Workplace environment of earth-moving machine operators in terms of anthropometric data development in the Slovak republic.

BACKGROUND: Population data are gathered using the sampling unit at the appropriate time and due to various reasons (e.g. nutrition survey of the population, style of living, etc.), they can be changed due to trends for longer periods of time. OBJECTIVE: The aim of the paper is to analyse selected anthropometric parameters relevant to the design of the earth-moving machine operator workplace environment and to compare the gathered data to the standard ISO 3411. METHODS: The set of five dimensions and factors of the Slovak adult male population was analysed over the course of the years 2002-2018. RESULTS: A significant increase in the parameter -body weight was observed. In total, mentioned dimension of male population increased by 0.4 kg (0.5%) during the time of analysis. Following the dot plot and linear regression equation the fact that the trend in growth is becoming a global phenomenon in Slovakia can be stated. CONCLUSIONS: In the future, it will be necessary to focus on updating the standards defining the workplace size in this industry sector as well as in others.

Trends in Workplace Injuries in Slovak Forest Enterprises.

The aim of the paper is to analyse the effect of key factors affecting the risk of workplace injuries and to identify the most common workplace accidents regarding injured body parts with respect to anthropometric data measurements of the population. Data associated with workplace accidents over the years 2000⁻2016 were drawn from the records of the state enterprise Forests of the Slovak Republic, situated in Banská Bystrica. Gathered data were processed and entered into the database complemented by the data on accidents of the self-employed working in the forestry industry. A total of 1874 workplace accidents in the state enterprise were recorded and statistically evaluated during the analysis period. A method for contingency table was used to analyse correlation between qualitative (categorical) variables in the dataset. A Poisson regression model was used to determine the injury rate. Forest harvesting is considered the most risky phase of the process of harvesting, processing, and transport. The highest number of workplace accidents (31.8% of all recorded workplace accidents) occurred during the forest harvesting phase during the analysis period. Timber skidding, with 16% of recorded accidents, was the second highest-risk phase. The workplace injury rate in the forest industry in Slovakia decreased over the course of the years 2000⁻2016. Head and facial injuries were those with the highest rate (67.1% injuries of these body parts) during the phase of harvesting and skidding.