1.Comparison of the predictive performance of SARIMA, Prophet, and BSTS models in forecasting the incidence of hand, foot, and mouth disease
LU Wenhai ; KONG Xiaojie ; SONG Lixia ; LU Chunru ; YU Bikun ; XIE Yan
Journal of Preventive Medicine 2026;38(1):79-84
Objective:
To compare the predictive performance of the seasonal autoregressive integrated moving average (SARIMA) model, the Prophet model, and the Bayesian structural time series (BSTS) model in forecasting the incidence of hand, foot, and mouth disease (HFMD) , so as to provide a basis for optimizing the early warning system of this disease.
Methods:
Weekly incidence data of HFMD in Longgang District, Shenzhen City from 2014 to 2024 were collected. The HFMD incidence data from 2014-2019 and 2023 were used as the training set to construct SARIMA, Prophet, and BSTS models, while the data from 2024 were used as the test set to compare and evaluate the predictive performance of the three models. The technique for order preference by similarity to ideal solution (TOPSIS) method was employed to calculate the C-value. This approach integrates multiple evaluation metrics, such as the mean absolute error (MAE), mean squared error (MSE), root mean squared error (RMSE), and symmetric mean absolute percentage error (SMAPE), to comprehensively assess model performance.
Results:
A total of 150 111 cases of HFMD were reported in Longgang District from 2014 to 2024, with an average annual incidence of 400.72/105. The weekly incidence fluctuated between 0 and 63.78/105, exhibiting a bimodal seasonal pattern characterized by a primary peak from May to July and a secondary peak from September to October. In the training set, all three models demonstrated a good fit to the bimodal epidemic trend of HFMD, with the BSTS model achieving the best fit. The BSTS model yielded performance metrics as follows: MAE=0.124, MSE=0.050, RMSE=0.223, SMAPE=0.021, and a C-value of 1.000. In the test set, all three models, including SARIMA, Prophet, and BSTS, performed well for short-term predictions (≤16 weeks), with the Prophet model showing relatively superior predictive performance. However, the prediction accuracy of all models declined as the forecast horizon extended. During the primary peak period (May-July), the Prophet model exhibited better predictive performance, whereas the BSTS model performed relatively better during the secondary peak period (September-October).
Conclusions
For the short-term forecasting of weekly HFMD incidence, the Prophet model outperformed both the SARIMA and BSTS models. During the primary peak period, the Prophet model demonstrated superior predictive performance, whereas the BSTS model exhibited better accuracy in forecasting the secondary peak period.
2.Explainable Machine Learning Model for Predicting Prognosis in Patients with Malignant Tumors Complicated by Acute Respiratory Failure: Based on the eICU Collaborative Research Database in the United States
Zihan NAN ; Linan HAN ; Suwei LI ; Ziyi ZHU ; Qinqin ZHU ; Yan DUAN ; Xiaoting WANG ; Lixia LIU
Medical Journal of Peking Union Medical College Hospital 2026;17(1):98-108
To develop and validate a model for predicting intensive care unit (ICU) mortality risk in patients with malignant tumors complicated by acute respiratory failure (ARF) based on an explainable machine learning framework. Clinical data of patients with malignant tumors and ARF were extracted from the eICU Collaborative Research Database in the United States, including demographic characteristics, comorbidities, vital signs, laboratory test indicators, and major interventions within the first 24 hours after ICU admission.The study outcome was ICU death.Enrolled patients were randomly divided into a training set and a validation set at a ratio of 7:3.Predictor variables were selected using least absolute shrinkage and selection operator (LASSO) regression.Five machine learning algorithms-extreme gradient boosting (XGBoost), support vector machine (SVM), Logistic regression, multilayer perceptron (MLP), and C5.0 Decision Tree-were employed to construct predictive models.Model performance was evaluated based on the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and other metrics.The optimal model was further interpreted using the Shapley additive explanations (SHAP) algorithm. A total of 3196 patients with malignant tumors complicated by ARF were included.The training set comprised 2, 261 patients and the validation set 935 patients; 683 patients died during ICU stay, while 2513 survived.LASSO regression ultimately selected 12 variables closely associated with patient ICU outcomes, including sepsis comorbidity, use of vasoactive drugs, and within the first 24 hours after ICU admission: minimum mean arterial pressure, maximum heart rate, maximum respiratory rate, minimum oxygen saturation, minimum serum bicarbonate, minimum blood urea nitrogen, maximum white blood cell count, maximum mean corpuscular volume, maximum serum potassium, and maximum blood glucose.After model evaluation, the XGBoost model demonstrated the best performance.The AUCs for predicting ICU mortality risk in the training and validation sets were 0.940 and 0.763, respectively; accuracy was 88.3% and 81.2%;sensitivity was 98.5% and 95.9%.Its predictive performance also remained optimal in sensitivity analyses.SHAP analysis indicated that the top five variables contributing to the model's predictions were minimum oxygen saturation, minimum serum bicarbonate, minimum mean arterial pressure, use of vasoactive drugs, and maximum white blood cell count. This study successfully developed a mortality risk prediction model for ICU patients with malignant tumors complicated by ARF based on a large-scale dataset and performed explainability analysis.The model aids clinicians in early identification of high-risk patients and implementing individualized interventions.
