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UBC Theses and Dissertations

Bayesian spatial and ecological modeling of suicide rates Lin, Yi


Suicide and suicide attempts constitute major public and mental health problems in many countries. The risk factors of suicide include not only psychological and other individual features but also the characteristics of the community in which the people live. Therefore, in order to better understand the potential impacts of community characteristics on suicide, the regional level effects of suicide need to be thoroughly examined. For this thesis, an ecological analysis was incorporated into a Bayesian disease mapping study in order to estimate suicide rates, explore regional risk factors, and discern spatial patterns in suicide risks. Fully Bayesian disease mapping and ecological regression methods were used to estimate area-specific suicide risks, investigate spatial variations, and explore and quantify the associations between regional characteristics and suicide occurrences. The fact that spatially smoothed estimates of suicide rates highlight the high risk regions can act as stable health outcome indicators at the regional level. Furthermore, regional characteristics explored as potential risk factors of suicide rates can provide a better understanding of regional variations of suicide rates. Both can help in planning future public health prevention programs. In order to avoid multicollinearity among risk factors and reduce the dimensionality of the risk indicators, Principal Component Analysis and Empirical Bayes method (via Penalized Quasi-Likelihood) were applied in variable selection and highlighting risk patterns. Using 10-year aggregated data for all age groups and both genders, this study conducted a comprehensive analysis of suicide hospitalization and mortality rates in eighty-four Local Health Areas in British Columbia (Canada). A broad range of regional characteristics was investigated and different associations with suicide rates were observed in different demographic and gender groups. The major regional risk patterns related to suicide rates across age groups were social and economic characteristics, which include unemployment rates, income, education attainment, marital status, family structure, and dwellings. Some age groups also showed a relation to aboriginal population, immigrants, and language. The results of this study may inform policy initiatives and programs for suicide prevention.

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