Injury risk factors to farm and ranch operators in the Central United States

Profile and risk factors in farmer injuries: a review based on Haddon matrix and 5 E's risk reduction strategy

Farmers are considered a high-risk group for intentional and unintentional injuries. This review identified significant risk factors for agricultural injuries in farmers and explored injury prevention countermeasures based on the literature. Therefore, CiteSpace software was used to analyze the relevant literature in this field. Additionally, we identified both key risk factors and countermeasures using the Haddon matrix and the 5 E's risk reduction strategies conceptual framework, respectively. The risk factors were identified from four categories (host, agent, physical environment, and social environment) corresponding to three phases (pre-event, event, and post-event). Interventions of 5 E's risk reduction strategies including education, engineering, enforcement, economic, and emergency response have been proven effective in preventing injuries or reducing their severity. Our findings provide a comprehensive foundation and research direction for the study and prevention of injuries among farmers.

Using Partnerships and Multiple Data Sources to Surveil Agricultural Injuries: Considerations and Recommendations

This article describes an interprofessional collaboration between Sanford Health and North Dakota State University that strengthens agricultural injury surveillance in the upper Midwest by using multiple sources of health data and geographic information systems (GIS) technology. We provide methodological insights and considerations for using and combining facility-level trauma registry (FLTR) data, national data sets, and GIS to identify areas with disproportionate agricultural injury prevalence. Additionally, we discuss the benefits of FLTR data, how and why it is collected, the data it contains, and how it can be combined with national datasets to fill-in surveillance gaps. Lastly, we offer recommendations for building cross-institutional and interprofessional partnerships.

Tractor Injuries in the Upper Midwestern United States: a retrospective analysis of four trauma centers

OBJECTIVES

The purpose of the present study was to characterize the incidence, injury characteristics, and outcomes of patients presented to four trauma facilities located in the upper Midwest with tractor-related agricultural injuries.

METHODS

We performed a retrospective review of the facility level trauma registries of four trauma centers located in North Dakota, South Dakota, and Minnesota between January 1, 2010 and December 31, 2021. We characterized the incidence, severity and outcomes of traumatic tractor-related agricultural injuries for pediatric and adult patients. We described the nature of these injuries by severity, anatomical site, type, age, sex, and length of stay (LoS). Injury severity was evaluated using Injury Severity Score (ISS) and Abbreviated Injury Scale (AIS).

RESULTS

Findings indicated that farmers aged 65 and older experience polytraumatic, severe tractor-related agricultural injuries and fatalities. Of the 177 tractor patients analyzed, 40 patients were between the ages of 65 and 74 years and 45 patients were 75 and over. Male farmers aged 65 and older are injured year-round, many are discharged to skilled nursing facilities for additional care, are spending more time in the hospital, and have the highest rate of critical injuries out of all age groups. Moreover, the patients who died as a result of tractor-related agricultural injuries were men over 65 years. The most common tractor-related agricultural injuries include falls from tractors (n = 53), struck by object falling/propelled from tractor (n = 25), rollovers (n = 26), and runovers (n = 24). Falls from tractors accounted for 33% of all tractor-related upper extremity fractures, 36% of head injuries and 29% of chest injuries.

CONCLUSION

The findings from this study indicate that tractor-related agricultural injuries represent a significant problem in the upper Midwest. Older, male farm workers experience a higher incidence of tractor-related agricultural injuries, and all tractor-related fatalities occurred in individuals 65 years of age and older. These results underscore the need for further investigation into aging-related farm safety issues.

Recruitment of Row Crop Farmers into a Research Study to Assess Farm Hazards

Farmers are at an elevated risk for injuries and are, therefore, highly sought after for research studies. However, their participation in research studies is low. We examine how characteristics of the farmer, farm location, and timing of recruitment contact impact the probability that farmers will engage and participate in a study of injuries and related farm hazards. Study data were obtained from the Farm Safety Study conducted at the University of Iowa between June 2019 and March 2020. We used recruitment data from participants enrolled using Farm Journal magazine subscription lists. Multinomial logistic regression was used for predictive modeling. Predictor variables included the time of day and the farm season in which phone contact for study recruitment was attempted, as well as the rurality of the farm. Two models were created to characterize screening and participation of farmers in the study. Farm season and time of day of the last recruitment call increased the likelihood of farmers being screened for study participation and completing the study. Specifically, contacting farmers during the growing season and during the daytime, regardless of farm rurality, resulted in higher probabilities of participation. Studies of agricultural injury may be more efficiently conducted, with higher participation responses, when circumstances of the recruitment call are considered. This work serves as a starting place for much-needed methodological research to identify factors that increase participation of farmers and farm workers in research studies.

