Affiliations: [a] College of Health Professions, Medical University of South Carolina, Charleston, SC, USA
| [b]
Shepherd Center, Atlanta, GA, USA
| [c] College of Education, Health, & Human Services, Kent State University, Kent, OH, USA
Correspondence:
[*]
Address for correspondence: James S. Krause, PhD, College of Health Professions, Medical University of South Carolina, 151-B Rutledge Ave, MSC 962, Charleston, SC 29425, USA. Tel.: +1 843 792 1337; E-mail: krause@musc.edu.
Abstract: BACKGROUND:Spinal cord injury (SCI) and multiple sclerosis (MS) are disabling conditions associated with low employment rates and loss of earnings. OBJECTIVE:Quantify the relationships of demographic, educational, and functional characteristics with gainful employment and earnings after SCI or MS. METHODS:Participants were adults under age 65 with SCI (n = 1275) or MS (n = 1107) identified through a specialty hospital or a state-based surveillance registry in the southeastern United States. An econometric model of cross-sectional data using a two-step data analytic model examined employment status and earnings. This included one model that was restricted to only those employed (conditional earnings) and another model that included all participants, using $0 earnings for those who were unemployed (unconditional earnings – earnings not conditional upon being employed). RESULTS:Diagnosis was not significantly related to employment status. Several functional characteristics were associated with lower odds of employment and higher unconditional earnings (cognition, walking, shopping independently). Higher conditional earnings were reported by those with MS ($16,405) and those without difficulty in cognition ($8,532) and bathing ($20,932). Higher educational attainment was related to probability of employment and greater earnings. CONCLUSIONS:Those with SCI and those with several types of functional limitations have lower quality of employment, as measured by earnings. Efforts should be made to enhance quality of employment for those at greatest risk for unemployment and underemployment.
