The association between smoking and family health with the mediation role of personality among Chinese people: nationwide cross-sectional study.

BACKGROUND: There may be unexplored interactions between family health, personality, and smoking that could help provide new perspectives on tobacco control. OBJECTIVE: To examine the relationship between the health of one's family and their smoking habits, as well as investigate the potential influence of personality on this relationship. METHODS: For this cross-sectional investigation, a national survey conducted in China in 2022 recruited a total of 21,916 individuals. The Family Health Scale was utilized to assess the health of the family. The 10-item Big Five Inventory scale was utilized to assess the Big five personality traits. The relationship between big five personality, family health, and smoking were investigated using binary and linear logistic regression. The indirect effects mediated by Big five personality were analyzed using mediation analysis with Sobel tests, and the indirect effects were composited using the Karlson-Holm-Breen method. RESULTS: The overall prevalence of smoking in the study population was 14.87%, 26.19% for males and 3.54% for females. Urban and rural smoking prevalence was 13.81% and 16.10% respectively. Binary logistic regression analysis revealed a significant negative relationship between smoking and family health (odds ratio 0.964, 95% CI 0.959, 0.970, P < 0.001) with covariates controlled. The Karlson-Holm-Breen composition facilitated the connection between extraversion (47.81%) and nervousness (52.19%). CONCLUSIONS: Preventive interventions for smoking behavior should prioritize family health and the Big five personality as significant areas to focus on. According to this study, in addition to implementing various interventions for different personalities, family health should be strengthened to reduce smoking behavior.

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.

Impact of Preparative Isolation of C-Glycosylflavones Derived from Dianthus superbus on In Vitro Glucose Metabolism.

Dianthus superbus L. has been extensively studied for its potential medicinal properties in traditional Chinese medicine and is often consumed as a tea by traditional folk. It has the potential to be exploited in the treatment of inflammation, immunological disorders, and diabetic nephropathy. Based on previous studies, this study continued the separation of another subfraction of Dianthus superbus and established reversed-phase/reversed-phase and reversed-phase/hydrophilic (RPLC) two-dimensional (2D) high-performance liquid chromatography (HPLC) modes, quickly separating two C-glycosylflavones, among which 2″-O-rhamnosyllutonarin was a new compound and isomer with 6‴-O-rhamnosyllutonarin. This is the first study to investigate the effects of 2″-O-rhamnosyllutonarin and 6‴-O-rhamnosyllutonarin on cellular glucose metabolism in vitro. First, molecular docking was used to examine the effects of 2″-O-rhamnosyllutonarin and 6″-O-rhamnosyllutonarin on AKT and AMPK; these two compounds exhibited relatively high activity. Following this, based on the HepG2 cell model of insulin resistance, it was proved that both of the 2″-O-rhamnosyllutonarin and 6‴-O-rhamnosyllutonarin demonstrated substantial efficacy in ameliorating insulin resistance and were found to be non-toxic. Simultaneously, it is expected that the methods developed in this study will provide a basis for future studies concerning the separation and pharmacological effects of C-glycosyl flavonoids.

Risk profiles for smoke behavior in COVID-19: a classification and regression tree analysis approach.

BACKGROUND: COVID-19 pandemic emerged worldwide at the end of 2019, causing a severe global public health threat, and smoking is closely related to COVID-19. Previous studies have reported changes in smoking behavior and influencing factors during the COVID-19 period, but none of them explored the main influencing factor and high-risk populations for smoking behavior during this period. METHODS: We conducted a nationwide survey and obtained 21,916 valid data. Logistic regression was used to examine the relationships between each potential influencing factor (sociodemographic characteristics, perceived social support, depression, anxiety, and self-efficacy) and smoking outcomes. Then, variables related to smoking behavior were included based on the results of the multiple logistic regression, and the classification and regression tree (CART) method was used to determine the high-risk population for increased smoking behavior during COVID-19 and the most profound influencing factors on smoking increase. Finally, we used accuracy to evaluated the performance of the tree. RESULTS: The strongest predictor of smoking behavior during the COVID-19 period is acceptance degree of passive smoking. The subgroup with a high acceptation degree of passive smoking, have no smokers smoked around, and a length of smoking of ≥ 30 years is identified as the highest smoking risk (34%). The accuracy of classification and regression tree is 87%. CONCLUSION: The main influencing factor is acceptance degree of passive smoking. More knowledge about the harm of secondhand smoke should be promoted. For high-risk population who smoke, the "mask protection" effect during the COVID-19 pandemic should be fully utilized to encourage smoking cessation.

The Association Between Personality Traits and Health-Related Quality of Life and the Mediating Role of Smoking: Nationwide Cross-Sectional Study.

