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Mark S. Tremblay

Bio: Mark S. Tremblay is an academic researcher from Children's Hospital of Eastern Ontario. The author has contributed to research in topics: Screen time & Population. The author has an hindex of 100, co-authored 541 publications receiving 43843 citations. Previous affiliations of Mark S. Tremblay include Statistics Canada & Kenyatta University.


Papers
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Journal ArticleDOI
TL;DR: The findings suggest that the measurement method may have a significant impact on the observed levels of physical activity, which poses a problem for both reliance on self- report measures and for attempts to correct for self-report – direct measure differences.
Abstract: Accurate assessment is required to assess current and changing physical activity levels, and to evaluate the effectiveness of interventions designed to increase activity levels. This study systematically reviewed the literature to determine the extent of agreement between subjectively (self-report e.g. questionnaire, diary) and objectively (directly measured; e.g. accelerometry, doubly labeled water) assessed physical activity in adults. Eight electronic databases were searched to identify observational and experimental studies of adult populations. Searching identified 4,463 potential articles. Initial screening found that 293 examined the relationship between self-reported and directly measured physical activity and met the eligibility criteria. Data abstraction was completed for 187 articles, which described comparable data and/or comparisons, while 76 articles lacked comparable data or comparisons, and a further 30 did not meet the review's eligibility requirements. A risk of bias assessment was conducted for all articles from which data was abstracted. Correlations between self-report and direct measures were generally low-to-moderate and ranged from -0.71 to 0.96. No clear pattern emerged for the mean differences between self-report and direct measures of physical activity. Trends differed by measure of physical activity employed, level of physical activity measured, and the gender of participants. Results of the risk of bias assessment indicated that 38% of the studies had lower quality scores. The findings suggest that the measurement method may have a significant impact on the observed levels of physical activity. Self-report measures of physical activity were both higher and lower than directly measured levels of physical activity, which poses a problem for both reliance on self-report measures and for attempts to correct for self-report – direct measure differences. This review reveals the need for valid, accurate and reliable measures of physical activity in evaluating current and changing physical activity levels, physical activity interventions, and the relationships between physical activity and health outcomes.

2,469 citations

Journal ArticleDOI
TL;DR: It is hoped that the definitions resulting from this comprehensive, transparent, and broad-based participatory process will result in standardized terminology that is widely supported and adopted, thereby advancing future research, interventions, policies, and practices related to sedentary behaviors.
Abstract: Background: The prominence of sedentary behavior research in health science has grown rapidly. With this growth there is increasing urgency for clear, common and accepted terminology and definitions. Such standardization is difficult to achieve, especially across multi-disciplinary researchers, practitioners, and industries. The Sedentary Behavior Research Network (SBRN) undertook a Terminology Consensus Project to address this need. Method: First, a literature review was completed to identify key terms in sedentary behavior research. These key terms were then reviewed and modified by a Steering Committee formed by SBRN. Next, SBRN members were invited to contribute to this project and interested participants reviewed and provided feedback on the proposed list of terms and draft definitions through an online survey. Finally, a conceptual model and consensus definitions (including caveats and examples for all age groups and functional abilities) were finalized based on the feedback received from the 87 SBRN member participants who responded to the original invitation and survey. Results: Consensus definitions for the terms physical inactivity, stationary behavior, sedentary behavior, standing, screen time, non-screen-based sedentary time, sitting, reclining, lying, sedentary behavior pattern, as well as how the terms bouts, breaks, and interruptions should be used in this context are provided. Conclusion: It is hoped that the definitions resulting from this comprehensive, transparent, and broad-based participatory process will result in standardized terminology that is widely supported and adopted, thereby advancing future research, interventions, policies, and practices related to sedentary behaviors.

2,025 citations

Journal ArticleDOI
TL;DR: Overall, the data show trends of under‐reporting for weight and BMI and over-reporting for height, although the degree of the trend varies for men and women and the characteristics of the population being examined.
Abstract: Obesity is a rapidly increasing public health problem, with surveillance most often based on self-reported values of height and weight. We conducted a systematic review to determine what empirical evidence exists regarding the agreement between objective (measured) and subjective (reported) measures in assessing height, weight and body mass index (BMI). Five electronic databases were searched to identify observational and experimental studies on adult populations over the age of 18. Searching identified 64 citations that met the eligibility criteria and examined the relationship between self-reported and directly measured height or weight. Overall, the data show trends of under-reporting for weight and BMI and over-reporting for height, although the degree of the trend varies for men and women and the characteristics of the population being examined. Standard deviations were large indicating that there is a great deal of individual variability in reporting of results. Combining the results quantitatively was not possible because of the poor reporting of outcomes of interest. Accurate estimation of these variables is important as data from population studies such as those included in this review are often used to generate regional and national estimates of overweight and obesity and are in turn used by decision makers to allocate resources and set priorities in health.

