中国北方老年人轻度认知障碍的影响因素探究
发布时间：2018-08-27 14:59
【摘要】：目的:本研究目的是寻找中国北方≥60y老年人轻度认知障碍(Mild Cognitive Impairment,MCI)的影响因素。通过分析生活方式、膳食因素、生化指标、免疫指标、血浆脂肪酸(Fatty Acid,FA)与MCI的关系,探究MCI的影响因素,为寻找MCI的有效干预手段以及为以后对MCI进一步的研究提供新的线索。方法:在河北省石家庄市用简单随机抽样的方法随机抽取三个社区开展一项病例对照研究,以三个社区的所有60y的老年人为研究对象。本研究研究对象的选取分为两步:首先根据社区居民健康档案按照纳入和排除标准对所有老年人进行初步筛选;然后再进行基本资料调查后,结合纳入和排除标准对老年人进行再次筛选。最后根据MCI的诊断标准、问卷和体检数据,由卫生部北京医院精神内科专家做出最终诊断,找出该三个社区中的全部MCI患者;再根据正常认知诊断标准确定三个社区中的全部正常认知者,利用简单随机抽样的方法抽取得到对照组,使对照组与MCI组的数量比为1:1。本研究的工作主要包括对研究对象进行认知状况、生活方式和膳食因素等资料的调查;并及时开展血液生化指标、免疫指标以及血浆FA等指标的实验室检测。在后期数据处理中,本文将通过分析生活方式、膳食因素、血脂指标、免疫指标、脂肪酸(Fatty Acid,FA)与MCI的关系,寻找MCI的影响因素,具体分析过程为:先对各项指标在两组中的分布进行初步分析;然后用单因素logistic回归分析探讨生活方式、膳食因素、生化指标、代谢性疾病、免疫指标以及血浆脂肪酸各自对MCI的影响;在进行单因素分析后,将单因素分析中有统计学意义的变量纳入多因素logistic回归模型,得出MCI的独立影响因素。在结果分析中,分类变量的描述用例数(n)和构成比(%),定量变量的描述用均数(x)±标准差(S)或中位数(M)和上下四分位数(Q1,Q3)表示;分类变量的两组间比较采用χ2检验,不符合条件者采用秩和检验;定量变量的两组间比较采用t检验,不符合使用条件者采用wilcoxon符号秩和检验。MCI的影响因素探究先使用单因素logistic回归分析,然后使用多因素logistic回归模型进行分析。结果:1各项指标在不同认知状况人群中的分布年龄(p=0.0114)、受教育程度(p0.0001)与MCI有明显的关系。与对照组相比,MCI组中低年龄段60-64y所占比例低(42.74%55.65%),中间年龄段65-69y(33.87%23.39%)、70-74y(17.74%8.87%)所占比例高于对照组,而高年龄段75-y(5.65%12.1%)占的比例又再次低于对照组。MCI中受教育程度较高的人群占的比例低于对照组;MCI组中参加学习活动的比例低于对照组(12.1%18.55%),MCI的做家务时间明显少于对照组(p.0001);MCI组偶尔吸烟(6.45%5.65%)和经常吸烟(11.29%4.03%,p=0.0908)的人占的比例均高于对照组;而两组中居住状况(p=0.7757)、娱乐活动(p=0.9265)、饮酒(p=0.3903)、静坐时间(p=0.1599)、睡眠时间(p=0.5955)的分布没有明显差异。膳食因素中,对照组摄入蛋类的频次多于MCI组、而坚果类的摄入频率比MCI少。米面杂粮等、蔬菜菌藻、水果、禽肉、畜肉、淡水鱼贝类、海水鱼贝类、豆类及制品等在MCI组和正常组中的分布也没有差异。MCI组中 HDL-C(1.141.18)、ApoA-1(1.511.42)的水平均低于对照组,而ApoB(0.910.83)、ApoE(4.193.58)的水平均高于对照组,但是两组中其他指标 TC、TG、LDL-C、HDL-C/LDL-C、PL(a)、LP-PLA2 的水平在两组中的差异并不明显。MCI中患高血压(54.03%40.32%)、血脂异常(46.77%32.26%)、糖尿病(17.74%8.06%)的比例均高于对照组。血脂异常包含的三种疾病高胆固醇血症、高甘油三酯血症、低高密度脂蛋白胆固醇血症、贫血在两组的分布并没有明显的差别。免疫指标CRP、IL-6、TNF-α在MCI和对照组水平的分布没有明显的差异。本研究还重点分析了血浆FA在MCI组和对照组中的分布。SFA的总含量在两组中没有差异,但是其组分C16:0(p=0.0061)在MCI组的含量低于对照组。MUFA在两组的分布没有明显差异。PUFA中n-3 PUFA的总含量在两组没有差异,但是其组分C22:6n-3的水平在对照组中较高(p=0.0057);而MCI组中n-6PUFA的总含量(p0.0001)及其组分C18:2n-6c的水平均比对照组高(p=0.0003);PUFA 总含量比值 n-3/n-6PUFA(p=0.0140)和 C22:6n-3/C20:4n-6(p=0.0294)在正常组中的水平均高于MCI组。2各项指标与MCI关系的单因素logistic回归分析通过单因素logistic回归分析后,年龄、受教育程度、失眠情况、视力状况、吸烟、做家务时间等都是MCI的影响因素。