Improving Private Well Testing Programs: Experimental Evidence from Iowa.

Approximately 23 million U.S. households rely on private wells for drinking water. This study first summarizes drinking water behaviors and perceptions from a large-scale survey of households that rely on private wells in Iowa. Few households test as frequently as recommended by public health experts. Around 40% of households do not regularly test, treat, or avoid their drinking water, suggesting pollution exposure may be widespread among this population. Next, we utilize a randomized control trial to study how nitrate test strips and information about a free, comprehensive water quality testing program influence households' behaviors and perceptions. The intervention significantly increased testing, including high-quality follow-up testing, but had limited statistically detectable impacts on other behaviors and perceptions. Households' willingness to pay for nitrate test kits and testing information exceeds program costs, suggesting that the intervention was welfare-enhancing.

A Teach-the-Teacher Module for Human Trafficking Bedside Instruction.

Introduction: Human trafficking (HT) is a public health issue that adversely affects patients' well-being. Despite the prevalence of trafficked persons in health care settings, a lack of educational modules exists for use in clinical contexts. We developed a 50-minute train-the-trainer module on HT. Methods: After piloting the workshop for faculty, fellows, and residents (n = 19) at the Society for Academic Emergency Medicine (SAEM) national conference, we implemented it in medical students' curricula during their emergency medicine clerkship at the University of Iowa (n = 162). We evaluated the worskhop by (a) a retrospective pre-post survey of self-reported ability to (1) define HT, (2) recognize high-risk signs, (3) manage situations with trafficked persons, and (4) teach others about HT, and (b) a 3-month follow-up survey to assess longitudinal behavior change. Results: In both contexts, results demonstrated improvement across all learning outcomes (pre-post differences of 1.5, 1.3, 1.9, and 1.7 on a 4-point Likert-type scale for each learning objective above, respectively, at the SAEM conference and 1.2, 1.0, 1.3, and 1.3 at the University of Iowa; p < .001 for all). In the 3-month follow-up, we observed statistically significant changes in self-reported consideration of and teaching about HT during clinical encounters among learners who had previously never done either (p < .001 and p = .006, respectively). Discussion: This train-the-trainer module is a brief and effective clinical tool for bedside teaching about HT, especially among people who have never previously considered HT in a clinical context.

Bovine Rhinitis B Virus Variant as the Putative Cause of Bronchitis in Goat Kids.

A diagnostic investigation into an outbreak of fatal respiratory disease among young goats in Iowa, USA revealed bronchitis lesions of unknown etiology and secondary bacterial bronchopneumonia. Hypothesis-free metagenomics identified a previously unreported picornavirus (USA/IA26017/2023), and further phylogenetic analysis classified USA/IA26017/2023 as an aphthovirus related to bovine rhinitis B virus. Viral nucleic acid was localized to lesions of bronchitis using in situ hybridization. This marks the first report of a picornavirus putatively causing respiratory disease in goats and highlights the potential for cross-species transmission of aphthoviruses.

An evaluation of statistical models of microcystin detection in lakes applied forward under varying climate conditions.

Algal blooms can threaten human health if cyanotoxins such as microcystin are produced by cyanobacteria. Regularly monitoring microcystin concentrations in recreational waters to inform management action is a tool for protecting public health; however, monitoring cyanotoxins is resource- and time-intensive. Statistical models that identify waterbodies likely to produce microcystin can help guide monitoring efforts, but variability in bloom severity and cyanotoxin production among lakes and years makes prediction challenging. We evaluated the skill of a statistical classification model developed from water quality surveys in one season with low temporal replication but broad spatial coverage to predict if microcystin is likely to be detected in a lake in subsequent years. We used summertime monitoring data from 128 lakes in Iowa (USA) sampled between 2017 and 2021 to build and evaluate a predictive model of microcystin detection as a function of lake physical and chemical attributes, watershed characteristics, zooplankton abundance, and weather. The model built from 2017 data identified pH, total nutrient concentrations, and ecogeographic variables as the best predictors of microcystin detection in this population of lakes. We then applied the 2017 classification model to data collected in subsequent years and found that model skill declined but remained effective at predicting microcystin detection (area under the curve, AUC ≥ 0.7). We assessed if classification skill could be improved by assimilating the previous years' monitoring data into the model, but model skill was only minimally enhanced. Overall, the classification model remained reliable under varying climatic conditions. Finally, we tested if early season observations could be combined with a trained model to provide early warning for late summer microcystin detection, but model skill was low in all years and below the AUC threshold for two years. The results of these modeling exercises support the application of correlative analyses built on single-season sampling data to monitoring decision-making, but similar investigations are needed in other regions to build further evidence for this approach in management application.