Farm Machinery Injuries: A Retrospective Analysis of Admissions at a Level I Trauma Center in North Dakota

OBJECTIVES

The purpose of the present study was to characterize the incidence, injury characteristics, and outcomes of patients presented to a Level I adult trauma center in Fargo, North Dakota, with farm machinery injuries (FMI).

METHODS

We performed a retrospective review of the trauma registry of Sanford Medical Center Fargo (SMCF) between January 2010 and December 2020. We compared admission characteristics of FMI admissions to non-FMI admissions, identified the types of machinery that are most commonly associated with FMI, and described the nature of these injuries by severity, anatomical site, type, age, sex, and length of stay (LoS). Injury severity was evaluated using Injury Severity Score (ISS).

RESULTS

Findings indicated that FMI admissions had a higher mean ISS, longer ICU LoS, and a higher mortality rate than non-FMI admissions. The leading cause of fatal and non-fatal FMI in this region are tractors. Males experience 91.2% of tractor injuries, and individuals 65 and over account for nearly 53% of all tractor injuries (n = 18). Males accounted for all deaths, tractor and otherwise. The "other machinery" category was the second most common category and accounted for 50% of female patients. Additionally, 24.5% of all FMI are related to machine maintenance.

CONCLUSION

The findings from this study indicate that FMI injuries represent a significant problem in the upper Midwest. Older, male farm workers experience a higher incidence of tractor-related injuries, and all tractor-related deaths occurred in individuals 65 years of age and older. These results underscore the need for further investigation into aging-related farm safety issues.

Agricultural Injuries: Risk Factors and Severity by Affected Body Part among US (Midwest) Farmers

OBJECTIVES

Statistics from the United States Bureau of Labor Statistics indicate that agriculture consistently ranks as the most hazardous industry in the US. To identify specific targets for prevention, we investigated injury risk factor profiles separately for each injured body site. We also characterized the severity of agricultural injuries by injured body site using the type of medical care and lost work time due to injury.

METHODS

We used the Central States Center for Agricultural Safety and Health (CS-CASH) surveillance data for 2018 to perform descriptive statistics and regression modeling.

RESULTS

We found that 12% (513/4351) of the participants experienced one or more injuries in the previous 12 months. Compared to female operators, male operators had 3.53 (95% CI: 1.17-10.68) times higher odds of back injury. Operators in livestock production had 2.77 times (95% CI:1.12-6.82), 2.28 times (95% CI:1.25-4.14), and 1.69 times (95% CI:1.10-2.59) higher odds of injury to the chest/trunk, finger, and leg/knee/hip, respectively, compared to operators in crop or mixed production. After adjusting for age and gender, operators who worked full time (vs. part-time) on the farm/ranch had 2.11 times (95% CI:1.03-4.34) higher odds of back injury. Arm/shoulder and leg/knee/hip injuries were more frequent in older age groups.

CONCLUSIONS

Prevention measures should be tailored considering specifically livestock producers with emphasis on trainings on proper livestock handling, such as being gentle, establishing routine, keeping distance, and avoiding sudden and loud noise when handling animals. Applying these techniques avoid startling the animals and reduce the risk of injuries.

Ensuring data quality and maximizing efficiency in coding agricultural and forestry injuries: Lessons to improve occupational injury surveillance

INTRODUCTION

Specialized occupational injury surveillance systems are filling the gap in the undercount of work-related injuries in industries such as agriculture and forestry. To ensure data quality and maximize efficiency in the operation of a regional occupational injury surveillance system, the need for continued dual coding of occupational injury records was assessed.

METHODS

Kappa scores and percent agreement were used to compare interrater reliability for assigned variables in 1,259 agricultural and forestry injuries identified in pre-hospital care reports. The variables used for the comparison included type of event, source of injury, nature of injury, part of body, injury location, intentionality, and farm and agriculture injury classification (FAIC).

RESULTS

Kappa (κ) ranged from 0.2605 for secondary source to 0.8494 for event and exposure. Individual coder accuracy ranged from medium to high levels of agreement. Agreement beyond the first digit of OIICS coding was measured in percent agreement, and type of event or exposure, body part, and primary source of injury continued to meet levels of accord reaching 70% or greater agreement between all coders and the final choice, even to the most detailed 4th digit of OIICS.

CONCLUSIONS

This research supports evidence-based decision making in customizing an occupational injury surveillance system, ultimately making it less costly while maintaining data quality. We foresee these methods being applicable to any surveillance system where visual inspection and human decisions are levied.

