Weighing and modelling factors influencing serum cortisol and melatonin concentration among workers that are exposed to various sound pressure levels using neural network algorithm: An empirical study

Abstract

Background Noise is one of the most common harmful agents in the workplace. Exposure to excessive noise can lead to complications such as cardiovascular disorders, disturbance of body hormones’ rhythm and hearing loss. This study aimed at weighing and modelling factors influencing serum cortisol and melatonin concentrations of workers that are exposed to various sound pressure levels using neural network algorithm. Methodology A case-control design was adopted in the current research. The required data were collected from 75 industrial and mining firm staff members. They were assigned to three groups with equal sample sizes (25 workers). In developing the conceptual model in regard to variables that may affect workers’ serum cortisol and melatonin concentration, SPL, age, weight, and height were included. The influence of SPL on serum cortisol concentration as assessed in the three shifts. Moreover, radioimmunoassay (RIA) was utilized to assess serum cortisol and melatonin concentrations. Neural network algorithm was subsequently exploited to weigh and model predictor factors. IBM SPSS Modeler 18.0 was the software program used for data analysis. Results The average cortisol concentration values for administrative, condensing, and pelletizing units respectively were 10.24 ± 2.35, 12.15 ± 3.46, and 14.91 ± 4.16 . On the other hand, the average melatonin concentration values for administrative, condensing, and pelletizing units respectively were 37 ± 12.52, 34 ± 13.15, and 27 ± 9.54 . According to the results of the developed model for cortisol, SPL3 (32%) and age (5%) respectively had the highest and lowest impact. On the other hand, considering the model developed for melatonin, height (27%) and SPL1 (10%) were the most and least influential factors in that order. The accuracy rates of the model were also found to be 95% for cortisol and 97% for melatonin. Conclusion Comparing cortisol concentrations during various shifts revealed a significant reduction (from the beginning to the end of the shift) in all the three groups. Further, the rise of SPL would result in higher secretion of cortisol. Moreover, in all the three groups, the average serum melatonin concentration went up from the beginning to the middle of the shift and then declined to the end of the shift. Considering the accuracy rates of the models developed to predict hormones, neural network algorithm is a suitable and powerful tool for weighing and modelling factors influencing serum cortisol and melatonin concentrations.

The association between circadian rhythm of cortisol and shift work regularity among midwives—A multicenter study in Southeast China

“…According to the latest research findings, cortisol, as a health biomarker of circadian rhythm, has been extensively investigated ( 11 ).…”

“…The cortisol release is typically in line with circadian rhythm, which is believed to grow within the first hour after waking up and reach its pinnacle around 30–45 min after waking up. It gradually dwindles during the day and falls to the minimum at mid-night ( 11 , 12 ). Such circadian rhythm was verified through the logarithmic distribution of the 86 midwives' cortisol for two consecutive days in our study.…”

Acoustic characteristics of bedrooms in two types of long-term care facilities in China

“…It is commonly acknowledged that everyday exposure to excessive noise can negatively affect both physical and mental health [ [1] , [2] , [3] , [4] , [5] , [6] , [7] ]. Elderly people are more sensitive to their surroundings than are healthy adults; thus, noise can profoundly impact their sleep, emotional state, and physiological indicators [ [8] , [9] , [10] , [11] , [12] , [13] ].…”