scholarly journals Improvement in Sleep Duration was Associated with Higher Cognitive Function among Middle-Aged and Elderly Chinese Participants

2020 ◽  
Author(s):  
Jianian Hua ◽  
Hongpeng Sun ◽  
Yueping She
Keyword(s):  
Cognitive Function ◽  
Sleep Duration ◽  
Linear Models ◽  
Generalized Additive Models ◽  
Cognitive Status ◽  
Additive Models ◽  
Short Sleep Duration ◽  
Estimation Equations ◽  
Global Cognition ◽  
Figure Drawing

AbstractStudy objectivesRodent studies suggested that improvement in sleep duration might correlate with better cognitive function. We aimed to examine the associations between changes in sleep duration and cognitive function.Methods10325 individuals from the China Health and Retirement Longitudinal Study (CHARLS) were included. Self-reported nocturnal sleep duration and cognitive function were assessed in CHARLS 2011, 2013 and 2015 (Wave 1, Wave 2, Wave3). Cognitive function was assessed by a global cognition score, which included three domains: episodic memory, figure drawing and Telephone Interview of Cognitive Status (TICS). Generalized additive models (GAM) and Generalized estimation equations (GEE) were used to examine the associations between baseline sleep duration and longitudinal cognitive function. We used generalized linear models (GLM) to study the associations between changes in sleep duration and cognitive function in Wave 3.ResultsAfter adjusting for potential confounders, change from short sleep duration (SSD) to moderate sleep duration (MSD) was associated with better global cognition scores (β=0.54, P <0.01). Change from SSD to long sleep duration (LSD) (β=-0.94, P <0.001) or change from LSD to SSD (β=-1.38, P <0.01) was associated with lower global cognition. For individuals with MSD, ≥2 h increase (β=-0.89, P <0.001) or decrease (β=-0.70, P <0.001) in sleep duration was associated with lower global cognition.ConclusionsFor short sleepers, improvement in sleep duration correlated with better cognition. For long sleepers, there was no need to reduce sleep duration. Excessive changes or deviation from the moderate duration was associated with lower cognition.

scholarly journals Higher visit-to-visit total cholesterol variability is associated with lower cognitive function among middle-aged and elderly Chinese men

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Jianian Hua ◽  
Yanan Qiao ◽  
Chaofu Ke ◽  
Yueping Shen
Keyword(s):  
Cognitive Function ◽  
Episodic Memory ◽  
Total Cholesterol ◽  
Estimating Equation ◽  
Cognitive Status ◽  
Linear Regression Models ◽  
High Tc ◽  
Elderly Chinese ◽  
Global Cognition ◽  
Figure Drawing

Abstract To examine the prospective associations between total cholesterol (TC) variability and cognitive function in a large sample of Chinese participants aged 45 years and above. A total of 6,377 people who participated in the China Health and Retirement Longitudinal Study (CHARLS) were included. TC variability was defined as the intra-individual standard deviation over two blood tests in CHARLS 2011 and 2015 (Wave 1 and Wave 3). Cognitive function was assessed by a global cognition score, which included three tests: episodic memory, figure drawing and Telephone Interview of Cognitive Status (TICS). Multivariate linear regression models (MRLMs) and generalized estimating equation (GEE) were used to investigate associations between TC variability and cognitive scores. After adjusting for potential confounders, male participants with higher visit-to-visit TC variability showed lower global cognition scores (β = − 0.71, P < 0.001). After further adjustment for baseline cognition, the association remained statistically significant (β = − 0.68, P < 0.001). The domains with declines were focused on episodic memory (β = − 0.22, P = 0.026) and TICS (β = − 0.44, P = 0.004). However, these associations were not found in women (β = − 0.10, P = 0.623). For men, the rates of decline in global cognition increased by 0.14 (β = − 0.14, P = 0.009) units per year while TC variability increased by 1 mmol/L. For males, higher visit-to-visit TC variability correlated with lower cognitive function and an increased rate of decreases in memory. More attention should be paid to cognitive decline in males with high TC variability, and particularly, on decreases in memory, calculation, attention and orientation.

