Machine learning assessment of white blood cell counts in workers exposed to benzene: a historical cohort study.

To explore the fitting effect of the ARIMA, GM(1,1), and RANSAC model in the changes of white blood cells (WBC) in benzene-exposed workers, and select the optimal model to predict the WBC count of workers. Among 350 employees in an aerospace process manufacturing enterprise in Nanjing, workers with 10 years of benzene exposure were selected, and used Excel software to organize the WBC data, and the ARIMA model and RANSAC model were established by R software, and the GM(1, 1) model was established by DPS software, and the magnitude of the mean absolute percentage error (MAPE) of fitting three models to WBC counts was compared. The MAPE based on the ARIMA(2,1,2) model is 6.78%, the MAPE based on the GM(1,1) model is 5.19%, and the MAPE based on the RANSAC model is 6.37%, so the GM( 1,1) model was more suitable for fitting the trend of WBC counts in benzene exposed workers in this study. The GM(1,1) model is suitable for fitting WBC counts in a small sample size and can provide a short-term prediction of WBC counts in benzene-exposed workers and provide basic information for occupational health risk assessment of workers.

Effectiveness of online and offline health education myopia intervention on primary school students / 中国学校卫生

Objective@#To assess the effectiveness of online and offline myopia prevention and control health education interventions using wearable behavior monitoring tools for non myopic elementary school students,so as to provide evidence based medical support for public health practices.@*Methods@#From May to June in 2021, two schools were selected within the same county in Jiangsu Province. School 1 conducted online and offline parental health education ( n =111), while school 2 exclusively conducted offline health education activities, representing the traditional intervention group ( n =122). Students from both schools underwent monitoring through wearable behavior tracking tools, with feedback reports provided (eye distance, eye duration, ambient light, and outdoor exposure time). Both schools relied on activities to carry out health education interventions, and organized the distribution of promotional materials and display boards. The intervention group also established WeChat groups to conduct online "Healthy Parents Action" (answering and providing feedback on health knowledge related to myopia prevention and control, myopia prevention and control, science popularization, etc. raised by parents). Evaluation criteria included myopia rates, post dilation refractive error, and axial length, with a tracking period of two years (from 2021 to 2023). Additionally, the study collected refractive parameters from non myopic students who did not participate in wearable tool monitoring in the 12 classes across the two schools.@*Results@#The baseline results indicated that there were no significant differences between the two groups in terms of refractive parameters and wearable tool monitoring results (including screen time, viewing distance, outdoor exposure time, and homework light exposure)( t/Z/χ 2=1.94,1.17,0.58,0.40,0.80,0.69,0.32, P >0.05). After a two-year follow up, in the first and second year, the myopia rate of the online Healthy Parents Action group (11.4%, 29.7%) were lower than that of the traditional group (26.2%, 50.9%), and the degree of refractive change in the intervention group [0.63(0.38,1.19)D] was lower than that of the traditional group [0.91(0.40,1.50)D], and all the differences were statistically significant( χ 2/ Z =4.93，10.37，2.29， P <0.05). However, there were no significant differences ( P >0.05) in axial length changes between the two groups over the twoyear intervention period. Nevertheless, in the second year, the axial length change in the traditional group [0.35(0.20,0.65)mm] was lower than that in the natural observation group [0.55(0.30,0.75)mm], and this difference was statistically significant ( Z =1.92, P <0.05).@*Conclusions@#Online and offline myopia prevention and control health education can effectively reduce myopia rates. The intervention mode combining wearable behavior monitoring tools with online health education may have better effects, but further large sample and multi center studies are needed to provide additional evidence and confirmation.

Occupational Mercury Exposure at a Thermometer Facility - Jiangsu Province, 2019.

WHAT IS ALREADY KNOWN ABOUT THIS TOPIC?: Mercury is still used in the manufacture of some thermometers in China. This may pose health risks if exposure is not properly prevented and controlled. WHAT IS ADDED BY THIS REPORT?: An onsite investigation of a workplace at a thermometer facility in Jiangsu Province in 2019 found heavily elevated airborne and urinary mercury levels among a massive number of workers exposed to mercury. Traditional and obsolete technology as well as inadequate protection measures for occupational hazards caused this high level of exposure. WHAT ARE THE IMPLICATIONS FOR PUBLIC HEALTH PRACTICE?: Employers at thermometer producing facilities need to adopt effective protection measures and implement strict management. Monitoring exposure, adopting better engineering controls, diligent cleaning, and providing recommended personal protective equipment (PPE) along with training to their workers properly can alleviate mercury exposure at their facilities. In addition, transitioning to mercury-free thermometers would eliminate the risk of mercury exposure.

[Association of DNMT3a's single nucleotide polymorphisms with susceptibility to noise-induced hearing loss in Chinese workers].

OBJECTIVE: To investigate the potential association of DNMT3a's single nucleotide polymorphism with susceptibility to noise-induced hearing loss( NIHL) in Chinese noise-exposed workers. METHODS: A case-control study was performed, and 998 noise-exposed workers from a chemical fibre factory and an energy company, who underwent occupational health examination in 2015, were enrolled as study subjects. Then, general information and noise exposure of the study subjects were obtained through questionnaire survey and on-site noise detection. According to the result of audiological evaluation, they were divided into case group( n = 498, high-frequency threshold shift >25 dB) and man-matched control group( n = 500, high-frequency threshold shift ≤25 dB). At last, genotyping of DNMT3a rs7590760 was conducted with TaqMan-PCR technique. RESULTS: In the dominant model, the distribution of rs7590760 genotypes between the case group and the control group was statistically significant( P = 0. 001). The NIHL risk of subjects with CC/CG genotype is 1. 56 times the risk of those carrying GG genotype, with an adjusted OR = 1. 56( 95% CI 1. 22-2. 01). After the noise exposure period and noise exposure intensity were stratified, the adjusted OR values for noise exposure period ≤16 years, > 16 years and noise intensity ≤85, 86-92 and >92 dB were respectively 1. 67( 95% CI 1. 17-2. 38), 1. 52( 95% CI 1. 06-2. 17), 1. 56( 95% CI 1. 06-2. 30), 1. 67( 95% CI 0. 94-2. 99) and 1. 51( 95% CI 1. 01-2. 26). CONCLUSION: The CC/CG genotype of rs7590760 in DNMT3a gene is a potential risk factor for noise-induced hearing loss in Chinese noise-exposed workers.