Approximately 73% of the United States (US) population on public water systems receives fluoridated water for tooth decay prevention. In Los Angeles (LA) County, 89% of cities are at least partially fluoridated. Drinking water is the primary source of fluoride exposure in the US. Studies conducted in Mexico and Canada suggest that prenatal fluoride exposure, at levels relevant to the US, may contribute to poorer neurodevelopment in offspring. However, data on biomarkers and patterns of fluoride exposure among US pregnant women are scarce. This study examined urinary fluoride levels according to sociodemographic factors and metal co-exposures among pregnant women in the US.

Participants were from the Maternal and Developmental Risks from Environmental and Social Stressors (MADRES) cohort based in Los Angeles, California. There were 293 and 490 women with urine fluoride measured during the first and third trimesters of pregnancy, respectively. An intra-class correlation coefficient examined consistency of specific gravity-adjusted maternal urinary fluoride (MUFsg) between trimesters. Kruskal-Wallis and Mann-Whitney U tests examined associations of MUFsg with sociodemographic variables. Spearman correlations examined associations of MUFsg with blood and urine metals within and between trimesters. A False Discovery Rate (FDR) correction accounted for multiple comparisons. The criterion for statistical significance was an alpha of 0.05.

Participants were approximately 29 years old on average, and 80% were Hispanic or Latina. Median (IQR) MUFsg during trimesters one and three was 0.65 (0.5) mg/L and 0.8 (0.59) mg/L, respectively. MUFsg levels were moderately consistent between trimesters (N=292, ICC = 0.46, 95%CI: 0.32,0.57). Maternal age was positively associated with MUFsg during first (p = 0.16, p = 0.006) and third (p = 0.18, p < 0.001) trimesters. MUFsg differed by race/ethnicity during first and third trimesters (N = 293, H (3) = 7.99, p = 0.046; N = 486, H (3) = 25.31, p < 0.001, respectively). Specifically, MUFsg was higher for White, Non-Hispanic participants (first trimester Median (IQR) =1.03 (1.31) mg/L; third trimester Median (IQR) = 1.32 (1.24) mg/L) than for Hispanic participants in both trimesters (first trimester Median (IQR) =0.64 (0.48) mg/L; third trimester Median (IQR) = 0.76 (0.55) mg/L). Additionally, during trimester three, MUFsg was higher for White, Non-Hispanic participants than for Black Non-Hispanic participants (Median (IQR) = 0.82 (0.49) mg/L). MUFsg also differed by education during trimester one (N = 293, H (4) = 10.61, p = 0.031), and was higher for participants with some graduate training than for those with high school or some college/technical school education (ps = 0.03 and 0.04, respectively). After FDR correction, MUFsg was associated with blood lead (N =91, p = 0.29, p = 0.024) and urinary cadmium (N =279, p = 0.19, p = 0.042), copper (N=279, p = 0.16, p = 0.042), and tungsten (N=279, p = 0.16, p = 0.049) during trimester three.

Consistent with studies conducted in Canada and Mexico, MUFsg increased across pregnancy. Lower MUFsg among Hispanic and Non-Hispanic Black participants may reflect lower tap water consumption. Metal co-exposures are important to consider when examining potential neurodevelopmental impacts of fluoride.

Exposure to toxic chemicals during early brain development increases the risk of neurodevelopmental problems in children. Parents' and prospective parents' understanding of the impact of toxic chemicals on brain development and the efficacy of translation tools for children's environmental health literacy are poorly understood. We developed and validated a questionnaire, PRevention of Toxic chemicals in the Environment for Children Tool (PRoTECT) to assess knowledge of toxic chemicals and neurodevelopment, intentions to reduce exposures to toxic chemicals, and preferences for actions by government and industry to prevent neurodevelopmental disorders. Using PRoTECT, we surveyed people of child-bearing age across five countries (Canada, United States (US), United Kingdom (UK), India, and Australia) to identify general patterns of responses on this questionnaire by demographic characteristics, including country, age, gender, parental status, pregnancy status, and education. We also employed a randomized control design to examine the efficacy of a knowledge translation video to instill knowledge and prompt behavioral changes to reduce exposures to toxic chemicals immediately following its presentation and after a six-week follow-up period.

We recruited 15,594 participants, ages 18 to 45, via CloudResearch's Prime Panels between October-December 2021. After completing the PRoTECT survey, participants were randomly assigned to watch the video Little Things Matter: Impact of Toxic Chemicals on Brain Development (i.e., the experimental group) or to serve as the control group. Next, both groups answered a series of questions to assess their knowledge of toxic chemicals, their intentions to reduce exposures to toxic chemicals, and barriers to changing their behaviours. After six-weeks, we recontacted a subset (N=4,842) of participants to repeat PRoTECT and answer the same series of behavioural questions assessing whether they modified any of their behaviours to reduce exposure and why or why not.