1,821 citations

Journal ArticleDOI
TL;DR: Evidence suggests that daily TV viewing in excess of 2 hours is associated with reduced physical and psychosocial health, and that lowering sedentary time leads to reductions in BMI.
Abstract: Accumulating evidence suggests that, independent of physical activity levels, sedentary behaviours are associated with increased risk of cardio-metabolic disease, all-cause mortality, and a variety of physiological and psychological problems. Therefore, the purpose of this systematic review is to determine the relationship between sedentary behaviour and health indicators in school-aged children and youth aged 5-17 years. Online databases (MEDLINE, EMBASE and PsycINFO), personal libraries and government documents were searched for relevant studies examining time spent engaging in sedentary behaviours and six specific health indicators (body composition, fitness, metabolic syndrome and cardiovascular disease, self-esteem, pro-social behaviour and academic achievement). 232 studies including 983,840 participants met inclusion criteria and were included in the review. Television (TV) watching was the most common measure of sedentary behaviour and body composition was the most common outcome measure. Qualitative analysis of all studies revealed a dose-response relation between increased sedentary behaviour and unfavourable health outcomes. Watching TV for more than 2 hours per day was associated with unfavourable body composition, decreased fitness, lowered scores for self-esteem and pro-social behaviour and decreased academic achievement. Meta-analysis was completed for randomized controlled studies that aimed to reduce sedentary time and reported change in body mass index (BMI) as their primary outcome. In this regard, a meta-analysis revealed an overall significant effect of -0.81 (95% CI of -1.44 to -0.17, p = 0.01) indicating an overall decrease in mean BMI associated with the interventions. There is a large body of evidence from all study designs which suggests that decreasing any type of sedentary time is associated with lower health risk in youth aged 5-17 years. In particular, the evidence suggests that daily TV viewing in excess of 2 hours is associated with reduced physical and psychosocial health, and that lowering sedentary time leads to reductions in BMI.

1,782 citations

Journal ArticleDOI
TL;DR: This work proposes that journal editors adopt a consistent definition of the term sedentary and require that all manuscripts published within their journal adhere to this common terminology, and suggests that authors use the term “inactive” to describe those who are performing insufficient amounts of MVPA.
Abstract: There has recently been an increase in research related to the health impact of sedentary behaviour (e.g., sitting) (Tremblay et al. 2010). Numerous studies suggest that those who engage in high amounts of sedentary behaviour can be at increased risk of morbidity and mortality regardless of their level of moderateto vigorous-intensity physical activity (MVPA) (Dunstan et al. 2010; Grøntved and Hu 2011; Katzmarzyk et al. 2009; Thorp et al. 2011; Wijndaele et al. 2011). Further, it has been noted that there is often little association between sedentary behaviour and MVPA (Biddle et al. 2004; Ekelund et al. 2006) and that it is possible for an individual to accumulate large amounts of both MVPA and sedentary behaviour in the course of a day (Healy et al. 2008; Katzmarzyk et al. 2009; Owen et al. 2010; Tremblay et al. 2010; Wong and Leatherdale 2008). Taken together, these findings suggest that too much sitting and too little MVPA represent separate and distinct risk factors for chronic, noncommunicable diseases (e.g., cardiovascular disease, diabetes, cancer). While research into the biology and health impact of sedentary behaviour represents an exciting new field of study, current inconsistencies in terminology are confusing for students, researchers, policymakers, and the general public. In short, the term “sedentary” currently has two separate and contradictory operational definitions. In this emerging field of research, sedentary behaviours are typically defined by both low energy expenditure (e.g., resting metabolic rate, typically ≤1.5 metabolic equivalents (METs)) and a sitting or reclining posture (Owen et al. 2010; Pate et al. 2008; Tremblay et al. 2010). In this context, a person may be described as sedentary if they engage in a large amount of sedentary behaviour. In contrast, in the sport and exercise literature the term sedentary is frequently used to describe the absence of some threshold of MVPA (Church et al. 2009; Melanson et al. 2009; Mullen et al. 2011; Sims et al. 2012; Smith et al. 2010). Thus, it is common for researchers in this field to describe a participant as sedentary because they are not meeting physical activity guidelines. Hence, many exercise studies include a “sedentary control group” or refer to their participants as coming from a “sedentary population” because of their lack of physical activity without actually measuring or assessing their level of sedentary behaviour. It is not difficult to see how these conflicting definitions of the term sedentary can easily lead to confusion. When reading the title or abstract of an article, it is often difficult to ascertain which definition of sedentary the authors have employed. If an article focuses on the health impact of a “sedentary lifestyle”, are they concerned with excessive sitting–lying down, the lack of physical activity, or both? Further, it is surprisingly common for articles within a given academic journal to oscillate between one definition and the other. To prevent further confusion, we propose that journal editors adopt a consistent definition of the term sedentary and require that all manuscripts published within their journal adhere to this common terminology. We suggest that journals formally define sedentary behaviour as any waking behaviour characterized by an energy expenditure ≤1.5 METs while in a sitting or reclining posture. In contrast, we suggest that authors use the term “inactive” to describe those who are performing insufficient amounts of MVPA (i.e., not meeting specified physical activity guidelines). The formal adoption of the above definitions by journal editors and reviewers would greatly improve the clarity of research and discussion related to these important health behaviours and help researchers searching for studies specific to sedentary behaviour or physical inactivity. We hope the research community will support these definitions and we look forward to further improvements in our understanding of the health impacts of sedentary behaviour and physical activity.

