| [Objective]To find out distribution characteristics of menstrual disorders of the trainattendants. Analysis on the association between psychological factors, such asoccupational stress, depression, and menstrual disorders which were not arised fromorganic diseases. Investigate the psychological factors which affect the menstrualdisorders and bio-interaction between the psychological factors. Establish theBack-propagation artificial neural network model of the psychological factors andmenstrual disorders. Explore function of the interaction of the polymorphisms of GRand occupational stress in the menstrual disorders. Make the pertinent interventionstudy to protect the procreation health of the train attendants. Supply scientific basisto create healthy and high-performance working environment and improveoccupational bio-quality of the train attendants.[Methods]1807female train attendants who work in Nanchang Railway the Fuzhou Depot,Bureau for more than half year, among which1664is valid are cluster-sampled, thevalid recovery rate is92.09%.94conductor or passenger steward work in Fuzhou orXiamen station who were administered the same bureau were handy sample.357blood sample were collected by systematic sampling according to the number of thequestionnaire.Menstrual status was assessed by index of reproductive epidemiology provided byorganization of women occupational health of the occupational health andoccupational disease party. The questionnares of Effort-Reward ImbalanceQuestionnaire, Family Stress Scale Questionnaire, Center for Epidemiological Survey, Depression Scale et al were used to estimate the psychological factors. Investigate theother affect factors of menstrual disorder simultaneity. The genomic DNA wasextracted from the sample blood, afterwards, the polymorphisms of GR were tested byPCR-RFLP. Univarite and multivariate logistic regression, generalized multifactordimensionality reduction, crossover analysis were use to identify the independent andinteraction effects of the the psychological factors and gene. Establish theBack-propagation artificial neural network model of the psychological factors andmenstrual disorders by using the Neural Network Toolbox of Matlab7.0softwarepackage.[Results]1. The prevalence of menstrual disorders was60.9%. The prevalence of menstrualdisorders after work was47.7%which was higher than the station’s (41.5%). Amongthe types of menstrual disorders, the prevalence of menstrual cycle disorders washighest (46.8%) which is significantly higher than the station’s (28.7%).2. According to univarite and multivariate logistic regression, occupational stress,family stress, depression, smoking, childbearing history enter the regression equation.occupational stress, family stress, depression, smoking were dangerous factors ofmenstrual disorders, childbearing history was protective factor. The odds ratios(OR)of the high levels of occupational stress was2.094(95%CI=1.664～2.635), the OR ofthe high levels of family stress was1.637(95%CI=291～2.077), the OR of depressionwas1.933(95%CI=1.560～2.394), the OR of smoking was7.403(95%CI=1.717～31.919). The OR of childbearing history was0.338(95%CI=0.219～0.521）).According to generalized multifactor dimensionality reduction, occupational stresswas the most important dangerous factor.3. Analysis the interaction of the occupational stress and other factors: Compared withthe low levels of occupational stress and non-depression, the OR of high levels ofoccupational stress and depression was2.680(95%CI:1.975-3.638), the OR of highlevels of occupational stress and non-depression was1.512（95%CI:1.129-2.025）, theOR of low levels of occupational stress and depression was1.183(95%CI：0.745，1.879). According to crossover analysis, there was add interaction between occupational stress and depression. Compared with the low levels of occupationalstress and the low levels of family stress, the OR of the high levels of occupationalstress and family stress was2.324（95%CI:1.681-3.213）, the OR of the high levels ofoccupational stress and the low levels of family stress was1.655（95%CI:1.262-2.171）, the OR of the low levels of occupational stress and the high levels offamily stress was1.319(95%CI:0.786，2.212).4. According to the relationship between occupational stress, overcommitement,family stress, depression, smoking, childbearing history and menstrual disorders,establish the Back-propagation artificial neural network model of the psychologicalfactors and menstrual disorders. After training the neural network, the error ofperformance decreased and the coefficient of regression was0.852biger than0.8. Theresponse of the Back-propagation artificial neural network model was better.5.The frequency of the variation of the site GR BclⅠ(rs41423247) was22.83%. Thefrequency of the variation of the site GR N363S(rs6195) and GRER22/23EK(rs6189/6190) all were0. Compared with GR BclⅠwild type and thelow levels of occupational stress, the OR of GR BclⅠmutant type and the high levelsof occupational stress was3.345（95%CI:1.647-6.794）, the OR of GR BclⅠwildtype and the high levels of occupational stress was2.501（95%CI:1.296-4.829）, theOR of GR BclⅠmutant type and the low levels of occupational stress was1.271（95%CI:0.588-2.749）.[Conclusions]1. The prevalence of menstrual cycle disorders in train attendants was higher.2. The menstrual disorders in train attendants were affected by the combined action ofpsychological factors. Occupational stress was the most important dangerous factor.3. It was feasible to establish the Back-propagation artificial neural network model ofthe psychological factors and menstrual disorders according to the relationshipbetween occupational stress, overcommitement, family stress, depression, smoking,childbearing history and menstrual disorders.4. There was add interaction between occupational stress and depression to menstrualdisorders after work. 5. The frequency of the variation of the BclⅠ、N363S and ER22/23EK sites in theNR3C1were similar to other studies for Asian. There were not statics relationshipbetween the GR BclⅠ and menstrual disorders. There was not interaction for the GRBclⅠ and occupational stress. |
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