Sex difference in the association between BMI and cognitive impairment in Chinese older adults.

BACKGROUND: The association between body mass index (BMI) and cognitive impairment (CI) has been the subject of extensive research, yet the precise dose-response effects remain undefined. METHODS: Older adults were selected from the 2011/2012 survey at baseline and the new recruits from the 2014 and 2018 waves of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Multiple logistic regression models were used to evaluate the association between BMI categories and CI, and Restricted Cubic Spline (RCS) was used to explore the nonlinear relationship between BMI and CI. RESULTS: The study included 29,380 older adults aged from 65 to 117 years, with an average age of 82 years. Of these, 13,465 were men, and 5359 exhibited cognitive impairment. The logistic model indicated that in female participants, being underweight was positively correlated with CI (OR:1.32; 95%CI 1.20-1.46), whereas being overweight was inversely correlated with CI (OR:0.86; 95%CI 0.75-0.99), and we didn't find any association between BMI category and CI in male participants. RCS modeling revealed a U-shaped relationship between BMI and CI. When stratified by sex, men exhibited a similar trend, with the lowest risk at a BMI of 22.774 kg/ m2, while women had the lowest risk of CI at a BMI of 24.817 kg/ m2. LIMITATION: This was a cross-sectional study, it cannot provide information on causal relationships. CONCLUSION: A U-shaped relationship was observed between BMI and CI in older adults, more pronounced in the male population, suggesting that male older adults may need to manage their BMI more rigorously.

High-performance aqueous zinc ion hybrid capacitors obtained by Na2SO4 additive and dense pore structure.

In this study, the electrochemical performance of zinc ion hybrid capacitors (ZICs) was improved by employing carbon-based materials and electrolyte together. First, we prepared pitch-based porous carbon HC-800 as the electrode material, which possessed a large specific surface area (3607 m2 g-1) and a dense pore structure. This provided abundant adsorption sites for zinc ions, and thus stored more charges. Subsequently, 0.5 M Na2SO4 was added to 1 M Zn(CF3SO3)2 electrolyte via the cationic additive strategy, and the adsorption energy of sodium and zinc ions on the zinc electrode was calculated. The results showed that sodium ions would preferentially be adsorbed on the surface of the zinc electrode, which would inhibit the growth of zinc dendrites, and thus prolong the service life of the zinc electrode. Finally, the presence of solvated zinc ions in the narrowly distributed pores of HC-800 was studied, and the results showed that Zn(H2O)62+ underwent a desolvation process, resulting in the removal of two water molecules to form a tetrahedral structure of Zn(H2O)42+, which made the central surface of the zinc ions closer to the surface of HC-800, and thus the more capacitance achieved. Furthermore, the uniform distribution of Zn(H2O)42+ in the dense and neat pores of HC-800, improved the space charge density. Consequently, the assembled ZIC exhibited a high capacity (242.25 mA h g-1 at 0.5 A g-1) and ultra-long cycle stability (capacity retention at 87% after 110 000 charge/discharge cycles at a high current density of 50 A g-1 and a coulombic efficiency of 100%) and an energy density of 186.1 W h kg-1 and power density of 41 004 W kg-1.

Review on the Application of Low-Field Nuclear Magnetic Resonance Technology in Coalbed Methane Production Simulation.

Low-field nuclear magnetic resonance has become one of the main methods to characterize static parameters and dynamic changes in unconventional reservoirs. The research focus of this paper is process simulation of coalbed methane (CBM) production. The dynamic variation of pore volume with different pore sizes during pressure drop, methane desorption-diffusion process, and methane-water interaction during migration is discussed. Moreover, the calculation principles of NMR single and multifractal models are systematically described, and the applicability of NMR fractal models within different research contexts is discussed. Four aspects need urgent attention in the application of this technology in CBM production: (1) overburden NMR technology has limitations in characterizing the stress sensitivity of shale and high-rank coal reservoirs with micropores developed, and we should aim to enable an accurate description of micropore pore stress sensitivity; (2) dynamic NMR physical simulation of reservoir gas and water production based on in-situ and actual geological development conditions should become one of the key aspects of follow-up research; (3) low-temperature freeze-thaw NMR technology, as a new pore-fracture characterization method, needs to be further applied in characterizing the distribution characteristics of pores and fractures; and (4) NMR fractal model should be used as the main theoretical method to expand the simulation results. The applicability of different fractal models in characterizing pore-fracture structure (static) and CBM production process (dynamic) needs to be clarified.

