Study On Agricultural Machinery Injury In North Of China And Related Risk Factors

Objective:To investigate prevalence of agricultural machinery injuries and related factors that affected agricultural machinery injury rate, to explore relationship between them. To evaluate the type, cause, place, and injury body part etc. of epidemiological of machinery injuries. Provide objective and scientific references for establishing preventive strategies.Methods:The purposive-cluster sampling methods were carried out to select 1921 agricultural machinery operators from Heilungkiang province, Shanxi province, Hebei province, Henan province, and Shandong province into this survey. The agricultural machinery injury status and related factors were investigated. Chi-square test was used to analysis the injury status between different subgroups, logistic regression was used to analysis the relationship of injury and factors, BP neural network was used to analysis the importance of related factors to injury, and difference of the results was compared. Results:(1) Agricultural machinery injury rate in north of China is 13.07%, the characteristics which had significant difference include: gender, per capita family income, sleep difficult, sleepy, related disease, smoking during machine operation, drink, drunk, satisfy degree of family income, debt in last year, stress and CES-D 10 score.(2) The variables that statistical significance from univariate logistic regression include: gender, per capita family income, sleep difficult, sleepy, related disease, smoking during machine operation, drink, drunk, satisfy degree of family income, debt in last year, stress and CES-D 10 score, which in accordance with the chi-square test. After multivariate logistic regression adjusted, variables that still statistical significance included: gender, per capita family income, vision, drunk, satisfy degree of family income, debt in last year, and stress.(3) The first ten variables that impact the injury rate resulted from BP neural network included: gender, audition, education level, vision, per capita family income, debt, sleepy and sleep difficult. The results from BP neural network correspond with that from logistic regression.(4) The most frequently injury type was scratch(55.78%), second frequently was Strain and sprain; the most frequently injury body part was four limbs, especially the hands and arms; the most frequently injury cause was caught in running equipment/machinery, crushed by equipment/machinery, fall from nonmoving vehicle and stuck by slipping handheld object; the most frequently machine that caused injury was tractors and transport machine; The most frequently occurred months were April, May, June; the majority injury full-recovered(82.87%), prognosis were well. Conclusion:Agricultural machinery injury rate was very high in China, and with the development of agricultural mechanization, agricultural machinery injury rate tend to increase. Therefore it's imperative to investigate agricultural machinery injury and propose preventive measures.