• Journal of Nutrition and Health
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• v.41 no.8
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• pp.733-741
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• 2008

In the present study, we comprehensively examined the associations of plasma levels of total adiponectin and high molecular weight (HMW) adiponectin with the features of cardiometabolic risks including body fat distribution, dyslipidemia, insulin resistance and inflammatory markers in a cross-sectional study of 110 treated hypertensive patients. Blood lipid profiles, high sensitivity C-reactive protein (hsCRP) and homeostasis model assessment of insulin resistance (HOMA- IR) derived from fasting glucose and insulin concentrations were determined. Plasma levels of tumor necrosis factor-${\alpha}$ (TNF-${\alpha}$), interleukin-6 (IL-6) and intercellular adhesion molecule-1 (ICAM-1) were analyzed using ELISA. The results showed that plasma levels of HMW-adiponectin were negatively associated with body mass index (BMI, r = - 0.203, p < 0.05) and waist circumference (r = -0.307, p < 0.01), which was not shown in total adiponectin. Plasma levels of HMW-adiponectin were negatively associated with triglyceride (r = -0.223, p < 0.05) and positively associated with HDL-cholesterol (r = 0.228, p < 0.05). Plasma levels of adiponectin were positively associated with HDL-cholesterol (r = 0.224, p < 0.05). Plasma levels of HMW-adiponectin were negatively associated with hsCRP (r = -0.276, p < 0.01) and IL-6 (r = -0.272, p < 0.01). In addition, there were weak associations between plasma levels of HMWadiponectin and TNF-${\alpha}$ (r = -0.163, p = 0.07) and ICAM-1 (r = -0.158, p = 0.09). However, there were no significant associations of total adiponectin with inflammatory markers except hsCRP (r = -0.203, p < 0.05). Stepwise multiple linear regression analysis showed that only plasma levels of HMW-adiponectin was an independent factor influencing serum levels of hsCRP, a marker of systemic low grade inflammation, after adjusting for age, gender, BMI, waist circumference, alcohol intake, smoking status, blood lipids, total adiponectin and drug use (p < 0.01). These results suggest that HMW-adiponectin, rather than total adiponectin, is likely to be closely associated with the features of cardiometabolic risks in treated hypertensive patients and might be effective biomarker for the prediction of cardiovascular disease.

• Sleep Medicine and Psychophysiology
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• v.21 no.1
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• pp.5-13
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• 2014

Objectives: Depression, sleep complaints and cognitive impairments are commonly observed in the elderly. Elderly subjects with depressive symptoms have been found to show both poor cognitive performances and sleep disturbances. However, the relationship between sleep complaints and cognitive dysfunction in elderly depression is not clear. The aim of this study is to identify the association between sleep disturbances and cognitive decline in late-life depression. Methods: A total of 282 elderly people who underwent nocturnal polysomnography in a sleep laboratory were enrolled in the study. The Korean version of the Neuropsychological Assessment Battery developed by the Consortium to Establish a Registry for Alzheimer's Disease (CERAD-K) was applied to evaluate cognitive function. Depressive symptoms were assessed with the geriatric depression scale (GDS) and subjective sleep quality was measured using the Pittsburg sleep quality index (PSQI). Results: The control group ($GDS{\leq}9$) when compared with mild ($10{\leq}GDS{\leq}16$) and severe ($17{\leq}GDS$) depression groups, had significantly different scores in the Trail making test part B (TMT-B), Benton visual retention test part A (BVRT-A), and Stroop color and word test (SCWT)(all tests p<0.05). The PSQI score, REM sleep duration, apnea-hypopnea index and oxygen desaturation index were significantly different across the three groups (all indices, p<0.05). A stepwise multiple regression model showed that educational level, age and GDS score were predictive for both TMT-B time (adjusted $R^2$=35.6%, p<0.001) and BVRT-A score (adjusted $R^2$=28.3%, p<0.001). SCWT score was predicted by educational level, age, apnea-hypopnea index (AHI) and GDS score (adjusted $R^2$=20.6%, p<0.001). Poor sleep quality and sleep structure alterations observed in depression did not have any significant effects on cognitive deterioration. Conclusion: Older adults with depressive symptoms showed mild sleep alterations and poor cognitive performances. However, we found no association between sleep disturbances (except sleep apnea) and cognitive difficulties in elderly subjects with depressive symptoms. It is possible that the impact of sleep disruptions on cognitive abilities was hindered by the confounding effect of age, education and depressive symptoms.