Objective: To determine the association between exposure to entertainment screen content on mobile phones and symptoms of anxiety-depression co-morbidity among college students,so as to provide evidence for mental health interventions. Methods: A baseline survey was conducted from April to May 2019. A total of 1 135 college students were selected from one university each in Shangrao City, Jiangxi Province and Hefei City, Anhui Province using cluster random sampling method. A follow up study was conducted in November 2019, resulting in 1 110 matched valid responses. Self rating questionnaires were used to assess the exposure of entertainment screen content. The Depression Anxiety Stress Scale-21(DASS-21) and the Patient Health Questionnaire-9 (PHQ-9) were used to evaluate the anxiety symptoms, depressive symptoms, and symptoms of anxiety-depression co-morbidity among college students. A multivariate binary Logistic regression model was constructed following initial intergroup comparisons with Chi-square test to determine the association between baseline exposure to mobile entertainment screen content and the risk of symptoms of anxiety depression co-morbidity at baseline and the 6 month follow up. Results: The prevalence rates of symptoms of anxiety-depression co-morbidity among college students were 25.4% and 20.6% at baseline and follow up, respectively.After adjusting for confounding factors such as gender, self rated family economic status and self rated health status, the results of multivariate binary Logistic regression analysis showed that compared with the appropriate exposure level group, the exposure of entertainment screen content on mobile phones at baseline, including frequent exposure to reading( OR =1.65,95% CI =1.14-2.39), occasional exposure to other entertainment screen content ( OR =1.46,95% CI =1.01-2.10)and frequent exposure to other entertainment screen content( OR =1.76,95% CI =1.20-2.60), increased the co-occurrence risk of symptoms of anxiety-depression co-morbidity among college students during the follow up period (all P <0.05). Conclusion Occasional or frequert exposure to mobile entertainment screen content can increase the risk of symptoms of anxiety depression co-morbidity among college students.

Objective: To investigate the association between screening detected myopia in primary school students and mixed exposure to air pollutants, so as to provide a scientific basis for the prevention and control of myopia in children and adolescents. Methods: From May to July 2023, a cluster random sampling method was used to select 15 102 primary school students in grades 3 through 6 from Hefei, Zhongshan, Shenyang, and Nanchang citys. Data were collected through questionnaires, distance vision screening, and computerized refraction. Monthly average concentration data for particulate matter (PM 10 ), fine particulate matter (PM 2. 5), NO 2 and SO 2 were used to calculate the annual average pollutant concentrations for primary school students. Quantile g computation model was employed to analyze the association between mixed exposure to air pollutants and screening detected myopia. Results: The differences in concentrations of the four pollutants among cities were statistically significant ( H =12 886.0, 13 285.0, 8 559.0, 13 181.0, all P <0.01). In the overall sample, there was no statistically significant association between combined exposure to air pollutants and the risk of myopia ( β=0.033, 95%CI=-0.004-0.072, P =0.08). Stratified analysis by outdoor activity time showed that among primary school students with outdoor activity time ≤1 h/d, mixed exposure to air pollutants was positively associated with the risk of myopia ( β=0.050, 95%CI=0.002-0.099, P =0.04); after stratification by city, combined exposure to air pollutants was significantly associated with the risk of myopia among primary school students in Nanchang and Shenyang [ β (95% CI )= 0.232(0.175-0.289), 0.080(0.006-0.155), both P <0.05], whereas no statistically significant association was observed among primary school students in Hefei and Zhongshan [ β (95% CI )=-0.010(-0.071-0.051), -0.032(-0.167-0.102), both P ＞ 0.05 ]. Conclusions Exposure to multiple air pollutants may increase the risk of myopia in primary school students, with the risk influenced by time spent outdoors and geographical location. It is recommended that outdoor activity management for children be strengthened in areas with higher air pollution levels, and that environmental factors be incorporated into comprehensive myopia prevention and control strategies.

With the growing emphasis on maternal and child oral health, the significance of managing oral health across preconception, pregnancy, and infancy stages has become increasingly apparent. Oral health challenges extend beyond affecting maternal well-being, exerting profound influences on fetal and neonatal oral development as well as immune system maturation. This expert consensus paper, developed using a modified Delphi method, reviews current research and provides recommendations on maternal and child oral health management. It underscores the critical role of comprehensive oral assessments prior to conception, diligent oral health management throughout pregnancy, and meticulous oral hygiene practices during infancy. Effective strategies should be seamlessly integrated across the life course, encompassing preconception oral assessments, systematic dental care during pregnancy, and routine infant oral hygiene. Collaborative efforts among pediatric dentists, maternal and child health workers, and obstetricians are crucial to improving outcomes and fostering clinical research, contributing to evidence-based health management strategies.
Humans ; Pregnancy ; Female ; Infant ; Consensus ; Mouth Diseases/therapy* ; Pregnancy Complications/therapy* ; Oral Health ; Infant, Newborn ; Delphi Technique ; Oral Hygiene

