Association of Modifiable Lifestyle Factors With Cortical Amyloid Burden and Cerebral Glucose Metabolism in Older Adults With Mild Cognitive Impairment.

Importance: Understanding the association of lifestyle factors with mild cognitive impairment enables the development of evidence-based interventions for delaying cognitive impairment. Objective: To explore whether objectively measured lifestyle factors, such as physical activity, conversation, and sleep, are associated with cortical amyloid burden and cerebral glucose metabolism in older adults with mild cognitive impairment. Design, Setting, and Participants: This cohort study included 855 community-dwelling adults in Usuki, Oita Prefecture, Japan, aged 65 years or older. Data were collected from August 2015 to December 2017. Participants were reviewed to examine risk and protective lifestyle factors for dementia. Data analysis was conducted in June 2019. Exposures: Wearable sensors, carbon-11 labeled Pittsburgh compound B positron emission tomography images, and fluorine-18 fluorodeoxyglucose positron emission tomography images. Main Outcomes and Measures: Wearable sensor data, such as walking steps, conversation time, and sleep, were collected from August 2015 to October 2017, and positron emission tomography images were collected from October 2015 to December 2017. A multiple regression model and change-point regression model were used to examine the association of lifestyle factors with mean amyloid or fluorodeoxyglucose uptake, assessed on the basis of a standardized uptake value ratio of the frontal lobes, temporoparietal lobes, and posterior cingulate gyrus with the cerebellar cortex as the reference region. The bootstrap method was used to obtain nonparametric 95% CIs on the associations of lifestyle factors with cognitive decline. Results: Of the 855 adults in the study, 118 (13.8%) were diagnosed with mild cognitive impairment, with a mean (SD) age of 75.7 (5.8) years and 66 (55.9%) women. Total sleep time was inversely associated with fluorodeoxyglucose uptake after adjusting for covariates (ß = -0.287; 95% CI, -0.452 to -0.121, P < .001). Change-point regression showed an inverse association between total sleep time and mean amyloid uptake when sleep duration was longer than 325 minutes (B = -0.0018; 95% CI, -0.0031 to -0.0007). Conclusions and Relevance: To our knowledge, this is the first study to demonstrate that total sleep time was associated with brain function in older adults with mild cognitive impairment. Sleep duration is a potentially modifiable risk factor for dementia at the mild cognitive impairment stage.

Relationship Between the Japanese Version of the Montreal Cognitive Assessment and PET Imaging in Subjects with Mild Cognitive Impairment.

BACKGROUND: The Montreal Cognitive Assessment (MoCA) test has high sensitivity and specificity for detecting mild cognitive impairment or early dementia. How the MoCA score relates to findings of positron emission tomography imaging, however, remains unclear. OBJECTIVE: This prospective study examined the relationship between the Japanese version of the MoCA (MoCA-J) test and brain amyloid deposition or cerebral glucose metabolism among subjects with mild cognitive impairment. METHODS: A total of 125 subjects with mild cognitive impairment underwent the MoCA-J test, and amyloid- and 18F-fluorodeoxyglucose- positron emission tomography. Linear correlation analysis and multiple linear regression analysis were conducted to investigate the relationship between the MoCA-J score and demographic characteristics, amyloid deposition, and cerebral glucose metabolism. Moreover, Statistical Parametric Mapping 8 was used for a voxel-wise regression analysis of the MoCA-J score and cerebral glucose metabolism. RESULTS: The MoCA-J score significantly correlated with age, years of education, and the Mini-Mental State Examination score. After adjusting for age, sex, and education, the MoCA-J score significantly correlated negatively with amyloid retention (ß= -0.174, p= 0.031) and positively with cerebral glucose metabolism (ß= 0.183, p= 0.044). Statistical Parametric Mapping showed that Japanese version of MoCA score correlated with glucose metabolism in the bilateral frontal and parietal lobes, and the left precuneus. CONCLUSION: The total MoCA-J score correlated with amyloid deposition and frontal and parietal glucose metabolism in subjects with mild cognitive impairment. Our findings support the usefulness of the MoCA-J test for screening subjects at high risk for Alzheimer's disease.

Modifiable Lifestyle Factors and Cognitive Function in Older People: A Cross-Sectional Observational Study.

Background: The development of evidence-based interventions for delaying or preventing cognitive impairment is an important challenge. Most previous studies using self-report questionnaires face problems with reliability and consistency due to recall bias or misclassification among older people. Therefore, objective measurement of lifestyle components is needed to confirm the relationships between lifestyle factors and cognitive function. Aims: The current study examined the relationship between lifestyle factors collected with wearable sensors and cognitive function among community-dwelling older people using machine learning. Methods: In total, 855 participants (mean age: 73.8 years) wore a wristband sensor for 7.8 days on average every 3 months. Various lifestyle parameters were measured, including walking steps, conversation time, total sleep time (TST), sleep efficiency, time awake after sleep onset, awakening count, napping time, and heart rate. Random forest (RF) regression analysis was used to examine the relationships between total daily sensing data and Mini-Mental State Examination (MMSE) scores. Confounding factor analysis was conducted with models that were adjusted and unadjusted for demographic and vascular risk factors, and selected variables were assessed as risk and protective factors using partial dependence plots (PDPs). Results: Lifestyle data were collected for 31.3 ± 7.1 days per year using wristband sensors. RF regression analysis adjusted for age, gender, and education levels selected four variables, including number of walking steps, conversation time, TST, and heart rate. Moreover, walking steps, conversation time, and heart rate remained after RF regression analysis adjusted for demographic and vascular risk factors. Number of walking steps, conversation time, and heart rate were categorized as protective factors, whereas TST was categorized as a risk factor for cognitive function. Although PDPs of number of walking steps and heart rate revealed continuously increased MMSE scores, those of conversation time and TST and revealed that the tendency in the graph was reversed at the boundary of a particular threshold (321.1 min for conversation time, 434.1 min for TST). Conclusions: Lifestyle factors, such as physical activity, sleep, and social activity appear to be associated with cognitive function among older people. Physical activity and appropriate durations of sleep and conversation are important for cognitive function.