Risk Factors for Brain Health in Agricultural Work: A Systematic Review

The plantation system and the roots of the southern rural mortality penalty in the northern Blackland Prairies of Texas

In recent decades, public health researchers have observed that the health of rural people has declined relative to the health of urban people in the United States. This disparity in health and life expectancy across the rural/urban divide has been described as the Rural Mortality Penalty. However, public health researchers have also noted that health and life expectancies are not uniform across the rural United States, but vary according to race, sex, gender, and other factors. Rural health disparities also vary geospatially and are especially pronounced in the American South, leading to recent calls for greater attention to the structural factors that shape the health of rural Southerners. In this study, we take an anthropological and historically explicit approach to study the impacts of systemic violence on rural health. Specifically, we focus on farm labor within the plantation system as a context where geospatial, racial, and sexual differences in mortality, often studied in isolation, find a common historical source. Here we analyze vital records data from the post-emancipation period in the Blackland Prairies ecoregion of Texas, a period when emerging forms of plantation labor such as tenant farming, convict leasing, and migrant labor were being developed to maintain the plantation economy after the abolishment of chattel slavery. We find that the plantation system remains a strong predictor of differential mortalities in rural Texas, accounting for nearly all the variation that exists across the rural/urban divide and elucidating the complex interactions of race, sex, labor, and health in the rural South.

Farming activity and risk of treated thyroid disorders: Insights from the TRACTOR project, a nationwide cohort study

BACKGROUND

Epidemiological data regarding thyroid diseases are lacking, in particular for occupationally exposed populations.

OBJECTIVES

To compare the risk of hypothyroidism and hyperthyroidism between farming activities within the complete population of French farm managers (FMs).

METHODS

Digital health data from retrospective administrative databases, including insurance claims and electronic health/medical records, was employed. This cohort data spanned the entirety of French farm managers (FMs) who had undertaken work at least once from 2002 to 2016. Survival analysis with the time to initial medication reimbursement as timescale was used to examine the association (hazard ratio, HR) between 26 specific farming activities and both treated hypothyroidism and hyperthyroidism. A distinct model was developed for each farming activity, comparing FMs who had never engaged in the specific farming activity between 2002 and 2016 with those who had. All analyses were adjusted for potential confounders (e.g., age), and sensitivity analyses were conducted.

RESULTS

Among 1088561 FMs (mean age 46.6 [SD 14.1]; 31% females), there were 31834 hypothyroidism cases (75% females) and 620 hyperthyroidism cases (67% females), respectively. The highest risks were observed for cattle activities for both hyperthyroidism (HR ranging from 1.75 to 2.42) and hypothyroidism (HR ranging from 1.41 to 1.44). For hypothyroidism, higher risks were also observed for several animal farming activities (pig, poultry, and rabbit), as well as fruit arboriculture (HR = 1.22 [1.14-1.31]). The lowest risks were observed for activities involving horses. Sex differences in the risk of hypothyroidism were observed for eight activities, with the risk being higher for males (HR = 1.09 [1.01-1.20]) than females in viticulture (HR = 0.97 [0.93-1.00]). The risk of hyperthyroidism was two times higher for male dairy farmers than females.

DISCUSSION

Our findings offer a comprehensive overview of thyroid disease risks within the FM community. Thyroid ailments might not stem from a single cause but likely arise from the combined effects of various causal agents and triggering factors (agricultural exposome). Further investigation into distinct farming activities-especially those involving cattle-is essential to pinpoint potential risk factors that could enhance thyroid disease monitoring in agriculture.

Machine learning and XAI approaches highlight the strong connection between O 3 and N O 2 pollutants and Alzheimer's disease

Alzheimer's disease (AD) is the most common type of dementia with millions of affected patients worldwide. Currently, there is still no cure and AD is often diagnosed long time after onset because there is no clear diagnosis. Thus, it is essential to study the physiology and pathogenesis of AD, investigating the risk factors that could be strongly connected to the disease onset. Despite AD, like other complex diseases, is the result of the combination of several factors, there is emerging agreement that environmental pollution should play a pivotal role in the causes of disease. In this work, we implemented an Artificial Intelligence model to predict AD mortality, expressed as Standardized Mortality Ratio, at Italian provincial level over 5 years. We employed a set of publicly available variables concerning pollution, health, society and economy to feed a Random Forest algorithm. Using methods based on eXplainable Artificial Intelligence (XAI) we found that air pollution (mainly O 3 and N O 2 ) contribute the most to AD mortality prediction. These results could help to shed light on the etiology of Alzheimer's disease and to confirm the urgent need to further investigate the relationship between the environment and the disease.

