本文選題：新疆不同職業(yè)人群 + 職業(yè)緊張��； 參考：《新疆醫(yī)科大學(xué)》2017年博士論文

【摘要】：目的:調(diào)查新疆不同職業(yè)人群職業(yè)緊張、睡眠質(zhì)量狀況及其影響因素,并分析兩者之間的關(guān)系,研究神經(jīng)遞質(zhì)對(duì)新疆不同職業(yè)人群職業(yè)緊張和睡眠質(zhì)量的影響。探討DRD2、NET、COMT、GABRA、5-HTR2A和5-HTTLPR基因多態(tài)性與睡眠質(zhì)量的關(guān)系,比較不同睡眠質(zhì)量組以及不同緊張程度組間5-HTT基因啟動(dòng)子區(qū)DNA甲基化的差異,探討表觀遺傳學(xué)在職業(yè)緊張與睡眠質(zhì)量相關(guān)性中的作用。綜合分析基因-基因、基因-環(huán)境(職業(yè)緊張)交互作用對(duì)新疆不同職業(yè)人群睡眠質(zhì)量的影響。完善新疆不同職業(yè)人群職業(yè)緊張和睡眠質(zhì)量的流行病學(xué)資料,為制定和提高新疆不同職業(yè)人群的睡眠質(zhì)量提供科學(xué)依據(jù)。方法:1)本研究采取多階段抽樣方法,使用職業(yè)緊張量表、付出-回報(bào)失衡量表、匹茲堡睡眠質(zhì)量量表,對(duì)2,650名新疆不同職業(yè)人群進(jìn)行現(xiàn)況調(diào)查。2)隨機(jī)抽取240人作為神經(jīng)遞質(zhì)的測(cè)定對(duì)象,利用ELISA法檢測(cè)血漿5-HT、NE、E、DA、GABA水平,利用結(jié)構(gòu)方程模型分析職業(yè)緊張、神經(jīng)遞質(zhì)以及睡眠質(zhì)量之間的關(guān)系。3)分層隨機(jī)抽取720名研究對(duì)象,應(yīng)用SNaPshot技術(shù)檢測(cè)多巴胺D2受體(rs1799732、rs1800497)、去甲腎上腺素轉(zhuǎn)運(yùn)體(rs2242446、rs5569)、γ-氨基丁酸A型受體(rs3219151、rs2279020)、兒茶酚-O-甲基轉(zhuǎn)移酶(rs4680)、五羥色胺2A受體(rs6311、rs6313)和5-HTTLPR基因10個(gè)位點(diǎn)的多態(tài)性,比較不同睡眠質(zhì)量組的基因型分布,了解影響睡眠質(zhì)量的易感基因。4)采用MethylTarget技術(shù)檢測(cè)五羥色胺轉(zhuǎn)運(yùn)體(5-HTT)啟動(dòng)子區(qū)DNA甲基化程度。5)應(yīng)用SHEsis軟件進(jìn)行單體型分析,廣義多因子降維法(GMDR)構(gòu)建基因-基因、基因-環(huán)境交互作用對(duì)睡眠質(zhì)量影響的最佳模型。應(yīng)用多元Logistic回歸分析方法進(jìn)行基因-基因、基因-環(huán)境的交互作用危險(xiǎn)性分析,計(jì)算交互作用風(fēng)險(xiǎn)的比值比(OR)及其95%可信區(qū)間(CI)。結(jié)果:1)本次研究共發(fā)放調(diào)查問(wèn)卷2,650份,收回有效合格問(wèn)卷2,400份,問(wèn)卷有效率為90.6%。2)本次調(diào)查的新疆不同職業(yè)人群職業(yè)緊張得分中小學(xué)教師、野外油田工人、鐵路職工高于大學(xué)教師、行政管理人員和銀行職員(P0.05);工齡10~20年者職業(yè)任務(wù)得分高于工齡20年者(P0.05);男性職業(yè)任務(wù)、個(gè)體緊張反應(yīng)得分高于女性(P0.05);少數(shù)民族職業(yè)任務(wù)和個(gè)體緊張反應(yīng)得分高于漢族(P0.05);碩士及以上學(xué)歷者職業(yè)任務(wù)得分高于本科和大中專以下學(xué)歷者(p0.05);吸煙者職業(yè)任務(wù)和個(gè)體緊張反應(yīng)得分高于未吸煙者(p0.05);飲酒者職業(yè)任務(wù)得分高于未飲酒者(p0.05)。3)不同工種外在付出、內(nèi)在投入和工作回報(bào)得分有差異(p0.05),其中野外油田工人、中小學(xué)教師和鐵路職工付出-回報(bào)不平衡;不同工齡外在付出、內(nèi)在投入和工作回報(bào)得分有差異(p0.05);不同性別工作回報(bào)、內(nèi)在投入得分差異有統(tǒng)計(jì)學(xué)意義(p0.05),其中工作回報(bào)得分女性高于男性(p0.05),內(nèi)在投入得分男性高于女性(p0.05),提示男性付出-回報(bào)不平衡;不同文化程度外在付出、工作回報(bào)和內(nèi)在投入得分差異有統(tǒng)計(jì)學(xué)意義(p0.05),其中碩士及以上學(xué)歷者付出-回報(bào)不平衡;不同吸煙狀況工作回報(bào)和內(nèi)在投入得分差異有統(tǒng)計(jì)學(xué)意義(p0.05),其中吸煙者付出-回報(bào)不平衡。4)新疆不同職業(yè)人群psqi總分為(4.92±3.15)分,以psqi總分5分作為判斷睡眠質(zhì)量問(wèn)題的標(biāo)準(zhǔn),新疆不同職業(yè)人群睡眠質(zhì)量問(wèn)題發(fā)生率為36.4%;大學(xué)教師、野外油田工人和鐵路職工睡眠質(zhì)量得分高于中小學(xué)教師、行政管理人員和銀行員工(p0.05);工齡20年和工齡10~20年者睡眠質(zhì)量得分高于工齡≤10年者(p0.05),隨著工齡的增加,研究對(duì)象的睡眠質(zhì)量隨之下降;女性睡眠質(zhì)量得分高于男性(p0.05),離異或喪偶者睡眠質(zhì)量得分高于未婚者(p0.05);吸煙者睡眠質(zhì)量得分高于不吸煙者(p0.05)。5)不同緊張強(qiáng)度組在psqi總分、主觀睡眠質(zhì)量、睡眠時(shí)間、睡眠障礙、催眠藥物和日間功能障礙上得分差異有統(tǒng)計(jì)學(xué)意義(p0.05);其中高度緊張強(qiáng)度組psqi總分、睡眠時(shí)間、睡眠障礙和日間功能障礙高于中度緊張組和低度緊張組(p0.05),高度緊張組催眠藥物得分高于低度緊張組(p0.05),中度緊張組主觀睡眠質(zhì)量得分高于低度緊張組(p0.05),隨著緊張程度的增高,睡眠質(zhì)量越差。不同付出-回報(bào)失衡組在psqi總分、入睡時(shí)間、睡眠時(shí)間、睡眠障礙、催眠藥物和日間功能障礙上得分差異有統(tǒng)計(jì)學(xué)意義(p0.05),高付出-低回報(bào)組得分均高于低付出-高回報(bào)組(p0.05),高付出-低回報(bào)組睡眠質(zhì)量較差。6)高度緊張組血漿5-ht、ne水平高于中、低度職業(yè)緊張組(p0.05);高付出-低回報(bào)組血漿ne水平高于低付出-高回報(bào)組(p0.05)。