ABSTRACT
This paper assesses mortality rate for a cohort of drug users in Puerto Rico compared with that of the Island's general population, examining causes of death and estimating relative risk of death. Date and cause of death were obtained from death certificates during 1998. Vital status was confirmed through contact with subjects, family, and friends. HIV/AIDS was the major cause of death (47.7%), followed by homicide (14.6%), and accidental poisoning (6.3%). Females had higher relative risk of death than males in all age categories. Not living with a sex partner and not receiving drug treatment were related to higher mortality due to HIV/AIDS. Drug injection was the only variable explaining relative risk of death due to overdose. Puerto Rico needs to continue developing programs to prevent HIV/AIDS among drug users. Special attention should be given to young women, who appear to be in greatest need of programs to prevent early mortality.
Subject(s)
Humans , Male , Female , Adult , Hispanic or Latino/statistics & numerical data , Substance-Related Disorders/mortality , Age Distribution , Cause of Death , Cohort Studies , HIV Infections/mortality , Puerto Rico/ethnology , Regression Analysis , Risk Factors , Sex DistributionABSTRACT
In this study, the contribution of four distinct domains of the Help Seeking-Decision Making model to predicting the use of mental health services is examined. Using a proposed methodology the authors assess the relevance of this model and its domains to mental services planning. The methodology combines logistic regression analysis and receiver operating characteristic (ROC) curves. Logistic regression analysis allows us to examine the individual variables of the model and generate predictions about use. ROC curves allow us to compare and interpret the relative contribution of a predisposing domain, a physical and mental health domain, an enabling-restrictive domain, and an organizational domain in correctly classifying users and nonusers of mental health services. The physical and mental health domain yielded a Somer's D-statistic of 0.7, which corresponds to an 85% correct classification of randomly selected pairs of users and nonusers. The study findings suggest that comparing ROC curves helps to describe and interpret the domains of the model that are relevant for making predictions about who will or will not use mental health services during a 1-year period.
