| Background Many epidemiological studies showed that there is a close relationship between type 2 diabetes mellitus(T2DM) and cognitive dysfunction. Type 2 diabetes is characterized by chronic hyperglycemia, which can increase the risk of vascular dementia. Chronic hyperglycemia may contribute to microvascular changes and ischemia in the brain. Nonetheless, the correlation between hyperglycemia and cognitive function in nondemented geriatric patients with type 2 diabetes remains unclear. Because A1 c values indicate whether glucose metabolism is controlled in diabetics, this study assessed the association of A1 c levels with cognitive deficits in elderly patients with type 2 diabetes. If we can understand the relationship between A1 c and mild cognitive impairment(MCI),we maybe delay the occurrence of MCI in elderly patients with type 2 diabetes.Objective 1. To understand the relationship between glycosylated hemoglobin(Alc) and MCI in the different status of glucose metabolism, different age groups 2. Comparison of the difference of two kinds of criteria between 75 g oral glucose tolerance test(OGTT) and Alc in consistency relationship with the cognitive functions 3. To understand the influencing factors and the difference in the outcome of the conversion to cognitive decline among the MCI subjects and normal cognitive function with different socio-demographic and personality characteristics、disease history、and hereditary feature in type 2 diabetic patients.Methods This study intends to include three parts: cross-sectional survey, control case study and cohort study by standardized clinical research designing. 1. research objectsA cross-sectional study was conducted among the community-dwelling elders aged over 60 in eight community health service center in Taijiang and Cangshan District of Fuzhou city. A total of 5196 subjects(80.7% of the eligible subjects) participated in the baseline survey(2013.01-2013.06). Finally we screened 4192 study populations, including 1174 cases of patients with type 2 diabetes, 412 cases of patients with impaired glucose regulation, 2606 cases of non diabetic patients. 216 subjects with T2DM-MCI were screened from the baseline population and were treated as the cohort population. The follow-up interviews were performed every half a year. We completed a total of 4 visits. 2. research methods(1)The baseline assessment By cluster random sampling,4192 aged people over 60 were ultimately involved. This survey composed of face-to-face interviews and self-administered questionnaires including questions on socio-demographic features, medical conditions. The scale such as Mini-mental state examination(MMSE)、Montreal Cognitive Assessment(Mo CA) and Activity of daily living(ADL) have been performed to measure cognitive function. Of all the 4192 community-dwelling participants underwent psychometric testing,406 subjects met our criteria for MCI. 75 g oral glucose tolerance test(OGTT) was conducted in the non-diabetics people. We aimed to compared the difference of two kinds of criteria between OGTT and Alc in consistency relationship with the cognitive functions.(2)The case control study A matched case-control study was conducted to analyze influencing factors of mild cognitive impairment among the type 2 diabetes. Two hundred and sixteen cases together with 216 controls were interviewed with a uniformed questionnaire. Cases were matched with controls by age decade, education group and gender. All the subjects can accomplish psychological tests independently with adequate cognition and memory. Cox regression model of survival analysis was selected todeal with non-geometric proportional matched data which is difficult to analyze by logistic regression model.(3)The cohort study 216 subjects with T2DM-MCI were screened from the baseline population, all of which were treated as the cohort population.The follow-up interviews were performed every six months. We completed a total of 4 visits, respectively in December 2014, June 2015, December 2015. Cox regression model was performed to analyze prediction value of socio-demographic and personality characteristics、disease history、and hereditary feature on whether can be converted into cognitive decline or not.(4)The laboratory examination Blood samples were drawn in the morning after overnight fasting. MMSE, Mo CA and ADL was developed to detect cognitive function.