The Relationships Between Components of Metabolic Syndrome and Mild Cognitive Impairment Subtypes: A Cross-Sectional Study of Japanese Older Adults

2017 ◽  
Vol 60 (3) ◽  
pp. 913-921 ◽  
Author(s):  
Seongryu Bae ◽  
Hiroyuki Shimada ◽  
Sangyoon Lee ◽  
Hyuma Makizako ◽  
Sungchul Lee ◽  
...  
Keyword(s):  
Older Adults ◽  
Metabolic Syndrome ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Cross Sectional ◽  
Japanese Older Adults

scholarly journals Correlates of Sleep Disturbance among Older Adults with Mild Cognitive Impairment: A Cross-Sectional Study

2020 ◽  
Vol 17 (13) ◽  
pp. 4862
Author(s):  
Dan Song ◽  
Doris S. F. Yu ◽  
Qiuhua Sun ◽  
Guijuan He
Keyword(s):  
Older Adults ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Sleep Disturbance ◽  
Cross Sectional Study ◽  
Healthy Controls ◽  
Sectional Study ◽  
Related Factors ◽  
Cross Sectional ◽  
Comorbidity Burden

Individuals with mild cognitive impairment (MCI) are at high risk for dementia development. Sleep disturbance is often overlooked in MCI, although it is an important risk factor of cognitive decline. In the absence of a cure for dementia, managing the risk factors of cognitive decline in MCI is likely to delay disease progression. To develop interventions for sleep disturbance in MCI, its related factors should be explored. This study aimed to identify and compare the correlates of sleep disturbance in older adults with MCI and those in cognitively healthy older adults. A comparative cross-sectional study was adopted. Data were obtained from 219 Chinese community-dwelling older adults (female: 70.3%), which consisted of 127 older adults with MCI and 92 age-matched cognitively healthy controls. The candidate correlates of sleep disturbance included socio-demographic correlates, health-related factors, lifestyle-related factors and psychological factor. Descriptive, correlational and regression statistics were used for data analysis. The prevalence of sleep disturbance in MCI was 70.1% compared to that of 56.5% in cognitively healthy controls (p < 0.001). The multivariate analysis indicated that, in participants with MCI, depressive symptoms (Beta = 0.297, p = 0.001), comorbidity burden (Beta = 0.215, p = 0.012) and physical activity (Beta = −0.297, p = 0.001) were associated with sleep disturbance. However, in the cognitively healthy controls, only depressive symptoms (Beta = 0.264, p = 0.028) and comorbidity burden (Beta = 0.361, p = 0.002) were associated with sleep disturbance. This finding highlights that sleep disturbance is sufficiently prominent to warrant evaluation and management in older adults with MCI. Furthermore, the findings elucidate several important areas to target in interventions aimed at promoting sleep in individuals with MCI.

scholarly journals Impaired abstract thinking may discriminate between normal aging and vascular mild cognitive impairment

2010 ◽  
Vol 68 (2) ◽  
pp. 179-184 ◽  
Author(s):  
Felipe Kenji Sudo ◽  
Gilberto Sousa Alves ◽  
Carlos Eduardo de Oliveira Alves ◽  
Maria Elisa Lanna ◽  
Letice Ericeira-Valente ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cerebrovascular Disease ◽  
Cognitive Deficits ◽  
Cross Sectional Study ◽  
Abstract Thinking ◽  
Sectional Study ◽  
Cross Sectional ◽  
Elderly Individuals ◽  
Healthy Elderly

OBJECTIVE: Cerebrovascular disease (CVD) is associated with cognitive deficits. This cross-sectional study examines differences among healthy elderly controls and patients with vascular mild cognitive impairment (VaMCI) and vascular dementia (VaD) in performances on CAMCOG subscales. METHOD: Elderly individuals (n=61) were divided into 3 groups, according to cognitive and neuroimaging status: 16 controls, 20 VaMCI and 25 VaD. VaMCI and VaD individuals scored over 4 points on the Hachinski Ischemic Scale. RESULTS: Significant differences in total CAMCOG scores were observed across the three groups (p<0.001). VaD subjects performed worse than those with VaMCI in most CAMCOG subscales (p<0.001). All subscales showed differences between controls and VaD (p<0.001). Performance on abstract thinking showed difference between VaMCI and controls (p<0.001). CONCLUSION: CAMCOG discriminated controls from VaMCI and VaD. Assessment of abstract thinking may be useful as a screening item for diagnosis of VaMCI.

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