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Karin Lobenius-Palmér, Birgitta Sjöqvist, Anita Hurtig-Wennlöf and Lars-Olov Lundqvist

sedentary time to ensure good present and future health for youth with disabilities. To design PA interventions for youth with disabilities, it is first necessary to know levels of PA and how PA is influenced by different factors, such as sex, age, and type of disability. This information is important for

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Angelika Wientzek, Anna Floegel, Sven Knüppel, Matthaeus Vigl, Dagmar Drogan, Jerzy Adamski, Tobias Pischon and Heiner Boeing

The aim of our study was to investigate the relationship between objectively measured physical activity (PA) and cardiorespiratory fitness (CRF) and serum metabolites measured by targeted metabolomics in a population- based study. A total of 100 subjects provided 2 fasting blood samples and engaged in a CRF and PA measurement at 2 visits 4 months apart. CRF was estimated from a step test, whereas physical activity energy expenditure (PAEE), time spent sedentary and time spend in vigorous activity were measured by a combined heart rate and movement sensor for a total of 8 days. Serum metabolite concentrations were determined by flow injection analysis tandem mass spectrometry (FIA-MS/MS). Linear mixed models were applied with multivariable adjustment and p-values were corrected for multiple testing. Furthermore, we explored the associations between CRF, PA and two metabolite factors that have previously been linked to risk of Type 2 diabetes. CRF was associated with two phosphatidylcholine clusters independently of all other exposures. Lysophosphatidylcholine C14:0 and methionine were significantly negatively associated with PAEE and sedentary time. CRF was positively associated with the Type 2 diabetes protective factor. Vigorous activity was positively associated with the Type 2 diabetes risk factor in the mutually adjusted model. Our results suggest that CRF and PA are associated with serum metabolites, especially CRF with phosphatidylcholines and with the Type 2 diabetes protective factor. PAEE and sedentary time were associated with methionine. The identified metabolites could be potential mediators of the protective effects of CRF and PA on chronic disease risk.

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Alexis C. Frazier-Wood, Ingrid B. Borecki, Mary F. Feitosa, Paul N. Hopkins, Caren E. Smith and Donna K. Arnett


Time spent in sedentary activities (such as watching television) has previously been associated with several risk factors for cardiovascular disease (CVD) such as increased low-density lipoprotein cholesterol (LDL-C). Little is known about associations with lipoprotein subfractions. Using television and computer screen time in hours per day as a measure of sedentary time, we examined the association of screen time with lipoprotein subfractions.


Data were used from men and women forming the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study population. Mixed linear models specified lipoprotein measures as the outcome, and screen time as the predictor for fourteen lipoprotein subfraction measures, and included age, smoking status, pedigree, and fat, carbohydrate daily alcohol and energy intake as covariates. Analyses were run separately for men (n = 623) and women (n = 671). A step-down Bonferroni correction was applied to results. The analysis was repeated for significant results (p < .05), additionally controlling for body mass index (BMI) and moderate and vigorous physical activity.


Linear models indicated that screen time was associated with five lipoprotein parameters in women: the concentration of large VLDL particles (p = .01), LDL particle number (p = .01), concentration of small LDL particles (p = .04), the concentration of large HDL particles (p = .04), and HDL diameter (p = .02). All associations remained after controlling for moderate or vigorous physical activity and BMI.


We show that sedentary time is associated with lipoprotein measures, markers of cardiometabolic disease, independently of physical activity and BMI, in women but not men.

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Julien Tripette, Haruka Murakami, Hidemi Hara, Ryoko Kawakami, Yuko Gando, Harumi Ohno, Nobuyuki Miyatake and Motohiko Miyachi

, Sports, Science, and Technology, 2015 ). PA and Physical Fitness Step count (steps/day) and moderate-to-vigorous PA (MET-hr/day) were assessed objectively during a 1-month period, using accelerometer-based waist-worn PA monitors (Actimarker EW4800; Panasonic, Osaka, Japan). Sedentary time (<1.5 METs

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Julie Masurier, Marie-Eve Mathieu, Stephanie Nicole Fearnbach, Charlotte Cardenoux, Valérie Julian, Céline Lambert, Bruno Pereira, Martine Duclos, Yves Boirie and David Thivel

-to-vigorous physical activity declining with age, coupled with a concomitant increase in sedentary time ( Husu et al., 2016 ). Not only will this decline in physical activity result in lower energy expenditure (EE), recent evidences suggest that it will also favor increased energy intake (EI), contributing to the

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Jaehun Jung, Willie Leung, Bridgette Marie Schram and Joonkoo Yun

objectively-measured physical activity and sedentary time among children with and without significant movement impairments . Human Movement Science, 47 , 159 – 165 . PubMed doi:10.1016/j.humov.2016.03.004 10.1016/j.humov.2016.03.004 Leung , W. , Siebert , E.A. , & Yun , J. ( 2017 ). Measuring

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Ali Brian, Sally Taunton, Lauren J. Lieberman, Pamela Haibach-Beach, John Foley and Sara Santarossa

with children’s physical activity, sedentary time, and screen time by socioeconomic status . International Journal of Behavioral Nutrition and Physical Activity, 9 , 88 . PubMed doi:10.1186/1479-5868-9-88 10.1186/1479-5868-9-88 Temple , V.A. , & Foley , J.T. ( 2017 ). A peek at the

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Ali Brian, Sally Taunton, Chelsee Shortt, Adam Pennell and Ryan Sacko

measure of PA for children aged 3–5 years ( Pate, Almeida, McIver, Pfeiffer, & Dowda, 2006 ). Accelerometers are sensitive to PA in children, and cut points can distinguish between sedentary time and PA ( Van Cauwenberghe, Labarque, Trost, Bourdeaudhuij, & Cardon, 2011 ). Body Mass Index Participants

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Sarpreet Kahlon, Kiah Brubacher-Cressman, Erica Caron, Keren Ramonov, Ruth Taubman, Katherine Berg, F. Virginia Wright and Alicia J. Hilderley

models . Qualitative Health Research, 28 ( 3 ), 339 – 345 . PubMed ID: 29313466 doi:10.1177/1049732317750127 10.1177/1049732317750127 Obeid , J. , Balemans , A.C.J. , Noorduyn , S.G. , Gorter , J.W. , & Timmons , B.W. ( 2014 ). Objectively measured sedentary time in youth with cerebral