Most participants (i.e., 75-85%) agreed that toxic chemicals can impact brain development and endorsed preferences (∼85%) for allocating more resources to prevent neurodevelopmental disorders, especially people with higher education, parents and pregnant women, and people who lived in India. Despite this, a large proportion of participants (∼50%) trusted industry and believed that government effectively regulated toxic chemicals. After the six-week follow-up, experimental participants showed greater changes in scores on PRoTECT (i.e., between 5-15% change), indicating greater knowledge about harms posed by toxic chemicals, more intentions to reduce exposure, and stronger preferences for prevention as compared to the control group. Differences were larger among people from the US, those who were more highly educated, and people in their thirties. However, the differences between groups in making behavioural changes to reduce exposures were attenuated at the six-week follow up as compared to baseline. Significant barriers to reduce exposure to toxic chemicals were reported by both groups and included cost, inconvenience, and not knowing how to determine whether a product is non-toxic or where to purchase non-toxic products.

We observed greater knowledge and concerns about toxic chemicals among more affluent respondents, pregnant women and parents, and people living in India across both groups. While the video enhanced participants' knowledge about toxic chemicals and intentions to reduce exposure, they indicated that barriers hindered them from making behavioral changes.

Agricultural workers are immersed in environments associated with increased risk for adverse psychiatric and neurological outcomes. Agricultural work-related risks to brain health include exposure to pesticides, heavy metals, and organic dust. Despite this, there is a gap in our understanding of the underlying brain systems impacted by these risks. This study explores clinical and cognitive domains, and functional brain activity in agricultural workers. We hypothesized that a history of agricultural work-related risks would be associated with poorer clinical and cognitive outcomes as well as changes in functional brain activity within cortico-striatal regions.

The sample comprised 17 agricultural workers and a comparison group of 45 non-agricultural workers recruited in the Northern Colorado area. All participants identified as White and non-Hispanic. The mean age of participants was 51.7 years (SD = 21.4, range 18-77), 60% identified as female, and 37% identified as male. Participants completed the National Institute of Health Toolbox (NIH Toolbox) and Montreal Cognitive Assessment (MoCA) on their first visit. During the second visit, they completed NIH Patient-Reported Outcomes Measurement Information System (PROMIS) measures and underwent functional magnetic resonance imaging (fMRI; N = 15 agriculture and N = 35 non-agriculture) while completing a working memory task (Sternberg). Blood oxygen-level dependent (BOLD) response was compared between participants. Given the small sample size, the whole brain voxel-wise group comparison threshold was set at alpha = .05, but not otherwise corrected for multiple comparisons. Cohen’s d effect sizes were estimated for all voxels.

Analyses of cognitive scores showed significant deficits in episodic memory for the agricultural work group. Additionally, the agricultural work group scored higher on measures of self-reported anger, cognitive concerns, and social participation. Analyses of fMRI data showed increased BOLD activity around the orbitofrontal cortex (medium to large effects) and bilaterally in the entorhinal cortex (large effects) for the agricultural work group. The agricultural work group also showed decreased BOLD activity in the cerebellum and basal ganglia (medium to large effects).

To our knowledge, this study provides the first-ever evidence showing differences in brain activity associated with a history of working in agriculture. These findings of poorer memory, concerns about cognitive functioning, and increased anger suggest clinical relevance. Social participation associated with agricultural work should be explored as a potential protective factor for cognition and brain health. Brain imaging data analyses showed increased activation in areas associated with motor functioning, cognitive control, and emotion. These findings are limited by small sample size, lack of diversity in our sample, and coarsely defined risk. Despite these limitations, the results are consistent with an overall concern that risks associated with agricultural work can lead to cognitive and psychiatric harm via changes in brain health. Replications and future studies with larger sample sizes, more diverse participants, and more accurately defined risks (e.g., pesticide exposure) are needed.

Evidence has shown that the environment is an often overlooked social determinant of health (SDoH) of emotional, neural, and cognitive development. Aspects of the built environment relate to health factors and equity in living conditions, and may contribute to racial, ethnic, or economic health disparities. For example, urbanicity is linked with negative factors including less access to green space (i.e. gray space), increase in air pollution, temperatures, and socio-economic inequalities. While there is existing research on access to green space on some mental health and cognitive outcomes, there is limited research on the presence of gray space linked with cognitive functioning in youth. While some studies have shown that aspects of the neighborhood environment (e.g. access to healthy food, air pollution, heat exposure, and walkability) can impact neural and cognitive functioning, few to date have disentangled unique contributions of these factors in a large, national cohort. Therefore, the aim of the present study was to identify the best fitting model testing multiple SDoHs related to gray space on overall cognitive functioning in youth enrolled in the Adolescent Brain Cognitive Development (ABCD) Study.