Mechanisms underlying episodic nitrate and phosphorus leaching from poorly drained agricultural soils.

Poorly drained depressions within tile-drained croplands can have disproportionate environmental and agronomic impacts, but mechanisms controlling nutrient leaching remain poorly understood. We monitored nitrate and soluble reactive phosphorus (SRP) leaching using zero-tension soil lysimeters across a depression to upland gradient over 2 years in a corn-soybean (Zea mays L.-Glycine max [L.] Merr.) field in Iowa. We also measured stable isotopes (δ15N and δ18O) of nitrate to examine its sources and transformations. SRP concentrations peaked during winter and early spring after phosphorus (P) fertilization (mean = 3 mg P L-1), with highest values in the depression, and SRP was relatively stable thereafter (mean = 0.3 mg P L-1) irrespective of periods of high soil moisture that led to widespread iron (Fe) reduction across the field. During a near-average precipitation year, nitrate stable isotopes indicated direct leaching of fertilizer nitrate within days of application, followed by nitrification of fertilizer ammonium and several weeks of denitrification in depressional soils. Nevertheless, nitrate concentrations remained high (mean = 28 mg N L-1) in the depression despite strong isotopic evidence for denitrification (>48% N removal). During a wet year, nitrate concentrations were lower in the depression than upland and nitrate isotopes were highly variable, consistent with nearly complete nitrate removal by denitrification in the depression and significant denitrification in upland soils. We conclude that poorly drained depressional soils can potentially decrease nitrate leaching via denitrification under sustained wet conditions, but they inconsistently denitrify and are vulnerable to high nitrate and SRP losses when soils are not saturated, especially following fertilization.

Predicting dental caries outcomes in young adults using machine learning approach.

OBJECTIVES: To predict the dental caries outcomes in young adults from a set of longitudinally-obtained predictor variables and identify the most important predictors using machine learning techniques. METHODS: This study was conducted using the Iowa Fluoride Study dataset. The predictor variables - sex, mother's education, family income, composite socio-economic status (SES), caries experience at ages 9, 13, and 17, and the cumulative estimates of risk and protective factors, including fluoride, dietary, and behavioral variables from ages 5-9, 9-13, 13-17, and 17-23 were used to predict the age 23 D2+MFS count. The following machine learning models (LASSO regression, generalized boosting machines (GBM), negative binomial (NegGLM), and extreme gradient boosting models (XGBOOST)) were compared under 5-fold cross validation with nested resampling techniques. RESULTS: The prevalence of cavitated level caries experience at age 23 (mean D2+MFS count) was 4.75. The predictive analysis found LASSO to be the best performing model (compared to GBM, NegGLM, and XGBOOST), with a root mean square error (RMSE) of 0.70, and coefficient of determination (R2) of 0.44. After dichotomization of the predicted and observed values of the LASSO regression, the classification results showed accuracy, precision, recall, and ROC AUC of 83.7%, 85.9%, 93.1%, 68.2%, respectively. Previous caries experience at age 13 and age 17 and sugar-sweetened beverages intakes at age 13 and age 17 were found to be the four most important predictors of cavitated caries count at age 23. CONCLUSION: Our machine learning model showed high accuracy and precision in the prediction of caries in young adults from a longitudinally-obtained predictor variables. Our model could, in the future, after further development and validation with other diverse population data, be used by public health specialists and policy-makers as a screening tool to identify the risk of caries in young adults and apply more targeted interventions. However, data from a more diverse population are needed to improve the quality and generalizability of caries prediction.