在60-74y范围内,年龄越小,发生MCI的风险越小(均有p0.05,且与60-64y组相比,65-69y、70-74y两组发生MCI的风险分别为1.885倍、2.603倍);但75-y组MCI的发生风险与60-64y组没有差异(p=0.3121)。受教育程度越高,发生MCI的风险越低。失眠、视力下降、吸烟等均是MCI的危险因素,做家务每增加一个小时,MCI的发生风险变为原来的0.621倍。对食物摄入频率与MCI做单因素logistic回归分析,发现膳食因素与MCI的关系并不明显。将生化指标按照三分位数划分为低水平组、中等水平组、高水平组。HDL-C(高水平组OR=0.532)、ApoA-1(高水平组OR=0.490)是MCI的保护因素。ApoB(中等水平组、高水平组OR=1.882、2.294)、ApoE(高水平组OR=2.368)是MCI的危险因素。TC(OR=0.517)、LP(a)(OR=0.491)仅在中等水平对MCI有保护作用。而免疫指标与MCI并没有表现出明显的关系。代谢性疾病中,高血压(OR=1.740)、糖尿病(OR=2.458)、血脂异常(OR=1.845)是MCI的危险因素(OR1)。而血脂异常的三种具体类型与MCI没有表现出明显的关系。SFA组分C16:0在MCI组的含量低于对照组(p=0.0061)。MUFA在MCI组和对照组中并没有明显差异(p=0.2782)。PUFA中n-3PUFA的总含量在两组没有差异,但是其组分C22:6n-3的水平在对照组中较高(p=0.0057);n-6PUFA的总含量在MCI组中较高(p.0001),其组分C18:2n-6c的水平在MCI组中较高(p=0.0003)。两组中比值 n-3/n-6 PUFA(p=0.0140)和 C22:6n-3/C20:4n-6(p=0.0294)在正常组中的水平均高于MCI组。将各种FA按照三分位数分为三组,分别为低水平组、中等水平组、高水平组,分析FA在不同水平时对MCI的影响。在MCI组和对照组中C16:0、C22:6n-3、n-6PUFA 总含量、C18:2n-6c 以及两个比值 n-3/n-6PUFA 和 C22:6n-3/C20:4n-6 在MCI组和对照组中的部分分组之间仍然有明显的差距,此外,n-3PUFA总含量(p=0.0330)、C20:4n-6(p=0.0005)在MCI组和对照组中的分布也存在明显差异。3各项指标与MCI关系的多因素logistic回归分析将生活方式、载脂蛋白、LP(a)、LP-PLA2、代谢性疾病、血浆FA中单因素logistic回归分析中有统计学意义的指标纳入多因素logistic分析模型中。生活方式中的受教育程度、做家务时间,代谢性疾病中的血脂异常以及血浆FA中的C20:4n-6、比值n-3/n-6PUFA都是MCI的独立影响因素。受教育程度越高(与小学及以下学历相比,中学中专和大专大学及以上学历OR分别为0.248、0.133)、做家务时间越长(做家务时间每增加1h,OR=0.605)、比值n-3/n-6PUFA越大(与低水平组相比,高水平组的OR=0.361),MCI发生的风险越小,这些是MCI的独立保护因素;而中等水平的C20:4n-6是MCI的危险因素(与低水平组相比,中等水平OR=2.600,但高水平组与低水平组发生MCI的风险无明显差异),血脂异常(OR=3.075)是MCI发生的独立危险因素。4结论生活方式中年龄、受教育程度是MCI的影响因素,其中MCI发生的危险性在60-74y内随年龄增加而增加,而在75-y时危险性降低;受教育程度是MCI的独立影响因素;做家务能防止和延缓MCI的发生和发展。膳食因素中食物摄入频次对MCI的影响不明显。生化指标中HDL-C以及载脂蛋白ApoA-1、ApoB、ApoE均是MCI的影响因素。代谢性疾病也是MCI的危险因素,其中血脂是MCI的独立危险因素。在本研究中并未发现免疫指标与MCI有关系。FA与MCI有密切的关系。SFA中C16:0是认知的保护因素。n-3PUFA中的C18:3n-3在中等水平时对认知有损害作用;C22:6n-3对MCI有保护作用,且有一个有效作用的界值。n-6PUFA对认知有损害作用,一方面可能会通过抑制n-3PUFA进入和在组织内分布;一方面可能会与n-3PUFA竞争合成过程中的酶,进而抑制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.
【学位授予单位】：中国疾病预防控制中心
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：R749.1
本文编号：2207631
[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.
【学位授予单位】：中国疾病预防控制中心
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：R749.1
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