偏相關(guān)分析發(fā)現(xiàn),職業(yè)任務(wù)和個(gè)體緊張反應(yīng)與5-ht和ne呈正相關(guān)關(guān)系(p0.05),個(gè)體應(yīng)對(duì)資源得分與da呈負(fù)相關(guān)關(guān)系(p0.05);外在付出與ne呈正相關(guān)關(guān)系(p0.05),內(nèi)在投入與5-ht呈正相關(guān)關(guān)系(p0.05);個(gè)體緊張反應(yīng)和外在付出均與gaba水平呈負(fù)相關(guān)關(guān)系(p0.05)。睡眠質(zhì)量問(wèn)題組的5-ht、da和e水平高于非睡眠質(zhì)量問(wèn)題組(p0.05)。偏相關(guān)分析發(fā)現(xiàn),5-ht、ne、da和e水平與睡眠質(zhì)量部分因子呈正相關(guān)關(guān)系(p0.05),gaba水平與睡眠時(shí)間呈負(fù)相關(guān)關(guān)系(p0.05)。7)多元logistic回歸分析發(fā)現(xiàn)影響睡眠質(zhì)量的因素為:工種、個(gè)體緊張反應(yīng)、外在付出、工作回報(bào)、內(nèi)在投入、5-ht、ne和da;通過(guò)對(duì)職業(yè)緊張-生理緊張反應(yīng)(神經(jīng)遞質(zhì))-睡眠質(zhì)量之間復(fù)雜關(guān)聯(lián)的結(jié)構(gòu)方程模型發(fā)現(xiàn),職業(yè)緊張、付出-回報(bào)失衡、生理緊張反應(yīng)對(duì)睡眠質(zhì)量有直接影響,職業(yè)緊張對(duì)生理緊張反應(yīng)有直接影響,生理緊張反應(yīng)是職業(yè)緊張對(duì)睡眠質(zhì)量影響的中介因素。8)多巴胺d2受體(drd2)基因、去甲腎上腺素轉(zhuǎn)運(yùn)體(net)基因、γ-氨基丁酸a型受體(gabra)基因、兒茶酚-o-甲基轉(zhuǎn)移酶(comt)基因、五羥色胺2a受體(5-htr2a)基因和5-httlpr基因的10個(gè)tagsnps位點(diǎn)不同睡眠質(zhì)量組基因型分布均符合hardy-weinberg平衡定律。9)睡眠質(zhì)量遺傳易感性分析:?drd2受體基因rs1800497位點(diǎn)a1a1基因型入睡時(shí)間、睡眠時(shí)間、睡眠障礙和催眠藥物得分均高于a2a2基因型組(p0.05);a1a1基因型(or=1.938,95%ci:1.228-3.058)是睡眠質(zhì)量問(wèn)題的易感基因型;?net基因rs5569位點(diǎn)aa基因型主觀睡眠質(zhì)量和睡眠效率得分高于gg基因型(p0.05);ag基因型(or=1.569,95%ci:1.109-2.220)和aa基因型(or=2.231,95%ci:1.353-3.678)是睡眠質(zhì)量問(wèn)題的易感基因型;?gabra1基因rs2279020位點(diǎn)g等位基因突變頻率為64.9%;gg基因型主觀睡眠質(zhì)量和睡眠效率得分高于aa基因型和ag基因型(p0.05);gg基因型(or=1.183,95%ci:1.064-2.015)是睡眠質(zhì)量問(wèn)題的易感基因型;?5-htr2a基因rs6311位點(diǎn)gg基因型主觀睡眠質(zhì)量和日間功能障礙得分均高于aa基因型組和ag基因型組(p0.05),r6313位點(diǎn)cc基因型主觀睡眠質(zhì)量和睡眠效率得分高于tt基因型(p0.05);rs6311位點(diǎn)的gg基因型(or=1.929,95%ci:1.222-3.047)和rs6313位點(diǎn)cc基因型(or=3.344,95%ci:2.062-5.422)是睡眠質(zhì)量問(wèn)題的易感基因型;?5-httlpr基因ss基因型主觀睡眠質(zhì)量得分高于ll基因型組(p0.05);ss基因型(or=2.118,95%ci:1.053-4.257)是睡眠質(zhì)量問(wèn)題的易感基因型;?comt基因rs4680位點(diǎn)不同基因型組間睡眠質(zhì)量得分沒(méi)有差異(p0.05);logistic回歸顯示rs4680位點(diǎn)多態(tài)性對(duì)睡眠質(zhì)量沒(méi)有影響。10)高職業(yè)緊張組5-htt基因啟動(dòng)子區(qū)cpg2、cpg4、cpg6、cpg8、cpg12、cpg13、cpg16、cpg17、cpg47和cpg58位點(diǎn)甲基化水平低于低職業(yè)緊張組(p0.05);睡眠質(zhì)量問(wèn)題組5-htt基因啟動(dòng)子區(qū)cpg5、cpg8、cpg13、cpg14、cpg16、cpg30、cpg34和cpg47位點(diǎn)甲基化水平低于非睡眠質(zhì)量問(wèn)題組(p0.05);睡眠質(zhì)量問(wèn)題組中高度職業(yè)緊張組cpg13、cpg16、cpg34和cpg47位點(diǎn)甲基化水平低于低度職業(yè)緊張組(p0.05)。11)通過(guò)分析單倍體型與睡眠質(zhì)量問(wèn)題易感性的關(guān)系發(fā)現(xiàn)drd2基因rs1799732位點(diǎn)和rs1800497位點(diǎn)的i-a1為睡眠質(zhì)量的危險(xiǎn)單倍型,i-a2為保護(hù)單倍型;net基因rs2242446位點(diǎn)和rs5569位點(diǎn)的t-a為睡眠質(zhì)量的危險(xiǎn)單倍型,t-g為保護(hù)單倍型;5-htr2a基因rs6313和rs6311位點(diǎn)的g-c為睡眠質(zhì)量危險(xiǎn)單倍型,g-t為保護(hù)單倍型;gabra基因rs2279020位點(diǎn)和rs3219151位點(diǎn)的a-c為睡眠質(zhì)量保護(hù)單倍型,g-c為危險(xiǎn)單倍型。12)采用gmdr軟件分析,rs1800497、rs2279020和rs6313位點(diǎn)組成的交互模型是所生成的基因-基因交互模型中的最佳模型。進(jìn)一步的logistic回歸分析發(fā)現(xiàn),drd2基因rs1800497位點(diǎn)、grbra1基因rs2279020位點(diǎn)和5-htr2a基因rs6313位點(diǎn)的交互作用能增加新疆不同職業(yè)人群睡眠質(zhì)量問(wèn)題的患病風(fēng)險(xiǎn)(OR=1.186,95%CI:1.015-3.432);rs6313、職業(yè)緊張和ERI組成的交互作用模型為最佳基因-環(huán)境交互作用模型,進(jìn)一步的Logistic回歸分析發(fā)現(xiàn),三者之間的交互作用能使新疆不同職業(yè)人群睡眠質(zhì)量問(wèn)題的患病風(fēng)險(xiǎn)增加(OR=1.171,95%CI:1.012-1.355)。