Humans ; Mining ; Noise, Occupational ; statistics & numerical data ; Occupational Exposure ; statistics & numerical data ; Work Schedule Tolerance

OBJECTIVETo measure and analyze the personal noise exposure of city metro station workers by using noise dosimeter.

METHODSAccording to job category and work type, all workers were divided into 4 groups. The workers from each group were selected as subjects for personal noise exposure measurement. CEL-320 dosimeters were worn by each subject and noise data collected by a phone fixed at collar. All subjects were asked to take notes about their working activities when they were wearing CEL-320 dosimeters. Each worker's one workday LAeq, geometric mean and range of each group were computed.

RESULTSThere were many noise sources in the metro station, and the noise exposure was unstable. The varieties of personal noise levels were recorded among 48 workers, the highest LAeq work type was of the instrument room, (81.8 +/- 2.5) dB (A), and the biggest LAeq rang was of the hall, 8.1 dB (A). The lowest LAeq was of the station control room (68.7 +/- 1.8) dB (A) and the lowest LAeq rang also was there, 4.0 dB (A).

CONCLUSIONThe personal noise exposure of metro station should be implicated. Measuring personal noise exposure individually with dosimeters might obtain the noise exposure level more integrally in the complicated environment.

Humans ; Noise, Occupational ; statistics & numerical data ; Occupational Exposure ; analysis ; statistics & numerical data ; Railroads ; Urban Population

OBJECTIVETo explore the relationship between sample size and variance of means for personal noise exposure in weaving workers as to contributing evidence for establishing personal noise exposure measurement guideline.

METHODSA personal noise exposure measurement database from a group of weaving workers was used in the randomized re-sampling data analysis. The sampling cases were one number selecting from one to fifteen at each randomized re-sampling procedure. The randomized re-sampling was one thousand times from original personal noise exposure measurement database to get one thousands of re-sampling database. One thousands of L(Aeq.8 h) mean were calculated by re-sampling databases. The variation of randomized re-sampling means was analyzed for different re-sampling numbers.

RESULTSThe change for narrow trend of maximum, minimum, 95 percent number, 5 percent number of L(Aeq.8 h) mean was faster when randomized re-sampling number was smaller in variation vs randomized re-sampling number curve analysis. After that, the change for narrow trend of L(Aeq.8 h) mean was smooth for increasing the randomized re-sampling numbers. The 95% - 5% of L(Aeq.8 h) mean was about half for randomized re-sampling four cases (3.30 dB) vs one case (7.40 dB), and about one third for seven cases (2.44 dB), and about one fourth for eleven cases (1.85 dB).

CONCLUSIONThe sample size in personal noise exposure measurement guideline could be selected from four to eleven.

Humans ; Noise, Occupational ; statistics & numerical data ; Occupational Exposure ; statistics & numerical data ; Sample Size ; Sampling Studies

China ; Humans ; Occupational Exposure ; statistics & numerical data ; Solvents

China ; Humans ; Industry ; statistics & numerical data ; Lead ; blood ; Occupational Exposure

OBJECTIVETo analyze the results of an occupational hazards survey of specially supervised enterprises (156 enterprise-times) during 2011-2012 in one district of Shenzhen, China and find out the changes in occupational hazards in these enterprises, and to put forward countermeasures for the prevention and control of occupational hazards.

METHODSOccupational hazards monitoring results for specially supervised enterprises (156 enterprise-times) during 2011-2012 were included. Comparison and analysis were performed between different years, different industries, different occupational hazards, and different sizes of enterprises.

RESULTSA total of 1274 monitoring sites from these specially supervised enterprises were included, of which qualification rate was 73.55% (937/1274), and the noise monitoring sites showed the lowest qualification rate. The overall qualification rate in 2012 (70.37%) was significantly lower than that in 2011 (80.94%) (χ(2) = 15.38, P < 0.01). In electronics industry, the qualification rate in 2012 was significantly lower than that in 2011 (χ2 = 11.27, P = 0.001). Comparison of various hazards in different industries indicated that electronic enterprises and furniture enterprises had the lowest qualification rate in noise monitoring, printing enterprises had the lowest qualification rate in organic solvent monitoring, and furniture enterprises had the lowest qualification rate in dust monitoring. Comparison between different sizes of enterprises indicated that the qualification rate of large and medium enterprises in 2012 was significantly lower than that in 2011, while the qualification rate of small enterprises in 2012 was significantly higher than that in 2011 (P < 0.01 or P < 0.05).

CONCLUSIONIn the prevention and control of occupational hazards in specially supervised enterprises, special attention should be paid to the control of organic solvents in printing enterprises and noise and dust in furniture enterprises.

Air Pollutants, Occupational ; China ; Dust ; Industry ; statistics & numerical data ; Noise, Occupational ; Occupational Exposure ; statistics & numerical data ; Occupational Health ; statistics & numerical data ; Solvents

Air Pollutants, Occupational ; analysis ; Female ; Hexanes ; analysis ; poisoning ; Humans ; Male ; Occupational Exposure ; statistics & numerical data ; Shoes

Humans ; Occupational Exposure ; statistics & numerical data ; Occupational Health ; Physical Examination ; Surveys and Questionnaires

Dust ; Humans ; Iron ; Mining ; Noise, Occupational ; Occupational Exposure ; statistics & numerical data ; Vibration

OBJECTIVETo provide data for the occupational health supervision by analyzing the occupational health status in manufacturing industry in Guangzhou, China.

METHODSThe occupational health investigation was performed in 280 enterprises randomly selected from 8 industries based on industry stratification. According to the occupational health standards, 198 out of the 280 enterprises were supervised and monitored. Sample testing was performed in 3~5 workplaces where workers were exposed to the highest concentration/intensity of occupational hazard for the longest time. Comparative analyses of the overproof rates of hazard were performed among enterprises, workplaces, and testing items from different industries.

RESULTSThe concentrations of occupational hazard in 42.93% (85/198) of enterprises and 22.96% (200/871) of workplaces were above the limit concentration. The most severe hazards were the noises in shipbuilding and wooden furniture industries and the welding fumes in shipbuilding industry. Less than 30% of enterprises were able to provide occupational health examination and periodic test reports of occupational hazard in workplaces. The rate of the workers with abnormal occupational health examination results and the need for reexamination reached 6.63% (832/12 549), and they were mostly from shipbuilding, wooden furniture, and chemical industries.

CONCLUSIONThe occupational health supervision should be strengthened in enterprises, and hazard from noises and dusts should be selectively controlled or reduced. The publication of relevant data and information of occupational health in enterprises should be promoted to enhance social supervision.

Chemical Industry ; China ; Dust ; Humans ; Interior Design and Furnishings ; Manufacturing Industry ; statistics & numerical data ; Noise, Occupational ; Occupational Exposure ; statistics & numerical data ; Occupational Health ; statistics & numerical data ; Welding ; Workplace