1.Prevalence and influencing factors of school bullying experienced by primary and middle school students
ZHU Yunjiao ; GU Fang ; MENG Jia ; LI Juanjuan ; SHEN Yu ; GAO Lei
Journal of Preventive Medicine 2025;37(1):1-6
Objective:
To investigate the situation and influencing factors of school bullying experienced by primary and middle school students, so as to provide the basis for formulating school bullying intervention measures and promoting students' physical and mental health development.
Methods:
All the counties (cities, districts) in Zhejiang Province were stratified to urban and suburban areas, primary, junior high and senior high school students were selected using a stratified cluster sampling method. Basic information, lifestyle and school bullying were collected through questionnaire surveys. Factors affecting school bullying experienced by primary and middle school students were analyzed using a multivariable logistic regression model.
Results:
Totally 137 846 valid questionnaires were recovered, with an effective recovery rate of 97.17%. There were 72 526 males (52.61%) and 65 320 females (47.39%). There were 47 561 primary school students (34.50%), 47 701 junior high school students (34.61%) and 42 584 senior high school students (30.89%). A total of 3 987 students suffered from school bullying, accounting for 2.89%. The proportions of being maliciously teased, being intentionally excluded from group activities/isolated, being teased about physical defects or appearance, being hit/kicked/pushed/shoved/locked in a room, being threatened, and being extorted for money were 2.04%, 1.18%, 1.11%, 0.86%, 0.84% and 0.83%, respectively. Multivariable logistic regression analysis showed that the students who were males (OR=1.122, 95%CI: 1.048-1.202), lived in suburban areas (OR=1.322, 95%CI: 1.233-1.418), lived in areas with medium (OR=1.086, 95%CI: 1.006-1.173) or underdeveloped (OR=1.298, 95%CI: 1.191-1.415) economic level, had higher academic levels (junior high school, OR=1.380, 95%CI: 1.270-1.499; senior high school, OR=1.210, 95%CI: 1.083-1.351), lived on campus (OR=1.489, 95%CI: 1.372-1.616), engaged in fights (OR=6.029, 95%CI: 5.585-6.509), attempted to smoke (OR=1.320, 95%CI: 1.128-1.545), drank (OR=1.735, 95%CI: 1.575-1.912), were scolded and beaten by parents (OR=1.972, 95%CI: 1.822-2.135) and were obese (OR=1.240, 95%CI: 1.132-1.360) were more likely to experience school bullying.
Conclusion
The harm of school bullying to the physical and mental health of primary and middle school students should be taken seriously, and active policy measures should be adopted to strengthen intervention.
2.Changing distribution and resistance profiles of common pathogens isolated from urine in the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Yanming LI ; Mingxiang ZOU ; Wen'en LIU ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(3):287-299
Objective To investigate the distribution and antimicrobial resistance profiles of the common pathogens isolated from urine from 2015 to 2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods The bacterial strains were isolated from urine and identified routinely in 51 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Antimicrobial susceptibility was determined by Kirby-Bauer method,automatic microbiological analysis system and E-test according to the unified protocol.Results A total of 261 893 nonduplicate strains were isolated from urine specimen from 2015 to 2021,of which gram-positive bacteria accounted for 23.8%(62 219/261 893),and gram-negative bacteria 76.2%(199 674/261 893).The most common species were E.coli(46.7%),E.faecium(10.4%),K.pneumoniae(9.8%),E.faecalis(8.7%),P.mirabilis(3.5%),P.aeruginosa(3.4%),SS.agalactiae(2.6%),and E.cloacae(2.1%).The strains were more frequently isolated from inpatients versus outpatients and emergency patients,from females versus males,and from adults versus children.The prevalence of ESBLs-producing strains in E.coli,K.pneumoniae and P.mirabilis was 53.2%,52.8%and 37.0%,respectively.The prevalence of carbapenem-resistant strains in E.coli,K.pneumoniae,P.aeruginosa and A.baumannii was 1.7%,18.5%,16.4%,and 40.3%,respectively.Lower than 10%of the E.faecalis isolates were resistant to ampicillin,nitrofurantoin,linezolid,vancomycin,teicoplanin and fosfomycin.More than 90%of the E.faecium isolates were ressitant to ampicillin,levofloxacin and erythromycin.The percentage of strains resistant to vancomycin,linezolid or teicoplanin was<2%.The E.coli,K.pneumoniae,P.aeruginosa and A.baumannii strains isolated from ICU inpatients showed significantly higher resistance rates than the corresponding strains isolated from outpatients and non-ICU inpatients.Conclusions E.coli,Enterococcus and K.pneumoniae are the most common pathogens in urinary tract infection.The bacterial species and antimicrobial resistance of urinary isolates vary with different populations.More attention should be paid to antimicrobial resistance surveillance and reduce the irrational use of antimicrobial agents.
