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.

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.

Wasp sting refers to a series of clinical syndromes caused by the venom in the tail poison sac of the poisonous bee when attacking the attacked body, mainly manifested as local skin damage, systemic allergic reaction and multi-organ dysfunction syndrome (MODS) . Wasp venom can also act on the nervous system, and cause rare complications such as cerebral hemorrhage, subarachnoid hemorrhage, cerebral infarction, epilepsy, encephalitis, and Parkinson's disease, which can seriously affect the prognosis. This review will elaborate the above complications for clinical reference.

Wasp sting refers to a series of clinical syndromes caused by the venom in the tail poison sac of the poisonous bee when attacking the attacked body, mainly manifested as local skin damage, systemic allergic reaction and multi-organ dysfunction syndrome (MODS) . Wasp venom can also act on the nervous system, and cause rare complications such as cerebral hemorrhage, subarachnoid hemorrhage, cerebral infarction, epilepsy, encephalitis, and Parkinson's disease, which can seriously affect the prognosis. This review will elaborate the above complications for clinical reference.

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: 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.

Objective: To explore the association among neck-shoulder pain (NSP), low back pain (LBP) and co occurring symptoms with mental sub health in adolescents, so as to provide evidence for improving physical and mental health of adolescents. Methods: Stratified cluster random sampling method was used to select 7 986 students from 12 middle and high schools in Shenzhen, Nanchang, and Shenyang cities from October to December 2019. The Assessment of Spinal Health of Youth (ASHY) and the Brief Instrument on Psychological Health of Youth (BIOPHY) were used to assess NSP, LBP and mental sub health. Binary Logistic regression model was used to analyze the association between NSP, LBP and co occurring symptoms with mental sub health in adolescents. Results: The detection rates of adolescents with NSP, LBP and co occurring symptoms and mental sub health were 9.1% , 9.8%, 9.5%, and 10.0%, respectively. The co occurring rate of neck shoulder pain, low back pain and mental sub health was 3.2%. After adjusting for confounding variables such as gender, age, being an only child, family residence, and parental education level, NSP ( OR=6.01, 95%CI =5.02-7.19), LBP ( OR=5.08, 95%CI =4.25-6.07), and co occurring symptoms ( OR= 5.96 , 95%CI =4.98-7.12) in adolescents were positively correlated with mental sub health risk ( P <0.01). Stratifying the gender, boys with NSP, LBP and co occurring symptoms ( OR =6.84, 5.80, 6.74)had a higher risk of mental sub health compared to girls ( OR =5.52, 4.65, 5.49) ( P <0.01). Conclusions NSP, LBP and co occurring symptoms in adolescents are associated with mental sub health. The mental health status of boys is more affected by NSP, LBP and their co occurring symptoms. Measures should be taken to improve spinal health in adolescents to reduce the incidence of mental sub health.

Objective: The aim of the present study was to develop the beverage addiction scale for college students,so as to provide an effective tool for assessing college students beverage addiction. Methods: In November 2022, a cluster sample of 8 792 college students from three colleges in Yunnan and Jiangxi were surveyed by Beverage Addication Scale for College Students. After a through literature review, 12 items were proposed, including withdrawal symptoms, health effects and addiction symptoms, with 4 items each. The ttest and correlation analysis were used to filter the items, and exploratory factor analysis and confirmatory factor analysis were used to evaluate the structural validity of the questionnaire. In May 2023, 5 279 college students from the above three universities were surveyed again to evaluate the reliability and validity of the scale and the positive demarcation value of symptoms. Results: The scale fitted into a tool for measuring symptoms of beverage dependence in a college student population. The scale was composed of 11 items in accordance with withdrawal symptoms, health effects and addiction symptoms, with a cumulative contribution rate of variance was 74.51%. Cronbach α coefficients for the overall scale and three dimensions were 0.94, 0.88, 0.90 and 0.92, respectively. The correlation coefficient between each item and the total score ranged from 0.56 to 0.79, and the correlation coefficient with the dimension ranged from 0.71 to 0.92. The confirmatory factor analysis model was well fitted, and the RMSEA, CFI, TLI and SRMR value were 0.06, 0.95, 0.93 and 0.04, respectively. The application of the scale showed that scores on the scale and each dimension ≥P85 were positive for symptoms. Conclusion The reliability and validity of Beverage Addiction Scale for College Students is good, which can be used to evaluate the beverage addiction symptom of college students.