3.Pain, agitation, and delirium practices in Chinese intensive care units: A national multicenter survey study.
Xiaofeng OU ; Lijie WANG ; Jie YANG ; Pan TAO ; Cunzhen WANG ; Minying CHEN ; Xuan SONG ; Zhiyong LIU ; Zhenguo ZENG ; Man HUANG ; Xiaogan JIANG ; Shusheng LI ; Erzhen CHEN ; Lixia LIU ; Xuelian LIAO ; Yan KANG
Chinese Medical Journal 2025;138(22):3031-3033
4.Development and application of intensive care unit digital intelligence multimodal shift handover system.
Xue BAI ; Lixia CHANG ; Wei FANG ; Zhengang WEI ; Yan CHEN ; Zhenfeng ZHOU ; Min DING ; Hongli LIU ; Jicheng ZHANG
Chinese Critical Care Medicine 2025;37(10):950-955
OBJECTIVE:
To develop a digital intelligent multimodal shift handover system for the intensive care unit (ICU) and evaluate its application effect in ICU shift handovers.
METHODS:
A research and development team was established, consisting of 1 department director, 1 head nurse, 3 information technology engineers, 3 nurses, and 2 doctors. Team members were assigned responsibilities including overall coordination and planning, platform design and maintenance, pre-application training, collection and organization of clinical feedback, and research investigation respectively. A digital intelligent multimodal shift handover system was developed for ICU based on the Shannon-Weaver linear transmission model. This innovative system integrated automated data collection, intelligent dynamic monitoring, multidimensional condition analysis and visual reporting functions. A cloud platform was used to gather data from multi-parameter vital signs monitors, infusion pumps, ventilators and other devices. Artificial intelligence algorithms were employed to standardize and analyze the data, providing personalized recommendations for healthcare professionals. A self-controlled before-after method was adopted. Before the application of the ICU digital intelligent multimodal shift handover system (from December 2023 to March 2024), the traditional verbal bedside handover was used; from June 2024 to March 2025, the ICU digital intelligent multimodal shift handover system was applied for shift handovers. Questionnaires before the application of the shift handover system were collected in April 2024, and those after the application were collected in April 2025. The shift handover time, handover quality (scored by the nursing handover evaluation scale), satisfaction with doctor-nurse communication (scored by the ICU doctor-nurse scale) before and after the application of the handover system were compared, and nurses' satisfaction with the shift handover system (scored by the clinical nursing information system effectiveness evaluation scale) was investigated.
RESULTS:
After the application of the ICU digital intelligent multimodal shift handover system, the shift handover time was significantly shorter than that before the application [minutes: 20 (15, 25) vs. 30 (22, 40)], the handover quality was significantly higher than that before the application [score: 84.0 (78.0, 88.5) vs. 71.0 (55.0, 79.0)], and the satisfaction with doctor-nurse communication was also significantly higher than that before the application (score: 84.58±6.79 vs. 74.50±11.30). All differences were statistically significant (all P < 0.05). In addition, the nurses' system effectiveness evaluation scale score was 102.30±10.56, which indicated that nurses had a very high level of satisfaction with the ICU digital intelligent multimodal shift handover system.
CONCLUSIONS
The application of the ICU digital intelligent multimodal shift handover system can shorten the shift handover time, improve the handover quality, and enhance the satisfaction with doctor-nurse communication. Nurses have a high level of satisfaction with this system.
