Cardiometabolic disease is one of the leading causes of morbidity and mortality in adults. In recent years, the prevalence of cardiometabolic disease has increased year by year, becoming a major problem in the global disease burden. The occurrence and development of cardiometabolic risk are affected by many factors. Shift work as an occupational hazard has been widely concerned. Nurses are a typical population for shift work, but few studies have looked at the association between their shift work and cardiometabolic risk. This article reviewed the current situation of cardiometabolic risk and the research progress on the association between shift work and cardiometabolic risk among nurses. The results showed that cardiometabolic risk is prevalent in the nurse population. Shift work is associated with cardiometabolic risks such as metabolic syndrome, cardiovascular disease, diabetes, and dyslipidemia, and is mediated by circadian rhythm disorder, hormone secretion disorder, and stress response. However, the causal relationship between shift work and cardiometabolic risk is still unclear, and further prospective cohort studies should be conducted to improve the understanding of the impact of shift work on cardiometabolic risk in order to improve the cardiometabolic health status of nurses.

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 promote the application of drones in emergency rescue and related fields， expand “low-altitude+ medical” rescue services， and advance the standardization of “low-altitude+medical” distribution services. METHODS The Consensus on Low-altitude Transport and Delivery Services for Emergency Medicines via Drones （2025 Edition） （hereinafter referred to as the Consensus） was jointly initiated by the Division of Therapeutic Drug Monitoring， Chinese Pharmacological Society and the Expert Committee on Precision Medication of the Guangdong Pharmaceutical Association. Guangzhou Red Cross Hospital served as the leading unit， organizing 53 multidisciplinary experts nationwide to participate in drafting and reviewing. A nominal group technique was employed to discuss and finalize the consensus outline， resulting in a preliminary draft. Delphi method was employed， and 11 external review experts were invited to conduct the evaluation. After the experts’ opinions were analyzed and integrated， the Consensus was finalized. RESULTS & CONCLUSIONS The finalized Consensus includes its purpose， principles， and applicable scenarios， basic requirements， and operational procedures for low-altitude transport and delivery of emergency medications； distribution requirements and precautions for controlled substances， fragile medications， and temperature-sensitive medications； and recommendations for emergency medications supplies suitable for the low-altitude transportation and distribution. The release of this Consensus is expected to provide guidance and support for the standardization of “low-altitude+medical” distribution services and the application of low-altitude economy in the healthcare sector.

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 analyze the association between sleep chronotype and suicidal psychological behaviors among middle school students, so as to provide a scientific basis for the prevention and control of middle school students suicide. Methods: In October 2021 and November 2022, a multistage cluster sampling method was used to conduct baseline and followup surveys in Shenyang, Zhengzhou, Nanchang, and Taiyuan cities in China, and a total of 6 656 middle and high school students were included as the research subjects. The Chisquare test was used to analyze the groups differences, and generalized estimating equation was used to analyze the associations between middle school students sleep chronotype and suicide ideation, suicide plan and suicide attempt, and the grade stratification was carried out. Results: Baseline detection of suicide ideation, suicide plan, and suicide attempt were 26.3%, 12.6%, and 5.3%, respectively, with followup rates of 21.0%, 10.0%, and 4.8% for each, and varied significantly by gender, academic stress, smoking or alcohol use, and anxiety or depressive symptoms among middle school students (χ2=11.93-880.20, P<0.05). After adjusting for gender, academic stress, physical activity, smoking, alcohol use, anxiety and depressive symptoms, generalized estimating equations showed that compared with the morning sleep chronotype, the OR(95%CI) for suicide ideation, suicide plan and suicide attempt were 1.61(1.36-1.89), 1.66(1.35-2.05) and 1.41(1.06-1.88) among evening chronotype students, and were higher among junior 1.78(1.39-2.27), 2.00(1.48-2.69) and senior middle school students 1.84(1.44-2.35), 1.67(1.20-2.33) (P<0.05). Conclusion There is a positive association between evening sleep chronotype and middle school students suicidal psychological behavior, and improving sleep chronotype may be one of the effective measures to prevent middle school students suicide.

