Background

The Agricultural Health Study (AHS) is a prospective study of licensed pesticide applicators (largely farmers) and their spouses in Iowa and North Carolina. We evaluate the impact of occupational pesticide exposure misclassification on relative risks using data from the cohort and the AHS Pesticide Exposure Study (AHS/PES).

Methods

We assessed the impact of exposure misclassification on relative risks using the range of correlation coefficients observed between measured post-application urinary levels of 2,4-dichlorophenoxyacetic acid (2,4-D) and chlorpyrifos metabolite and exposure estimates based on an algorithm from 83 AHS pesticide applications.

Results

The correlations between urinary levels of 2,4-D and chlorpyrifos metabolite and estimated exposure intensity scores from the expert-derived algorithm were about 0.4 for 2,4-D (n=64), 0.8 for liquid chlorpyrifos (n=4), and 0.6 for granular chlorpyrifos (n=12). Correlations of urinary levels with individual exposure determinants (e.g., kilograms of active ingredient used, duration of application, or number of acres treated) were lower and ranged from −0.36 to 0.19. These findings indicate that scores from an a priori expert-derived algorithm developed for the AHS were more closely related to measured urinary levels than the several individual exposure determinants evaluated here. Estimates of potential bias in relative risks observed in the AHS based on the correlations from the AHS/PES and the proportion of the AHS cohort exposed to various pesticides indicate that nondifferential misclassification of exposure using the algorithm would bias some estimates toward the null, but less than the misclassification associated with individual exposure determinants.

Conclusions

Based on these correlations and the proportion of the AHS cohort exposed to various pesticides, the potential bias in relative risks from nondifferential exposure misclassification is reduced when exposure estimates are based on an expert algorithm compared to estimates based on separate individual exposure determinants often used in epidemiologic studies. Although correlations between algorithm scores and urinary levels were quite good (i.e., correlations between 0.4 and 0.8), exposure misclassification would still bias relative risk estimates in the AHS towards the null and diminish study power.

Previous research demonstrates increased prostate cancer risk for pesticide applicators and pesticide manufacturing workers. Although underlying mechanisms are unknown, human biomonitoring studies indicate increased genetic damage (e.g. chromosomal aberrations) with pesticide exposure. Given that the nucleotide excision repair (NER) pathway repairs a broad range of DNA damage, we evaluated interactions between pesticide exposure and 324 single-nucleotide polymorphisms (SNPs) tagging 27 NER genes among 776 prostate cancer cases and 1444 male controls in a nested case–control study of white Agricultural Health Study pesticide applicators. We determined interaction P values using likelihood ratio tests from logistic regression models and three-level pesticide variables (none/low/high) based on lifetime days of use weighted to an intensity score. We adjusted for multiple comparisons using the false discovery rate (FDR) method. Of the 17 interactions that met FDR <0.2, 3 displayed a monotonic increase in prostate cancer risk with increasing exposure in one genotype group and no significant association in the other group. Men carrying the variant A allele at ERCC1 rs2298881 exhibited increased prostate cancer risk with high versus no fonofos use [odds ratio (OR) 2.98; 95% confidence interval (CI) 1.65–5.39; Pinteract = 3.6 × 10−4; FDR-adjusted P = 0.11]. Men carrying the homozygous wild-type TT genotype at two correlated CDK7 SNPs, rs11744596 and rs2932778 (r2 = 1.0), exhibited increased risk with high versus no carbofuran use (OR 2.01; 95% CI 1.31–3.10 for rs11744596; Pinteract = 7.2 × 10−4; FDR-adjusted P = 0.09). In contrast, we did not observe associations among men with other genotypes at these loci. While requiring replication, our findings suggest a role for NER genetic variation in pesticide-associated prostate cancer risk.

Background: Risks of most types of leukemia from exposure to acute high doses of ionizing radiation are well known, but risks associated with protracted exposures, as well as associations between radiation and chronic lymphocytic leukemia (CLL), are not clear.

Objectives: We estimated relative risks of CLL and non-CLL from protracted exposures to low-dose ionizing radiation.

Methods: A nested case–control study was conducted in a cohort of 110,645 Ukrainian cleanup workers of the 1986 Chornobyl nuclear power plant accident. Cases of incident leukemia diagnosed in 1986–2006 were confirmed by a panel of expert hematologists/hematopathologists. Controls were matched to cases on place of residence and year of birth. We estimated individual bone marrow radiation doses by the Realistic Analytical Dose Reconstruction with Uncertainty Estimation (RADRUE) method. We then used a conditional logistic regression model to estimate excess relative risk of leukemia per gray (ERR/Gy) of radiation dose.

Results: We found a significant linear dose response for all leukemia [137 cases, ERR/Gy = 1.26 (95% CI: 0.03, 3.58]. There were nonsignificant positive dose responses for both CLL and non-CLL (ERR/Gy = 0.76 and 1.87, respectively). In our primary analysis excluding 20 cases with direct in-person interviews < 2 years from start of chemotherapy with an anomalous finding of ERR/Gy = –0.47 (95% CI: < –0.47, 1.02), the ERR/Gy for the remaining 117 cases was 2.38 (95% CI: 0.49, 5.87). For CLL, the ERR/Gy was 2.58 (95% CI: 0.02, 8.43), and for non-CLL, ERR/Gy was 2.21 (95% CI: 0.05, 7.61). Altogether, 16% of leukemia cases (18% of CLL, 15% of non-CLL) were attributed to radiation exposure.

