Vibration can produce a wide variety of different effects to the operators. Farm equipment operators are usually exposed to whole-body vibration which transmitted via the seat or via the floor and feet. This vibration contributes to operator fatigue and can have a detrimental effect on job performance and safety.
The objective of this study was to determine whether body mass index (BMI) influences the risk of low back pain (LBP) in a population exposed to whole body vibration (WBV). For this a survey conducted in nine farm machinery-servicing stations belong to the Ministry of Agriculture (MOA), Farm machinery station in Gemiza, Egyptian Project for improving the main crops production in Sakha, and the local sector of farm machinery during the years of 2008-2009 through periodic visits. Vibration measurements were performed according to ISO 2631-1, 1997.
Two measurements were taken: stand height, and weight the results revealed that the tractor (Nasr model) which has no suspended seat and range of 60-65 horse power in the sample under study considers the highest equipment gives WBV data the frequency weighted RMS acceleration magnitude of the largest single orthogonal axis is in the vertical axis (Z) and also for VDV of weighted RMS acceleration. This constitutes a high risk on the labor body, followed by UTB tractor and rice combine. On the other hand, the WBV emission levels recorded during the harvesting by wheat combine and threshing tasks were low which constitute no risk on the labor body
The results revealed that the highest number of injured labors was in the age group of (41-45) years (46.4%), followed by (46-50) years (28.6%),
but the least number of injured labors was in the age group of (34-40) years (14.3%), and followed by (51-55) years (10.7%). Type of pain indicated that the highest number of pain was (47%) for temporary LBP, followed by (22.6%) for healthy body, and (8.3%) for chronic LBP. Results showed that there are significant differences between the different types of equipment during the variation of farm operations, significant correlation, and significant relationship between accidents factors.