Characterizing the Neurodevelopmental Pesticide Exposome in a Children's Agricultural Cohort

Leveraging Administrative Health Databases to Address Health Challenges in Farming Populations: Scoping Review and Bibliometric Analysis (1975-2024)

BACKGROUND

Although agricultural health has gained importance, to date, much of the existing research relies on traditional epidemiological approaches that often face limitations related to sample size, geographic scope, temporal coverage, and the range of health events examined. To address these challenges, a complementary approach involves leveraging and reusing data beyond its original purpose. Administrative health databases (AHDs) are increasingly reused in population-based research and digital public health, especially for populations such as farmers, who face distinct environmental risks.

OBJECTIVE

We aimed to explore the reuse of AHDs in addressing health issues within farming populations by summarizing the current landscape of AHD-based research and identifying key areas of interest, research gaps, and unmet needs.

METHODS

We conducted a scoping review and bibliometric analysis using PubMed and Web of Science. Building upon previous reviews of AHD-based public health research, we conducted a comprehensive literature search using 72 terms related to the farming population and AHDs. To identify research hot spots, directions, and gaps, we used keyword frequency, co-occurrence, and thematic mapping. We also explored the bibliometric profile of the farming exposome by mapping keyword co-occurrences between environmental factors and health outcomes.

RESULTS

Between 1975 and April 2024, 296 publications across 118 journals, predominantly from high-income countries, were identified. Nearly one-third of these publications were associated with well-established cohorts, such as Agriculture and Cancer and Agricultural Health Study. The most frequently used AHDs included disease registers (158/296, 53.4%), electronic health records (124/296, 41.9%), insurance claims (106/296, 35.8%), population registers (95/296, 32.1%), and hospital discharge databases (41/296, 13.9%). Fifty (16.9%) of 296 studies involved >1 million participants. Although a broad range of exposure proxies were used, most studies (254/296, 85.8%) relied on broad proxies, which failed to capture the specifics of farming tasks. Research on the farming exposome remains underexplored, with a predominant focus on the specific external exposome, particularly pesticide exposure. A limited range of health events have been examined, primarily cancer, mortality, and injuries.

CONCLUSIONS

The increasing use of AHDs holds major potential to advance public health research within farming populations. However, substantial research gaps persist, particularly in low-income regions and among underrepresented farming subgroups, such as women, children, and contingent workers. Emerging issues, including exposure to per- and polyfluoroalkyl substances, biological agents, microbiome, microplastics, and climate change, warrant further research. Major gaps also persist in understanding various health conditions, including cardiovascular, reproductive, ocular, sleep-related, age-related, and autoimmune diseases. Addressing these overlooked areas is essential for comprehending the health risks faced by farming communities and guiding public health policies. Within this context, promoting AHD-based research, in conjunction with other digital data sources (eg, mobile health, social health data, and wearables) and artificial intelligence approaches, represents a promising avenue for future exploration.

Assessing How Social Exposures Are Integrated in Exposome Research: A Scoping Review

BACKGROUND

Exposome research aims to describe and understand the extent to which all the exposures in human environments may affect our health over the lifetime. However, the way in which humans interact with their environment is socially patterned. Failing to account for social factors in research exploring the exposome may underestimate the magnitude of the effect of exposures or mask inequalities in the distribution of both exposures and outcomes.

OBJECTIVES

We aimed to describe the extent to which social factors appear in the exposome literature, the manner in which they are used in empirical analyses and statistical modeling, and the way in which they are considered in the overall scientific approach.

METHODS

We conducted a scoping review of the literature using three databases (PubMed, Embase, and Web of Science) up to January 2022. We grouped studies based on the way in which the social variables were used in the analyses and quantified the type and frequency of social variables mentioned in the articles. We also qualitatively described the scientific approach used by authors to integrate social variables.

RESULTS

We screened 1,001 records, and 73 studies were included in the analysis. Fifty-five (∼ 75 % ) used social variables as exposures or confounders or both, and a wide array of social variables were represented in the articles. Individual-level social variables were more often found, especially education and race/ethnicity, as well as neighborhood-level deprivation indices. Half of the studies used a hypothesis-free approach and the other half, a hypothesis-driven approach. However, in the latter group, of 35 studies, only 8 reported and discussed at least one possible social mechanism underlying the relationship observed between the social variable and the outcome.

DISCUSSION

Social factors in exposome research should be considered in a more systematic way, considering their role in structuring both the specific external and the internal exposome. Doing so could help to understand the mechanisms of construction and, potentially, alleviate social inequalities in health and mitigate the emergence of new ones. https://doi.org/10.1289/EHP11015.

