The Research Core will serve as the nucleus connecting the partnering institutions'research activities while incubating new research ideas. The theme of the Core, as well as of the theme of the entire National Transdisciplinary Collaborative Center for African American Men's Health (NTCC), is the reduction of disparities related to African American men's health over the life course. Our objective is to advance the understanding of racial/ethnic disparities as they relate to African American men's health throughout the life course, with the goal of developing and implementing interventions to address these disparities. We will pursue this objective in two ways: 1) by developing and testing interventions directed at the most important causes of morbidity and mortality at various stages during the life course of African American males;and 2) by studying the development and progression of risk factors for the main causes of morbidity and mortality of African American males over the life course, as well as factors related to racial/ethnic health disparities, utilizing data from ongoing longitudinal epidemiological studies. Our ultimate goal is to reduce and eventually eliminate racial/ethnic disparities related to African American men's health. We will build on the success of the research conducted by our NIMHD-funded Centers of Excellence (COEs), our Enhancing Minority Participation in Clinical Trials (EMPaCT) U24 National Consortium, and our history of partnership in the past several years. Our COEs and the EMPaCT Consortium will also provide an infrastructure and facilities to leverage the Cores/Programs proposed in this application, to ensure the success of the proposed and future research.

Agency
National Institute of Health (NIH)
Institute
National Institute on Minority Health and Health Disparities (NIMHD)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
5U54MD008620-03
Application #
8668144
Study Section
Special Emphasis Panel (ZMD1)
Project Start
Project End
Budget Start
2014-07-01
Budget End
2015-06-30
Support Year
3
Fiscal Year
2014
Total Cost
Indirect Cost
Name
University of Alabama Birmingham
Department
Type
DUNS #
City
Birmingham
State
AL
Country
United States
Zip Code
35294
Zhang, Jing; Yuan, Yiping; Chu, Haitao (2016) The Impact of Excluding Trials from Network Meta-Analyses - An Empirical Study. PLoS One 11:e0165889
Kenigsberg, Tat'Yana A; Winston 3rd, Willie; Gibson, Priscilla A et al. (2016) African American caregivers' resources for support: Implications for children's perceived support from their caregiver. Child Youth Serv Rev 61:337-344
Hong, Hwanhee; Chu, Haitao; Zhang, Jing et al. (2016) A Bayesian missing data framework for generalized multiple outcome mixed treatment comparisons. Res Synth Methods 7:6-22
Ho, Yen-Yi; Guan, Weihua; O'Connell, Michael et al. (2016) Powerful association test combining rare variant and gene expression using family data from Genetic Analysis Workshop 19. BMC Proc 10:251-255
Ma, Xiaoye; Chen, Yong; Cole, Stephen R et al. (2016) A hybrid Bayesian hierarchical model combining cohort and case-control studies for meta-analysis of diagnostic tests: Accounting for partial verification bias. Stat Methods Med Res 25:3015-3037
Abbott, Kenneth L; Nyre, Erik T; Abrahante, Juan et al. (2015) The Candidate Cancer Gene Database: a database of cancer driver genes from forward genetic screens in mice. Nucleic Acids Res 43:D844-8
Ma, Xiaoye; K Suri, Muhammad Fareed; Chu, Haitao (2014) A trivariate meta-analysis of diagnostic studies accounting for prevalence and non-evaluable subjects: re-evaluation of the meta-analysis of coronary CT angiography studies. BMC Med Res Methodol 14:128
Chen, Yong; Liu, Yulun; Ning, Jing et al. (2014) A composite likelihood method for bivariate meta-analysis in diagnostic systematic reviews. Stat Methods Med Res :
Chen, Liddy M; Ibrahim, Joseph G; Chu, Haitao (2014) Flexible stopping boundaries when changing primary endpoints after unblinded interim analyses. J Biopharm Stat 24:817-33
Ho, Yen-Yi; Baechler, Emily C; Ortmann, Ward et al. (2014) Using gene expression to improve the power of genome-wide association analysis. Hum Hered 78:94-103

Showing the most recent 10 out of 11 publications