Objective:To evaluate the clinical application of the SITA faster (SFR) visual field strategy in glaucoma patients.Methods:A diagnostic test was adopted.A total of 72 subjects who visited the Eye and ENT Hospital Affiliated to Fudan University during September 2018 to February 2019 were collected, including 28 normal subjects (56 eyes) and 44 glaucoma patients (86 eyes). The consistency and convenience of visual field tests were evaluated using SITA Standard (SS) and SITA Fast (SF), or SS and SITA Faster (SFR) in normal subjects and glaucoma patients.Test duration, visual field index (VFI), mean deviation (MD) and the number of defect points with probabilities of <5%, <2%, <1%, and <0.5% in the pattern deviation probability plots were recorded, and tested for difference, correlation and consistency.This study followed the Declaration of Helsinki.Written informed consent was obtained from all subjects prior to their entering the study cohort.The study protocol was approved by the Ethics Committee of the Eye and ENT Hospital of Fudan University.Results:For all of the included subjects, the mean test durations of SF and SFR were (64±13)% and (44±10)% compared to that of SS, respectively.MD and VFI evaluated by SS and SF, or by SS and SFR, showed no significant difference in either the normal subjects or the glaucoma patients (all at P>0.05). Across all included subjects, the positive correlation and consistency of MD and VFI were good ( r=0.99, P<0.01). However, for the results of the probability points in the pattern deviation probability blot, there was no difference among normal subjects, but the correlation and consistency were not good.In the deviation probability blot, there was a greater number of defect points of P<0.5% in glaucoma patients evaluated via SS compared to those evaluated by SFR, and the difference was statistically significant ( Z=-2.28, P=0.02). Apart from this, the number of defect points in glaucoma patients showed no difference between SS and SF, or between SS and SFR, and the correlation and consistency were higher in glaucoma patients than those in the normal subjects. Conclusions:Compared with SF and SS, SFR saves more test time.Except for partial variances in the pattern deviation probability blot, the difference between visual field strategies is relatively small and the results are basically consistent.

Background Printing and copying equipment is likely to release a large amount of particulate matter, thereby endangering human health. However, there is insufficient research on the level of particulate matter released by printers in offices and its influencing factors. Objective This study is designed to investigate the usage of printing equipment in college teachers' offices and the level of indoor particulate matter during printing, and to explore the influence of printer location and indoor ventilation on the particulate matter pollution level released during printer operation. Methods From 9:00 to 16:00 on January 4 to 6, 2021, 20 faculty offices in a university in Beijing were selected by convenient sampling to measure the indoor particulate matter level during printing, and to investigate the printing equipment usage of 31 users in the offices. Besides, experiments were designed to explore the influence of position and distance from a printer, ventilation, and the distance between a printer and a nearby window during ventilation on the number concentration of particulate matter released by the printers. Results Except one printer being placed on the ground, the other 30 printers were placed on office desks (0.71±0.16) m above the ground. Among them, 65% of the printers (n=20) were less than 1 m away from the users horizontally, and 74% of the users (n=23) accessed the printers 1-5 times a week, printing (7.03±4.07) pages per time. The peak mass concentrations in users' offices during printing of PM₁₀, PM_2.5, and PM₁ were (21.96±12.96), (7.92±5.54), and (5.77±5.00) μg·m⁻³, respectively, and the peak number concentration of PM_0.25−0.28 was (40941±36926) P·L⁻¹. The experiments showed that when the particle sizer was located in the front, side, and back of the printers, the peak values of PM_0.25−0.28 number concentration during printing were (24257±551), (12588±1354), and (11192±249) P·L⁻¹, respectively, and the difference among them was statistically significant (F=214.9, P<0.01); when the particle sizer was placed 0.1, 0.2, and 0.3 m away from the printers, the peak values of PM_0.25−0.28 number concentration during printing were (24257±551), (19847±1426), and (16480±878) P·L⁻¹, respectively, and the difference among them was statistically significant (F=44.66, P<0.01); when the experiment room was ventilated or not, the peak values of PM_0.25−0.28 number concentration during printing were (18595±488) and (24257±551) P·L⁻¹, respectively, and the difference between them was statistically significant (F=192.6, P<0.01); when the distance between the printer and the window was 1, 2, 3 m, the peak values of PM_0.25-0.28 number concentration during printing were (16780±823), (18347±348), and (18595±488) P·L⁻¹, respectively, and the difference among them was statistically significant (F=8.407, P<0.05). Conclusion The overall printer workload is small and the concentration of particulate matter in the faculty offices is low when the printers are working. Printer position, distance, ventilation, and the distance from a nearby window under ventilation conditions are factors affecting the concentration of particulate matter released by the printers.

