HRS Bibliography

Bibliography Search
Export 1142 results:
Filters: First Letter Of Last Name is D  [Clear All Filters]

Journal Article

Dong XS, Wang X, Daw C, Ringen K. Chronic diseases and functional limitations among older construction workers in the United States: a 10-year follow-up study. J Occup Environ Med. 2011;53(4):372-80. doi:10.1097/JOM.0b013e3182122286.
http://www.ncbi.nlm.nih.gov/pubmed/21407096?dopt=Abstract
Latham-Mintus K, Doshi S, Moorthi RN. CHRONIC KIDNEY DISEASE, MUSCLE WEAKNESS, AND MOBILITY LIMITATION. Innovation in Aging. 2019;3(Suppl 1):S523 - S523.
Das A. Chronic Ongoing Stressors and C-Reactive Protein: A Within-Person Study. J Aging Health. 2019:898264319862419. doi:10.1177/0898264319862419.
http://www.ncbi.nlm.nih.gov/pubmed/31315485?dopt=Abstract
Martin-Bassols N, de New SC, Johnston DW, Shields MA. Cognitive activity at work and the risk of dementia. Health Econ. 2023;32(7):1561-1580. doi:10.1002/hec.4679.
Whitlock EL, L Diaz-Ramirez G, Smith AK, W Boscardin J, Avidan MS, M. Glymour M. Cognitive Change After Cardiac Surgery Versus Cardiac Catheterization: A Population-Based Study. The Annals of Thoracic Surgergy. 2019;107(4):1119-1125. doi:10.1016/j.athoracsur.2018.10.021.
http://www.ncbi.nlm.nih.gov/pubmed/30578068?dopt=Abstract
Hu P, Lee J, Beaumaster S, et al. Cognitive Function and Cardiometabolic-Inflammatory Risk Factors Among Older Indians and Americans. Journal of the American Geriatrics Society. 2020;68 (Suppl 3):S36-S44. doi:10.1111/jgs.16734.
Mariano J, Marques S, Ramos MR, de Vries H. Cognitive functioning mediates the relationship between self-perceptions of aging and computer use behavior in late adulthood: Evidence from two longitudinal studies. Computers in Human Behavior. 2021;121:106807. doi:10.1016/j.chb.2021.106807.
Saito Y, Kim JK, Davarian S, Hagedorn A, Crimmins EM. Cognitive Performance Among Older Persons in Japan and the United States. Journal of the American Geriatrics Society. 2019. doi:10.1111/jgs.16163.
Dushi I, Iams HM. Cohort differences in wealth and pension participation of near-retirees. Soc Secur Bull. 2008;68(3):45-66.
http://www.ncbi.nlm.nih.gov/pubmed/19260617?dopt=Abstract
Domingue BW, Conley DC, Fletcher JM, Boardman JD. Cohort Effects in the Genetic Influence on Smoking. Behav Genet. 2016;46(1):31-42. doi:10.1007/s10519-015-9731-9.
http://www.ncbi.nlm.nih.gov/pubmed/26223473?dopt=Abstract
Sheehan CM, Domingue BW, Crimmins EM. Cohort Trends in the Gender Distribution of Household Tasks in the United States and the Implications for Understanding Disability. Journal of Aging and Health. 2019. doi:10.1177/0898264318793469.
Rietveld CA, Esko T, Davies G, et al. Common genetic variants associated with cognitive performance identified using the proxy-phenotype method. Proc Natl Acad Sci U S A. 2014;111(38):13790-4. doi:10.1073/pnas.1404623111.
http://www.ncbi.nlm.nih.gov/pubmed/25201988?dopt=Abstract
Rietveld CA, Esko T, Davies G, et al. Common genetic variants associated with cognitive performance identified using the proxy-phenotype method. Proc Natl Acad Sci U S A. 2014;111(38):13790-4. doi:10.1073/pnas.1404623111.
