditions. On the other hand, about two-third persons aged 45 years and above were dying from non-communicable diseases. Female were at greater risk of dying from non-communicable diseases (IRR: 1.22, 95 per cent CI: 1.11-1.34, p < 0.001). Research limitations/implications – The epidemiologic transition in India has produced a shift in mortality from communicable, maternal, perinatal and nutritional conditions to non-communicable diseases, with little or no role played by injuries regardless of the level of all-cause mortality. Coupled with the effects of population age structures, other factors were also responsible for the bulk of the inter-regional disparities. These factors include differences in the populations’ health risks associated with the natural or built environments, prevalence of behavioural risk factors, or gaps in the capacities of health systems to respond to specific disease challenges, social stratification and others. Originality/value – This paper described the trends, patterns and geographic variability in India’s causes-of-death profile in terms of communicable diseases, non-communicable diseases and injuries, and socio-economic and demographic determinants of patterns in the profile.