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The NLSY Kinship Links: Using the NLSY79 and NLSY-Children Data to Conduct Genetically-Informed and Family-Oriented Research

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Abstract

The National Longitudinal Survey of Youth datasets (NLSY79; NLSY-Children/Young Adults; NLSY97) have extensive family pedigree information contained within them. These data sources are based on probability sampling, a longitudinal design, and a cross-generational and within-family data structure, with hundreds of phenotypes relevant to behavior genetic (BG) researchers, as well as to other developmental and family researchers. These datasets provide a unique and powerful source of information for BG researchers. But much of the information required for biometrical modeling has been hidden, and has required substantial programming effort to uncover—until recently. Our research team has spent over 20 years developing kinship links to genetically inform biometrical modeling. In the most recent release of kinship links from two of the NLSY datasets, the direct kinship indicators included in the 2006 surveys allowed successful and unambiguous linking of over 94 % of the potential pairs. In this paper, we provide details for research teams interested in using the NLSY data portfolio to conduct BG (and other family-oriented) research.

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Notes

  1. David Rowe, Rodgers’ original collaborator on the kinship linking projects, passed away in February, 2003.

  2. In September, 1996, Baydar and Rodgers/Rowe compared kinship links, and found that their independent efforts produced highly similar linking results, a rate of agreement of 94.3 %.

  3. Rodgers et al. (2008) presented the Mother–Daughter–Aunt–Niece (MDAN) design, in which correlations from mother to daughter pairs are compared biometrically to those from aunt to niece pairs. Mothers and aunts are often either the same person (i.e., a mother of one or more NLSYC daughters also was the aunt of one or more NLSYC nieces), or are related as sisters or half-sisters, providing substantial control over unobserved heterogeneity due to family background.

  4. An interesting challenge involves verbal identification of certain cross-generational pairs, because of implied gender. We specify Parent–Child kinship links simply as “ParentChild” links. But to separately identify aunt–niece, aunt–nephew, uncle–niece, and uncle–nephew files would require gender identification of members of the kinship links (creating inconsistency compared to other links such as full sibling, half sibling, twin, and parent–children, identified without gender specification). We have searched the literature/internet for resolutions of this problem; an interesting solution refers to non-gendered Nieces or Nephews as “Niblings,” the counterpart to non-gendered “Siblings.” We created a new name for non-gendered Uncle/Aunts of “Niblings;” we use “AUncle” for this category. Thus, an Uncle/Aunt in Gen1 paired with Niblings in Gen2 are designated as “AUncleNibling” pairs within our files.

References

  • Baydar N, Greek A (2001) Analysis of data from related individuals. Working paper, Battell Centers for Public Health Research and Evaluation, Seattle

  • Beaver KM, Connolly EJ, Schwartz JA, Al-Ghamdi AS, Kobeisy AN (2013) Genetic and environmental contributions to stability and change in levels of self-control. J Crim Justice 41:300–308

    Article  Google Scholar 

  • Chase-Lansdale PL, Mott FL, Brooks-Gunn J, Phillips DA (1991) Children of the National Longitudinal Survey of Youth: a unique research opportunity. Dev Psychol 27:918–931

    Article  Google Scholar 

  • Cheung AK, Harden KP, Tucker-Drob EM (2014) Gene x Environment interactions in early externalizing behaviors: parental emotional support and socioeconomic context as moderators of genetic influences? Behav Genet 44(5):468–486

    Article  PubMed  Google Scholar 

  • Cleveland HH, Wiebe RP, van den Oord EJCG, Rowe DC (2000) Behavior problems among children from different family structures: the influence of genetic self-selection. Child Dev 71:733–751

    Article  PubMed  Google Scholar 

  • Connolly EJ, Beaver KM (2014) Examining the genetic and environmental influences on self-control and delinquency: results from a genetically informative analysis of sibling pairs. J Interpers Violence 29:707–735

    Article  PubMed  Google Scholar 

  • D’Onofrio BM, Turkheimer E, Emery RE, Maes HH, Eaves LJ (2007) A children of twins study of parental divorce and offspring psychopathology. J Child Psychol Psychiatry 48:667–675

    Article  PubMed  PubMed Central  Google Scholar 

  • D’Onofrio BM, Van Hulle CA, Waldman ID, Rodgers JL, Harden KP, Rathouz PJ, Lahey BB (2008) Smoking during pregnancy and offspring externalizing problems: an exploration of genetic and environmental confounds. Dev Psychopathol 20:139–164