Relative impacts of Varroa destructor (Mesostigmata:Varroidae) infestation and pesticide exposure on honey bee colony health and survival in a high-intensity corn and soybean producing region in northern Iowa.

The negative effects of Varroa and pesticides on colony health and survival are among the most important concerns to beekeepers. To compare the relative contribution of Varroa, pesticides, and interactions between them on honey bee colony performance and survival, a 2-year longitudinal study was performed in corn and soybean growing areas of Iowa. Varroa infestation and pesticide content in stored pollen were measured from 3 apiaries across a gradient of corn and soybean production areas and compared to measurements of colony health and survival. Colonies were not treated for Varroa the first year, but were treated the second year, leading to reduced Varroa infestation that was associated with larger honey bee populations, increased honey production, and higher colony survival. Pesticide detections were highest in areas with high-intensity corn and soybean production treated with conventional methods. Pesticide detections were positively associated with honey bee population size in May 2015 in the intermediate conventional (IC) and intermediate organic (IO) apiaries. Varroa populations across all apiaries in October 2015 were negatively correlated with miticide and chlorpyrifos detections. Miticide detections across all apiaries and neonicotinoid detections in the IC apiary in May 2015 were higher in colonies that survived. In July 2015, colony survival was positively associated with total pesticide detections in all apiaries and chlorpyrifos exposure in the IC and high conventional (HC) apiaries. This research suggests that Varroa are a major cause of reduced colony performance and increased colony losses, and honey bees are resilient upon low to moderate pesticide detections.

Causes of Death in the Presence of Law Enforcement in Johnson County, Iowa, 2011-2020.

Objectives. To examine sudden and unexpected or trauma-related deaths that occurred in the presence of law enforcement in Johnson County, Iowa, between 2011 and 2020. Methods. We identified deaths in the presence of law enforcement using definitions from the National Association of Medical Examiners. We obtained data, including demographics, cause and manner of death, toxicology results, and circumstances and location of event leading to death, from comprehensive medical examiner investigative reports. Results. There were 165 deaths that occurred in the presence of law enforcement: 114 were from a known disease, and 51 were either trauma related or the sudden, unexpected initial presentation of a previously unrecognized disease. Three deaths occurred in the context of physical restraint by law enforcement. Suicide was the leading manner of death among trauma-related deaths; the means of suicide was predictable based on in-custody (hanging) or precustody (firearm) circumstances. Conclusions. Our findings highlight the potential role of medical examiners and coroners in improving completeness of data on reporting death in the presence of law enforcement to public health agencies. (Am J Public Health. 2024;114(6):642-650. https://doi.org/10.2105/AJPH.2024.307616).

Citizen science initiatives document biodiversity baselines at an urban lake.

Changes to biodiversity from urbanization are occurring worldwide, and baseline data is vital to document the magnitude and direction of these alterations. We set out to document the biodiversity of an urban lake in Eastern Iowa that was devoid of baseline data prior to a renovation project that will convert the site into a major area for human recreation. Throughout the course of one year, we studied the biodiversity at Cedar Lake utilizing the citizen-science application iNaturalist coupled with semi-structured BioBlitz events, which we compared to previous opportunistic observations at the site. From a semi-structured approach to document biodiversity with citizen science, our analyses revealed more diverse community metrics over a shorter period compared to more than a decade of prior observations.

Comparing modern identification methods for wild bees: Metabarcoding and image-based morphological taxonomic assignment.

