Risk profiling of tobacco epidemic and estimated number of smokers living in China: a cross-sectional study based on PBICR.

BACKGROUND: Evidence on the prevalence of smoking in China remains insufficient, with most previous studies focusing on a single region. However, smoking prevalence exhibits significant inequalities across the entire country. This study aimed to evaluate the risk of tobacco prevalence across the country, taking into account spatial inequalities. METHODS: The data used in this study were collected in 23 provinces, 5 autonomous regions, and 4 municipalities directly under the central government in 2022. Large population survey data were used, and a Bayesian geostatistical model was employed to investigate smoking prevalence rates across multiple spatial domains. FINDINGS: Significant spatial variations were observed in smokers and exposure to secondhand smoke across China. Higher levels of smokers and secondhand smoke exposure were observed in western and northeastern regions. Additionally, the autonomous region of Tibet, Shanghai municipality, and Yunnan province had the highest prevalence of smokers, while Tibet, Qinghai province, and Yunnan province had the highest prevalence of exposure to secondhand smoke. CONCLUSION: We have developed a model-based, high-resolution nationwide assessment of smoking risks and employed rigorous Bayesian geostatistical models to help visualize smoking prevalence predictions. These prediction maps provide estimates of the geographical distribution of smoking, which will serve as strong evidence for the formulation and implementation of smoking cessation policies. HIGHLIGHTS: Our study investigated the prevalence of smokers and exposure to secondhand smoke in different spatial areas of China and explored various factors influencing the smoking prevalence. For the first time, our study applied Bayesian geostatistical modeling to generate a risk prediction map of smoking prevalence, which provides a more intuitive and clear understanding of the spatial disparities in smoking prevalence across different geographical regions, economic levels, and development status. We found significant spatial variations in smokers and secondhand smoke exposure in China, with higher rates in the western and northeastern regions.

Medical Personnel Behavior Preferences for Providing mHealth Service in China: A Discrete Choice Experiment.

Purpose: This study aims to investigate factors affecting medical personnel behavioral preferences for providing mHealth in China, so as to provide decision-making basis for mHealth providers and managers to encourage more doctors to participate in mHealth service delivery. Methods: Typical case sampling techniques were applied in a hospital setting to conduct a discrete choice experimental questionnaire survey of doctors (n=216) concerning mHealth preferences between July and October 2022. A conditional logit model was used to assess medical personnel preferences for each attribute and level of mHealth services. Results: Length of service, information security, subjects of treatment and financial compensation all have a significant effect on medical staff's preference for providing mHealth services (p < 0.05). In terms of service duration and financial compensation, medical staff preferred mHealth services that provided shorter service duration and higher financial compensation; in terms of information security, medical staff preferred mHealth services with confidentiality of diagnostic and therapeutic information compared to information disclosure; and in terms of treatment targets, medical staff preferred the general population compared to key populations, such as pregnant women, the elderly, infants and children. Conclusion: The preference of medical professionals to provide mHealth services is affected by a variety of factors. By enhancing the confidentiality of information in mHealth services, providing more options for service recipients, increasing their financial compensation, and shortening the duration of the service or increasing the number of service hours that can be adjusted can guide improvement of mHealth services and promoting of its adoption among medical professionals.

Association of depression symptoms and sleep quality with state-trait anxiety in medical university students in Anhui Province, China: a mediation analysis.