Objective: To analyze the association and dose response relationship between physical activity and inflammatory markers in college students, so as to provide a reference for promoting cardiometabolic health in college students. Methods: A cluster random sampling method was used to select 747 college students from two universities in Hefei, Anhui Province and Shangrao, Jiangxi Province from April to May 2019. Physical activity was assessed by using the International Physical Activity Questionnaire-Short Form (IPAQ-SF), and peripheral blood was collected to detect plasma inflammatory factor levels [including hypersensitive C reactive protein (hsCRP), interleukin-10 (IL-10), interleukin-1β (IL-1β), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α)]. The differences between the groups were compared by using the χ 2 test and the Kruskal-Wallis rank sum test, and the association between physical activity and inflammatory markers was analyzed by using the Generalized Linear Model. The dose response relationship between physical activity and inflammatory markers was analyzed using the Restricted Cubic Spline Model. Results: The proportions of low physical activity, moderate physical activity, and high physical activity groups of college students were 15.9%, 53.7% and 30.4%, respectively. The levels of hsCRP, IL-10, IL-1β, IL-6 and TNF-α in the high physical activity group were 0.38(0.21, 1.10)mg/L, 70.74(47.90, 116.43)pg/mL, 1.75(1.21, 2.64)pg/mL, 4.33(2.93, 6.82) pg/mL , 5.27(3.89, 7.30)pg/mL,the levels in the low physical activity group were 0.80(0.31, 1.30)mg/L, 73.88 (47.90, 124.24)pg/mL, 1.88(1.42, 2.81) pg/mL, 4.82 (3.64, 6.67) pg/mL, 5.63 (4.34, 7.62)pg/mL, the levels in the moderate physical activity group were 0.63(0.25, 1.30)mg/L, 89.78(58.21, 127.65)pg/mL, 2.21(1.59, 3.27)pg/mL, 5.15( 3.72 , 7.72)pg/mL, 5.87( 4.63 , 8.00)g/mL, and the differences were statistically significant ( H=10.66, 11.38, 27.79, 14.13, 9.44, P <0.05). After adjusting for variables such as gender, body mass index, smoking, alcohol consumption and health status, the results of Generalized Linear Model showed that compared with the high physical activity group, the low physical activity group ( OR=2.20, 95%CI = 1.46- 3.31) and the moderate physical activity group ( OR=1.65, 95%CI =1.22-2.25) were more likely to have high levels of hsCRP, and the moderate physical activity group was more likely to have high levels of IL-1β ( OR=1.85, 95%CI =1.36-2.51), IL-6 ( OR=1.44, 95%CI =1.06-1.96), and TNF-α ( OR=1.43, 95%CI =1.05-1.94) ( P <0.05). The Restricted Cubic Spline Model showed that there was no linear dose response relationship between the time of moderate to vigorous physical activity weekly and IL-10, IL-6, II-1β, and TNF-α ( P <0.05). Conclusion There is an association between physical activity and inflammation in college students, and moderate to high intensity per week could reduce inflammation levels to promote cardiometabolic health in college students.

ObjectiveTo investigate the main risk factors for liver cirrhosis in chronic hepatitis B （CHB） patients with high metabolic risk， to establish a noninvasive predictive model， and to compare the diagnostic efficiency of this model and other models including fibrosis-4 （FIB-4）， aspartate aminotransferase-to-platelet ratio index （APRI）， gamma-glutamyl transpeptidase-to-platelet ratio （GPR）， and Forns index. MethodsA total of 527 CHB patients with high metabolic risks who were admitted to The Second Affiliated Hospital of Guangxi Medical University from September 1， 2017 to October 31， 2022 were enrolled as subjects， and they were randomly divided into modeling group with 368 patients and validation group with 159 patients at a ratio of 7∶3. The LASSO regression analysis and the multivariate Logistic regression analysis were performed for the modeling group to identify independent risk factors， and a nomogram model was established. The receiver operating characteristic （ROC） curve， the calibration curve， and the decision curve analysis were used to validate the nomogram prediction model in the modeling group and the validation group and assess its discriminatory ability， calibration， and clinical practicability. The Delong test was used to compare the area under the ROC curve （AUC） of the nomogram prediction model and other models. ResultsThe multivariate Logistic regression analysis showed that prealbumin （odds ratio ［OR］ = 0.993， 95% confidence interval ［CI］： 0.988 — 0.999， P= 0.019）， thrombin time （OR=1.182， 95% CI： 1.006 — 1.385， P=0.047）， log₁₀ total bilirubin （TBil） （OR=1.710， 95%CI： 1.239 — 2.419， P=0.001）， and log₁₀ alpha-fetoprotein （AFP） （OR=1.327， 95%CI： 1.052 — 1.683， P=0.018） were independent influencing factors for liver cirrhosis in CHB patients with high metabolic risks. A nomogram model for risk prediction was established based on the multivariate analysis， which had an AUC of 0.837 （95%CI： 0.788 — 0.888）， a specificity of 73.5%， and a sensitivity of 84.7%， as well as a significantly higher diagnostic efficiency than the models of FIB-4 （0.739）， APRI （0.802）， GPR （0.800）， and Forns index （0.709） （Z=2.815， 2.271， 1.989， and 2.722， P=0.005， 0.017， 0.045， and 0.006）. ConclusionThe nomogram model established based on prealbumin， thrombin time， log₁₀ TBil， and log₁₀ AFP has a certain clinical application value.