Intensive Care Units
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Humans
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Patient Handoff
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Artificial Intelligence
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Algorithms
5.Longitudinal extrauterine growth restriction in extremely preterm infants: current status and prediction model
Xiaofang HUANG ; Qi FENG ; Shuaijun LI ; Xiuying TIAN ; Yong JI ; Ying ZHOU ; Bo TIAN ; Yuemei LI ; Wei GUO ; Shufen ZHAI ; Haiying HE ; Xia LIU ; Rongxiu ZHENG ; Shasha FAN ; Li MA ; Hongyun WANG ; Xiaoying WANG ; Shanyamei HUANG ; Jinyu LI ; Hua XIE ; Xiaoxiang LI ; Pingping ZHANG ; Hua MEI ; Yanju HU ; Ming YANG ; Lu CHEN ; Yajing LI ; Xiaohong GU ; Shengshun QUE ; Xiaoxian YAN ; Haijuan WANG ; Lixia SUN ; Liang ZHANG ; Jiuye GUO
Chinese Journal of Neonatology 2024;39(3):136-144
Objective:To study the current status of longitudinal extrauterine growth restriction (EUGR) in extremely preterm infants (EPIs) and to develop a prediction model based on clinical data from multiple NICUs.Methods:From January 2017 to December 2018, EPIs admitted to 32 NICUs in North China were retrospectively studied. Their general conditions, nutritional support, complications during hospitalization and weight changes were reviewed. Weight loss between birth and discharge > 1SD was defined as longitudinal EUGR. The EPIs were assigned into longitudinal EUGR group and non-EUGR group and their nutritional support and weight changes were compared. The EPIs were randomly assigned into the training dataset and the validation dataset with a ratio of 7∶3. Univariate Cox regression analysis and multiple regression analysis were used in the training dataset to select the independent predictive factors. The best-fitting Nomogram model predicting longitudinal EUGR was established based on Akaike Information Criterion. The model was evaluated for discrimination efficacy, calibration and clinical decision curve analysis.Results:A total of 436 EPIs were included in this study, with a mean gestational age of (26.9±0.9) weeks and a birth weight of (989±171) g. The incidence of longitudinal EUGR was 82.3%(359/436). Seven variables (birth weight Z-score, weight loss, weight growth velocity, the proportion of breast milk ≥75% within 3 d before discharge, invasive mechanical ventilation ≥7 d, maternal antenatal corticosteroids use and bronchopulmonary dysplasia) were selected to establish the prediction model. The area under the receiver operating characteristic curve of the training dataset and the validation dataset were 0.870 (95% CI 0.820-0.920) and 0.879 (95% CI 0.815-0.942), suggesting good discrimination efficacy. The calibration curve indicated a good fit of the model ( P>0.05). The decision curve analysis showed positive net benefits at all thresholds. Conclusions:Currently, EPIs have a high incidence of longitudinal EUGR. The prediction model is helpful for early identification and intervention for EPIs with higher risks of longitudinal EUGR. It is necessary to expand the sample size and conduct prospective studies to optimize and validate the prediction model in the future.
