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Agricultural aircraft operations are an integral part of the agricultural sector. According to the National Agriculture Aviation Association (NAAA), aerial applications are conducted in all 50 states of the U.S. and account for 28% of all treated cropland. A typical application operation consists of an operator (Part 137 certificate holder, permission to apply chemicals to agricultural crops) and one or more pilots. This article explores the risk perceptions of operators (pilots with a Part 137 certificate) and non-operators (pilots without a Part 137 certificate) using data from two industry surveys. In an effort to explain the differences between risk perceptions of operators and non-operators, a series of regression analyses were conducted controlling for age, work experience, prior encounters with hazards and history of reported injuries. In addition to exploring the aggregated perceptions across all hazards, perceptions of specific hazards were also examined. Data indicate that non-operators perceive hazards as significantly more dangerous than operators. Power lines are perceived as the most hazardous, followed by communication towers and meteorological towers. The regression results indicate that risk perception differences remain even after controlling for differences in age, work experiences, prior hazard encounters and injuries between the two groups. Heterogeneity in risk perceptions within an organization can result in discrepancies over daily decision-making concerning operations. Further research is needed to identify the causal factors behind the observed differences. [ABSTRACT FROM AUTHOR]

Traditionally, structured or coded data fields from a crash report are the basis for identifying crashes involving different types of vehicles, such as farm equipment. However, using only the structured data can lead to misclassification of vehicle or crash type. The objective of the current article is to examine the use of machine learning methods for identifying agricultural crashes based on the crash narrative and to transfer the application of models to different settings (e.g., future years of data, other states). Different data representations (e.g., bag-of-words [BoW], bag-of-keywords [BoK]) and document classification algorithms (e.g., support vector machine [SVM], multinomial naïve Bayes classifier [MNB]) were explored using Texas and Louisiana crash narratives across different time periods. The BoK-support vector classifier (SVC), BoK-MNB, and BoW-SVC models trained with Texas data were better predictive models than the baseline rule-based algorithm on the future year test data, with F1 scores of 0.88, 0.89, 0.85 vs. 0.84. The BoK-MNB trained with Louisiana data performed the closest to the baseline rule-based algorithm on the future year test data (F1 scores, 0.91 baseline rule-based algorithm vs. 0.89 BoK-MNB). The BoK-SVC and BoK-MNB models trained with Texas and Louisiana data were better productive models for Texas future year test data with F1 scores 0.89 and 0.90 vs. 0.84. The BoK-MNB model trained with both states' data was a better predictive model for the Louisiana future year test data, F1 score 0.94 vs. 0.91. The findings of this study support that machine learning methodologies can potentially reduce the amount of human power required to develop key word lists and manually review narratives. [ABSTRACT FROM AUTHOR]

Objective: Crash reports contain precoded structured data fields and a crash narrative that can be a source of rich information not included in the structured data. The narrative can be useful for identifying vulnerable roadway users, such as agricultural workers. However, using the narratives often requires manual reviews that are time consuming and costly. The objective of this research was to develop a simple and relatively inexpensive, semi-automated tool for screening crash narratives and expediting the process of identifying crashes with specific characteristics, such as agricultural crashes. Methods: Crash records for Louisiana from 2010 to 2015 were obtained from the Louisiana Department of Transportation (LaDOTD). Records with narratives were extracted and stratified by vehicle type. The majority of analyses focused on a vehicle type of farm equipment (Type T). Two keyword lists, an inclusion list and an exclusion list, were created based on the published literature, subject-matter experts, and findings from a pilot project. Next, a semi-automated tool was developed in Microsoft Excel to identify agricultural crashes. Lastly, the tool's performance was assessed using a gold standard set of agricultural narratives identified through manual review. Results: The tool reduced the search space (e.g., number of narratives that need manual review) for narratives requiring manual review from 6.7 to 59.4% depending on the research question. Sensitivity was high, with 96.1% of agricultural crash narratives being correctly classified. Of the gold standard agricultural narratives, 58.3% included an equipment keyword and 72.8% included a farm equipment brand. Conclusion: This article provides information on how crash narratives can supplement structured crash data. It also provides an easy-to-implement method to facilitate incorporating narratives into safety research along with keyword lists for identifying agricultural crashes. [ABSTRACT FROM AUTHOR]