    PubMed  PubMed Central  Google Scholar 

  • D’Onofrio BM, Goodnight JA, Van Hulle CA, Waldman ID, Rodgers JL, Rathouz PJ, Lahey BB (2009) Maternal age at childbirth and offspring disruptive behavior: testing the causal hypothesis. J Child Psychol Psychiatry 50:1018–1028

    Article  PubMed  PubMed Central  Google Scholar 

  • D’Onofrio BM, Rickert ME, Langstrom N, Donahue KL, Coyne CA, Larsson H, Ellingson JM, Van Hulle CA, Iliadou AN, Rathouz PJ, Lahey BB, Lichtenstein P (2012) Familial confounding of the association between maternal smoking during pregnancy and offspring substance use and problems: converging evidence across samples and measures. Arch Gen Psychiatry 69:1140–1150

    Article  PubMed  PubMed Central  Google Scholar 

  • DeFries JC, Fulker D (1985) Multiple regression analysis of twin data. Behav Genet 15:467–473

    Article  PubMed  Google Scholar 

  • Doughty D, Rodgers JL (2000) Behavior genetic modeling of menarche in U.S. females. In: Rodgers JL, Rowe DC, Miller WB (eds) Genetic influences on fertility and sexuality. Kluwer Academic Press, Boston

    Google Scholar 

  • Eaves L, Heath A, Martin N, Maes H, Neale M, Kendler K, Kirk K, Corey L (1999) Comparing the biological and cultural inheritance of personality and social attitudes in the Virginia 30,000 study of twins and their relatives. Twin Res 2:62–80

    Article  PubMed  Google Scholar 

  • Fisher RA (1918) The correlation between relatives on the supposition of Mendelian inheritance. Philos Trans R Soc Edinburgh 52:399–433

    Article  Google Scholar 

  • Goodnight JA, Lahey BB, Van Hulle CA, Rodgers JL, Rathouz PJ, Waldman ID, D’Onofrio BM (2012) A quasi-experimental analysis of the influence of neighborhood disadvantage on child and adolescent conduct problems. J Abnorm Psychol 121:95–108

    Article  PubMed  PubMed Central  Google Scholar 

  • Goodnight JA, D’Onofrio BM, Cherlin AJ, Emery RE, Van Hulle CA, Lahey BB (2013) Effects of multiple maternal relationship transitions on offspring antisocial behavior in childhood and adolescence: a cousin-comparison analysis. J Abnorm Child Psychol 41:185–198

    Article  PubMed  PubMed Central  Google Scholar 

  • Green DM, Swets JA (1966) Signal detection theory and psychophysics. Wiley, New York

    Google Scholar 

  • Guo G, Wang JM (2002) The mixed or multilevel models for behavior genetic analysis. Behav Genet 32:37–49

    Article  PubMed  Google Scholar 

  • Harris KM, Halpern CT, Smolen A, Haberstick B (2006) The national longitudinal study of adolescent health (Add Health) twin data. Twin Res Hum Genet 9:988–997

    Article  PubMed  Google Scholar 

  • Harris KM, Halpern CT, Haberstick BC, Smolen A (2013) The national longitudinal study of adolescent health (Add Health) sibling pairs data. Twin Res Hum Genet 16:391–398

    Article  PubMed  PubMed Central  Google Scholar 

  • Hart SA, Petrill SA, Kamp Dush CM (2010) Genetic influences on language, reading, and mathematics skills in a national sample: an analysis using the National Longitudinal Survey of Youth. Lang Speech Hear Serv Sch 41:118

    Article  PubMed  PubMed Central  Google Scholar 

  • Jaffee S, Van Hulle C, Rodgers JL (2011) Effects of non-maternal care in the first three years on children’s academic skills and behavioral functioning in childhood and early adolescence: a sibling comparison study. Child Dev 84:1076–1081

    Article  Google Scholar 

  • Johnson W, Turkheimer E, Gottesman I, Bouchard TJ (2010) Beyond heritability: twin studies in behavioral research. Curr Dir Psychol Sci 18:217–220

