Evidence map›Paper›PMID 42502904›Full record

ArticleACR open rheumatology2026

Accelerometry-Derived Activity and Sleep Patterns in the NIH All of Us Cohort: Insights and Predictive Potential for Inflammatory Arthritis.

Souptik Barua, Adeep Kulkarni, Dhairya Upadhyay, Samika Hariharan, Imani Ashman, Kyra Chen, Aristotelis Tsirigos, Jose U Scher, Rebecca H Haberman

Abstract read
In one paragraph

Article in ACR open rheumatology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Souptik BaruaDivision of Precision Medicine, Department of Medicine, New York University Grossman School of Medicine, New York City.ORCID https://orcid.org/0000-0002-1675-8874
Adeep KulkarniDivision of Precision Medicine, Department of Medicine, New York University Grossman School of Medicine, New York City.
Dhairya UpadhyayDivision of Precision Medicine, Department of Medicine, New York University Grossman School of Medicine, New York City.
Samika HariharanDivision of Precision Medicine, Department of Medicine, New York University Grossman School of Medicine, New York City.
Imani AshmanDivision of Precision Medicine, Department of Medicine, New York University Grossman School of Medicine, New York City.
Kyra ChenDivision of Rheumatology, Department of Medicine, New York University Grossman School of Medicine, New York City.
Aristotelis TsirigosDivision of Precision Medicine, Department of Medicine, New York University Grossman School of Medicine, New York City.
Jose U ScherDivision of Rheumatology, Department of Medicine, New York University Grossman School of Medicine, New York City.ORCID https://orcid.org/0000-0002-1072-6994
Rebecca H HabermanDivision of Rheumatology, Department of Medicine, New York University Grossman School of Medicine, New York City.ORCID https://orcid.org/0000-0002-7119-8136

Funding

NIAMS NIH HHS 1K23-AR-082955NIAMS NIH HHS 1UC2-AR-081029NIAMS NIH HHS 3UC-2AR-081039-02S1NIAMS NIH HHS R01-AR-084274NIAMS NIH HHS T32-AR-069515NYU Colton Center for AutoimmunityThe Beatrice Snyder FoundationThe Riley Family Foundation
6 · The paper itself

Abstract

objectiveThe relationship between physical activity and sleep with inflammatory arthritis (IA) is understudied, and existing research has relied largely on self-report or short-term assessments. The NIH All of Us database provides long-term accelerometry data, enabling more precise estimation of the association between lifestyle behaviors and IA.

methodsParticipants from the All of Us database who shared electronic health record and Fitbit data were included. Daily activity and sleep metrics were compared between individuals with and without IA using multiple linear regression. Cox proportional hazards regression was used to examine the association of activity and sleep patterns with incident IA in a 10-year follow-up period.

resultsA total of 23,855 participants were included, 200 of whom had IA. Participants with IA took fewer daily steps (P < 0.001) and had greater sleep variability (P < 0.001) compared to those without IA. 122 individuals had incident IA. Every 1,000 extra daily steps were associated with a 7% lower risk of IA (hazard ratio [HR] 0.93 [95% confidence interval (CI) 0.87-0.99], P = 0.02). Compared to those who walked <5,000 steps daily, those who walked 5,000 to 10,000 steps and 10,000+ steps had a 41% (HR 0.59 [95% CI 0.39-0.91], P = 0.02) and 50% (HR 0.50 [95% CI 0.29-0.86], P = 0.01) reduction in risk of IA.

conclusionIndividuals with IA had reduced step counts and more sleep variability compared to those without IA, highlighting how physical activity and sleep contribute to IA. Additionally, increased daily step count was associated with decreased risk of incident IA, suggesting a possible research intervention for those at high risk of IA.

Identifiers

PMID42502904
PMCPMC13401751

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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.