Conclusions: Exposure to low doses and to low dose-rates of radiation from post-Chornobyl cleanup work was associated with a significant increase in risk of leukemia, which was statistically consistent with estimates for the Japanese atomic bomb survivors. Based on the primary analysis, we conclude that CLL and non-CLL are both radiosensitive.

Background

Cigarette smoking is associated with esophageal adenocarcinoma (EAC), esophagogastric junctional adenocarcinoma (EGJA) and esophageal squamous cell carcinoma (ESCC), and alcohol consumption with ESCC. However, no analyses have examined how delivery rate modifies the strength of odds ratio (OR) trends with total exposure, i.e., the impact on the OR for a fixed total exposure of high exposure rate for short duration compared with low exposure rate for long duration.

Methods

The authors pooled data from 12 case-control studies from the Barrett’s Esophagus and Esophageal Adenocarcinoma Consortium (BEACON), including 1,242 (EAC), 1,263 (EGJA) and 954 (ESCC) cases and 7,053 controls, modeled joint ORs for cumulative exposure and exposure rate for cigarette smoking and alcohol consumption, and evaluated effect modification by sex, body mass index (BMI), age and self-reported acid reflux.

Results

For smoking, all sites exhibited inverse delivery rate effects, whereby ORs with pack-years increased, but trends weakened with increasing cigarettes/day. None of the examined factors modified associations, except for ESCC where younger ages at diagnosis enhanced smoking effects (P<0.01). For EAC and EGJA, ORs with drink-years exhibited inverse associations in <5 drinks/day consumers and no association in heavier consumers. For ESCC, ORs with drink-years increased, with trends strengthening with greater drinks/day. There was no significant effect modification, except for EAC and EGJA where acid reflux mitigated the inverse associations (P=0.02). For ESCC, younger ages at diagnosis enhanced drinking-related ORs (P<0.01).

Conclusions

Patterns of ORs by pack-years and drink-years, delivery rate effects and effect modifiers revealed common as well as distinct etiologic elements for these diseases.

Background

To explore associations with prostate cancer and farming, it is important to investigate the relationship between pesticide use and single nucleotide polymorphisms (SNPs) in xenobiotic metabolic enzyme (XME) genes.

Objectives

We evaluated pesticide-SNP interactions between 45 pesticides and 1,913 XME SNPs with respect to prostate cancer among 776 cases and 1,444 controls in the Agricultural Health Study.

Methods

We used unconditional logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs). Multiplicative SNP-pesticide interactions were calculated using a likelihood ratio test.

Results

A positive monotonic interaction was observed between petroleum oil/petroleum distillate use and rs1883633 in the oxidative stress gene glutamate-cysteine ligase (GCLC) (p-interaction=1.0×10−4); men carrying at least one variant allele (minor allele) experienced an increased prostate cancer risk (OR=3.7, 95% CI: 1.9–7.3). Among men carrying the variant allele for thioredoxin reductase 2 (TXNRD2) rs4485648, microsomal epoxide hyrdolase 1 (EPHX1) rs17309872, or myeloperoxidase (MPO) rs11079344, increased prostate cancer risk was observed with high compared to no petroleum oil/petroleum distillate (OR=1.9, 95% CI: 1.1–3.2, p-interaction=0.01), (OR=2.1, 95% CI: 1.1–4.0, p-interaction=0.01), or terbufos (OR=3.0, 95% CI: 1.5–6.0 p-interaction=2.0×10−3) use, respectively. No interactions were deemed noteworthy at the false discovery rate = 0.20 level; the number of observed interactions in XMEs was comparable to the number expected by chance alone.

Conclusions

We observed several pesticide-SNP interactions in oxidative stress and phase I/phase II enzyme genes and risk of prostate cancer. Additional work is needed to explain the joint contribution of genetic variation in XMEs, pesticide use, and prostate cancer risk.

Background

Greater tobacco smoking and alcohol consumption and lower body mass index (BMI) increase odds ratios (OR) for oral cavity, oropharyngeal, hypopharyngeal and laryngeal cancers; however, there are no comprehensive sex-specific comparisons of ORs for these factors.

Methods

We analyzed 2,441 oral cavity (925 females and 1,516 males), 2,297 oropharynx (564 females and 1,733 males), 508 hypopharynx (96 females and 412 males) and 1,740 larynx (237 females and 1,503 males) cases from the INHANCE consortium of 15 head and neck cancer case-control studies. Controls numbered from 7,604 to 13,829 subjects, depending on analysis. Analyses fitted linear-exponential excess ORs models.

Results

ORs were increased in underweight (<18.5 BMI) relative to overweight and obese categories (≥25 BMI) for all sites and were homogeneous by sex. ORs by smoking and drinking in females compared to males were significantly greater for oropharyngeal cancer (p<0.01 for both factors), suggestive for hypopharyngeal cancer (p=0.05 and p=0.06, respectively), but homogeneous for oral cavity (p=0.56 and p=0.64) and laryngeal (p=0.18 and p=0.72) cancers.