3.Changing resistance profiles of Enterococcus in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Na CHEN ; Ping JI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WEN ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(3):300-308
Objective To understand the distribution and changing resistance profiles of clinical isolates of Enterococcus in hospitals across China from 2015 to 2021.Methods Antimicrobial susceptibility testing was conducted for the clinical isolates of Enterococcus according to the unified protocol of CHINET program by automated systems,Kirby-Bauer method,or E-test strip.The results were interpreted according to the Clinical & Laboratory Standards Institute(CLSI)breakpoints in 2021.WHONET 5.6 software was used for statistical analysis.Results A total of 124 565 strains of Enterococcus were isolated during the 7-year period,mainly including Enterococcus faecalis(50.7%)and Enterococcus faecalis(41.5%).The strains were mainly isolated from urinary tract specimens(46.9%±2.6%),and primarily from the patients in the department of internal medicine,surgery and ICU.E.faecium and E.faecalis strains showed low level resistance rate to vancomycin,teicoplanin and linezolid(≤3.6%).The prevalence of vancomycin-resistant E.faecalis and E.faecium was 0.1%and 1.3%,respectively.The prevalence of linezolid-resistant E.faecalis increased from 0.7%in 2015 to 3.4%in 2021,while the prevalence of linezolid-resistant E.faecium was 0.3%.Conclusions The clinical isolates of Enterococcus were still highly susceptible to vancomycin,teicoplanin,and linezolid,evidenced by a low resistance rate.However,the prevalence of linezolid-resistant E.faecalis was increasing during the 7-year period.It is necessary to strengthen antimicrobial resistance surveillance to effectively identify the emergence of antibiotic-resistant bacteria and curb the spread of resistant pathogens.
4.Changing resistance profiles of Enterobacter isolates in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Shaozhen YAN ; Ziyong SUN ; Zhongju CHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yi XIE ; Mei KANG ; Fengbo ZHANG ; Ping JI ; Zhidong HU ; Jin LI ; Sufang GUO ; Han SHEN ; Wanqing ZHOU ; Yingchun XU ; Xiaojiang ZHANG ; Xuesong XU ; Chao YAN ; Chuanqing WANG ; Pan FU ; Wei JIA ; Gang LI ; Yuanhong XU ; Ying HUANG ; Dawen GUO ; Jinying ZHAO ; Wen'en LIU ; Yanming LI ; Hua YU ; Xiangning HUANG ; Bin SHAN ; Yan DU ; Shanmei WANG ; Yafei CHU ; Yuxing NI ; Jingyong SUN ; Yunsong YU ; Jie LIN ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Yan JIN ; Chunhong SHAO ; Jihong LI ; Lixia ZHANG ; Juan MA ; Yunzhuo CHU ; Sufei TIAN ; Jinju DUAN ; Jianbang KANG ; Ruizhong WANG ; Hua FANG ; Fangfang HU ; Yunjian HU ; Xiaoman AI ; Fang DONG ; Zhiyong LÜ ; Hong ZHANG ; Chun WANG ; Yong ZHAO ; Ping GONG ; Lei ZHU ; Jinhua MENG ; Xiaobo MA ; Yanping ZHENG ; Jinsong WU ; Yuemei LU ; Ruyi GUO ; Yan ZHU ; Kaizhen WEN ; Yirong ZHANG ; Chunlei YUE ; Jiangshan LIU ; Wenhui HUANG ; Shunhong XUE ; Xuefei HU ; Hongqin GU ; Jiao FENG ; Shuping ZHOU ; Yan ZHOU ; Yunsheng CHEN ; Qing MENG ; Bixia YU ; Jilu SHEN ; Rui DOU ; Shifu WANG ; Wen HE ; Longfeng LIAO ; Lin JIANG
