Objective: To quantitatively evaluate the association between mild cognitive impairment and all-cause mortality. Methods: The research papers of the association between cognitive impairment and all-cause mortality in the elderly in the databases of PubMed, EMBASE, Wang Fang data and CNKI published as of August 1, 2021 were comprehensively retrieved. Software R 4.02 was used for Meta-analysis. Results: A total of 9 research papers were included, involving 48 709 patients. The quality of included papers was high. The results of Meta-analysis showed that the association between mild cognitive impairment and the increased risk of all-cause mortality was statistically significant. Compared with the normal cognitive population, the risk of mortality in the elderly with mild cognitive impairment increased by 39% (HR=1.39, 95%CI: 1.18-1.63). Conclusions: The current research evidence showed that mild cognitive impairment assessed by MMSE screening scale can be used as an independent predictor of the increased risk of all-cause mortality in the elderly population in China. However, due to the limitation of the number of included studies and sample size, the conclusions need to be supported by more evidence studies.
Aged ; China/epidemiology* ; Cognition ; Cognition Disorders ; Cognitive Dysfunction/epidemiology* ; Humans ; Mass Screening

Aged ; Cognitive Dysfunction/epidemiology* ; Cross-Sectional Studies ; Geriatric Assessment ; Humans ; Independent Living ; Sarcopenia/epidemiology*

Objective: To explore the effect of sleep duration on the risk of cognitive impairment in the elderly in China. Methods: Baseline data of 9 679 elderly individuals with intact cognition were collected from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) in 2005, and followed up was conducted until 2018. Cox proportional hazards model was used to analyze the association between different sleep durations and the risk for cognitive impairment in the elderly. Results: Compared with elderly with sleep duration of 6 hours per day, those with sleep duration less than 5 hours had increased risk for cognitive impairment by 30% (HR=1.30, 95%CI: 1.05-1.62), and those with sleep durations of 7 hours, 8 hours and more than 9 hours had increased risk for cognitive impairment by 34% (HR=1.34,95%CI: 1.09-1.64), 40% (HR=1.40,95%CI: 1.17-1.69) and 43% (HR=1.43,95%CI: 1.19-1.70), respectively. Trend test showed that the risk of cognitive impairment increased with the extension of sleep duration (>6 h), and there was a dose-response relationship (P<0.001). However, self-rated sleep quality was not associated with the risk for cognitive impairment in the elderly. Conclusions: The shorter and longer sleep duration were associated an increased risk of cognitive impairment in the elderly aged ≥65 years in China, suggesting that optimizing sleep duration might delay the occurrence of cognitive impairment.
Aged ; China/epidemiology* ; Cognitive Dysfunction/epidemiology* ; Cohort Studies ; Humans ; Risk Factors ; Sleep

Objective: To explore the relationship between nutrient-related dietary pattern and mild cognitive impairment (MCI) in middle-aged and elderly people. Methods: A total of 6 444 middle-aged and elderly people aged ≥55 years were selected in 2018 China Health and Nutrition Survey. MCI was evaluated by Mini-Mental State Examination, and the intakes of various foods were obtained by consecutive 3-day 24-hour dietary survey and weighing method. The intakes of various nutrients and total dietary energy were calculated based on the food composition table. Demographic and social information, lifestyle and health status of the respondents were obtained through questionnaire survey and physical measurements. In this study, vitamin C, vitamin E, zinc, iron, copper and selenium were selected as dependent variables. Nutrient-related dietary patterns were extracted by reduced rank regression method, and the relationship between dietary patterns and MCI was analyzed by multivariate logistic regression model. Results: Six dietary patterns were extracted in this study, and dietary pattern 1 with the highest explanatory degree was selected for subsequent analysis. Dietary pattern 1 was characterized by higher intakes of legume products, vegetables, fruits, nuts, pork, aquatic products and plant oil. Multivariate logistic regression analysis showed that the risk of MCI was lower in Q₄ dietary score group than in Q₁ dietary score group (OR=0.69, 95%CI: 0.49-0.98) in the 55-64 age group. In people with sleep duration of 8 hours per day, the risk of MCI was reduced in Q₂, Q₃ and Q₄ dietary score groups compared with the Q₁ dietary score group, with OR values of 0.68 (95%CI: 0.51-0.92), 0.67 (95%CI: 0.49-0.92) and 0.65 (95%CI: 0.45-0.92), respectively. Interaction analysis showed that the risk for MCI increased in those aged 65-74 years and ≥75 years compared with those aged 55-64 years in Q₁ dietary score group. However, the risk for MCI decreased in both age groups as dietary pattern scores increased. Compared with those with sleep duration less or more than 8 hours per day in Q₁ dietary score group, those with sleep duration of 8 hours per day in Q₂ and Q₃ dietary score groups had a reduced risk for MCI. Conclusion: Dietary patterns with higher intakes of legume products, vegetables, fruits, nuts, pork, aquatic products, and plant oil are negatively associated with MCI in people aged 55-64 years and those who slept 8 hours per day, and may reduce the risk of MCI with aging.
Aged ; Middle Aged ; Humans ; Feeding Behavior/psychology* ; Diet ; Cognitive Dysfunction/epidemiology* ; Nutrients ; Vegetables ; China/epidemiology*

