BACKGROUND

Type 2 Diabetes Mellitus (T2DM) patients are predisposed to cognitive decline and dementia. The cooccurrence of the two diseases translate to a higher medical cost. Identification of factors contributing to cognitive impairment is warranted.

To determine the predictors of cognitive impairment among Filipino patients with Type 2 Diabetes Mellitus.

This is a cross-sectional analytical study involving Filipino patients diagnosed with T2DM in the outpatient clinic. A total of 171 patients were included and were screened using AD8-P tool.

A total of 171 adult patients were included and screened for cognitive impairment.19.3% were cognitively impaired, with mean age of 59.6 years old (vs. 55.5 years old, p < 0.029), and two-thirds were female. The mean duration of the patient’s diabetes was 11.2 years. After adjusting for confounders and multi-collinearity, the duration of diabetes was significantly associated with cognitive impairment with odds of developing cognitive impairment increasing as the duration reach 10 years above. Those with T2DM for at least ten years were 2.5 times more likely to develop cognitive impairment, holding the age constant. (OR = 2.5, 95% CI – 1.0 to 5.8, p < 0.043).

19.3% of Filipino patients with Type 2 Diabetes Mellitus in a tertiary government hospital are cognitively impaired and this can occur even in less than 65 years old. The ten years or longer duration of T2DM increases the risk of developing cognitive impairment by 2.5%.

Aging is a major risk factor for many human diseases, including cognitive impairment, which affects a large population of the elderly. In the past few decades, our understanding of the molecular and cellular mechanisms underlying the changes associated with aging and age-related diseases has expanded greatly, shedding light on the potential role of these changes in cognitive impairment. In this article, we review recent advances in understanding of the mechanisms underlying brain aging under normal and pathological conditions, compare their similarities and differences, discuss the causative and adaptive mechanisms of brain aging, and finally attempt to find some rules to guide us on how to promote healthy aging and prevent age-related diseases.
Humans ; Aged ; Aging/pathology* ; Brain ; Cognitive Dysfunction ; Risk Factors

China is facing the peak of an ageing population, and there is an increase in demand for intelligent healthcare services for the elderly. The metaverse, as a new internet social communication space, has shown infinite potential for application. This paper focuses on the application of the metaverse in medicine in the intervention of cognitive decline in the elderly population. The problems in assessment and intervention of cognitive decline in the elderly group were analyzed. The basic data required to construct the metaverse in medicine was introduced. Moreover, it is demonstrated that the elderly users can conduct self-monitoring, experience immersive self-healing and health-care through the metaverse in medicine technology. Furthermore, we proposed that it is feasible that the metaverse in medicine has obvious advantages in prediction and diagnosis, prevention and rehabilitation, as well as assisting patients with cognitive decline. Risks for its application were pointed out as well. The metaverse in medicine technology solves the problem of non-face-to-face social communication for elderly users, which may help to reconstruct the social medical system and service mode for the elderly population.
Aged ; Humans ; Cognitive Dysfunction/prevention & control* ; Aging ; China ; Internet ; Technology

Objective: To explore the status quo, differences and influencing factors of health concern among the elderly in urban and rural areas. Methods: The data of China Health and Retirement Tracking Survey (CHARLS) in 2018 were used to describe the health concerns of the elderly in urban and rural areas by selecting relevant indicators. The differences of health concerns of the elderly in urban and rural areas were compared from two aspects of social demographic characteristics and health status. Multivariate logistic regression model was used to analyze the factors affecting the health concern of the elderly in urban and rural areas. Results: A total of 7 758 urban and rural elderly were included, including 1 913 urban elderly and 5 845 rural elderly. Half (3 899, 50.3%) of the elderly are at the average level of health concern, and there is a difference between urban and rural elderly (χ²=186.61,P<0.05). The rural and urban elderly with different characteristics had different health concerns. The rural elderly with more than two diseases had higher health concerns (χ²=13.71, P=0.001), and different living types of urban elderly people have different health concerns (χ²=28.96, P<0.001). Regression analysis showed that the health concern of the elderly in urban and rural areas was affected by many factors, gender (OR=1.51, P<0.001), health status (OR=2.18, P<0.001), cognitive function impairment (OR=2.93, P<0.001), depression (OR=0.49, P<0.001) is the main factor affecting the difference of health attention of the elderly in urban and rural areas. Whether to receive pension was the influential factor of health concern of the rural elderly (OR=0.63, P<0.05); Disability was an influential factor in the health concern of the urban elderly (OR=2.11, P<0.05). Conclusion: There is much room to improve the health attention of the elderly in urban and rural areas. It is suggested to increase the economic security of the elderly in rural areas and pay special attention to the disabled elderly in urban areas, so as to further improve the health status of the elderly groups.
Humans ; Aged ; Aging ; Retirement ; China ; Cognition ; Cognitive Dysfunction