Abstract: To analyze the relationship between parenting behaviors and sleep problems of preschool children, so as to provide a strategic decision support for child growth and parenting behavior improvement. Methods: Using the questionnaire data of 27 200 preschool children parents selected from 11 cities in Hubei, Anhui and Jiangsu provinces in October 2017, parents parenting behavior was assessed by Parent Behavior Inventory (PBI), and children s sleep problems were assessed by Children s Sleep Habits Questionnaire (CSHQ). Data were analyzed using descriptive statistics and Logistic regression models. Results: The reporting rate of sleep problems among preschool children was 15.3%. After adjusting for confounding factors, maternal hostile/coercive parenting behavior scores (medium level: OR=1.38; high level: OR=1.86) and paternal hostile/coercive parenting behavior scores (medium level: OR=1.17; high level: OR=1.59) were positively correlated with sleep problems (P<0.05). Hostile/coercive parenting behaviors by their parents (maternal high level: the OR values were 1.75, 2.97, 1.86, and 2.75 respectively; paternal high level: OR values were 1.79, 1.91, 1.69, and 1.79 respectively) were positively associated with sleep problems in preschool children aged 3, 4, 5, and 6. Scores of parental support/engaged (fathers of 4yearold children medium level: OR=0.84; fathers of 5yearold children medium and high level: OR=0.84, 0.82) were negatively correlated with children aged 4 and 5 (P<0.05). High level maternal supportive/engaged and paternal hostile/coercive scores were positively associated with child sleep problems (OR=1.93); high level maternal hostile/coercive and paternal supportive/engaged scores were positively associated with child sleep problems (OR=1.93); high scores of parental hostile/coercive were positively correlated with child sleep problems (OR=2.60) (P<0.05). Conclusion Sleep problems among children are related to parenting behaviors, especially hostile/coercive parenting behaviors that increases the risk of sleep problems among children.

Abstract Common diseases among students such as myopia, overweight and obesity, scoliosis, and mental health problems are prevalent, which usually exist concurrently under similar public health influencing factors. Therefore, there is a need to carry out the joint prevention of multimorbidity. The National Disease Control and Prevention Administration of China have organize the development of the Technical Guidelines for the Joint Prevention of Common Disease Multimorbidity among Students (hereafter referred to as the Guidelines). For the first time, the Guidelines clarifies the concept of multimorbidity joint prevention, specifies that the departments of centers for disease control and prevention should strengthen environmental and behavioral surveillance, proposes integrated public health interventions for multimorbidity joint prevention based on a three tiered prevention strategy, and recommends the appropriate technology of a healthy lifestyle featuring six key principles. It also advocates exploring the establishment of a six in one model (government-professional institution-community-school-family-students collaboration) for multimorbidity joint prevention, which has achieved a leap in theory and practice in the prevention and control of common diseases among students. The article focuses on the background, theoretical basis and core content of the Guidelines, in order to improve the understanding of the Guidelines by professionals in public health institutions and people concerned about students health, and to promote the application and dissemination of the Guidelines.

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 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 clinical characteristics and outcomes of type 2 autoimmune pancreatitis (AIP) and compare with type 1 AIP.Methods:Clinical data of the patients diagnosed with type 2 AIP by the International Consensus on diagnostic criteria of AIP at Peking Union Medical College Hospital from January 2001 to December 2022 were retrospectively analyzed, and type 1 AIP patients diagnosed in Peking Union Medical College Hospital from January 1985 to December 2016 were collected as controls. The clinical symptoms, treatments and follow-ups were analyzed.Results:A total of 25 patients with type 2 AIP were included, of which 16 cases (64.0%) were pathologically confirmed cases (13 cases by endoscopic ultrasound puncture, 2 cases by surgery, and 1 case by interventional puncture), and 9 cases (36.0%) were suspected. The average age of onset was 40 years old. Most patients ( n=23, 92.0%) had abdominal pain along with emaciation to a various degree. Among them, 3 cases primarily presented as acute pancreatitis. Two cases were diagnosed after surgery for pancreatic masses. Eighteen cases were complicated with inflammatory bowel disease, including 16 cases with ulcerative colitis, one case with Crohn's disease, and one case with indeterminate colitis. All patients had typical imaging manifestations, including 13 cases (52.0%) with diffuse pancreatic enlargement, 12 cases (48.0%) with focal or multifocal pancreatic lesions, and 5 cases (20.0%) with simultaneous focal pancreatic masses and diffuse enlargement. All patients had normal serum IgG4 levels, anti-neutropil cytoplasmic antibodies (ANCA) positivity rate was 35.3% (6/17), and anti-nuclear antibody (ANA) positivity rate was 29.2% (7/24). Two surgical patients recovered well after surgery, and the other patients all achieved clinical and imaging relief after hormone therapy, and no recurrence was seen during follow-up. Compared with type 1 AIP, type 2 AIP had younger onset age, main manifestation as abdominal pain without jaundice, rare involvement with extra-pancreatic organs, the lesions mainly located in the intestine and normal IgG4 level with statistically significant differences. The recurrence rate of type 2 AIP was lower than that of type 1 AIP (0 vs 16%). Conclusions:Type 2 AIP has different clinical characteristics from type 1 AIP. Due to the lack of specific serum markers, the diagnosis is more difficult. It responds well to glucocorticoids and has a low recurrence rate.