    Article  PubMed  PubMed Central  Google Scholar 

  • Lahey BB, Van Hulle CA, Rathouz PJ, Rodgers JL, D’Onofrio BM, Waldman ID (2009) Are oppositional-defiant and hyperactive-inattentive symptoms developmental precursors to conduct problems in late childhood?: genetic and environmental links. J Abnorm Child Psychol 37:45–58

    Article  PubMed  PubMed Central  Google Scholar 

  • Lai C-Q (2006) How much of human height is genetic and much is due to nutrition? Scientific American

  • Lynn SK, Barrett LF (2014) “Utilizing” signal detection theory. Psychol Sci 25:1663–1673

    Article  PubMed  PubMed Central  Google Scholar 

  • McArdle JJ, Prescott CA (2005) Mixed-effects variance components models for biometrical family analyses. Behav Genet 35:631–652

    Article  PubMed  Google Scholar 

  • Mendle J, Harden KP, Turkheimer E, Van Hulle CA, D’Onofrio BM, Brooks-Bunn J, Rodgers JL, Emery RE, Lahey BB (2009) Associations between father absence and age of first sexual intercourse. Child Dev 80:1463–1480

    Article  PubMed  PubMed Central  Google Scholar 

  • Miller WB, Bard DE, Pasta DJ, Rodgers JL (2010) Biodemographic modeling of the links between fertility motivation and fertility outcomes in the NLSY79. Demography 47:393–414

    Article  PubMed  PubMed Central  Google Scholar 

  • Mook DG (1983) In defense of external invalidity. Am Psychol 38:379–387

    Article  Google Scholar 

  • Neale MC, Cardon LR (1992) Methodology for genetic studies of twins and families. Springer, New York

    Book  Google Scholar 

  • Neale MC, Hunter MD, Pritikin JN, Zahery M, Brick TR, Kickpatrick RM, Estabrook R, Bates TC, Maes HH, Boker SM (2015) OpenMx 2.0: extended structural equation and statistical modeling. Psychometrika. 10.1007/s11336-014-9435-8

  • Neiss M, Rowe DC, Rodgers JL (2002) Does education mediate the relationship between IQ and age of first birth? A behavior genetic analysis. J Biosoc Sci 34:259–275

    Article  PubMed  Google Scholar 

  • Roberts DF, Billewicz WZ, McGregor IA (1978) Heritability of stature in a West African population. Ann Hum Genet 42:15–24

    Article  PubMed  Google Scholar 

  • Rodgers JL (1996) NLSY Youth linking algorithm. Unpublished manuscript, Department of Psychology, University of Oklahoma

  • Rodgers JL, Kohler H-P (2005) Reformulating and simplifying the DF analysis model. Behav Genet 35:211–217

    Article  Google Scholar 

  • Rodgers JL, Rowe DC, Li C (1994a) Beyond nature versus nurture: DF analysis of nonshared influences on problem behaviors. Dev Psychol 30:374–384

    Article  Google Scholar 

  • Rodgers JL, Rowe DC, May K (1994b) DF analysis of NLSY IQ/achievement data: nonshared environmental influences. Intelligence 19:157–177

    Article  Google Scholar 

  • Rodgers JL, Rowe DC, Buster M (1999) Nature, nurture, and first sexual intercourse in the USA: fitting behavioral genetic models to NLSY kinship data. J Biosoc Sci 31:29–41

    Article  PubMed  Google Scholar 

  • Rodgers JL, Cleveland HH, van den Oord EJCG, Rowe DC (2000) Resolving the debate over birth order, family size, and intelligence. Am Psychol 55:599–612

    Article  PubMed  Google Scholar 

  • Rodgers JL, Buster M, Rowe DC (2001) Genetic and environmental influences on delinquency: DF analysis of NLSY kinship data. J Quant Criminol 17:145–168

    Article  Google Scholar 

  • Rodgers JL, Bard DE, Miller WB (2007) Multivariate Cholesky models of human female fertility patterns in the NLSY. Behav Genet 37:345–361

    Article  PubMed  PubMed Central  Google Scholar 

  • Rodgers JL, Bard DE, Johnson AB, D’Onofrio BM, Miller WB (2008) The cross-generational mother-daughter-aunt-niece design: establishing validity of the MDAN design with NLSY fertility variables. Behav Genet 38:567–578

