HRS Bibliography

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Frytak JR, Harley CR, Finch MD. Socioeconomic Status and Health over the Life Course: Capital as a Unifying Concept. In: Mortimer JT, Shanahan MJ, eds. Handbook of the Life Course. Handbook of the Life Course. New York: Kluwer Academic/Plenum Publishers; 2003:623-643. doi:10.1007/978-0-306-48247-2_28.
Frytak JR, Harley CR, Finch MD. Socioeconomic Status and Health over the Life Course: Capital as a Unifying Concept. In: Mortimer JT, Shanahan MJ, eds. Handbook of the Life Course. Handbook of the Life Course. New York: Kluwer Academic/Plenum Publishers; 2003:623-643. doi:10.1007/978-0-306-48247-2_28.
Klopack ET, Thyagarajan B, Faul J, et al. Socioeconomic status and immune aging in older US adults in the health and retirement study. Biodemography and Social Biology. 2022;67(3-4):187-202. doi:10.1080/19485565.2022.2149465.
Stringhini S, Carmeli C, Jokela M, et al. Socioeconomic status, non-communicable disease risk factors, and walking speed in older adults: multi-cohort population based study. BMJ. 2018;360:k1046. doi:10.1136/bmj.k1046.
Demirkan A, Lahti J, Direk N, et al. Somatic, positive and negative domains of the Center for Epidemiological Studies Depression (CES-D) scale: a meta-analysis of genome-wide association studies. Psychol Med. 2016;46(8):1613-23. doi:10.1017/S0033291715002081.
http://www.ncbi.nlm.nih.gov/pubmed/26997408?dopt=Abstract
Demirkan A, Lahti J, Direk N, et al. Somatic, positive and negative domains of the Center for Epidemiological Studies Depression (CES-D) scale: a meta-analysis of genome-wide association studies. Psychol Med. 2016;46(8):1613-23. doi:10.1017/S0033291715002081.
http://www.ncbi.nlm.nih.gov/pubmed/26997408?dopt=Abstract
Demirkan A, Lahti J, Direk N, et al. Somatic, positive and negative domains of the Center for Epidemiological Studies Depression (CES-D) scale: a meta-analysis of genome-wide association studies. Psychol Med. 2016;46(8):1613-23. doi:10.1017/S0033291715002081.
http://www.ncbi.nlm.nih.gov/pubmed/26997408?dopt=Abstract
Li M, Li Y, Weeks O, et al. SOS2 and ACP1 Loci Identified through Large-Scale Exome Chip Analysis Regulate Kidney Development and Function. Journal of the American Society of Nephrology . 2017;28(3):981-994. doi:10.1681/ASN.2016020131.
Li M, Li Y, Weeks O, et al. SOS2 and ACP1 Loci Identified through Large-Scale Exome Chip Analysis Regulate Kidney Development and Function. Journal of the American Society of Nephrology . 2017;28(3):981-994. doi:10.1681/ASN.2016020131.
Li M, Li Y, Weeks O, et al. SOS2 and ACP1 Loci Identified through Large-Scale Exome Chip Analysis Regulate Kidney Development and Function. Journal of the American Society of Nephrology . 2017;28(3):981-994. doi:10.1681/ASN.2016020131.
Li M, Li Y, Weeks O, et al. SOS2 and ACP1 Loci Identified through Large-Scale Exome Chip Analysis Regulate Kidney Development and Function. Journal of the American Society of Nephrology . 2017;28(3):981-994. doi:10.1681/ASN.2016020131.
Li M, Li Y, Weeks O, et al. SOS2 and ACP1 Loci Identified through Large-Scale Exome Chip Analysis Regulate Kidney Development and Function. Journal of the American Society of Nephrology . 2017;28(3):981-994. doi:10.1681/ASN.2016020131.
Li M, Li Y, Weeks O, et al. SOS2 and ACP1 Loci Identified through Large-Scale Exome Chip Analysis Regulate Kidney Development and Function. Journal of the American Society of Nephrology . 2017;28(3):981-994. doi:10.1681/ASN.2016020131.
Li M, Li Y, Weeks O, et al. SOS2 and ACP1 Loci Identified through Large-Scale Exome Chip Analysis Regulate Kidney Development and Function. Journal of the American Society of Nephrology . 2017;28(3):981-994. doi:10.1681/ASN.2016020131.
Fang H, Keane MP, Silverman DS. Sources of Advantageous Selection: Evidence from the Medigap Insurance Market. Journal of Political Economy. 2008;116(2):303-350. doi:https://doi.org/10.1086/587623.
Zhang B, de Leon CFMendes, Langa KM, et al. Source-Specific Air Pollution and Loss of Independence in Older Adults Across the US. JAMA Netw Open. 2024;7(6):e2418460. doi:10.1001/jamanetworkopen.2024.18460.
http://www.ncbi.nlm.nih.gov/pubmed/38941096?dopt=Abstract
Falba T, Sindelar JL. Spousal concordance in health behavior change. Health Serv Res. 2008;43(1 Pt 1):96-116. doi:10.1111/j.1475-6773.2007.00754.x.
http://www.ncbi.nlm.nih.gov/pubmed/18211520?dopt=Abstract
Fletcher JM. Spousal concordance in telomere length: New evidence from older adults in the US. PLoS One. 2018;13(11):e0202388. doi:10.1371/journal.pone.0202388.
http://www.ncbi.nlm.nih.gov/pubmed/30383762?dopt=Abstract
Farnham MP, Sevak P. State Fiscal Institutions and Empty-Nest Migration: Are Tiebout voters hobbled?. Journal of Public Economics. 2006;90(3):407 -427. doi:https://doi.org/10.1016/j.jpubeco.2005.07.005.
Chen Y, Fang H. The State of Mental Health Among the Elderly Chinese. Cambridge, MA: National Bureau of Economic Research; 2020. doi:10.3386/w26690.
Walsemann KM, Hair NL, Farina MP, Tyagi P, Jackson H, Ailshire JA. State-level desegregation in the U.S. South and mid-life cognitive function among Black and White adults. Social Science & Medicine (1983). Forthcoming;338:116319. doi:10.1016/j.socscimed.2023.116319.
Willis M, Staudinger UM, Factor-Litvak P, Calvo E. Stress and salivary telomere length in the second half of life: A comparison of life-course models. Advances in Life Course Research. 2019;39:34-41. doi:10.1016/j.alcr.2019.02.001.
Weinstein M, Willis RJ. Stretching Social Surveys to Include Bioindicators: Possibilities for the Health and Retirement Study, Experience from The Taiwan Study of the Elderly. In: Finch CE, Vaupel JW, Kinsella K, eds. Cells and Surveys: Should Biological Measures Be Included in Social Research?. Cells and Surveys: Should Biological Measures Be Included in Social Research? National Academy Press; 2001.
Fischer K. Study: Mid-life loneliness serves as risk factor for death later.
Davies G, Lam M, Harris SE, et al. Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function. Nature Communications. 2018;9(1):2098. doi:10.1038/s41467-018-04362-x.