Evidence map›Paper›PMID 27053434›Full record

ArticleJournal of science and medicine in sport2016

Correlates of US adult physical activity and sedentary behavior patterns.

Sydney A Jones, Fang Wen, Amy H Herring, Kelly R Evenson

Abstract read
In one paragraph

Article in Journal of science and medicine in sport, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing 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

34 citing papers in PubMed.

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  19. Device-measured sedentary behavior and physical activity in older adults differ by demographic and health-related factors.European review of aging and physical activity : official journal of the European Group for Research into Elderly and Physical Activity · 2020
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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

4 authors.

Sydney A JonesDepartment of Epidemiology, Gillings School of Global Public Health, University of North Carolina, USA. Electronic address: SydneyJones@unc.edu.
Fang WenDepartment of Epidemiology, Gillings School of Global Public Health, University of North Carolina, USA.
Amy H HerringDepartment of Biostatistics, Gillings School of Global Public Health, University of North Carolina, USA.
Kelly R EvensonDepartment of Epidemiology, Gillings School of Global Public Health, University of North Carolina, USA.

Funding

Cardiovascular Epidemiology Training GrantT32HL007055 · NHLBI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Wayne D. Rosamond · 1986 to 2026
$10.0M
Research Services CoreP2CHD050924 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI KAREN B GUZZO · 2015 to 2026
$9.6M
National Associations of Objectively Measured Physical Activity and MortalityR21HL115385 · NHLBI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI EVENSON, KELLY R. · 2012 to 2013
$393k
NHLBI NIH HHS R21 HL115385NHLBI NIH HHS T32 HL007055NICHD NIH HHS P2C HD050924
6 · The paper itself

Abstract

objectivesPhysical activity and sedentary behavior patterns may be differentially associated with socio-demographic and health measures. We explored correlates of day-to-day patterns over a week in accelerometer measured physical activity and sedentary behavior to inform intervention development.

designCross-sectional study.

methodsNational Health and Nutrition Examination Survey (NHANES) adult participants (≥20 years) in 2003-2006 wore an accelerometer for 1 week. Accelerometer data from 7236 participants were used to derive latent classes describing day-to-day patterns over a week of physical activity and sedentary behavior. Correlates of each pattern were identified using multinomial logistic regression from 21 potential variables grouped into four domains: socio-demographic, acculturation, cardiovascular, and health history.

resultsOlder age, female sex, higher body mass index, and history of chronic disease were consistently associated with lower odds of being in a more active compared to the least active class. In contrast, being employed, speaking Spanish at home, and having better self-rated health were associated with higher odds of being in a more active compared to the least active class.

conclusionsCorrelates of physical activity and sedentary behavior patterns were identified from all domains (socio-demographic, acculturation, cardiovascular, and health history). Most correlates that were positively associated with physical activity were negatively associated with sedentary behavior. Better understanding of the correlates of physical activity and sedentary behavior patterns can inform interventions to promote physical activity and reduce sedentary behavior.

Indexed as

ExerciseSedentary BehaviorAccelerometryAdultAge FactorsBody Mass IndexCross-Sectional StudiesFemaleHealth BehaviorHealth StatusHumansLogistic ModelsMaleMiddle AgedNutrition SurveysSex FactorsAccelerometryLatent class analysisMotor activitySurveillanceWeekend warrior

Identifiers

PMID27053434
PMCPMC5036978

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.