6.Evaluation of the efficacy and safety of phacoemulsification under the IOL protection: a randomized controlled clinical study
Yujiao JIN ; Nan LI ; Qiushuang SUN ; Weiyi JIN ; Meiling JIANG ; Yingfeng LIU ; Yan LU ; Lixia SUN ; Renzhe CUI
Chinese Journal of Experimental Ophthalmology 2024;42(3):248-255
Objective:To observe the therapeutic effect of intraocular lens (IOL) protected phacoemulsification (PHACO) in patients with hard nucleus cataract.Methods:A randomized controlled clinical study was conducted.A total of consecutive 120 patients (120 eyes) with hard nucleus cataract of Emery grade Ⅳ or Ⅴ were enrolled from January 2019 to May 2022.The patients were randomly divided into PHACO group receiving routine PHACO, IOL protected PHACO group receiving PHACO under IOL protection, and extracapsular cataract extraction (ECCE) group receiving ECCE, with 40 cases (40 eyes) in each group.Finally, 99 patients completed the follow-up, including 30 cases (30 eyes) in PHACO group, 35 cases (35 eyes) in IOL protected PHACO group, and 34 cases (34 eyes) in ECCE group.The total operation time, intraoperative PHACO time and cumulative energy release of each patient were recorded.The corneal endothelial cell density (ECD), coefficient of variation in endothelial cell area (CV), hexagonal endothelial cell ratio (6A), corneal astigmatism and the number of eyes with different grades of uncorrected visual acuity were measured and compared after 3-month follow-up.The intraoperative and postoperative complications were recorded.This study adhered to the Declaration of Helsinki and was approved by the Ethics Committee of Yanbian University Hospital (NO.2023002).Patients were informed of study content and purpose and signed a consent form before treatment.Results:There was no significant difference in ultrasonic energy and time between PHACO group and IOL protected PHACO group ( P=0.691, 0.982).The total operation time was (38.81±2.73) and (36.45±3.45) minutes in PHACO group and IOL protected PHACO group, significantly shorter than (69.60±4.35) minutes in ECCE group (both at P<0.001).There was no significant difference in age, sex, lens nucleus hardness and other baseline data among the three groups before operation (all at P>0.05).Three months after operation, the number of patients with higher uncorrected visual acuity in PHACO group and IOL protected PHACO group was larger than that in ECCE group ( P=0.006, 0.007).The ECD and 6A in IOL protected PHACO group were (2 155.57±177.88)/mm 2 and (41.31±5.18)%, respectively, which were significantly higher than (1 912.64±224.11)/mm 2 and (36.18±3.27)% in PHACO group, and the CV in IOL protected PHACO group was (50.34±5.90)%, which was lower than (55.67±3.30)% in PHACO group, showing statistically significant differences ( P=0.007, 0.003, 0.005).At 1 week and 3 months after the operation, the corneal astigmatism was significantly lower in IOL-protected PHACO group than in ECCE group, but higher than in PHACO group, and the difference were statistically significant (all at P<0.05). Conclusions:Compared with conventional PHACO, IOL-protected PHACO can effectively reduce the damage of corneal endothelium caused by ultrasonic energy, shorten the operation time and reduce postoperative inflammatory reaction compared with ECCE, and does not significantly increase postoperative corneal astigmatism.IOL-protected PHACO is an effective improved surgical method for patients with hard nucleus cataract.
7.Genetic analysis of transcription factors in dopaminergic neuronal development in Parkinson’s disease
Yuwen ZHAO ; Lixia QIN ; Hongxu PAN ; Tingwei SONG ; Yige WANG ; Xiaoxia ZHOU ; Yaqin XIANG ; Jinchen LI ; Zhenhua LIU ; Qiying SUN ; Jifeng GUO ; Xinxiang YAN ; Beisha TANG ; Qian XU
Chinese Medical Journal 2024;137(4):450-456
Background::Genetic variants of dopaminergic transcription factor-encoding genes are suggested to be Parkinson’s disease (PD) risk factors; however, no comprehensive analyses of these genes in patients with PD have been undertaken. Therefore, we aimed to genetically analyze 16 dopaminergic transcription factor genes in Chinese patients with PD.Methods::Whole-exome sequencing (WES) was performed using a Chinese cohort comprising 1917 unrelated patients with familial or sporadic early-onset PD and 1652 controls. Additionally, whole-genome sequencing (WGS) was performed using another Chinese cohort comprising 1962 unrelated patients with sporadic late-onset PD and 1279 controls.Results::We detected 308 rare and 208 rare protein-altering variants in the WES and WGS cohorts, respectively. Gene-based association analyses of rare variants suggested that MSX1 is enriched in sporadic late-onset PD. However, the significance did not pass the Bonferroni correction. Meanwhile, 72 and 1730 common variants were found in the WES and WGS cohorts, respectively. Unfortunately, single-variant logistic association analyses did not identify significant associations between common variants and PD. Conclusions::Variants of 16 typical dopaminergic transcription factors might not be major genetic risk factors for PD in Chinese patients. However, we highlight the complexity of PD and the need for extensive research elucidating its etiology.