Chinese Journal of Infection and Chemotherapy 2024;24(3):309-317
Objective To examine the changing antimicrobial resistance profile of Enterobacter spp.isolates in 53 hospitals across China from 2015 t0 2021.Methods The clinical isolates of Enterobacter spp.were collected from 53 hospitals across China during 2015-2021 and tested for antimicrobial susceptibility using Kirby-Bauer method or automated testing systems according to the CHINET unified protocol.The results were interpreted according to the breakpoints issued by the Clinical & Laboratory Standards Institute(CLSI)in 2021(M100 31st edition)and analyzed with WHONET 5.6 software.Results A total of 37 966 Enterobacter strains were isolated from 2015 to 2021.The proportion of Enterobacter isolates among all clinical isolates showed a fluctuating trend over the 7-year period,overall 2.5%in all clinical isolates amd 5.7%in Enterobacterale strains.The most frequently isolated Enterobacter species was Enterobacter cloacae,accounting for 93.7%(35 571/37 966).The strains were mainly isolated from respiratory specimens(44.4±4.6)%,followed by secretions/pus(16.4±2.3)%and urine(16.0±0.9)%.The strains from respiratory samples decreased slightly,while those from sterile body fluids increased over the 7-year period.The Enterobacter strains were mainly isolated from inpatients(92.9%),and only(7.1±0.8)%of the strains were isolated from outpatients and emergency patients.The patients in surgical wards contributed the highest number of isolates(24.4±2.9)%compared to the inpatients in any other departement.Overall,≤ 7.9%of the E.cloacae strains were resistant to amikacin,tigecycline,polymyxin B,imipenem or meropenem,while ≤5.6%of the Enterobacter asburiae strains were resistant to these antimicrobial agents.E.asburiae showed higher resistance rate to polymyxin B than E.cloacae(19.7%vs 3.9%).Overall,≤8.1%of the Enterobacter gergoviae strains were resistant to tigecycline,amikacin,meropenem,or imipenem,while 10.5%of these strains were resistant to polycolistin B.The overall prevalence of carbapenem-resistant Enterobacter was 10.0%over the 7-year period,but showing an upward trend.The resistance profiles of Enterobacter isolates varied with the department from which they were isolated and whether the patient is an adult or a child.The prevalence of carbapenem-resistant E.cloacae was the highest in the E.cloacae isolates from ICU patients.Conclusions The results of the CHINET Antimicrobial Resistance Surveillance Program indicate that the proportion of Enterobacter strains in all clinical isolates fluctuates slightly over the 7-year period from 2015 to 2021.The Enterobacter strains showed increasing resistance to multiple antimicrobial drugs,especially carbapenems over the 7-year period.