Pesticides in doormat and floor dust from homes close to treated fields: Spatio-temporal variance and determinants of occurrence and concentrations

Indoor dust has been postulated as an important matrix for residential pesticide exposure. However, there is a lack of information on presence, concentrations and determinants of multiple pesticides in dust in residential homes close to treated fields. Our objective was to characterize the spatial and temporal variance of pesticides in house dust, study the use of doormats and floors as proxies for pesticides in indoor dust and identify determinants of occurrence and concentrations. Homes within 250 m from selected bulb fields were invited to participate. Homes within 20 km from these fields but not having agricultural fields within 500 m were selected as controls. House dust was vacuumed in all homes from floors (VFD) and from newly placed clean doormats (DDM). Sampling was done during two periods, when pesticides are used and not-used. For determination of 46 prioritized pesticides, a multi-residue extraction method was used. Most statistical analyses are focused on the 12 and 14 pesticides that were detected in >40% of DDM and VFD samples, respectively. Mixed models were used to evaluate relationships between possible determinants and pesticides occurrence and concentrations in DDM and VFD. 17 pesticides were detected in more than 50% of the homes in both matrixes. Concentrations differed by about a factor five between use and non-use periods among homes within 250 m of fields and between these homes and controls. For 7 pesticides there was a moderate to strong correlation (Spearman rho 0.30-0.75) between concentrations in DDM and VFD. Distance to agricultural fields and air concentrations were among the most relevant predictors for occurrence and levels of a given pesticide in DDM. Concentrations in dust are overall higher during application periods and closer to fields (<250 m) than further away. The omnipresence of pesticides in dust lead to residents being exposed all year round.

Multiple neonicotinoids in children's cerebro-spinal fluid, plasma, and urine

BACKGROUND

Neonicotinoids (NN) are selective neurotoxic pesticides that bind to insect but also mammal nicotinic acetycholine receptors (nAChRs). As the most widely used class of insecticides worldwide, they are ubiquitously found in the environment, wildlife, and foods, and thus of special concern for their impacts on the environment and human health. nAChRs are vital to proper brain organization during the prenatal period and play important roles in various motor, emotional, and cognitive functions. Little is known on children's contamination by NN. In a pilot study we tested the hypothesis that children's cerebro-spinal fluid (CSF) can be contaminated by NN.

METHODS

NN were analysed in leftover CSF, blood, and urine samples from children treated for leukaemias and lymphomas and undergoing therapeutic lumbar punctions. We monitored all neonicotinoids approved on the global market and some of their most common metabolites by ultra-high performance liquid chromatography-tandem mass spectrometry.

RESULTS

From August to December 2020, 14 children were consecutively included in the study. Median age was 8 years (range 3-18). All CSF and plasma samples were positive for at least one NN. Nine (64%) CSF samples and 13 (93%) plasma samples contained more than one NN. Thirteen (93%) CSF samples had N-desmethyl-acetamiprid (median concentration 0.0123, range 0.0024-0.1068 ng/mL), the major metabolite of acetamiprid. All but one urine samples were positive for ≥ one NN. A statistically significant linear relationship was found between plasma/urine and CSF N-desmethyl-acetamiprid concentrations.

CONCLUSIONS

We have developed a reliable analytical method that revealed multiple NN and/or their metabolites in children's CSF, plasma, and urine. Our data suggest that contamination by multiple NN is not only an environmental hazard for non-target insects such as bees but also potentially for children.

Pesticide exposure among Latinx child farmworkers in North Carolina

BACKGROUND

Although pesticides have adverse effects on child health and development, little research has examined pesticide exposure among child farmworkers. This analysis addresses two specific aims: (1) describes pesticide exposure among Latinx child farmworkers in North Carolina, and (2) delineates factors associated with this pesticide exposure.

METHODS

In 2018 (n = 173) and 2019 (n = 156) Latinx child farmworkers completed interviews and wore silicone wristbands for a single day to measure pesticide exposure. Wristbands were analyzed for 70 pesticides.

RESULTS

Most Latinx child farmworkers were exposed to multiple pesticides; the most frequent were pyrethroids (69.9% in 2018, 67.9% in 2019), organochlorines (51.4% in 2018, 55.1% in 2019), and organophosphates (51.4% in 2018, 34.0% in 2019). Children were exposed to a mean of 2.15 pesticide classes in 2018 and 1.91 in 2019, and to a mean of 4.06 pesticides in 2018 and 3.34 in 2019. Younger children (≤15 years) had more detections than older children; children not currently engaged in farm work had more detections than children currently engaged in farm work. Migrant child farmworkers had more detections than nonmigrants. For specific pesticides with at least 20 detections, detections and concentrations were generally greater among children not currently engaged in farm work than children currently engaged.

CONCLUSIONS

Children who live in farmworker communities are exposed to a plethora of pesticides. Although further research is needed to document the extent of pesticide exposure and its health consequences, sufficient information is available to inform the policy needed to eliminate this pesticide exposure in agricultural communities.

