To explore the relationship between body roundness index (BRI) and new onset arthritis, and provide a new perspective for the prevention and treatment of arthritis.

A cohort study design was adopted, using the data of 2011 and 2020 in the China longitudinal study on the China Health and Retirement Longitudinal Study (CHARLS), taking BRI as the exposure factor, high-density lipoprotein cholesterol (HDL-C), total cholesterol, triglycerides, low-density lipoprotein cholesterol (LDL-C) as the intermediary variables, including demographic characteristics such as age and gender, smoking, alcohol consumption and other health behaviors as confounding factors, and new onset arthritis as the outcome. Statistical analysis was carried out using multiple model logistic regression strategy, restricted cubic spline, subgroup analysis and intermediary analysis. Compared with relevant studies, the main purpose of the dose-response relationship we explored is to study whether there is a nonlinear relationship between exposure and outcome, that is, whether the risk of outcome will change accordingly with the change of exposure level.

A total of 5 166 participants were included, and BRI was positively correlated with arthritis, with an OR value of 1.196 (95% CI: 1.047-1.367). The prevalence of new onset arthritis increased by 19.6% when BRI increased by a quartile range; The dose-response relationship showed that BRI > 3.943 was positively correlated with the incidence of arthritis; Subgroup analysis showed that the positive correlation between BRI and new onset arthritis was not affected by many factors; Mediation analysis showed that HDL-C had a protective effect on arthritis, mediating about 6.84% of the impact of BRI on the incidence of arthritis. The mediation effect of total cholesterol, triglycerides and LDL-C was not significant; The AUC of BRI for predicting new onset arthritis (0.546) was higher than that of BMI (0.527).

The increased level of BRI may lead to an increased risk of arthritis, and HDL-C may alleviate this risk. In the future, its clinical application potential and regulatory strategies should be explored to reduce the incidence of arthritis and improve the prognosis.

To explore the association between physical activity level (PAL) and Circadian syndrome (CircS) in Chinese middle-aged and elderly population.

Based on the 2013 China Health and Retirement Longitudinal Study (CHARLS) data, middle-aged and elderly people ≥45 years old with complete key data were selected. The association between PAL and CircS was analysed by multiple logistic regression. In addition, subgroup analyses, interaction tests, smoothed curve fitting, and threshold effect analyses were performed.

A total of 5 851 middle-aged and older adults were included as study subjects, with a prevalence of CircS of 24.18% and PAL of 4 548 (1 732.5, 10 584)(MET-min/w). Fully adjusted multivariate logistic regression showed a significant negative association between PAL and CircS prevalence (OR=0.73, 95% CI: 0.62-0.87; P<0.001). The consistency of this association was confirmed by subset analyses and interaction tests for multiple subgroups. Smoothed curve fitting and threshold effect analyses revealed a nonlinear relationship with a threshold of 3 810 MET-min/w.

There is a negative association between the PAL and the risk of developing CircS. Moderate physical activity may allow early intervention in individuals at risk for CircS.

This study aimed to identify the dual trajectories of social isolation and depression among middle-aged and older patients with hypertension, discuss the relationship between the dual trajectories, and investigate common influential factors. Method Using data from 2013 to 2020 of the China Health and Retirement Longitudinal Study (CHARLS), a longitudinal cohort was formed for the study. A group-based trajectory model was used to identify trajectories of social isolation and depression in 3 223 middle-aged and older patients with hypertension and the relationship between the dual trajectories. Multi-class logistic regression was used to analyze common influential factors of the dual trajectories.

