Tag Archives: accident

1969–1983 E. Merisalu J. Leppälä, M. Jakob and R.H. Rautiainen
Variation in Eurostat and national statistics of accidents in agriculture
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Variation in Eurostat and national statistics of accidents in agriculture

E. Merisalu¹* J. Leppälä², M. Jakob³ and R.H. Rautiainen²⁴

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
*Correspondence: eda.merisalu@emu.ee

Abstract:

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.

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1953–1959 J. McNamara, P. Griffin, J. Phelan, W.E. Field and J. Kinsella
Farm health and safety adoption through engineering and behaviour change
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Farm health and safety adoption through engineering and behaviour change

J. McNamara¹²*, P. Griffin³, J. Phelan², W.E. Field⁴ and J. Kinsella²

¹Teagasc- Agriculture and Food Development Authority, E32YW08 Kildalton, Co. Kilkenny, Ireland
²School of Agriculture and Food Science, University College Dublin, D04 V1W8 Dublin 4, Ireland
³Health and Safety Authority, Metropolitan Building, D01 K0Y8 Dublin 1, Ireland
⁴University, Agricultural & Biological Engineering Department, IN 47907-2093 West Lafayette, Indiana, U.S.A.
*Correspondence: john.g.mcnamara@teagasc.ie

Abstract:

The agriculture sector is one of the most hazardous occupations worldwide. The EU farming population is predominantly self-employed, who are largely outside the scope of EU occupational safety and health (OSH) legislation. Utilising effective communications approaches to transmit clear messages is a possible way of motivating farmer OSH adoption. The Public Health Model (PHM) of accident causation conceptualises an accident as occurring due to multiple interacting physical and human factors while the Social-Ecologic Framework enhances the PHM by defining various levels of the social environment which are influential on persons’ OSH actions. A knowledge gap exists in how farmers conceptualise accident causation. The aim of this study is to report findings of a Score Card exercise conducted among Irish farmers (n = 1,151) to reveal knowledge on farmers’ conceptualisation of accident causation where farmers ranked in order of importance up to five causes of farm accidents. First ranked items related to ‘machinery/ vehicles’, ‘organisational’ and ‘livestock’ as accident causation factors (92%). Overall rankings for up to five ranked causes identified six causes: ‘machinery/ vehicles’, ‘organisational’, ‘livestock’, ‘slurry related’, ‘trips, falls, buildings-related’ and ‘electrical’ (96.5%). The study data indicated that farmers’ perceptions of accident causes were inaccurate when compared with objective fatal farm accident data. The study concluded that communicating accurate and contemporary OSH messages to farmers has potential to assist with farm accident prevention. Based on the multiple and interacting risk factors arising in agriculture it is suggested that more elaborate study of farm accident prevention is warranted.

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