Objectives: According to the Centers for Disease Control and Prevention (CDC), highway transportation crashes are the number one cause of fatal occupational injuries in the United States. The rate of fatal crashes in logging far exceeds the average annual rate for all sectors combined, yet few studies examine logging-related transportation crashes, and little is known about factors influencing the frequency of these crashes. The purpose of this study was to identify factors associated with fatal and nonfatal injuries among drivers involved in a single vehicle logging-related crash in Louisiana. Methods: All crashes involving a single logging vehicle from 2010 to 2015 were extracted from a dataset provided by the Louisiana Department of Transportation and Development. Descriptive statistics were computed to characterize crashes by person, vehicle, and environmental factors. A multiple logistic regression model was constructed to identify variables associated with driver injury (fatal and non-fatal). Results: There were 361 crashes involving a single logging vehicle from 2010 to 2015 in Louisiana. Variables associated with driver injury included no seat belt use (OR = 3.23; 95% CI = 1.47–7.10), a violation issued for careless operation of the vehicle (OR = 3.23; 95% CI = 1.40–7.46), a harmful event classified as cargo or equipment loss or shift (OR = 2.47; 95% CI = 1.27–4.82), and a harmful event classified as the vehicle running off the road to the left (OR = 2.29; 95% CI = 1.12–4.70). Conclusion: Injury prevention efforts in the logging industry in Louisiana, including commercial vehicle licensing procedures, could benefit from additional driver training to improve crash avoidance skills and careless driving, seat belt use, and methods for securing loads. [ABSTRACT FROM AUTHOR]

In the United States, there is limited literature on occupational pesticide exposures despite being associated with adverse health outcomes, including in large states such as Texas. The purpose of this article is to characterize occupational pesticide poison center exposures in Texas. Descriptive statistics were used to describe exposures (eg, exposure routes, type of pesticide, medical outcome, clinical effects, and temporal/seasonal patterns). From 2000 to 2015, there were 2,303 occupational pesticide poison center exposures. Common types of reported pesticides were insecticides (67.3%), herbicides (17.7%), and repellents (5.8%). The highest proportion of exposures were among those aged 20 to 29 years (24.9%). The top clinical effect categories were gastrointestinal (25.8%), neurological (19.2%), and dermal (14.9%). Characterizing occupational pesticide poison center exposures can support improved surveillance systems and guide future research or interventions. [ABSTRACT FROM AUTHOR]

Objective: This article describes how perceived discrimination shapes the way Latino farmworkers encounter injuries and seek out treatment. Methods: After 5 months of ethnographic fieldwork, 89 open-ended, semistructured interviews were analyzed. NVivo was used to code and qualitatively organize the interviews and field notes. Finally, codes, notes, and co-occurring dynamics were used to iteratively assess the data for major themes. Results: The primary source of perceived discrimination was the "boss" or farm owner. Immigrant status was also a significant influence on how farmworkers perceived the discrimination. Specifically, the ability to speak English and length of stay in the United States were related to stronger perceptions of discrimination. Finally, farm owners compelled their Latino employees to work through their injuries without treatment. Conclusions: This ethnographic account brings attention to how discrimination and lack of worksite protections are implicated in farmworkers' injury experiences and suggests the need for policies that better safeguard vulnerable workers. [ABSTRACT FROM AUTHOR]