scholarly journals Bidirectional Associations between Short or Long Sleep Duration and Cognitive Function: the China Health and Retirement Longitudinal Study

2021 ◽  
Author(s):  
Jianian Hua ◽  
Hongpeng Sun ◽  
Qi Fang
Keyword(s):  
Longitudinal Study ◽  
Cognitive Function ◽  
Sleep Duration ◽  
Short Sleep Duration ◽  
Short Sleep ◽  
Bidirectional Association ◽  
Long Sleep ◽  
Global Cognition ◽  
Bidirectional Associations ◽  
Prospective Longitudinal

AbstractIMPORTANCEThe bidirectional association between sleep duration and cognitive function has not been conclusively demonstrated.OBJECTIVETo investigate the longitudinal association between sleep duration and cognitive function among middle-aged and elderly Chinese participants.Design, SETTING, AND PARTICIPANTSA national representative and prospective longitudinal study in China. 7984 participants aged 45 years and above were assessed at baseline between June 2011 and March 2012 (wave 1) and 2013 (wave 2), 2015 (wave 3) and 2018 (wave4).MAIN OUCOMES AND MEASURESSelf-reported nighttime sleep duration was evaluated by interview. Cognitive function was evaluated via assessments of global cognition, which reflected the ability of episodic memory, visuospatial construction, calculation, orientation and attention.ResultsRegarding the 7984 participants in wave 4, the mean (SD) age was 64.7 (8.4), 3862 (48.4) were male, and 6453 (80.7) lived in rural area. There were 14981, 11768 (78.6%), 10192 (68.0%), 7984 (53.3%) participants in the four waves of the study, respectively. Latent growth models showed both sleep duration and global cognition worsen over time. Cross-lagged models indicated that long or short sleep duration in the previous wave was associated lower global cognition in the next wave (standardized β=-0.066; 95%CI: −0.073, −0.059; P<0.001; Wave 1 to 2), and lower global cognition in the previous wave was associated with long or short sleep duration in the next wave (standardized β=-0.106; 95%CI: −0.116, −0.096; P<0.001; Wave 1 to 2). Global cognition was probably the major driver in this reciprocal associations.CONCLUSIONS AND REVELANCEThere were bidirectional associations between long or short sleep duration and cognitive function. Lower cognitive function had a stronger association with worse cognitive function than the reverse. A moderate sleep duration is always recommended. Moreover, attention should be paid on the declined cognition and cognitive therapy among older adults with short or long sleep duration.

scholarly journals Elevated HDL Levels Linked to Poorer Cognitive Ability in Females With Parkinson’s Disease

2021 ◽  
Vol 13 ◽  
Author(s):  
Megan C. Bakeberg ◽  
Anastazja M. Gorecki ◽  
Jade E. Kenna ◽  
Alexa Jefferson ◽  
Michelle Byrnes ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Function ◽  
Cognitive Performance ◽  
Linear Models ◽  
Low Density Lipoprotein ◽  
Density Lipoprotein ◽  
Cognitive Status ◽  
Cross Sectional ◽  
Age Related

IntroductionCholesterol levels have been associated with age-related cognitive decline, however, such an association has not been comprehensively explored in people with Parkinson’s disease (PD). To address this uncertainty, the current cross-sectional study examined the cholesterol profile and cognitive performance in a cohort of PD patients.MethodsCognitive function was evaluated using two validated assessments (ACE-R and SCOPA-COG) in 182 people with PD from the Australian Parkinson’s Disease Registry. Total cholesterol (TC), high-density lipoprotein (HDL), low-density lipoprotein (LDL), and Triglyceride (TRG) levels were examined within this cohort. The influence of individual lipid subfractions on domain-specific cognitive performance was investigated using covariate-adjusted generalised linear models.ResultsFemales with PD exhibited significantly higher lipid subfraction levels (TC, HDL, and LDL) when compared to male counterparts. While accounting for covariates, HDL levels were strongly associated with poorer performance across multiple cognitive domains in females but not males. Conversely, TC and LDL levels were not associated with cognitive status in people with PD.ConclusionHigher serum HDL associates with poorer cognitive function in females with PD and presents a sex-specific biomarker for cognitive impairment in PD.

