Assessment of a pesticide exposure intensity algorithm in the agricultural health study.

The accuracy of the exposure assessment is a critical factor in epidemiological investigations of pesticide exposures and health in agricultural populations. However, few studies have been conducted to evaluate questionnaire-based exposure metrics. The Agricultural Health Study (AHS) is a prospective cohort study of pesticide applicators who provided detailed questionnaire information on their use of specific pesticides. A field study was conducted for a subset of the applicators enrolled in the AHS to assess a pesticide exposure algorithm through comparison of algorithm intensity scores with measured exposures. Pre- and post-application urinary biomarker measurements were made for 2,4-D (n=69) and chlorpyrifos (n=17) applicators. Dermal patch, hand wipe, and personal air samples were also collected. Intensity scores were calculated using information from technician observations and an interviewer-administered questionnaire. Correlations between observer and questionnaire intensity scores were high (Spearman's r=0.92 and 0.84 for 2,4-D and chlorpyrifos, respectively). Intensity scores from questionnaires for individual applications were significantly correlated with post-application urinary concentrations for both 2,4-D (r=0.42, P<0.001) and chlorpyrifos (r=0.53, P=0.035) applicators. Significant correlations were also found between intensity scores and estimated hand loading, estimated body loading, and air concentrations for 2,4-D applicators (r-values 0.28-0.50, P-values<0.025). Correlations between intensity scores and dermal and air measures were generally lower for chlorpyrifos applicators using granular products. A linear regression model indicated that the algorithm factors for individual applications explained 24% of the variability in post-application urinary 2,4-D concentration, which increased to 60% when the pre-application urine concentration was included. The results of the measurements support the use of the algorithm for estimating questionnaire-based exposure intensities in the AHS for liquid pesticide products. Refinement of the algorithm may be possible using the results from this and other measurement studies.

Micronuclei assessment in the urothelial cells of women using hair dyes and its modulation by genetic polymorphisms.

Increases in the frequency of micronuclei (MN) in exposed cells can be used as a measure of genotoxicity. Hair dyes contain chemicals that are eliminated by urine and could be genotoxic to urothelial cells. To address this question, we evaluated whether hair dye use is associated with an increase in the frequency of MN in urothelial cells, and whether this association is modified by NAT1 (N-acetyltransferase 1), NAT2 (N-acetyltransferase 2) and GSTM1 (glutathione-S-transferase M1) genotypes. We included 92 women participating as controls in a bladder cancer case-control study in Spain. Of those, 72 had adequate number of cells to be included in the MN analysis. There were no significant differences in the mean MN frequency in women using hair dyes in the last month (9.88 MN/1000 cells), in comparison with the MN in unexposed women (9.50 MN/1000 cells). No statistically significant differences in MN frequency were observed by type of hair dye or color of the hair dye. Comparison of subjects in the highest quartile of MN frequency (> or = 12 MN/1000 cells) and those in the lowest quartile (< or = 4 MN/1000 cells) suggested an association between hair dye use and elevated MN frequency (OR 14.2 (95% CI 0.81-247.8; P=0.069)). None of the polymorphisms examined significantly modified association between hair dye use and frequency of MN. Findings of an increased frequency of MN in urothelial cells of hair dye users suggest a possible genotoxic effect of hair dye compounds and need confirmation in larger studies.

Detailed exposure assessment for a molecular epidemiology study of benzene in two shoe factories in China.

OBJECTIVES: We carried out a detailed exposure assessment of benzene and toluene in two shoe factories in Tianjin, China. Our goal was to identify workers with a broad range of benzene exposures, for an epidemiologic study relating exposure to early biologic effects. METHODS: A comprehensive exposure survey program was initiated. Over a period of 16 months, 2783 personal solvent exposure samples were collected in two workplaces from 250 workers. Mixed-effects models were used to identify factors affecting exposure. Principal component analyses (PCA) and subsequent regression analyses on the scores of the identified principal components were used to relate potential co-exposures to various exposure sources present in the workplace. RESULTS: The mean benzene exposure level was 21.86 p.p.m. (10th-90th percentiles 5.23-50.63 p.p.m.) in the smaller shoe factory (factory A) and 3.46 p.p.m. (10th-90th percentiles 0.20-7.00 p.p.m.) in the larger shoe factory (factory B). Within-factory exposure levels differed among job titles and were higher for subjects directly involved in handling glues. In contrast, mean toluene levels were relatively similar in the two factories (factory A, 9.52 p.p.m.; factory B, 15.88 p.p.m.). A seasonal trend was identified for both benzene and toluene in factory B. This could be explained in part by changes in air movement and ventilation patterns occurring during the year. A seasonal trend was not present in the smaller shoe factory, where general ventilation was absent. Supplemental analysis showed that exposure levels to other hydrocarbons were low (< or =5 p.p.m.), less than 5% of their respective ACGIH threshold limit values, and generally comparable in the two factories. PCA showed that co-exposures in factory B could largely be explained by glue sources that were used in distinct areas in the workplace. CONCLUSIONS: We demonstrated the occurrence of a broad range of benzene exposure levels in two shoe manufacturing factories in Tianjin, China. Benzene and toluene exposures were determined in part by the degree of contact with glues, the benzene and toluene content of each glue, air movement and ventilation patterns. The availability of long-term monthly personal monitoring data provides an excellent opportunity to estimate individual exposures at different times during the 1 yr period of observation.