Evidence map›Paper›PMID 27285490›Full record

Observational studyMedicine and science in sports and exercise2016

No Evidence of Reciprocal Associations between Daily Sleep and Physical Activity.

Jonathan A Mitchell, Suneeta Godbole, Kevin Moran, Kate Murray, Peter James, Francine Laden, J Aaron Hipp, Jacqueline Kerr, Karen Glanz

Abstract readObservational Study
In one paragraph

Observational study in Medicine and science in sports and exercise, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed.

  1. Trial
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  7. Sleep duration and timing are associated with next-day physical activity: Insights from two large-scale wearable sensor studies.Proceedings of the National Academy of Sciences of the United States of America · 2025
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  8. 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

9 authors.

Jonathan A Mitchell1Division of Gastroenterology, Hepatology and Nutrition, Children's Hospital of Philadelphia, Philadelphia, PA; 2Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA; 3Department of Family Medicine and Public Health, University of California, San Diego, San Diego, CA; 4Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL; 5School of Psychology and Counseling, Queensland University of Technology, Brisbane, AUSTRALIA; 6Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA; 7Department of Environmental Health and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA; 8Department of Parks, Recreation, and Tourism Management and Center for Geospatial Analytics, NC State University, Raleigh, NC; 9Perelman School of Medicine and School of Nursing, University of Pennsylvania, Philadelphia, PA.
Suneeta Godbole
Kevin Moran
Kate Murray
Peter James
Francine Laden
J Aaron Hipp
Jacqueline Kerr
Karen Glanz

Funding

Life Course Cancer Epidemiology Cohort in WomenUM1CA176726 · NCI · HARVARD SCHOOL OF PUBLIC HEALTH · PI WILLETT, WALTER C. · 2013 to 2017
$15.7M
TREC Coordination CenterU01CA116850 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI THORNQUIST, MARK · 2005 to 2016
$13.3M
Sleep Duration, Childhood Energy Balance, and Insulin Resistance in AdolescenceU54CA155626 · NCI · HARVARD SCHOOL OF PUBLIC HEALTH · PI HU, FRANK B · 2011 to 2015
$9.6M
The Women In Steady Exercise Research (WISER) SurwVor TrialU54CA155850 · NCI · UNIVERSITY OF PENNSYLVANIA · PI CHODOSH, LEWIS A · 2011 to 2015
$9.1M
UCSD Biorepository Shared ResourceU54CA155435 · NCI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PATTERSON, RUTH E · 2011 to 2015
$9.1M
Worksite Policies and neighborhood Influences on Obesity and Cancer RiskU54CA155496 · NCI · WASHINGTON UNIVERSITY · PI COLDITZ, GRAHAM A. · 2011 to 2016
$9.0M
CVD Epidemiology Training Program in Behavior, the Environment and Global HealthT32HL098048 · NHLBI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI Goodarz Danaei, ERIC B RIMM · 2009 to 2026
$6.9M
DIET, PHYSICAL ACTIVITY, AND THE RELATIONSHIP BETWEEN AIR POLLUTION AND CVDR01ES017017 · NIEHS · BRIGHAM AND WOMEN'S HOSPITAL · PI LADEN, FRANCINE · 2009 to 2012
$1.7M
Sleep, Energetic Behaviors, and Adolescent Obesity during the Transition from Middle to High SchoolK01HL123612 · NHLBI · CHILDREN'S HOSP OF PHILADELPHIA · PI MITCHELL, JONATHAN ANDREW · 2015 to 2019
$787k
Obesity susceptibility loci and breast cancer risk in BRCA1 and BRCA2 mutation caF32CA162847 · NCI · UNIVERSITY OF PENNSYLVANIA · PI MITCHELL, JONATHAN ANDREW · 2011 to 2013
$173k
High resolution measures of behavioral cancer risk factors from mobile technologyK99CA201542 · NCI · HARVARD SCHOOL OF PUBLIC HEALTH · PI JAMES, PETER · 2016 to 2016
$129k
NCI NIH HHS F32 CA162847NCI NIH HHS K99 CA201542NCI NIH HHS U01 CA116850NCI NIH HHS U54 CA155435NCI NIH HHS U54 CA155496NCI NIH HHS U54 CA155626NCI NIH HHS U54 CA155850NCI NIH HHS UM1 CA176726NHLBI NIH HHS K01 HL123612NHLBI NIH HHS T32 HL098048NIEHS NIH HHS R01 ES017017
6 · The paper itself

Abstract

purposeThis study aimed to determine whether physical activity patterns are associated with sleep later at night and if nighttime sleep is associated with physical activity patterns the next day among adult women.

methodsWomen (N = 353) living throughout the United States wore a wrist and a hip accelerometer for 7 d. Total sleep time (TST, hours per night) and sleep efficiency (SE, %) were estimated from the wrist accelerometer, and moderate to vigorous physical activity (MVPA, >1040 counts per minute, h·d) and sedentary behavior (SB, <100 counts per minute, h·d) were estimated from the hip accelerometer. Mixed-effects models adjusted for age, race, body mass index, education, employment, marital status, health status, and hip accelerometer wear time were used to analyze the data. Follow-up analyses using quantile regression were used to investigate associations among women with below average TST and MVPA and above average SB.

resultsThe average age of our sample was 55.5 yr (SD = 10.2 yr). The majority of participants were White (79%) and married (72%), and half were employed full time (49%). The participants spent on average 8.9 and 1.1 h·d in SB and MVPA, respectively, and 6.8 h per night asleep. No associations were observed between MVPA and SB with nighttime TST or SE. There were no associations between nighttime TST and SE with MVPA or SB the next day. The findings were the same in the quantile regression analyses.

conclusionIn free-living adult women, accelerometry-estimated nighttime sleep and physical activity patterns were not associated with one another. On the basis of our observational study involving a sample of adult women, higher physical activity will not necessarily improve sleep at night on a day-to-day basis (and vice versa).

Indexed as

AccelerometryExerciseFemaleHipHumansMiddle AgedSleepTime FactorsWrist

Identifiers

PMID27285490
PMCPMC5026562

What OpenQuestion holds

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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.