Impaired glucose metabolism slows executive function independent of cerebral ischemic lesions in Japanese elderly: the Takahata study

Tooth Loss-associated Cognitive Impairment in the Elderly: A Community-based Study in Japan

Objective Dementia is a major cause of disruption for a healthy life expectancy in Japan. It has been suggested that the number of teeth is a modifiable risk factor for cognitive impairment and dementia. We therefore examined the possible association between the cognitive function and the number of natural and artificial teeth in community-dwelling Japanese elderly individuals. Methods Among the participants in our prospective, community-based study, 210 elderly individuals (103 men and 107 women; 78.1±4.9 years; mean age±standard deviation) underwent both dental examinations and a Mini-Mental State Examination (MMSE), as well as various medical checkups, in 2016 and 2017. Results The number of natural teeth was significantly associated with an individual's MMSE score. The percentage of cognitively normal subjects (MMSE scores: 27-30) decreased significantly with a decrease in the number of natural teeth. Among the MMSE items, the calculation ability was significantly and independently associated with the number of natural teeth. Regression was calculated as the predicted score of MMSE =21+0.3× (years of schooling) +0.1× (number of natural teeth). Among individuals with 19 or fewer natural teeth, those who had a total of 20 teeth or more, including both natural and artificial teeth, had significantly higher MMSE scores than those who had 19 or fewer natural and artificial teeth combined. Conclusion The number of natural teeth was significantly associated with the cognitive function, especially the calculation ability, and the use of artificial teeth was associated with the preservation of the cognitive function in community-dwelling elderly individuals.

Cognitive impairment, brain ischemia and shorter telomeres are predictors of mortality in the Japanese elderly: A 13-year prospective community-based study

OBJECTIVE

To examine whether cognitive impairment, deep white matter hyperintensity (DWMH) on brain MRI, and shorter telomere length would be predictors of mortality in community-dwelling Japanese elderly.

METHODS

We followed 259 individuals (74% of all the residents at age 70) from age 70 to 83 years. The mean observation period was 133 ± 34 months. The key clinical characteristics examined included DWMH on brain MRI and cognitive function. Telomere length was also measured in 81 subjects. Both univariate and multivariate analyses were performed.

RESULTS

Of the 259 subjects, 69 subjects (30 men, 39 women; 26.6%) died during the follow-up period. Cognitive impairment, smoking habits, diabetes mellitus, and moderate to severe DWMH were significant predictors of total mortality in univariate analysis. However, only cognitive impairment and moderate to severe DWMH remained as significant independent predictors of death in multivariate analysis. The rate of mortality increased with additional number of risk factors (cognitive impairment and DWMH). The total mortality of subjects with both cognitive impairment and DWMH was 71.4%. The median telomere length was 7.8 kb in the deceased and 8.2 kb in the living subjects. The deceased subjects had significantly shorter telomere length (P = .0025) than the living subjects. Telomere length with moderate to severe DWMH was higher than without moderate to severe DWMH on brain MRI (P = .017).

CONCLUSIONS

The present study revealed that cognitive impairment, DWMH, and shorter telomere length were significant predictors of total mortality in the community-dwelling Japanese elderly. Furthermore, the combination of cognitive impairment and DWMH increased the mortality rate, as compared with a single risk factor. It is also clarified that a significant difference was present in telomere length by severity of DWMH.

Modeling metabolic syndrome and its association with cognition: the Northern Manhattan study

Metabolic syndrome (MetS) is a clustering of vascular risk factors and is associated with increased risk of cardiovascular disease. Less is known about the relationship between MetS and cognition. We examined component vascular risk factors of MetS as correlates of different cognitive domains. The Northern Manhattan Study (NOMAS) includes 1290 stroke-free participants from a largely Hispanic multi-ethnic urban community. We used structural equation modeling (SEM) to model latent variables of MetS, assessed at baseline and an average of 10 years later, at which time participants also underwent a full cognitive battery. The two four-factor models, of the metabolic syndrome (blood pressure, lipid levels, obesity, and fasting glucose) and of cognition (language, executive function, psychomotor, and memory), were each well supported (CFI=0.97 and CFI=0.95, respectively). When the two models were combined, the correlation between metabolic syndrome and cognition was -.31. Among the metabolic syndrome components, only blood pressure uniquely predicted all four cognitive domains. After adjusting for age, gender, race/ethnicity, education, smoking, alcohol, and risk factor treatment variables, blood pressure remained a significant correlate of all domains except memory. In this stroke-free race/ethnically diverse community-based cohort, MetS was associated with cognitive function suggesting that MetS and its components may be important predictors of cognitive outcomes. After adjusting for sociodemographic and vascular risk factors, blood pressure was the strongest correlate of cognitive performance. Findings suggest MetS, and in particular blood pressure, may represent markers of vascular or neurodegenerative damage in aging populations.