    Article  PubMed  PubMed Central  Google Scholar 

  • Rodgers JL, Van Hulle C, D’Onofrio BM, Rathouz PJ, Beasley WH, Johnson AB, Waldman ID, Lahey BB (2015) Behavior problems and timing of menarche: a developmental longitudinal biometrical analysis using the NLSY-Children data. Behav Genet 45:51–70

    Article  PubMed  Google Scholar 

  • Rowe DC, Cleveland HH (1996) Academic achievement in African-Americans and Whites: are the developmental processes similar? Intelligence 23:205–228

    Article  Google Scholar 

  • Rowe DC, Vaszonyi AT, Flannery DJ (1995) Ethnic and racial similarity in developmental process: a study of academic achievement. Psychol Sci 6:33–38

    Article  Google Scholar 

  • Salsberry PJ, Reagan PB (2010) Effects of heritability, shared environment and non-shared intrauterine conditions on child and adolescent BMI. Obesity 18(9):1775–1780

    Article  PubMed  Google Scholar 

  • Shadish WR, Cook TD, Campbell DT (2002) Experimental and quasi-experimental designs for generalized causal inference. Houghton Mifflin, Boston

    Google Scholar 

  • Silverntoinen K, Kaprio J, Kahelma E (2000) Genetic and environmental contribgutions to the association etween body height and educational attainment: a study of adult Finnish twins. Behav Genet 30:477–485

    Article  Google Scholar 

  • van den Oord EJCG (2001) Estimating effects of latent and measured genotypes in multilevel models. Stat Methods Med Res 10:393–407

    Article  PubMed  Google Scholar 

  • van den Oord EJCG, Rowe DC (1997) An examination of genotype-environment interactions for academic achievement in an U.S. national longitudinal survey. Intelligence 25:205–228

    Article  Google Scholar 

  • van den Oord EJCG, Rowe DC (1999) A cousin study of associations between family demographic characteristics and children’s intellectual ability. Intelligence 27:251–266

    Article  Google Scholar 

  • Van Hulle CA, Waldman ID, D’Onofrio BM, Rodgers JL, Rathouz PJ, Lahey BB (2009) Developmental structure of genetic influences on antisocial behavior across childhood and adolescence. J Abnorm Psychol 118:711–721

    Article  PubMed  PubMed Central  Google Scholar 

  • Visscher PM (2008) Sizing up human height variation. Nat Genet 40:489–490

    Article  PubMed  Google Scholar 

  • Visscher PM, Medland SE, Ferreira MAR, Morley KI, Zhu G, Cornes BK, Montgomery GW, Martin NG (2006) Assumption-free estimation of heritability from genome-wide identity-by-descent sharing between full siblings. PLoS Genet 2(e41):316–325

    Google Scholar 

  • Wichman A, Rodgers JL, MacCallum RC (2006) A multilevel approach to the relationship between birth order and intelligence. Pers Soc Psychol Bull 32:117–127

    Article  PubMed  Google Scholar 

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Acknowledgments

Three grants from the National Institutes of Health (NICHD) have supported the work described within this paper: in the 1990s, R01-HD21973; in 2003–2007 RO1-HD043265; in 2012–2014, R01-HD065865 (Joseph Lee Rodgers was PI on each grant). The authors express appreciation to the Bureau of Labor Statistics and the National Opinion Research Center for longstanding expertise in conceptualizing, funding, and collecting the NLSY data. Particular appreciation is expressed to many individuals at the Center for Human Resource Research at Ohio State for expert management of the NLSY data, and more specifically for conceptual, statistical, and data management support of past NLSY kinship linking efforts. Those individuals at CHRR include Randy Olsen, Elizabeth Cooksey, Frank Mott, Paula Baker, Steven McClaskie, and Karima Nagy. The co-authors on this paper are those who have contributed to coding or conceptualizing the NLSY kinship links since the original linking projects in the early 1990s; with the exception of van den Oord, who developed his own code for NLSYC kinship links, each co-author has been financially supported on one or more of the NIH grants listed above.

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Correspondence to Joseph Lee Rodgers.

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Edited by Brian D’Onofrio.

David C. Rowe—deceased.

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Rodgers, J.L., Beasley, W.H., Bard, D.E. et al. The NLSY Kinship Links: Using the NLSY79 and NLSY-Children Data to Conduct Genetically-Informed and Family-Oriented Research. Behav Genet 46, 538–551 (2016). https://doi.org/10.1007/s10519-016-9785-3

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