Conclusions

The extent that OR modifications of smoking and drinking by sex for oropharyngeal and, possibly, hypopharyngeal cancers represent true associations, or derive from unmeasured confounders or unobserved sex-related disease subtypes (e.g., human papillomavirus positive oropharyngeal cancer) remains to be clarified.

Background

Mood disorders may affect lung cancer risk. We evaluated this hypothesis in two large studies.

Methodology/Principal Findings

We examined 1,939 lung cancer cases and 2,102 controls from the Environment And Genetics in Lung cancer Etiology (EAGLE) case-control study conducted in Italy (2002–2005), and 82,945 inpatients with a lung cancer diagnosis and 3,586,299 person-years without a lung cancer diagnosis in the U.S. Veterans Affairs Inpatient Cohort (VA study), composed of veterans with a VA hospital admission (1969–1996). In EAGLE, we calculated odds ratios (ORs) and 95% confidence intervals (CI), with extensive adjustment for tobacco smoking and multiple lifestyle factors. In the VA study, we estimated lung cancer relative risks (RRs) and 95% CIs with time-dependent Poisson regression, adjusting for attained age, calendar year, hospital visits, time within the study, and related previous medical diagnoses. In EAGLE, we found decreased lung cancer risk in subjects with a personal history of mood disorders (OR: 0.59, 95% CI: 0.44–0.79, based on 121 lung cancer incident cases and 192 controls) and family history of mood disorders (OR: 0.62, 95% CI: 0.50–0.77, based on 223 lung cancer cases and 345 controls). The VA study analyses yielded similar results (RR: 0.74, 95% CI: 0.71–0.77, based on 2,304 incident lung cancer cases and 177,267 non-cancer person-years) in men with discharge diagnoses for mood disorders. History of mood disorders was associated with nicotine dependence, alcohol and substance use and psychometric scales of depressive and anxiety symptoms in controls for these studies.

Conclusions/Significance

The consistent finding of a relationship between mood disorders and lung cancer risk across two large studies calls for further research into the complex interplay of risk factors associated with these two widespread and debilitating diseases. Although we adjusted for smoking effects in EAGLE, residual confounding of the results by smoking cannot be ruled out.

Background. Lipid metabolism processes have been implicated in prostate carcinogenesis. Since several pesticides are lipophilic or are metabolized via lipid-related mechanisms, they may interact with variants of genes in the lipid metabolism pathway. Methods. In a nested case-control study of 776 cases and 1444 controls from the Agricultural Health Study (AHS), a prospective cohort study of pesticide applicators, we examined the interactions between 39 pesticides (none, low, and high exposure) and 220 single nucleotide polymorphisms (SNPs) in 59 genes. The false discovery rate (FDR) was used to account for multiple comparisons. Results. We found 17 interactions that displayed a significant monotonic increase in prostate cancer risk with pesticide exposure in one genotype and no significant association in the other genotype. The most noteworthy association was for ALOXE3 rs3027208 and terbufos, such that men carrying the T allele who were low users had an OR of 1.86 (95% CI = 1.16–2.99) and high users an OR of 2.00 (95% CI = 1.28–3.15) compared to those with no use of terbufos, while men carrying the CC genotype did not exhibit a significant association. Conclusion. Genetic variation in lipid metabolism genes may modify pesticide associations with prostate cancer; however our results require replication.

The Agricultural Health Study (AHS), a large prospective cohort, was designed to elucidate associations between pesticide use and other agricultural exposures and health outcomes. The cohort includes 57,310 pesticide applicators who were enrolled between 1993 and 1997 in Iowa and North Carolina. A follow-up questionnaire administered 5 years later was completed by 36,342 (63%) of the original participants. Missing pesticide use information from participants who did not complete the second questionnaire impedes both long-term pesticide exposure estimation and statistical inference of risk for health outcomes. Logistic regression and stratified sampling were used to impute key variables related to the use of specific pesticides for 20,968 applicators who did not complete the second questionnaire. To assess the imputation procedure, a 20% random sample of participants was withheld for comparison. The observed and imputed prevalence of any pesticide use in the holdout dataset were 85.7% and 85.3%, respectively. The distribution of prevalence and days/year of use for specific pesticides were similar across observed and imputed in the holdout sample. When appropriately implemented, multiple imputation can reduce bias and increase precision and can be more valid than other missing data approaches.

Background

Most studies of the association between diesel exhaust exposure and lung cancer suggest a modest, but consistent, increased risk. However, to our knowledge, no study to date has had quantitative data on historical diesel exposure coupled with adequate sample size to evaluate the exposure–response relationship between diesel exhaust and lung cancer. Our purpose was to evaluate the relationship between quantitative estimates of exposure to diesel exhaust and lung cancer mortality after adjustment for smoking and other potential confounders.

