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|Title: ||International children's accelerometry database (ICAD): design and methods|
|Authors: ||Sherar, Lauren B.|
Esliger, Dale W.
Cooper, Ashley R.
Riddoch, Christopher J.
|Issue Date: ||2011|
|Publisher: ||BioMed Central Ltd / © Sherar et al;|
|Citation: ||SHERAR, L.B. ... et al, 2011. International children's accelerometry database (ICAD): design and methods. BMC Public Health, 11, 485.|
|Abstract: ||Background: Over the past decade, accelerometers have increased in popularity as an objective measure of physical activity in free-living individuals. Evidence suggests that objective measures, rather than subjective tools such as questionnaires, are more likely to detect associations between physical activity and health in children. To date, a number of studies of children and adolescents across diverse cultures around the globe have collected accelerometer measures of physical activity accompanied by a broad range of predictor variables and associated health outcomes. The International Children's Accelerometry Database (ICAD) project pooled and reduced raw accelerometer data using standardized methods to create comparable outcome variables across studies. Such data pooling has the potential to improve our knowledge regarding the strength of relationships between physical activity and health. This manuscript describes the contributing studies, outlines the standardized methods used to process the accelerometer data and provides the initial questions which will be addressed using this novel data repository. Methods. Between September 2008 and May 2010 46,131 raw Actigraph data files and accompanying anthropometric, demographic and health data collected on children (aged 3-18 years) were obtained from 20 studies worldwide and data was reduced using standardized analytical methods. Results: When using 8, 10 and 12 hrs of wear per day as a criterion, 96%, 93.5% and 86.2% of the males, respectively, and 96.3%, 93.7% and 86% of the females, respectively, had at least one valid day of data. Conclusions: Pooling raw accelerometer data and accompanying phenotypic data from a number of studies has the potential to: a) increase statistical power due to a large sample size, b) create a more heterogeneous and potentially more representative sample, c) standardize and optimize the analytical methods used in the generation of outcome variables, and d) provide a means to study the causes of inter-study variability in physical activity. Methodological challenges include inflated variability in accelerometry measurements and the wide variation in tools and methods used to collect non-accelerometer data. © 2011 Sherar et al; licensee BioMed Central Ltd.|
|Description: ||This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.|
|Sponsor: ||Funding for the project was provided by the National Preventative Research
Initiative (NPRI; http://www.npri.org.uk). Funding partners are: British Heart
Foundation; Cancer Research UK; Department of Health; Diabetes UK;
Economic and Social Research Council; Medical Research Council; Research
and Development Office for the Northern Ireland Health and Social Services;
Chief Scientist Office, Scottish Executive Health Department; The Stroke
Association; Welsh Assembly Government and World Cancer Research Fund.|
|Publisher Link: ||http://dx.doi.org/10.1186/1471-2458-11-485|
|Appears in Collections:||Published Articles (Sport, Exercise and Health Sciences)|
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