Population-attributable fractions of risk factors for all-cause dementia in China rural and urban areas: a cross-sectional study.

BACKGROUND: The prevalence of dementia in China, particularly in rural areas, is consistently increasing; however, research on population-attributable fractions (PAFs) of risk factors for dementia is scarce. METHODS: We conducted a cross-sectional survey, namely, the China Multicentre Dementia Survey (CMDS) in selected rural and urban areas from 2018 to 2020. We performed face-to-face interviews and neuropsychological and clinical assessments to reach a consensus on dementia diagnosis. Prevalence and weighted PAFs of eight modifiable risk factors (six classical: less childhood education, hearing impairment, depression, physical inactivity, diabetes, and social isolation, and two novels: olfactory decline and being unmarried) for all-cause dementia were estimated. RESULTS: Overall, CMDS included 17,589 respondents aged ≥ 65 years, 55.6% of whom were rural residents. The age- and sex-adjusted prevalence for all-cause dementia was 9.11% (95% CI 8.96-9.26), 5.19% (5.07-5.31), and 11.98% (11.8-12.15) in the whole, urban, and rural areas of China, respectively. Further, the overall weighted PAFs of the eight potentially modifiable risk factors were 53.72% (95% CI 52.73-54.71), 50.64% (49.4-51.89), and 56.54% (55.62-57.46) in the whole, urban, and rural areas of China, respectively. The eight risk factors' prevalence differed between rural and urban areas. Lower childhood education (PAF: 13.92%) and physical inactivity (16.99%) were primary risk factors in rural and urban areas, respectively. CONCLUSIONS: The substantial urban-rural disparities in the prevalence of dementia and its risk factors exist, suggesting the requirement of resident-specific dementia-prevention strategies.

The Hubei Memory and Aging Cohort Study: Study Design, Baseline Characteristics, and Prevalence of Cognitive Impairments.

BACKGROUND: Despite the improved access to health services in China, inadequate diagnosis and management of dementia are common issues, especially in rural regions. OBJECTIVE: The Hubei Memory & Aging Cohort Study was designed as a prospective study in Central China to determine the prevalence, incidence, and risk factors for dementia and mild cognitive impairment (MCI) among urban and rural older adults. METHODS: From 2018-2020, participants aged ≥65 years were screened, and data regarding their life behaviors, families, socio-economic status, physical and mental health, social and psychological factors, and cognition were collected. Diagnoses of MCI and dementia were made via consensus diagnosis using the Diagnostic and Statistical Manual of Mental Disorders fourth edition criteria. RESULTS: Of 8,221 individuals who completed their baseline clinical evaluation, 4,449 (54.1%) were women and 3,164 (38.4%) were from remote rural areas (average age: 71.96 years; mean education period: 7.58 years). At baseline, 25.98%(95%confidence interval [CI]: 24.99-26.96) and 7.24%(95%CI: 6.68-7.80) of the participants were diagnosed with MCI and dementia, respectively. Prevalence showed a strong relationship with age. The substantial disparities between rural and urban regions in MCI and dementia prevalence and multiple dementia-related risk factors were revealed. Especially for dementia, the prevalence rate in rural areas was 2.65 times higher than that in urban regions. CONCLUSION: Our results suggested that public health interventions are urgently needed to achieve equitable diagnosis and management for people living with dementia in the communities across urban and rural areas.

Urban-rural disparities in mild cognitive impairment and its functional subtypes among community-dwelling older residents in central China.

BACKGROUND: Substantial variations in the prevalence of mild cognitive impairment (MCI) and its subtypes have been reported, although mostly in geographically defined developed countries and regions. Less is known about MCI and its subtypes in rural areas of less developed central China. AIMS: The study aimed to compare the prevalence of MCI and its subtypes in residents aged 65 years or older in urban and rural areas of Hubei Province, China. METHODS: Participants aged 65 years or older were recruited between 2018 and 2019. Inperson structured interviews and clinical and neuropsychological assessments were performed at city health community centres and township hospitals. RESULTS: Among 2644 participants without dementia, 735 had MCI, resulting in a prevalence of 27.8% for total MCI, 20.9% for amnestic MCI (aMCI) and 6.9% for non-amnestic MCI (naMCI). The prevalence of MCI in urban and rural areas was 20.2% and 44.1%, respectively. After adjusting for demographic factors, the prevalence of total MCI, aMCI and naMCI differed significantly between rural and urban areas (adjusted odds ratio (OR) 2.10, 1.44 and 3.76, respectively). Subgroup analysis revealed an association between rural socioeconomic and lifestyle disadvantage and MCI and its subtypes. CONCLUSIONS: Our findings suggest that the prevalence of MCI among urban residents in central China is consistent with that in other metropolis areas, such as Shanghai, but the prevalence in rural areas is twice that in urban areas. Prospective studies and dementia prevention in China should focus on rural areas.

