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Line Anita Bjørkelund Børrestad, Lars Østergaard, Lars Bo Andersen and Elling Bere

Background:

To provide more accurate assessment of commuting behavior and potential health effect, it is important to have accurate methods. Therefore, the current study aimed to a) compare questionnaire reported mode of commuting with objectively measured data from accelerometer and cycle computer, b) compare moderate vigorous physical activity (MVPA) among children cycling vs. walking to school, and c) thus calculate possible underestimated MVPA, when using accelerometers to measure commuter cycling.

Methods:

A total of 78 children, average age 11.4 (SD = 0.5), participated in the study. Physical activity was measured with cycle computers and accelerometers for 4 days. Mode of commuting and demographic information was self-reported in a questionnaire.

Results:

Children who reported to cycle to school spent significantly more time cycling than those who walked to school, 53.6 (SD = ± 33.9) minutes per day vs. 25.5 (SD = ± 24.6) minutes per day (P = .002) (ie, showing that MVPA, measured by accelerometers, underestimated 28.1 minutes per day among children cycling to school vs. those not cycling to school).

Conclusion:

To provide more accurate assessment of active commuting in children and adolescents future studies should incorporate multiple methodologies such as global position systems (GPS), accelerometers, cycle computers, and self-reported measurements.

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Jakob Tarp, Lars B. Andersen and Lars Østergaard

Background:

Cycling to and from school is an important source of physical activity (PA) in youth but it is not captured by the dominant objective method to quantify PA. The aim of this study was to quantify the underestimation of objectively assessed PA caused by cycling when using accelerometry.

Methods:

Participants were 20 children aged 11 to 14 years from a randomized controlled trial performed in 2011. Physical activity was assessed by accelerometry with the addition of heart rate monitoring during cycling to school. Global positioning system (GPS) was used to identify periods of cycling to school.

Results:

Mean minutes of moderate-to-vigorous physical activity (MVPA) during round-trip commutes was 10.8 (95% CI: 7.1−16.6). Each kilometer of cycling meant an underestimation of 9314 (95% CI: 7719−11238) counts and 2.7 (95% CI: 2.1−3.5) minutes of MVPA. Adjusting for cycling to school increased estimates of MVPA/day by 6.0 (95% CI: 3.8−9.6) minutes.

Conclusions:

Cycling to and from school contribute substantially to levels of MVPA and to mean counts/min in children. This was not collected by accelerometers. Using distance to school in conjunction with self-reported cycling to school may be a simple tool to improve the methodology.

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Robin C. Puett, Dina Huang, Jessica Montresor-Lopez, Rashawn Ray and Jennifer D. Roberts

activity: a GPS/GIS analysis of the PEACH project . Prev Med . 2010 ; 51 ( 2 ): 148 – 152 . PubMed ID: 20542493 doi:10.1016/j.ypmed.2010.06.001 31. Floyd MF , Bocarro JN , Smith WR , et al . Park-based physical activity among children and adolescents . Am J Prev Med . 2011 ; 41 ( 3 ): 258

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Silvia Varela, José M. Cancela, Manuel Seijo-Martinez and Carlos Ayán

.1002/gps.4056 10.1002/gps.4056 Hajek , A. , Brettschneider , C. , Lange , C. , Posselt , T. , Wiese , B. , Susanne Steinmann , S. , … AgeCoDe Study Group . ( 2015 ). Longitudinal predictors of institutionalization in old age . PLoS ONE, 10 , e0144203 . PubMed ID: 26658776 doi:10

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Lauren M. Robins, Ted Brown, Aislinn F. Lalor, Rene Stolwyk, Fiona McDermott and Terry Haines

. International Journal of Geriatric Psychiatry, 14 , 936 – 940 . PubMed doi:10.1002/(SICI)1099-1166(199911)14:11<936::AID-GPS39>3.0.CO;2-1 10.1002/(SICI)1099-1166(199911)14:11<936::AID-GPS39>3.0.CO;2-1 Brownson , R.C. , Eyler , A.A. , King , A.C. , Brown , D.R. , Shyu , Y.L. , & Sallis , J

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Lauren T. Ptomey, Eric D. Vidoni, Esteban Montenegro-Montenegro, Michael A. Thompson, Joseph R. Sherman, Anna M. Gorczyca, Jerry L. Greene, Richard A. Washburn and Joseph E. Donnelly

moderate Alzheimer’s disease: A pilot study . International Journal of Geriatric Psychiatry, 29 ( 12 ), 1242 – 1248 . PubMed ID: 24733599 doi:10.1002/gps.4096 10.1002/gps.4096 Fredman , L. , Bertrand , R.M. , Martire , L.M. , Hochberg , M. , & Harris , E.L. ( 2006 ). Leisure-time exercise

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Lennart Raudsepp and Eva-Maria Riso

. International Journal of Geriatric Psychiatry, 24 , 1192 – 1200 . PubMed doi:10.1002/gps.2245 10.1002/gps.2245 Julien , D. , Gauvin , L. , Richard , L. , Kestens , Y. , & Payette , H. ( 2013 ). Longitudinal associations between walking frequency and depressive symptoms in older adults: results

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Kayla Regan, Felicia White, David Harvey and Laura E. Middleton

a 5-year period for African American and White dementia caregivers . International Journal of Geriatric Psychiatry, 23 , 857 – 862 . PubMed ID: 18338341 doi:10.1002/gps.1996 10.1002/gps.1996 Deary , I.J. , Watson , R. , Booth , T. , & Gale , C.R. ( 2013 ). Does cognitive ability

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James W. Navalta, Jeffrey Montes, Nathaniel G. Bodell, Charli D. Aguilar, Ana Lujan, Gabriela Guzman, Brandi K. Kam, Jacob W. Manning and Mark DeBeliso

fitness super watch, utilizes GPS tracking to determine distance and pace. Sensors and components include 3-axis accelerometers, digital compass, optical heart rate monitor, altimeter, ambient light sensor, and vibration motor. Immediately prior to testing each participant, the following demographic

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Nicolas Farina, Laura J. Hughes, Amber Watts and Ruth G. Lowry

between self and other-reported everyday functioning by cognitive status: Dementia, mild cognitive impairment, and healthy elders . International Journal of Geriatric Psychiatry, 20 ( 9 ), 827 – 834 . PubMed ID: 16116577 doi:10.1002/gps.1367 10.1002/gps.1367 Farina N. , Tabet N. , & Rusted J