結(jié)論:1)男性、少數(shù)民族、工齡10~20年、已婚、吸煙或飲酒的中小學(xué)教師、野外油田工人、鐵路職工職業(yè)緊張得分較高。男性、高學(xué)歷的野外油田工人、中小學(xué)教師和鐵路職工付出-回報(bào)不平衡。2)研究人群PSQI總分和睡眠質(zhì)量問(wèn)題患病率較高,說(shuō)明睡眠質(zhì)量較差。3)隨著緊張程度的增加,睡眠質(zhì)量隨之下降。付出-回報(bào)失衡越重,睡眠質(zhì)量越差。4)神經(jīng)遞質(zhì)對(duì)職業(yè)緊張和睡眠質(zhì)量產(chǎn)生影響;工種(鐵路職員、野外油田工人)、個(gè)體緊張反應(yīng)、外在付出、內(nèi)在投入、5-HT、NE和DA是睡眠質(zhì)量的危險(xiǎn)因素,而工作回報(bào)是睡眠質(zhì)量問(wèn)題的保護(hù)因素;職業(yè)緊張、付出-回報(bào)失衡、生理緊張反對(duì)睡眠質(zhì)量有直接影響,職業(yè)緊張對(duì)生理緊張反應(yīng)有直接影響,生理緊張反應(yīng)是職業(yè)緊張對(duì)睡眠質(zhì)量影響的中介因素。5)DRD2受體基因rs1800497位點(diǎn)A1A1基因型、NET基因rs5569位點(diǎn)AA基因型、GABRA1基因rs2279020位點(diǎn)GG基因型、5-HTR2A基因rs6311位點(diǎn)GG基因型和r6313位點(diǎn)CC基因型以及5-HTTLPR基因SS基因型是睡眠質(zhì)量問(wèn)題的易感基因型。6)5-HTT基因啟動(dòng)子區(qū)DNA甲基化水平降低,可增加職業(yè)緊張和睡眠質(zhì)量問(wèn)題的風(fēng)險(xiǎn),5-HTT基因啟動(dòng)子區(qū)DNA甲基化水平在職業(yè)緊張與睡眠質(zhì)量相關(guān)性中有一定的調(diào)控作用。7)DRD2基因、NET基因、GABRA基因和5-HTR2A基因tag SNPs位點(diǎn)可以通過(guò)單倍型的聯(lián)合影響睡眠質(zhì)量。8)DRD2基因rs1800497位點(diǎn)、GRBRA1基因rs2279020位點(diǎn)和5-HTR2A基因rs6313位點(diǎn)的基因-基因交互作用和rs6313、職業(yè)緊張和ERI組成的環(huán)境-基因交互作用能增加新疆不同職業(yè)人群睡眠質(zhì)量問(wèn)題的患病風(fēng)險(xiǎn)。
[Abstract]:Objective: To investigate the occupational stress, sleep quality and its influencing factors in different occupational groups in Xinjiang, and to analyze the relationship between the two and study the effects of neurotransmitters on occupational stress and sleep quality in different occupational groups in Xinjiang. The relationship between the polymorphism of DRD2, NET, COMT, GABRA, 5-HTR2A and 5-HTTLPR and the quality of sleep is discussed and the different sleep is compared. The difference of DNA methylation in the 5-HTT gene promoter region between the sleep quality group and the different tension groups, and to explore the role of epigenetics in the relationship between occupational stress and sleep quality. The effect of gene gene, gene environment (occupational stress) interaction on the sleep quality of different occupational groups in Xinjiang. To improve the different occupations in Xinjiang. The epidemiological data of occupational stress and quality of sleep in the population provided a scientific basis for making and improving the quality of sleep in different occupational groups in Xinjiang. Methods: 1) a multi stage sampling method was adopted in this study, using the occupational stress scale, the pay return imbalance scale, the Pittsburgh sleep quality scale, and the 2650 different occupational groups in Xinjiang. 240 people were randomly selected as the target of neurotransmitters, and the plasma 5-HT, NE, E, DA, GABA levels were detected by ELISA, and the structural equation model was used to analyze occupational stress, neurotransmitters and the relationship between sleep quality and.3) by stratified random extraction of 720 research subjects and using SNaPshot technique to detect dopamine D2 receptor (rs1799732,) Rs1800497), the norepinephrine transporter (rs2242446, rs5569), gamma