scholarly journals The Evolution of Data Sharing Practices in the Psychological Literature

2021 ◽  
Author(s):  
Judith Neve ◽  
Guillaume A Rousselet
Keyword(s):  
Data Sharing ◽  
Linear Models ◽  
Generalized Additive Models ◽  
Additive Models ◽  
Future Research ◽  
Science Data ◽  
Editorial Policies ◽  
Psychological Science ◽  
The Impact

Sharing data has many benefits. However, data sharing rates remain low, for the most part well below 50%. A variety of interventions encouraging data sharing have been proposed. We focus here on editorial policies. Kidwell et al. (2016) assessed the impact of the introduction of badges in Psychological Science; Hardwicke et al. (2018) assessed the impact of Cognition’s mandatory data sharing policy. Both studies found policies to improve data sharing practices, but only assessed the impact of the policy for up to 25 months after its implementation. We examined the effect of these policies over a longer term by reusing their data and collecting a follow-up sample including articles published up until December 31st, 2019. We fit generalized additive models as these allow for a flexible assessment of the effect of time, in particular to identify non-linear changes in the trend. These models were compared to generalized linear models to examine whether the non-linearity is needed. Descriptive results and the outputs from generalized additive and linear models were coherent with previous findings: following the policies in Cognition and Psychological Science, data sharing statement rates increased immediately and continued to increase beyond the timeframes examined previously, until reaching close to 100%. In Clinical Psychological Science, data sharing statement rates started to increase only two years following the implementation of badges. Reusability rates jumped from close to 0% to around 50% but did not show changes within the pre-policy nor the post-policy timeframes. Journals that did not implement a policy showed no change in data sharing rates or reusability over time. There was variability across journals in the levels of increase, so we suggest future research should examine a larger number of policies to draw conclusions about their efficacy. We also encourage future research to investigate the barriers to data sharing specific to psychology subfields to identify the best interventions to tackle them.

scholarly journals An investigation of human vs. technology-induced variation in catchability for a selection of European fishing fleets

2011 ◽  
Vol 68 (10) ◽  
pp. 2252-2263 ◽  
Author(s):  
Stéphanie Mahévas ◽  
Youen Vermard ◽  
Trevor Hutton ◽  
Ane Iriondo ◽  
Angélique Jadaud ◽  
...  
Keyword(s):  
Linear Models ◽  
Generalized Additive Models ◽  
Technical Information ◽  
Fishing Effort ◽  
Additive Models ◽  
Induced Variation ◽  
Fishing Fleets ◽  
The Impact ◽  
Selection Of ◽  
Experience Effect

Abstract Mahévas, S., Vermard, Y., Hutton, T., Iriondo, A., Jadaud, A., Maravelias, C. D., Punzón, A., Sacchi, J., Tidd, A., Tsitsika, E., Marchal, P., Goascoz, N., Mortreux, S., and Roos, D. 2011. An investigation of human vs. technology-induced variation in catchability for a selection of European fishing fleets. – ICES Journal of Marine Science, 68: 2252–2263. The impact of the fishing effort exerted by a vessel on a population depends on catchability, which depends on population accessibility and fishing power. The work investigated whether the variation in fishing power could be the result of the technical characteristics of a vessel and/or its gear or whether it is a reflection of inter-vessel differences not accounted for by the technical attributes. These inter-vessel differences could be indicative of a skipper/crew experience effect. To improve understanding of the relationships, landings per unit effort (lpue) from logbooks and technical information on vessels and gears (collected during interviews) were used to identify variables that explained variations in fishing power. The analysis was undertaken by applying a combination of generalized additive models and generalized linear models to data from several European fleets. The study highlights the fact that taking into account information that is not routinely collected, e.g. length of headline, weight of otter boards, or type of groundrope, will significantly improve the modelled relationships between lpue and the variables that measure relative fishing power. The magnitude of the skipper/crew experience effect was weaker than the technical effect of the vessel and/or its gear.

