Associations of Vigorous-Intensity Physical Activity with Biomarkers in Youth

Justin B. Moore, Michael W. Beets, Keith Brazendale, Steven N. Blair, Russell R. Pate, Lars B. Andersen, Sigmund A. Anderssen, Anders Grøntved, Pedro C. Hallal, Katarzyna Kordas, Susi Kriemler, John J. Reilly, Luis B. Sardinha

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Introduction Physical activity (PA) conveys known cardiometabolic benefits to youth, but the contribution of vigorous-intensity PA (VPA) to these benefits is unknown. Therefore, we sought to determine (a) the associations between VPA and cardiometabolic biomarkers independent of moderate-intensity PA (MPA) and time sedentary and (b) the accelerometer cut point that best represents the threshold for health-promoting VPA in youth. Methods Data from the International Children's Accelerometry Database (ICAD) were analyzed in 2015. The relationship between cardiometabolic biomarkers and four categories of VPA estimated via three sets of cut points were examined using isotemporal substitution quantile regression modeling at the 10th, 25th, 50th, 75th, and 90th percentile of the distribution of each biomarker, separately. Age, sex, accelerometer wear time, sedentary time, and MPA were controlled for while allowing substitution for light-intensity PA. Data from 11,588 youth (4-18 yr) from 11 ICAD studies (collected 1998-2009) were analyzed. Results Only 32 of 360 significant associations were observed. Significant, negative relationships were observed for VPA with waist circumference and insulin. Replacing light-intensity PA with VPA (corresponding to at the 25th to 90th percentiles of VPA) was associated with 0.67 (-1.33 to -0.01; P = 0.048) to 7.30 cm (-11.01 to -3.58; P < 0.001) lower waist circumference using Evenson and ICAD cut points (i.e., higher counts per minute). VPA levels were associated with 12.60 (-21.28 to -3.92; P = 0.004) to 27.03 pmol·L -1 (-45.03 to -9.03; P = 0.003) lower insulin levels at the 75th to 90th percentiles using Evenson and ICAD cut points when substituted for light PA. Conclusions Substituting light PA with VPA was inversely associated with waist circumference and insulin. However, VPA was inconsistently related to the remaining biomarkers after controlling for time sedentary and MPA.

Original languageEnglish (US)
Pages (from-to)1366-1374
Number of pages9
JournalMedicine and Science in Sports and Exercise
Volume49
Issue number7
DOIs
StatePublished - Jan 1 2017

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Accelerometry
Biomarkers
Exercise
Waist Circumference
Databases
Light
Insulin
Health

All Science Journal Classification (ASJC) codes

  • Orthopedics and Sports Medicine
  • Physical Therapy, Sports Therapy and Rehabilitation

Cite this

Moore, J. B., Beets, M. W., Brazendale, K., Blair, S. N., Pate, R. R., Andersen, L. B., ... Sardinha, L. B. (2017). Associations of Vigorous-Intensity Physical Activity with Biomarkers in Youth. Medicine and Science in Sports and Exercise, 49(7), 1366-1374. https://doi.org/10.1249/MSS.0000000000001249
Moore, Justin B. ; Beets, Michael W. ; Brazendale, Keith ; Blair, Steven N. ; Pate, Russell R. ; Andersen, Lars B. ; Anderssen, Sigmund A. ; Grøntved, Anders ; Hallal, Pedro C. ; Kordas, Katarzyna ; Kriemler, Susi ; Reilly, John J. ; Sardinha, Luis B. / Associations of Vigorous-Intensity Physical Activity with Biomarkers in Youth. In: Medicine and Science in Sports and Exercise. 2017 ; Vol. 49, No. 7. pp. 1366-1374.
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abstract = "Introduction Physical activity (PA) conveys known cardiometabolic benefits to youth, but the contribution of vigorous-intensity PA (VPA) to these benefits is unknown. Therefore, we sought to determine (a) the associations between VPA and cardiometabolic biomarkers independent of moderate-intensity PA (MPA) and time sedentary and (b) the accelerometer cut point that best represents the threshold for health-promoting VPA in youth. Methods Data from the International Children's Accelerometry Database (ICAD) were analyzed in 2015. The relationship between cardiometabolic biomarkers and four categories of VPA estimated via three sets of cut points were examined using isotemporal substitution quantile regression modeling at the 10th, 25th, 50th, 75th, and 90th percentile of the distribution of each biomarker, separately. Age, sex, accelerometer wear time, sedentary time, and MPA were controlled for while allowing substitution for light-intensity PA. Data from 11,588 youth (4-18 yr) from 11 ICAD studies (collected 1998-2009) were analyzed. Results Only 32 of 360 significant associations were observed. Significant, negative relationships were observed for VPA with waist circumference and insulin. Replacing light-intensity PA with VPA (corresponding to at the 25th to 90th percentiles of VPA) was associated with 0.67 (-1.33 to -0.01; P = 0.048) to 7.30 cm (-11.01 to -3.58; P < 0.001) lower waist circumference using Evenson and ICAD cut points (i.e., higher counts per minute). VPA levels were associated with 12.60 (-21.28 to -3.92; P = 0.004) to 27.03 pmol·L -1 (-45.03 to -9.03; P = 0.003) lower insulin levels at the 75th to 90th percentiles using Evenson and ICAD cut points when substituted for light PA. Conclusions Substituting light PA with VPA was inversely associated with waist circumference and insulin. However, VPA was inconsistently related to the remaining biomarkers after controlling for time sedentary and MPA.",
author = "Moore, {Justin B.} and Beets, {Michael W.} and Keith Brazendale and Blair, {Steven N.} and Pate, {Russell R.} and Andersen, {Lars B.} and Anderssen, {Sigmund A.} and Anders Gr{\o}ntved and Hallal, {Pedro C.} and Katarzyna Kordas and Susi Kriemler and Reilly, {John J.} and Sardinha, {Luis B.}",
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Moore, JB, Beets, MW, Brazendale, K, Blair, SN, Pate, RR, Andersen, LB, Anderssen, SA, Grøntved, A, Hallal, PC, Kordas, K, Kriemler, S, Reilly, JJ & Sardinha, LB 2017, 'Associations of Vigorous-Intensity Physical Activity with Biomarkers in Youth', Medicine and Science in Sports and Exercise, vol. 49, no. 7, pp. 1366-1374. https://doi.org/10.1249/MSS.0000000000001249

