【摘要】：目的:本研究目的是尋找中國北方≥60y老年人輕度認知障礙(Mild Cognitive Impairment,MCI)的影響因素。通過分析生活方式、膳食因素、生化指標、免疫指標、血漿脂肪酸(Fatty Acid,FA)與MCI的關系,探究MCI的影響因素,為尋找MCI的有效干預手段以及為以后對MCI進一步的研究提供新的線索。方法:在河北省石家莊市用簡單隨機抽樣的方法隨機抽取三個社區(qū)開展一項病例對照研究,以三個社區(qū)的所有60y的老年人為研究對象。本研究研究對象的選取分為兩步:首先根據社區(qū)居民健康檔案按照納入和排除標準對所有老年人進行初步篩選;然后再進行基本資料調查后,結合納入和排除標準對老年人進行再次篩選。最后根據MCI的診斷標準、問卷和體檢數據,由衛(wèi)生部北京醫(yī)院精神內科專家做出最終診斷,找出該三個社區(qū)中的全部MCI患者;再根據正常認知診斷標準確定三個社區(qū)中的全部正常認知者,利用簡單隨機抽樣的方法抽取得到對照組,使對照組與MCI組的數量比為1:1。本研究的工作主要包括對研究對象進行認知狀況、生活方式和膳食因素等資料的調查;并及時開展血液生化指標、免疫指標以及血漿FA等指標的實驗室檢測。在后期數據處理中,本文將通過分析生活方式、膳食因素、血脂指標、免疫指標、脂肪酸(Fatty Acid,FA)與MCI的關系,尋找MCI的影響因素,具體分析過程為:先對各項指標在兩組中的分布進行初步分析;然后用單因素logistic回歸分析探討生活方式、膳食因素、生化指標、代謝性疾病、免疫指標以及血漿脂肪酸各自對MCI的影響;在進行單因素分析后,將單因素分析中有統計學意義的變量納入多因素logistic回歸模型,得出MCI的獨立影響因素。在結果分析中,分類變量的描述用例數(n)和構成比(%),定量變量的描述用均數(x)±標準差(S)或中位數(M)和上下四分位數(Q1,Q3)表示;分類變量的兩組間比較采用χ2檢驗,不符合條件者采用秩和檢驗;定量變量的兩組間比較采用t檢驗,不符合使用條件者采用wilcoxon符號秩和檢驗。MCI的影響因素探究先使用單因素logistic回歸分析,然后使用多因素logistic回歸模型進行分析。結果:1各項指標在不同認知狀況人群中的分布年齡(p=0.0114)、受教育程度(p0.0001)與MCI有明顯的關系。與對照組相比,MCI組中低年齡段60-64y所占比例低(42.74%55.65%),中間年齡段65-69y(33.87%23.39%)、70-74y(17.74%8.87%)所占比例高于對照組,而高年齡段75-y(5.65%12.1%)占的比例又再次低于對照組。MCI中受教育程度較高的人群占的比例低于對照組;MCI組中參加學習活動的比例低于對照組(12.1%18.55%),MCI的做家務時間明顯少于對照組(p.0001);MCI組偶爾吸煙(6.45%5.65%)和經常吸煙(11.29%4.03%,p=0.0908)的人占的比例均高于對照組;而兩組中居住狀況(p=0.7757)、娛樂活動(p=0.9265)、飲酒(p=0.3903)、靜坐時間(p=0.1599)、睡眠時間(p=0.5955)的分布沒有明顯差異。膳食因素中,對照組攝入蛋類的頻次多于MCI組、而堅果類的攝入頻率比MCI少。米面雜糧等、蔬菜菌藻、水果、禽肉、畜肉、淡水魚貝類、海水魚貝類、豆類及制品等在MCI組和正常組中的分布也沒有差異。MCI組中 HDL-C(1.141.18)、ApoA-1(1.511.42)的水平均低于對照組,而ApoB(0.910.83)、ApoE(4.193.58)的水平均高于對照組,但是兩組中其他指標 TC、TG、LDL-C、HDL-C/LDL-C、PL(a)、LP-PLA2 的水平在兩組中的差異并不明顯。MCI中患高血壓(54.03%40.32%)、血脂異常(46.77%32.26%)、糖尿病(17.74%8.06%)的比例均高于對照組。血脂異常包含的三種疾病高膽固醇血癥、高甘油三酯血癥、低高密度脂蛋白膽固醇血癥、貧血在兩組的分布并沒有明顯的差別。免疫指標CRP、IL-6、TNF-α在MCI和對照組水平的分布沒有明顯的差異。本研究還重點分析了血漿FA在MCI組和對照組中的分布。SFA的總含量在兩組中沒有差異,但是其組分C16:0(p=0.0061)在MCI組的含量低于對照組。MUFA在兩組的分布沒有明顯差異。PUFA中n-3 PUFA的總含量在兩組沒有差異,但是其組分C22:6n-3的水平在對照組中較高(p=0.0057);而MCI組中n-6PUFA的總含量(p0.0001)及其組分C18:2n-6c的水平均比對照組高(p=0.0003);PUFA 總含量比值 n-3/n-6PUFA(p=0.0140)和 C22:6n-3/C20:4n-6(p=0.0294)在正常組中的水平均高于MCI組。2各項指標與MCI關系的單因素logistic回歸分析通過單因素logistic回歸分析后,年齡、受教育程度、失眠情況、視力狀況、吸煙、做家務時間等都是MCI的影響因素。在60-74y范圍內,年齡越小,發(fā)生MCI的風險越小(均有p0.05,且與60-64y組相比,65-69y、70-74y兩組發(fā)生MCI的風險分別為1.885倍、2.603倍);但75-y組MCI的發(fā)生風險與60-64y組沒有差異(p=0.3121)。受教育程度越高,發(fā)生MCI的風險越低。失眠、視力下降、吸煙等均是MCI的危險因素,做家務每增加一個小時,MCI的發(fā)生風險變?yōu)樵瓉淼?.621倍。對食物攝入頻率與MCI做單因素logistic回歸分析,發(fā)現膳食因素與MCI的關系并不明顯。將生化指標按照三分位數劃分為低水平組、中等水平組、高水平組。HDL-C(高水平組OR=0.532)、ApoA-1(高水平組OR=0.490)是MCI的保護因素。ApoB(中等水平組、高水平組OR=1.882、2.294)、ApoE(高水平組OR=2.368)是MCI的危險因素。TC(OR=0.517)、LP(a)(OR=0.491)僅在中等水平對MCI有保護作用。而免疫指標與MCI并沒有表現出明顯的關系。代謝性疾病中,高血壓(OR=1.740)、糖尿病(OR=2.458)、血脂異常(OR=1.845)是MCI的危險因素(OR1)。而血脂異常的三種具體類型與MCI沒有表現出明顯的關系。SFA組分C16:0在MCI組的含量低于對照組(p=0.0061)。MUFA在MCI組和對照組中并沒有明顯差異(p=0.2782)。PUFA中n-3PUFA的總含量在兩組沒有差異,但是其組分C22:6n-3的水平在對照組中較高(p=0.0057);n-6PUFA的總含量在MCI組中較高(p.0001),其組分C18:2n-6c的水平在MCI組中較高(p=0.0003)。兩組中比值 n-3/n-6 PUFA(p=0.0140)和 C22:6n-3/C20:4n-6(p=0.0294)在正常組中的水平均高于MCI組。將各種FA按照三分位數分為三組,分別為低水平組、中等水平組、高水平組,分析FA在不同水平時對MCI的影響。在MCI組和對照組中C16:0、C22:6n-3、n-6PUFA 總含量、C18:2n-6c 以及兩個比值 n-3/n-6PUFA 和 C22:6n-3/C20:4n-6 在MCI組和對照組中的部分分組之間仍然有明顯的差距,此外,n-3PUFA總含量(p=0.0330)、C20:4n-6(p=0.0005)在MCI組和對照組中的分布也存在明顯差異。3各項指標與MCI關系的多因素logistic回歸分析將生活方式、載脂蛋白、LP(a)、LP-PLA2、代謝性疾病、血漿FA中單因素logistic回歸分析中有統計學意義的指標納入多因素logistic分析模型中。