Climate Influences on Meningitis Incidence in Northwest Nigeria

2014 ◽  
Vol 6 (1) ◽  
pp. 62-76 ◽  
Author(s):  
Auwal F. Abdussalam ◽  
Andrew J. Monaghan ◽  
Vanja M. Dukić ◽  
Mary H. Hayden ◽  
Thomas M. Hopson ◽  
...  
Keyword(s):  
Generalized Linear Models ◽  
Linear Models ◽  
Generalized Additive Models ◽  
Skill Score ◽  
Additive Models ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Explanatory Variables ◽  
Score Statistics

Abstract Northwest Nigeria is a region with a high risk of meningitis. In this study, the influence of climate on monthly meningitis incidence was examined. Monthly counts of clinically diagnosed hospital-reported cases of meningitis were collected from three hospitals in northwest Nigeria for the 22-yr period spanning 1990–2011. Generalized additive models and generalized linear models were fitted to aggregated monthly meningitis counts. Explanatory variables included monthly time series of maximum and minimum temperature, humidity, rainfall, wind speed, sunshine, and dustiness from weather stations nearest to the hospitals, and the number of cases in the previous month. The effects of other unobserved seasonally varying climatic and nonclimatic risk factors that may be related to the disease were collectively accounted for as a flexible monthly varying smooth function of time in the generalized additive models, s(t). Results reveal that the most important explanatory climatic variables are the monthly means of daily maximum temperature, relative humidity, and sunshine with no lag; and dustiness with a 1-month lag. Accounting for s(t) in the generalized additive models explains more of the monthly variability of meningitis compared to those generalized linear models that do not account for the unobserved factors that s(t) represents. The skill score statistics of a model version with all explanatory variables lagged by 1 month suggest the potential to predict meningitis cases in northwest Nigeria up to a month in advance to aid decision makers.

scholarly journals Percolation models of pathogen spillover

2019 ◽  
Vol 374 (1782) ◽  
pp. 20180331 ◽  
Author(s):  
Alex D. Washburne ◽  
Daniel E. Crowley ◽  
Daniel J. Becker ◽  
Kezia R. Manlove ◽  
Marissa L. Childs ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Linear Models ◽  
Mechanistic Model ◽  
Piecewise Linear ◽  
Generalized Additive Models ◽  
Additive Models ◽  
Management Intervention ◽  
Management Concepts ◽  
The Impact ◽  
Reservoir Hosts

Predicting pathogen spillover requires counting spillover events and aligning such counts with process-related covariates for each spillover event. How can we connect our analysis of spillover counts to simple, mechanistic models of pathogens jumping from reservoir hosts to recipient hosts? We illustrate how the pathways to pathogen spillover can be represented as a directed graph connecting reservoir hosts and recipient hosts and the number of spillover events modelled as a percolation of infectious units along that graph. Percolation models of pathogen spillover formalize popular intuition and management concepts for pathogen spillover, such as the inextricably multilevel nature of cross-species transmission, the impact of covariance between processes such as pathogen shedding and human susceptibility on spillover risk, and the assumptions under which the effect of a management intervention targeting one process, such as persistence of vectors, will translate to an equal effect on the overall spillover risk. Percolation models also link statistical analysis of spillover event datasets with a mechanistic model of spillover. Linear models, one might construct for process-specific parameters, such as the log-rate of shedding from one of several alternative reservoirs, yield a nonlinear model of the log-rate of spillover. The resulting nonlinearity is approximately piecewise linear with major impacts on statistical inferences of the importance of process-specific covariates such as vector density. We recommend that statistical analysis of spillover datasets use piecewise linear models, such as generalized additive models, regression clustering or ensembles of linear models, to capture the piecewise linearity expected from percolation models. We discuss the implications of our findings for predictions of spillover risk beyond the range of observed covariates, a major challenge of forecasting spillover risk in the Anthropocene. This article is part of the theme issue ‘Dynamic and integrative approaches to understanding pathogen spillover’.

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