Methods

We conducted a nested case–control study in a cohort of 12 315 workers in eight non-metal mining facilities, which included 198 lung cancer deaths and 562 incidence density–sampled control subjects. For each case subject, we selected up to four control subjects, individually matched on mining facility, sex, race/ethnicity, and birth year (within 5 years), from all workers who were alive before the day the case subject died. We estimated diesel exhaust exposure, represented by respirable elemental carbon (REC), by job and year, for each subject, based on an extensive retrospective exposure assessment at each mining facility. We conducted both categorical and continuous regression analyses adjusted for cigarette smoking and other potential confounding variables (eg, history of employment in high-risk occupations for lung cancer and a history of respiratory disease) to estimate odds ratios (ORs) and 95% confidence intervals (CIs). Analyses were both unlagged and lagged to exclude recent exposure such as that occurring in the 15 years directly before the date of death (case subjects)/reference date (control subjects). All statistical tests were two-sided.

Results

We observed statistically significant increasing trends in lung cancer risk with increasing cumulative REC and average REC intensity. Cumulative REC, lagged 15 years, yielded a statistically significant positive gradient in lung cancer risk overall (P trend = .001); among heavily exposed workers (ie, above the median of the top quartile [REC ≥ 1005 μg/m3-y]), risk was approximately three times greater (OR = 3.20, 95% CI = 1.33 to 7.69) than that among workers in the lowest quartile of exposure. Among never smokers, odd ratios were 1.0, 1.47 (95% CI = 0.29 to 7.50), and 7.30 (95% CI = 1.46 to 36.57) for workers with 15-year lagged cumulative REC tertiles of less than 8, 8 to less than 304, and 304 μg/m3-y or more, respectively. We also observed an interaction between smoking and 15-year lagged cumulative REC (P interaction = .086) such that the effect of each of these exposures was attenuated in the presence of high levels of the other.

Conclusion

Our findings provide further evidence that diesel exhaust exposure may cause lung cancer in humans and may represent a potential public health burden.

Background

Current information points to an association between diesel exhaust exposure and lung cancer and other mortality outcomes, but uncertainties remain.

Methods

We undertook a cohort mortality study of 12 315 workers exposed to diesel exhaust at eight US non-metal mining facilities. Historical measurements and surrogate exposure data, along with study industrial hygiene measurements, were used to derive retrospective quantitative estimates of respirable elemental carbon (REC) exposure for each worker. Standardized mortality ratios and internally adjusted Cox proportional hazard models were used to evaluate REC exposure–associated risk. Analyses were both unlagged and lagged to exclude recent exposure such as that occurring in the 15 years directly before the date of death.

Results

Standardized mortality ratios for lung cancer (1.26, 95% confidence interval [CI] = 1.09 to 1.44), esophageal cancer (1.83, 95% CI = 1.16 to 2.75), and pneumoconiosis (12.20, 95% CI = 6.82 to 20.12) were elevated in the complete cohort compared with state-based mortality rates, but all-cause, bladder cancer, heart disease, and chronic obstructive pulmonary disease mortality were not. Differences in risk by worker location (ever-underground vs surface only) initially obscured a positive diesel exhaust exposure–response relationship with lung cancer in the complete cohort, although it became apparent after adjustment for worker location. The hazard ratios (HRs) for lung cancer mortality increased with increasing 15-year lagged cumulative REC exposure for ever-underground workers with 5 or more years of tenure to a maximum in the 640 to less than 1280 μg/m3-y category compared with the reference category (0 to <20 μg/m3-y; 30 deaths compared with eight deaths of the total of 93; HR = 5.01, 95% CI = 1.97 to 12.76) but declined at higher exposures. Average REC intensity hazard ratios rose to a plateau around 32 μg/m3. Elevated hazard ratios and evidence of exposure–response were also seen for surface workers. The association between diesel exhaust exposure and lung cancer risk remained after inclusion of other work-related potentially confounding exposures in the models and were robust to alternative approaches to exposure derivation.

Conclusions

The study findings provide further evidence that exposure to diesel exhaust increases risk of mortality from lung cancer and have important public health implications.

Exposure to respirable elemental carbon (REC), a component of diesel exhaust (DE), was assessed for an epidemiologic study investigating the association between DE and mortality, particularly from lung cancer, among miners at eight mining facilities from the date of dieselization (1947–1967) through 1997. To provide insight into the quality of the estimates for use in the epidemiologic analyses, several approaches were taken to evaluate the exposure assessment process and the quality of the estimates. An analysis of variance was conducted to evaluate the variability of 1998–2001 REC measurements within and between exposure groups of underground jobs. Estimates for the surface exposure groups were evaluated to determine if the arithmetic means (AMs) of the REC measurements increased with increased proximity to, or use of, diesel-powered equipment, which was the basis on which the surface groups were formed. Estimates of carbon monoxide (CO) (another component of DE) air concentrations in 1976–1977, derived from models developed to predict estimated historical exposures, were compared to 1976–1977 CO measurement data that had not been used in the model development. Alternative sets of estimates were developed to investigate the robustness of various model assumptions. These estimates were based on prediction models using: (i) REC medians rather AMs, (ii) a different CO:REC proportionality than a 1:1 relation, and (iii) 5-year averages of historical CO measurements rather than modeled historical CO measurements and DE-related determinants. The analysis of variance found that in three of the facilities, most of the between-group variability in the underground measurements was explained by the use of job titles. There was relatively little between-group variability in the other facilities. The estimated REC AMs for the surface exposure groups rose overall from 1 to 5 μg m−3 as proximity to, and use of, diesel equipment increased. The alternative estimates overall were highly correlated (∼0.9) with the primary set of estimates. The median of the relative differences between the 1976–1977 CO measurement means and the 1976–1977 estimates for six facilities was 29%. Comparison of estimated CO air concentrations from the facility-specific prediction models with historical CO measurement data found an overall agreement similar to that observed in other epidemiologic studies. Other evaluations of components of the exposure assessment process found moderate to excellent agreement. Thus, the overall evidence suggests that the estimates were likely accurate representations of historical personal exposure levels to DE and are useful for epidemiologic analyses.