PRACTICAL APPLICATIONS

Assessing the rigor of occupational injury record coding provides critical information to tailor surveillance protocols, especially those targeted to make the system less costly. System administrators should consider evaluating the quality of coding, especially when dealing with free-text narratives before deciding on single coder protocols. Further, quality checks should remain a part of the system going forward.

Occupational injury rates among Norwegian farmers: A sociotechnical perspective

INTRODUCTION

This study addressed relative injury risk among Norwegian farmers, who are mostly self-employed and run small farm enterprises. The aim was to explore the relative importance of individual, enterprise, and work environment risks for occupational injury and to discuss the latent conditions for injuries using sociotechnical system theory.

METHOD

Injury report and risk factors were collected through a survey among Norwegian farm owners in November 2012. The response rate was 40% (n = 2,967). Annual work hours were used to calculate injury rates within groups. Poisson regression using the log of hours worked as the offset variable allowed for the modeling of adjusted rate ratios for variables predictive of injury risk. Finally, safety climate measures were introduced to assess potential moderating effects on risk.

RESULTS

Results showed that the most important risk factors for injuries were the design of the workplace, type of production, and off-farm work hours. The main results remained unchanged when adding safety climate measures, but the measures moderated the injury risk for categories of predominant production and increased the risk for farmers working with family members and/or employees. An overall finding is how the risk factors were interrelated.

CONCLUSIONS

The study identified large structural diversities within and between groups of farmers. The study drew attention to operating conditions rather than individual characteristics. The farmer's role (managerial responsibility) versus regulation and safety climate is important for discussions of injury risk. Practical Applications: We need to study sub-groups to understand how regulation and structural changes affect work conditions and management within different work systems, conditioned by production. It is important to encourage actors in the political-economic system to become involved in issues that were found to affect the safety of farmers.

Nonfatal Agricultural Injuries Treated in Emergency Departments: 2015-2019

Utilizing emergency department admissions to estimate and describe agricultural injuries in the United States (U.S.) provides a unique view of one of the country's most dangerous occupations. This study characterizes and provides nationally representative estimates of persons with non-fatal agricultural-related injuries treated in emergency departments in the U.S.We conducted a cross-sectional study using U.S. Consumer Product Safety Commission, National Electronic Injury Surveillance System (NEISS) data for patients treated in emergency departments from January 1, 2015 to December 31, 2019. We queried all cases in the NEISS database using the location code "farm" and with a narrative search using relevant key words.An estimated 62,079 people were treated in an emergency department for agricultural related injuries. The mean age estimate in this population was 39 years-old, with ages ranging from 1 to 95. Almost two-thirds of patients were male, and almost 80% were white. Approximately 30% and 22% of those injured were youth and elderly patients, respectively. The majority of injuries occurred from April through September. The most common injury was fracture, followed by open wound or amputation. There were significant differences between the body parts injured in youth versus adult patients. The primary source of injury was in the vehicles category, with tractors being the dominant vehicle type.Agricultural vehicles remain a major source of injuries that require treatment in emergency departments. Previous methods of quantifying severe ag-related injuries were limited; our research utilized NEISS data to portray injury statistics more accurately.

Agricultural Injuries among Farmers and Ranchers in the Central United States during 2011-2015

The high risk of occupational fatalities in agriculture is well documented, but information on non-fatal injuries is lacking due to challenges in injury surveillance. This surveillance study explored the frequency, characteristics, and risk factors for non-fatal injuries among farmers and ranchers in the central United States. The Central States Center for Agricultural Safety and Health (CS-CASH), in collaboration with the USDA National Agricultural Statistics Service (NASS), conducted annual surveys (n = 34,777 sent) during 2011-2015 covering a seven-state region (Iowa, Kansas, Minnesota, Missouri, North Dakota, Nebraska, and South Dakota). The average response rate was 32% in the five consecutive annual surveys. The average injury incidence rate was 7.0 injuries/100 operators per year. Most injuries (89%) occurred during agricultural work. The most frequent sources of injury were livestock (22%), machinery (13%), and hand tools (12%). Risk factors for injury included: male gender, younger age (vs. 65+ years), farming as the primary occupation, greater work time, greater land area, ranch (vs. farm), organic farming, internet access, and production of several types of crops and animals. Most injuries (56%) required a doctor visit, and 12% required hospitalization. The average medical costs were $1,936 out of pocket and $8,043 paid by insurance. The combined average costs for most serious injuries were $7,858. Most injuries (66%) resulted in some lost time from agricultural work, and 13% were serious, resulting in more than 30 days of lost work time. The non-fatal injury rate for self-employed farmers and ranchers was higher than that of hired agricultural workers reported by the Bureau of Labor Statistics. This result reaffirms farming/ranching as a dangerous occupation and emphasizes the need for efforts to prevent agricultural injuries, especially those associated with identified injury sources and risk factors.