Objective: To construct and compare the dynamic prediction models of the risk of mild cognitive impairment (MCI) in the elderly based on six different cognitive function scales. Methods: Based on longitudinal data from the Alzheimer's Disease Neuroimaging Initiative from 2005 to 2020, Mini-mental state examination (MMSE), functional activities questionnaire (FAQ), Alzheimer's disease assessment scale-cognitive (ADAS-Cog) 11, ADAS-Cog13, ADAS delayed word recall (ADASQ4), and Rey auditory verbal learning test (RAVLT)_immediate were used as longitudinal cognitive function evaluation indicators to assess the longitudinal changes in cognitive function. The joint model was used to analyze association between indicators variation trajectory and survival outcome MCI, and construct the risk prediction model of MCI in the elderly, the linear mixed model was constructed the longitudinal sub-model which described the evolution of a repeated measure over time, a proportional hazards model was constructed the survival sub-model, and the two sub-models were connected through the correlation parameter (α). The areas under the receiver operator characteristic curve (AUC) were used to evaluate the predictive efficacy of the model in the follow-up period of (t, t+Δt). The starting point t was selected at the 30^th, 42^nd, and 54^th month, and the Δt was selected as 15 and 21 months. Based on the prediction model, an example of the research object was selected for dynamic individual predictions of the risk of MCI. Results: Finally, 544 older adults (aged 60 years and above) with normal baseline cognitive status were included, of which 119 cases (21.9%) had MCI during the follow-up process were regarded as the case group, and 425 cases remained normal as the control group. The joint model suggests that the longitudinal trajectories of the six evaluation indicators are all related to the risk of MCI (P<0.001). The risk of MCI decreased by 32.3% (HR=0.677, 95%CI: 0.541-0.846) and 10.8% (HR=0.892, 95%CI: 0.865-0.919) for each one-point increase of MMSE and RAVLT_immediate longitudinal scores. The risk of MCI increased by 53.2% (HR=1.532, 95%CI: 1.393-1.686), 36.2% (HR=1.362, 95%CI: 1.268-1.462), 23.2% (HR=1.232, 95%CI: 1.181-1.285), and 85.1% (HR=1.851, 95%CI:1.629-2.104) for each one-point increase of FAQ, ADAS-Cog11, ADAS-Cog13, and ADASQ4 longitudinal scores. AUC results show that RAVLT_immediate (0.760 2) and ADASQ4 (0.755 8) have higher average prediction efficiency, followed by ADAS-Cog13 (0.743 7), ADAS-Cog11 (0.715 3), FAQ (0.700 8) and MMSE (0.629 5). ADASQ4 joint model was used to provide a dynamic individual prediction of the risk of MCI. The average probability of MCI after five years of follow-up and ten years of follow-up in the example individuals were 8% and 40%, respectively. Conclusions: The RAVLT_immediate and ADASQ4 scales, which are only for memory tests, have high accuracy in predicting the risk of MCI. Using the RAVLT_immediate and ADASQ4 scales as longitudinal cognitive function evaluation indicators to construct a joint model, the results can provide a basis for realizing MCI risk prediction for the elderly.
Aged ; Alzheimer Disease/psychology* ; Cognition ; Cognitive Dysfunction/epidemiology* ; Humans ; Middle Aged ; Neuropsychological Tests ; Risk Factors