Three trajectories of social isolation were identified: low-stable without social isolation, medium-stable without social isolation, and high-increasing with social isolation. Three depression trajectories were observed: low-stable without depression, medium-increasing with depression, and high-stable with depression. Dual-trajectory analysis showed in middle-aged and older patients with hypertension who were in the medium-stable without social isolation and high-increasing with social isolation trajectory groups, the probability of depression trajectories in the medium-increasing with depression and high-stable with depression groups was 61.84% to 87.46%. In middle-aged and older patients with hypertension who belonged to the medium-increasing with depression and high-stable with depression trajectory groups, the probability of social isolation in the medium-stable without social isolation and high-increasing with social isolation trajectory groups was 70.03% to 91.63%. The level of education(social isolation trajectories in middle school RRR=0.756, 95% CI：0.599-0.954, RRR=0.496, 95% CI: 0.326-0.755; social isolation trajectories in high school or above RRR=0.516, 95% CI: 0.375-0.709, RRR=0.262, 95% CI: 0.137-0.501; depression trajectories in middle school RRR=0.773, 95% CI: 0.622-0.959, RRR=0.728, 95% CI: 0.574-0.994, depression trajectories in high school or above RRR=0.421, 95% CI: 0.309-0.571, RRR=0.439, 95% CI: 0.253-0.763) and sleeping 7-9 hours a night (social isolation trajectories RRR=0.824, 95% CI: 0.681-0.997, RRR=0.596, 95% CI: 0.440-0.806; depression trajectories RRR=0.597, 95% CI: 0.501-0.711, RRR=0.486, 95% CI: 0.362-0.653) were common influential factors of the dual trajectories of social isolation and depression.

There is a high degree of consistency and significant correlation between the social isolation trajectory and the depression trajectory. Interventions targeting the dual trajectories and co-factors of social isolation and depression should be considered to improve their effectiveness.

To explore the effects of individual smoking cessation cognition and spousal support on married smokers’ smoking cessation behavior, and to analyse the role of gender differences on smoking cessation behavior.

A convenience sampling method was used to recruit married smokers from Jiangsu and Shandong to conduct an online questionnaire survey to collect information on demographic characteristics, smoking and cessation, individual smoking cessation cognition and spousal support. Binary logistic regression was used to analyse the relationships between smoking cessation cognition, spousal support, smoking cessation attempts, and the willingness to quit smoking with family support.

715 married smokers completed the questionnaire. After controlling for potential confounders, the results showed that perceived risk of smoking-related diseases (aOR=1.29, 95% CI: 1.05–1.59) and positive outcome expectations for quitting (aOR=1.27, 95% CI: 1.06–1.51) were positively associated with smoking cessation attempts among married male smokers, whereas no statistical associationwas found between smoking cessation cognition and smoking cessation attempts among women. Regardless of gender, perceived risk of smoking-related diseases, self-efficacy, smoking cessation plan, and spousal emotional support were positively associated with the willingness to quit smoking; negative outcome expectations for quitting (aOR=0.78, 95% CI: 0.65–0.93) were negatively associated with the willingness to quit smoking among male smokers, while no statistically significant associationwas found among female smokers.

Perceived risk of smoking-related diseases and positive outcome expectations for quitting are protective factors for smoking cessation attempts among married male smokers, while female smokers’ smoking cessation cognition failed to translate into actual quitting behavior. Additionally, negative outcome expectations for quitting are risk factors for willingness to quit smoking among married male smokers. Therefore, individualized smoking cessation intervention strategies should be developed taking into account gender differences.

To construct an evaluation indicator system for the development of occupational disease clinical specialties, providing a basis for the construction and evaluation of occupational disease clinical specialties.

An initial expert consultation questionnaire was developed through literature research and group discussions. The Delphi method was applied to conduct two rounds of expert consultations with 34 experts in the field of occupational diseases from 13 provinces (autonomous regions and municipalities) including Beijing, Sichuan, and Henan. The final evaluation indicator system for occupational disease clinical specialties was formed, and the hierarchical weights of each index were determined using the priority diagram method.

The response rates for the two rounds of expert consultations were 97.14% and 94.12%. The expert authority coefficients were 0.856 and 0.860, and the Kendall’s concordance coefficients of the experts were 0.18 and 0.12 (P<0.01). The final occupational disease clinical specialty evaluation indicator system consisted of 5 first-level indicators, 17 second-level indicators, and 67 third-level indicators.

The enthusiasm, authority, and consistency of the two rounds of expert consultations were high. This evaluation indicator system is scientifically sound and reliable, providing a reference for the construction and high-quality development of occupational disease clinical specialties.