Multisource surveillance for non-fatal work-related agricultural injuries

Objectives: Development of a state-wide comprehensive surveillance system for non-fatal work-related farm injuries, since non-fatal injuries that occur to the self-employed (i.e., many farm owners/operators), family workers, federal government workers and small farms with fewer than 11 employees are not included in the Bureau of Labor Statistics employer-based survey used to produce the U.S. National statistics of work-related injuries.Methods: In 2015 and 2016, inpatient discharge summaries, emergency department, and hospital-based outpatient clinic records from all 134 of Michigan's hospitals with ICD-9 codes 989.0-.1, E827.0-.9, E849.1, E906.8, E919.0 or ICD-10 codesT65.0-.1, V80, Y92.7, W55.1-.4, W30 were reviewed to identify non-fatal work-related farm injuries.Results: We identified 1,559 non-fatal work-related farm injury incidents that occurred in 1,525 individuals, with 74% being among men. The most common parts of the body injured were an upper limb (38.2%) and a lower limb (23.7%). The most common types of injury were contusions (26.4%) and fractures (19.9%). Owners/operators accounted for 44.1% and hired hands for 42.9% of individuals injured. Injuries caused by cows were the predominant cause: 472 (31.5%) of all the injuries. Dairy farms accounted for 39.6% of all cases for which the farm type was recorded.Conclusion: A comprehensive system to identify non-fatal work-related farm injuries among all individuals who work on a farm, including owner/operators, family members and migrant and seasonal farm laborers, was implemented using hospital, emergency department and hospital-based outpatient clinic medical records. Such a system is important to be able to identify hazards and target prevention.

Use of Neural Networks to Identify Safety Prevention Priorities in Agro-Manufacturing Operations within Commercial Grain Elevators

The grain handling industry plays a significant role in U.S. agriculture by storing, distributing, and processing a variety of agricultural commodities. Commercial grain elevators are hazardous agro-manufacturing work environments where workers are prone to severe injuries, due to the nature of the activities and workplace. Safety incidents in agro-manufacturing operations generally arise from a combination of factors, rather than a single cause, therefore, research on occupational incidents must look deeper into identifying the underlying causes, through the application of advanced analyses methods. In occupational safety, it is possible to estimate and predict probability of safety risks through developing artificial neural network predictive models. Due to the significance of safety risk assessment in the design and prioritization of effective prevention measures, this study aimed at classifying and predicting causes of occupational incidents in grain elevator agro-manufacturing operations in the Midwest region of the United States. Workers’ compensation claims data, from 2008 to 2016, were utilized for training multilayer perceptron (MLP) and radial basis function (RBF) neural networks. Both MLP and RBF models could predict the probability of safety risks with a high overall accuracy of 60%, 61%. Based on values of AUC (area under the curve) from the ROC (receiving operating charts), both models predicted the probability of individual safety risks with a high accuracy rate of between 71.5% and 99.2%. In addition, sensitivity analysis showed that nature of injury is the most significant determinant of safety risks probability, along with type of injury. The novelty of this study is the use of the artificial neural network methodology to analyze multi-level causes of occupational incidents as the sources of safety risks in bulk storage facilities. The results confirm that artificial neural networks are useful in safety risk estimation, and identifying the incidents’ risk factors. The implementation of safety measures in grain elevators can help in preventing occupational injuries, saving lives, and reducing the occurrence and severity of such incidents in industrial work environments.

Identifying Safety Training Resource Needs in the Cattle Feeding Industry in the Midwestern United States

Cattle feedyards are a high-risk environment. They are characterized by high rates of occupational injuries and illnesses. As such, there is a clear need to address the health and safety of cattle feedyard workers. Therefore, the purpose of this cross-sectional study was to explore safety training practices and preferences in the cattle feeding industry. A survey of feedyard managers, feedyard safety trainers, and feedyard operators was conducted (n = 28). We found that only half of respondents had dedicated safety personnel; however, there was interest in a safety training program, conducted through short hands-on and in-person methods with materials available in English and Spanish. The majority of participants were also interested in a feedyard safety certification program. Participants reaffirmed the importance of partnering with industry and other stakeholders when conducting these types of programs. The results of this Phase 1-type translational research study will be used to guide the development of feedyard safety trainings and a corresponding recognition program for feedyards and feedyard workers as part of the “Improving Safety and Health of Cattle Feedyard Workers” project.