SEARCHCOHORTepidemiology, public health

cohort·epidemiology, public health, research methods, observational study·PMC10194909

Importance of missingness in baseline variables: A case study of the All of Us Research Program

PLOS ONE · 14 authors, 10 centres

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TL;DR

This study analyzed baseline survey data from the All of Us Research Program to describe patterns of missing responses. It found that while overall survey completion was high, historically underrepresented groups had higher rates of missing data.

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This observational study analyzed baseline survey data from 334,183 participants in the All of Us Research Program collected between May 31, 2017, and September 30, 2020. The central finding was that 97.0% of participants completed all baseline surveys, with a median skip rate of 5.0% of questions. Limitations include that this is a snapshot as of September 2020 and did not review additional surveys or other data sources like electronic health records. The implications are that while overall missingness is low, differential missingness exists, which researchers should account for in analyses to avoid bias.

STUDY TYPE

cohort

SPECIALTY

epidemiology

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ORIGINAL PAPER

PMC10194909

Importance of missingness in baseline variables: A case study of the All of Us Research Program

PLOS ONE

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ABSTRACT

Objective The All of Us Research Program collects data from multiple information sources, including health surveys, to build a national longitudinal research repository that researchers can use to advance precision medicine. Missing survey responses pose challenges to study conclusions. We describe missingness in All of Us baseline surveys. Study design and setting We extracted survey responses between May 31, 2017, to September 30, 2020. Missing percentages for groups historically underrepresented in biomedical research were compared to represented groups. Associations of missing percentages with age, health literacy score, and survey completion date were evaluated. We used negative binomial regression to evaluate participant characteristics on the number of missed questions out of the total eligible questions for each participant. Results The dataset analyzed contained data for 334,183 participants who submitted at least one baseline survey. Almost all (97.0%) of the participants completed all baseline surveys, and only 541 (0.2%) participants skipped all questions in at least one of the baseline surveys. The median skip rate was 5.0% of the questions, with an interquartile range (IQR) of 2.5% to 7.9%. Historically underrepresented groups were associated with higher missingness (incidence rate ratio (IRR) [95% CI]: 1.26 [1.25, 1.27] for Black/African American compared to White). Missing percentages were similar by survey completion date, participant age, and health literacy score. Skipping specific questions were associated with higher missingness (IRRs [95% CI]: 1.39 [1.38, 1.40] for skipping income, 1.92 [1.89, 1.95] for skipping education, 2.19 [2.09–2.30] for skipping sexual and gender questions). Conclusion Surveys in the All of Us Research Program will form an essential component of the data researchers can use to perform their analyses. Missingness was low in All of Us baseline surveys, but group differences exist. Additional statistical methods and careful analysis of surveys could help mitigate challenges to the validity of conclusions.

CITATION EXPORT

Robert M. Cronin, Xiaoke Feng, Lina Sulieman et al.. Importance of missingness in baseline variables: A case study of the All of Us Research Program. PLOS ONE. (2023). https://doi.org/10.1371/journal.pone.0285848

AUTHORS

14 · 10 CENTRES

Robert M. Cronin, Xiaoke Feng, Lina Sulieman, Brandy Mapes, Shawn Garbett, Ashley Able, Ryan Hale, Mick P. Couper, Heather Sansbury, Brian K. Ahmedani, Qingxia Chen, Ralph C. A. Rippe, Bijan Najafi, Bijan Najafi

1 Department of Internal Medicine, The Ohio State University, Columbus, Ohio, United States of America
2 Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
3 Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
4 Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
5 Survey Research Center, University of Michigan, Ann Arbor, Michigan, United States of America
6 Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
7 Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, United States of America
8 National Institutes of Health, Bethesda, Maryland, United States of America
9 Center for Health Policy & Health Services Research, Henry Ford Health, Detroit, Michigan, United States of America
Baylor College of Medicine, UNITED STATES

EDITOR / REVIEWER

Bijan Najafi