aminobutyric acid A receptor (rs3219151, rs2279020), catechol -O- methyltransferase (rs4680), five serotonin 2A receptor (rs6311, rs6313) and 5-HTTLPR gene polymorphisms, compared with the genotype distribution of different sleep quality groups, understand the susceptible basis of sleep quality. .4) using MethylTarget technology to detect DNA methylation degree in the promoter region of five serotonin transporter (5-HTT).5) using SHEsis software for haplotype analysis and generalized multiple factor reduction (GMDR) construction of gene gene gene, gene environment interaction on the best model of sleep quality. Multiple Logistic regression analysis was used to carry out genes. - gene, gene - environment interaction risk analysis, the ratio Ratio ratio (OR) and 95% confidence interval (CI) of the interaction risk (CI). Results: 2650 questionnaires were issued in this study, 2400 valid questionnaires were collected, and the efficiency of the questionnaire was 90.6%.2) in this survey, the occupational stress scores in different occupational groups in Xinjiang Teachers, field workers, railway workers were higher than university teachers, administrators and bank staff (P0.05); the career tasks of 10~20 years were higher than those of 20 years (P0.05); male occupational tasks, individual tension response scores were higher than women (P0.05); ethnic minority occupational tasks and individual tension response scores were higher than those of the Han (P0.05); master's degree (P0.05); The professional task scores of those with or above were higher than those of the undergraduate and junior secondary school (P0.05); the scores of occupational tasks and individual stressful responses of smokers were higher than those of non smokers (P0.05); the professional task scores of drinkers were higher than those of non drinkers (P0.05).3) and the internal input and work return score were different (P0.05), among them, the field was different (P0.05). Oil field workers, primary and middle school teachers and railway workers pay unbalance; the external pay, internal investment and work return score differ (P0.05); the difference in the internal input score is statistically significant (P0.05), among which the score of work returns is higher than that of men (P0.05), and the inner input is higher than that of the female. Sex (P0.05) showed that male pay and return imbalances; the difference of external pay, work return and internal input were statistically significant (P0.05), in which the payback and return were not balanced; the difference of work return and internal investment in different smoking conditions was statistically significant (P0.05), in which smokers paid. - return imbalanced.4) the total score of PSQI in different occupational groups in Xinjiang was (4.92 + 3.15), and the total score of PSQI was 5 points as the standard for judging the quality of sleep. The incidence of sleep quality of different occupational groups in Xinjiang was 36.4%; university