Evidence map›Paper›PMID 37200348›Full record

ArticlePloS one2023

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

Robert M Cronin, Xiaoke Feng, Lina Sulieman, Brandy Mapes, Shawn Garbett, Ashley Able, Ryan Hale, Mick P Couper, Heather Sansbury, Brian K Ahmedani and 1 more

Abstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Unmet social needs and diverticulitis: a phenotyping algorithm and cross-sectional analysis.Journal of the American Medical Informatics Association : JAMIA · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Robert M CroninDepartment of Internal Medicine, The Ohio State University, Columbus, Ohio, United States of America.ORCID 0000-0003-1916-6521
Xiaoke FengDepartment of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.
Lina SuliemanDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.
Brandy MapesVanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.
Shawn GarbettDepartment of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.ORCID 0000-0003-4079-5621
Ashley AbleVanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.
Ryan HaleVanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.
Mick P CouperSurvey Research Center, University of Michigan, Ann Arbor, Michigan, United States of America.
Heather SansburyNational Institutes of Health, Bethesda, Maryland, United States of America.
Brian K AhmedaniCenter for Health Policy & Health Services Research, Henry Ford Health, Detroit, Michigan, United States of America.
Qingxia ChenDepartment of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.

Funding

Enhancing All of Us Data Resources for Nutrition Precision Health: the All of Us Data and Research CenterU2COD023196 · OD · VANDERBILT UNIVERSITY MEDICAL CENTER · PI GLAZER, DAVID, HARRIS, PAUL A. · 2016 to 2022
$143.7M
Trans-America Consortium of the Health Care Systems Research Network for the All of Us Research ProgramOT2OD026550 · OD · HENRY FORD HEALTH SYSTEM · PI AHMEDANI, BRIAN KENNETH, JOHNSON, CHRISTINE C · 2018 to 2022
$57.3M
Using Patient-Centered Guidelines in a Technology Platform to Improve Health Care in Adults with Sickle Cell DiseaseK23HL141447 · NHLBI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI CRONIN, ROBERT M · 2018 to 2022
$921k
DARSaW: Developing, Assessing, and Refining Synthetic Sampling Weights to Improve Generalizability of the All of Us Research Program DataR21MD019103 · NIMHD · VANDERBILT UNIVERSITY MEDICAL CENTER · PI CHEN, QINGXIA, CRONIN, ROBERT M · 2023 to 2024
$449k
NHLBI NIH HHS K23 HL141447NIH HHS OT2 OD026550NIH HHS U2C OD023196NIMHD NIH HHS R21 MD019103
6 · The paper itself

Abstract

objectiveThe 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

settingWe 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.

resultsThe 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).

conclusionSurveys 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.

Indexed as

Population HealthHealth SurveysHumansSexual BehaviorSurveys and Questionnaires

Identifiers

PMID37200348
PMCPMC10194909

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.