生活方式中的受教育程度、做家務時間,代謝性疾病中的血脂異常以及血漿FA中的C20:4n-6、比值n-3/n-6PUFA都是MCI的獨立影響因素。受教育程度越高(與小學及以下學歷相比,中學中專和大專大學及以上學歷OR分別為0.248、0.133)、做家務時間越長(做家務時間每增加1h,OR=0.605)、比值n-3/n-6PUFA越大(與低水平組相比,高水平組的OR=0.361),MCI發(fā)生的風險越小,這些是MCI的獨立保護因素;而中等水平的C20:4n-6是MCI的危險因素(與低水平組相比,中等水平OR=2.600,但高水平組與低水平組發(fā)生MCI的風險無明顯差異),血脂異常(OR=3.075)是MCI發(fā)生的獨立危險因素。4結論生活方式中年齡、受教育程度是MCI的影響因素,其中MCI發(fā)生的危險性在60-74y內隨年齡增加而增加,而在75-y時危險性降低;受教育程度是MCI的獨立影響因素;做家務能防止和延緩MCI的發(fā)生和發(fā)展。膳食因素中食物攝入頻次對MCI的影響不明顯。生化指標中HDL-C以及載脂蛋白ApoA-1、ApoB、ApoE均是MCI的影響因素。代謝性疾病也是MCI的危險因素,其中血脂是MCI的獨立危險因素。在本研究中并未發(fā)現免疫指標與MCI有關系。FA與MCI有密切的關系。SFA中C16:0是認知的保護因素。n-3PUFA中的C18:3n-3在中等水平時對認知有損害作用;C22:6n-3對MCI有保護作用,且有一個有效作用的界值。n-6PUFA對認知有損害作用,一方面可能會通過抑制n-3PUFA進入和在組織內分布;一方面可能會與n-3PUFA競爭合成過程中的酶,進而抑制n-3PUFA的作用。
[Abstract]:AIM: To explore the influencing factors of mild cognitive impairment (MCI) in elderly people (> 60 y) in northern China. To explore the relationship between MCI and lifestyle, dietary factors, biochemical indicators, immune indicators, plasma fatty acid (FA), and to explore the influencing factors of MCI. Methods: A case-control study was conducted in three communities randomly selected from Shijiazhuang City, Hebei Province. All 60y elderly in three communities were selected as subjects. The study was divided into two steps: first, according to the health status of community residents. According to the inclusion and exclusion criteria, all the elderly were initially screened, then the basic data were investigated, and then the elderly were screened again according to the inclusion and exclusion criteria. All the MCI patients in the study group were identified according to the diagnostic criteria of normal cognition, and all the normal cognitive people in the three communities were selected by simple random sampling to control group. The ratio between the control group and MCI group was 1:1. In the later data processing, this paper will analyze the life style, dietary factors, blood lipid index, immune index, the relationship between fatty acid (FA) and MCI, and find out the influencing factors of MCI. The specific analysis process is as follows: first of all, the various indicators. The distribution of MCI in the two groups was analyzed preliminarily; then the effects of lifestyle, dietary factors, biochemical indicators, metabolic diseases, immune indicators and plasma fatty acids on MCI were investigated by univariate logistic regression analysis; after univariate analysis, the statistically significant variables in univariate analysis were included in multivariate logistic regression analysis. In the result analysis, the descriptive use cases (n) and constituent ratio (%) of the classified variables, the descriptions of the quantitative variables were expressed by mean (x) + standard deviation (S) or median (M) and upper and lower quartile (Q1, Q3); the comparison between the two groups of the classified variables was performed by_2 test, and the rank sum test was used for those who did not meet the criteria. The comparison between the two groups was conducted by t test, and those who did not meet the use conditions were tested by Wilcoxon symbolic rank sum test. The influencing factors of MCI were analyzed by single factor Logistic regression, and then analyzed by multi-factor logistic regression model. Compared with the control group, the proportion of 60-64y in MCI group was