Despite the fact that the production factors of industrial enterprises regarding the microclimate, noise, vibration, dust, and more, have a complex effect on the workforce, the effects of their mutual summation or potentiation are still not well understood. The issues related to studying the nature, origin, and intensity of impact regarding the individual production factors and their combinations against the background of the bodily neuro-emotional tension are covered poorly in the literature also. This lack of information makes it difficult to develop scientifically based recommendations for forecasting and reducing the intensity of adverse factors within the working environment, which confirms the thematic novelty of this study (1). The proposed methodological approach to monitor working conditions allows the individually tailored calculation of the functional stress level in the workers’ body with regard to working conditions, profession, age, and length of service.
In order to carry out preventive measures at industrial enterprises at the National Academy of Mining Sciences, Nur-Sultan/Kazakhstan, criteria have been calculated to identify risk groups and predicting the loss of working capacity in the context of actual production activities. This approach allows us to assess and predict the functional stress of workers depending on age, length of service, profession, personal characteristics, as well as an assessment of the level of adverse influence of factors of the production environment on the body. Therefore, it is feasible for conducting preventive medical examinations and prenosological diagnostics.
Accordingly, we developed methodological recommendations, introduced these into the production industry, and included them in the course of lectures at medical education institutions.
Impact assessment of production factors on the worker´s health and performance at mining-metallurgical enterprises
The identification of impact factors arising within the working environment that create psycho-emotional stress for a person and the development of criteria to assess and predict the nervous-emotional stress of the body itself is an urgent task of occupational health (2). The activities of workers at metallurgical enterprises is characterized by a whole complex of harmful production factors, the most significant of which are: heating microclimate, noise, dust, chemical factors, increased nervous and emotional stress, requiring constant attention, speed and accuracy of reactions, and heavy load of sensory systems. Undoubtedly, that affects the functional state of the worker’s body and morbidity cases with temporary disability (MTD).
A factorial disperse analysis showed that the studied indicators reflecting the health state deteriorated not only with an increasing age, but also with the professional experience. Thus, in 30 years old worker’s compensatory links consistently linked almost all the studied functional features, and the correlation coefficient between them exceeded 0.6, which indicated significant system tension. Further, these phenomena are typical for workers with and experience of up to five years and regardless of age, indicating a low adaptation of the body to working conditions. In the group of workers 30 to 39 years old, the optimization of the physiological system and adaptability was noted, indicating adaptation to working conditions, which is formed after ten to 14 years of work experience.
In summer workers between the age of 40 to 49 years and with an experience of 15 to 19 years, a decrease in the regulation of the body functions was observed regarding the actualization and lability of the cardiovascular system (CS), neuromuscular activity (NA), and the central nervous system (CNS). Furthermore, an increase in the physiological state index (PhSI) and the work ability index (WAI) indicates a decrease in the adaptive potential of individual functions.
This necessitates the formation of a certain set of so-called limiting links, which allow clear correlation measures to ensure the stability of the whole system at the stage of adaptive function realignments to achieve the proper functional level. In workers 50 years old and older, who display a work experience of 20 to 25 years, the cumulation peak of all mentioned phenomena is characterized by the development of a poor adaptation, which is in turn manifested in various diseases. In these cases, the circulatory system is impacted first, which forces workers to leave the professional cohort voluntarily or involuntarily due to disability.
Thus, the age-seniority categories of the surveyed workers all repeat a set of compensatory connections formed at the age of 30 years, 30 to 39 years, 40 to 49 years, and 50 and more years indicating the existence of a uniform regulatory mechanism that provides a steadily function of an organism as a biological system. At the same time, the low level and premature decrease in efficiency as well as the functional depletion to adapt to the effects of a complex set of harmful factors at the working environment significantly reduce the professional suitability of workers in the system “man – production factors – health”. However, a more accurate description and categorization is only possible by analyzing the morbidity by correlating the length of service and age.
