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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. 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. 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. 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. [ABSTRACT FROM AUTHOR]

In developing countries, subsistence gold mining entails mixing metallic mercury with crushed sediments to extract gold. In this approach, the gold−mercury amalgam is heated to evaporate mercury and obtain gold. Thus, the highly volatile mercury can be absorbed through inhalation, resulting in adverse health effects. Urinalysis can be used to detect mercury, which is excreted in urine and feces, and correlate exposure with toxic effects. The current gold standard analytical methods are based on fluorescence or inductively coupled plasma mass spectrometry methods, but are expensive, time consuming, and are not easily accessible in countries where testing is needed. In this work, we report on a miniature electrochemical sensor that can rapidly detect mercury in urine at levels well below the US Biological Exposure Index (BEI) limit of 50 ppb (μg/L). The sensor is based on a thin‐film gold electrode and anodic stripping voltammetry electroanalytical approach. The sensor successfully detected mercury at trace levels in urine, with a limit of detection of ∼15 ppb Hg in the linear range of 20–80 ppb. With the low‐cost disposable sensors and portable instrumentation, it is well suited for point‐of‐care applications. [ABSTRACT FROM AUTHOR]