http://www.ncbi.nlm.nih.gov/pubmed/25201988?dopt=Abstract
Rietveld CA, Esko T, Davies G, et al. Common genetic variants associated with cognitive performance identified using the proxy-phenotype method. Proc Natl Acad Sci U S A. 2014;111(38):13790-4. doi:10.1073/pnas.1404623111.
http://www.ncbi.nlm.nih.gov/pubmed/25201988?dopt=Abstract
Rietveld CA, Esko T, Davies G, et al. Common genetic variants associated with cognitive performance identified using the proxy-phenotype method. Proc Natl Acad Sci U S A. 2014;111(38):13790-4. doi:10.1073/pnas.1404623111.
http://www.ncbi.nlm.nih.gov/pubmed/25201988?dopt=Abstract
Ware EB, Mukherjee B, Sun YV, Diez-Roux AV, Kardia SLR. Comparative genome-wide association studies of a depressive symptom phenotype in a repeated measures setting by race/ethnicity in the Multi-Ethnic Study of Atherosclerosis. BMC Genet. 2015;16:118. doi:10.1186/s12863-015-0274-0.
http://www.ncbi.nlm.nih.gov/pubmed/26459564?dopt=Abstract
Verma C, Zhang M, Li M, Bergren S, Dong XQ. A Comparison of Cognitive Function in Pine Study to Health and Retirement Study & CHARLS Study. Innovation in Aging. 2020;4(Suppl 1):924. doi:10.1093/geroni/igaa057.3390.
O'Shea DM, Alaimo H, Davis JD, Galvin JE, Tremont G. A comparison of cognitive performances based on differing rates of DNA methylation GrimAge acceleration among older men and women. Neurobiology & Aging. 2023;123:83-91. doi:10.1016/j.neurobiolaging.2022.12.011.
Zhang B, Weuve J, Langa KM, et al. Comparison of Particulate Air Pollution From Different Emission Sources and Incident Dementia in the US. JAMA Intern Med. 2023. doi:10.1001/jamainternmed.2023.3300.
Zhang B, Weuve J, Langa KM, et al. Comparison of Particulate Air Pollution From Different Emission Sources and Incident Dementia in the US. JAMA Intern Med. 2023. doi:10.1001/jamainternmed.2023.3300.
Bloomberg M, Dugravot A, Sommerlad A, Kivimäki M, Singh-Manoux A, Sabia S. Comparison of sex differences in cognitive function in older adults between high- and middle-income countries and the role of education: a population-based multicohort study. Age Ageing. 2023;52(2). doi:10.1093/ageing/afad019.
http://www.ncbi.nlm.nih.gov/pubmed/36821646?dopt=Abstract
Ben-Avraham D, Karasik D, Verghese J, et al. The complex genetics of gait speed: genome-wide meta-analysis approach. Aging (Albany NY). 2017;9(1):209-246. doi:10.18632/aging.101151.
http://www.ncbi.nlm.nih.gov/pubmed/28077804?dopt=Abstract
Ben-Avraham D, Karasik D, Verghese J, et al. The complex genetics of gait speed: genome-wide meta-analysis approach. Aging (Albany NY). 2017;9(1):209-246. doi:10.18632/aging.101151.
http://www.ncbi.nlm.nih.gov/pubmed/28077804?dopt=Abstract
Ben-Avraham D, Karasik D, Verghese J, et al. The complex genetics of gait speed: genome-wide meta-analysis approach. Aging (Albany NY). 2017;9(1):209-246. doi:10.18632/aging.101151.
http://www.ncbi.nlm.nih.gov/pubmed/28077804?dopt=Abstract
Ben-Avraham D, Karasik D, Verghese J, et al. The complex genetics of gait speed: genome-wide meta-analysis approach. Aging (Albany NY). 2017;9(1):209-246. doi:10.18632/aging.101151.
http://www.ncbi.nlm.nih.gov/pubmed/28077804?dopt=Abstract