BACKGROUND: The prevalence of depression symptoms among medical students is particularly high, and it has increased during the COVID-19 epidemic. Sleep quality and state-trait anxiety are risk factors for depression, but no study has yet investigated the mediating role of state-trait anxiety in the relationship between poor sleep quality and depression symptoms in medical students. This study aims to investigate the relationship among depression symptoms, sleep quality and state-trait anxiety in medical university students in Anhui Province. METHODS: This was a cross-sectional survey of 1227 students' online questionnaires collected from four medical universities in Anhui Province using a convenience sampling method. We measured respondents' sleep quality, state-trait anxiety, and depression symptoms using three scales: the Pittsburgh Sleep Quality Index (PSQI), the State-Trait Anxiety Inventory (STAI) and the Self-rating Depression Scale (SDS). We analysed the mediating role of STAI scores on the association between PSQI scores and SDS scores through the Sobel-Goodman Mediation Test while controlling for covariates. P < 0.05 was considered statistically significant. RESULTS: A total of 74.33% (912) and 41.40% (518) of the respondents reported suffering from poor sleep quality and depression symptoms. Sleep quality, state-trait anxiety, and depression symptoms were positively associated with each other (ß = 0.381 ~ 0.775, P < 0.001). State-trait anxiety partially mediated the association between sleep quality and depression symptoms (Sobel test Z = 15.090, P < 0.001), and this mediating variable accounted for 83.79% of the association when adjusting for potential confounders. Subgroup analysis further revealed that STAI scores partially mediated the association between PSQI scores and SDS scores in females and rural students and fully mediated the association between PSQI scores and SDS scores in males and urban students. CONCLUSIONS: This study found that sleep quality and state-trait anxiety have a significant predictive effect on depression symptoms. State-trait anxiety mediated the relationship between sleep quality and depression symptoms, with a more complex mechanism observed among rural and female medical students. Multiple pathways of intervention should be adopted, such as encouraging students to self-adjust, providing professional psychological intervention and timely monitoring, enriching extracurricular activities, and making changes in policies regarding long shifts and working hours.

An ultra-sensitive colorimetric Hg(2+)-sensing assay based on DNAzyme-modified Au NP aggregation, MNPs and an endonuclease.

This paper reports the development of an ultra-sensitive colorimetric method for the detection of trace mercury ions involving DNAzymes, Au nanoparticle aggregation, magnetic nanoparticles and an endonuclease. DNAzyme-sensing elements are conjugated to the surface of Au nanoparticle-2, which can crosslink with the T-rich strands coated on Au nanoparticle-1 to form Au nanoparticle aggregation. Other T-rich stands are immobilized on the surface of MNPs. The specific hybridization of these two T-rich strands depends on the presence of Hg(2+), resulting in the formation of a T-Hg(2+)-T structure. Added endonuclease then digests the hybridized strands, and DNAzyme-modified Au NP aggregation is released, catalysing the conversion of the colourless ABTS into a blue-green product by H2O2-mediated oxidation. The increase in the adsorption spectrum of ABTS(+) at 421 nm is related to the concentration of Hg(2+). This assay was validated by detecting mercury ion concentrations in river water. The colorimetric responses were not significantly altered in the presence of 100-fold excesses of other metal ions such as Zn(2+), Pb(2+), Cd(2+), Mn(2+), Ca(2+) and Ni(2+). The inclusion of both Au NP aggregation and an endonuclease enables the assay to eliminate interference from the magnetic nanoparticles with colorimetric detection, decrease the background and improve the detection sensitivity. The calibration curve of the assay was linear over the range of Hg(2+) concentrations from 1 to 30 nM, and the detection limit was 0.8 nM, which is far lower than the 10 nM US EPA limit for drinking water.

A novel optical thrombin aptasensor based on magnetic nanoparticles and split DNAzyme.

In this paper, we report a novel and sensitive optical sensing protocol for thrombin detection based on magnetic nanoparticles (MNPs) and thrombin aptamer, employing split HRP-mimicking DNAzyme halves as its sensing element, which can catalyze the H(2)O(2)-mediated oxidation of the colorless ABTS into a blue-green product. A single nucleotide containing the recognition element and sensing element is utilized in our protocol. The specific recognition of thrombin and its aptamer leads to the structure deformation of the DNA strands and causes the split of the DNAzyme halves. Therefore, the decrease of absorption spectra can be recorded by the UV-visible Spectrophotometer. DNA-coated MNPs are utilized to separate the interferential materials from the analyst, thus making this assay can be applied in the detection of thrombin in complex samples, such as human plasma. This original, sensitive and cost-effective assay showed favorable recognition for thrombin. The absorbance signals with the concentration of thrombin over a range from 0.5 to 20 nM and the detection limit of thrombin was 0.5 nM. The controlled experiments showed that thrombin signal was not interfered in the presence of other co-existence proteins.