teachers, field workers and railway workers were higher than primary and secondary school teachers, administrators and silver The sleep quality scores of 20 years and 10~20 years were higher than those of less than 10 years (P0.05). The sleep quality of the subjects decreased with the increase of working age; the sleep quality scores of women were higher than those of men (P0.05), and the sleep quality scores of divorced or widowed persons were higher than those of unmarried men (P0.05), and the sleep quality scores of smokers were higher than those of the unmarried people (P0.05). Smokers (P0.05).5) in the PSQI total score of different intensity groups, the scores of subjective sleep quality, sleep time, sleep disorder, hypnotic drugs and daytime dysfunction were statistically significant (P0.05), and the total score of PSQI, sleep time, sleep disorder and daytime dysfunction in the high tension group were higher than those in the moderate stress group and the low tension group (P0 .05), in the high tension group, the scores of hypnotic drugs were higher than the low tension group (P0.05). The subjective sleep quality score of the moderate stress group was higher than the low tension group (P0.05), the worse the sleep quality was with the increase of tension. The different pay return imbalance group was in the PSQI total, sleep time, sleep disorder, hypnotic drug, and daytime dysfunction. The score difference was statistically significant (P0.05), the scores of the high pay and low return group were higher than the low pay group (P0.05), the high pay and low return group had poor sleep quality.6) the Plasma 5-HT, the ne level was higher than the low occupational stress group (P0.05), and the plasma NE level in the high pay low return group was higher than the low pay high return group (P0.05). Partial phase was higher than the low pay and high return group (P0.05). The relationship between occupational task and individual stress was positively correlated with 5-HT and ne (P0.05), and there was a negative correlation between individual coping resources and DA (P0.05); external pay was positively correlated with ne (P0.05), and intrinsic input was positively correlated with 5-HT (P0.05); individual tension response and external pay were negatively correlated with GABA (P). 0.05) the level of 5-HT, DA and E in the sleep quality group was higher than that of the non sleep quality group (P0.05). Partial correlation analysis found that the level of 5-HT, NE, DA and E had a positive correlation with the quality of sleep (P0.05), and the level of GABA was negatively correlated with the sleep time (P0.05).7) multiple regression analysis found that the factors affecting the quality of sleep were: work Species, individual stress response, external pay, work return, internal input, 5-HT, NE, and Da; through a structural equation model of the complex association between occupational stress physiological stress response (neurotransmitter) - sleep quality, occupational