The effects of occupational noise on blood pressure and heart rate of workers in an automotive parts industry

Abstract

BACKGROUND: One of the most important impacts of industrial noise is physiological and psychological effects. The increases in workers’ blood pressure and heart rate were detected during and after exposure to high levels of noise. The objectives of this research were to determine whether the noise exposures have any effects on blood pressure and heart rate of workers in the automotive parts industry.

METHODS: This case study was done in 2011 at different units of an automotive parts manufacturing in Tehran. Sound pressure level was measured at different units of the factory with a calibrated instrument. Demographic features of workers were gathered with an appropriate questionnaire. Heart rate and blood pressure were measured twice in a day in the start time of work day (before exposure to noise) and middle shift hours (during exposure to noise) in the occupational physician office. For analyzing data, chi-square, independent sample t-test, paired t-test, and analysis of covariance (ANCOVA) were used. P < 0.050 was considered statistically significant.

RESULTS: The average age of workers in the case and control groups was 35.71 ± 8.10 and
33.40 ± 10.41 years, respectively. There was no difference between the average age of case and control groups (P = 0.436). The results of ANCOVA revealed the significant differences between the mean changes of heart rate F _{(1, 37)} = 26.68, P < 0.001, systolic blood pressure
F _{(1, 37)} = 21.70, P < 0.001, and diastolic blood pressure F _{(1, 37)} = 26.20, P < 0.001 of workers in the case and control groups.

CONCLUSION: Exposure to industrial noise may increase the heart rate of workers. Although rises in heart rate, systolic, and diastolic blood pressure of workers in the case group were observed after exposure to noise, the values of heart rate, systolic, and diastolic blood pressure were in the normal range. Further experimental investigations are needed to determine the relationships between these variables.