Christine T Cigolle1,2,3, Corey L Nagel4,5, Caroline S Blaum2,6, Jersey Liang7, Ana R Quiñones5,8. 1. Department of Family Medicine, University of Michigan, Ann Arbor. 2. Department of Internal Medicine, University of Michigan, Ann Arbor. 3. VA Ann Arbor Healthcare System, Geriatric Research, Education and Clinical Center, Michigan. 4. School of Nursing, Oregon Health and Science University, Portland. 5. Department of Public Health and Preventive Medicine, Oregon Health and Science University, Portland. 6. Department of Medicine, New York University Langone Medical Center, University of Michigan, Ann Arbor. 7. School of Public Health, University of Michigan, Ann Arbor. 8. Portland Veterans Affairs Medical Center, Oregon.
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).
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).
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