Metabolic syndrome factors and risk of postoperative depression in high-grade glioma patients in a 1.5-year prospective study

To date, the relationship between metabolic syndrome factors and the risk of glioma-related depression is still unclear, and no study investigates this relationship. Our aim was to investigate the relationship between metabolic syndrome factors and the risk of postoperative depression in high-grade patients. A total of 386 high-grade glioma patients participated in blood sample collection for metabolic syndrome factors analysis and the hospital anxiety and depression scale testing. The association between metabolic syndrome factors and the risk of postoperative depression was assessed using Cox regression proportional hazards models, and Student's t tests were used to evaluate the differences in demographic variables and clinical characteristics in subgroups. The incidence of postoperative depression in our 1.5-year follow-up was 30.5%. We found the risk of postoperative depression was elevated with increased blood glucose level [hazard ratios (HR) 2.277, 95% confidence interval (CI) 1.201-4.320, top vs. bottom quartile]. The hazard ratio was increased for z-scores of blood glucose (HR 1.672 per unit standard deviation, 95% CI 1.311-2.133] and of the combined metabolic syndrome score (HR 1.080, 95% CI 1.000-1.167). In addition, risk of postoperative depression risk was increased in high-grade glioma patients with high blood glucose levels (≥6.0 mmol/l) (HR 2.084, 95% CI 1.235-3.515). However, we did not find significant associations between postoperative depression and other metabolic syndrome factors, including body mass index, systolic blood pressure, diastolic blood pressure, cholesterol, and triglycerides. Depression is prevalent among patients with high-grade glioma after operation. Blood glucose level is positively associated with the risk of postoperative depression, and might be involved in the etiology of postoperative depression, and may predict its development in high-grade glioma patients.

Response time measurements in the iOS app-based Token Test, the Brief Token Test in the elderly

AIM

A pen and paper Token Test utilizing binary scoring of accuracy-inaccuracy in responses evaluates linguistic functions including verbal comprehension. However, the test might not be sensitive enough to detect the aging effect on performance in normal older adults unless the test utilizes a multidimensional scoring system. We hypothesized that the measurement of response time (RT) instead of accuracy would be a feasible way to measure deterioration of verbal comprehension as a function of age in this linguistically vulnerable population.

METHODS

Data were acquired from 174 community-dwelling normal older adults (147 females and 27 males, mean age 75.9 ± 6.13 years, range 65-94 years). In order to automatically quantify accuracies and RT, we developed an iOS app-based Token Test, comprising of four subtests (24 items, 6 items in each subtest), and administered it to each participant.

RESULTS

RT of the second, third and fourth subtests (P<0.001, P<0.01, P<0.05, respectively) and the average RT across all four subtests (P<0.01) had significant partial correlation coefficients with age. The results of the multiple linear regression analyses showed that the models for RT and average RT analyses of the three subtests (2, 3 and 4) included the age variable.

CONCLUSION

RT measurement of the iOS app-based Token Test could be highly useful and convenient to better detect abnormalities in linguistic efficiency. RT measurement in the Token Test could be used as a screening tool for linguistic slowing in the elderly population.

Effects of type 2 diabetes on 12-year cognitive change: results from the Maastricht Aging Study

OBJECTIVE

To examine the effects of baseline and incident diabetes on change in cognitive function over 12 years.

RESEARCH DESIGN AND METHODS

A sample of 1,290 individuals aged ≥ 40 years at baseline, participating in the Maastricht Aging Study, were cognitively tested at baseline, after 6 years, and after 12 years. Of these, 68 participants had type 2 diabetes at baseline, and 54 and 57 had incident diabetes at the 6- and 12-year follow-up, respectively. Changes in performance on tests of information-processing speed, executive function, and verbal memory from baseline to 6- and 12-year follow-up were compared between groups using linear mixed models. Effects of diabetes on cognitive decline were adjusted for demographic variables, history of smoking, alcohol intake, and comorbid conditions, including hypertension, cardiovascular disease, BMI, and depression.

RESULTS

Participants with baseline diabetes showed larger decline in information-processing speed (estimate -7.64; P < 0.01), executive function (21.82; P < 0.01), and delayed word recall (-1.35; P < 0.05) over the 12-year follow-up compared with control subjects. No significant difference in decline was observed for immediate word recall. Compared with control subjects, participants with incident diabetes showed subtle early decline in information-processing speed only. Interestingly, they did not show larger decline in any other cognitive domain.

CONCLUSIONS

Individuals with baseline type 2 diabetes show accelerated cognitive decline, particularly in information-processing speed and executive function, compared with individuals without diabetes. In incident diabetes, decline in speed becomes detectable first, and cognitive decline seems to increase with increasing exposure time.