Effects of Bodyweight

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Introduction

Back pain is common in general population. Also, occupational back pain represents significant morbidity and cost to industry. Researchers reported a 17.6% 12-month prevalence of back pain, responsible for 149.1 million lost workdays, where 65% of the cases were attributed to occupational activities (Guo et al, 1995). A research indicates that workers’ compensation claims for the low back represent a disproportionate share of the costs, with low back claims ranging from 16% to 19% of all claims, but constituting 30% to 41% of the total costs (Webster and Snook, 1994). Total costs of occupationally related low back pain has been estimated from $50 billion to $100 billion for direct medical and indirect costs in the U.S. (Frymoyer and Cats-Baril, 1991).

Researchers use biomechanical spine models to understand spine pain causes and risk factors. Actually, the assessment of spinal loads, stability and subsequently the estimate of injury risk in most of tasks is possible only through biomechanical models. There are a lot of spine model (e.g. Granata and Wilson, 2001; Daggfeldt and Thorstensson, 2003; Arjamand and Shirazi-Adl, 2006) which developed to answer a particular research question especially about spinal loads in different levels. While detailed biomechanical models are more accurate and reliable but they do not use by ergonomists. Since their complexity make them usefulness. So regression based models and equations have built to solve this drawback (Waters et al,1993 (NIOSH); American Conference of Governmental Industrial Hygienists, 2005 (ACGIH TLV); Snook and Ciriello, 1991; University of Michigan, 2001 (3DSSPP); Merryweather et al, 2009 (HCBCF); McGill et al., 1996; Fathallah et al,1999; Arjmand et al, 2011). ...

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...shear force (S) at the L4-L5 disc.

Regression procedure: The output variables will relate to input variables through a regression equation:

Spinal load=a_0+ a_1 W+a_2 H

Solving all possible combination of input variables require nine analyses. For each set of input variables PCSA and moment arm of trunk muscles will calculate and spinal loads will obtained through the model. Output variables will be used to find coefficients of regression equation.

Results

Current biomechanical spine models don’t consider individual factors and their effects on spinal loads. This study tries to find the influence of body weight and height over spinal loads. Results of this study can improve the accuracy of spine models. The results will be compared with the outputs of spine models in 3DSSPP and AnyBody™, which use simple scaling algorithms according to weight and height.

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