Moreover, when analyzing the dynamics of the indicators by occupational groups, the highest values were obtained for workers engaged directly in the production process and thus in contact with the whole complex set of production factors and, as a result, receiving a “full load” on their body. Here, it should be noted that auxiliary workers do not fully experience the full range of harmful factors, because their work only encompasses repairs when the production equipment either stands still or does not function fully. In accordance with official duties, engineering and technical workers are also not always faced with harmful production factors. In the structure of morbidity in all workshops leading place is occupied by respiratory diseases (ORD), in second place indicators of diseases of the musculoskeletal system, in third place injury, in fourth place diseases of the digestive system.
Among men and women across all areas, the leading disease is of respiratory nature again followed by impacts on the musculoskeletal system. Then, injuries are third among men and digestive abnormalities among women. In fourth place, cardiovascular diseases are present in both men and women, followed by digestive diseases in men.
To assess the impact on the morbidity of the complex set of production factors, a Spearman rank correlation analysis was performed. In doing so, the obtained values of the correlation coefficient in the interval from 0 to 1 (-1), in accordance with method N. Dogle were consistent with the presence of a direct (inverse) relationship in which an increase in one trait leads to an increase (decrease) in another (3).
As you know, the correlation degree is measured by the binding force, which can be high, medium, and low depending on the correlation coefficient value. According to the data obtained, the strength of the relationship, e. g., between the “age” factor, “experience”, “occupational group”, and “sick persons” was labeled “strong”, whereas with “cases of morbidity” the strength of the relationship was “average” (Table 1).
Thus, the health level analysis of workers at the metallurgical enterprise showed that harmful factors of the working environment negatively affect their health, which is reflected in the high morbidity values with temporary disability (TD), both in cases and on days of disability. At the same time and in accordance with the classification, their values correspond to a high-level classification. In addition, this is confirmed by the percentage of sick people, which also corresponds to the high level. To assess the impact of a set of production factors on morbidity, it is usually necessary to further establish the nature and extent of the relationship between the factors. Moreover, changing the value of one indicator leads to a subsequent change of another value. To solve this problem, the correlation analysis method was used.
One of the leading events in the practice of hygienic, physiological, and pathophysiological studies is the problem of identifying the relationship between the factors, the search for suitable methods to obtain results that enable the evaluation of one factor despite and in correlation with other, also possibly changing factors. In this regard, the correlation analysis method is the key to answer how the different and separately measurable features or traits of the body are dependent or independent of one another, and whether it is possible to draw a conclusion about one trait based on properties found for other traits (3).
Concluding this study, a mathematical prognostic model for the morbidity level was developed to establish quantitative relationships between the hygienic parameters of the factors regarding the working environment and the morbidity level. As the level of morbidity is influenced not only by working conditions, work experience, thus quantitative values, but also by intangible and qualitative factors such as social and living conditions, education level, marital status, etc. Their individual and overall impact is difficult to calculate. Further, and in different situations, the degree of their influence is not the same, and their changes in dynamics are random. All this makes it difficult to quantify the relationship between the production factors of the environment and the level of morbidity. Therefore, whenever the correlation and regression analysis method were not feasible for its application or resulted in extremely inefficient and only approximate values in comparison, the regular intensive indicators (RII) method was chosen. Here, the following formula was developed to assess the impact of a set of factors at the working environment and social factors on the health level or the calculation of the disability risk (3).
Risk = Ra x K1 + Re x K2 + Rw x K3 + Rg x K4 (Equation 1)
with R = regulatory intensive indicator of the incidence by
a = age;
e = experience;
w = work profession;
g = gender; and
K (1,2,3,4) = weight coefficients.
To assess the disability risk, it is necessary to have an idea of the range of possible fluctuations in risk indicators for persons working in this production workplace first. By summarizing the product of the weight coefficients on the RII (Table 2) having the lowest values for each of the factors, we obtained the minimum risk of loss Rmin, when adding up the maximum values of each factor we obtain the according maximum risk of loss Rmax (4).
The difference between these risks (Rmax – Rmin) represents the entire fluctuation range within which all the values of the integrated risk assessment for people working in this workshop are located. When taking the range of fluctuations in complex estimates and their nature into account, it is possible to distribute all workers in one shop to the following groups: with a favorable forecast, needing attention, and displaying an unfavorable risk of losing performance, i. e. adverse prognosis (5).