With the decline of bee populations worldwide, studies determining current wild bee distributions and diversity are increasingly important. Wild bee identification is often completed by experienced taxonomists or by genetic analysis. The current study was designed to compare two methods of identification including: (1) morphological identification by experienced taxonomists using images of field-collected wild bees and (2) genetic analysis of composite bee legs (multiple taxa) using metabarcoding. Bees were collected from conservation grasslands in eastern Iowa in summer 2019 and identified to the lowest taxonomic unit using both methods. Sanger sequencing of individual wild bee legs was used as a positive control for metabarcoding. Morphological identification of bees using images resulted in 36 unique taxa among 22 genera, and >80% of Bombus specimens were identified to species. Metabarcoding was limited to genus-level assignments among 18 genera but resolved some morphologically similar genera. Metabarcoding did not consistently detect all genera in the composite samples, including kleptoparasitic bees. Sanger sequencing showed similar presence or absence detection results as metabarcoding but provided species-level identifications for cryptic species (i.e., Lasioglossum). Genus-specific detections were more frequent with morphological identification than metabarcoding, but certain genera such as Ceratina and Halictus were identified equally well with metabarcoding and morphology. Genera with proportionately less tissue in a composite sample were less likely to be detected using metabarcoding. Image-based methods were limited by image quality and visible morphological features, while genetic methods were limited by databases, primers, and amplification at target loci. This study shows how an image-based identification method compares with genetic techniques, and how in combination, the methods provide valuable genus- and species-level information for wild bees while preserving tissue for other analyses. These methods could be improved and transferred to a field setting to advance our understanding of wild bee distributions and to expedite conservation research.

Identifying predictors of COVID-related delays in cancer-specific medical care.

PURPOSE: Evidence of the impact of the COVID-19 pandemic on cancer prevention and control is growing, but little is known about patient-level factors associated with delayed care. We analyzed data from a survey focused on Iowan cancer patients' COVID-19 experiences in the early part of the pandemic. METHODS: Participants were recruited from the University of Iowa Holden Comprehensive Cancer Center's Patients Enhancing Research Collaborations at Holden (PERCH) program. We surveyed respondents on demographic characteristics, COVID-19 experiences and reactions, and delays in any cancer-related health care appointment, or cancer-related treatment appointments. Two-sided significance tests assessed differences in COVID-19 experiences and reactions between those who experienced delays and those who did not. RESULTS: There were 780 respondents (26% response), with breast, prostate, kidney, skin, and colorectal cancers representing the majority of respondents. Delays in cancer care were reported by 29% of respondents. In multivariable-adjusted models, rural residents (OR 1.47; 95% CI 1.03, 2.11) and those experiencing feelings of isolation (OR 2.18; 95% CI 1.37, 3.47) were more likely to report any delay, where experiencing financial difficulties predicted delays in treatment appointments (OR 5.72; 95% CI 1.96, 16.67). Health insurance coverage and concern about the pandemic were not statistically significantly associated with delays. CONCLUSION: These findings may inform cancer care delivery during periods of instability when treatment may be disrupted by informing clinicians about concerns that patients have during the treatment process. Future research should assess whether delays in cancer care impact long-term cancer outcomes and whether delays exacerbate existing disparities in cancer outcomes.

Predictors of survival of large non-occlusal non-incisal glass-ionomer restorations in older adults.

PURPOSE: This study aimed to investigate the predictors of survival of non-occlusal non-incisal glass-ionomer restorations as a surrogate for root surface restorations among older adults. METHODS: In a retrospective cohort analysis using the University of Iowa College of Dentistry electronic dental records, we included 721 patients aged 65+ who received 2+ surface non-occlusal non-incisal glass ionomer restorations placed from January 2005 - December 2011. Restorations were followed until September 2017 or until they were deemed to have failed. RESULTS: At baseline, participants' mean age was 77.6 ± 8.2 years, and 45.8% were females. Most patients were self-pay (65.2%). Most restorations were placed by residents and dental students (82.7%) and included only two surfaces (95.6%). About half (49.1%) failed during follow-up, with a median survival time of 3.7 years. The time ratio for lower incisors compared to other teeth was 0.6 (p = .006), for three-and-four-surface restorations compared to two was 0.7 (p = .007), for faculty as providers compared to residents and students was 1.4 (p = .039), and for the Geriatric & Special Needs Clinic compared to others was 0.8 (p = .013). Time ratios less than one indicate association with shorter durations for restorations, and time ratios greater than one indicate association with longer durations for restorations. CONCLUSION: Tooth type, number of restored surfaces, provider type, and clinic were all significant factors associated with survival of these restorations.