stress, pay return imbalance, physiological tension response directly affect the quality of sleep, and occupational stress to physiological stress The reaction has a direct effect. The physiological stress is the mediator of occupational stress on the quality of sleep.8) the dopamine D2 receptor (DRD2) gene, the norepinephrine transporter (net) gene, the gamma Aminobutyrate receptor (gabra) gene, the catechol -o- methyltransferase (COMT) gene, the five serotonin 2A receptor (5-HTR2A) gene and the 5-HTTLPR gene 10. The genotype distribution of different sleep quality groups in tagSNPs loci was consistent with the Hardy-Weinberg equilibrium law.9) genetic susceptibility analysis of sleep quality: the DRD2 receptor gene rs1800497 locus a1a1 genotypic sleep time, sleep time, sleep disorder and hypnotic drug score were higher than the a2a2 type group (P0.05); a1a1 genotype (or=1.938,95%ci:1.228-3.0). 58) is the susceptible genotype of sleep quality problems; the score of the subjective sleep quality and sleep efficiency of the rs5569 locus AA genotype of the net gene is higher than that of the GG genotype (P0.05), and the Ag genotype (or=1.569,95%ci:1.109-2.220) and AA genotype (or=2.231,95%ci:1.353-3.678) are the susceptible genotypes of the sleep mass problem; the rs2279020 locus of the GABRA1 gene is the allele of the G allele. Because the frequency of mutation was 64.9%, the score of subjective sleep quality and sleep efficiency of GG genotypes was higher than that of AA genotype and Ag genotype (P0.05), and GG genotype (or=1.183,95%ci:1.064-2.015) was a susceptible genotype of sleep quality problems, and the subjective sleep sleep quality and daytime dysfunction score of GG genotype of 5-HTR2A gene were higher than that of the AA genotype group at the 5-HTR2A gene rs6311 site. And the Ag genotype group (P0.05), the score of the subjective sleep quality and sleep efficiency of the r6313 locus CC genotype was higher than that of the TT genotype (P0.05), and the GG genotypes (or=1.929,95%ci:1.222-3.047) of the rs6311 locus and the CC genotype of the rs6313 loci (or=3.344,95%ci:2.062-5.422) were the susceptible genotypes of the sleep quality problems; The quality score was higher than that of the LL genotype group (P0.05); the SS genotype (or=2.118,95%ci:1.053-4.257) was a susceptible genotype of sleep quality problems; there was no difference in the sleep quality score between the rs4680 loci of the COMT gene (P0.05); logistic regression showed that the rs4680 locus polymorphism did not affect the quality of sleep in.10) and the 5-HTT base of the high occupational stress group Cpg2, cpg4, cpg6, cpg8, cpg12, cpg13, cpg16, cpg17, cpg47, and cpg58 methylation levels were lower than those of the low occupational stress group (P0.05). The level of methylation at cpg13, cpg16, cpg34, and cpg47 loci in the high occupational stress group was lower than the low occupational stress group (P0.05).11) by analyzing the relationship between the haplotype and