To explore the mechanism of Mycobacterium tuberculosis (Mtb) resistance to fluoroquinolones (FQs) drugs at the genetic level, the whole genome sequencing of fluoroquinolone-resistant Mtb induced in vitro and clinical isolates was conducted.

Mtb standard strain H37Rv was induced into standard levofloxacin (LFX) resistant strain and high-level drug-resistant strain in LJ medium by concentration gradient induction method in vitro. The induced strains and drug-free control strains of each generation were collected and preserved. FQs-resistant strains in clinical isolates were screened, and the sensitivity of the induced strains and clinical isolates to 14 anti-tuberculosis drugs was detected by liquid microplate method, and then the whole genome was sequenced and analyzed.

The analysis of LFX-resistant Mtb model found that the resistance of Mtb to FQs drugs may be related to gene mutations, gyrB (Ala504Thr, Asp461Asn), gyrA (Ala90Val), PE_PGRS31 (Ala395fs), panB (Asp184_Ala187del), aroD (Asp61Asn), devS (Gly348Arg) and rv3446c (Ala178Thr). GWAS analysis of clinical isolates detected 17 new mutation sites that may be related to FQs drug resistance, namely gyrA(p.Glu21Gln, p.Gly668Asp, p.Ser95Thr, p.Glu213Asp, p.His280Arg, p.Ala384Val), gyrB(er132Ala, p.Met291Ile), PE_PGRS31(p.Ser365Phe, p.Pro254Leu, p.Thr252Ile, p.Val352Ile), rv3446c(p.Arg284Pro, p.Leu389Phe, p.Ala164Val) anddevS(p.Val307Ala, p.Ile283Thr).

The LFX-resistant Mtb model constructed in this study provides an ideal biological model for exploring the mechanism of Mtb drug resistance to FQs. Whole genome sequencing has analyzed the mechanism of Mycobacterium tuberculosis resistance to fluoroquinolones from the gene level, and the obtained new mutation sites related to fluoroquinolone resistance still need to be further studied and verified.

To compare the prediction effect of SARIMA and its combined models on the incidence of hand foot and mouth disease (HFMD), and to explore the influence of COVID-19 on the SARIMA model.

The incidence trend of HFMD in Shenzhen was analyzed through the time series decomposition method. A SARIMA model was established based on the monthly incidence of HFMD from 2011 to 2023. The optimal model was selected by comparing the performance of MAE, MSE, RMSE, and MAPE, and was used to construct a combined model with the SVR model and the XGBoost model. The incidence from January to July 2024 was predicted using the optimal model.

The incidence trend of HFMD in Shenzhen from 2011 to 2023 was seasonal, and the peak was from May to June and September to October each year. The SARIMA model that did not include incidence data during the COVID-19 pandemic outperformed the included model. Based on MAE, MSE and RMSE indicators, the combined model performed better than the single SARIMA model when the prediction time exceeded 4 months. The SARMI-SVR model wassuperior to the SARMI-XGBoost model in overall performance, especially in the performance of MAPE.

Including the incidence data during the COVID-19 epidemic will degrade the performance of the SARIMA model. The prediction effect of SARMI-SVR model is better than SARIMA model and SARMI-XGboost model, which can be used to predict the incidence of HFMD and provide a reference for disease surveillance and early warning.

To investigate the causal relationship between gestational diabetes mellitus (GDM) and attention deficit hyperactivity disorder (ADHD) using Mendelian randomization to provide genetic evidence supporting the risk of developing ADHD.

Based on pooled data from genome-wide association analyses, MR analysis was conducted using five methods, including the inverse variance weighting method, MR-Egger regression, and the weighted median method. Sensitivity analyses were performed using the MR-Egger regression test, the MR-PRESSO test, the Cochran Q test, and the leave-one-out method. Two-sample MR analyses and validation group analyses explored the existence of a causal relationship between GDM and ADHD, while multivariate Mendelian randomization examined the direct, independent causal effect of GDM on ADHD after adjusting for factors such as obesity and autism spectrum disorder (ASD).