Using baseline data (n = 8,802) from ABCD 4.0 data, this study used environmental measures and linked external databases to characterize SDoH variables predicting youths’ cognitive functioning via the NIH Toolbox (e.g. total cognitive composite score). This study used geospatial mapping to estimate exposure to air pollutants and heat. Additionally, the National Walkability Index was linked to assess walkability of neighborhood. Exposure to gray space (e.g. impervious surfaces) and access to healthy food were assessed via the Child Opportunity Index 2.0. An exhaustive search for the best subsets of these variables (gray space, access to healthy food, walkability, air pollution, and heat exposure) predicting cognitive performance was run to examine the best fitting model based on adjusted R2, using the 'leaps’ package in R. Then, a multiple linear mixed effects regression model, using the lmer package in R, was fitted adjusting for various and relevant demographic factors.

The results of the regression indicated that walkability index (F(1, 1322.4) = 11.07, p < 0.001) and heat exposure (F(1, 81.1) = 5.54, p < 0.001) explained a significant amount of the variance (Adjusted R2 = 20%) predicting total cognitive performance while controlling for sex, age, household income, parent education, marital status, family relatedness, and site.

Findings suggest that walkability of the neighborhood and heat exposure may play a role in cognitive development over and above other SDoHs and demographic factors. However, this study was limited to baseline assessment and a single measurement of total composite cognitive score, thus it is crucial for future research to investigate relationships over the life course across cognitive domains to further clarify these findings. The present study can help inform future public policy on improving lived and built environments, which may aid in supporting cognitive development in youth. These findings identify key factors, walkability and heat exposure, to consider when investigating the interaction between poverty, health, and environmental justice.

Veterans from the 1991 Gulf War (GW) experienced several neurotoxicant exposures, including chemical weapons, pesticide sprays and creams, oil well fires and pyridostigmine bromide anti-nerve gas pills during the war. Research has shown these exposures to affect cognition and mood. Moreover, MR diffusion imaging has shown microstructural changes in the white matter that may be related to psychomotor slowing. Over a third of all GW veterans suffer from a chronic multi-symptom disorder called Gulf War Illness (GWI). The Kansas Criteria for GWI consists of six distinct criteria including symptoms of fatigue/sleep problems, pain symptoms, neurologic/cognitive/mood symptoms, gastrointestinal symptoms, respiratory symptoms, and skin symptoms. The Boston Gulf War Illness Consortium (GWIC) was a multi-site study designed to assess symptoms of GWI. After the conclusion of the GWIC study, the Boston Biorepository Recruitment and Integrative Network for Gulf War Illness (BBRAIN) was developed to harmonize retrospectively collected GW Veteran data while simultaneously collecting Time 2 data and samples from GW veterans who participated in the original study. This analysis includes the first 58 participants who have completed the GWIC study and the BBRAIN study.

We conducted a longitudinal analysis of cognitive outcomes from the BBRAIN data repository. Verbal learning, memory, attention, and executive functioning were assessed using neuropsychological tests including the Continuous Performance Test (CPT3), Trail Making Test A, Delis-Kaplan Executive Function System (DKEFS), California Verbal Learning Test (CVLT-II). A total of 58 participants were re-evaluated from the original GWIC cohort with a total of 47 cases and 11 controls. Paired t-tests for the cognitive measures were completed separately for GWI cases and healthy GW veteran controls for each of the neuropsychological test measures. Average time between assessments was four years.

The overall sample was on average 56 years old, 84% male and 75% White. The average level of education was 15 years. GWI cases showed significantly more commission errors and slower reaction times on the CPT3 at Time 2 compared to Time 1 (p < 0.05). Cases also showed a slowing in time to completion on Trails A at the second time point (p<0.05). On the other hand, controls only showed significantly slower reaction times on the CPT3 at Time 2 (p<0.05).

These results showed that veterans with GWI are showing more decline over time in cognitive functioning particularly on psychomotor slowing and impulsivity than control veterans. It is important to document illness trajectories for veterans with GWI in order to devise strategies for interventions and treatments. The importance of studying longitudinal cohorts is to document changes in the same individuals over time. The next steps are to assess if this accelerated aging develops into neurodegenerative conditions by using brain imaging and other biomarkers in addition to cognitive evaluations. This could identify individuals who should be the focus of targeted treatment strategies while there is still time to intervene.