Background

Socio-economic status is known to influence health throughout life. In childhood, studies have shown increased injury rates in more deprived settings. Socio-economic status may therefore be related to rates of certain medical procedures, such as computed tomography (CT) scans. This study aimed to assess socio-economic variation among young people having CT scans in Northern England between 1990 and 2002 inclusive.

Methods

Electronic data were obtained from Radiology Information Systems of all nine National Health Service hospital Trusts in the region. CT scan data, including sex, date of scan, age at scan, number and type of scans were assessed in relation to quintiles of Townsend deprivation scores, obtained from linkage of postcodes with census data, using χ2 tests and Spearman rank correlations.

Results

During the study period, 39,676 scans were recorded on 21,089 patients, with 38,007 scans and 19,485 patients (11344 male and 8132 female) linkable to Townsend scores. The overall distributions of both scans and patients by quintile of Townsend deprivation scores were significantly different to the distributions of Townsend scores from the census wards included in the study (p < 0.0001). There was a significant association between type of scan and deprivation quintile (p < 0.0001), primarily due to the higher proportions of head scans in the three most deprived quintiles, and slightly higher proportions of chest scans and abdomen and pelvis scans in the least deprived groups. There was also a significant association (p < 0.0001) between the patient's age at the time of the CT scan and Townsend deprivation quintiles, with slightly increasing proportions of younger children with increasing deprivation. A similar association with age (p < 0.0001) was seen when restricting the data to include only the first scan of each patient. The number of scans per patient was also associated with Townsend deprivation quintiles (p = 0.014).

Conclusions

Social inequalities exist in the numbers of young people undergoing CT scans with those from deprived areas more likely to do so. This may reflect the rates of injuries in these individuals and implies that certain groups within the population may receive higher radiation doses than others due to medical procedures.

Comparing agricultural cohorts with the general population is challenging because the general healthiness of farmers may mask potential adverse health effects of farming. Using data from the Agricultural Health Study, a cohort of 89,656 pesticide applicators and their spouses (N = 89, 656) in North Carolina and Iowa, the authors computed standardized mortality ratios (SMRs) comparing deaths from time of the enrollment (1993–1997) through 2007 to state-specific rates. To compensate for the cohort's overall healthiness, relative SMRs were estimated by calculating the SMR for each cause relative to the SMR for all other causes. In 1,198,129 person-years of follow-up, 6,419 deaths were observed. The all-cause mortality rate was less than expected (SMRapplicators = 0.54, 95% confidence interval (CI): 0.52, 0.55; SMRspouses = 0.52, 95% CI: 0.50, 0.55). SMRs for all cancers, heart disease, and diabetes were significantly below 1.0. In contrast, applicators experienced elevated numbers of machine-related deaths (SMR = 4.15, 95% CI: 3.18, 5.31), motor vehicle nontraffic accidents (SMR = 2.80, 95% CI: 1.81, 4.14), and collisions with objects (SMR = 2.12, 95% CI: 1.25, 3.34). In the relative SMR analysis for applicators, the relative mortality ratio was elevated for lymphohematopoietic cancers, melanoma, and digestive system, prostate, kidney, and brain cancers. Among spouses, relative SMRs exceeded 1.0 for lymphohematopoietic cancers and malignancies of the digestive system, brain, breast, and ovary. Unintentional fatal injuries remain an important risk for farmers; mortality ratios from several cancers were elevated relative to other causes.

Background: Previous research indicates increased prostate cancer risk for pesticide applicators and pesticide manufacturing workers. Although underlying mechanisms are unknown, evidence suggests a role of oxidative DNA damage.

Objectives: Because base excision repair (BER) is the predominant pathway involved in repairing oxidative damage, we evaluated interactions between 39 pesticides and 394 tag single-nucleotide polymorphisms (SNPs) for 31 BER genes among 776 prostate cancer cases and 1,444 male controls in a nested case–control study of white Agricultural Health Study (AHS) pesticide applicators.

Methods: We used likelihood ratio tests from logistic regression models to determine p-values for interactions between three-level pesticide exposure variables (none/low/high) and SNPs (assuming a dominant model), and the false discovery rate (FDR) multiple comparison adjustment approach.

