Journal of Agromedicine最新文献

Farming is one of the top industries in Michigan and has the highest fatality rate. National sources of non-fatal farm injuries underestimate the burden, especially among children. In this paper, we provide a more accurate estimate of non-fatal farm injuries in Michigan by using an ongoing multi-source surveillance system. Michigan's farm-injury surveillance system includes abstractions of hospital-based medical records, poison control center calls, ambulance runs, and workers' compensation claims for individuals with a farm-related injury. For this analysis, injury onset occurred in 2015 to 2021 and included all injuries regardless of age or occupation. We identified 4,306 injuries in adults and 336 injuries in youth. For those 0-13 years of age all but two were family members. For those 14-15 and 16-17 years of age, 19% and 45%, respectively were hired hands. For adults, 51% were owner/operators, 43% were hired hands, and 5% were family members. For all ages, the most frequent injury source was cattle. Lacerations/cuts/punctures were the most common type of injury for those < 14 years of age while for older individuals it was contusions/bruises. The plurality of injuries occurred in the summer months. Children working on a farm are in unique situation and tracking injuries and identifying injury sources provide necessary information to protect their health and well-being. Michigan's farm-injury surveillance system will continue to provide a comprehensive count of work-related injuries among Michigan's farming population. The information is used to direct public health intervention both at the individual and population level.

Objectives: This study collected data related to agricultural injuries, analyzed their causes, and suggested possible remedial actions. Few studies from developing countries have investigated this important topic. Such investigations are extremely important and are required to frame national policies.

Methods: A well-designed structured form was developed to collect and evaluate data on agricultural incidents, their causes, the severity of injuries, and possible prevention methods. The authors followed a door-to-door survey methodology to collect data with the help of local village leaders.

Results: Less educated and older adults in the age group 31 to 45 years were more prone to agricultural incidents (p < .05). The mean age of the victims was 35.02 years (95% CI 32.7 to 37.3); 124 (91.18%) of the victims were men; and 21 (15.4%) of the cases were fatal. Tractor rollovers caused most of the deaths. Chaff cutters were responsible for most of the incidents that required amputation. Eighteen (45%) of the chaff-cutter incidents occurred in the evening between 3:00 PM and 6:00 PM, and 12 (30%) of these incidents occurred due to fatigue.

Conclusions: The authors strongly recommend that rollover protective structures (ROPS) for tractors and seat belts should be made mandatory in India. Public guidelines emphasizing mandatory higher education for farmers and a model curriculum for both schools and colleges that focuses on the safety of rural populations should be developed. Special training should be provided on the safe operation of machinery and a definitive work - rest schedule should be followed to prevent fatigue and protect agricultural workers from incidents.

Objective: Generation of reliable data underpins the effectiveness of Occupational Health and Safety (OHS) surveillance systems. Despite the importance of understanding OHS data systems, there are few papers that provide overviews of their structure and/or content. This paper introduces a basic framework for assessing OHS data systems that will be of use to researchers internationally. We applied this approach to assess the Irish OHS data system by undertaking a data mapping exercise.

Method: We developed a checklist based on recommendations of monitoring and measurement of OHS proposed by the National Academies of Sciences, Engineering, and Medicine (USA). An assessment of published reports that present systematic OHS surveillance data was undertaken to identify the institutions or organisations responsible for collecting and curating the data, their remit, and, associated with this, their respective case definitions. We then provide an overview of the variables collected and these are then mapped against the checklist.

Results: The assessment highlights that whilst the farm fatalities dataset provides complete coverage of all fatalities, regardless of age or employment status, the same is not true of the three non-fatal injuries datasets reviewed. There are important differences in the data collection methods and, associated with this, which populations are covered.

Practical application: The assessment approach provides valuable insights into the strengths and weaknesses of a critical element of OHS surveillance systems, namely the production of datasets. This knowledge is important for researchers as understanding the data that informs their research is fundamental to good science. It is critical for policy-makers and other stakeholders to understand the strengths and weaknesses on which OHS policy, strategies, or education and training interventions are developed.

Objective: Agriculture is a dangerous industry, with evidence indicating a disproportionate burden among Hispanic/Latinx workers. There is a need to expand the utilization of different data systems to improve the surveillance of precarious workers within agriculture. This analysis describes inclusion criteria to identify farm-related injuries and illnesses in hospital data utilizing ICD-10 codes to better assess health equity issues involving Hispanic/Latinx workers and their associated costs.

Methods: Discharge data of agriculture-related injuries and illnesses treated in Illinois hospitals and emergency departments from 2018 to 2021 were extracted using ICD-10 diagnosis and location of injury codes. Injury cause, nature, severity, and course of clinical care are stratified by ethnicity. Multivariable models were developed to assess differences in injury severity, level of care required, and cost of care.

Results: We identified 3,745 farm-related injuries and illnesses treated in Illinois hospitals between 2018 and 2021, of which 196 involved Hispanic/Latinx individuals. Hispanic/Latinx patients were substantially younger and disproportionately covered by workers' compensation insurance or uninsured. Compared to non-Hispanic/Latinx individuals, Hispanic/Latinx patients suffered injuries from different mechanisms, particularly involving animals and cutting/piercing instruments. While non-Hispanic/Latinx individuals demonstrated more severe injuries based on the descriptive statistics, after controlling for confounding (particularly age), we did not observe ethnic disparities in injury severity or level of care required. However, the cost of care was equivalent to or higher among Hispanic/Latinx persons.

