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Modeling Disability Trajectories and Mortality of the Oldest-Old in China

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Demography

Abstract

This article uses a group-based modeling approach to jointly estimate disability and mortality trajectories over time based on data from the population aged 80 and older in China, and explores relations of demographic, socioeconomic, and early-life characteristics to membership in gender-specific trajectory groups. A three-group model best fits the data for both males and females. For most groups, predicted numbers of limitations in activities of daily living (ADLs) increase with age, but the pace is gradual in some cases and rapid in others. For each gender, the estimated mortality probability trajectories for the three groups follow a hierarchy that is related to the predicted ADL counts at age 80. Only a few characteristics predict trajectory-group membership. Prior nonagricultural occupation is associated with less favorable disability trajectories for both genders. For females, rural residence, a greater number of children ever born, and having a father who did not work in agriculture are associated with more favorable trajectories. For a small group of males who received education, disability is moderate but changes little with age. Findings may reflect heterogeneity of survival among the least advantaged, as well as a possible expansion of morbidity among a small advantaged group.

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Acknowledgments

The current research was assisted by a grant from the National Institutes of Health–National Institute on Aging, Grant No. 1R21 AG036938-01, “Modeling Disability Trajectories in Rapidly Aging Population.” The authors thank Douglas A. Wolf for his thoughtful comments on an earlier version of this article, Danan Gu for providing insight into the CLHLS data set, and two anonymous reviewers. An earlier version of this article was presented at the annual meeting of the Population Association of America, Detroit, Michigan, April 30–May 2, 2009.

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Authors and Affiliations

  1. Department of Social and Behavioral Sciences, University of California San Francisco, 3333 California Street, San Francisco, CA, 94118, USA

    Zachary Zimmer

  2. RAND Corporation, Arlington, VA, USA

    Linda G. Martin

  3. Heinz College, Carnegie Mellon University, Pittsburgh, PA, USA

    Daniel S. Nagin

  4. Behavioral Genetics Research Program, University of Pittsburgh, Pittsburgh, PA, USA

    Bobby L. Jones

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  1. Zachary Zimmer
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Correspondence to Zachary Zimmer.

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Zimmer, Z., Martin, L.G., Nagin, D.S. et al. Modeling Disability Trajectories and Mortality of the Oldest-Old in China. Demography 49, 291–314 (2012). https://doi.org/10.1007/s13524-011-0075-7

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  • DOI: https://doi.org/10.1007/s13524-011-0075-7

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