The two-sample MR preliminary analysis (OR=1.209, 95% CI: 1.023-1.423, P=0.026) and the validation group analysis (OR=1.030, 95% CI: 1.006-1.055, P=0.015) indicated that GDM had a positive causal relationship with the risk of ADHD, suggesting that an increased risk of GDM contributing to a higher risk of ADHD. The results of MVMR analysis showed that GDM and ADHD still showed a causal relationship after controlling for Obesity and ASD (OR=1.030, 95% CI:1.008-1.054, P=0.008).

This study confirms the causal relationships between GDM, obesity, and ASD with ADHD from a genetic perspective, providing a reference for future research.

Toinvestigate whether maternal vitamin D deficiency (VDD) prevents normal placental development through the Wnt/β-catenin signalling pathway during preconception and pregnancy, which in turn triggers adverse pregnancy outcomes.

Four-week-old female SD rats were randomly divided into two groups according to body mass, Ctrl group fed with standard rat chow and VDD group fed with vitamin D deficiency chow. After eight weeks of feed intervention and successful construction of the VDD rat model, blood was taken from the orbits, male and female were co-caged. The females were executed at 18 days of gestation (GD18).Tissue samples were collectedfor later experiment.

At eight weeks of modelling,the serum 25(OH)D levels of female rats in VDD group were significantly lower compared with those of the Ctrl group(P<0.001). At GD18, measured the placental 25(OH)D, 1,25(OH)₂D, and VDR levels, these indexes in the VDD group were (6.75 ± 1.40) ng/ml, (24.23 ± 8.31) ng/L, (74.46±27.54) nmol/L, which were significantly lower than indexes in the Ctrl group: (16.76±3.12) ng/ml, (36.19±4.27) ng/L, and (137.52±26.25) nmol/L(P<0.01). Placenta diameter, weight, syncytial trophoblast area, and foetal weight were measured at GD18. There was a significant difference between the two groups. At GD18, compared with the Ctrl group, the number of implanted fetuses and live fetuses per litter decreased, but the number of absorbed fetuses increased in the VDD group. The level of β-catenin hosphorylation was significantly increase in the placental tissues of pregnant rats in the VDD group.

Maternal vitamin D deficiency before and during pregnancy is an important cause of placental dysplasia, which in turn can induce adverse pregnancy outcomes, and the mechanism may involve the Wnt/β-catenin signalling pathway.

To explore the relationship between dietary fiber intake and cognitive function, providing insights for nutritional interventions to prevent cognitive impairment.

Adults over 50 years old from the 2022 Southwest Population Cohort were selected as study subjects. Multiple linear regression and multivariable logistic regression models were used to analyze the relationship between dietary fiber intake and cognitive impairment. Subgroup analysis was performed to explore the association between dietary fiber intake and cognitive impairment across different age and gender groups.

A total of 1 267 participants were included,the median dietary fiber intake of the participants was 13.3 g/d. The dietary fiber intake of individuals with cognitive dysfunction, specifically those with mild cognitive impairment (11.6 g/d), was significantly lower than that of the normal group (13.7 g/d), and the difference was statistically significant (Z=3.93, P<0.001). After adjusting for age, gender, body mass index, education, smoking, per capita monthly household income, hypertension, diabetes, and daily energy intake, dietary fiber intake was positively correlated with cognitive function scores. The logistic regression analysis showed that, compared to the lowest dietary fiber intake group (Q1), the highest dietary fiber intake group (Q4) had a reduced risk of cognitive dysfunction, with statistically significant OR values of 0.29 (95% CI: 0.16–0.53), 0.27 (95% CI: 0.14–0.49), and 0.39 (95% CI: 0.18–0.84). The impact of dietary fiber intake was more pronounced in males and in individuals aged 63 and above.

There is a negative association between dietary fiber intake and cognitive dysfunction, suggesting that dietary fiber may be a protective factor against cognitive dysfunction, with this association being particularly significant in males and individuals aged 63 years and older.