Summary of Roadway Incidents Involving Farm Equipment in Five Midwestern States Using the Fatality Analysis Reporting System (FARS).

Roadway incidents involving farm equipment is a growing area of concern among agricultural safety and health and public health professionals. The aim of this project was to evaluate the usefulness of the Fatality Analysis Reporting System (FARS) and analyze the number of roadway fatal incidents that involve farm equipment. Data collected from the FARS through the National Highway Traffic Safety Administration was used to summarize roadway incidents involving farm equipment. Cases from five midwestern states were analyzed from January to December 2020 using SPSS. Incidents involving farm equipment resulted in 25 cases with Iowa, Michigan, and Wisconsin all reporting six cases each. The most common manner of incidents were single-vehicle crashes and rear-ending incidents. Most of the events occurred during busy agricultural seasons, most often occurring in June and August with five cases each. The FARS dataset is a useful tool to identify cases, but it faces limitations, such as only reporting fatalities and lack of information on specific farm equipment involved in incidents. The results from the study are helpful to better understand roadway incidents and guide future intervention strategies.

Effects of deploying ethanol lures in tandem with generic pheromone lures for attraction of cerambycid beetles in field bioassays.

Male cerambycid beetles of the large subfamilies Cerambycinae and Lamiinae produce aggregation-sex pheromones that attract both sexes. The pheromones of many species are conserved among both closely related species (e.g., congeners) and more distantly related species (e.g., different subfamilies), including those endemic to different continents. This parsimony in pheromone structures suggests that multiple species may be attracted to traps baited with blends of pheromones, and such blends are finding use in delineating geographic ranges of native species and in surveillance programs for incursions of exotic species. Here, we present the results of a field experiment conducted at multiple sites in Iowa that tested the effects of deploying ethanol lures in tandem with a 6-component blend of common pheromone components for cerambycine and lamiine species and a 5-component blend that specifically targeted lamiines. Eight cerambycine species showed significant treatment effects, most of which were attracted to the 6-component blend, and ethanol increased attraction for half of these species. Two cerambycine species were attracted only by ethanol. Seven lamiine species were attracted by the lamiine-specific blend, alone or when combined with ethanol, and 3 of these species also were attracted to the 6-component blend. Taken together, these findings provide further evidence that carefully crafted blends of pheromones can be used to monitor the presence or abundance of multiple cerambycid species. Ethanol either increased the number of beetles attracted by pheromones or had no effect, so there is no apparent downside to deploying ethanol lures in combination with pheromones.

Firearm exposure and safety training of rural Iowa youth.

PURPOSE: Our objective was to investigate rural adolescents' use of firearms and whether they had received firearm training. METHODS: 2019 Iowa FFA Leadership Conference attendees were surveyed. Descriptive and comparative analyses were performed. RESULTS: One thousand three hundred and eighty-two FFA members aged 13-18 years participated. The vast majority (85%) had fired a rifle/shotgun; 58% reported firing them >20 times. Of those who had fired rifles/shotguns, 32% had done so before 9 years old; 79% before 13 years. Most had also fired a handgun (62%), with 30% having fired handguns >20 times. Of those who had fired handguns, 34% had done so before 11 years old. The average age for first firing rifles/shotguns was 10.1 (SD 2.9) years, and 11.9 (SD 2.8) years for handguns. Males, older teenagers, and those living on farms or in the country had significantly greater percentages that had fired a rifle/shotgun or a handgun. Greater proportions of males had used firearms >20 times and started firing them at younger ages. Over half (55%) reported having gone hunting. Of those, 24% first hunted before 9 years old; 48% before 11 years. Of those who had used a firearm, 61% had completed a firearm safety training course. For hunters, 80% had taken a course. CONCLUSIONS: Most participants had used firearms, and many did so at very young ages. Substantial numbers had not received formal training. The authors believe that families should be counseled when it is developmentally appropriate to introduce youth to firearms, and all should take firearm safety training before using them.

