HRS Bibliography

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Deelen J, Evans DS, Arking DE, et al. A meta-analysis of genome-wide association studies identifies multiple longevity genes. Nature Communications. 2019;10(1):3669. doi:10.1038/s41467-019-11558-2.
http://www.ncbi.nlm.nih.gov/pubmed/31413261?dopt=Abstract
Deelen J, Evans DS, Arking DE, et al. A meta-analysis of genome-wide association studies identifies multiple longevity genes. Nature Communications. 2019;10(1):3669. doi:10.1038/s41467-019-11558-2.
http://www.ncbi.nlm.nih.gov/pubmed/31413261?dopt=Abstract
Yengo L, Sidorenko J, Kemper KE, et al. Meta-analysis of genome-wide association studies for height and body mass index in ∼700000 individuals of European ancestry. Human Molecular Genetics. 2018;27(20):3641-3649. doi:10.1093/hmg/ddy271.
http://www.ncbi.nlm.nih.gov/pubmed/30124842?dopt=Abstract
Yengo L, Sidorenko J, Kemper KE, et al. Meta-analysis of genome-wide association studies for height and body mass index in ∼700000 individuals of European ancestry. Human Molecular Genetics. 2018;27(20):3641-3649. doi:10.1093/hmg/ddy271.
Liu C, Kraja AT, Smith JA, Morrison AC, et al. Meta-analysis identifies common and rare variants influencing blood pressure and overlapping with metabolic trait loci. Nat Genet. 2016;48(10):1162-70. doi:10.1038/ng.3660.
Liu C, Kraja AT, Smith JA, Morrison AC, et al. Meta-analysis identifies common and rare variants influencing blood pressure and overlapping with metabolic trait loci. Nat Genet. 2016;48(10):1162-70. doi:10.1038/ng.3660.
Liu C, Kraja AT, Smith JA, Morrison AC, et al. Meta-analysis identifies common and rare variants influencing blood pressure and overlapping with metabolic trait loci. Nat Genet. 2016;48(10):1162-70. doi:10.1038/ng.3660.
Liu C, Kraja AT, Smith JA, Morrison AC, et al. Meta-analysis identifies common and rare variants influencing blood pressure and overlapping with metabolic trait loci. Nat Genet. 2016;48(10):1162-70. doi:10.1038/ng.3660.
Liu C, Kraja AT, Smith JA, Morrison AC, et al. Meta-analysis identifies common and rare variants influencing blood pressure and overlapping with metabolic trait loci. Nat Genet. 2016;48(10):1162-70. doi:10.1038/ng.3660.
Liu C, Kraja AT, Smith JA, Morrison AC, et al. Meta-analysis identifies common and rare variants influencing blood pressure and overlapping with metabolic trait loci. Nat Genet. 2016;48(10):1162-70. doi:10.1038/ng.3660.
Fisher GG, Stachowski A, Infurna FJ, Faul J, Grosch J, Tetrick LE. Mental work demands, retirement, and longitudinal trajectories of cognitive functioning. J Occup Health Psychol. 2014;19(2):231-42. doi:10.1037/a0035724.
http://www.ncbi.nlm.nih.gov/pubmed/24635733?dopt=Abstract
Fisher GG, Stachowski A, Infurna FJ, Faul J, Grosch J, Tetrick LE. Mental work demands, retirement, and longitudinal trajectories of cognitive functioning. J Occup Health Psychol. 2014;19(2):231-42. doi:10.1037/a0035724.
http://www.ncbi.nlm.nih.gov/pubmed/24635733?dopt=Abstract
Bogan VL, Fertig AR. Mental health and retirement savings: Confounding issues with compounding interest. Health Economics. 2018;27:404-425. doi:https://doi.org/10.1002/hec.3579.
Bakulski KM, Fu M, Faul J, Jin Y, Ware EB. Mendelian randomization of smoking behavior on cognitive status among older Americans. Alzheimer's & Dementia: The Journal of the Alzheimer's Association. 2020;16(S10):e041221. doi:10.1002/alz.041221.
Bakulski KM, Fu M, Faul J, Jin Y, Ware EB. Mendelian randomization of smoking behavior on cognitive status among older Americans. Alzheimer's & Dementia: The Journal of the Alzheimer's Association. 2020;16(S10):e041221. doi:10.1002/alz.041221.
Fu M, Bakulski KM, Higgins C, Ware EB. Mendelian Randomization of Dyslipidemia on Cognitive Impairment Among Older Americans. Frontiers in Neurology. 2021;12(660212). doi:10.3389/fneur.2021.660212.
González HM, Bowen ME, Fisher GG. Memory decline and depressive symptoms in a nationally representative sample of older adults: the Health and Retirement Study (1998-2004). Dement Geriatr Cogn Disord. 2008;25(3):266-71. doi:10.1159/000115976.
http://www.ncbi.nlm.nih.gov/pubmed/18270489?dopt=Abstract
Waite LL, Fishman P, Basu A, Crane PK, Larson EB, Coe NB. Medicare expenditures attributable to dementia. Health Services Research. 2019. doi:10.1111/1475-6773.13134.
http://www.ncbi.nlm.nih.gov/pubmed/30868557?dopt=Abstract
Daras LCoots, Feng Z, Wiener JM, Kaganova Y. Medicare Expenditures Associated With Hospital and Emergency Department Use Among Beneficiaries With Dementia. Inquiry. 2017;54:46958017696757. doi:10.1177/0046958017696757.
Jones JBailey, De Nardi M, French E, McGee R, Rodgers R. Medical Spending, Bequests, and Asset Dynamics Around the Time of Death. Cambridge, MA: National Bureau of Economic Research; 2020. doi:10.3386/w26879.
Kapinos K, Fischer SH, Mulcahy A, Hayden O, Barron R. Medical Costs for Osteoporosis-Related Fractures in High-Risk Medicare Beneficiaries. Journal of the American Geriatrics Society. 2018;66(12):2298-2304. doi:10.1111/jgs.15585.
De Nardi M, French E, Jones JBailey. Medicaid Insurance in Old Age. Ann Arbor, MI: Michigan Retirement and Disability Research Center, University of Michigan; 2012.
Fang H, Keane MP, Khwaja A, Salm M, Silverman DS. Mechanisms of Structural Models: The Case of the Mickey Mantle Effect. American Economic Review, Papers and Proceedings. 2007;May:53-9.
Heisler MM, Faul J, Hayward RA, Langa KM, Blaum CS, Weir DR. Mechanisms for racial and ethnic disparities in glycemic control in middle-aged and older Americans in the health and retirement study. Arch Intern Med. 2007;167(17):1853-60. doi:10.1001/archinte.167.17.1853.
http://www.ncbi.nlm.nih.gov/pubmed/17893306?dopt=Abstract
Coyne D, Fadlon I, Porzio T. Measuring Valuation of Liquidity with Penalized Withdrawals. National Bureau of Economic Research; 2022. doi:10.3386/w30007.