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Bailey and Dynarski's work cited in Bloomberg article on growing U.S. inequality

Frey says current minority college completion rates predict decline in college-educated Americans

Kimball and unnamed coauthor examine male bias in economics

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Call for Proposals: Small Grants for Research Using PSID Data. Due March 2, 2015

PSC Fall 2014 Newsletter now available

Martha Bailey and Nicolas Duquette win Cole Prize for article on War on Poverty

Michigan's graduate sociology program tied for 4th with Stanford in USN&WR rankings

Next Brown Bag

Monday, Jan 26
Jeff Smith, Consequences of Student-College Mismatch

Early mortality and years of potential life lost among Veterans Affairs patients with depression

Archived Abstract of Former PSC Researcher

Zivin, Kara, M. Ilgen, P. Pfeiffer, D. Welsh, J. McCarthy, M. Valenstein, E. Miller, K. Islam, and H. Kales. 2012. "Early mortality and years of potential life lost among Veterans Affairs patients with depression." Psychiatric Services, 63(8): 823-6.

OBJECTIVE: Substantial literature documents excess and early mortality among individuals with serious mental illness, but there are relatively few data about mortality and depression. METHODS: During fiscal year 2007, data from the U.S. Department of Veterans Affairs and the National Death Index were used to calculate mean age of death and years of potential life lost (YPLL) associated with 13 causes of death among veterans with (N=701,659) or without (N=4,245,193) depression. RESULTS: Compared with nondepressed patients, depressed patients died younger (71.1 versus 75.9) and had more YPLL (13.4 versus 10.2) as a result of both natural and unnatural causes. Depending on the cause of death, depressed patients died between 2.5 and 8.7 years earlier and had 1.5 to 6.1 YPLL compared with nondepressed patients. CONCLUSIONS: These findings have important implications for clinical practice, given that improved quality of care may be needed to reduce early mortality among depressed VA patients.

DOI:10.1176/appi.ps.201100317 (Full Text)

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