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To investigate the risk of lung cancer after exposure to welding fumes, hexavalent chromium (Cr(VI)), and nickel, we analyzed 3,418 lung cancer cases and 3,488 controls among men from 2 German case-control studies (1988–1996). We developed a welding-process exposure matrix from measurements of these agents, and this was linked with welding histories from a job-specific questionnaire to calculate cumulative exposure variables. Logistic regression models were fitted to estimate odds ratios with confidence intervals conditional on study, and they adjusted for age, smoking, and working in other at-risk occupations. Additionally, we mutually adjusted for the other exposure variables under study. Overall, 800 cases and 645 controls ever worked as regular or occasional welders. Odds ratios for lung cancer with high exposure were 1.55 (95% confidence interval (CI): 1.17, 2.05; median, 1.8 mg/m3 × years) for welding fumes, 1.85 (95% CI: 1.35, 2.54; median, 1.4 μg/m3 × years) for Cr(VI), and 1.60 (95% CI: 1.21, 2.12; median, 9 μg/m3 × years) for nickel. Risk estimates increased with increasing cumulative exposure to welding fumes and with increasing exposure duration for Cr(VI) and nickel. Our results showed that welding fumes, Cr(VI), and nickel might contribute independently to the excess lung cancer risk associated with welding. However, quantitative exposure assessment remains challenging.

Lead (Pb) is a recognized neurotoxin. Pb2+ can interfere with divalent metal transporters and ion channels and may thus affect other brain metals and cation signaling in neurons. Thereby, cognitive and sensory functions can be impaired. Whereas cognitive effects are well described less is known about olfaction and motor functions in the general population at currently lower exposure levels. The objective of this study was to evaluate the influence of Pb in blood (PbB) on odor identification and fine motor skills within the framework of the Heinz Nixdorf Recall Study (HNRS), a prospective cohort study among an elderly German population. Data on odor identification assessed with Sniffin’ sticks and fine motor test results were collected during the second follow-up of HNRS (2011–2014) in 1188 elderly men aged 55 to 86 years. PbB was determined in 1140 blood samples archived at baseline (2000–2003) and in 796 samples from the second follow-up. The association between PbB and impaired odor identification (normosmia as reference) was estimated with proportional odds ratios (PORs) with 95% confidence intervals (CI). The odds ratios (OR) of substantially impaired dexterity (tapping hits 90th percentile) were estimated with mixed logistic regression models for test results with both hands, where PbB was adjusted for covariates. PbB at baseline (median 32.9 μg/L; 2.27% ≥90 μg/L) was higher than at follow-up (25.9 μg/L; 0.84% ≥90 μg/L). The individual concentrations were correlated (Spearman rs 0.59, 95% CI 0.54 – 0.63). PORs of an impaired odor identification in men with baseline PbB ≥90 μg/L were 1.96 (95% CI 0.94–4.11) and 1.57 (95% CI 0.47–5.19) with follow-up PbB. Fine-motor tests were not affected by elevated PbB with the exception of tapping in men with follow-up PbB ≥50 μg/L (OR 2.14, 95% CI 1.09–4.23). Increasing age had strong effects on all outcomes. Low education was associated with impaired odor identification, tapping, and aiming. Also, alcohol consumption and current smoking affected the test results, particularly steadiness. In this community-based cohort of elderly men, we could confirm indication of an influence of elevated PbB on odor identification. Small numbers of men with elevated PbB due to an on-going trend of decreasing PbB in the general population, strong covariates and multiple comparisons hamper the evaluation of adversity of these effects of PbB on olfaction and dexterity.

The aim of this study was to estimate average occupational exposure to inhalable nickel (Ni) using the German exposure database MEGA. This database contains 8052 personal measurements of Ni collected between 1990 and 2009 in adjunct with information on the measurement and workplace conditions. The median of all Ni concentrations was 9 μg/m3 and the 95th percentile was 460 μg/m3. We predicted geometric means (GMs) for welders and other occupations centered to 1999. Exposure to Ni in welders is strongly influenced by the welding process applied and the Ni content of the used welding materials. Welding with consumable electrodes of high Ni content (>30%) was associated with 10-fold higher concentrations compared with those with a low content (

This study aimed to estimate occupational exposure to inhalable hexavalent chromium (Cr(VI)) using the exposure database MEGA. The database has been compiling Cr(VI) concentrations and ancillary data about measurements at German workplaces. We analysed 3659 personal measurements of inhalable Cr(VI) collected between 1994 and 2009. Cr(VI) was determined spectrophotometrically at 540 nm after reaction with diphenylcarbazide. We assigned the measurements to pre-defined at-risk occupations using the information provided about the workplaces. Two-thirds of the measurements were below the limit of quantification (LOQ) and multiply imputed according to the distribution above LOQ. The 75th percentile value was 5.2 μg/m(3) and the 95th percentile was 57.2 μg/m(3). We predicted the geometric mean for 2h sampling in the year 2000, and the time trend of Cr(VI) exposure in these settings with and without adjustment for the duration of measurements. The largest dataset was available for welding (N = 1898), which could be further detailed according to technique. The geometric means were above 5 μg/m(3) in the following situations: spray painting, shielded metal arc welding, and flux-cored arc welding if applied to stainless steel. The geometric means were between 1 μg/m(3) and 5 μg/m(3) for gas metal arc welding of stainless steel, cutting, hard-chromium plating, metal spraying and in the chemical chromium industry. The exposure profiles described here are useful for epidemiologic and industrial health purposes. Exposure to Cr(VI) varies not only between occupations, but also within occupations as shown for welders. In epidemiologic studies, it would be desirable to collect exposure-specific information in addition to the job title.

Journal of occupational medicine and toxicology : JOMT 5(15), (2010). doi:10.1186/1745-6673-5-15, Published by BioMed Central Ltd., London