The IBM spss 20.0(Armonk, NY, USA) was used for data analysis. Descriptive statistics were used to summarise and describe all the data. Mean and standard deviation were used to describe continuous data while frequency and percentages were used to describe categorical data. Differ ences in HRQoL, LUTS psychosocial well-being among and subgroups of socio-demographics and d were clinical examined using either independent t-test for two groups or one-way analysis of variance(ANovA) for three or more groups. The linear association between HRQol, LUTS and psychological well-being was analysed using Pearson's product-moment correlation. Multiple linear regression analysis using an enter method was conducted to determine the predictors of PCs and MCS of SF-12, which were entered as the two main dependent variables. All the potential predictive factors that demonstrated significant correlations with POS or MCS(i.e. p 0.05) were included in the multiple linear regression analysis to determine the predictive factors of HRQol. The level of significance of all statistical tests performed was set at p 0.05 and two-tailed.