Using data from table 2 and equation 1, the risk of loss for workers on the floor in workshop 1 was calculated with K1=1,39; K2=1,83; K3=2,09; K4=1,07 as weight coefficients of the incidence by age, experience, work profession, and gender.
Risk (workshop 1) = 1,39 x Ra + 1,83 x Re + 2,09 x Rw + 1,07 x Rg
- Example 1 – Worker of workshop 1:
L. M. As-va
Age: 29; experience: 4 years; work profession: fueler; gender: female.
Using data from table 2 for Ra = 1,024; Re = 0,984; Rw = 1,082; Rg = 1,131, the risk of loss in efficiency on the example of worker workshop 1 L. M. As-va amounts to:
Risk (L. M. As-va) = 1,39 x 1,024+1,83 x 0,984+2,09 x 1,082+1,07 x 1,131 = 6,62
Conclusion: According to table 3 worker L. M. As-va belongs to the group with an adverse prognosis.
- Example 2 – Worker of workshop 1:
H. A. Mos-v
Age: 45; experience: 12 years; work profession: mechanic; gender: male
Risk (H. A. Mos-v) = 1,397 x 0,905+1,83 x 1,182+2,09 x 0,96+1,07 x 0,988 = 6,69
Conclusion: H. A. Mos-v belongs to the group with an adverse prognosis.
- Example 3 – Worker of workshop 1:
A. I. Sha-n
Age: 52; experience: 25 years; work profession: engineer; gender: male.
Risk (A. I. Sha-n) = 1,397 x 0,820+1,83 x 0,791+ 2,09 x 0,518+1,07 x 0,988 = 4,73
Conclusion: A. I. Sha-n belongs to the group with a favorable prognosis.
The obtained equations and quantitative criteria of the risk of loss and thus disability allow to simplify the procedure of a complex integrated assessment and risk prediction. At the same time, it can assess the degree of adverse effects of harmful factors of production and labor process indirectly to enable the development and implementation of a set of preventive measures (6).
- Occupational and production factors affect performance and determine the dynamics of long-term forecasts of the risk of disability.
- Changes in age and length of service lead to a limitation of the range regarding functional capabilities of the body and deterioration of health indicators, as well as stimulate timely prevention, diagnostic, treatment, and rehabilitation measures.
- Multivariate analysis made it possible to develop a mathematical model to assess and predict the functional stress of the body.
Quantitative criteria regarding age and length of service have been developed to identify risk groups and assess the work capacity loss in relation to the individual profession and assignments. The low level of functional system adaptations reserves to the impact of a range of harmful work environment factors reduces occupational fitness in the system “man – work-related factors – health”. The proposed criteria for risk and functional tension allow a procedure simplification when diagnosing the health conditions of by-product-coking industry workers.
For the first time, a comprehensive assessment of the functional state of by-product-coking industry workers in the specific conditions of their workplace has been achieved successfully. New data were obtained on the tension of functional systems and adaptive capabilities of by-product-coking industry workers as well as on the efficiency level of their work ability in relation to age, experience, work profession and gender. The use of a multi-factor regression model to assess the workers’ morbidity risk and range allows the development of health-improving, medico-ecological, and hygienic measures as well as a comprehensive health status monitoring.
The model is feasible to conduct periodic medical examinations and developing preventive measures.
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(2) Izmerov, N. F.; Denisov, E. I.: Occupational health risk for workers (Guide). M.: 2003. 448 pp.
(3) Dogle, N. V.; Yurkevich, A. Y.: Morbidity with temporary disability. M.: 1984. 176 pp.
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(5) Alpysbayeva, Z. T.: Mathematical analysis of the influence of unfavorable factors of by-product coke production on the morbidity of workers. In: N. K. Smagulov, Z .T. Alpysbayeva // Bulletin of Science of the Kazakh Agrotechnical University named after S. S. Seifullina, 2009, No. 3, pp 137-143.
(6) Alpysbayeva, Z. T.: Comprehensive assessment of the impact of working conditions on the health indicators of workers of coke-chemical production. In: N. K. Smagulov, Z. T. Alpysbayeva, A. Zeinullina // Modern technologies in preventive and clinical medicine: Materials of an interuniversity scientific conference with international participation. 4th May 2010, MMSU, Moscow, pp 118-122.