Associations of Vigorous-Intensity Physical Activity with Biomarkers in Youth. / Moore, Justin B.; Beets, Michael W.; Brazendale, Keith; Blair, Steven N.; Pate, Russell R.; Andersen, Lars B.; Anderssen, Sigmund A.; Grøntved, Anders; Hallal, Pedro C.; Kordas, Katarzyna; Kriemler, Susi; Reilly, John J.; Sardinha, Luis B.

In: Medicine and Science in Sports and Exercise, Vol. 49, No. 7, 01.01.2017, p. 1366-1374.

Research output: Contribution to journalArticle

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T1 - Associations of Vigorous-Intensity Physical Activity with Biomarkers in Youth

AU - Moore, Justin B.

AU - Beets, Michael W.

AU - Brazendale, Keith

AU - Blair, Steven N.

AU - Pate, Russell R.

AU - Andersen, Lars B.

AU - Anderssen, Sigmund A.

AU - Grøntved, Anders

AU - Hallal, Pedro C.

AU - Kordas, Katarzyna

AU - Kriemler, Susi

AU - Reilly, John J.

AU - Sardinha, Luis B.

PY - 2017/1/1

Y1 - 2017/1/1

N2 - Introduction Physical activity (PA) conveys known cardiometabolic benefits to youth, but the contribution of vigorous-intensity PA (VPA) to these benefits is unknown. Therefore, we sought to determine (a) the associations between VPA and cardiometabolic biomarkers independent of moderate-intensity PA (MPA) and time sedentary and (b) the accelerometer cut point that best represents the threshold for health-promoting VPA in youth. Methods Data from the International Children's Accelerometry Database (ICAD) were analyzed in 2015. The relationship between cardiometabolic biomarkers and four categories of VPA estimated via three sets of cut points were examined using isotemporal substitution quantile regression modeling at the 10th, 25th, 50th, 75th, and 90th percentile of the distribution of each biomarker, separately. Age, sex, accelerometer wear time, sedentary time, and MPA were controlled for while allowing substitution for light-intensity PA. Data from 11,588 youth (4-18 yr) from 11 ICAD studies (collected 1998-2009) were analyzed. Results Only 32 of 360 significant associations were observed. Significant, negative relationships were observed for VPA with waist circumference and insulin. Replacing light-intensity PA with VPA (corresponding to at the 25th to 90th percentiles of VPA) was associated with 0.67 (-1.33 to -0.01; P = 0.048) to 7.30 cm (-11.01 to -3.58; P < 0.001) lower waist circumference using Evenson and ICAD cut points (i.e., higher counts per minute). VPA levels were associated with 12.60 (-21.28 to -3.92; P = 0.004) to 27.03 pmol·L -1 (-45.03 to -9.03; P = 0.003) lower insulin levels at the 75th to 90th percentiles using Evenson and ICAD cut points when substituted for light PA. Conclusions Substituting light PA with VPA was inversely associated with waist circumference and insulin. However, VPA was inconsistently related to the remaining biomarkers after controlling for time sedentary and MPA.

AB - Introduction Physical activity (PA) conveys known cardiometabolic benefits to youth, but the contribution of vigorous-intensity PA (VPA) to these benefits is unknown. Therefore, we sought to determine (a) the associations between VPA and cardiometabolic biomarkers independent of moderate-intensity PA (MPA) and time sedentary and (b) the accelerometer cut point that best represents the threshold for health-promoting VPA in youth. Methods Data from the International Children's Accelerometry Database (ICAD) were analyzed in 2015. The relationship between cardiometabolic biomarkers and four categories of VPA estimated via three sets of cut points were examined using isotemporal substitution quantile regression modeling at the 10th, 25th, 50th, 75th, and 90th percentile of the distribution of each biomarker, separately. Age, sex, accelerometer wear time, sedentary time, and MPA were controlled for while allowing substitution for light-intensity PA. Data from 11,588 youth (4-18 yr) from 11 ICAD studies (collected 1998-2009) were analyzed. Results Only 32 of 360 significant associations were observed. Significant, negative relationships were observed for VPA with waist circumference and insulin. Replacing light-intensity PA with VPA (corresponding to at the 25th to 90th percentiles of VPA) was associated with 0.67 (-1.33 to -0.01; P = 0.048) to 7.30 cm (-11.01 to -3.58; P < 0.001) lower waist circumference using Evenson and ICAD cut points (i.e., higher counts per minute). VPA levels were associated with 12.60 (-21.28 to -3.92; P = 0.004) to 27.03 pmol·L -1 (-45.03 to -9.03; P = 0.003) lower insulin levels at the 75th to 90th percentiles using Evenson and ICAD cut points when substituted for light PA. Conclusions Substituting light PA with VPA was inversely associated with waist circumference and insulin. However, VPA was inconsistently related to the remaining biomarkers after controlling for time sedentary and MPA.

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