(5)The statistical analysis Database was constructed by Epi Date3.0 software,All the data information were input by two graduate students for two times. Statistical Analysis were performed by SPSS18.0 software.Continuous data were expressed as the mean with the corresponding standard deviation, or as the median where indicated(P25–P75). Categorical variables were presented as a count and percentage. We examined the distribution of continuous and categorical variables using t-test and χ2-test. We used logistic regression in univariate and multivariate modeling to estimate the association between influencing factors and cognitive decline, adjust for possible confounding variables. Cox regression model of survival analysis was selected to deal with non-geometric proportional matched data which is difficult to analyze by Logistic regression model. P-values less than 0.05 were considered statistically significant.Results1. Results showed that an overall prevalence of MCI was 9.70%. The incidence of MCI was 18.4%, 8.0%, 6.0% respectively in T2 DM group, pre diabetes group, normal glucose metabolism group(P < 0.001). 2. Univariate analyses showed that the prevalence of MCI were significantly different among different groups assigned in the fasting blood glucose, A1 c, low density lipoprotein cholesterol, body mass index, MMSE score and Mo CA score(P < 0.01). 3. Significant predictor variables were as follows:age, education level, A1 c, LDL-C, smoking and history of stroke. 4. In non diabetic patients, Alc increasing per 1%, the risk of MCI increased by 40%, but adjusting for age and education level, there is no correlation between A1 c and MCI, the value of OR and 95%CI was 1.32(0.89-1.85). In type 2 diabetic patients with Alc less than 7%, Alc increasing per 1%, the risk of MCI increased by 41%, but adjusting for age and education level, the correlation between A1 c and MCI did not exist, the value of OR and 95%CI was 1.01(0.87-1.15). But in type 2 diabetes mellitus with Alc more than 7%, even when adjusted for age and years of education, Alc increasing per 1%, the risk of MCI increased by 28%, the value of OR and 95%CI was 1.28(1.02-1.71). 5. After adjusting age and education level, Alc was related to MCI. FBG was also associated with cognitive impairment, but OGTT 2 hours glucose level showed no correlation to MCI. 6. In elderly patients with type 2 diabetes mellitus, a 1% higher A1 C value was associated with a 0.21-point lower MMSE score, as well as a 0.11-point lower Mo CA score. 7. Associations between decreased MMSE scores or Mo CA scores and A1 c levels were not consistently similar between subgroups. Associations between significant A1 c levels and reduced scores were detected in women and men.No significant relationships among patients older than 80 years(n=215; OR=1.019; 95% CI=0.968~1.099; p=0.251) were detected. 8. Incidence density of T2DM-MCI subjects is16.51%,while that of T2DM-NC subjects is 5.75%. By Log-rank test, there is significant difference in Survival curve on the outcome of cognitive decline between cognitive decline group and normal cognitive group in type 2 diabetes(χ2=10.563, P<0.01). 9. For two-year follow-up, by univariate and multivariate cox regression analysis, age, female, low education level, hypertension, coronary heart disease, stock, A1 c, SBP, LDL-C is the risk factors of cognitive decline in the mid cognitive impairment with type 2 diabetes.Conclusion 1. There is a high incidence of MCI in elderly people of Taijiang and Cangshan District in Fuzhou, especially in elderly type 2 diabetes. 2. Cross-sectional study showed that age, education level, A1 c, LDL-C, smoking and history of stroke are the risk factors of MCI without regarding for diabetes. 3. Alc and fasting blood glucose are associated with mild cognitive impairment. OGTT 2 hours blood glucose showed no correlation with cognitive function. 4. Chronic hyperglycemia appears to be independently associated with cognitive function in nondemented elderly patients with type 2 diabetes. When cognitive assessments are performed, comprehensive factors such as advanced age, education level, duration of diabetes, hypertension and other vascular risks should be accounted for because they will impact the data. Especially in senior geriatric patients(age ≥80 years), the relationship between A1 c and cognitive function was weakened. 5. Elderly patients with type 2 diabetes is associated with higher prevalence of mid cognitive impairment, which should be given enough attention to.Therapies aimed at preventing cognitive decline and dementia should proactively target elderly diabetics in their sixties and seventies. |
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