5.Changing resistance profiles of Proteus,Morganella and Providencia in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Yunmin XU ; Xiaoxue DONG ; Bin SHAN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Ping JI ; Fengbo ZHANG ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Hongyan ZHENG ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WEN ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(4):410-417
Objective To understand the changing distribution and antimicrobial resistance profiles of Proteus,Morganella and Providencia in hospitals across China from January 1,2015 to December 31,2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods Antimicrobial susceptibility testing was carried out following the unified CHINET protocol.The results were interpreted in accordance with the breakpoints in the 2021 Clinical & Laboratory Standards Institute(CLSI)M100(31 st Edition).Results A total of 32 433 Enterobacterales strains were isolated during the 7-year period,including 24 160 strains of Proteus,6 704 strains of Morganella,and 1 569 strains of Providencia.The overall number of these Enterobacterales isolates increased significantly over the 7-year period.The top 3 specimen source of these strains were urine,lower respiratory tract specimens,and wound secretions.Proteus,Morganella,and Providencia isolates showed lower resistance rates to amikacin,meropenem,cefoxitin,cefepime,cefoperazone-sulbactam,and piperacillin-tazobactam.For most of the antibiotics tested,less than 10%of the Proteus and Morganella strains were resistant,while less than 20%of the Providencia strains were resistant.The prevalence of carbapenem-resistant Enterobacterales(CRE)was 1.4%in Proteus isolates,1.9%in Morganella isolates,and 15.6%in Providencia isolates.Conclusions The overall number of clinical isolates of Proteus,Morganella and Providencia increased significantly in the 7-year period from 2015 to 2021.The prevalence of CRE strains also increased.More attention should be paid to antimicrobial resistance surveillance and rational antibiotic use so as to prevent the emergence and increase of antimicrobial resistance.
6.Changing distribution and resistance profiles of Klebsiella strains in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Chuyue ZHUO ; Yingyi GUO ; Chao ZHUO ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WEN ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(4):418-426
Objective To understand the changing distribution and antimicrobial resistance profiles of Klebsiella strains in 52 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Antimicrobial susceptibility testing was carried out according to the unified CHINET protocol.The susceptibility results were interpreted according to the breakpoints in the Clinical & Laboratory Standards Institute(CLSI)M100 document.Results A total of 241,549 nonduplicate Klebsiella strains were isolated from 2015 to 2021,including Klebsiella pneumoniae(88.0%),Klebsiella aerogenes(5.8%),Klebsiella oxytoca(5.7%),and other Klebsiella species(0.6%).Klebsiella strains were mainly isolated from respiratory tract(48.49±5.32)%.Internal medicine(22.79±3.28)%,surgery(17.98±3.10)%,and ICU(14.03±1.39)%were the top 3 departments where Klebsiella strains were most frequently isolated.K.pneumoniae isolates showed higher resistance rate to most antimicrobial agents compared to other Klebsiella species.Klebsiella isolates maintained low resistance rates to tigecycline and polymyxin B.ESBLs-producing K.pneumoniae and K.oxytoca strains showed higher resistance rates to all the antimicrobial agents tested compared to the corresponding ESBLs-nonproducing strains.The K.pneumoniae and carbapenem-resistant K.pneumoniae(CRKP)strains isolated from ICU patients demonstrated higher resistance rates to majority of the antimicrobial agents tested than the strains isolated from non-ICU patients.The CRKP strains isolated from adult patients had higher resistance rates to most of the antimicrobial agents tested than the corresponding CRKP strains isolated from paediatric patients.Conclusions The prevalence of carbapenem-resistant strains in Klebsiella isolates increased greatly from 2015 to 2021.However,the Klebsiella isolates remained highly susceptible to tigecycline and polymyxin B.Antimicrobial resistance surveillance should still be strengthened for Klebsiella strains.
