A Model to Determine the Level of Serum Aldosterone in the Workers Attributed to the Combined Effects of Sound Pressure Level, Exposure Time and Serum Potassium Level: A Field-Based Study

Occupational exposure to excessive noise is one of the biggest work-related challenges in the world. This phenomenon causes the release of stress-related hormones, which in turn, negatively affects cardiovascular risk factors.
The current study study aimed to determine the level of workers’ serum aldosterone in light of the combined effect of sound pressure level, exposure time and serum potassium level.
This cross-sectional, descriptive, analytical study was conducted on 45 workers of Gol-Gohar Mining and Industrial Company in the fall of 2014. The subjects were divided into three groups (one control and two case groups), each including 15 workers. Participants in the control group were selected from workers with administrative jobs (exposure to the background noise). On the other hand, participants in the case groups were selected from the concentrator and pelletizing factories exposed to excessive noise. Serum aldosterone and potassium levels of participants were assessed at three different time intervals: at the beginning of the shift and before exposure to noise (7:30 - 8:00 AM), during exposure to noise (10:00 - 10:30 AM), and during continuous exposure (1:30 - 2:00 PM). The obtained data were transferred into SPSS ver. 18. Repeated measures analysis of variance (ANOVA) was used to develop the statistical model of workers’ aldosterone level in light of the combined effect of sound pressure level, exposure time, and serum potassium level.
The results of the final statistical model to determine the level of serum aldosterone based on the combined effect of sound pressure level, exposure time and serum potassium level indicated that the sound pressure level had a significant influence on the human’s serum aldosterone level (P = 0.04). In addition, the effects of exposure time and serum potassium on aldosterone level were statistically significant with P-values of 0.008 and 0.001, respectively.
The obtained model in the study revealed that the results of predictive models to determine aldosterone level were very similar to real values; therefore, the obtained values of this model were largely in line with the ones obtained from the field.