Risto Rautiainen

Environmental allergies plague millions of adults every year. Farmers and ranchers are at a heightened risk of exposure to allergens due to their occupation. Few studies have addressed the contribution of occupational exposures to environmental allergies and potential preventive strategies to reduce exposure. The objective of this study is to determine whether occupational exposures affect the risk of environmental allergies among farmers and ranchers in the central midwestern states. Surveillance data from the Central States Center for Agricultural Safety and Health Farm and Ranch Health and Safety Surveys from 2018, 2020, and 2023 were analyzed to investigate risk factors for environmental allergies. Logistic regression was used to evaluate associations. The study was conducted across seven states, including Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, and South Dakota. Surveys were mailed to randomly selected agricultural operations. Eligible participants were farm and ranch operators with an email address and an estimated gross farm income of at least $5,000. The study was sent to "operators" defined as those who manage a farm or ranch business. The primary outcome variable is the presence of environmental allergies, assessed through self-reported physician-diagnosed allergies. The primary variable of interest was air contaminant exposure. Additional predictor variables included skin exposures, musculoskeletalexposures, workstrain symptoms,musculoskeletal discomfort, sex, age, type of operation, primary occupation, percentage of worktime, and production variables. Beingfemale (OR = 1.84) and having a primary occupation other than farm/ranch work (OR = 1.47) were significantly associated with higher odds of environmental allergies. Surprisingly, participants without symptoms of work strain (OR = 1.72), musculoskeletal discomfort (OR = 1.93), and musculoskeletal exposures (OR = 1.48) were positivelyassociated with environmental allergies. Occupational exposures, including respiratory exposure to grain, feed, or hay dust (OR = 1.43), road dust (OR = 1.39), skin contact with pesticides or fertilizers (OR = 1.22), and detergents and disinfectants (OR = 1.22) increased theodds of having environmental allergies. Dairy (OR = 0.61) and grainproduction (OR = 0.75) decreased the odds. These findings highlight the need for occupational health interventions aimed at reducing respiratory and skin exposures in farm and ranch environments.

Objectives: This study examined the prevalence and risk factors for asthma among farm and ranch operators in seven Midwestern States, using surveillance data from 2018, 2020, and 2023. Methods: Regression models were developed to identify predictors of asthma, including demographic factors, agricultural exposures, and physical activity. Results: The overall prevalence of asthma was 4.7%. Asthma was significantly associated with respiratory exposures to grain, feed, or hay dust (adjusted odds ratio [AOR], 2.14; 95% confidence interval [CI], 1.74–2.63) and animal confinement dust (AOR, 1.72; 95% CI, 1.35–2.21) after adjusting for demographics and work time on farm/ranch. Conclusion: The identified occupational risk factors highlight the importance of surveillance and targeted prevention among agricultural populations to further reduce the long-term respiratory exposures, particularly in animal confinement operations.

The number of women choosing agriculture as an occupation is increasing. Agriculture is dangerous work, and women are at risk of serious injury, but the research on injuries in females is sparse. Women perform different types of farmwork and have different exposures than men. Studies have not assessed injury in a large group of female agricultural operators. In this study, we used XGBoost, a machine learning algorithm, and logistic regression to examine 17 factors hypothesized to be associated with injury in 1529 farm and ranch women. The sample was split into a training group of 1070, and the results were replicated in a test group of 459. The model accuracy was 88%. We compared the results of XGBoost to those of the logistic regression models and computed odds ratios to estimate effect sizes. We found that the two methods generally agreed. XGBoost identified the total number of musculoskeletal symptoms, age, sleep deprivation, high work-related stress, and exposure to respiratory irritants as being important to injury. The multivariate logistic regression model identified higher income, higher stress, younger age, and number of musculoskeletal symptoms as being significantly associated with injury. The analysis highlights the importance of musculoskeletal disorders and work strain to injury in women.

