Variation in Eurostat and national statistics of accidents in agriculture
¹Estonian University of Life Sciences, Fr.R. Kreutzwaldi 56/1, EE51006 Tartu, Estonia
²Natural Resources Institute Finland (Luke), Latokartanonkaari 9, FI-00790 Helsinki
³Leibniz Institute for Agricultural Engineering and Bioeconomy, Max-Eyth-Allee 100, DE14469 Potsdam, Germany
⁴University of Nebraska Medical Center, Omaha, Nebraska, US68198-4388, USA
Agriculture is known as a hazardous industry worldwide, although there are great challenges in enumerating the size of the workforce and numbers of accidents at work. The aim of the study was to characterize variation in agricultural accident statistics in European countries and opportunities to improve collection and reporting of accident data in agriculture on the national and European levels. This study explored the incidence of fatal (FA) and non-fatal work accidents (NFA) in agriculture (excluding forestry and fishing) in selected European countries, using Eurostat and national sources in 2013. Eurostat reported highest NFA rates (per 100,000 workers) in Finland (5331) and lowest in Greece (5). The highest FA rate was reported in Malta (51), while zero fatalities were reported in Estonia, Greece, Luxembourg, Slovenia, Sweden and Iceland. Eurostat and national statistics differed in many cases. Some variations were observed in European and national statistics. Germany reported 89 fatalities (rate 2.3/100,000) in Eurostat and 160 (rate 16.3/100,000) in national sources. Poland, with a similar land area and five times more farms and workers as Germany, reported only 4 fatalities in agriculture in Eurostat. The Estonian Labour Inspectorate (2013) registered 785 NFAs per 100,000 agricultural workers, while the rate in Eurostat was more than twice as high (1914/100,000). Finland and Sweden with similar agricultural structures had a ten-fold difference in NFA rates in Eurostat; Finland 5,331 and Sweden 554 per 100,000 workers. These examples illustrate the large variation in agricultural accident statistics due to: a) farm structure, b) use of reference populations, c) under-reporting, d) different inclusion/exclusion criteria and e) interpretation by users. Some inconsistencies are structural due to lacking social insurance schemes for farmers, family labour and undocumented workers. Some inconsistencies could be addressed by better implementation of ESAW harmonizing rules. Alternative methods, such as standardized surveys, could be considered to augment Eurostat statistics.