1,653 citations


Cited by
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01 Jan 2016
TL;DR: The using multivariate statistics is universally compatible with any devices to read, allowing you to get the most less latency time to download any of the authors' books like this one.
Abstract: Thank you for downloading using multivariate statistics. As you may know, people have look hundreds times for their favorite novels like this using multivariate statistics, but end up in infectious downloads. Rather than reading a good book with a cup of tea in the afternoon, instead they juggled with some harmful bugs inside their laptop. using multivariate statistics is available in our digital library an online access to it is set as public so you can download it instantly. Our books collection saves in multiple locations, allowing you to get the most less latency time to download any of our books like this one. Merely said, the using multivariate statistics is universally compatible with any devices to read.

14,604 citations

Journal ArticleDOI
02 Jan 2015-BMJ
TL;DR: The PRISMA-P checklist as mentioned in this paper provides 17 items considered to be essential and minimum components of a systematic review or meta-analysis protocol, as well as a model example from an existing published protocol.
Abstract: Protocols of systematic reviews and meta-analyses allow for planning and documentation of review methods, act as a guard against arbitrary decision making during review conduct, enable readers to assess for the presence of selective reporting against completed reviews, and, when made publicly available, reduce duplication of efforts and potentially prompt collaboration. Evidence documenting the existence of selective reporting and excessive duplication of reviews on the same or similar topics is accumulating and many calls have been made in support of the documentation and public availability of review protocols. Several efforts have emerged in recent years to rectify these problems, including development of an international register for prospective reviews (PROSPERO) and launch of the first open access journal dedicated to the exclusive publication of systematic review products, including protocols (BioMed Central's Systematic Reviews). Furthering these efforts and building on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines, an international group of experts has created a guideline to improve the transparency, accuracy, completeness, and frequency of documented systematic review and meta-analysis protocols--PRISMA-P (for protocols) 2015. The PRISMA-P checklist contains 17 items considered to be essential and minimum components of a systematic review or meta-analysis protocol.This PRISMA-P 2015 Explanation and Elaboration paper provides readers with a full understanding of and evidence about the necessity of each item as well as a model example from an existing published protocol. This paper should be read together with the PRISMA-P 2015 statement. Systematic review authors and assessors are strongly encouraged to make use of PRISMA-P when drafting and appraising review protocols.

