Evidence map›Paper›PMID 34870267›Full record

ArticleFrontiers in digital health2021

Distinct Circadian Assessments From Wearable Data Reveal Social Distancing Promoted Internal Desynchrony Between Circadian Markers.

Yitong Huang, Caleb Mayer, Olivia J Walch, Clark Bowman, Srijan Sen, Cathy Goldstein, Jonathan Tyler, Daniel B Forger

Open access · goldAbstract read
In one paragraph

Article in Frontiers in digital health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.9field-weighted citation impact, top 30% of its field
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

9 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
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  5. Review
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  8. Circadian regulation of pulmonary disease: the importance of timing.Clinical science (London, England : 1979) · 2023
    Review
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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

8 authors at 3 institutions in 1 country.

Yitong HuangDepartment of Mathematics, Dartmouth College, Hanover, NH, United States.
Caleb MayerDepartment of Mathematics, University of Michigan, Ann Arbor, MI, United States.
Olivia J WalchDepartment of Neurology, University of Michigan, Ann Arbor, MI, United States.
Clark BowmanDepartment of Mathematics and Statistics, Hamilton College, Clinton, NY, United States.
Srijan SenMichigan Neuroscience Institute, University of Michigan, Ann Arbor, MI, United States.
Cathy GoldsteinDepartment of Neurology, University of Michigan, Ann Arbor, MI, United States.
Jonathan TylerDepartment of Mathematics, University of Michigan, Ann Arbor, MI, United States.
Daniel B ForgerDepartment of Mathematics, University of Michigan, Ann Arbor, MI, United States.
University of Michigan–Ann Arbor · USDartmouth College · USHamilton College · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mobile measures of human circadian rhythms (CR) are needed in the age of chronotherapy. Two wearable measures of CR have recently been validated: one that uses heart rate to extract circadian rhythms that originate in the sinoatrial node of the heart, and another that uses activity to predict the laboratory gold standard and central circadian pacemaker marker, dim light melatonin onset (DLMO). We first find that the heart rate markers of normal real-world individuals align with laboratory DLMO measurements when we account for heart rate phase error. Next, we expand upon previous work that has examined sleep patterns or chronotypes during the COVID-19 lockdown by studying the effects of social distancing on circadian rhythms. In particular, using data collected from the Social Rhythms app, a mobile application where individuals upload their wearable data and receive reports on their circadian rhythms, we compared the two circadian phase estimates before and after social distancing. Interestingly, we found that the lockdown had different effects on the two ambulatory measurements. Before the lockdown, the two measures aligned, as predicted by laboratory data. After the lockdown, when circadian timekeeping signals were blunted, these measures diverged in 70% of subjects (with circadian rhythms in heart rate, or CRHR, becoming delayed). Thus, while either approach can measure circadian rhythms, both are needed to understand internal desynchrony. We also argue that interventions may be needed in future lockdowns to better align separate circadian rhythms in the body.

Indexed as

circadian rhythmheart rateinternal desynchronysocial distancingwearables

Identifiers

PMID34870267
PMCPMC8634937
OpenAlexW3213882375

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.