A cohort study of association between sleep duration and cognitive impairment in the elderly aged 65 years and older in China / 中华流行病学杂志

Objective: To explore the effect of sleep duration on the risk of cognitive impairment in the elderly in China. Methods: Baseline data of 9 679 elderly individuals with intact cognition were collected from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) in 2005, and followed up was conducted until 2018. Cox proportional hazards model was used to analyze the association between different sleep durations and the risk for cognitive impairment in the elderly. Results: Compared with elderly with sleep duration of 6 hours per day, those with sleep duration less than 5 hours had increased risk for cognitive impairment by 30% (HR=1.30, 95%CI: 1.05-1.62), and those with sleep durations of 7 hours, 8 hours and more than 9 hours had increased risk for cognitive impairment by 34% (HR=1.34,95%CI: 1.09-1.64), 40% (HR=1.40,95%CI: 1.17-1.69) and 43% (HR=1.43,95%CI: 1.19-1.70), respectively. Trend test showed that the risk of cognitive impairment increased with the extension of sleep duration (>6 h), and there was a dose-response relationship (P<0.001). However, self-rated sleep quality was not associated with the risk for cognitive impairment in the elderly. Conclusions: The shorter and longer sleep duration were associated an increased risk of cognitive impairment in the elderly aged ≥65 years in China, suggesting that optimizing sleep duration might delay the occurrence of cognitive impairment.

A cohort study on the influence of the chronic diseases on falls among middle-aged and older Chinese / 中华流行病学杂志

Objective: To analyze the influence of chronic diseases on falls among middle-aged and older Chinese. Methods: Baseline data of 13 670 middle-aged and older adults recruited from China Health and Retirement Longitudinal Study (CHARLS) in 2011 were used and followed up to 2018, among those were 7 443 (54.45%) middle-aged people aged 45-59 and 6 227 (45.55%) older adults aged 60 and above. The Cox proportional hazards model was used to analyze the effects of different types, the number of chronic diseases and the interaction between chronic illness and other factors on the fall risk of middle-aged and older people. Results: After adjusting for confounding factors, respiratory diseases increased the risk of falls by 21% (HR=1.21, 95%CI:1.02-1.45), and arthritis increased the risk of falls by 27% (HR=1.27,95%CI: 1.12-1.43) in the group aged 45-59, kidney disease increased the risk of falls by 26% (HR=1.26, 95%CI: 1.03-1.53) in the group aged 60 and above. A linear dose-response relationship between the number of chronic diseases and fall risk (χ2=133.61, P<0.001) was found in all the age groups. The interaction between having chronic diseases and the factors of females (HR=1.64, 95%CI: 1.43-1.89), impaired activities of daily living (ADL) (HR=1.66, 95%CI: 1.39-1.99), and having a fall history (HR=2.58, 95%CI: 2.24-2.97) increased the risk of falls. Conclusions: There is a positive linear relationship between the number of chronic diseases and the fall risk among Chinese aged 45 and above. The female middle-aged and elderly patients with chronic diseases and the middle-aged and elderly patients with impaired ADL or a history of falls are the high-risk groups for falls that need to be focused on intervention. The window of fall injury prevention should be moved forward to the middle-aged stage in time.

Discrimination of Microbe Species by Laser Induced Breakdown Spectroscopy / 分析化学

Laser induced breakdown spectroscopy ( LIBS ) was proposed to rapidly discriminate microbe species. Ten species of microbes were prepared in lab. Filter papers were selected as substrate for enriching bacteria and enhancing the quality of LIBS. The images of plasma were collected by ICCD camera and LIBS spectra were obtained by spectrometers. The results displayed that the images and spectra were different from 10 bacteria. It was demonstrated that this method was feasible to discriminate bacteria species by analyzing image and/or spectroscopy. Furthermore, nine smooth and multiple scattering correction ( MSC) were utilized to preprocess the LIBS full-spectrum data in the wavelength range of 200-420 nm and 560-680 nm. And principal component analysis ( PCA) and PCA-RF ( Random forest) were compared to validate the accuracy of discrimination. The investigation showed that the PCA-RF model coupled with suitable methods in preprocessing data could identify bacteria. The accuracy was 99. 6% for ten species of microbes by evaluating LIBS spectra in training set, and 96. 7% in predicting set. This report indicated that it is feasible to differentiate bacteria species by analyzing LIBS spectra.