Family structure and young adult health outcomes

Abstract

Previous research finds adverse effects of nontraditional family structures on cognitive and educational outcomes, but less is known about potential impacts on health. We use the National Longitudinal Study of Adolescent Health to examine two health statuses (self-reported overall health and depression) and one health behavior (smoking), estimating both static logit models of point-in-time health and discrete-time hazard models of health transitions. Overall, we find adverse associations between nontraditional family structures and health statuses and behavior. There are long-lasting associations of family structure with outcomes well into adulthood, not all of which are evident in adolescence. Dynamic estimates often inform but also provide new information not seen in the static model. “Unpacking” the family structure variables by period of childhood provides insight into how the timing of family break-ups affects the life trajectories of health and health behavior. Our findings differ remarkably by gender. Girls’ health appears more sensitive to family structure than boys’. In combination with prior findings in the literature, our findings intriguingly suggest that family break-ups and changes affect boys mostly through cognitive, educational, and emotional channels, while girls are most affected in their health and health behaviors. A major methodological contribution of this study is better measurement of family structure. We find that many adverse associations are masked by cruder measures in typical use.

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Notes

  1. 1.

    Conway and Li (2012) also note that even families labeled “single mother” may represent a wide variety of experiences.

  2. 2.

    For brevity, we abstract from investments made by step-parents, which could also be included as arguments. We assume there is a single child, foregoing modeling further parental trade-offs.

  3. 3.

    Children whose biological father lived with the mother at Wave I are assumed to have always lived in a traditional two-parent household, misclassifying biological fathers who left and returned to the household by Wave I.

  4. 4.

    Add Health defines a marriage-like relationship as “living with someone as if you were married to him…when you are not.”

  5. 5.

    3075 individuals were dropped because they were under 15 and 824 because they were over 18. We also drop adolescents whose mothers’ marital or marriage-like partners died, who spent 6 or more months away from the biological mother by Wave I, who did not report living with his/her biological mother, or who did not have a sampling weight (361, 641, 98, and 561 adolescents, respectively).

  6. 6.

    Censoring is minimal.

  7. 7.

    Father could be misclassified as “never present” when mothers do not report ever being married (or in a marriage-like relationship); biological fathers marry the mother subsequent to the child’s birth; or biological fathers in social relationships do not marry the mother.

  8. 8.

    For ages 11–15, we combine ‘no other males’ together with ‘other males present’ due to a small number of the latter.

  9. 9.

    Missing income is imputed to approximately 10 % of the sample using mother’s marital status, race, ethnicity, occupation, and educational attainment.

  10. 10.

    Missing birth weights are imputed to 5 % of the sample by assigning the sample mean by gender.

  11. 11.

    Radloff (1977) describes the CES-D scale. Add Health contains a modified version. To maintain internal consistency, we use the five questions asked in all waves. Cutoff scores in Waves I and II follow Roberts et al. (1991) and cutoff scores in Waves III and IV follow Irwin et al (1999).

  12. 12.

    When Eq. (4) takes a recursive form, the change in health between any two waves is some function of the intervening investments.

  13. 13.

    Findings did not differ substantively with and without the polynomial in the specification.

  14. 14.

    Add Health surveys the adolescent’s smoking history at Wave I, so it is possible to determine if an individual both started and quit prior to Wave I. Therefore, the quitting analysis includes transitions occurring before Wave I.

  15. 15.

    We are grateful to an anonymous referee for pointing this out.

  16. 16.

    We are grateful to an anonymous referee for pointing this out.

  17. 17.

    Statistics for the full set of variables for female and male respondents are available in Tables A1 and A2, respectively, in the electronic appendix.

  18. 18.

    Consistent with Akashi-Ronquest (2009), the entry of a stepfather, controlling for income, does not offset the adverse influence of biological father departure. We are grateful to an anonymous referee for pointing this out.

  19. 19.

    Results of our robustness checks are available upon request.

  20. 20.

    Health insurance coverage of adolescents in the sample is high, at 90 %, and there is a reduction of only 2 percentage points in coverage if the father ever left.

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Acknowledgments

The authors would like to thank Craig Gundersen and Paul McNamara for helpful comments and suggestions. Carl Nelson’s assistance with data manipulation and retrieval was invaluable. All responsibility for errors rests with the authors. This research uses data from Add Health, a program project directed by Kathleen Mullan Harris and designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill, and funded by Grant P01-HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, with cooperative funding from 23 other federal agencies and foundations. Special acknowledgment is due Ronald R. Rindfuss and Barbara Entwisle for assistance in the original design. Information on how to obtain the Add Health data files is available on the Add Health website (http://www.cpc.unc.edu/addhealth). No direct support was received from Grant P01-HD31921 for this analysis.

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Correspondence to Alexander N. Slade.

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Slade, A.N., Beller, A.H. & Powers, E.T. Family structure and young adult health outcomes. Rev Econ Household 15, 175–197 (2017). https://doi.org/10.1007/s11150-015-9313-x

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Keywords

  • Family structure
  • Adolescent health
  • Discrete-time hazard models
  • National Longitudinal Study of Adolescent Health

JEL Classification

  • I12
  • J12