Occupational health and safety of Finnish dairy farmers using automatic milking system

Introduction: Conventional pipeline and parlor milking expose dairy farmers and workers to adverse health outcomes. In recent years, automatic milking system (AMS) has gained much popularity in Finland, but the changes in working conditions when changing to AMS are not well-known. The aim of this study was to investigate the occupational health and safety risks in using AMS, compared to conventional milking systems (CMS). Methods: An anonymous online survey was sent to each Finnish dairy farm with an AMS in 2014. Only those dairy farmers with prior work experience in CMS were included in the final analysis consisting of descriptive statistics and frequency distributions. Results: We received 228 usable responses (131 male and 97 female; 25.2% response rate). The majority of the participants found that AMS had brought flexibility to the organization of farm work, and it had increased leisure time, quality of life, productivity of dairy work, and the attractiveness of dairy farming among the younger generation. In addition, AMS reduced the perceived physical strain on the musculoskeletal system as well as the risk of occupational injuries and diseases, compared to CMS. However, working in close proximity to the cattle, particularly training of heifers to use the AMS, was regarded as a high-risk work task. In addition, the daily cleaning of the AMS and manual handling of rejected milk were regarded as physically demanding. The majority of the participants stated that mental stress caused by the monotonous, repetitive, paced, and hurried work had declined after changing to AMS. However, some indicated increased mental stress because of the demanding management of the AMS. In addition, nightly alarms caused by the AMS, lack of adequately skilled hired labor or farm relief workers, and taking care of the 24/7 standby for the AMS caused mental stress. Conclusions: Based on this study, AMS may have significant potential in the prevention of adverse health outcomes in milking of dairy cows. In addition, AMS may improve the productivity of dairy work and sustainability of dairy production. However, certain characteristics of the AMS require further attention with regard to occupational health and safety risks

Quantitative characterization of clumping in Scots pine crowns

Peer reviewe

Safety and animal handling practices among women dairy operators

v2011o

Protecting cattle feedyard workers in the Central States region: Exploring state, regional, and national data on fatal and nonfatal injuries in agriculture and the beef production sector

Working in agriculture can be dangerous. Despite ongoing efforts of Extension, animal production worker safety has not been adequately addressed. We present state, regional, and national counts and rates on fatal and nonfatal injuries in agriculture and animal production using publicly available data from the Bureau of Labor Statistics. We found that animal production had a high number of fatal injuries and a higher rate of nonfatal injuries than the average within agriculture. More needs to be done to protect livestock workers from injury. Extension professionals can play a key role in increasing safety knowledge and changing behaviors

Comparison of Agricultural Injury and Fatality Characteristics Obtained from Media Monitoring Versus Official Statistics

Objective of project: 1. Compare the characteristics of fatal injuries reported by CFOI and CS-CASH media monitoring 2. Analyze the agreement between CFOI reported injuries and CS-CASH media monitoring fatal injuries Planning/Research Method: Background: The Bureau of Labor Statistics, Census of Fatal Occupational Injuries (CFOI) provides statistics on occupational fatalities, but information on individual cases is not reported. The Central States Center for Agricultural Safety and Health (CS-CASH) tracks media reports of agricultural injury and fatality cases to augment CFOI data. Methods: Data was obtained from variety of sources. The primary data source was Google Alerts and other sources includes press clippings and local media reports. The key words used for selecting relevant articles were “farm accident”, “farm incident”, “farm death”, “ranch accident”, “ranch death” and “livestock. All agricultural related incidents occurring in Nebraska, Iowa, Minnesota, South Dakota, North Dakota, Missouri and Kansas between 2012-June 2016 were selected for analysis. Data was obtained from CFOI database for different type of injury events and compared to those obtained from different media sources using 2 independent t test. An association between fatalities or farm injuries and other characteristics was determined in a using a Pearson Chi square and a multivariate analysis using a multiple logistic regression model. Results: We found significant differences in CS-CASH media monitoring data between fatal and non-fatal injuries. Google alerts included a higher proportion of roadway incidents, …, …, and … compared to data from press clips from print media. CFOI data included a higher proportion of …, …., and … fatalities compared to data from CS-CASH media monitoring.We found significant differences in CS-CASH media monitoring data between fatal and non-fatal injuries (p\u3c0.0001). CFOI data included a higher proportion of injuries from struck, contact and fall when compared to CS-CASH media monitoring data. However, there is no significant difference between the CFOI data and the CS-CASH media monitoring of fatal injury data for “caught” (p=0.094) Conclusion: This study suggests an agreement between CFOI data and media monitoring data for fatal injury events due to being caught in running equipment.https://digitalcommons.unmc.edu/coph_pres/1002/thumbnail.jp

Factors Associated with Fatalities in Production Agriculture

Background: Studying the work environment and demographics of agricultural workers involved in fatal incidents can provide valuable information on the cause of fatalities and lead to better prevention measures. Objectives: To determine populations at risk of fatalities and the determinants of fatalities in production agriculture. Method: Agricultural injury and fatality data were obtained from Press clippings and Google alerts covering seven Midwest States (SD, ND, MN, IA, NE, KS and MO). Google Alerts were collected based on key words including: “farm accident”, “farm incident”, “farm death”, “ranch accident”, ”ranch incident”, “ranch death”, “ATV farm death”, “ATV ranch death”, “livestock death”, as well as other descriptors. Articles from Google Alerts were screened. Relevant articles were analyzed, and data were then extracted and added to the database. Differences in demographic and characteristics between fatal and non-fatal injuries were compared within the CS-CASH media monitoring database using the chi-square and logistic regression model. Results: A total of 1048 agricultural-related injuries including 586(56%) non-fatal cases and 462 (54.16%) fatalities were collected between 2011 to 2017 across the seven Midwest states by CSCASH monitoring database. We found that fatality was significantly associated with; age group (p\u3c0.0001), type of injury event (p\u3c0.0001), source of injury (p=0.01), time of injury (p=0.0018), activities during injury (p=0.0002), place of injury (p\u3c0.0001) and gender (p=0.0004) in a univariate analysis. It was further discovered in a multiple logistic regression that age groups, time and the place of injury were good predictors of fatalities. Conclusion: This study suggests that place of injury, time of injury and age of the victims were possible determinants of fatalities and males, elderly and the infants had more fatalities in agricultural production industry.https://digitalcommons.unmc.edu/coph_pres/1004/thumbnail.jp

Maatalouskoneiden työturvallisuusriskit ja niiden hallinta

201

Maatalouskoneiden työturvallisuusriskit ja niiden hallinta

201

Occupational injuries and diseases among commercial fishers in Finland 1996-2015

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