Results: The interaction between fonofos and rs1983132 in NEIL3 [nei endonuclease VIII-like 3 (Escherichia coli)], which encodes a glycosylase that can initiate BER, was the most significant overall [interaction p-value (pinteract) = 9.3 × 10–6; FDR-adjusted p-value = 0.01]. Fonofos exposure was associated with a monotonic increase in prostate cancer risk among men with CT/TT genotypes for rs1983132 [odds ratios (95% confidence intervals) for low and high use compared with no use were 1.65 (0.91, 3.01) and 3.25 (1.78, 5.92), respectively], whereas fonofos was not associated with prostate cancer risk among men with the CC genotype. Carbofuran and S-ethyl dipropylthiocarbamate (EPTC) interacted similarly with rs1983132; however, these interactions did not meet an FDR < 0.2.

Conclusions: Our significant finding regarding fonofos is consistent with previous AHS findings of increased prostate cancer risk with fonofos exposure among those with a family history of prostate cancer. Although requiring replication, our findings suggest a role of BER genetic variation in pesticide-associated prostate cancer risk.

An algorithm developed to estimate pesticide exposure intensity for use in epidemiologic analyses was revised based on data from two exposure monitoring studies. In the first study, we estimated relative exposure intensity based on the results of measurements taken during the application of the herbicide 2,4-dichlorophenoxyacetic acid (2,4-D) (n = 88) and the insecticide chlorpyrifos (n = 17). Modifications to the algorithm weighting factors were based on geometric means (GM) of post-application urine concentrations for applicators grouped by application method and use of chemically-resistant (CR) gloves. Measurement data from a second study were also used to evaluate relative exposure levels associated with airblast as compared to hand spray application methods. Algorithm modifications included an increase in the exposure reduction factor for use of CR gloves from 40% to 60%, an increase in the application method weight for boom spray relative to in-furrow and for air blast relative to hand spray, and a decrease in the weight for mixing relative to the new weights assigned for application methods. The weighting factors for the revised algorithm now incorporate exposure measurements taken on Agricultural Health Study (AHS) participants for the application methods and personal protective equipment (PPE) commonly reported by study participants.

Genome-wide association studies have identified 8q24 region variants as risk factors for prostate cancer. In the Agricultural Health Study, a prospective study of licensed pesticide applicators, we observed increased prostate cancer risk with specific pesticide use among those with a family history of prostate cancer. Thus, we evaluated the interaction between pesticide use, 8q24 variants and prostate cancer risk. The authors estimated odds ratios (ORs) and 95% confidence intervals (CIs) for interactions between 211 8q24 variants, 49 pesticides and prostate cancer risk in 776 cases and 1,444 controls. The ORs for a previously identified variant, rs4242382, and prostate cancer increased significantly (p<0.05) with exposure to the organophosphate insecticide, fonofos, after correction for multiple testing, per allele ORnonexposed= 1.17 (95% CI: 0.93, 1.48), per allele ORlow=1.30 (95% CI: 0.75, 2.27), per allele ORhigh=4.46 (95% CI: 2.17, 9.17), p-interaction=0.002, adjusted p-interaction = 0.02. Similar effect modification was observed for three other organophosphate insecticides, coumaphos, terbufos, and phorate and one pyrethroid insecticide, permethrin. Among ever users of fonofos, subjects with 3 or 4 risk alleles at rs7837328 and rs4242382 had approximately 3 times the risk of prostate cancer (OR=3.14 95% CI: 1.41, 7.00) compared with subjects who had zero risk alleles and never used fonofos. We observed a significant interaction between variants on chromosome 8q24, pesticide use, and risk of prostate cancer. Insecticides, particularly organophosphates, were the strongest modifiers of risk, although the biologic mechanism is unclear. This is the first report of effect modification between 8q24 and an environmental exposure on prostate cancer risk.

Objective

Our objective is to re-evaluate cancer incidence among Agricultural Health Study participants.

Methods

Standardized incidence ratios (SIR) and Relative Standardized Ratios were calculated.

Results

A significant excess of prostate cancer was seen for private and commercial applicators, SIR = 1.19 (95% Confidence Interval (CI) 1.14, 1.25) and SIR = 1.28 (95% CI 1.00, 1.61), respectively. Excesses were observed for lip cancer, SIR = 1.97 (95% CI 1.02, 3.44), and multiple myeloma, SIR = 1.42 (95% CI 1.00, 1.95) among private applicators from North Carolina and for marginal zone lymphoma among Iowa spouses, SIR = 2.34 (95% CI 1.21, 4.09).

Conclusions

While lower rates of smoking and increased physical activity probably contribute to the lower overall cancer incidence, agricultural exposures including pesticides, viruses, bacteria, sunlight, and other chemicals may increase risks for specific cancer sites.

