本文關(guān)鍵詞： 艾滋病 注射吸毒 空間分析 多水平模型 地理加權(quán)回歸模型　出處：《中國(guó)疾病預(yù)防控制中心》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：目的： 了解并分析1995-2011年我國(guó)吸毒者艾滋病感染的空間特點(diǎn),并在感染及數(shù)據(jù)可能存在聚集性的情況下,分析影響其感染艾滋病病毒(Human immunodeficieney virus,HIV)的個(gè)體因素和宏觀因素。 研究方法： 利用1995-2011年間以注射吸毒為途徑感染HIV者和艾滋病病人(Acquired Immune Deficiency Syndrome,AIDS)數(shù)據(jù),分別以省份和區(qū)縣為水平進(jìn)行空間聚集性分析并生成熱點(diǎn)區(qū)縣的中心位點(diǎn)。 收集我國(guó)2011哨點(diǎn)監(jiān)測(cè)的吸毒者數(shù)據(jù)進(jìn)行我國(guó)吸毒者艾滋病感染個(gè)體影響因素的分析,利用三水平Logistic模型,分析我國(guó)社區(qū)吸毒者艾滋病流行的影響因素,計(jì)算相關(guān)變量的參數(shù)估計(jì)值及OR值。 建立地理加權(quán)回歸模型探究社會(huì)經(jīng)濟(jì)因素對(duì)我國(guó)吸毒者艾滋病感染的影響,為了減少自變量間的共線性,通過主成分分析從經(jīng)濟(jì)、交通、社會(huì)保障與安全及衛(wèi)生四方面各提取一個(gè)綜合變量作為自變量,并定義2007年-2011年全國(guó)累計(jì)注射吸毒者艾滋病報(bào)告密度為應(yīng)變量擬合地理加權(quán)回歸模型,分析宏觀因素對(duì)我國(guó)吸毒者艾滋病感染的影響,以得到全國(guó)各省份綜合變量的局部系數(shù)值。 研究結(jié)果： 1995-2011年間,我國(guó)注射吸毒者艾滋病感染分布并不均勻,經(jīng)空間全局自相關(guān)檢驗(yàn),我國(guó)累積注射吸毒者艾滋病感染在全國(guó)范圍內(nèi)存在聚集性(Moran's I=0.066,Z值=32.629且P0.05),并且逐年注射吸毒者艾滋病感染均具有聚集性。1995-2011年間局部熱點(diǎn)多位于西部新疆維吾爾自治區(qū)及西南部云南、廣西壯族自治區(qū)、四川省等。其中,1995-2003年期間,西部地區(qū)熱點(diǎn)局限于新疆省,西南部地區(qū)熱點(diǎn)有由從西向東轉(zhuǎn)移的趨勢(shì)。2004-2011年期間,西部地區(qū)熱點(diǎn)位置仍處于新疆維吾爾自治區(qū),西南部地區(qū)熱點(diǎn)有由從邊境向內(nèi)陸轉(zhuǎn)移的趨勢(shì)。 2011年我國(guó)哨點(diǎn)監(jiān)測(cè)共調(diào)查社區(qū)吸毒人員42011人,HIV感染率為5.01%(95%CI：4.80%,5.22%)。零模型分析結(jié)果顯示顯示社區(qū)吸毒者艾滋病感染在區(qū)縣水平、省份水平上均有聚集性。進(jìn)一步通過三水平Logistic模型分析影響因素,結(jié)果顯示,感染丙肝(OR=6.404,95%CI:5.411,7.580)、共用針具(OR=4.043,95%CI：3.545,4.618)、注射吸毒(OR=1.736,95%CI:1.391,2.167)、少數(shù)民族(OR=1.728,95%CI:1.446,2.065)等人口學(xué)特征及行為學(xué)因素是社區(qū)吸毒者感染HIV的危險(xiǎn)因素。 2007-2011年間,我國(guó)累積注射吸毒者艾滋病報(bào)告密度存在空間上的聚集性(Moran's1=0.102,Z值=2.472且P0.05)。由地理加權(quán)回歸模型可得,經(jīng)濟(jì)水平系數(shù)在大多數(shù)省份為負(fù)值。交通系數(shù)為另一個(gè)系數(shù)多為負(fù)值的社會(huì)經(jīng)濟(jì)綜合變量。衛(wèi)生水平系數(shù)、社會(huì)保障與安全系數(shù)在省級(jí)水平上多為正值。經(jīng)地理回歸模型擬合后,對(duì)模型預(yù)測(cè)各省艾滋病感染數(shù)與真實(shí)值的差值(殘差)進(jìn)行全局自相關(guān)檢驗(yàn),未發(fā)現(xiàn)空間自相關(guān)性(Moran's1=0.030,Z值=1.970,P=0.56)。模型校正后R2=62.5%、Condition Number均小于30,說明模型擬合效果良好。 研究結(jié)論： 1995-2011年間我國(guó)注射吸毒艾滋病感染存在空間上的聚集性,近年來局部熱點(diǎn)數(shù)量有所增加出現(xiàn)由邊境向內(nèi)陸轉(zhuǎn)移的趨勢(shì)。在分析我國(guó)吸毒者艾滋病感染的影響因素時(shí),多水平模型可以用于處理我國(guó)艾滋病哨點(diǎn)監(jiān)測(cè)數(shù)據(jù),并得出較為真實(shí)的結(jié)論,但仍需在群體水平繼續(xù)探索相應(yīng)的影響因素。地理加權(quán)回歸模型可被用于分析我國(guó)宏觀因素對(duì)吸毒者艾滋病感染流行的影響,可體現(xiàn)出我國(guó)各省經(jīng)濟(jì)、交通、社會(huì)保障與安全及衛(wèi)生水平對(duì)其吸毒者艾滋病感染流行有不同的響應(yīng)性。
[Abstract]:Purpose : To understand and analyze the spatial characteristics of HIV infection among drug users in China from 1995 to 2011 , and to analyze the individual factors and macro - factors affecting the infection of human immunodeficiency virus ( HIV ) in the presence of infection and data aggregation . Study method : The data of HIV and AIDS patients were infected by injecting drug use from 1995 to 2011 , and spatial clustering analysis was conducted at the provincial and district level , respectively , and the central site of hot spot district was generated . The influence factors of HIV / AIDS infection among drug users in our country were analyzed by collecting the data of drug users monitored in 2011 . Using the three - level Logistic model , the influencing factors of AIDS epidemic among community drug users in our country were analyzed , and the parameters estimation value and OR value of relevant variables were calculated . The effects of socio - economic factors on HIV infection in our country were investigated by establishing a geographical weighted regression model . In order to reduce the collinearity among the variables , an integrated variable was extracted from the four aspects of economy , transportation , social security and safety and health through principal component analysis . Results of the study : During the period from 1995 to 2011 , the distribution of AIDS infection among injecting drug users in China was not uniform , and the global self - correlation test was conducted in China . In the period 1995 - 2011 , the hot spots in the western region were limited to Xinjiang and Southwest Yunnan , Guangxi Zhuang Autonomous Region , Sichuan Province and so on . In 2011 , China sentinel surveillance co - investigated 42011 community drug users with HIV infection rate of 5.01 % ( 95 % CI : 4.80 % , 5.22 % ) . The results of the zero - model analysis showed that the prevalence of HIV infection in community drug users was aggregated at the county level and in the provincial level . The results showed that the factors influencing the infection of HIV by community drug users were the demographic characteristics and behavioral factors such as hepatitis C ( OR = 6.404 , 95 % CI : 5.411 , 7.580 ) , common needle set ( OR = 1.0736 , 95 % CI : 1.391 , 2.167 ) and ethnic minorities ( OR = 1.728 , 95 % CI : 1.446 , 2.065 ) . During the period from 2007 to 2011 , there was a spatial clustering of AIDS report density ( Moran ' s1 = 0.102 , Z = 2.472 and P0.05 ) . Based on the geographic regression model , the economic horizontal coefficient is negative in most provinces . The traffic coefficient is a social and economic comprehensive variable with more negative values . The health level coefficient , social security and safety factor are more positive at the provincial level . After fitting by the georegression model , the difference between the number of AIDS infection and the real value ( residual ) is globally self - correlated , and no spatial autocorrelation is found ( Moran ' s1 = 0.030 , Z = 1.970 , P = 0.56 ) . After model calibration R2 = 62.5 % , Condition Number is less than 30 , which shows that the model fitting effect is good . Conclusions of the study : In the period of 1995 - 2011 , there is a spatial aggregation of HIV / AIDS infection in China . In recent years , the number of local hot spots has increased from the border to the inland . In the analysis of the factors affecting the HIV infection in our country , the multi - level model can be used to deal with the AIDS sentinel surveillance data in China , and to obtain a more realistic conclusion . The geographical weighted regression model can be used to analyze the impact of macro - factors on HIV infection in China .

【學(xué)位授予單位】：中國(guó)疾病預(yù)防控制中心
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：R512.91

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本文編號(hào)：1523349