Agricultural activities and risk of Alzheimer's disease: the TRACTOR project, a nationwide retrospective cohort study

Data regarding Alzheimer's disease (AD) occurrence in farming populations is lacking. This study aimed to investigate whether, among the entire French farm manager (FM) workforce, certain agricultural activities are more strongly associated with AD than others, using nationwide data from the TRACTOR (Tracking and monitoring occupational risks in agriculture) project. Administrative health insurance data (digital electronic health/medical records and insurance claims) for the entire French agricultural workforce, over the period 2002-2016, on the entire mainland France were used to estimate the risk of AD for 26 agricultural activities with Cox proportional hazards model. For each analysis (one for each activity), the exposed group included all FMs that performed the activity of interest (e.g. crop farming), while the reference group included all FMs who did not carry out the activity of interest (e.g. FMs that never farmed crops between 2002 and 2016). There were 5067 cases among 1,036,069 FMs who worked at least one year between 2002 and 2016. Analyses showed higher risks of AD for crop farming (hazard ratio (HR) = 3.72 [3.47-3.98]), viticulture (HR = 1.29 [1.18-1.42]), and fruit arboriculture (HR = 1.36 [1.15-1.62]). By contrast, lower risks of AD were found for several animal farming types, in particular for poultry and rabbit farming (HR = 0.29 [0.20-0.44]), ovine and caprine farming (HR = 0.50 [0.41-0.61]), mixed dairy and cow farming (HR = 0.46 [0.37-0.57]), dairy farming (HR = 0.67 [0.61-0.73]), and pig farming (HR = 0.30 [0.18-0.52]). This study shed some light on the association between a wide range of agricultural activities and AD in the entire French FMs population.

Research of Pesticide Metabolites in Human Brain Tumor Tissues by Chemometrics-Based Gas Chromatography-Mass Spectrometry Analysis for a Hypothetical Correlation between Pesticide Exposure and Risk Factor of Central Nervous System Tumors

Pesticides are widely used, resulting in continuing human exposure with potential health impacts. Some exposures related to agricultural works have been associated with neurological disorders. Since the 2000s, the hypothesis of the role of pesticides in the occurrence of central nervous system (CNS) tumors has been better documented in the literature. However, the etiology of childhood brain cancers still remains largely unknown. The major objective of this work was to assess the potential role of pesticide exposure as a risk factor for CNS tumors based on questionnaires and statistical analysis of information collected from patients hospitalized in the Neurosurgery Department of the Habib Bourguiba Hospital Medium in Sfax, Tunisia, during the period from January 1, 2022, to May 31, 2023. It also aimed to develop a simple and rapid analytical method by the gas chromatography-mass spectrometry technique for the research traces of pesticide metabolites in some collected human brain tumor tissues in order to more emphasize our hypothesis for such a correlation between pesticide exposure and brain tumor development. Patients with a history of high-risk exposure were selected to conduct further analysis. Chemometric methods were adapted to discern intrinsic variation between pathological and control groups and ascertain effective separation with the identification of differentially expressed metabolites accountable for such variations. Three samples revealed traces of pesticide metabolites that were mostly detected at an early age. The histopathological diagnosis was medulloblastoma for a 10-year-old child and high-grade gliomas for 27- and 35-year-old adults. The bivariate analyses (odds ratio >1 and P value <5%) confirmed the great probability of developing cancer by an exposure case. The Cox proportional hazards model revealed the risk of carcinogenicity beyond the age of 50 as a long-term effect of pesticide toxicity. Our study supports the correlation between pesticide exposure and the risk of development of human brain tumors, suggesting that preconception pesticide exposure, and possibly exposure during pregnancy, is associated with an increased childhood brain tumor risk. This hypothesis was enhanced in identifying traces of metabolites from the carbamate insecticide class known for their neurotoxicity and others from pyridazinone, organochlorines (OCs), triazole fungicide, and N-nitroso compounds known for their carcinogenicity. The 2D-OXYBLOT analysis confirmed the neurotoxicity effect of insecticides to induce oxidative damage in CNS cells. Aldicarb was implicated in brain carcinogenicity confirmed by the identification of oxime metabolites in a stress degradation study. Revealing "aziridine" metabolites from the OC class may better emphasize the theory of detecting traces of pesticide metabolites at an early age. Overall, our findings lead to the recommendation of limiting the residential use of pesticides and the support of public health policies serving this objective that we need to be vigilant in the postmarketing surveillance of human health impacts.