Effects of pyrethroids on brain development and behavior: Deltamethrin

Deltamethrin (DLM) is a Type II pyrethroid pesticide widely used in agriculture, homes, public spaces, and medicine. Epidemiological studies report that increased pyrethroid exposure during development is associated with neurobehavioral disorders. This raises concern about the safety of these chemicals for children. Few animal studies have explored the long-term effects of developmental exposure to DLM on the brain. Here we review the CNS effects of pyrethroids, with emphasis on DLM. Current data on behavioral and cognitive effects after developmental exposure are emphasized. Although, the acute mechanisms of action of DLM are known, how these translate to long-term effects is only beginning to be understood. But existing data clearly show there are lasting effects on locomotor activity, acoustic startle, learning and memory, apoptosis, and dopamine in mice and rats after early exposure. The most consistent neurochemical findings are reductions in the dopamine transporter and the dopamine D1 receptor. The data show that DLM is developmentally neurotoxic but more research on its mechanisms of long-term effects is needed.

Pesticide exposure among Latinx children: Comparison of children in rural, farmworker and urban, non-farmworker communities

Personal pesticide exposure is not well characterized among children in vulnerable, immigrant communities. We used silicone wristbands in 2018-2019 to assess pesticide exposure in 8 year old Latinx boys and girls in rural, farmworker families (n = 73) and urban, non-farmworker families (n = 60) living in North Carolina who were enrolled in the PACE5 Study, a community-based participatory research study. We determined the detection and concentrations (ng/g) of 75 pesticides and pesticide degradation products in the silicone wristbands worn for one week using gas chromatography electron capture detection and employed gas chromatography mass spectrometry. Differences by personal and family characteristics were tested using analysis of variance or Wilcoxon Rank Sum tests when necessary. Pesticide concentrations above the limit of detection were analyzed, and reported as geometric means and 95% confidence intervals (CI). The most frequently detected pesticide classes were organochlorines (85.7%), pyrethroids (65.4%), and organophosphates (59.4%), with the most frequently detected specific pesticides being alpha-chlordane (69.2%), trans-nonachlor (67.7%), gamma-chlordane (66.2%), chlorpyrifos (54.9%), cypermethrin (49.6%), and trans-permethrin (39.1%). More of those children in urban, non-farmworker families had detections of organochlorines (93.3% vs. 79.5, p = 0.0228) and pyrethroids (75.0% vs. 57.5%, p = 0.0351) than did those in rural, farmworker families; more children in rural, farmworker families had detections for organophosphates (71.2% vs. 45.0%, p= 0.0022). Children in urban, non-farmworker families had greater concentrations of alpha-chlordane (geometric mean (GM) 18.98, 95% CI 14.14, 25.47 vs. 10.25, 95% CI 7.49, 14.03; p= 0.0055) and dieldrin (GM 17.38, 95% CI 12.78 23.62 vs. 8.10, 95% CI 5.47, 12.00; p= 0.0034) than did children in rural, farmworker families. These results support the position that pesticides are ubiquitous in the living environment for children in vulnerable, immigrant communities, and argue for greater effort in documenting the widespread nature of pesticide exposure among children, with greater effort to reduce pesticide exposure.

Bayesian Profile Regression to Deal With Multiple Highly Correlated Exposures and a Censored Survival Outcome. First Application in Ionizing Radiation Epidemiology

As multifactorial and chronic diseases, cancers are among these pathologies for which the exposome concept is essential to gain more insight into the associated etiology and, ultimately, lead to better primary prevention strategies for public health. Indeed, cancers result from the combined influence of many genetic, environmental and behavioral stressors that may occur simultaneously and interact. It is thus important to properly account for multifactorial exposure patterns when estimating specific cancer risks at individual or population level. Nevertheless, the risk factors, especially environmental, are still too often considered in isolation in epidemiological studies. Moreover, major statistical difficulties occur when exposures to several factors are highly correlated due, for instance, to common sources shared by several pollutants. Suitable statistical methods must then be used to deal with these multicollinearity issues. In this work, we focused on the specific problem of estimating a disease risk from highly correlated environmental exposure covariates and a censored survival outcome. We extended Bayesian profile regression mixture (PRM) models to this context by assuming an instantaneous excess hazard ratio disease sub-model. The proposed hierarchical model incorporates an underlying truncated Dirichlet process mixture as an attribution sub-model. A specific adaptive Metropolis-Within-Gibbs algorithm-including label switching moves-was implemented to infer the model. This allows simultaneously clustering individuals with similar risks and similar exposure characteristics and estimating the associated risk for each group. Our Bayesian PRM model was applied to the estimation of the risk of death by lung cancer in a cohort of French uranium miners who were chronically and occupationally exposed to multiple and correlated sources of ionizing radiation. Several groups of uranium miners with high risk and low risk of death by lung cancer were identified and characterized by specific exposure profiles. Interestingly, our case study illustrates a limit of MCMC algorithms to fit full Bayesian PRM models even if the updating schemes for the cluster labels incorporate label-switching moves. Then, although this paper shows that Bayesian PRM models are promising tools for exposome research, it also opens new avenues for methodological research in this class of probabilistic models.