The Duke Center for Population Health and Aging (CPHA) will continue its highly synergistic interdisciplinary environment to develop faculty in aging and to foster important research breakthroughs, particularly in the overlapping areas of biodemography (i.e. biological and biomedical demography of aging), life course studies of health and well-being across the life span, and intergenerational studies, including the transmission of health and longevity. These activities will be supported by a strong administrative Core that provides central cohesive clerical, technical and research services;programming to support pilot research initiatives and advanced training for doctoral and postdoctoral students;and innovative interinstitutional networks that will enable the continuation of collaboration and training in the region. A key resource to be developed is a statistical data enclave to improve the distribution of useful public data that protect the confidentiality of study subjects.

Public Health Relevance

The CPHA will advance understanding of the determinants of healthy aging and longevity by developing new research areas, supporting and enlarging the world's community of demographic scientists, and developing new mathematical and statistical methods for the analysis of data related to the biodemogaphy of aging as well as data management services.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Center Core Grants (P30)
Project #
2P30AG034424-06
Application #
8743499
Study Section
Special Emphasis Panel (ZAG1)
Program Officer
Haaga, John G
Project Start
2009-07-15
Project End
2019-06-30
Budget Start
2014-09-15
Budget End
2015-06-30
Support Year
6
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Duke University
Department
Type
Organized Research Units
DUNS #
City
Durham
State
NC
Country
United States
Zip Code
27705
Domingue, Benjamin W; Belsky, Daniel W (2017) The social genome: Current findings and implications for the study of human genetics. PLoS Genet 13:e1006615
Sun, Shiquan; Hood, Michelle; Scott, Laura et al. (2017) Differential expression analysis for RNAseq using Poisson mixed models. Nucleic Acids Res 45:e106
Stallard, Eric; Kinosian, Bruce; Stern, Yaakov (2017) Personalized predictive modeling for patients with Alzheimer's disease using an extension of Sullivan's life table model. Alzheimers Res Ther 9:75
Belsky, Daniel W; Caspi, Avshalom; Cohen, Harvey J et al. (2017) Impact of early personal-history characteristics on the Pace of Aging: implications for clinical trials of therapies to slow aging and extend healthspan. Aging Cell 16:644-651
Schaefer, Jonathan D; Caspi, Avshalom; Belsky, Daniel W et al. (2017) Enduring mental health: Prevalence and prediction. J Abnorm Psychol 126:212-224
Jones, Owen R; Vaupel, James W (2017) Senescence is not inevitable. Biogerontology 18:965-971
Domingue, Benjamin W; Liu, Hexuan; Okbay, Aysu et al. (2017) Genetic Heterogeneity in Depressive Symptoms Following the Death of a Spouse: Polygenic Score Analysis of the U.S. Health and Retirement Study. Am J Psychiatry 174:963-970
Steenstrup, Troels; Kark, Jeremy D; Verhulst, Simon et al. (2017) Telomeres and the natural lifespan limit in humans. Aging (Albany NY) 9:1130-1142
Richmond-Rakerd, Leah S; Belsky, Daniel W (2017) Swedish Register Analysis of Divorce and Alcohol Use Disorder Highlights Social Relationships as a Target for Preventive Psychiatry and Genetic Research. Am J Psychiatry 174:411-413
Akushevich, I; Yashkin, A P; Kravchenko, J et al. (2017) Theory of partitioning of disease prevalence and mortality in observational data. Theor Popul Biol 114:117-127

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