Context:Although national poison center data show that pesticides were the 8th most commonly reported substance category (3.27%) for children aged ≤5 years in 2014, there is limited information on childhood and adolescent pesticide exposures. Objective:This study assessed pesticide-related poison center exposures in children and adolescents aged ≤19 years from 2000–2013 in Texas to characterize the potential burden of pesticides. Materials and methods:Pesticide-related poison center exposures among children and adolescents aged ≤19 years reported to Texas poison centers were identified. The distribution of exposures was estimated by gender, age category, medical outcome, management site, exposure route, and pesticide category. Results:From 2000 to 2013, there were 61,147 pesticide-related poison center exposures in children and adolescents aged ≤19 years. The prevalence was highest among males at 864.24 per 100,000 population. The prevalence of unintentional exposures was highest among children aged ≤5 years at 2310.69 per 100,000 population, whereas the prevalence of intentional exposures was highest among adolescents aged 13–19 years at 13.82 per 100,000 population. A majority of medical outcomes reported were classified as having no effect (30.24%) and not followed, but minimal clinical effects possible (42.74%). Of all the exposures, 81.24% were managed on site. However, 57% of intentional exposures were referred to or treated at a health-care facility. The most common routes of exposure were ingestion (80.83%) and dermal (17.21%). The most common pesticide categories included rodenticides (30.02%), pyrethrins/pyrethroids (20.69%), and other and unspecified insecticides (18.14%). Discussion:The study found differences in the frequency of exposures by intent for sex and age categories, and identified the most common medical outcomes, management site, exposure route, and pesticide category. Conclusion:Through characterizing pesticide-related poison center exposures, future interventions can be designed to address groups with higher prevalence of exposure. [ABSTRACT FROM PUBLISHER]

Commercial fishing continues to have one of the highest rates of occupational fatalities compared with other work sectors in the United States. Attitudes/beliefs among Vietnamese shrimp fishermen of the Gulf of Mexico may influence behaviors that are risk factors for fatal and nonfatal injuries. The study employs a community trial with quasi-experimental pretest/posttest intervention design. An advisory group made up of key stakeholders including representatives from the US Coast Guard was assembled. A survey was designed using the Theory of Planned Behavior as the theoretical framework. Three community groups at port sites along the Texas/Louisiana Gulf Coasts were identified. Focus groups were convened at each site to select priority areas for risk intervention using training and awareness measures. Initial and follow-up surveys were administered pre-/post-interventions for each of the three community groups (2008, n = 217 completed surveys; 2012, n = 206 completed surveys). The follow-up survey was condensed and "intent to act" questions were added for the priority concerns identified (noise-induced hearing loss, machinery/winches, and fatigue). Statistically significant changes (P ranging from.000 to.042) were observed in selective attitude/belief responses for hearing/noise and fatigue. Intent to action or to adopt the intervention was high among all three groups of shrimp fishermen (hearing conservation, 82.4%; machinery/winch safety, 94.6%; fatigue awareness, 95.3%). Simple, yet culturally appropriate training and awareness measures in the form of visual and written safety messages favorably influence attitudes, beliefs, and behavioral intent related to priority risk factors identified by Vietnamese commercial shrimp fishermen along the Texas and Louisiana Gulf Coasts. [ABSTRACT FROM AUTHOR]

This study examined the effects on motor vehicle crashes of a policy change that led to the introduction of a very large number of off-sale alcohol outlets in Lubbock, Texas. Times-series analysis of total crashes and single-vehicle nighttime (SVN) crashes was used to compare the periods before and after the policy change in Lubbock and in a comparison area. The results of the analysis revealed some weak effects on total crashes, but no statistically significant effects were found for SVN crashes. Possible reasons for the essentially null findings of the current study regarding the effects of the policy change on motor vehicle crashes are discussed. These include the fact that there were a small number of off-sale outlets already present in the community and that motor vehicle travel immediately following alcohol consumption is less likely to occur with alcohol purchased from an off-sale outlet compared to an on-sale outlet. [ABSTRACT FROM AUTHOR]

