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What Matters Most for Predicting Survival? A Multinational Population-Based Cohort Study

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  • Noreen Goldman
  • Dana A Glei
  • Maxine Weinstein

Abstract

Despite myriad efforts among social scientists, epidemiologists, and clinicians to identify variables with strong linkages to mortality, few researchers have evaluated statistically the relative strength of a comprehensive set of predictors of survival. Here, we determine the strongest predictors of five-year mortality in four national, prospective studies of older adults. We analyze nationally representative surveys of older adults in four countries with similar levels of life expectancy: England (n = 6113, ages 52+), the US (n = 2023, ages 50+), Costa Rica (n = 2694, ages 60+), and Taiwan (n = 1032, ages 53+). Each survey includes a broad set of demographic, social, health, and biological variables that have been shown previously to predict mortality. We rank 57 predictors, 25 of which are available in all four countries, net of age and sex. We use the area under the receiver operating characteristic curve and assess robustness with additional discrimination measures. We demonstrate consistent findings across four countries with different cultural traditions, levels of economic development, and epidemiological transitions. Self-reported measures of instrumental activities of daily living limitations, mobility limitations, and overall self-assessed health are among the top predictors in all four samples. C-reactive protein, additional inflammatory markers, homocysteine, serum albumin, three performance assessments (gait speed, grip strength, and chair stands), and exercise frequency also discriminate well between decedents and survivors when these measures are available. We identify several promising candidates that could improve mortality prediction for both population-based and clinical populations. Better prognostic tools are likely to provide researchers with new insights into the behavioral and biological pathways that underlie social stratification in health and may allow physicians to have more informed discussions with patients about end-of-life treatment and priorities.

Suggested Citation

  • Noreen Goldman & Dana A Glei & Maxine Weinstein, 2016. "What Matters Most for Predicting Survival? A Multinational Population-Based Cohort Study," PLOS ONE, Public Library of Science, vol. 11(7), pages 1-11, July.
  • Handle: RePEc:plo:pone00:0159273
    DOI: 10.1371/journal.pone.0159273
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    References listed on IDEAS

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    1. John P A Ioannidis, 2005. "Why Most Published Research Findings Are False," PLOS Medicine, Public Library of Science, vol. 2(8), pages 1-1, August.
    2. Eileen Crimmins & Jung Kim & Sarinnapha Vasunilashorn, 2010. "Biodemography: New approaches to understanding trendsand differences in population health and mortality," Demography, Springer;Population Association of America (PAA), vol. 47(1), pages 41-64, March.
    3. Michael D. Hurd & Daniel McFadden & Angela Merrill, 2001. "Predictors of Mortality among the Elderly," NBER Chapters, in: Themes in the Economics of Aging, pages 171-198, National Bureau of Economic Research, Inc.
    4. Pantell, M. & Rehkopf, D. & Jutte, D. & Syme, S.L. & Balmes, J. & Adler, N., 2013. "Social isolation: A predictor of mortality comparable to traditional clinical risk factors," American Journal of Public Health, American Public Health Association, vol. 103(11), pages 2056-2062.
    5. David A. Wise, 2001. "Themes in the Economics of Aging," NBER Books, National Bureau of Economic Research, Inc, number wise01-1.
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    Cited by:

    1. Antonio D. Lázaro-Sánchez & Asunción Juárez Marroquí & Jose Antonio Quesada Rico & Domingo Orozco-Beltrán, 2022. "Risk Factors for Cancer Mortality in Spain: Population-Based Cohort Study," IJERPH, MDPI, vol. 19(16), pages 1-11, August.
    2. Glei, Dana A. & Weinstein, Maxine, 2023. "Economic distress, obesity, and the rise in pain," Social Science & Medicine, Elsevier, vol. 339(C).
    3. Hiram Beltran-Sanchez & Noreen Goldman & Anne Pebley & Josefina Flores Morales, 2020. "Calloused hands, shorter life? Occupation and older-age survival in Mexico," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 42(32), pages 875-900.
    4. Constant, Amelie F. & Milewski, Nadja, 2021. "Self-selection in physical and mental health among older intra-European migrants," The Journal of the Economics of Ageing, Elsevier, vol. 19(C).
    5. Andrasfay, Theresa & Goldman, Noreen, 2020. "Physical functioning and survival: Is the link weaker among Latino and black older adults?," Social Science & Medicine, Elsevier, vol. 255(C).

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