lower (42.74% 55.65%), 65-69y in the middle age group (33.87% 23.39%), 70-74y (17.74% 8.87%) was higher than that in the control group, and 75-y in the high age group (5.65% 12.1%) was lower than that in the control group again. The proportion of participants in the MCI group was lower than that in the control group (12.1% 18.55%) and the time spent on housework in the MCI group was significantly less than that in the control group (p.0001); the proportion of occasional smokers (6.45% 5.65%) and frequent smokers (11.29% 4.03%, P = 0.0908) in the MCI group was higher than that in the control group; while the living conditions (p = 0.7757) and recreational activities (p = 0.92%) in the MCI group were higher than that in the control group. 65), drinking (p = 0.3903), sitting time (p = 0.1599), sleeping time (p = 0.5955) were not significantly different. Among dietary factors, the frequency of eggs intake in the control group was higher than that in the MCI group, while the frequency of nuts intake was lower than that in the MCI group. The levels of HDL-C (1.141.18) and ApoA-1 (1.511.42) in MCI group were lower than those in control group, while the levels of ApoB (0.910.83) and ApoE (4.193.58) were higher than those in control group, but the levels of TC, TG, LDL-C, HDL-C/LDL-C, PL (a) and LP-PLA2 were not significantly different between the two groups. The prevalence of hypercholesterolemia, hypertriglyceridemia, hypohigh-density lipoprotein cholesterolemia, and anemia were not significantly different between the two groups. Immune indexes CRP, IL-6 and TNF-alpha in MCI and the control group were not significantly different. There was no significant difference in the distribution of plasma FA between the MCI group and the control group. There was no difference in the total content of SFA between the two groups, but the content of component C16:0 (p = 0.0061) in the MCI group was lower than that in the control group. There was no significant difference in the distribution of MUFA between the two groups. However, the levels of component C22:6n-3 were higher in the control group (p = 0.0057), the total content of n-6PUFA (p 0.0001) and its component C18:2n-6c in the MCI group were higher than those in the control group (p = 0.0003), the ratio of total content of PUFA to total content of n-3/n-6PUFA (p = 0.0140) and C22:6n-3/C20:4n-6 (p = 0.0294) in the normal group were higher than those in the MCI group. Univariate logistic regression analysis showed that age, education level, insomnia, visual acuity, smoking and housework time were all influencing factors of MCI. Within the 60-74y range, the younger the age, the lower the risk of MCI (all p0.05), and compared with the 60-64y group, the 65-69y and 70-74y groups had wind of MCI. The higher the education level, the lower the risk of MCI. Insomnia, decreased vision, and smoking were all risk factors of MCI. Every hour of housework, the risk of MCI increased to 0.621 times. Single factor Logistic regression analysis showed that the relationship between dietary factors and MCI was not obvious. The biochemical indexes were divided into low level group, middle level group and high level group according to three-digit. HDL-C (high level group OR = 0.532), ApoA-1 (high level group OR = 0.490) were protective factors of MCI. ApoB (middle level