Purpose: The rate for fatal injuries in the agriculture, forestry, and fishing (AFF) sector far exceeds the rate for all sectors combined in the United States, based on the National Census of Fatal Occupational Injury (CFOI). Data from CFOI also illustrate that transportation crashes are among the top causes of fatal occupational injuries in the United States. However, little is known about transportation crashes involving AFF vehicles, specifically logging trucks in the southwest (SW) region (Arkansas, Louisiana, New Mexico, Oklahoma, and Texas). The purpose of the ongoing SW AgCrash project is to develop an integrated database of AFF crashes that occurred on roadways in the SW region. These data are being assessed to determine their usefulness for supporting injury surveillance and the identification of injury risk factors. Methods: Crash records covering approximately the period of 2010 to 2018 were obtained from the department of transportation in each state. Logging truck vehicles were identified based on coded data fields pertaining to vehicle and cargo body styles. Logging truck-related crashes were characterized over time using descriptive statistics and geospatial plots. Multiple and multinomial logistic regression is being used to identify factors associated with more versus less severe crashes in Texas. Results/Findings: Louisiana, followed by Texas, and Arkansas recorded the largest numbers of logging truck-related crashes overall, which corresponds to their greater logging activity. Crash rates per total vehicle miles travelled were highest in Arkansas and Louisiana. Based on preliminary analyses, factors associated with more severe logging truck related crashes in Texas included overturned vehicle, failure to yield right of way, lack of restraint, and speeding. Practical Application: Although crash records have limitations, they can be a valuable source of data for monitoring the frequency of crashes involving logging trucks, as well as for identifying potential risk factors and countermeasures. Products constructed through the SW AgCrash project support targeted outreach and education for reducing crash risk. [ABSTRACT FROM AUTHOR]

While documentation of pesticide exposure among agricultural workers is increasing, similar data describing exposure in migrant farmworkers is lacking. Exposure assessment in migrant farmworker populations is difficult since this population travels seasonally for employment in temporary work environments. The present feasibility study addressed these obstacles by teaching participants to obtain dust samples that could be used to measure pesticide exposure at the time of exposure during the migration season. Using floor dust wipes in their temporary housing, mothers were asked to collect and return via U.S. mail, one house dust sample per week for four weeks. Of 10 mothers invited to participate in 2003, seven mothers submitted a total of 27 samples. Samples underwent chemical analysis for organophosphate and triazine pesticides. One or more pesticides were present in dust extracts at concentrations above the detection limit in 24 samples. Results indicate that farmworker mothers are willing and able to collect and return repeated samples while migrating. [ABSTRACT FROM AUTHOR]

This study assessed potential biases introduced by using maternal proxies for reporting work hazards, illness symptoms, and acute agricultural injuries in studies of migrant farmworker families. A convenience sample of 79 mother/spouse and mother/oldest child pairs was obtained from a two-year cohort study of migrant farmworker families from Starr County, Texas. Pairs completed an interviewer-administered survey including 27 close-ended items describing work history, illness symptoms, and acute injuries during the 2001 migration season. Data analysis included prevalence, sensitivity, and specificity measures. Maternal proxy reports of subjective symptoms of a spouse or child were approximately 50% lower than spouse or child self-reports. Sensitivity and specificity of mothers' responses regarding hazard items were higher for spouses than for children. For items measuring illness symptoms, sensitivity of mothers' responses for spouses and oldest child pairs was generally less than 30%; however, specificity was generally above 90%. For acute agricultural injury, the mother/spouse sensitivity was 75%, the mother/child 40%, and specificities were 100% and 97%, respectively. Sensitivity and specificity for spouse pairs was generally higher than mother/child pairs for work hazards, illness symptoms and acute injuries. While mothers may be acceptable proxies for spouses in this population, efforts should be made to collect data directly from adolescent children in studies of agricultural injuries. [ABSTRACT FROM AUTHOR]

This cross-sectional study examined the association between self-reported nonfatal occupational injuries among high school students in South Texas and their self-reported general use of substances. Data were collected using a self-administered, anonymous questionnaire (n = 3365). The independent variables included alcohol, marijuana, cocaine, inhalant, and steroid use. The dependent variable was occupational injury. Adjusting for grade, sex, ethnicity, and work intensity, odds ratios were calculated using logistic regression. Supporting an association with each substance, odds ratios consistently strengthened as use increased. Additional researchis merited given the scant number of previous studies. The associations for inhalant (OR, 5.61) and steroid (OR, 7.63) use argue for their inclusion in future research. [ABSTRACT FROM AUTHOR]

An abstract of the article "A Study of Neuromotor Function and Work Injury Risk Among Hispanic Adolescent Farmworkers: Pilot Test Findings" by Eva M. Shipp, Amit Bhattacharya and Cyndy Cox is presented.