the sleep quality problem, the DRD2 gene rs1799732 site and the rs1800497 locus i-a1 were the dangerous haplotypes of the sleep quality, and i-a2 was the protective haplotype; The T-A of the loci and rs5569 loci is a dangerous haplotype of sleep quality, T-G is the protection haplotype, and the G-C of the 5-HTR2A gene rs6313 and rs6311 loci is the haplotype of the sleep quality risk, G-T is the haplotype, the rs2279020 and rs3219151 loci of the gabra gene are the haplotype of the sleep quality protection. Analysis, the interaction model of the rs1800497, rs2279020 and rs6313 sites is the best model in the gene gene interaction model. Further logistic regression analysis found that the interinteraction of the DRD2 gene rs1800497 site, the grbra1 gene rs2279020 site and the 5-HTR2A gene rs6313 site could increase the sleep quality of different occupational populations in Xinjiang. The risk of the disease (OR=1.186,95%CI:1.015-3.432); the interaction model of rs6313, occupational stress and ERI was the best gene environment interaction model. Further Logistic regression analysis found that the interaction between the three groups could increase the risk of sleep quality problems in different occupational groups in Xinjiang (OR=1.171,95%CI:1. 012-1.355) conclusion: 1) male, ethnic minority, working age 10~20, married, smoking or drinking primary and secondary school teachers, field workers, railway workers have higher occupational stress scores. Male, high educated field workers, primary and secondary school teachers and railway workers pay off balance.2) study the total score of PSQI and the prevalence rate of sleep quality problems The higher, poor sleep quality.3) with the increase of tension, the quality of sleep decreased. The heavier the pay - return imbalance, the worse the quality of sleep.4); the neurotransmitters had an impact on occupational stress and quality of sleep; the types of work (railway staff, field workers), individual stress reactions, external pay, internal input, 5-HT, NE and DA were sleep quality. The risk factors of quantity, and work reward is the protective factor of sleep quality problems, occupational stress, pay return imbalance, physiological tension against sleep quality has direct influence, occupational stress has direct effect on physiological stress response, physiological tension reaction is the intermediary factor of occupational stress on sleep quality.5) DRD2 receptor gene rs1800497 position Point A1A1 genotypes, NET gene rs5569 locus AA genotypes, GABRA1 gene rs2279020 loci GG genotypes, 5-HTR2A gene rs6311 loci GG genotypes and r6313 loci CC genotypes and sleep quality problems are susceptible genotypes. There is a certain correlation between the DNA methylation level of 5-HTT gene promoter and the quality of sleep in the risk of sleep quality.
【學(xué)位授予單位】：新疆醫(yī)科大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2017
【分類號(hào)】：R13
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本文編號(hào)：2020158