BACKGROUND: The July 2018 Japan Floods caused enormous damage to western Japan. Such disasters can especially impact elderly persons. Research has shown that natural disasters exacerbated a decline in cognitive function, but to date, there have been no studies examining the effects of this disaster on the elderly. The object of this study was to reveal the effect of this disaster in terms of cognitive decline among the elderly. METHODS: Study participants were certified users of the long-term care insurance (LTCI) system in Hiroshima, Okayama, and Ehime prefectures from May 2018 to June 2018. The observation period was from July 2018 to December 2018. Our primary outcome was cognitive decline after the disaster using a dementia symptomatology assessment. In addition to a crude model, a multivariate Cox proportional hazards model was used to assess the cognitive decline of victims, adjusting for age classification, gender, the level of dementia scale before the disaster occurred, residential environment, whether a participant used facilities shut down after the disaster, and population density. After we confirmed that the interaction term between victims and residential environment was statistically significant, we stratified them for the analysis. RESULTS: The total number of participants was 264,614. Victims accounted for 1.10% of the total participants (n = 2,908). For the Cox proportional hazards model, the hazard ratio of the victims was 1.18 (95% confidential interval (CI): 1.05-1.32) in the crude model and 1.12 (95% CI: 1.00-1.26) in the adjusted model. After being stratified by residential environment, the hazard ratio of home victims was 1.20 (95% CI: 1.06-1.36) and the hazard ratio of facility victims was 0.89 (95% CI: 0.67-1.17). CONCLUSIONS This study showed that elderly living at home during the 2018 Japan Floods were at risk for cognitive decline. Medical providers, care providers, and local governments should establish a system to check on the cognitive function of elderly victims and provide necessary care support.
Aged ; Cognitive Dysfunction/etiology* ; Floods ; Humans ; Insurance, Long-Term Care ; Japan/epidemiology* ; Retrospective Studies

Objective: To understand the transition rules of cognitive frailty and its influencing factors in the elderly in China and provide evidence for the early intervention of cognitive frailty. Methods: Data were retrospectively collected from China Health and Retirement Longitudinal Study with 3 round consecutive survey (2011, 2013, 2015) and the state of the subjects were classified into four categories: robust-normal cognitive, cognitive impairment, physical frailty, and cognitive frailty. A multi-state Markov model was established to explore the transition rules of cognitive frailty and its influencing factors. Results: A total of 3 470 older adults were included, and 350 (10.09%) had cognitive frailty at baseline. After two years, the probability of cognitive frailty in the cognitive impairment population was higher than that in people with physical frailty (31.6% vs. 7.6%). Persons with cognitive frailty were more likely to become physical frailty (29.7% vs. 15.6%). Being women (HR=1.599, 95%CI: 1.058-2.417), comorbidity (HR=3.035, 95%CI: 1.090-8.450), and depression (HR=1.678, 95%CI: 1.153-2.441) were the risk factors associated with cognitive frailty in the elderly, while being educated (HR=2.367, 95%CI: 1.567-3.575) was a protective factor for the transition of cognitive frailty to physical frailty. Conclusions: The prevalence of cognitive frailty is relatively high in the elderly in China. Those with cognitive impairment have a higher probability of cognitive frailty. Gender, education level, comorbidity, and depression are the main influencing factors for the occurrence and transition of cognitive frailty.
Aged ; China/epidemiology* ; Cognition ; Cognitive Dysfunction/epidemiology* ; Female ; Frail Elderly ; Frailty/epidemiology* ; Geriatric Assessment ; Humans ; Longitudinal Studies ; Male ; Retrospective Studies

Objective: To analyze the association of fasting plasma glucose (FPG) with mild cognitive impairment (MCI) in the Chinese middle-aged and elderly population from four provinces. Methods: Data were drawn from the baseline data of the Community-based Cohort Study on Nervous System Disease 2018-2019. We selected 3 272 subjects aged 55 and above with completed information on demographics, lifestyle, disease history, cognitive test, psychological assessment, and bio-chemistries measurement, and who were capable of performing basic activities of daily living but without Alzheimer's disease during recruitment. A multivariate logistic regression model was employed to analyze the association between FPG and MCI. Results: Median level of FPG in the study population was 5.5 mmol/L. The prevalence of MCI was 24.8%, and those in groups of the FPG quintile were 19.4%, 22.2%, 29.2%, 26.6%, and 26.1%, respectively, which significantly increased the trend (P=0.002). After adjustment of confounders, multivariate logistic regression analysis found that the MCI risk of subjects in the Q₃,Q₄ and Q₅ groups was 1.641 (95%CI: 1.226-2.131), 1.373 (95%CI: 1.036-1.825), 1.402 (95%CI: 1.054-1.871) times as high as that in the Q₁ group, respectively. Conclusion: High FPG level might serve as a risk factor for MCI in the middle-aged and elderly population, suggesting the importance of monitoring and controlling plasma glucose even without diabetes.
Middle Aged ; Humans ; Aged ; Fasting ; Blood Glucose ; Activities of Daily Living ; Cohort Studies ; Cognitive Dysfunction/epidemiology* ; China/epidemiology*