Objective: To explore the status quo, differences and influencing factors of health concern among the elderly in urban and rural areas. Methods: The data of China Health and Retirement Tracking Survey (CHARLS) in 2018 were used to describe the health concerns of the elderly in urban and rural areas by selecting relevant indicators. The differences of health concerns of the elderly in urban and rural areas were compared from two aspects of social demographic characteristics and health status. Multivariate logistic regression model was used to analyze the factors affecting the health concern of the elderly in urban and rural areas. Results: A total of 7 758 urban and rural elderly were included, including 1 913 urban elderly and 5 845 rural elderly. Half (3 899, 50.3%) of the elderly are at the average level of health concern, and there is a difference between urban and rural elderly (χ²=186.61,P<0.05). The rural and urban elderly with different characteristics had different health concerns. The rural elderly with more than two diseases had higher health concerns (χ²=13.71, P=0.001), and different living types of urban elderly people have different health concerns (χ²=28.96, P<0.001). Regression analysis showed that the health concern of the elderly in urban and rural areas was affected by many factors, gender (OR=1.51, P<0.001), health status (OR=2.18, P<0.001), cognitive function impairment (OR=2.93, P<0.001), depression (OR=0.49, P<0.001) is the main factor affecting the difference of health attention of the elderly in urban and rural areas. Whether to receive pension was the influential factor of health concern of the rural elderly (OR=0.63, P<0.05); Disability was an influential factor in the health concern of the urban elderly (OR=2.11, P<0.05). Conclusion: There is much room to improve the health attention of the elderly in urban and rural areas. It is suggested to increase the economic security of the elderly in rural areas and pay special attention to the disabled elderly in urban areas, so as to further improve the health status of the elderly groups.
Humans ; Aged ; Aging ; Retirement ; China ; Cognition ; Cognitive Dysfunction

BACKGROUND AND PURPOSE: Epidemiological studies have suggested the presence of strong correlations among diet, lifestyle, and dementia onset. However, these studies have unfortunately had major limitations due to their inability to fully control the various potential confounders affecting the nutritional status. The purpose of the current study was to determine the nutritional status of participants in the Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer's Disease (KBASE) and to identify clinical risk factors for being at risk of malnutrition or being malnourished. METHODS: Baseline data from 212 participants [119 cognitively unimpaired (CU), 56 with mild cognitive impairment (MCI), and 37 with dementia] included in the KBASE database were analyzed. All participants underwent a comprehensive cognitive test and MRI at baseline. The presence of malnutrition at baseline was measured by the Mini Nutritional Assessment score. We examined the cross-sectional relationships of clinical findings with nutritional status using multiple logistic regression applied to variables for which p<0.2 in the univariate analysis. Differences in cortical thickness according to the nutritional status were also investigated. RESULTS: After adjustment for demographic, nutritional, and neuropsychological factors, participants with dementia had a significantly higher odds ratio (OR) for being at risk of malnutrition or being malnourished than CU participants [OR=5.98, 95% CI=1.20–32.97] whereas participants with MCI did not (OR=0.62, 95% CI=0.20–1.83). Cortical thinning in the at-risk/malnutrition group was observed in the left temporal area. CONCLUSIONS: Dementia was found to be an independent predictor for the risk of malnutrition compared with CU participants. Our findings further suggest that cortical thinning in left temporal regions is related to the nutritional status.
Aged ; Aging ; Alzheimer Disease ; Brain ; Cerebral Cortex ; Dementia ; Diet ; Early Diagnosis ; Epidemiologic Studies ; Humans ; Life Style ; Logistic Models ; Magnetic Resonance Imaging ; Malnutrition ; Mild Cognitive Impairment ; Nutrition Assessment ; Nutritional Status ; Odds Ratio ; Risk Factors ; Temporal Lobe

BACKGROUND AND PURPOSE: Semantic memory remains more stable than episodic memory across the lifespan, which makes it potentially useful as a marker for distinguishing pathological aging from normal senescence. To obtain a better understanding of the transitional stage evolving into Alzheimer's dementia (AD), we focused on the amnestic mild cognitive impairment (aMCI) stage stratified based on β-amyloid (Aβ) pathology. METHODS: We analyzed the raw data from Korean version of the Boston Naming Test (K-BNT) and the Controlled Oral Word Association Test (COWAT). For K-BNT, the frequencies of six error types and accuracy rates were evaluated. For a qualitative assessment of the COWAT, we computed the number of switching, number of clusters, and mean cluster size. RESULTS: The data from 217 participants were analyzed (53 normal controls, 66 with Aβ− aMCI, 56 with Aβ+ aMCI, and 42 disease controls). There were fewer semantically related errors and more semantically unrelated errors on the K-BNT in Aβ+ aMCI than in Aβ− aMCI, without a gross difference in the z score. We also found that Aβ+ aMCI showed a more prominent deficit in the number of clusters in the semantic fluency task [especially for animal names (living items)] than Aβ− aMCI. CONCLUSIONS: In spite of similar clinical manifestations, Aβ+ aMCI was more similar to AD than Aβ− aMCI in terms of semantic memory disruption. Semantic memory may serve as an early indicator of brain Aβ pathology. Therefore, semantic memory dysfunction deserves more consideration in clinical practice. Longitudinal research with the follow-up data is needed.
Aging ; Alzheimer Disease ; Animals ; Brain ; Dementia ; Follow-Up Studies ; Humans ; Memory* ; Memory, Episodic ; Mild Cognitive Impairment* ; Pathology ; Semantics* ; Word Association Tests