9,361 citations

Journal ArticleDOI
Marie Ng1, Tom P Fleming1, Margaret Robinson1, Blake Thomson1, Nicholas Graetz1, Christopher Margono1, Erin C Mullany1, Stan Biryukov1, Cristiana Abbafati2, Semaw Ferede Abera3, Jerry Abraham4, Niveen M E Abu-Rmeileh, Tom Achoki1, Fadia AlBuhairan5, Zewdie Aderaw Alemu6, Rafael Alfonso1, Mohammed K. Ali7, Raghib Ali8, Nelson Alvis Guzmán9, Walid Ammar, Palwasha Anwari10, Amitava Banerjee11, Simón Barquera, Sanjay Basu12, Derrick A Bennett8, Zulfiqar A Bhutta13, Jed D. Blore14, N Cabral, Ismael Ricardo Campos Nonato, Jung-Chen Chang15, Rajiv Chowdhury16, Karen J. Courville, Michael H. Criqui17, David K. Cundiff, Kaustubh Dabhadkar7, Lalit Dandona1, Lalit Dandona18, Adrian Davis19, Anand Dayama7, Samath D Dharmaratne20, Eric L. Ding21, Adnan M. Durrani22, Alireza Esteghamati23, Farshad Farzadfar23, Derek F J Fay19, Valery L. Feigin24, Abraham D. Flaxman1, Mohammad H. Forouzanfar1, Atsushi Goto, Mark A. Green25, Rajeev Gupta, Nima Hafezi-Nejad23, Graeme J. Hankey26, Heather Harewood, Rasmus Havmoeller27, Simon I. Hay8, Lucia Hernandez, Abdullatif Husseini28, Bulat Idrisov29, Nayu Ikeda, Farhad Islami30, Eiman Jahangir31, Simerjot K. Jassal17, Sun Ha Jee32, Mona Jeffreys33, Jost B. Jonas34, Edmond K. Kabagambe35, Shams Eldin Ali Hassan Khalifa, Andre Pascal Kengne36, Yousef Khader37, Young-Ho Khang38, Daniel Kim39, Ruth W Kimokoti40, Jonas Minet Kinge41, Yoshihiro Kokubo, Soewarta Kosen, Gene F. Kwan42, Taavi Lai, Mall Leinsalu22, Yichong Li, Xiaofeng Liang43, Shiwei Liu43, Giancarlo Logroscino44, Paulo A. Lotufo45, Yuan Qiang Lu21, Jixiang Ma43, Nana Kwaku Mainoo, George A. Mensah22, Tony R. Merriman46, Ali H. Mokdad1, Joanna Moschandreas47, Mohsen Naghavi1, Aliya Naheed48, Devina Nand, K.M. Venkat Narayan7, Erica Leigh Nelson1, Marian L. Neuhouser49, Muhammad Imran Nisar13, Takayoshi Ohkubo50, Samuel Oti, Andrea Pedroza, Dorairaj Prabhakaran, Nobhojit Roy51, Uchechukwu K.A. Sampson35, Hyeyoung Seo, Sadaf G. Sepanlou23, Kenji Shibuya52, Rahman Shiri53, Ivy Shiue54, Gitanjali M Singh21, Jasvinder A. Singh55, Vegard Skirbekk41, Nicolas J. C. Stapelberg56, Lela Sturua57, Bryan L. Sykes58, Martin Tobias1, Bach Xuan Tran59, Leonardo Trasande60, Hideaki Toyoshima, Steven van de Vijver, Tommi Vasankari, J. Lennert Veerman61, Gustavo Velasquez-Melendez62, Vasiliy Victorovich Vlassov63, Stein Emil Vollset64, Stein Emil Vollset41, Theo Vos1, Claire L. Wang65, Xiao Rong Wang66, Elisabete Weiderpass, Andrea Werdecker, Jonathan L. Wright1, Y Claire Yang67, Hiroshi Yatsuya68, Jihyun Yoon, Seok Jun Yoon69, Yong Zhao70, Maigeng Zhou, Shankuan Zhu71, Alan D. Lopez14, Christopher J L Murray1, Emmanuela Gakidou1 
University of Washington1, Sapienza University of Rome2, Mekelle University3, University of Texas at San Antonio4, King Saud bin Abdulaziz University for Health Sciences5, Debre markos University6, Emory University7, University of Oxford8, University of Cartagena9, United Nations Population Fund10, University of Birmingham11, Stanford University12, Aga Khan University13, University of Melbourne14, National Taiwan University15, University of Cambridge16, University of California, San Diego17, Public Health Foundation of India18, Public Health England19, University of Peradeniya20, Harvard University21, National Institutes of Health22, Tehran University of Medical Sciences23, Auckland University of Technology24, University of Sheffield25, University of Western Australia26, Karolinska Institutet27, Birzeit University28, Brandeis University29, American Cancer Society30, Ochsner Medical Center31, Yonsei University32, University of Bristol33, Heidelberg University34, Vanderbilt University35, South African Medical Research Council36, Jordan University of Science and Technology37, New Generation University College38, Northeastern University39, Simmons College40, Norwegian Institute of Public Health41, Boston University42, Chinese Center for Disease Control and Prevention43, University of Bari44, University of São Paulo45, University of Otago46, University of Crete47, International Centre for Diarrhoeal Disease Research, Bangladesh48, Fred Hutchinson Cancer Research Center49, Teikyo University50, Bhabha Atomic Research Centre51, University of Tokyo52, Finnish Institute of Occupational Health53, Heriot-Watt University54, University of Alabama at Birmingham55, Griffith University56, National Center for Disease Control and Public Health57, University of California, Irvine58, Johns Hopkins University59, New York University60, University of Queensland61, Universidade Federal de Minas Gerais62, National Research University – Higher School of Economics63, University of Bergen64, Columbia University65, Shandong University66, University of North Carolina at Chapel Hill67, Fujita Health University68, Korea University69, Chongqing Medical University70, Zhejiang University71
TL;DR: The global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013 is estimated using a spatiotemporal Gaussian process regression model to estimate prevalence with 95% uncertainty intervals (UIs).

9,180 citations