Background: Farm operators are at a high risk of developing skin cancer due to their occupational sun exposure. With the growing incidence of skin cancer, it is also important to evaluate other occupational risk factors. Farm operators confront numerous physical, chemical, and biological hazards in their work environment. This study investigated whether dermal exposures to pesticides/fertilizers, animals/livestock, detergents/disinfectants, and fuels/solvents/paints were associated with the risk of skin cancer in farm and ranch operators.Methods: Surveillance data from the Central States Center for Agricultural Safety and Health (CS‐CASH) Farm and Ranch Health and Safety Surveys in 2018 and 2020 were used to explore the risk of skin cancer in farm operators in seven US central states. Farm production variables from the DTN Farm Market database were merged with survey responses. The associations of skin cancer and exposure variables were analyzed using descriptive statistics and regression modeling.Results: The prevalence of skin cancer was 10% among 7943 operators. Univariable analyses showed that men had 1.62 times higher odds of skin cancer compared to women. The odds of skin cancer increased significantly with age. Livestock, fed cattle, cow‐calf, and beef production increased the odds of skin cancer. Exposure to pesticides/fertilizers and fuels/solvents/paints also increased the odds of skin cancer compared to unexposed operators. In the final multivariable model, the associations of skin exposure to pesticides/fertilizers (odds ratio (OR) = 1.30, 95% CI: 1.08–1.56) and to fuels/solvents/paints (OR = 1.21, 95% CI: 1.01–1.45) remained statistically significant after adjusting for sex, age, and state. Having livestock also increased the odds of skin cancer (OR = 1.18, 95% CI: 1.00–1.38).Conclusion: Skin is a critical source of occupational exposures among farm operators. Increased odds of skin cancer in this study emphasizes the need for better protection against exposures to chemicals including pesticides/fertilizers, and fuels/solvents/paints.

In high-risk agricultural environments, tasks, weather, and work conditions vary throughout the year. Also, injuries peak during certain periods. The primary objective of this study was to examine operator- and farm-level characteristics as risk factors for injuries within each of the four seasons. The secondary objective was to examine seasonal differences in the incident location and primary cause of these injuries. We analyzed data from the 2018 and 2020 Farm and Ranch Health and Safety Surveys (FRHSS), conducted in seven U.S. states by the Central States Center for Agricultural Safety and Health (CS-CASH), which were collected using a stratified random sampling approach to ensure representativeness. The survey data were merged with operation-level data from the Farm Market iD database. We employed Generalized Estimating Equations (GEE) to examine the association of seasonal injuries with individual and operation-level characteristics. The chi-square test of independence was used to assess the association between injury incident location and season, as well as injury cause and season. Pairwise Z-tests of proportions were conducted to evaluate the differences in the proportions of injuries due to specific combinations of injury location and cause across each pair of seasons. Surveys conducted in 2018 and 2020 yielded a combined response rate of 15.9%, with 5,428 responses and 7,915 unique operators. Of these, 903 operators reported at least one injury during the past 12 months. Seasonally, most injuries occurred in spring (34.2%), followed by summer (24.7%). Male operators had higher injury odds in the spring (adjusted OR = 1.42) and summer (aOR = 2.41). Those managing both a farm and a ranch reported increased injury risks in winter (aOR = 1.73) and spring (aOR = 1.48). Operators in cow-calf operations faced higher springtime injury risks (aOR = 1.45). High stress and exhaustion were consistent risk factors across all seasons. The highest proportion of injury incidents occurred in the farmyard (43.6%), and livestock were the most common cause of injury (24.9%). Results highlight the need for season-specific prevention and intervention strategies, considering farmers' and ranchers' risk characteristics, injury locations, and causes. These findings can inform targeted measures for high-risk populations at optimal times and locations.

Background: Agriculture is a hazardous industry but the frequency and severity of agricultural injuries are not well documented as nonfatal injuries to self‐employed farmers are excluded from national surveillance. The aim of this study was to provide new injury rate and cost estimates in US agriculture.Methods: Injury data were obtained from 2018 to 2020 Farm and Ranch Health and Safety Surveys. Responses from 7,195 farm/ranch operators included injury frequency, medical expense, and lost work time data. These injury rate and cost data were used to estimate national injury costs for self‐employed farmers using Census of Agriculture operator count, injury costs for hired agricultural workers using Bureau of Labor Statistics (BLS) nonfatal injury count, and fatal injury costs using BLS count of fatal injuries.Results: The injury rate for self‐employed farmers and ranchers was 15.25 injuries per 100 operators or 11.9 “recordable” injuries per 100 full time equivalent operators (FTE). Average costs for nonfatal injuries were: $10,878 for medical care, $4735 for lost work time, and $15,613 in total per injury case. The total national agricultural injury cost estimate was $11.31 billion per year; 11.3% higher than the earlier benchmark using 1992 data; both in March 2024 dollars. The cost burden was 2.1% of the US national gross farm income and 13.4% of the net farm income in 2019.Conclusions: Injuries result in significant economic losses to farm and ranch operators, their family members, workers, and society. Preventive efforts should be scaled up to reduce the frequency and costs of agricultural injuries.