Background: There are positive and negative correlations in different directions between smoking, personality traits, and health-related quality of life (HRQOL), where smoking may mask the pathway between personality traits and HRQOL. Understanding the masking pathway of smoking between personality traits and HRQOL can elucidate the mechanisms of smoking's psychosocial effects and provide new ideas for developing tobacco control strategies. Objective: The purpose of this study was to investigate the correlation between Big Five personality traits and HRQOL and whether smoking mediates the relationship between them. Methods: This was a cross-sectional study using data from 21,916 respondents from the 2022 Psychology and Behavior Investigation of Chinese Residents survey. Linear regression models were used to analyze the correlations between smoking, Big Five personality traits, and HRQOL while controlling for potential confounders. The mediating role of smoking on the association between Big Five Personality traits and HRQOL was analyzed using the Sobel-Goodman mediation test. Results: Extraversion (ß=.001; P=.04), agreeableness (ß=.003; P<.001), and neuroticism (ß=.003; P<.001) were positively correlated with HRQOL, whereas openness was negatively correlated with HRQOL (ß=-.001; P=.003). Smoking was associated with a decrease in HRQOL and mediated the positive effect of HRQOL on extraversion (z=-2.482; P=.004), agreeableness (z=-2.264; P=.02), and neuroticism (z=-3.230; P=.001). Subgroup analyses further showed that smoking mediated the effect of neuroticism on HRQOL in the population with chronic illnesses (z=-2.724; P=.006), and in the population without chronic illnesses, smoking contributed to the effect of HRQOL on extraversion (z=-2.299; P=.02), agreeableness (z=-2.382; P=.02), and neuroticism (z=-2.213; P=.03). Conclusions: This study provided evidence that there is a correlation between personality traits and HRQOL. It also found that smoking plays a role in mediating the connection between personality traits and HRQOL. The development of future tobacco control strategies should consider the unique traits of each individual's personality, highlighting the significance of extraversion, agreeableness, and neuroticism.

The relationship of intimate partner violence on depression: the mediating role of perceived social support and the moderating role of the Big Five personality.

Introduction: This study aimed to explore the influence of Intimate Partner Violence (IPV) on depression, the mediating role of social support, and the moderating role of the Big Five personality traits in the relationship between social support and depression. Methods: Participants were recruited from Mainland China, using a stratified random sampling and quota sampling method. From June to August 2022, a diverse group of 21,916 participants (ranging from 12 to 100 years old) completed the Intimate Partner Violence Scale, Patient Health Questionnaire, Perceived Social Support Scale, and Big Five Inventory-Short Version. Results: IPV was significantly positively correlated with depression and significantly negatively correlated with perceived social support. Perceived social support plays a mediating role in the link between IPV and depression. Discussion: Healthcare workers should assess social support and provide adequate care or recommendations for increasing social support when patients with IPV report depressive symptoms. Patients can be coached by professionals to improve their resiliency by developing or nurturing more optimistic personality traits.

The mediating role of negative emotions in the relationship between smoking and health-related quality of life among Chinese individuals: A cross-sectional study.

INTRODUCTION: Although the negative impact of smoking on health has been confirmed in various studies, few have explored psychological factors mediating the relationship between smoking and health-related quality of life (HRQOL). This study aimed to investigate the relationship between smoking and HRQOL in the Chinese population and the mediating role of negative emotions (NEs). METHODS: Survey data were derived from a cross-sectional study conducted in China from 20 June to 31 August 2022. We recruited participants from 148 cities across the country using a stratified multistage sampling method. The HRQOL of the dependent variable was measured using the Chinese version of European Quality of Life-5 Dimensions (EQ-5D-5L). The Patient Health Questionnaire (PHQ-9), Generalized Anxiety Disorder (GAD-7), and Perceived Stress Scale (PSS-4) were used to measure NE parameters including depression, anxiety, and perceived stress, as the intermediate variables. A multiple parallel mediation model was used to analyze the mediating role of NEs in smoking and HRQOL. RESULTS: A total of 21916 valid questionnaires were collected, of which 3010 (13.7%) and 18906 (86.3%) were categorized into smokers and non-smokers, respectively. The HRQOL (EQ-VAS score) of smokers (71.70 ± 23.08) was lower than that of non-smokers (73.69 ± 21.32), whereas the depression and anxiety levels of smokers were higher than those of non-smokers (all p<0.001). Moreover, smoking, NEs (depression and anxiety), and HRQOL showed pairwise correlations. According to the mediation analysis, depression (ß= -0.461; 95% BCa CI: -0.664 - -0.268) and anxiety (ß= -0.279; 95% BCa CI: -0.435 - -0.138) mediated the relationship between smoking and HRQOL after adjusting for demographic and life factors. CONCLUSIONS: These findings emphasize the necessity of studying the interaction between smoking, HRQOL, and Nes, and complementing the research on the impact of psychological factors on the HRQOL of smokers. Public health activities should focus on mental health and take targeted measures for the prevention, treatment, and rehabilitation of smokers.

Influence of social support on subjective well-being of patients with chronic diseases in China: chain-mediating effect of self-efficacy and perceived stress.

Introduction: The well-being of patients with chronic diseases is an issue of widespread concern in public health. While social support is thought to have a positive effect on it, the mechanisms of its influence have not been fully addressed. Thus, we explored the possible mediating effects of self-efficacy and perceived stress to determine the relationship between social support and well-being in these patients. Methods: A cross-sectional study was conducted among 4,657 patients with chronic diseases in China. The PROCESS Macro model 6 of SPSS was employed to explore the intermediary role between variables. Results: Self-efficacy and perceived stress played a partial intermediary role between social support and subjective well-being, with an effect ratio of 48.25% and 23.61%, respectively. Self-efficacy and perceived stress had a chain intermediary effect (28.14%) between social support and subjective well-being. Discussion: This study suggested that improving the self-efficacy of patients with chronic diseases to cope with the changes in social support caused by the disease could reduce stress and enhance subjective well-being.