This report provides an overview of the exposure assessment process for an epidemiologic study that investigated mortality, with a special focus on lung cancer, associated with diesel exhaust (DE) exposure among miners. Details of several components are provided in four other reports. A major challenge for this study was the development of quantitative estimates of historical exposures to DE. There is no single standard method for assessing the totality of DE, so respirable elemental carbon (REC), a component of DE, was selected as the primary surrogate in this study. Air monitoring surveys at seven of the eight study mining facilities were conducted between 1998 and 2001 and provided reference personal REC exposure levels and measurements for other agents and DE components in the mining environment. (The eighth facility had closed permanently prior to the surveys.) Exposure estimates were developed for mining facility/department/job/year combinations. A hierarchical grouping strategy was developed for assigning exposure levels to underground jobs [based on job titles, on the amount of time spent in various areas of the underground mine, and on similar carbon monoxide (CO, another DE component) concentrations] and to surface jobs (based on the use of, or proximity to, diesel-powered equipment). Time trends in air concentrations for underground jobs were estimated from mining facility-specific prediction models using diesel equipment horsepower, total air flow rates exhausted from the underground mines, and, because there were no historical REC measurements, historical measurements of CO. Exposures to potentially confounding agents, i.e. respirable dust, silica, radon, asbestos, and non-diesel sources of polycyclic aromatic hydrocarbons, also were assessed. Accuracy and reliability of the estimated REC exposures levels were evaluated by comparison with several smaller datasets and by development of alternative time trend models. During 1998–2001, the average measured REC exposure level by facility ranged from 40 to 384 μg m−3 for the underground workers and from 2 to 6 μg m−3 for the surface workers. For one prevalent underground job, ‘miner operator’, the maximum annual REC exposure estimate by facility ranged up to 685% greater than the corresponding 1998–2001 value. A comparison of the historical CO estimates from the time trend models with 1976–1977 CO measurements not used in the modeling found an overall median relative difference of 29%. Other comparisons showed similar levels of agreement. The assessment process indicated large differences in REC exposure levels over time and across the underground operations. Method evaluations indicated that the final estimates were consistent with those from alternative time trend models and demonstrated moderate to high agreement with external data.

Diesel exhaust (DE) has been implicated as a potential lung carcinogen. However, the exact components of DE that might be involved have not been clearly identified. In the past, nitrogen oxides (NOx) and carbon oxides (COx) were measured most frequently to estimate DE, but since the 1990s, the most commonly accepted surrogate for DE has been elemental carbon (EC). We developed quantitative estimates of historical exposure levels of respirable elemental carbon (REC) for an epidemiologic study of mortality, particularly lung cancer, among diesel-exposed miners by back-extrapolating 1998–2001 REC exposure levels using historical measurements of carbon monoxide (CO). The choice of CO was based on the availability of historical measurement data. Here, we evaluated the relationship of REC with CO and other current and historical components of DE from side-by-side area measurements taken in underground operations of seven non-metal mining facilities. The Pearson correlation coefficient of the natural log-transformed (Ln)REC measurements with the Ln(CO) measurements was 0.4. The correlation of REC with the other gaseous, organic carbon (OC), and particulate measurements ranged from 0.3 to 0.8. Factor analyses indicated that the gaseous components, including CO, together with REC, loaded most strongly on a presumed ‘Diesel exhaust’ factor, while the OC and particulate agents loaded predominantly on other factors. In addition, the relationship between Ln(REC) and Ln(CO) was approximately linear over a wide range of REC concentrations. The fact that CO correlated with REC, loaded on the same factor, and increased linearly in log–log space supported the use of CO in estimating historical exposure levels to DE.

Background: Ingestion of inorganic arsenic in drinking water is recognized as a cause of bladder cancer when levels are relatively high (≥ 150 µg/L). The epidemiologic evidence is less clear at the low-to-moderate concentrations typically observed in the United States. Accurate retrospective exposure assessment over a long time period is a major challenge in conducting epidemiologic studies of environmental factors and diseases with long latency, such as cancer.

Objective: We estimated arsenic concentrations in the water supplies of 2,611 participants in a population-based case–control study in northern New England.

Methods: Estimates covered the lifetimes of most study participants and were based on a combination of arsenic measurements at the homes of the participants and statistical modeling of arsenic concentrations in the water supply of both past and current homes. We assigned a residential water supply arsenic concentration for 165,138 (95%) of the total 173,361 lifetime exposure years (EYs) and a workplace water supply arsenic level for 85,195 EYs (86% of reported occupational years).

Results: Three methods accounted for 93% of the residential estimates of arsenic concentration: direct measurement of water samples (27%; median, 0.3 µg/L; range, 0.1–11.5), statistical models of water utility measurement data (49%; median, 0.4 µg/L; range, 0.3–3.3), and statistical models of arsenic concentrations in wells using aquifers in New England (17%; median, 1.6 µg/L; range, 0.6–22.4).

Conclusions: We used a different validation procedure for each of the three methods, and found our estimated levels to be comparable with available measured concentrations. This methodology allowed us to calculate potential drinking water exposure over long periods.

Background: Atrazine is a triazine herbicide used widely in the United States. Although it is an animal carcinogen, the mechanism in rodents does not appear to operate in humans. Few epidemiologic studies have provided evidence for an association.

Methods: The Agricultural Health Study (AHS) is a prospective cohort that includes 57,310 licensed pesticide applicators. In this report, we extend a previous AHS analysis of cancer risk associated with self-reported atrazine use with six additional years of follow-up and more than twice as many cancer cases. Using Poisson regression, we calculated relative risk estimates and 95% confidence intervals for lifetime use of atrazine and intensity-weighted lifetime days, which accounts for factors that impact exposure.