This study examined agricultural machine accidents in Finland. In Finland, the relative share of the number of machine accidents of all accidents in agriculture has grown. In addition, agricultural machinery causes more than half of farmers' deaths at work. Most of the machine accidents occur when using field machinery. The two main objectives of the study were 1) to reduce farmers' machine accidents and their costs by publishing machine safety information cards in a magazine for farmers, and 2) to evaluate the impact of this safety information on the occurrence of machine accidents by following up accident statistics. In 2017, ten information cards on agricultural machinery safety were published in the Koneviesti farm machinery magazine. The topics of the information cards were the most dangerous farm machinery and how to avoid accidents with these: tractors, seeding and tilling machines, automatic functions in field machinery, trailers, ATVs, combines, front loaders, machinery used in livestock production, personal protective equipment, and machine maintenance work. One year after the intervention, the statistics of accidents caused by these machines were analysed, from ten years before to one year after the intervention. A statistically significant decrease in accident development after the intervention was observed among Koneviesti's farmer subscribers. By contrast, no corresponding decrease in accident development was observed among other farmers who were not subscribers to the Koneviesti magazine. The study produced practical training material on agricultural machinery safety.

Introduction and Methods: In this study, we evaluated self‐reported respiratory symptoms during agricultural work, respiratory protection use and experience, and perceived value of receiving respirators using Gear Up for Ag Health and Safety Program™ pre‐ and post‐surveys from 703 to 212 young adult hog producers in the United States. To our knowledge, this is one of the most extensive survey data sets on self‐reported respiratory symptoms and respiratory protection behaviors of collegiate‐aged young adults working in US livestock production.Results: About one‐third (37%) of young adult hog producers stated that they have experienced cough, shortness of breath, fever, and chills after working in dusty areas on the farm. Most (76.2%) stated that they were already “always” or “sometimes” wearing filtering facepiece (N95‐style) respirators, even before participating in an outreach program. About one‐third (30%) reported experience wearing a cartridge‐style respirator but only 5% reported having been fit‐tested for a respirator. Young adult male producers were significantly more likely to report use of both respirator types when compared to females, both before and after the program. Male producers were also more likely than females to engage in high‐risk farm tasks where respirators are recommended, such as cleaning out grain bins and mixing or grinding feed. Following an educational program, males and females reported using the respirators that they received at similar rates, and 20% of overall participants purchased additional respiratory protection.Discussion: The study found that young adult hog producers in postsecondary education are already wearing respirators with some frequency and at rates higher than previously reported by agricultural workers. More research is needed to make effective task‐based respirator‐use recommendations and investigate some significant gender differences among young adult hog producers observed in this study.

Objective: This study addressed the relationship of hearing loss and coexposure to solvents and noise among farmers and ranchers in central United States. Methods: The surveillance study included surveys to stratified random samples of operations in 2018 and 2020 (n = 34,146), requesting information on injuries, illnesses, exposures, and preventive measures. Responses (n = 7495) were analyzed using hierarchical multinomial logistic regression, adjusting for personal and work characteristics. Results: Nearly 60% of respondents exposed to both solvents and noise reported hearing loss. The exposures increased the adjusted odds of moderate/severe hearing loss as follows: solvents alone, (odds ratio [OR], 1.49; 95% confidence interval [CI], 0.93–2.38), noise alone (OR, 4.42; 95% CI, 3.39–5.76), and coexposure to both noise and solvents (OR, 6.03; 95% CI, 4.67–7.78). Conclusions: Solvent exposure, along with noise, should be considered in hearing conservation programs among farmers and ranchers.

Despite training and prevention programs, injury rates in agriculture remain high, and safety compliance is a challenge. Our aim was to compare farm operators’ reported safety priorities to related behaviors. Surveys were mailed to 1600 agricultural operators; 326 returned complete data. We asked respondents about their safety priorities and practices related to machinery, chemicals, and structures. Kappa statistics, factor analysis, structural equation modeling, and profile analysis were used to understand how practices and priorities were related. Agreement between priorities and practices was low to moderate with high variability. Most discrepancies between the two were found in storing pesticides safely, keeping safety data sheets, using personal protective equipment, grain bin entry, and ladder safety. Machinery questions formed consistent constructs for practices and priorities, where practices predicted priorities more strongly than priorities predicted practices. Younger operators were less frequently exercising safe behaviors compared to older operators. Three safety compliance groups were identified: low compliance (15% of respondents), moderate (61%), and high (24%). Overall, operators reported that safety was a high priority, but their practices suggested otherwise. The promotion of safety culture has been suggested as an underutilized means in agriculture to address the complex issues that lead to unsafe practices, regardless of whether they are tied to limited resources, work organization, working environments, machinery, work habits, or general attention to safety. Effective new ways focusing on operator motivation are needed to bridge the gap between safety priorities and practices.