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Literature supports an association between work and cardiovascular disease in adults. The objective of this study was to examine the relationship between current work status and elevated blood pressure in Hispanic adolescents. Participants were students in Hidalgo County, located along the Texas-Mexico border. Participants enrolled in the cohort study in ninth grade with assessments completed once a year for up to three years. Participants completed a self-report survey, while staff measured height, weight, waist circumference, blood pressure, and were screened for acanthosis nigricans. A generalized linear regression model with a logit link function was constructed to assess current work status and elevated blood pressure. Of the 508 participants, 29% had elevated blood pressure, which was associated with being male and other chronic disease indicators (e.g., acanthosis nigricans, overweight/obesity). The mean probability for elevated blood pressure was higher among currently working adolescents compared to those who were not. Findings were statistically significant (p < 0.05) at baseline. The findings illustrate that a large proportion of adolescents along the Texas-Mexico border may have elevated blood pressure and that working may be associated with it. Subsequent research is needed to confirm these findings, as well as to identify the mechanism for how work may increase hypertension in adolescents.

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 research is 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. Keywords: Adolescents, occupational injury, substance use, INTRODUCTION A substantial number of adolescents are working currently in the United States (1). The Bureau of Labor Statistics (BLS) reported that on average each month during the school year [...]

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]

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]

Accelerated failure time model is a popular model to analyze censored time-to-event data. Analysis of this model without assuming any parametric distribution for the model error is challenging, and the model complexity is enhanced in the presence of large number of covariates. We developed a nonparametric Bayesian method for regularized estimation of the regression parameters in a flexible accelerated failure time model. The novelties of our method lie in modeling the error distribution of the accelerated failure time nonparametrically, modeling the variance as a function of the mean, and adopting a variable selection technique in modeling the mean. The proposed method allowed for identifying a set of important regression parameters, estimating survival probabilities, and constructing credible intervals of the survival probabilities. We evaluated operating characteristics of the proposed method via simulation studies. Finally, we apply our new comprehensive method to analyze the motivating breast cancer data from the Surveillance, Epidemiology, and End Results Program, and estimate the five-year survival probabilities for women included in the Surveillance, Epidemiology, and End Results database who were diagnosed with breast cancer between 1990 and 2000. [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]

Objective: To honor Tom Waters's work on emerging occupational health issues, we review the literature on physical along with chemical exposures and their impact on functional outcomes.Background: Many occupations present the opportunity for exposure to multiple hazardous exposures, including both physical and chemical factors. However, little is known about how these different factors affect functional ability and injury. The goal of this review is to examine the relationships between these exposures, impairment of the neuromuscular and musculoskeletal systems, functional outcomes, and health problems with a focus on acute injury.Method: Literature was identified using online databases, including PubMed, Ovid Medline, and Google Scholar. References from included articles were searched for additional relevant articles.Results: This review documented the limited existing literature that discussed cognitive impairment and functional disorders via neurotoxicity for physical exposures (heat and repetitive loading) and chemical exposures (pesticides, volatile organic compounds [VOCs], and heavy metals).Conclusion: This review supports that workers are exposed to physical and chemical exposures that are associated with negative health effects, including functional impairment and injury. Innovation in exposure assessment with respect to quantifying the joint exposure to these different exposures is especially needed for developing risk assessment models and, ultimately, preventive measures.Application: Along with physical exposures, chemical exposures need to be considered, alone and in combination, in assessing functional ability and occupationally related injuries. [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]