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.

Mild cognitive impairment (MCI) is a high-risk factor for dementia¹ and a major public health issue worldwide, posing a serious social and financial burden on patients and caregivers.² Although the prevalence of late-life dementia is expected to increase, effective disease-modifying treatments are currently unavailable. Therefore, it is important to elucidate risk or protective factors associated with the cortical amyloid burden or brain function to delay cognitive impairment. Potentially modifiable risk factors for dementia have been identified and include low levels of education, vascular risk factors, lifestyle factors, and hearing loss.^2-5 In particular, physical inactivity, sleep disturbance, social isolation, and depression are important risk factors for late-life cognitive impairment.^5-8 Most observational studies have used self-report questionnaires that are of limited utility owing to their poor reliability and consistency, which is attributed to recall bias or misclassification, particularly among older people or those with MCI.^8,9 Wearable sensors have been used to evaluate lifestyle factors, such as physical activity and sleep, in large epidemiological studies.^10-14 Wearable sensors are noninvasive and cost-effective and can objectively measure total daily movement and sleep without recall bias. We have previously reported an association between objectively measured walking steps, conversation time, and global cognitive function in community-dwelling older adults,¹⁴ based on which we hypothesized that these lifestyle factors were associated with cortical amyloid burden or brain function. To our knowledge, only a few studies have examined the association between objectively measured lifestyle factors and the results of positron emission tomography (PET) imaging, including carbon-11 labeled Pittsburgh compound B (PiB)-PET and fluorine-18 fluorodeoxyglucose (FDG)-PET in older adults with MCI. Therefore, the present study aimed to use wearable sensors to explore whether modifiable lifestyle factors are associated with cortical amyloid burden and cerebral glucose metabolism in community-dwelling older adults with MCI.

Background: This study examined the effect of white matter lesions (WMLs) on regional cerebral blood flow (rCBF) in patients with Alzheimer’s disease (AD). Methods: Ninety-eight patients with AD were included in the study (40 men and 58 women; mean age, 78.1 years). Cognitive function was assessed using the Mini-Mental State Examination. Brain magnetic resonance imaging (MRI) and ^99mTc ethyl cysteinate dimer single photon emission computed tomography were performed in all subjects. AD patients were divided into two subgroups according to the presence of WMLs on MRI. A voxel-by-voxel group analysis using Statistical Parametric Mapping 8 was used to detect the differences in rCBF between the two groups. Results: Fifty-seven of 98 AD patients (58%) showed mild to moderate WMLs on MRI. The prevalence of hypertension was significantly higher in AD patients with WMLs than in those without WMLs. AD patients with WMLs exhibited a significantly decreased rCBF in the anterior cingulate gyrus and insula, compared to AD patients without WMLs. Conclusion: We suggest that WMLs might influence brain regions associated with the limbic system in patients with AD.

Benign gynecologic tumor, such as uterine adenomyosis, has been suggested to develop hypercoagulability. Although some cases of cerebral infarction associated with adenomyosis have been reported, the mechanism of hypercoagulation initiated by adenomyosis is still not clear, and the therapeutic strategy is uncertain. A 44-year-old woman was presented to our department with headache, left hand weakness, and gait disturbance during her menstrual phase. She had a history of adenomyosis and infertility treatment for 18 years and heavy menstrual bleeding. Magnetic resonance imaging on admission showed multiple hyperintense lesions in cortical and subcortical areas in the cerebrum and cerebellum on diffusion-weighted imaging. Transesophageal echocardiography showed neither embolic sources nor existence of foramen ovale. Her laboratory data revealed anemia, a high D-dimer level, and elevated levels of a mucinous tumor marker. She had adenomyosis and no malignancy was detected. Anticoagulation therapy with intravenous heparin followed by rivaroxaban did not prevent recurrence of cerebral infarction. We discontinued rivaroxaban, and started warfarin therapy with pseudomenopause treatment, which prevented recurrence for 6 months. Five months after her last pseudomenopause treatment, multiple cerebral infarctions occurred. Total hysterectomy was performed, which prevented recurrence of the multiple cerebral infarctions for 2 years without anticoagulation therapy. Our findings reveal for the first time that anticoagulation therapy, including novel oral anticoagulants, had no preventive effect against cerebral infarctions associated with adenomyosis in a middle-aged woman. Although pseudomenopause treatment temporarily prevented recurrence, resection of the adenomyosis might be the most effective therapy in these cases.