OBJECTIVE: To analyze the spatial distribution of the prevalence of cognitive dysfunction and its risk factors in Chinese population aged 45 years and above to provide evidence for formulating regional prevention and control strategies. METHODS: The study subjects with complete cognitive function data were selected from the follow-up data of the China Health and Retirement Longitudinal Study (CHARLS) Phase IV. ArcGis 10.4 software was used for spatial analysis of the prevalence of cognitive dysfunction in the population aged 45 years and above for each province based on the geographic information system (GIS) technology. RESULTS: In 2018, the overall prevalence of cognitive dysfunction was 33.59% (5951/17716) in individuals aged 45 and above in China. Global spatial autocorrelation analysis indicated a spatial clustering and a positive autocorrelation (P < 0.001) of the prevalence of cognitive dysfunction in the study subjects, with a Moran's I value of 0.333085. The results of local spatial autocorrelation analysis showed that the southwestern region of China was the main aggregation area of patients with cognitive dysfunction. Geographically weighted regression analysis suggested that a male gender, an advanced age, and illiteracy were the major risk factors for cognitive dysfunction (P < 0.05). These 3 risk factors showed a spatial distribution heterogeneity with greater impact in the northern, western, and northwestern regions of China, respectively. CONCLUSION The prevalence of cognitive dysfunction is relatively high in individuals aged 45 years and above in China. A male gender, an advanced age, and illiteracy are the major risk factors for cognitive dysfunction and show different spatial distribution patterns, with the northern, western and northwestern regions of China as the key areas for prevention and control, where the prevention and control measures should be designed based on local conditions.
Humans ; Male ; China/epidemiology* ; Cluster Analysis ; Cognitive Dysfunction/epidemiology* ; East Asian People ; Longitudinal Studies ; Risk Factors ; Middle Aged

Objective: To identify the main metals involved in cognitive impairment in the Chinese oldest old, and explore the association between these metal exposures and cognitive impairment. Methods: A cross-sectional study was conducted on 1 568 participants aged 80 years and older from Healthy Aging and Biomarkers Cohort Study (2017 to 2018). Fasting venous blood was collected to measure the levels of nine metals (selenium, lead, cadmium, arsenic, antimony, chromium, manganese, mercury, and nickel). The cognitive function of these participants was evaluated by using the Chinese version of the Mini-Mental State Examination (CMMSE). The random forest (RF) was applied to independently identify the main metals that affected cognitive impairment. The multivariate logistic regression model and restricted cubic splines (RCS) model were used to further verify the association of the main metals with cognitive impairment. Results: The age of 1 568 study subjects was (91.8±7.6) years old, including 912 females (58.2%) and 465 individuals (29.7%) with cognitive function impairment. Based on the RF model (the out-of-bag error rate was 22.9%), the importance ranking of variables was conducted and the feature screening of five times ten-fold cross-validation was carried out. It was found that selenium was the metal that affected cognitive function impairment, and the other eight metals were not included in the model. After adjusting for covariates, the multivariate logistic regression model showed that with every increase of 10 μg/L of blood selenium levels, the risk of cognitive impairment decreased (OR=0.921, 95%CI: 0.889-0.954). Compared with the lowest quartile(Q₁) of blood selenium, the ORs (95%CI) of Q₃ and Q₄ blood selenium were 0.452 (0.304-0.669) and 0.419 (0.281-0.622) respectively. The RCS showed a linear dose-response relationship between blood selenium and cognitive impairment (P_nonlinear>0.05). Conclusion: Blood selenium is negatively associated with cognitive impairment in the Chinese oldest old.
Aged, 80 and over ; Female ; Humans ; Selenium ; Cohort Studies ; Cross-Sectional Studies ; Metals/analysis* ; Cognitive Dysfunction/epidemiology* ; China/epidemiology*