METHODS: Prostate cancer cases diagnosed between 2003 and 2008 which met with the inclusion criteria were included in the study. One hundred and twelfth (112) pairs of cases and controls matched by age and ethnicity were analysed. McNemar Odds Ratios (OR(M)) were calculated using McNemar Calculator software for univariate analysis while conditional logistic regression was used for multivariate analysis, both using SPSS version 12.0.
RESULTS: Most of the prostate cancer patients (68.8%) that came for treatment in UKMMC were above 70 years old. The majority were Chinese (50.0%) followed by Malay (46.4%) and Indian (3.6%). Multivariate analysis showed cases were more likely to have a first-degree relative with a history of cancer (OR= 3.77, 95% CI= 1.19-11.85), to have been exposed to pesticides (OR= 5.57, 95% CI= 1.75-17.78) and consumed more meat (OR= 12.23, 95% CI= 3.89-39.01). Significantly reduced risks of prostate cancer were noted among those consuming more vegetables (OR= 0.12, 95% CI= 0.02-0.84), more tomatoes (OR= 0.35, 95% CI= 0.13-0.93) and those who had frequent sexual intercourse (OR= 0.44, 95% CI= 0.19-0.96).
CONCLUSION: Some lifestyle and occupation factors are strong predictors of the occurrence of prostate cancer among patients in UKMMC. More importantly, with the identification of the potentially modifiable risk factors, proper public health intervention can be improved.
METHODS: This was a cross-sectional study. All participants who fulfilled the requirements of the study according to the inclusion and exclusion criteria were enrolled. Study instruments included a demographic data questionnaire, Positive and Negative Symptom Scale (PANSS), Trail Making Tests, Rey's Auditory Verbal Learning Test (RAVLT) and Digit Span. Bivariate analyses were done using chi-square for categorical data and t-test for continuous data and multiple logistic regression analysis was done to identify predictors of employment status.
RESULTS: A total of 95 participants who fulfilled the inclusion criteria were enrolled into the study. Among the sociodemographic, clinical and cognitive variables studied marital status, educational level, mean scores of negative symptoms, Digit Span and RAVLT and Trail Making Tests were found to show significant association with employment status on bivariate analyses. However, when entered into a logistic regression model, only cognitive variables ie. Trail A and B, Digit Span and RAVLT were significant predictors of employment status.
CONCLUSIONS: The results from this study support the role of cognitive function, particularly, attention, working memory and executive functioning on attaining and maintaining employment in persons with schizophrenia as measured by the RAVLT, Digit Span and Trail Making Tests. These findings may act as preliminary evidence suggesting the importance of integrating cognitive rehabilitation in the psychosocial rehabilitation program for patients with schizophrenia in Malaysia.