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Inconsistency in the Self-report of Chronic Diseases in Panel Surveys: Developing an Adjudication Method for the Health and Retirement Study

  • Christine T. Cigolle*
  • , Corey L. Nagel
  • , Caroline S. Blaum
  • , Jersey Liang
  • , Ana R. Quiñones
  • *Corresponding author for this work
  • University of Michigan, Ann Arbor
  • Department of Veterans Affairs
  • Oregon Health and Science University
  • New York University
  • Portland VA Medical Center

Research output: Contribution to journal › Review article › peer-review

48 Scopus citations

Abstract

Objectives Chronic disease data from longitudinal health interview surveys are frequently used in epidemiologic studies. These data may be limited by inconsistencies in self-report by respondents across waves. We examined disease inconsistencies in the Health and Retirement Study and investigated a multistep method of adjudication. We hypothesized a greater likelihood of inconsistences among respondents with cognitive impairment, of underrepresented race/ethnic groups, having lower education, or having less income/wealth. Method We analyzed Waves 1995-2010, including adults 51 years and older (N = 24,156). Diseases included hypertension, heart disease, lung disease, diabetes, cancer, stroke, and arthritis. We used questions about the diseases to formulate a multistep adjudication method to resolve inconsistencies across waves. Results Thirty percent had inconsistency in their self-report of diseases across waves, with cognitive impairment, proxy status, age, Hispanic ethnicity, and wealth as key predictors. Arthritis and hypertension had the most frequent inconsistencies; stroke and cancer, the fewest. Using a stepwise method, we adjudicated 60%-75% of inconsistent responses. Discussion Discrepancies in the self-report of diseases across multiple waves of health interview surveys are common. Differences in prevalence between original and adjudicated data may be substantial for some diseases and for some groups, (e.g., the cognitively impaired).

Original languageEnglish
Pages (from-to)901-912
Number of pages12
JournalThe journals of gerontology. Series B, Psychological sciences and social sciences
Volume73
Issue number5
DOIs
StatePublished - 14 06 2018

Bibliographical note

Publisher Copyright:
© Published by Oxford University Press on behalf of The Gerontological Society of America 2016.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Data collection
  • Epidemiologic measurement
  • Population aging

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