Results: Overall, 36,357 (68%) of applicators reported using atrazine, among whom there were 3,146 cancer cases. There was no increase among atrazine users in overall cancer risk or at most cancer sites in the higher exposure categories compared with the lowest. Based on 29 exposed cases of thyroid cancer, there was a statistically significant risk in the second and fourth quartiles of intensity-weighted lifetime days. There was a similar pattern for lifetime days, but neither the risk estimates nor the trend were statistically significant and for neither metric was the trend monotonic.

Conclusions: Overall, there was no consistent evidence of an association between atrazine use and any cancer site. There was a suggestion of increased risk of thyroid cancer, but these results are based on relatively small numbers and minimal supporting evidence.

Obesity is associated with increased risks of several cancers including, colon, lower esophagus, kidney, female breast, and endometrium. Some studies have associated pesticides with higher risks of cancer in agricultural populations. The interaction between obesity and pesticide use on cancer risk has not been well studied. Using data from the Agricultural Health Study we examined the association between body mass index (BMI) and the risk of cancer at 17 sites, and the interaction between BMI and pesticide use. Pesticide applicators (primarly farmers), and their spouses residing in Iowa and North Carolina were enrolled between 1993 and 1997 and followed through 2005. This analysis included 39,628 men and 28,319 women who provided information on pesticide use, height and weight data, and were cancer-free at enrollment. Of all subjects, 64% were overweight or obese, and 4,432 incident cancers were diagnosed during the follow-up period. We found positive associations between BMI (continuous) and colon cancer among men (Hazard Ratio (HR) 1.05, 95% confidence interval (CI) 1.02–1.09) and breast cancer among postmenopausal women (HR 1.03, 95% CI 1.01–1.06), as well as an inverse association with lung cancer among men who were ever smokers (HR 0.92, 95% CI 0.88–0.96). Men who ever used carbofuran (HR=1.10, 95% CI 1.04–1.17), metolachlor (HR=1.09, 95% CI 1.04–1.15), and alachlor (HR=1.08, 95% CI 1.03–1.13) had significant positive associations between BMI and colon cancer, but non-users did not. Men who ever smoked and used carbofuran had a positive, although not significant, association between BMI and lung cancer, while users of carbofuran had a significant inverse association. These findings, which suggest that certain pesticides may modify the association between BMI and colon and lung cancer risk, should be further evaluated in other populations.

Background: Current knowledge about Chornobyl-related thyroid cancer risks comes from ecological studies based on grouped doses, case–control studies, and studies of prevalent cancers.

Objective: To address this limitation, we evaluated the dose–response relationship for incident thyroid cancers using measurement-based individual iodine-131 (I-131) thyroid dose estimates in a prospective analytic cohort study.

Methods: The cohort consists of individuals < 18 years of age on 26 April 1986 who resided in three contaminated oblasts (states) of Ukraine and underwent up to four thyroid screening examinations between 1998 and 2007 (n = 12,514). Thyroid doses of I-131 were estimated based on individual radioactivity measurements taken within 2 months after the accident, environmental transport models, and interview data. Excess radiation risks were estimated using Poisson regression models.

Results: Sixty-five incident thyroid cancers were diagnosed during the second through fourth screenings and 73,004 person-years (PY) of observation. The dose–response relationship was consistent with linearity on relative and absolute scales, although the excess relative risk (ERR) model described data better than did the excess absolute risk (EAR) model. The ERR per gray was 1.91 [95% confidence interval (CI), 0.43–6.34], and the EAR per 104 PY/Gy was 2.21 (95% CI, 0.04–5.78). The ERR per gray varied significantly by oblast of residence but not by time since exposure, use of iodine prophylaxis, iodine status, sex, age, or tumor size.

Conclusions: I-131–related thyroid cancer risks persisted for two decades after exposure, with no evidence of decrease during the observation period. The radiation risks, although smaller, are compatible with those of retrospective and ecological post-Chornobyl studies.

Odds ratios for head and neck cancer increase with greater cigarette and alcohol use and lower body mass index (BMI; weight (kg)/height2 (m2)). Using data from the International Head and Neck Cancer Epidemiology Consortium, the authors conducted a formal analysis of BMI as a modifier of smoking- and alcohol-related effects. Analysis of never and current smokers included 6,333 cases, while analysis of never drinkers and consumers of ≤10 drinks/day included 8,452 cases. There were 8,000 or more controls, depending on the analysis. Odds ratios for all sites increased with lower BMI, greater smoking, and greater drinking. In polytomous regression, odds ratios for BMI (P = 0.65), smoking (P = 0.52), and drinking (P = 0.73) were homogeneous for oral cavity and pharyngeal cancers. Odds ratios for BMI and drinking were greater for oral cavity/pharyngeal cancer (P < 0.01), while smoking odds ratios were greater for laryngeal cancer (P < 0.01). Lower BMI enhanced smoking- and drinking-related odds ratios for oral cavity/pharyngeal cancer (P < 0.01), while BMI did not modify smoking and drinking odds ratios for laryngeal cancer. The increased odds ratios for all sites with low BMI may suggest related carcinogenic mechanisms; however, BMI modification of smoking and drinking odds ratios for cancer of the oral cavity/pharynx but not larynx cancer suggests additional factors specific to oral cavity/pharynx cancer.