Conclusion: The case definition used for this analysis identified agriculture-related cases and provided insights on the course of clinical care by ethnicity. This strategy would likely yield valuable information in states with larger and more diverse agricultural workforces. More targeted research to appropriately scope the issue and inform interventions is needed to understand differential exposure and reduce agricultural workplace hazards and address the financial burden resulting from farm-related injuries.

Background: Agriculture is a hazardous industry with undocumented injury events. Credible surveillance measures are critical for this industry, especially to guide injury prevention programs with targeted recommendations for specific commodity groups and populations. This multi-phase study explored the feasibility for two state agency databases, the Ohio Bureau of Workers' Compensation (BWC) Program and the Emergency Medical Services Incident Reporting System (EMSIRS), to augment the state's Bureau of Labor Statistics (BLS) annual reports.

Methods: BWC data described injury claims in agricultural workplaces from 1999 to 2008. State EMSIRS data described the types of medical emergencies for which EMS services were requested to Ohio farms in 2013-2014. Descriptive analyses were performed on each distinctive source.

Results: Over 14,000 BWC claims were analyzed, with primary nature of injury identified as sprains and strains of bodily extremities; falls were the most common cause of injury. The EMSIRS data provided 1,376 cases, where EMS services were requested to Ohio farms at injury onset. Some cases had possibility to be excluded in CFOI or employment claims data, with 24% patients 65 years and older and 6% children 13 years and younger. The primary cause of injury was falls, and the highest reported injury type was blunt trauma.

Conclusions: Both BWC and EMSIRS databases showed the potential to enhance Ohio's agricultural surveillance data with viable information not found in previously used systems. Each agency database had its own merits to further clarify and quantify morbidity. When used together, these sources enrich surveillance statistics to describe Ohio's agricultural injury incidents.

Agriculture is one of the most important and also hazardous industries in Australia. Having a sound knowledge and understanding of the circumstance of injury events is critical to developing evidence-based intervention programs. This paper aims to provide a brief historical snapshot of the development of data systems underpinning the assessment of fatal farm injury in Australia and how it has impacted on safety policy and practice. The first Australian studies used coronial information to explore agricultural fatalities, these studies reviewed paper-based records (in-situ) and collected the information for analysis and reporting. This task was laborious and costly. When the National Coronial Information System (NCIS) was established in 2000, this allowed access to coronial records online. Information provided about the deceased includes demographics, contextual details on the nature of the fatality and autopsy, toxicology, and police reports, as-well-as the coroner's finding. Information from the NCIS, along with media reports, have been used to develop the farm fatality database. This information has been used to inform the safety goals and targets for farm commodity groups, identify key risks, provide long-term benchmark indicators and underpin the development of prevention materials and training resources. Without accurate, timely, concise and relevant data about injury occurring on farms, there is no evidence to drive policy and practice or to evaluate programs of work. As such, the continued utilization and extension of the NCIS data will prove crucial to further reducing the burden of preventable fatal injuries on Australian farms.

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.

Objective: The purpose of this study was to investigate characteristics associated with farm vehicle and farm labor transportation-related roadway crashes in the state of Florida. Agricultural roadway crashes related to these vehicles have not been explored in Florida.

Methods: The data for this study comes from the Florida Department of Highway Safety and Motor Vehicles (FLHSMV) for the years 2013-2021. The data is recorded by the Florida Highway Patrol when a vehicular crash has occurred. The data is then coded to allow the selection of farm and agricultural-related vehicles. Specifically, this study focuses on farm labor transport vehicles and farm vehicles (e.g. farm tractors).

Results: There were 744 farm vehicle- and 209 farm labor transportation-related crashes during the 9-year study period. The farm labor transport vehicle crashes involved a total of 420 vehicles and 1,329 individuals, and the farm vehicle crashes involved 1,458 vehicles and 1,652 individuals. Injury risk for non-farm labor transportation vehicle occupants was significantly higher than injury risk for farm labor transportation vehicle occupants.

Conclusions: The average fatality rate for farm vehicle-involved (2.1 fatalities per 100 crashes) and farm labor transportation vehicle-involved crashes (2.9 fatalities per 100 crashes) were much higher than the overall FL roadway crash fatality rate (0.45 fatalities per 100 crashes).

Evidence suggests that farm workers represent a high-risk population for the development of depression. The aim of the study was to clarify the association between pesticide exposure/poisoning and depression. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis were conducted in this systematic review and meta-analysis. Relevant studies were included through searching in PubMed, Scopus, Web of Science, ProQuest, CINAHL and pre-print services databases. A total of eight studies were included. A positive but non-significant association was observed between pesticide use and depression (OR = 1.123; 95% CI, 0.932-1.354, p-value = .221) while a significant positive association was observed between pesticide poisoning and depression (OR = 2.942; 95% CI, 1.791-4.831, p-value < .001). The present meta-analysis suggested clearly a significant positive association between pesticide poisoning and depression, confirming the hypothesis that pesticide poisoning is a risk factor of depression. It also revealed positive, yet non-significant association, between pesticide exposure and depression, a finding that enhances recent research but requires to be further supported by future cohort studies, including socioeconomic factors and biomarkers of depression.