Home > Publications database > Factors associated with habitual time spent in different physical activity intensities using multiday accelerometry. > print |
001 | 153218 | ||
005 | 20240229123042.0 | ||
024 | 7 | _ | |a 10.1038/s41598-020-57648-w |2 doi |
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037 | _ | _ | |a DKFZ-2020-00258 |
041 | _ | _ | |a eng |
082 | _ | _ | |a 600 |
100 | 1 | _ | |a Jaeschke, Lina |b 0 |
245 | _ | _ | |a Factors associated with habitual time spent in different physical activity intensities using multiday accelerometry. |
260 | _ | _ | |a [London] |c 2020 |b Macmillan Publishers Limited, part of Springer Nature |
336 | 7 | _ | |a article |2 DRIVER |
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336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1636705324_5415 |2 PUB:(DE-HGF) |
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336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
520 | _ | _ | |a To 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. |
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700 | 1 | _ | |a Steinbrecher, Astrid |b 1 |
700 | 1 | _ | |a Boeing, Heiner |b 2 |
700 | 1 | _ | |a Gastell, Sylvia |b 3 |
700 | 1 | _ | |a Ahrens, Wolfgang |0 0000-0003-3777-570X |b 4 |
700 | 1 | _ | |a Berger, Klaus |b 5 |
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700 | 1 | _ | |a Ebert, Nina |b 7 |
700 | 1 | _ | |a Fischer, Beate |b 8 |
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700 | 1 | _ | |a Hoffmann, Wolfgang |b 10 |
700 | 1 | _ | |a Jöckel, Karl-Heinz |b 11 |
700 | 1 | _ | |a Kaaks, Rudolf |0 P:(DE-He78)4b2dc91c9d1ac33a1c0e0777d0c1697a |b 12 |u dkfz |
700 | 1 | _ | |a Keil, Thomas |b 13 |
700 | 1 | _ | |a Kemmling, Yvonne |b 14 |
700 | 1 | _ | |a Kluttig, Alexander |b 15 |
700 | 1 | _ | |a Krist, Lilian |b 16 |
700 | 1 | _ | |a Leitzmann, Michael |b 17 |
700 | 1 | _ | |a Lieb, Wolfgang |b 18 |
700 | 1 | _ | |a Linseisen, Jakob |b 19 |
700 | 1 | _ | |a Löffler, Markus |b 20 |
700 | 1 | _ | |a Michels, Karin B |b 21 |
700 | 1 | _ | |a Obi, Nadia |b 22 |
700 | 1 | _ | |a Peters, Annette |b 23 |
700 | 1 | _ | |a Schipf, Sabine |b 24 |
700 | 1 | _ | |a Schmidt, Börge |b 25 |
700 | 1 | _ | |a Zinkhan, Melanie |b 26 |
700 | 1 | _ | |a Pischon, Tobias |b 27 |
773 | _ | _ | |a 10.1038/s41598-020-57648-w |g Vol. 10, no. 1, p. 774 |0 PERI:(DE-600)2615211-3 |n 1 |p 774 |t Scientific reports |v 10 |y 2020 |x 2045-2322 |
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