7.Changing resistance profiles of Staphylococcus isolates in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Yuling XIAO ; Mei KANG ; Yi XIE ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Ping JI ; Fengbo ZHANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WEN ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(5):570-580
Objective To investigate the changing distribution and antibiotic resistance profiles of clinical isolates of Staphylococcus in hospitals across China from 2015 to 2021.Methods Antimicrobial susceptibility testing was conducted for the clinical isolates of Staphylococcus according to the unified protocol of CHINET(China Antimicrobial Surveillance Network)using disk diffusion method and commercial automated systems.The CHINET antimicrobial resistance surveillance data from 2015 to 2021 were interpreted according to the 2021 CLSI breakpoints and analyzed using WHONET 5.6.Results During the period from 2015 to 2021,a total of 204,771 nonduplicate strains of Staphylococcus were isolated,including 136,731(66.8%)strains of Staphylococcus aureus and 68,040(33.2%)strains of coagulase-negative Staphylococcus(CNS).The proportions of S.aureus isolates and CNS isolates did not show significant change.S.aureus strains were mainly isolated from respiratory specimens(38.9±5.1)%,wound,pus and secretions(33.6±4.2)%,and blood(11.9±1.5)%.The CNS strains were predominantly isolated from blood(73.6±4.2)%,cerebrospinal fluid(12.1±2.5)%,and pleural effusion and ascites(8.4±2.1)%.S.aureus strains were mainly isolated from the patients in ICU(17.0±7.3)%,outpatient and emergency(11.6±1.7)%,and department of surgery(11.2±0.9)%,whereas CNS strains were primarily isolated from the patients in ICU(32.2±9.7)%,outpatient and emergency(12.8±4.7)%,and department of internal medicine(11.2±1.9)%.The prevalence of methicillin-resistant strains was 32.9%in S.aureus(MRSA)and 74.1%in CNS(MRCNS).Over the 7-year period,the prevalence of MRSA decreased from 42.1%to 29.2%,and the prevalence of MRCNS decreased from 82.1%to 68.2%.MRSA showed higher resistance rates to all the antimicrobial agents tested except trimethoprim-sulfamethoxazole than methicillin-susceptible S.aureus(MSSA).Over the 7-year period,MRSA strains showed decreasing resistance rates to gentamicin,rifampicin,and levofloxacin,MRCNS showed decreasing resistance rates to gentamicin,erythromycin,rifampicin,and trimethoprim-sulfamethoxazole,but increasing resistance rate to levofloxacin.No vancomycin-resistant strains were detected.The prevalence of linezolid-resistant MRCNS increased from 0.2%to 2.3%over the 7-year period.Conclusions Staphylococcus remains the major pathogen among gram-positive bacteria.MRSA and MRCNS were still the principal antibiotic-resistant gram-positive bacteria.No S.aureus isolates were found resistant to vancomycin or linezolid,but linezolid-resistant strains have been detected in MRCNS isolates,which is an issue of concern.
8.Value of intraperitoneal soluble interleukin-6 receptor in predicting ultrafiltration insufficiency in peritoneal dialysis patients
Han LI ; Wei NIU ; Xinyu SU ; Yiwei SHEN ; Hao YAN ; Zhenyuan LI ; Zanzhe YU ; Jiangzi YUAN ; Na JIANG ; Jiaying HUANG ; Zhaohui NI ; Leyi GU ; Wei FANG
Chinese Journal of Nephrology 2024;40(6):442-450
