Missing data approaches in longitudinal studies of aging: A case example using the National Health and Aging Trends Study

Missing data is a key methodological consideration in longitudinal studies of aging. We described missing data challenges and potential methodological solutions using a case example describing five-year frailty state transitions in a cohort of older adults. We used longitudinal data from the Nationa...

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Published inPloS one Vol. 18; no. 6; p. e0286984
Main Authors Duchesneau, Emilie D, Shmuel, Shahar, Faurot, Keturah R, Musty, Allison, Park, Jihye, Stürmer, Til, Kinlaw, Alan C, Yang, Yang Claire, Lund, Jennifer L
Format Journal Article
LanguageEnglish
Published United States Public Library of Science 08.06.2023
Public Library of Science (PLoS)
Subjects
Aged
Aging
Analysis
Baby boomers
Bias
Biology and Life Sciences
Data collection
Datasets
Engineering and Technology
Epidemiology
Evaluation
Expected values
Frail Elderly
Frailty
Frailty - epidemiology
Gender
Genotype & phenotype
Geriatric Assessment - methods
Gerontology
Government programs
Grip strength
Health services utilization
Humans
Longitudinal Studies
Medical research
Medicare
Medicine and Health Sciences
Medicine, Experimental
Missing data
Mobility
Older people
People and Places
Phenotypes
Physiology
Population
Public health
Research and Analysis Methods
Robustness
Trends
United States
Variables
United States
United States > US
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Summary:Missing data is a key methodological consideration in longitudinal studies of aging. We described missing data challenges and potential methodological solutions using a case example describing five-year frailty state transitions in a cohort of older adults. We used longitudinal data from the National Health and Aging Trends Study, a nationally-representative cohort of Medicare beneficiaries. We assessed the five components of the Fried frailty phenotype and classified frailty based on their number of components (robust: 0, prefrail: 1-2, frail: 3-5). One-, two-, and five-year frailty state transitions were defined as movements between frailty states or death. Missing frailty components were imputed using hot deck imputation. Inverse probability weights were used to account for potentially informative loss-to-follow-up. We conducted scenario analyses to test a range of assumptions related to missing data. Missing data were common for frailty components measured using physical assessments (walking speed, grip strength). At five years, 36% of individuals were lost-to-follow-up, differentially with respect to baseline frailty status. Assumptions for missing data mechanisms impacted inference regarding individuals improving or worsening in frailty. Missing data and loss-to-follow-up are common in longitudinal studies of aging. Robust epidemiologic methods can improve the rigor and interpretability of aging-related research.
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Competing Interests: Emilie Duchesneau has previously received salary support from AbbVie through the University of North Carolina at Chapel Hill for unrelated work. During the conduct of the study, Shahar Shmuel was a Postdoctoral Fellow at the University of North Carolina and also worked as a consultant for CERobs Consulting, LLC on projects unrelated to the submitted manuscript. Shahar Shmuel is currently employed by Pfizer Inc. for unrelated work. The study design, data analysis, and initial manuscript draft were completed prior to her employment at Pfizer Inc. Jennifer Lund receives research support to the University of North Carolina at Chapel Hill from AbbVie and Roche unrelated to the submitted manuscript. Jennifer Lund’s spouse was formerly employed by GlaxoSmithKline and previously owned stock in the company. Til Stürmer receives investigator-initiated research funding and support as Principal Investigator (R01AG056479) from the National Institute on Aging (NIA), and as Co-Investigator (R01CA174453, R01HL118255, R01MD011680), National Institutes of Health (NIH). He also receives salary support as Director of Comparative Effectiveness Research (CER), NC TraCS Institute, UNC Clinical and Translational Science Award (UL1TR002489), the Center for Pharmacoepidemiology (current members: GlaxoSmithKline, UCB BioSciences, Takeda, AbbVie, Boehringer Ingelheim), from pharmaceutical companies (Novo Nordisk), and from a generous contribution from Dr. Nancy A. Dreyer to the Department of Epidemiology, University of North Carolina at Chapel Hill. Dr. Stürmer does not accept personal compensation of any kind from any pharmaceutical company. He owns stock in Novartis, Roche, and Novo Nordisk. These conflicts of interest do not alter our adherence to PLOS ONE policies on sharing data and materials.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0286984