group, high level group OR = 1.882, 2.294), ApoE (high water group OR = 1.882, 2.294). TC (OR = 0.517) and LP (a) (OR = 0.491) had protective effects on MCI only at moderate levels. However, immune indexes were not significantly associated with MCI. Hypertension (OR = 1.740), diabetes mellitus (OR = 2.458) and dyslipidemia (OR = 1.845) were risk factors for MCI in metabolic diseases. There was no significant difference in the total content of n-3PUFA between MCI group and MCI group (p = 0.0061). There was no significant difference in the total content of n-3PUFA between MCI group and control group (p = 0.2782). There was no difference in the total content of n-3PUFA between the two groups, but the total content of component C22:6n-3 was higher in the control group (p = 0.0057). The ratio of n-3/n-6 PUFA (p = 0.0140) and C22:6n-3/C20:4n-6 (p = 0.0294) in the two groups were higher in the normal group than in the MCI group. The total content of C16:0, C22:6n-3, n-6PUFA, C18:2n-6c and the ratio of n-3/n-6PUFA and C22:6n-3/C20:4n-6 in MCI and control groups were still significantly different. In addition, the total content of n-3PUFA (p = 0.0330) and the distribution of C20:4n-6 (p = 0.0005) in MCI and control groups were significantly different. There were also significant differences. 3 Multivariate logistic regression analysis of the relationship between various indicators and MCI included lifestyle, apolipoprotein, LP (a), LP-PLA2, metabolic diseases, and statistically significant indicators in single-factor logistic regression analysis of plasma FA. The higher the education level (OR 0.248, 0.133 for junior secondary school, 0.133 for junior college and above) and the longer the housework time (OR = 0.605 for every hour of housework), the higher the ratio of n-3/n/n. The higher the - 6 PUFA (OR = 0.361 compared with the low level group), the lower the risk of MCI, these are independent protective factors of MCI; and the middle level of C20:4n - 6 is the risk factor of MCI (compared with the low level group, the middle level OR = 2.600, but the high level group and the low level group have no significant difference in the risk of MCI), dyslipidemia (OR = 3.075). Conclusion Age and education are the independent risk factors for MCI. The risk of MCI increases with age in 60-74y and decreases with age in 75-y. Education is an independent risk factor for MCI. Doing housework can prevent and delay the occurrence and development of MCI. HDL-C and apolipoprotein ApoA-1, ApoB and ApoE were the influencing factors of MCI. Metabolic diseases were also the risk factors of MCI. Blood lipid was an independent risk factor of MCI. No correlation was found between immune indexes and MCI. There was a close relationship between FA and MCI. C18:3n-3 in n-3PUFA is a protective factor for cognition. C18:3n-3 in n-3PUFA is harmful to cognition at moderate level; C22:6n-3 has protective effect on MCI and has a threshold of effective effect. n-6PUFA is harmful to cognition. On the one hand, it may inhibit the entry and distribution of n-3PUFA in tissues; on the other hand, it may compete with n-3PUFA in the process of synthesis. The enzyme further inhibits the action of n-3PUFA.
【學位授予單位】：中國疾病預防控制中心
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：R749.1

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