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Understanding the Disability Dynamics of Youth: Health Condition and Limitation Changes for Youth and Their Influence on Longitudinal Survey Attrition

Abstract

Disability status—experiencing a functional limitation caused by a health condition—is dynamic throughout the life cycle, even during adolescence and young adulthood. We use data from the 1997 cohort of the National Longitudinal Survey of Youth to better understand these dynamics, examining how health condition and limitation statuses evolve during adolescence and young adulthood as well as how changes in these characteristics are related to survey nonresponse and attrition. Health condition and limitation dynamics are evident in our data: the proportion of sample members who reported having a limitation in their activities for any interview increased from approximately 12 % during the initial interview (when sample members were 12 to 17 years old) to almost 25 % 13 years later. Multivariate analyses revealed that women are more likely than men to report changes in health condition or limitation status. Those with mild limitations were relatively less likely than those without limitations or with severe limitations to experience changes in limitation status. Somewhat surprisingly, a survival analysis of survey participation outcomes found limited correlation among health conditions, limitations, and either missing a survey interview for the first time or permanently leaving the survey sample.

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Notes

  1. 1.

    The weights used in the study are either included in the NLSY97 data or constructed using a program obtained from the Bureau of Labor Statistics (BLS). The NLSY97 includes the weights that make the entire NLSY97 sample nationally representative. However, for our analyses that involve subsamples of NLSY97 respondents, we must construct custom weights. The program from the BLS can create weights that make any subsample of NLSY97 respondents nationally representative.

  2. 2.

    A key assumption of a proportional hazard model is that when an explanatory variable’s value changes, the hazard function moves relative to the baseline hazard—an assumption that is testable (Grambsch and Therneau 1994). Results (not shown) revealed that the proportional hazard assumption was not rejected for the attrition analysis but was rejected for the first missed interview analysis. We therefore also estimated the first missed interview survival model assuming an underlying distribution for the hazard function. Using the Akaike information criterion to compare model results across distributional assumptions, we found that the Gompertz survival distribution fit best. However, the results from the Gompertz survival model did not differ qualitatively from the proportional hazard model results. Hence, to minimize the number of models we need to describe in this article, we present only the proportional hazard model results for the first missed interview analysis.

  3. 3.

    For a diagnostic test, in all regression analyses, we assessed the colinearity of the variables of interest using the variance inflation factor (VIF). We did not find a VIF large enough to warrant a concern of multicolinearity.

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Acknowledgments

The authors appreciate the assistance of Nora Paxton for programming support, Jody Schimmel Hyde for helpful comments on the analysis, and Jane Nelson for production support. Funding for this study was provided by the Research and Training Center on Disability Statistics and Demographics (StatsRRTC) at the University of New Hampshire, which is funded by the U.S. Department of Education, National Institute for Disability and Rehabilitation Research (NIDRR) (Grant No. H133B100015). The contents do not necessarily represent the policy of the U.S. Department of Education and you should not assume endorsement by the federal government (Edgar, 75.620 (b)).

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Correspondence to David R. Mann.

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Mann, D.R., Honeycutt, T. Understanding the Disability Dynamics of Youth: Health Condition and Limitation Changes for Youth and Their Influence on Longitudinal Survey Attrition. Demography 53, 749–776 (2016). https://doi.org/10.1007/s13524-016-0469-7

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Keywords

  • Youth
  • Transition to adulthood
  • Disability changes
  • Longitudinal surveys
  • Survey attrition