The contents of each tube were then

diluted 1 in 10 and a

The contents of each tube were then

diluted 1 in 10 and analysed by ICP-MS as per the method specified above. Five of each sample type were analysed. In order to ascertain whether a worker with a “steady” history of lead exposure would produce differing results to one whose lead exposure had fluctuated, it was necessary to quantify the degree to which each worker’s historical exposure had fluctuated. Over 90% of the lead content of whole blood is contained in the erythrocytes (Goyer, 2001). The average survival time of erythrocytes in the bloodstream is 120 days (Dessypris, 1999). To account for this, the mean of all blood lead values acquired since January 2009, and recorded ≥120 days Selleck Doxorubicin prior to the measurement of the study sample, was calculated for each individual. The difference between the result of the study blood lead value and the mean of the historical observations (Δ) was then calculated. The median Δ was −1 μg/dL, and the 25th and 75th percentiles −2 μg/dL and +1 μg/dL respectively. However, the presence of a small number of large Δ values produced an overall standard deviation Selleck Pexidartinib of 9.49 μg/dL. It was decided to categorise the samples for their exposure history according to the magnitude of Δ. History “1” included all samples where Δ ≤ ± 1 μg/dL; history

“2” all samples where Δ ≤ ± 2 μg/dL; history “3” all samples where Δ ≤ ± 3 μg/dL. Samples where Δ > ± 3 μg/dL were categorised as “fluctuating history”. Samples with no blood lead values recorded ≥120 days prior to the measurement of the study sample were categorised as “no sample history”. Neither the blood lead nor the salivary lead data were normally distributed, with the salivary

lead data more skewed than the blood Resminostat lead data. Both datasets could be much more closely approximated to a log-normal distribution; therefore the relationship between log(saliva lead) and log(blood lead) was investigated. Log(saliva lead) was plotted against log(blood lead) and the Pearson’s correlation coefficient (r) was calculated, for the entire dataset and for the various history categories. Multiple regression analyses were also carried out to investigate whether smoking status or the age of the participant had any effect on the saliva or blood lead levels, or on the relationship between the two. For the blood lead analysis, all CRM results were within the certified range. Values obtained for the CRMs were as follows: level 1 lot 36741 (certified range 9.39–14.1 μg/dL): n = 91 mean 11.1 μg/dL, standard deviation (SD) 0.63 μg/dL; level 3 lot 36743 (certified range 43.7–65.5 μg/dL): n = 91, mean 52.5 μg/dL, SD 2.81 μg/dL. The limit of detection (LOD) for the saliva analysis for the study was 0.011 μg/L, based on the mean of all the blank samples, plus three times the standard deviation of the mean (McNaught and Wilkinson, 1997). All results were greater than the LOD and therefore no non-detects were observed.

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