OBJECTIVES: This study aimed to evaluate the association between dental implants and cognitive function in community-dwelling older adults. METHODS: Data were collected from the baseline survey (2016–2017) of the Korean Frailty and Aging Cohort Study. The study sample comprised 1115 community-dwelling people aged 70 years to 84 years who had 0-19 natural teeth. Dental implants and natural teeth were identified by panoramic radiography, while the cognitive function was assessed by the Korean version of the Mini-Mental State Examination (MMSE-KC). The association between dental implants and cognitive function was analyzed by multiple linear regression. Sensitivity analysis was performed to test for potential bias. RESULTS: The mean number of natural teeth in the study population was 9.50 (standard deviation [SD], 6.42), and the mean MMSE-KC score was 24.93 (SD, 3.55). In the simple univariate analysis, tooth replacement, age, sex, smoking status, alcohol consumption, body mass index, osteoporosis, number of natural teeth, periodontitis, chewing discomfort, tooth-brushing frequency, education level, monthly household income, participation in economic activity, living alone, and marital status had a significant impact on the association. After adjusting for confounders, the association between dental implants and cognitive function remained significant (B, 0.85; standard error, 0.40; p<0.05). Age, body mass index, periodontitis, tooth-brushing frequency, and education level were also significantly associated with cognitive function. The results of the sensitivity analyses were consistent with those of the primary analysis. CONCLUSIONS: Dental implants were associated with cognitive function in older adults living in the community. Dental implants as tooth replacements may play a role in preserving cognitive function.
Adult ; Aging ; Alcohol Drinking ; Bias (Epidemiology) ; Body Mass Index ; Cognition ; Cognitive Reserve ; Cohort Studies ; Dental Implants ; Education ; Family Characteristics ; Humans ; Korea ; Linear Models ; Marital Status ; Mastication ; Osteoporosis ; Periodontitis ; Prostheses and Implants ; Radiography, Panoramic ; Smoke ; Smoking ; Surveys and Questionnaires ; Tooth

Diagnostic guidelines for the preclinical, mild cognitive impairment, and dementia stages of Alzheimer's disease (AD) were released by the National Institute on Aging and Alzheimer's Association (NIA-AA) in 2011. Promoted by the subsequent scientific progress, a unifying update, the ‘NIA-AA Research Framework', was published in 2018. This new research framework shifts the definition of AD from syndrome to biological construct based on biomarkers in living people. The biomarkers were grouped into β amyloid deposition (A), pathologic tau (T), and neurodegeneration (N) related, termed the ‘AT(N) classification system#x2019;, which could be extended with new biomarkers as they become available in the future. For the staging of cognitive impairment, three syndromal stages for observational studies and six numeric stages for clinical trials were also suggested. This biomarker-based classification combined with clinical staging is expected to enhance the understanding of AD as well as aid in precise targeting for interventional clinical trials. This review focused on the introduction of the new 2018 NIA-AA Research Framework. Although this framework has been proposed for research purposes, it is expected to be adopted into general clinical practice with thorough examination and validation in the future.
Alzheimer Disease ; Biomarkers ; Classification ; Cognition Disorders ; Dementia ; Mild Cognitive Impairment ; National Institute on Aging (U.S.) ; Plaque, Amyloid

OBJECTIVE: This study aimed to examine the association between normal-but-low folate levels and cognitive function in the elderly population using a prospective cohort study. METHODS: We analyzed 3,910 participants whose serum folate levels were within the normal reference range (1.5–16.9 ng/mL) at baseline evaluation in the population-based prospective cohort study named the “Korean Longitudinal Study on Cognitive Aging and Dementia.” The association between baseline folate quartile categories and baseline cognitive disorders [mild cognitive impairment (MCI) or dementia] was examined using binary logistic regression analysis adjusting for confounding variables. The risks of incident MCI and dementia associated with the decline of serum folate level during a 4-year follow-up period were examined using multinomial logistic regression analysis. RESULTS: The lowest quartile group of serum folate (≥1.5, ≤5.9 ng/mL) showed a higher risk of cognitive disorders than did the highest quartile group at baseline evaluation (odds ratio 1.314, p=0.012). Over the 4 years of follow-up, the risk of incident dementia was 2.364 times higher among subjects whose serum folate levels declined from the 2nd–4th quartile group to the 1st quartile than among those for whom it did not (p=0.031). CONCLUSION: Normal-but-low serum folate levels were associated with the risk of cognitive disorders in the elderly population, and a decline to normal-but-low serum folate levels was associated with incident dementia. Maintaining serum folate concentration above 5.9 ng/mL may be beneficial for cognitive status.
Aged ; Cognition ; Cognition Disorders ; Cognitive Aging ; Cohort Studies ; Confounding Factors (Epidemiology) ; Dementia ; Folic Acid ; Follow-Up Studies ; Humans ; Logistic Models ; Longitudinal Studies ; Prospective Studies ; Reference Values