HRS Bibliography

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2018

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.
Bishop NJ, Zuniga KE, Lucht AL. Latent Profiles of Macronutrient Density and their Association with Mobility Limitations in an Observational Longitudinal Study of Older U.S. Adults. The Journal of Nutrition, Health and Aging. 2018;22(6):645-654. doi:10.1007/s12603-017-0986-0.
http://www.ncbi.nlm.nih.gov/pubmed/29806853?dopt=Abstract
Ogilvie RP, Zabetian A, Mokdad AH, Narayan KMVenkat. Lifestyle Characteristics Among People With Diabetes and Prediabetes. In: Diabetes in America. 3rdrd ed. Diabetes in America. Bethesda, MD: National Institute of Diabetes and Digestive and Kidney Disease; 2018.
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.
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
Carr E, Fleischmann M, Goldberg M, et al. Occupational and educational inequalities in exit from employment at older ages: evidence from seven prospective cohorts. Occupational and Environmental Medicine. 2018;75(5):369 - 377. doi:10.1136/oemed-2017-10461910.1136/oemed-2017-104619.supp1.
Carr E, Fleischmann M, Goldberg M, et al. Occupational and educational inequalities in exit from employment at older ages: evidence from seven prospective cohorts. Occupational and Environmental Medicine. 2018;75(5):369 - 377. doi:10.1136/oemed-2017-10461910.1136/oemed-2017-104619.supp1.
Hurd MD, Smith JP, Zissimopoulos JM. The Potential Effects of Obesity on Social Security Claiming Behavior and Retirement Benefits. J Gerontol B Psychol Sci Soc Sci. 2018;73(4):723-732. doi:10.1093/geronb/gbw016.
http://www.ncbi.nlm.nih.gov/pubmed/27044665?dopt=Abstract
Turcot V, Lu Y, Highland HM, et al. Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity. Nat Genet. 2018;50(1):26-41. doi:10.1038/s41588-017-0011-x.
http://www.ncbi.nlm.nih.gov/pubmed/29273807?dopt=Abstract
Turcot V, Lu Y, Highland HM, et al. Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity. Nat Genet. 2018;50(1):26-41. doi:10.1038/s41588-017-0011-x.
http://www.ncbi.nlm.nih.gov/pubmed/29273807?dopt=Abstract
Turcot V, Lu Y, Highland HM, et al. Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity. Nat Genet. 2018;50(1):26-41. doi:10.1038/s41588-017-0011-x.
http://www.ncbi.nlm.nih.gov/pubmed/29273807?dopt=Abstract
Turcot V, Lu Y, Highland HM, et al. Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity. Nat Genet. 2018;50(1):26-41. doi:10.1038/s41588-017-0011-x.
http://www.ncbi.nlm.nih.gov/pubmed/29273807?dopt=Abstract
Turcot V, Lu Y, Highland HM, et al. Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity. Nat Genet. 2018;50(1):26-41. doi:10.1038/s41588-017-0011-x.
http://www.ncbi.nlm.nih.gov/pubmed/29273807?dopt=Abstract
Turcot V, Lu Y, Highland HM, et al. Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity. Nat Genet. 2018;50(1):26-41. doi:10.1038/s41588-017-0011-x.
http://www.ncbi.nlm.nih.gov/pubmed/29273807?dopt=Abstract
Chen C, Zissimopoulos JM. Racial and ethnic differences in trends in dementia prevalence and risk factors in the United States. Alzheimer's & Dementia (N Y). 2018;4:510-520. doi:10.1016/j.trci.2018.08.009.
http://www.ncbi.nlm.nih.gov/pubmed/30364652?dopt=Abstract
Zuniga KE, Bishop NJ. Recent cancer treatment and memory decline in older adults: An analysis of the 2002–2012 Health and Retirement Study. Journal of Geriatric Oncology. 2018;9(3):186-193. doi:10.1016/j.jgo.2017.10.004.
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.
Marker DA, Mardon R, Jenkins F, et al. State-level estimation of diabetes and prediabetes prevalence: Combining national and local survey data and clinical data. Statistics in Medicine. 2018;37(27):3975-3990. doi:10.1002/sim.7848.
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.
Zahodne LB, A Kraal Z, Zaheed AB, Sol K. Subjective Social Status Predicts Late-Life Memory Trajectories through Both Mental and Physical Health Pathways. Gerontology. 2018;64:466-474. doi:10.1159/000487304.
Zahodne LB, A Kraal Z, Zaheed AB, Sol K. Subjective Social Status Predicts Late-Life Memory Trajectories through Both Mental and Physical Health Pathways. Gerontology. 2018;64:466-474. doi:10.1159/000487304.
Zhao B. Too poor to retire? Housing prices and retirement. Review of Economic Dynamics. 2018;27:27-47. doi:10.1016/j.red.2017.11.002.
Raykov T, Zajacova A, Gorelick PB, Marcoulides GA. Using Latent Variable Modeling for Discrete Time Survival Analysis: Examining the Links of Depression to Mortality. Structural Equation Modeling: A Multidisciplinary Journal. 2018;25(2):287-293. doi:10.1080/10705511.2017.1364969.