Urban-Rural Disparities in the Association Between Body Mass Index and Cognitive Impairment in Older Adults: A Cross-Sectional Study in Central China.

BACKGROUND: Some studies have demonstrated an association between low and high body mass index (BMI) and an increased risk of dementia. However, only a few of these studies were performed in rural areas. OBJECTIVE: This cross-sectional study investigated the associations between BMI and cognitive impairment among community-dwelling older adults from rural and urban areas. METHODS: 8,221 older persons enrolled in the Hubei Memory & Ageing Cohort Study (HMACS) were recruited. Sociodemographic and lifestyle data, comorbidities, physical measurements, and clinical diagnoses of cognitive impairment were analyzed. Logistic regression was performed to assess the associations of BMI categories with cognitive impairment. A series of sensitivity analyses were conducted to test whether reverse causality could influence our results. RESULTS: Being underweight in the rural-dwelling participants increased the risk of cognitive impairment. Being overweight was a protective factor in rural-dwelling participants aged 65-69 years and 75-79 years, whereas being underweight was significantly associated with cognitive impairment (OR, 1.37; 95% CI: 1.03-1.83; p < 0.05). Sensitivity analyses support that underweight had an additive effect on the odds of cognitive impairment and was related to risk of dementia. Interaction test revealed that the differences between urban/rural in the relationship between BMI and cognitive impairment are statistically significant. CONCLUSION: Associations between BMI and cognitive impairment differ among urban/rural groups. Older people with low BMI living in rural China are at a higher risk for dementia than those living in urban areas.

Geological Control of Irreducible Water Within the Coal Matrix and Its Quantified Evaluation Model.

This paper adopts the measurement of mercury intrusion porosimetry and nuclear magnetic resonance (NMR) to analyze the pore system and the pore structure of coal samples, and the measurement of maceral group composition, scanning electron microscopy, and energy dispersive X-ray spectroscopy to obtain the organic/inorganic composition of coal samples. Gravimetric and NMR methods are both used to calculate irreducible water saturation of the samples, and qualitative and quantitative research studies are therefore conducted. The following knowledge is obtained. Coal samples can be classified as micro-trans-pore-dominated samples, meso-macro-pore-dominated samples, cleat-dominated samples, and even development samples. The main composition of the samples is organic, and a little kaolinite and pyrite can be observed. Irreducible water saturation obtained by the gravimetric method is almost close to that gained by the NMR method. The influencing parameters can be divided into two categories. The first category contains the maximum vitrinite reflectance, volumetric factor, fixed carbon yield, volatile yield, vitrinite percentage, and inertinite percentage, which have a strong correlation with irreducible water saturation. The second category includes the buried depth and median radius, and they have a weak correlation with irreducible water saturation. Multivariate regression shows that there is a linear quaternion equation between irreducible water saturation and independent variables such as maximum vitrinite reflectance, volumetric factor, volatile yield, and vitrinite percentage.

A dengue fever predicting model based on Baidu search index data and climate data in South China.

With the acceleration of global urbanization and climate change, dengue fever is spreading worldwide. Different levels of dengue fever have also occurred in China, especially in southern China, causing enormous economic losses. Unfortunately, there is no effective treatment for dengue, and the most popular dengue vaccine does not exhibit good curative effects. Therefore, we developed a Generalized Additive Mixed Model (GAMM) that gathered climate factors (mean temperature, relative humidity and precipitation) and Baidu search data during 2011-2015 in Guangzhou city to improve the accuracy of dengue fever prediction. Firstly, the time series dengue fever data were decomposed into seasonal, trend and remainder components by the seasonal-trend decomposition procedure based on loess (STL). Secondly, the time lag of variables was determined in cross-correlation analysis and the order of autocorrelation was estimated using autocorrelation (ACF) and partial autocorrelation functions (PACF). Finally, the GAMM was built and evaluated by comparing it with Generalized Additive Mode (GAM). Experimental results indicated that the GAMM (R2: 0.95 and RMSE: 34.1) has a superior prediction capability than GAM (R2: 0.86 and RMSE: 121.9). The study could help the government agencies and hospitals respond early to dengue fever outbreak.