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OALib Journal期刊
ISSN: 2333-9721
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Bias and imprecision in posture percentile variables estimated from short exposure samples

DOI: 10.1186/1471-2288-12-36

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Abstract:

The present study examined the statistical properties of estimated full-shift values of the 10th, 50th and 90th percentile and the 10th-90th percentile range of right upper arm elevation obtained from samples of seven different durations, ranging from 5 to 240 min. The sampling strategies were realized by simulation, using a parent data set of 73 full-shift, continuous inclinometer recordings among hairdressers. For each shift, sampling duration and exposure variable, the mean, standard deviation and sample dispersion limits (2.5% and 97.5%) of all possible sample estimates obtained at one minute intervals were calculated and compared to the true full-shift exposure value.Estimates of the 10th percentile proved to be upward biased with limited sampling, and those of the 90th percentile and the percentile range, downward biased. The 50th percentile was also slightly upwards biased. For all variables, bias was more severe with shorter sampling durations, and it correlated significantly with the true full-shift value for the 10th and 90th percentiles and the percentile range. As expected, shorter samples led to decreased precision of the estimate; sample standard deviations correlated strongly with true full-shift exposure values.The documented risk of pronounced bias and low precision of percentile estimates obtained from short posture samples presents a concern in ergonomics research and practice, and suggests that alternative, unbiased exposure variables should be considered if data collection resources are restricted.In ergonomics intervention and epidemiology studies, upper arm posture is often assessed and viewed as an important measure of biomechanical exposure [1-4]. This is justified by evidence that working with elevated arms is associated with increased risk of musculoskeletal disorders (MSD) in the shoulders [5,6]. The extent of 'rest' during occupational work has also been proposed to be an important determinant of risk [7,8], which suggests that the occur

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