Objective:To explore the associations between perceived built environment attributes and adults’ leisure-time physical activity in four cities of China.Methods:Multistage cluster random sampling method was used to select adults aged 25 to 64 in Hangzhou, Suzhou, Chengdu, and Qingdao. Data were collected from June 2017 to July 2018. The perception of the urban built environment was assessed by the neighborhood environment walkability scale-abbreviated (NEWS-A), and the physical activity was assessed by the International Physical Activity Questionnaire. Generalized linear mixed models were used to explore the relationship between the perceived built environment and leisure-time physical activities.Results:A total of 3 789 participants were included in the analysis. After adjusting for potential confounders, better access to public services ( OR=1.34, 95% CI: 1.02-1.75) and higher aesthetic quality ( OR=1.37, 95% CI: 1.09-1.73) were positively associated with the possibility of engaging in leisure-time physical activity in the past week. Similarly, these two attributes were positively associated with leisure-time walking. Higher scores on the perception of street connectivity were positively associated with leisure-time walking [ exp( β)=1.09, 95% CI: 1.00-1.19]. Higher residential density [ exp( β)=1.000 4, 95% CI:1.000 0-1.000 8], better access to physical activity destinations[ exp( β)=1.09, 95% CI: 1.00-1.19], and better aesthetics [ exp( β)=1.11, 95% CI:1.00-1.22] were associated with higher leisure-time physical activity. Similarly, these three attributes were positively associated with the possibility of meeting the WHO recommendations. Conclusion:Changing some urban built environment attributes may increase leisure-time physical activity.

Large population-based cohort study is an important resource for population disease prevention and control, the results of which provide scientific basis for individualized treatment and precise prevention, and it is also the key strategic content of precision medicine. The Chinese Preventive Medicine Association coordinated experienced researchers from the Chinese Academy of Medical Sciences and other professional institutes to write up the group standard entitled Technical specification of management for field investigation in large population-based cohort study (T/CPMA 001-2019). Based on the research of large population-based cohort study in China and the principle of scientific, normative, applicable, and feasible, the standard proposed six aspects of management requirements including institutional arrangement, personnel composition, equipment, materials, documents and finance, as well as the basic requirements of the on-site investigation, the requirements of each position and the overall quality control requirements, etc.. The standard aims to guide the large population-based cohorts that have been or intended to be established in China, including national cohorts, regional population cohorts, and special population cohorts, hence to improve scientific research level, accelerate scientific research output and provide localization basis for disease prevention and control in China.

Objective: To analyze the physical characteristics of fine particulate matters (PM_2.5) and submicron particulate matters (PM₁), and investigate the factors influencing the emission peak of printer particles. Methods: A 12-hour particle concentration monitoring for PM_2.5 and PM₁ was conducted in a printing shop on January 5^th, 2018. PM_2.5 in the air was analyzed after the monitoring process to figure out morphological characteristics and element composition of printer particles. Besides, experiments were carried out in an enclosed space to detect the number concentration peaks of PM₁ during every printing process. Influencing factors investigated in this study were printer types, toner coverages and interval time between different printing processes. Results: The 12-hour particles concentration monitoring showed that the number concentration of PM₁ and the mass concentration of PM_2.5 were 7.510×10⁴ pt/cm³ and 96.85 μg/m³. The diameter of most PM_2.5 was less than 100 nm, with a fractal dimension of 2.591. Most PM_2.5 appeared as regular spheres with typical agglomeration phenomenon, while some were in rhabditiform or irregular shapes. Element analysis showed that PM_2.5 was mainly composed of C, O, Si, Ca, with less metallic element. The PM₁ emission peak values of three printers were 3.60×10⁴, 3.43×10⁴, 0.31×10⁴ pt/cm³, respectively and the difference was not statistically significant (χ²=5.42, P>0.05). When the page coverage rate was 0%, 2.5%, 5%, 10%, 20% and 50%, the PM₁ emission peak value of printer A was 6.74×10⁴, 4.62×10⁴, 3.82×10⁴, 2.82×10⁴, 1.00×10⁴ and 1.08×10⁴ pt/cm³, and the difference was also not statistically significant (χ²=7.01, P>0.05). The natural logarithm of PM₁ emission peak value in printing work was associated with the resting time before printing and the change value of heating roller temperature (r value was 0.83 and 0.89, respectively, all P values<0.05). Conclusion PM_2.5 and PM₁ in the printing shop stayed at a high level. Particles appeared as various shapes and element compositions were complex. The temperature change of heating roller was one of most important factors that lead to the increased number concentration peak of PM₁.

Objective: To evaluate the correlation between alcohol consumption and obesity in adults in China. Methods: The information about alcohol consumption were collected at the baseline survey of the China Kadoorie Biobank. The general obesity and central obesity were defined by BMI and waist circumference (WC) respectively. Logistic regression model was employed to examine the relationship of drinking behavior with general obesity and central obesity. Results: A total of 249 873 adults were included. A J-shaped relationship was observed between alcohol consumption and obesity measurement index (BMI and WC) in men. Compared with non-drinkers, the proportion of general obesity and central obesity were lower in light drinkers (men: OR=0.65, 95%CI: 0.59-0.71 and OR=0.93, 95%CI: 0.88-0.98; women: OR=0.77, 95%CI: 0.65-0.91 and OR=0.89, 95%CI: 0.80-0.99). In men, the proportion of general obesity and central obesity was highest in heavy drinkers (OR=1.21, 95%CI: 1.12-1.32; OR=1.33, 95%CI: 1.27-1.40). BMI and WC were higher in those with a drinking frequency of 3-5 d/week, with largest of proportion of central obesity (men: OR=1.23, 95%CI: 1.16-1.31; women: OR=1.13, 95%CI: 0.99-1.28). The risk for central obesity in men who began drinking every week before 20 years old was 1.24 times higher than non-drinkers (95%CI: 1.16-1.33). Those who drank beer had lower proportion of general obesity (men: OR=0.74, 95%CI: 0.67-0.82; women: OR=0.54, 95%CI: 0.43-0.68). Conclusion The proportion of obesity was lower in light drinkers but higher in heavy drinkers; and the earlier drinking started, the higher the risk for obesity was.