Nitrate exposure from drinking water and dietary sources among Iowa farmers using private wells.

Nitrate levels are increasing in water resources across the United States and nitrate ingestion from drinking water has been associated with adverse health risks in epidemiologic studies at levels below the maximum contaminant level (MCL). In contrast, dietary nitrate ingestion has generally been associated with beneficial health effects. Few studies have characterized the contribution of both drinking water and dietary sources to nitrate exposure. The Agricultural Health Study is a prospective cohort of farmers and their spouses in Iowa and North Carolina. In 2018-2019, we assessed nitrate exposure for 47 farmers who used private wells for their drinking water and lived in 8 eastern Iowa counties where groundwater is vulnerable to nitrate contamination. Drinking water and dietary intakes were estimated using the National Cancer Institute Automated Self-Administered 24-Hour Dietary Assessment tool. We measured nitrate in tap water and estimated dietary nitrate from a database of food concentrations. Urinary nitrate was measured in first morning void samples in 2018-19 and in archived samples from 2010 to 2017 (minimum time between samples: 2 years; median: 7 years). We used linear regression to evaluate urinary nitrate concentrations in relation to total nitrate, and drinking water and dietary intakes separately. Overall, dietary nitrate contributed the most to total intake (median: 97 %; interquartile range [IQR]: 57-99 %). Among 15 participants (32 %) whose drinking water nitrate concentrations were at/above the U.S. Environmental Protection Agency MCL (10 mg/L NO3-N), median intake from water was 44 % (IQR: 26-72 %). Total nitrate intake was the strongest predictor of urinary nitrate concentrations (R2 = 0.53). Drinking water explained a similar proportion of the variation in nitrate excretion (R2 = 0.52) as diet (R2 = 0.47). Our findings demonstrate the importance of both dietary and drinking water intakes as determinants of nitrate excretion.

Modeling variation in mixture effects over space with a Bayesian spatially varying mixture model.

Mixture analysis is an emerging statistical tool in epidemiological research that seeks to estimate the health effects associated with mixtures of several exposures. This approach acknowledges that individuals experience many simultaneous exposures and it can estimate the relative importance of components in the mixture. Health effects due to mixtures may vary over space driven by to political, demographic, environmental, or other differences. In such cases, estimating a global mixture effect without accounting for spatial variation would induce bias in effect estimates and potentially lower statistical power. To date, no methods have been developed to estimate spatially varying chemical mixture effects. We developed a Bayesian spatially varying mixture model that estimates spatially varying mixture effects and the importance weights of components in the mixture, while adjusting for covariates. We demonstrate the efficacy of the model through a simulation study that varies the number of mixtures (one and two) and spatial pattern (global, one-dimensional, radial) and magnitude of mixture effects, showing that the model is able to accurately reproduce the spatial pattern of mixture effects across a diverse set of scenarios. Finally, we apply our model to a multi-center case-control study of non-Hodgkin lymphoma (NHL) in Detroit, Iowa, Los Angeles, and Seattle. We identify significant spatially varying positive and inverse associations with NHL for two mixtures of pesticides in Iowa and do not find strong spatial effects at the other three centers. In conclusion, the Bayesian spatially varying mixture model represents a novel method for modeling spatial variation in mixture effects.

Detection of lymphoproliferative disease virus in Iowa Wild Turkeys (Meleagris gallopavo): Comparison of two sections of the proviral genome.