Objective:To investigate the value of soluble interleukin-6 (IL-6) receptor (sIL-6R) level in predicting ultrafiltration insufficiency in peritoneal dialysis (PD) patients.Methods:It was a prospective cohort study. The patients who received continuous ambulatory PD and regular follow-up between November 2016 and July 2018 in the PD Center of Renji Hospital, School of Medicine, Shanghai Jiao Tong University were enrolled. Enzyme-linked immunosorbent assay was used to determine dialysate sIL-6R and its appearance rate (AR) was calculated. Patients were divided into high sIL-6R AR group and low sIL-6R AR group according to median value of sIL-6R AR and prospectively followed up until death, PD cessation, or the end of the study (December 31, 2022). Multiple linear regression was used to analyze the related factors of sIL-6R AR. Kaplan-Meier method and log-rank test were used to compare the survival rate difference of ultrafiltration insufficiency between high sIL-6R AR group and low sIL-6R AR group. Multivariate Cox regression and multivariate competing risk models were used to assess the risk factors associated with occurrence of ultrafiltration insufficiency.Results:A total of 198 PD patients were enrolled, including 115 (58.1%) males, with age of (54.9±13.7) years old and PD duration of 22.5 (6.6, 65.0) months. The sIL-6R AR of the cohort was 2 094.7 (1 672.4, 2 920.9) pg/min. Compared with low sIL-6R AR(<2 094.7 pg/min)group, high sIL-6R AR(>2 094.7 pg/min)group had older age ( t=-3.269, P=0.001), higher body mass index ( t=-3.248, P=0.001), proportion of combined diabetes mellitus ( χ2=8.890, P=0.003), 24 h glucose exposure ( Z=-2.257, P=0.024), 24 h ultrafiltration capacity ( Z=-2.515, P=0.012), 4 h dialysate creatinine to serum creatinine ratio ( t=-2.609, P=0.010), mass transfer area coefficient of creatinine ( Z=-2.308, P=0.021), IL-6 AR ( Z=-3.533, P<0.001) and solute glycoprotein 130 AR ( Z=-8.670, P<0.001), and lower serum albumin ( t=2.595, P=0.010) and residual renal function ( t=2.133, P=0.033). Multiple linear regression analysis showed that body mass index ( β=0.194, P=0.005), serum albumin ( β=-0.215, P=0.002) and dialysate lg[IL-6 AR] ( β=0.197, P=0.011) were independently correlated with sIL-6R AR. By the end of the study, 57 (28.8%) patients developed ultrafiltration insufficiency. Kaplan-Meier analysis showed that high sIL-6R AR group had a significantly inferior ultrafiltration insufficiency-free survival rate than that in low sIL-6R AR group (log-rank χ 2=5.375, P=0.020). Multivariate Cox regression analysis and multivariate competing risk models showed that high dialysate sIL-6R AR (>2 094.7 pg/min) was an independent influencing factor of ultrafiltration insufficiency ( HR=2.286 , 95% CI 1.254-4.165 , P=0.007 ; SHR=2.074, 95% CI 1.124-3.828, P=0.020) in PD patients. Conclusions:Dialysate sIL-6R level was associated with body mass index, serum albumin and dialysate IL-6 level. Dialysate sIL-6R may be a predictive factor of ultrafiltration insufficiency in PD patients.
9.Analysis of depressive symptoms and influencing factors among middle and high school students from 2018 to 2021 in Zhejiang Province
GU Fang, YANG Ying, ZHENG Weijun, MENG Jia, LI Juanjuan, SHEN Yu, GAO Lei, ZOU Yan, ZHANG Ronghua
Chinese Journal of School Health 2024;45(4):520-524
Objective:
To investigate the prevalence and associated factors of depressive symptoms among middle and high school students in Zhejiang Province, so as to provide scientific basis for the implementation of depressive intervention.
Methods:
Based on the health status and associated factors of middle and high school students in the project "Monitoring of Common Diseases and Health Influencing Factors of Students" during 2018 to 2021, a total of 73 309 students including middle school, ordinary high school and vocational high school surveyed in 11 cities of Zhejiang Province were selected by multi stage stratified cluster random sampling method. From 2018 to 2021, there were 6 008, 21 917, 23 712 and 21 672 students, respectively. The Chi square test and Logistic regression model were used to analyze the influencing factors of depressive symptoms in middle and high school students.