Objective: To describe the prevalence and the association of sleep quality trajectory, social jetlag and comorbid symptoms of anxiety and depression among college students, in order to provide a theoretical basis for improving the comorbid symptoms of anxiety and depression in college students. Methods: A questionnaire survey was conducted among 1 135 college students from two universities in Shangrao, Jiangxi Province and Hefei, Anhui Province from April to May 2019, and were followed up once every one year for a total of three times, with a valid sample size of 1 034 individuals after matching with the baseline survey. A selfassessment questionnaire was used to investigate the social jetlag of college students, the Generalized Anxiety Disorder-7 (GAD-7) and Patient Health Questionnaire 9 (PHQ-9) were used to evaluate anxiety and depression symptoms, respectively, while the Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep quality. College students with GAD-7 score ≥5 and PHQ-9 score ≥5 were defined as having comorbid anxiety and depression symptoms. Latent class growth model (LCGM) was employed to analyze the sleep quality trajectory of college students, and binary Logistic regression was used to analyze the relationship between social jetlag, sleep quality trajectory and comorbid symptoms of anxiety and depression. Results: The detection rate of comorbid symptoms of anxiety and depression among college students was 16.9%, and the detection rate of social jetlag ≥2 h was 13.8%. The sleep quality showed an overall improvement trend, and the two trajectories were good sleep quality (81.6%) and poor sleep quality (18.4%). Binary Logistic regression model showed that poor sleep quality and social jetlag ≥2 h were positively correlated with comorbid symptoms of anxiety and depression (OR=5.94, 1.84, P<0.05). Conclusions Poor sleep quality and social jetlag ≥2 h in college students increase the risk of comorbid symptoms of anxiety and depression. Early screening and intervention of sleep quality and reduction of social jetlag are crucial for enhancing the mental health of college students.

Objective: This study aimed to determine the predictive performance of non-contrast CT (NCCT) signs for hemorrhagic growth after intracerebral hemorrhage (ICH) when stratified by onset-to-imaging time (OIT). Materials and Methods: 1488 supratentorial ICH within 6 h of onset were consecutively recruited from six centers between January 2018 and August 2022. NCCT signs were classified according to density (hypodensities, swirl sign, black hole sign, blend sign, fluid level, and heterogeneous density) and shape (island sign, satellite sign, and irregular shape) features. Multivariable logistic regression was used to evaluate the association between NCCT signs and three types of hemorrhagic growth: hematoma expansion (HE), intraventricular hemorrhage growth (IVHG), and revised HE (RHE). The performance of the NCCT signs was evaluated using the positive predictive value (PPV) stratified by OIT. Results: Multivariable analysis showed that hypodensities were an independent predictor of HE (adjusted odds ratio [95% confidence interval] of 7.99 [4.87–13.40]), IVHG (3.64 [2.15–6.24]), and RHE (7.90 [4.93–12.90]). Similarly, OIT (for a 1-h increase) was an independent inverse predictor of HE (0.59 [0.52–0.66]), IVHG (0.72 [0.64–0.81]), and RHE (0.61 [0.54– 0.67]). Blend and island signs were independently associated with HE and RHE (10.60 [7.36–15.30] and 10.10 [7.10–14.60], respectively, for the blend sign and 2.75 [1.64–4.67] and 2.62 [1.60–4.30], respectively, for the island sign). Hypodensities demonstrated low PPVs of 0.41 (110/269) or lower for IVHG when stratified by OIT. When OIT was ≤ 2 h, the PPVs of hypodensities, blend sign, and island sign for RHE were 0.80 (215/269), 0.90 (142/157), and 0.83 (103/124), respectively. Conclusion Hypodensities, blend sign, and island sign were the best NCCT predictors of RHE when OIT was ≤ 2 h. NCCT signs may assist in earlier recognition of the risk of hemorrhagic growth and guide early intervention to prevent neurological deterioration resulting from hemorrhagic growth.

