HRS Bibliography

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Wilmoth JM, London AS, Himes CL. Inter-Cohort Variation in the Consequences of U.S. Military Service for Men's Mid- to Late-Life Body Mass Index Trajectories. In: Burton-Jeangros C, Cullati S, Sacker A, Blane D, eds. A Life Course Perspective on Health Trajectories and Transitions. A Life Course Perspective on Health Trajectories and Transitions. New York: Springer; 2015:133-154.
Byrd DAR, Gonzales E, Moody DLBeatty, et al. Interactive Effects of Chronic Health Conditions And Financial Hardship On Episodic Memory Among Older Blacks: Findings From The Health And Retirement Study. Research in Human Development. 2020;17(1):41 - 56. doi:10.1080/15427609.2020.1746159.
Kolli A, Zhou Y, Chung G, Ware EB, Langa KM, Ehrlich JR. Interactions between the apolipoprotein E4 gene and modifiable risk factors for cognitive impairment: a nationally representative panel study. BMC Geriatrics. 2022;22(1):938. doi:10.1186/s12877-022-03652-w.
Harrati A, Schmitz LL. The Interaction of Health, Genetics, and Occupational Demands in SSDI Determinations. Cambridge, MA: National Bureau of Economic Research, Retirement and Disability Research Center; 2020.
Zhao W, Ware EB, He Z, Kardia SLR, Faul J. Interaction between Social/Psychosocial Factors and Genetic Variants on Body Mass Index: A Gene-Environment Interaction Analysis in a Longitudinal Setting. International Journal of Environmental Research and Public Health. 2017;14(10):1153. doi:10.3390/ijerph14101153.
Wu YYan, Thompson MD, Youkhana F, Pirkle CM. Interaction between physical activity and polygenic score on type 2 diabetes mellitus in older Black and White participants from the Health and Retirement Study. The Journals of Gerontology: Series A . 2021;76(7):1214-1221. doi:10.1093/gerona/glab025.
McGarry K. Inter Vivos Transfers and Intended Bequests. Journal of Public Economics. 1999;73(3):321-51. doi:10.1016/S0047-2727(99)00017-1.
Engelhardt GV, Eriksen MD. Intended Bequests and Housing Equity in Older Age. Boston, MA: Center for Retirement Research at Boston College; 2021.
Wu Y, Zeng J, Zhang F, et al. Integrative analysis of omics summary data reveals putative mechanisms underlying complex traits. Nature Communications. 2018;9(1). doi:10.1038/s41467-018-03371-0.
Gustman AL, Steinmeier TL. Integrating Retirement Models. Cambridge, MA: National Bureau of Economic Research; 2009. doi:10.3386/w15607.
Austin J, Reynolds C, Kaye J. Integrating objective health measurement using sensors, devices and pervasive computing in large-scale surveys. 2016.PDF icon Download PDF (303.81 KB)
Brown-Podgorski B, Roberts E. Integrating Medicare And Medicaid Data To Improve Care Quality And Advance Health Equity Among Dual-Eligible Beneficiaries. Health Affairs; 2022. doi:10.1377/hpb20221011.325614.
Slob E. Integrating Genetics into Economics. 2021.
Crimmins EM, Seeman T. Integrating Biology into the Study of Health Disparities. In: Waite LJ, ed. Aging, Health, and Public Policy: Demographic and Economic Perspectives. Vol. 30. Aging, Health, and Public Policy: Demographic and Economic Perspectives. New York: Population Council; 2005:89-107.
Vivek S. Integrated Multi-Omics Approach to Predict Dementia: Using an Explainable Variational Autoencoder (E-VAE) Classifier Model. ProQuest Dissertations and Theses. 2023:111.
Bhattacharya J. Insuring the Near-Elderly: How Much Would Medicare Save?. Annals of Internal Medicine. 2009;151(11):816-817. doi:10.7326/0003-4819-151-11-200912010-00158.
Johnson RW, Davidoff AJ, Moon M. Insuring the Near Elderly: The Potential Role for Medicare Buy-In Plans. The Urban Institute. 2002;The Retirement Project Brief Series(No. 13).
Xu X, Patel DA, Vahratian A, Ransom SB. Insurance coverage and health care use among near-elderly women. Womens Health Issues. 2006;16(3):139-48. doi:10.1016/j.whi.2006.02.005.
http://www.ncbi.nlm.nih.gov/pubmed/16765290?dopt=Abstract
Martinussen T, Vansteelandt S, Tchetgen Tchetgen EJ, Zucker DM. Instrumental variables estimation of exposure effects on a time-to-event endpoint using structural cumulative survival models. Biometrics. 2017;73(4):1140-1149. doi:10.1111/biom.12699.
http://www.ncbi.nlm.nih.gov/pubmed/28493302?dopt=Abstract
Tchetgen Tchetgen EJ, Walter S, Vansteelandt S, Martinussen T, M. Glymour M. Instrumental variable estimation in a survival context. Epidemiology. 2015;26(3):402-410. doi:10.1097/ede.0000000000000262.
Nguyen TT, Tchetgen Tchetgen EJ, Kawachi I, et al. Instrumental variable approaches to identifying the causal effect of educational attainment on dementia risk. Ann Epidemiol. 2016;26(1):71-6.e1-3. doi:10.1016/j.annepidem.2015.10.006.
http://www.ncbi.nlm.nih.gov/pubmed/26633592?dopt=Abstract
Kapteyn A, Panis C. Institutions and Saving for Retirement: Comparing the United States, Italy, and the Netherlands. In: Wise DA, ed. Analyses in the Economics of Aging. Analyses in the Economics of Aging. Chicago: University of Chicago Press; 2005:281-316.
Sawadogo W, Adera T. Insomnia Symptoms Trajectories and increased risk of Stroke: A Prospective Cohort Study (P1-5.021). Neurology. 2023;100. doi:10.1212/WNL.0000000000201917.
Dong Y, Yang FMargaret. Insomnia symptoms predict both future hypertension and depression. Preventative Medicine. 2019;123:41-47. doi:10.1016/j.ypmed.2019.02.001.
http://www.ncbi.nlm.nih.gov/pubmed/30742871?dopt=Abstract
Yao W, Luo J, Yu X, Jiang W, Zhang D. Insomnia symptoms are associated with an increased risk of type 2 diabetes mellitus among adults aged 50 and older. Sleep and Breathing. 2022;26(3):1409-1416. doi:10.1007/s11325-021-02497-8.