Objective: The study aimed to describe the prevalence of mobile phone use and depressive symptoms and to examine the bidirectional associations between the two among college students, providinb evidence for mental health promotion among college students. Methods: A longitudinal study with follow up at 6 month intervals was conducted in 1 135 students from 2 universities in Hefei, Anhui Province and Shangrao, Jiangxi Province who were selected between April and May 2019. The last follow up was conducted between April and May 2021 based on questionnaire survey, and 999 valid participants were obtained after matching. The self designed questionnaire was used to investigate the duration of cellular phone use and use of cellular phone functions among college students. The Self rating Questionnaire for Adolescent Problematic Mobile Phone Use (SQAPMPU) and the Patient Health Questionnaire-9 (PHQ-9) were used to assess cellular phone dependence and depressive symptoms among college students. Pearson correlation analysis was used to examine the correlation between cellular phone use behavior and depressive symptoms at baseline and 2 years later; linear regression model was used to analyze the linear association between cellular phone use behavior and depressive symptoms scores; autoregressive cross lagged model was used to analyze the bidirectional associations between cellular phone use behaviors and depressive symptoms among college students over time. Results: The prevalence of mobile phone dependence and depressive symptoms among college students at baseline were 24.3% and 42.4%, respectively. The mean duration of mobile phone use among college students at baseline and the 2 year follow up were (2.84±0.90)h/d and (2.02±1.05)h/d, respectively; the mean scores of mobile phone dependence were (23.30±9.00) and (23.29±10.45), respectively; the mean scores of mobile phone function use were (30.12±6.66) and (29.12±7.27), respectively; and the mean scores of depressive symptoms were (4.51±4.76) and (2.61±4.40), respectively. Pearson correlation analysis showed there were significant positive correlations between duration of cellular phone use, cellular phone dependence, use of cellular phone functions at baseline or 2 years later and depressive symptoms 2 years later( r =0.08-0.50, P <0.05). Linear regression models showed a significant positive association between cellular phone dependence at baseline and depressive symptoms ( β=0.26, 95%CI =0.23-0.29) at baseline and 2 years later ( β=0.12, 95%CI =0.09-0.15). Autoregressive cross lagged models showed that cellular phone dependence at baseline positively predicted depressive symptoms 2 years later ( β =0.04) and depressive symptoms at baseline positively predicted cellular phone dependence 2 years later( β =0.23)( P <0.05). Conclusion There was a bidirectional association between cellular phone dependence and depressive symptoms among college students. Reducing cellular phone dependence is of positive significance for improving college students mental health.

Objective: To describe the prevalence and association of sleep quality and anxiety-depression co-morbid symptoms among nursing students, in order to provide a reference basis for promoting the development of nursing students mental health. Methods: Using a prospective study design, baseline survey was conducted in January 2019 among a random cluster sample of 1 716 individuals in three medical universities in Hefei, Anhui Province, and a follow-up survey was conducted in October 2019, with a valid number of 1 573 individuals after matching with the baseline survey. The Pittsburgh Sleep Quality Index (PSQI) was used to assess nursing students sleep quality, and the Depression Anxiety Stress Scale (DASS-21) to assess the anxiety-depression comorbid symptoms. Results: The detection rates of anxiety-depression co-morbidities among nursing students at baseline and follow-up survey were 16.9% and 18.2%, respectively, and the detection rates of poor sleep quality among nursing students at baseline and follow-up survey were 10.1% and 10.3%, respectively. The results of the binary Logistic regression model showed that baseline PSQI score were positively associated with the risk of anxiety-depression co-morbid symptoms among nursing students at baseline ( OR=1.49, 95%CI =1.40-1.59) and after nine months of follow-up ( OR=1.22, 95%CI =1.16-1.28). Furthermore, the influence of baseline sleep quality on the risk of anxiety-depression co-morbid symptoms were mainly concentrated in the five dimensions of sleep time, sleep efficiency, sleep disorders, hypnotic drugs and daytime dysfunction, and such effects of sleep time, sleep disorders and daytime dysfunction still existed in the follow-up investigation. Conclusion Poor sleep quality of nursing students can increase the risk of anxiety-depression co-morbidities. Improving sleep quality of nursing students has a positive effect on improving their mental health.