An accurate diagnostic test is an essential aspect of successfully monitoring and managing wildlife diseases. Lymphoproliferative Disease Virus (LPDV) is an avian retrovirus that was first identified in domestic turkeys in Europe and was first reported in a Wild Turkey (Meleagris gallopavo) in the United States in 2009. It has since been found to be widely distributed throughout North America. The majority of studies have utilized bone marrow and PCR primers targeting a 413-nucleotide sequence of the gag gene of the provirus to detect infection. While prior studies have evaluated the viability of other tissues for LPDV detection (whole blood, spleen, liver, cloacal swabs) none to date have studied differences in detection rates when utilizing different genomic regions of the provirus. This study examined the effectiveness of another section of the provirus, a 335-nucleotide sequence starting in the U3 region of the LTR (Long Terminal Repeat) and extending into the Matrix of the gag region (henceforth LTR), for detecting LPDV. Bone marrow samples from hunter-harvested Wild Turkeys (n = 925) were tested for LPDV with the gag gene and a subset (n = 417) including both those testing positive and those where LPDV was not detected was re-tested with LTR. The positive percent agreement (PPA) was 97.1% (68 of 70 gag positive samples tested positive with LTR) while the negative percent agreement (NPA) was only 68.0% (236 of 347 gag negative samples tested negative with LTR). Cohen's Kappa (κ = 0.402, Z = 10.26, p<0.0001) and the McNemar test (OR = 55.5, p<0.0001) indicated weak agreement between the two gene regions. We found that in Iowa Wild Turkeys use of the LTR region identified LPDV in many samples in which we failed to detect LPDV using the gag region and that LTR may be more appropriate for LPDV surveillance and monitoring. However, neither region of the provirus resulted in perfect detection and additional work is necessary to determine if LTR is more reliable in other geographic regions where LPDV occurs.

Pesticide use and inflammatory bowel disease in licensed pesticide applicators and spouses in the Agricultural Health Study.

BACKGROUND: Pesticide exposure has been linked to some autoimmune diseases and colorectal cancer, possibly via alteration of gut microbiota or other mechanisms. While pesticides have been linked to gut dysbiosis and inflammation in animal models, few epidemiologic studies have examined pesticides in relation to inflammatory bowel disease (IBD). OBJECTIVES: We evaluated use of pesticides and incident IBD in 68,480 eligible pesticide applicators and spouses enrolled in the Agricultural Health Study. METHODS: Self-reported IBD cases were identified from follow-up questionnaires between enrollment (1993-1997) and 2022. We evaluated IBD incidence in relation to self-reported ever use of 50 pesticides among applicators and spouses. We also explored associations with intensity-weighted lifetime days (IWLD) of pesticide use among male applicators. Covariate-adjusted hazard ratios (HR) and 95% confidence intervals (CI) were calculated using Cox regression. RESULTS: We identified 454 IBD cases, including 227 among male applicators. In analyses with applicators and spouses combined, associations were positive (HR > 1.2) for ever vs. never use of five organochlorine insecticides, three organophosphate insecticides, one fungicide, and five herbicides. HRs were highest for dieldrin (HR = 1.59, 95%CI: 1.03, 2.44), toxaphene (HR = 1.61, 95%CI: 1.17, 2.21), parathion (HR = 1.42, 95%CI: 1.03, 1.95), and terbufos (HR = 1.53, 95%CI: 1.19, 1.96). We had limited power in many IWLD of pesticide use analyses and did not find clear evidence of exposure-response trends; however, we observed elevated HRs in all tertiles of IWLD use of terbufos compared to never use (T1 vs. never use HR = 1.52, 95%CI: 1.03, 2.24; T2 vs. never use HR = 1.53, 95%CI: 1.04, 2.26; T3 vs. never use HR = 1.51, 95%CI: 1.03, 2.23). CONCLUSIONS: Exposure to specific pesticides was associated with elevated hazards of IBD. These findings may have public health importance given the widespread use of pesticides and the limited number of known modifiable environmental risk factors for IBD.