UPSI Digital Repository (UDRep)
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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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