Objective: To describe the association of different sleep characteristics and cardiometabolic risk among college students, so as to provide reference for health promotion of college students. Methods: By random cluster sampling method, a questionnaire survey and physical examination including blood pressure, waist circumference and blood lipid indicators, which were conducted in April and May of 2019 among a total of 1 179 college students from the first grade in two universities in Hefei City of Anhui Province and Shangrao City of Jiangxi Province. A total of 729 college students with valid questionnaires were included into analysis. The Pittsburgh Sleep Quality Index (PSQI) and Insomnia Severity Index (ISI) were used to investigate sleep behavior, and the Morning And Evening Questionnaire-5 (MEQ-5) was used to investigate sleep characteristics. The cardiometabolic risk score was derived using the sum of the standardized sex specific Z scores of waist circumference, mean arterial pressure, HDL cholesterol (multiplied by -1), triglycerides, and insulin resistance index. The rank sum tests were used to compare differences in cardiometabolic risk scores across demographic characteristics. Generalized linear models were used to compare the association of different sleep characteristics with cardiometabolic risk scores among college students. Results: The average cardiovascular metabolic risk score of college students was -0.32(-2.03, 1.58). There were statistically significant differences in cardiovascular metabolic risk scores among college students in variables such as smoking, health status, and physical activity levels ( t/F=-3.41, 12.88, 51.07, P <0.01). The results of the generalized linear model showed that nighttime preference ( B=1.89, 95%CI =1.02-3.49), insomnia symptoms ( B=3.25, 95%CI =1.79-5.90), and short or long sleep duration ( B=1.92, 95%CI =1.21-3.05) were positively correlated with the cardiovascular metabolic risk score of college students ( P <0.05). Conclusions Poor sleep patterns among college students are positively correlated with the risk of cardiovascular metabolism. The sleep behavior of college students should be actively changed to reduce the risk of cardiovascular disease.

Objective: To explore the longitudinal correlation between smartphone multitasking and depressive symptoms, so as to provide an evidence based basis for promoting the mental health of college students. Methods: A total of 967 college students were recruited from one university in Taiyuan, Chongqing, and Shenzhen cities, China, by using multi stage randomized cluster sampling from October to December 2021 at baseline, and a follow up survey was conducted in May 2022. Smartphone multitasking behaviors were assessed by means of the Assessment of Smartphone Multitasking for Adolescents (ASMA), and depressive symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9) among college students. Chi square tests were performed to compare the differences in depressive symptoms between different groups of demographic characteristics, and binary Logistic regression models were employed to analyze the associations between smartphone multitasking and depressive symptoms among college students. Results: The rates of depressive symptoms among college students at baseline and follow up were 35.2% and 42.3%, respectively. Compared to the low level smartphone multitasking index group at baseline, the moderate and high level groups were more likely to experience depressive symptoms at baseline (moderate level group: OR=1.74, 95%CI =1.22-2.50, high level group: OR=2.77, 95%CI =1.94-3.95) and followup (moderate level group: OR=1.41, 95%CI =1.01-1.95, high level group: OR=1.64, 95%CI =1.17-2.29) ( P <0.05). In addition, compared to the persistently low smartphone multitasking index, increased risk of depressive symptoms was associated with maintaining a moderate to high ( OR=2.94, 95%CI =1.83-4.71), and a higher ( OR=2.07, 95%CI =1.31-3.27) or lower smartphone multitasking index ( OR=2.02, 95%CI =1.27-3.19) ( P <0.05). Moreover, higher smartphone multitasking index scores were positively associated with the risk of new-onset depressive symptoms at follow up ( OR=1.87, 95%CI=1.07-3.27, P <0.05). Conclusions Smartphone multitasking behaviors are find to be associated with an increased risk of depressive symptoms in college students. There is a need to reduce smartphone multitasking in order to decrease depressive symptoms and promote students mental health.

To better cultivate stomatology students and to improve their understanding and mastery of the knowledge of oral genetic diseases, a representative disease (Treacher Collins syndrome) was selected from the pediatric dentistry curriculum to design a single-lesson teaching trial. In this trial, the BOPPPS teaching mode including bridge in, objective, pre-assessment, participatory learning, post-assessment, and summary steps was adopted for systematic teaching design. Furthermore, flipped classroom, problem-based learning (PBL), case-based learning (CBL), mind mapping, and other teaching forms were also involved. The results showed that after BOPPPS-mode teaching, 24 students (96.00%) agreed that this teaching mode could help them focus more on the contents, and 23 students (92.00%) reported that it promoted their active thinking and interaction during the class. Compared with the traditional plug-in teaching mode, 23 students (92.00%) reported better leaning experience and effect. Therefore, BOPPPS teaching mode can promote students' understanding of knowledge, improve their initiative and innovation, and improve the teaching effect.