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Objective: To identify risks factors associated with pressure ulcers (PrU) after spinal cord injury (SCI) by examining race and indicators of socioeconomic status (measured by income and education). We hypothesize African Americans will have a greater risk for PrUs than whites, but this relationship will be mediated by the 2 socioeconomic status indicators. Design: Cohort study. Setting: A large rehabilitation hospital in the southeastern US. Participants: 1,466 white and African American adults at least 1-year post-traumatic SCI. Outcome Measures: (a) PrUs in the past year, (b) current PrU, (c) surgery to repair a PrU since injury. Results: In preliminary analyses, race was significantly associated with having a current PrU and with having surgery to repair a PrU since injury. In multivariable analyses, the relationships of PrU with having a current PrU and with having surgery to repair a PrU were both mediated by income and education such that the relationships were no longer significant. Lower income was associated with increased odds of each PrU outcome. After controlling for other variables in the model, education was associated with increased odds of having a current PrU. Conclusion: These findings help clarify the relationships between race and socioeconomic status with PrUs after SCI. Specifically, a lack of resources, both financial and educational, is associated with worse PrU outcomes. These results can be used by both providers and policy makers when considering prevention and intervention strategies for PrUs among people with SCI.

Study design: Cross-sectional survey. Objective: To identify barriers and facilitators to employment after spinal cord injury (SCI) and their relationship with labor force participation. Methods: Participants were initially identified through specialty hospitals in the Midwest and Southeastern United States of America. 781 adults with traumatic SCI, at least 1 year post-injury, and between the ages of 18-64, participated. A 30-item instrument on barriers and facilitators to employment was administered. Analyses included exploratory factor analysis (EFA), confirmatory factor analysis (CFA) and comparisons of scores as a function of employment status. Results: EFA indicated six primary themes (root mean square error of approximation (RMSEA) ¼ 0.040), including: (a) resources, (b) health status, (c) disability considerations, (d) lack of importance, (e) disincentives and (f) motivation. CFA indicated an acceptable fit (RMSEA ¼ 0.078). Univariate analyses indicated each item and factor was significantly different as a function of labor force participation. After controlling for biographical and injury factors, multinomial logistic regression indicated three factors significantly differentiated those never employed, those currently unemployed but had worked since injury and those currently employed. Those employed reported higher scores for resources and motivation and lower scores for lack of importance. Conclusions: Barriers and facilitators were consistently related to labor force participation, with facilitators more highly related to labor force participation than barriers. Although loss of financial and medical benefits (disincentives) as well as health status have been reported as barriers to employment, they were not as highly correlated with labor force participation as were other factors.

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Objective: To develop and validate a latent model of health outcomes among persons with spinal cord injury. Methods: Survey data were collected at a large specialty hospital in the southeastern USA from 1,388 adult participants with traumatic spinal cord injury of at least 1 year's duration. Multiple indicators of health outcomes were used, including general health ratings, days adversely affected by poor health and poor mental health, treatments and hospitalizations, depressive symptoms, symptoms of illness or infection (eg, sweats, chills, fever), and multiple individual conditions (eg, pressure ulcers, subsequent injuries, fractures, contractures). Results: We performed exploratory factor analysis on half of the sample and confirmatory factor analysis on the other. A 6-factor solution was the best overall solution, because there was an excellent fit with the exploratory factor analysis (root mean square error of approximation 5 0.042) and acceptable fit with the confirmatory factor analysis (root mean square error of approximation 5 0.065). Four of the factors were types of secondary conditions, including symptoms of illness or infection, orthopedic conditions, pressure ulcers, and subsequent injuries. The 2 remaining factors reflected global health and treatment. Gender, race-ethnicity, age, injury severity, and years of education were all significantly related to at least 1 factor dimension, indicating variations in health outcomes related to these characteristics. Conclusion: Identification of the 6 factors represents an improvement over the utilization of multiple individual indicators, because composite scores generated from multiple individual indicators provide more informative and stable outcome scores than utilization of single indicators.