HRS Bibliography

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2005

Fisher GG, Faul J, Weir DR, Wallace RB. Documentation of Chronic Disease Measures in the Health and Retirement Study. Ann Arbor, Michigan: Institute for Social Research, University of Michigan; 2005.PDF icon Download PDF (460.3 KB)

2007

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

2011

Weir DR, Faul J, Langa KM. Proxy interviews and bias in the distribution of cognitive abilities due to non-response in longitudinal studies: a comparison of HRS and ELSA. Longit Life Course Stud. 2011;2(2):170-184. doi:10.14301/llcs.v2i2.116.
http://www.ncbi.nlm.nih.gov/pubmed/25360159?dopt=Abstract

2013

Crimmins EM, Faul J, Kim JKi, et al. Documentation of Biomarkers in the 2006 and 2008 Health and Retirement Study. Ann Arbor, Michigan: Institute for Social Research, University of Michigan; 2013.PDF icon Download PDF (364.89 KB)
Franceschini N, Fox E, Zhang Z, et al. Genome-wide association analysis of blood-pressure traits in African-ancestry individuals reveals common associated genes in African and non-African populations. Am J Hum Genet. 2013;93(3):545-54. doi:10.1016/j.ajhg.2013.07.010.
http://www.ncbi.nlm.nih.gov/pubmed/23972371?dopt=Abstract
Rietveld CA, Medland SE, Derringer J, et al. GWAS of 126,559 individuals identifies genetic variants associated with educational attainment. Science. 2013;340(6139):1467-71. doi:10.1126/science.1235488.
http://www.ncbi.nlm.nih.gov/pubmed/23722424?dopt=Abstract

2014

Sonnega A, Faul J, Ofstedal MBeth, Langa KM, Phillips JWR, Weir DR. Cohort Profile: the Health and Retirement Study (HRS). Int J Epidemiol. 2014;43(2):576-85. doi:10.1093/ije/dyu067.
http://www.ncbi.nlm.nih.gov/pubmed/24671021?dopt=Abstract
PDF icon Download PDF (288.38 KB)
Bihlmeyer NA, Brody JA, Smith AVernon, et al. Genetic diversity is a predictor of mortality in humans. BMC Genet. 2014;15:159. doi:10.1186/s12863-014-0159-7.
http://www.ncbi.nlm.nih.gov/pubmed/25543667?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
Crimmins EM, Kim JKi, McCreath H, Faul J, Weir DR, Seeman T. Validation of blood-based assays using dried blood spots for use in large population studies. Biodemography Soc Biol. 2014;60(1):38-48. doi:10.1080/19485565.2014.901885.
http://www.ncbi.nlm.nih.gov/pubmed/24784986?dopt=Abstract

2015

Nead KT, Li A, Wehner MR, et al. Contribution of common non-synonymous variants in PCSK1 to body mass index variation and risk of obesity: a systematic review and meta-analysis with evidence from up to 331 175 individuals. Human Molecular Genetics. 2015;24(12):3582-3594. doi:10.1093/hmg/ddv097.
Joshi PK, Esko T, Mattsson H, et al. Directional dominance on stature and cognition in diverse human populations. Nature. 2015;523(7561):459-62. doi:10.1038/nature14618.
http://www.ncbi.nlm.nih.gov/pubmed/26131930?dopt=Abstract
Crimmins EM, Faul J, Kim JKi, Weir DR. Documentation of Biomarkers in the 2010 and 2012 Health and Retirement Study. Ann Arbor, Michigan: Survey Research Center, University of Michigan; 2015:15.PDF icon Download PDF (198.27 KB)
Locke AE, Kahali B, Berndt SI, et al. Genetic studies of body mass index yield new insights for obesity biology. Nature. 2015;518(7538):197-206. doi:10.1038/nature14177.
http://www.ncbi.nlm.nih.gov/pubmed/25673413?dopt=Abstract
Broer L, Buchman AS, Deelen J, et al. GWAS of longevity in CHARGE consortium confirms APOE and FOXO3 candidacy. J Gerontol A Biol Sci Med Sci. 2015;70(1):110-8. doi:10.1093/gerona/glu166.
http://www.ncbi.nlm.nih.gov/pubmed/25199915?dopt=Abstract
Day FR, Ruth KS, Thompson DJ, et al. Large-scale genomic analyses link reproductive aging to hypothalamic signaling, breast cancer susceptibility and BRCA1-mediated DNA repair. Nat Genet. 2015;47(11):1294-303. doi:10.1038/ng.3412.
http://www.ncbi.nlm.nih.gov/pubmed/26414677?dopt=Abstract

2016

Faul J, Mitchell C, Zhao W. Estimating Telomere Length Heritability in an Unrelated Sample of Adults: Is Heritability of Telomere Length Modified by Life Course Socioeconomic Status?. Biodemography and Social Biology. 2016;62(1):73-86. doi:10.1080/19485565.2015.1120645.
Pattaro C, Teumer A, Gorski M, et al. Genetic associations at 53 loci highlight cell types and biological pathways relevant for kidney function. Nat Commun. 2016;7:10023. doi:10.1038/ncomms10023.
http://www.ncbi.nlm.nih.gov/pubmed/26831199?dopt=Abstract
Okbay A, Baselmans BML, De Neve J-E, et al. Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses. Nat Genet. 2016;48(6):624-33. doi:10.1038/ng.3552.
http://www.ncbi.nlm.nih.gov/pubmed/27089181?dopt=Abstract
Barban N, Jansen R, de Vlaming R, et al. Genome-wide analysis identifies 12 loci influencing human reproductive behavior. Nat Genet. 2016;48(12):1462-1472. doi:10.1038/ng.3698.
http://www.ncbi.nlm.nih.gov/pubmed/27798627?dopt=Abstract
Dunn EC, Wiste A, Radmanesh F, et al. GENOME-WIDE ASSOCIATION STUDY (GWAS) AND GENOME-WIDE BY ENVIRONMENT INTERACTION STUDY (GWEIS) OF DEPRESSIVE SYMPTOMS IN AFRICAN AMERICAN AND HISPANIC/LATINA WOMEN. Depress Anxiety. 2016;33(4):265-80. doi:10.1002/da.22484.
http://www.ncbi.nlm.nih.gov/pubmed/27038408?dopt=Abstract
Okbay A, Beauchamp JP, Fontana MAlan, et al. Genome-wide association study identifies 74 loci associated with educational attainment. Nature. 2016;533(7604):539-42. doi:10.1038/nature17671.
http://www.ncbi.nlm.nih.gov/pubmed/27225129?dopt=Abstract
Matteini AM, Tanaka T, Karasik D, et al. GWAS analysis of handgrip and lower body strength in older adults in the CHARGE consortium. Aging Cell. 2016;15(5):792-800. doi:10.1111/acel.12468.
http://www.ncbi.nlm.nih.gov/pubmed/27325353?dopt=Abstract
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.