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dc.contributor.authorJaeschke, Lina
dc.contributor.authorSteinbrecher, Astrid
dc.contributor.authorBoeing, Heiner
dc.contributor.authorGastell, Sylvia
dc.contributor.authorAhrens, Wolfgang
dc.contributor.authorBerger, Klaus
dc.contributor.authorBrenner, Hermann
dc.contributor.authorEbert, Nina
dc.contributor.authorFischer, Beate
dc.contributor.authorGreiser, Karin Halina
dc.contributor.authorHoffmann, Wolfgang
dc.contributor.authorJöckel, Karl-Heinz
dc.contributor.authorKaaks, Rudolf
dc.contributor.authorKeil, Thomas
dc.contributor.authorKemmling, Yvonne
dc.contributor.authorKluttig, Alexander
dc.contributor.authorKrist, Lilian
dc.contributor.authorLeitzmann, Michael
dc.contributor.authorLieb, Wolfgang
dc.contributor.authorLinseisen, Jakob
dc.contributor.authorLöffler, Markus
dc.contributor.authorMichels, Karin B
dc.contributor.authorObi, Nadia
dc.contributor.authorPeters, Annette
dc.contributor.authorSchipf, Sabine
dc.contributor.authorSchmidt, Börge
dc.contributor.authorZinkhan, Melanie
dc.contributor.authorPischon, Tobias
dc.date.accessioned2020-02-14T15:15:43Z
dc.date.available2020-02-14T15:15:43Z
dc.date.issued2020-01-21
dc.identifier.citationSci Rep. 2020 Jan 21;10(1):774. doi: 10.1038/s41598-020-57648-w.en_US
dc.identifier.issn2045-2322
dc.identifier.pmid31964962
dc.identifier.doi10.1038/s41598-020-57648-w
dc.identifier.urihttp://hdl.handle.net/10033/622136
dc.description.abstractTo investigate factors associated with time in physical activity intensities, we assessed physical activity of 249 men and women (mean age 51.3 years) by 7-day 24h-accelerometry (ActiGraph GT3X+). Triaxial vector magnitude counts/minute were extracted to determine time in inactivity, in low-intensity, moderate, and vigorous-to-very-vigorous activity. Cross-sectional associations with sex, age, body mass index, waist circumference, smoking, alcohol consumption, education, employment, income, marital status, diabetes, and dyslipidaemia were investigated in multivariable regression analyses. Higher age was associated with more time in low-intensity (mean difference, 7.3 min/d per 5 years; 95% confidence interval 2.0,12.7) and less time in vigorous-to-very-vigorous activity (-0.8 min/d; -1.4, -0.2), while higher BMI was related to less time in low-intensity activity (-3.7 min/d; -6.3, -1.2). Current versus never smoking was associated with more time in low-intensity (29.2 min/d; 7.5, 50.9) and less time in vigorous-to-very-vigorous activity (-3.9 min/d; -6.3, -1.5). Finally, having versus not having a university entrance qualification and being not versus full time employed were associated with more inactivity time (35.9 min/d; 13.0, 58.8, and 66.2 min/d; 34.7, 97.7, respectively) and less time in low-intensity activity (-31.7 min/d; -49.9, -13.4, and -50.7; -76.6, -24.8, respectively). The assessed factors show distinct associations with activity intensities, providing targets for public health measures aiming to increase activity.en_US
dc.language.isoenen_US
dc.publisherNPGen_US
dc.rightsAttribution-NonCommercial-ShareAlike 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/*
dc.titleFactors associated with habitual time spent in different physical activity intensities using multiday accelerometry.en_US
dc.typeArticleen_US
dc.contributor.departmentHZI,Helmholtz-Zentrum für Infektionsforschung GmbH, Inhoffenstr. 7,38124 Braunschweig, Germany.en_US
dc.identifier.journalScientific reportsen_US
refterms.dateFOA2020-02-14T15:15:43Z
dc.source.journaltitleScientific reports


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