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Type :thesis
Subject :RC Internal medicine
Main Author :Alramah, Maryam Ahmed Salem
Title :Development of multivariate prevalent cancer mapping model in Libya
Place of Production :Tanjong Malim
Publisher :Fakulti Sains dan Matematik
Year of Publication :2018
Corporate Name :Universiti Pendidikan Sultan Idris
PDF Guest :Click to view PDF file

Abstract : Universiti Pendidikan Sultan Idris
The aim of this study was to develop the best possible method for providing estimates of relative risk for cancers by utilizing a multivariate approach through shared component model to produce specific and shared spatial patterns of cancer disease in Libya. The methodology in this study is statistical model to development to jointly analyze the spatial variation in rates of several cancers with their four spatial components without any conditions. The data for incidence of breast, lung, prostate, bladder, stomach, colon and liver in Libya districts, were used in this study. Four risk factors representing smoking, low physical activity, overweight and alcohol consumption were considered. A general framework for jointly modelling the variation of seven cancers, some of which share latent spatial fields, is considered. Finally, a new Multivariate Shared Component model is successfully developed. The procedure for predicting relative risks based on the model is presented in order to suggest approximate future cancers diseases progression patterns for Libya. In this study, the new model and the existing models were then applied to the morbidity data of seven types of cancer and four components for female and males in Libya during 2006-2011. An overall assessment of the models was carried out based on the goodness of fit. The results of the Deviance Information Criterion (DIC) value (BYM: 821.841, Mixture model: 797.832, SCM: 794.788) demonstrated how the new model fits the data better than the existing models. Furthermore, the findings of the analysis or the spatial maps analysis showed that on the basis of the model, the areas of high risk were relatively distributed across the region. As a conclusion, an observed comparison of the existing models and the new model based on the posterior precision of the relative risk estimates, strongly suggests that the multivariate modelling approach is a valuable expansion over individual analyses. The shared component model also can be readily applied to other; cancers or non-communicable diseases, risk factors, spatial areas, and time periods. The implications is that the model will provide accurate and clear maps of cancer morbidity across all regions in Libya. The information will be valuable for guiding public health strategies to reduce cancer risk, as well as of risk -lifestyle behaviours through cancer disease and maintaining a healthy lifestyle.

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