HRS Bibliography

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Lee J, Phillips DF, Wilkens J. Gateway to Global Aging Data: Resources for Cross-National Comparisons of Family, Social Environment, and Healthy Aging. The Journals of Gerontology: Series B . 2021;76(Supplement_1):S5-S16. doi:10.1093/geronb/gbab050.
Garcia MA, Tarraf W, Reyes AM, Chiu C-T. Gender, Age of Migration, and Cognitive Life Expectancies among Older Latinos: Evidence from the Health and Retirement Study. The Journals of Gerontology, Series B . 2022;77(12):e226-e233. doi:10.1093/geronb/gbac133.
Geng J, Calasanti TM. Gender and the Subjective Well-Being of Older Widows and Widowers. The International Journal of Aging and Human Development. 2023. doi:10.1177/00914150221092990.
Glauber R. Gender Differences in Spousal Care Across the Later Life Course. Res Aging. 2017;39(8):934-959. doi:10.1177/0164027516644503.
http://www.ncbi.nlm.nih.gov/pubmed/27193046?dopt=Abstract
Gu R, Peng C, Zhang W. The Gender Gap in Household Bargaining Power: A Portfolio-Choice Approach. 2021. doi:http://dx.doi.org/10.2139/ssrn.3814200.
Gu R, Peng C, Zhang W. The Gender Gap in Household Bargaining Power: A Revealed-Preference Approach. Paris, France; 2022.
Stites SD, Gurian A, Coykendall C, et al. Gender of study partners and research participants associated with differences in study partner ratings of cognition and activity level. J Gerontol B Psychol Sci Soc Sci. 2023. doi:10.1093/geronb/gbad026.
Glauber R, Day MD. Gender, Spousal Caregiving, and Depression: Does Paid Work Matter?. Journal of Marriage and Family. 2018;80(2):537-554. doi:10.1111/jomf.2018.80.issue-210.1111/jomf.12446.
Zhao W, Yasutake K, August C, et al. Gene-by-Psychosocial Factor Interactions Influence Diastolic Blood Pressure in European and African Ancestry Populations: Meta-Analysis of Four Cohort Studies. Int J Environ Res Public Health. 2017;14(12). doi:10.3390/ijerph14121596.
http://www.ncbi.nlm.nih.gov/pubmed/29258278?dopt=Abstract
Zhao W, Yasutake K, August C, et al. Gene-by-Psychosocial Factor Interactions Influence Diastolic Blood Pressure in European and African Ancestry Populations: Meta-Analysis of Four Cohort Studies. Int J Environ Res Public Health. 2017;14(12). doi:10.3390/ijerph14121596.
http://www.ncbi.nlm.nih.gov/pubmed/29258278?dopt=Abstract
Fuentes Lde Las, Sung YJu, Noordam R, et al. Gene-educational attainment interactions in a multi-ancestry genome-wide meta-analysis identify novel blood pressure loci. Mol Psychiatry. 2021;26(6):2111-2125. doi:10.1038/s41380-020-0719-3.
Fuentes Lde Las, Sung YJu, Noordam R, et al. Gene-educational attainment interactions in a multi-ancestry genome-wide meta-analysis identify novel blood pressure loci. Mol Psychiatry. 2021;26(6):2111-2125. doi:10.1038/s41380-020-0719-3.
Fuentes Lde Las, Sung YJu, Noordam R, et al. Gene-educational attainment interactions in a multi-ancestry genome-wide meta-analysis identify novel blood pressure loci. Mol Psychiatry. 2021;26(6):2111-2125. doi:10.1038/s41380-020-0719-3.
Fuentes Lde Las, Sung YJu, Noordam R, et al. Gene-educational attainment interactions in a multi-ancestry genome-wide meta-analysis identify novel blood pressure loci. Mol Psychiatry. 2021;26(6):2111-2125. doi:10.1038/s41380-020-0719-3.
Fuentes Lde Las, Sung YJu, Noordam R, et al. Gene-educational attainment interactions in a multi-ancestry genome-wide meta-analysis identify novel blood pressure loci. Mol Psychiatry. 2021;26(6):2111-2125. doi:10.1038/s41380-020-0719-3.
Fuentes Lde Las, Sung YJu, Noordam R, et al. Gene-educational attainment interactions in a multi-ancestry genome-wide meta-analysis identify novel blood pressure loci. Mol Psychiatry. 2021;26(6):2111-2125. doi:10.1038/s41380-020-0719-3.
Fuentes Lde Las, Sung YJu, Noordam R, et al. Gene-educational attainment interactions in a multi-ancestry genome-wide meta-analysis identify novel blood pressure loci. Mol Psychiatry. 2021;26(6):2111-2125. doi:10.1038/s41380-020-0719-3.
Fuentes Lde Las, Sung YJu, Noordam R, et al. Gene-educational attainment interactions in a multi-ancestry genome-wide meta-analysis identify novel blood pressure loci. Mol Psychiatry. 2021;26(6):2111-2125. doi:10.1038/s41380-020-0719-3.
Fuentes Lde Las, Sung YJu, Noordam R, et al. Gene-educational attainment interactions in a multi-ancestry genome-wide meta-analysis identify novel blood pressure loci. Mol Psychiatry. 2021;26(6):2111-2125. doi:10.1038/s41380-020-0719-3.
Fuentes Lde Las, Sung YJu, Noordam R, et al. Gene-educational attainment interactions in a multi-ancestry genome-wide meta-analysis identify novel blood pressure loci. Mol Psychiatry. 2021;26(6):2111-2125. doi:10.1038/s41380-020-0719-3.
Fuentes Lde Las, Sung YJu, Noordam R, et al. Gene-educational attainment interactions in a multi-ancestry genome-wide meta-analysis identify novel blood pressure loci. Mol Psychiatry. 2021;26(6):2111-2125. doi:10.1038/s41380-020-0719-3.
Fuentes Lde Las, Sung YJu, Noordam R, et al. Gene-educational attainment interactions in a multi-ancestry genome-wide meta-analysis identify novel blood pressure loci. Mol Psychiatry. 2021;26(6):2111-2125. doi:10.1038/s41380-020-0719-3.
Lu AT, Hannon E, Levine ME, et al. Genetic architecture of epigenetic and neuronal ageing rates in human brain regions. Nature Communications. 2017;8. doi:10.1038/ncomms15353.
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
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