Results:
From 2018 to 2021, depressive symptoms detection rate of middle school students was 14.8%, with higher rate in girls (17.1%) than in boys (12.7%), higher rate in high school (17.1% in ordinary high school, 17.6% in vocational high school) than middle school (12.5%)( χ 2=278.77, 327.22, P <0.05). Univariate analysis showed that there were statistically significant differences in depressive symptoms detection rate among middle school students with different years (2018: 16.7%,2019: 17.9% , 2020: 13.1%, 2021: 13.0%), residence (yes: 16.3%, no:13.5%), body mass index classification (not overweight or obesity: 14.8%, overweight: 14.2%, Obesity: 15.7%), weekly exercise days (0-2 d: 17.1%, 3-5 d: 12.5%, 6-7 d: 13.1%) and bullying (yes: 35.5%, no: 10.7%) ( χ 2=293.40, 118.35, 7.83, 287.24, 4 978.84, P <0.05). Multivariate Logistic regression analysis showed that female students, ordinary high schools, vocational high schools, obesity, school bullying were positively correlated with depression ( OR =1.65, 1.70, 1.60, 1.12, 5.21), exercise 3 to 5 days per week, exercise 6 to 7 days per week were negatively correlated with depression ( OR=0.77, 0.81, P <0.01).
Conclusions
Depressive symptoms among middle and high school students in Zhejiang Province are prominent. Strengthening mental health education for students and providing attention and support from families, schools, and society are essential steps to reduce the occurrence of depressive symptoms among these students.
10.Malnutrition among primary and secondary school students from 2008 to 2021 in Zhejiang Province
YANG Ying, ZHENG Weijun, GU Fang, MENG Jia, LI Juanjuan, GAO Lei, SHEN Yu, ZHANG Ronghua
Chinese Journal of School Health 2024;45(9):1255-1259
Objective:
To describe the prevalence characteristics and trend of malnutrition among primary and secondary school students in Zhejiang Province from 2008 to 2021, so as to provide scientific references for targeted interventions on malnutrition among children and adolescents.
Methods:
Based on the National Student Common Diseases and Health Influencing Factors Surveillance Project, 81 228 primary and middle school students aged 9-17 from Zhejiang Province were recruited for a questionnaire in 2008, 2014 and 2021, with stratified cluster random sampling method. Malnutrition was determined by Screening for Malnutrition in School aged Children and Adolescents. The Kruskal-Wallis test was used for non normally distributed data, and the Chi square test was used for categorical data. A trend Chi square test analyzed detection rates across different years.
Results:
The prevalence rates of malnutrition, stunting, mild wasting, and moderate to severe wasting among primary and secondary school students in 2008, 2014 and 2021 were 12.0%, 6.6%, 6.0%; 1.2%, 0.5%, 0.3%; 6.0%, 3.9%, 3.6%; and 4.7%, 2.2%, 2.2%, with an overall declining trend ( χ 2 trend =532.73, 181.43, 161.24, 240.38, P <0.05). The prevalence rates of malnutrition and mild wasting in each year were higher in boys (13.7%, 7.6%; 7.5%, 5.0%; 7.1%, 4.5%) than in girls (10.3%, 4.4%; 5.5%, 2.7%; 4.8%, 2.5%) ( χ 2=54.45, 88.67; 47.04, 81.07; 85.28, 98.81; P <0.01). The difference in malnutrition prevalence between urban and rural areas gradually narrowed (12.5%, 11.6%; 6.9%, 6.3%; 6.0%, 6.0%), with no statistically significant difference in 2021 ( χ 2= 0.01 , P >0.05). Malnutrition among primary and secondary school students was primarily characterized by mild wasting (56.0%) in Zhejiang Province. Compared to 2008, the prevalence of malnutrition in 2014 and 2021 showed a steady upward trend with increasing age in Zhejiang Province( χ 2 trends =44.52, 11.78, P <0.01).
Conclusions
The prevalence of malnutrition among primary and secondary school students aged 9 to 17 years in Zhejiang Province decreases by year from 2008 to 2021. However, the prevalence increase steadily with age, and boys have a higher prevalence of malnutrition. Policies should be developed age , gender , and growth appropriate dietary patterns to reduce malnutrition among primary and secondary school students.


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