8.Epidemiology of rubella and its viral genetic characterization in China, 2021-2022
Cheng QIAN ; Ying LIU ; Jianlin CAI ; Aili CUI ; Liqun LI ; Lixia FAN ; Li LIU ; Shujie ZHOU ; Ying CHEN ; Xiaoxian CUI ; Naiying MAO ; Yan ZHANG ; Zhen ZHU
Chinese Journal of Experimental and Clinical Virology 2024;38(1):49-57
Objective:To understand the epidemiology of rubella and the genetic characteristics of the virus circulating during the period 2021-2022, providing basic scientific data for rubella prevention and control in China.Methods:National rubella incidence data for the period 2021-2022 were obtained from the Infectious Disease Surveillance System module and the Surveillance Report Management module of the China′s Disease Prevention and Control Information System. Positive rubella virus(RuV)isolates were obtained from the National Measles/Rubella Laboratory Network. Two nucleotide (nt) fragments [F1-480 (8 633-9 112 nt) and F2-633 (8 945-9 577 nt)] located in the E1 gene were amplified and determined by reverse transcription polymerase chain reaction (RT-PCR), and the target gene (E1-739) was obtained after collating and splicing. The sequences obtained in this study were used to construct a phylogenetic tree with the reported reference strains for genotype and lineage identification. Additionally, the phylogenetic analysis was performed to assess their genetic relatedness of RuV strains prevalent in China during 2018-2020 from GenBank database.Results:In 2021-2022, the rubella incidence in China was 0.06/100, 000 (2021: 840 cases; 2022: 784 cases), with cases primarily concentrated in the western and southern provinces. Age distribution analysis showed that rubella cases in 2021-2022 was mainly in children under 5 years of age (2021: 34.17%, 287/840; 2022: 42.09%, 330/784), with the highest proportion in children aged 0-2 years. Further analysis of the immunization history of cases revealed that in the 8-23 months age group, a significant proportion of cases had received only one dose of rubella containing vaccine (RCV); cases in the 2-14 years age group were mainly among children who had received two or more doses of RCV; however, cases over 15 years of age were primarily found in individuals who had not received RCV or had unknown immunization history. National virological surveillance data showed that totally 22 RuV virus isolates were obtained, from 6 provinces in China during 2021-2022, which belonged to lineage 1E-L2 (11 strains) and 2B-L2c (11 strains). And these viruses displayed high genetic homology with RuV prevalent from 2018 to 2020.Conclusions:The incidence of rubella in China was maintained at a low level during 2021-2022, and the prevalent RuV strains were lineage 1E-L2 and 2B-L2c.
9.National bloodstream infection bacterial resistance surveillance report (2022) : Gram-negative bacteria
Zhiying LIU ; Yunbo CHEN ; Jinru JI ; Chaoqun YING ; Qing YANG ; Haishen KONG ; Haifeng MAO ; Hui DING ; Pengpeng TIAN ; Jiangqin SONG ; Yongyun LIU ; Jiliang WANG ; Yan JIN ; Yuanyuan DAI ; Yizheng ZHOU ; Yan GENG ; Fenghong CHEN ; Lu WANG ; Yanyan LI ; Dan LIU ; Peng ZHANG ; Junmin CAO ; Xiaoyan LI ; Dijing SONG ; Xinhua QIANG ; Yanhong LI ; Qiuying ZHANG ; Guolin LIAO ; Ying HUANG ; Baohua ZHANG ; Liang GUO ; Aiyun LI ; Haiquan KANG ; Donghong HUANG ; Sijin MAN ; Zhuo LI ; Youdong YIN ; Kunpeng LIANG ; Haixin DONG ; Donghua LIU ; Hongyun XU ; Yinqiao DONG ; Rong XU ; Lin ZHENG ; Shuyan HU ; Jian LI ; Qiang LIU ; Liang LUAN ; Jilu SHEN ; Lixia ZHANG ; Bo QUAN ; Xiaoping YAN ; Xiaoyan QI ; Dengyan QIAO ; Weiping LIU ; Xiusan XIA ; Ling MENG ; Jinhua LIANG ; Ping SHEN ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2024;17(1):42-57
Objective:To report the results of national surveillance on the distribution and antimicrobial resistance profile of clinical Gram-negative bacteria isolates from bloodstream infections in China in 2022.Methods:The clinical isolates of Gram-negative bacteria from blood cultures in member hospitals of national bloodstream infection Bacterial Resistant Investigation Collaborative System(BRICS)were collected during January 2022 to December 2022. Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical and Laboratory Standards Institute(CLSI). WHONET 5.6 and SPSS 25.0 software were used to analyze the data.Results:During the study period,9 035 strains of Gram-negative bacteria were collected from 51 hospitals,of which 7 895(87.4%)were Enterobacteriaceae and 1 140(12.6%)were non-fermenting bacteria. The top 5 bacterial species were Escherichia coli( n=4 510,49.9%), Klebsiella pneumoniae( n=2 340,25.9%), Pseudomonas aeruginosa( n=534,5.9%), Acinetobacter baumannii complex( n=405,4.5%)and Enterobacter cloacae( n=327,3.6%). The ESBLs-producing rates in Escherichia coli, Klebsiella pneumoniae and Proteus spp. were 47.1%(2 095/4 452),21.0%(427/2 033)and 41.1%(58/141),respectively. The prevalence of carbapenem-resistant Escherichia coli(CREC)and carbapenem-resistant Klebsiella pneumoniae(CRKP)were 1.3%(58/4 510)and 13.1%(307/2 340);62.1%(36/58)and 9.8%(30/307)of CREC and CRKP were resistant to ceftazidime/avibactam combination,respectively. The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)complex was 59.5%(241/405),while less than 5% of Acinetobacter baumannii complex was resistant to tigecycline and polymyxin B. The prevalence of carbapenem-resistant Pseudomonas aeruginosa(CRPA)was 18.4%(98/534). There were differences in the composition ratio of Gram-negative bacteria in bloodstream infections and the prevalence of main Gram-negative bacteria resistance among different regions,with statistically significant differences in the prevalence of CRKP and CRPA( χ2=20.489 and 20.252, P<0.001). The prevalence of CREC,CRKP,CRPA,CRAB,ESBLs-producing Escherichia coli and Klebsiella pneumoniae were higher in provinicial hospitals than those in municipal hospitals( χ2=11.953,81.183,10.404,5.915,12.415 and 6.459, P<0.01 or <0.05),while the prevalence of CRPA was higher in economically developed regions(per capita GDP ≥ 92 059 Yuan)than that in economically less-developed regions(per capita GDP <92 059 Yuan)( χ2=6.240, P=0.012). Conclusions:The proportion of Gram-negative bacteria in bloodstream infections shows an increasing trend,and Escherichia coli is ranked in the top,while the trend of CRKP decreases continuously with time. Decreasing trends are noted in ESBLs-producing Escherichia coli and Klebsiella pneumoniae. Low prevalence of carbapenem resistance in Escherichia coli and high prevalence in CRAB complex have been observed. The composition ratio and antibacterial spectrum of bloodstream infections in different regions of China are slightly different,and the proportion of main drug resistant bacteria in provincial hospitals is higher than those in municipal hospitals.
10.Application of the comprehensive index method in occupational health risk assessment on chemical hazards in a metal product enterprise
Dongdong CAO ; Zihuan WANG ; Xiaoyu HU ; Lei ZHONG ; Lixia LIU ; Jia FU ; Li HU ; Liu LIU ; Yan YE
China Occupational Medicine 2024;51(5):533-538
Objective To evaluate the applicability of the comprehensive index method for assessing occupational health risks on chemical hazards in key work sites of a metal product enterprise. Methods A metal product enterprise in Beijing City was chosen as the research subject using the convenience sampling method. Occupational health investigations and chemical hazard monitoring were conducted at four work sites: grinding machine operation, welding, cutting, and painting. The comprehensive index method was used to determine the risk levels of chemical hazards. Results The grinding dust in the grinding machine operation work site was assessed as moderate risk. The nitrogen oxides and ozone in the welding (southeast) work sites were assessed as moderate risk. The nitrogen oxides ozone and welding fumes in the welding (northwest) and cutting work site were assessed as moderate risk. Benzene in the painting work site was assessed as moderate risk. All chemical hazards in other work sites were determined to pose low risks. Co-exposures to nitrogen oxides and ozone in the two welding work sites and cutting work site were classified as moderate risk. Co-exposure to ethylbenzene, xylene, methanol, ethyl acetate, and butyl acetate in the painting work site also posed moderate risk, while the co-exposure to toluene and methanol in the painting work site was assessed as low risk. Conclusion The comprehensive index method could be used for the occupational health risk assessment in the metal product enterprise. The enterprise should strengthen hazard control measures for exposure to grinding dust, welding fumes, nitrogen oxides, ozone, and benzene, and closely monitor the health risks associated with co-exposures of chemical hazards.


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