Background: Diesel engine exhaust (DEE) has recently been classified as a known human carcinogen.Objective: We derived a meta-exposure–response curve (ERC) for DEE and lung cancer mortality and estimated lifetime excess risks (ELRs) of lung cancer mortality based on assumed occupational and environmental exposure scenarios.Methods: We conducted a meta-regression of lung cancer mortality and cumulative exposure to elemental carbon (EC), a proxy measure of DEE, based on relative risk (RR) estimates reported by three large occupational cohort studies (including two studies of workers in the trucking industry and one study of miners). Based on the derived risk function, we calculated ELRs for several lifetime occupational and environmental exposure scenarios and also calculated the fractions of annual lung cancer deaths attributable to DEE.Results: We estimated a lnRR of 0.00098 (95% CI: 0.00055, 0.0014) for lung cancer mortality with each 1-μg/m3-year increase in cumulative EC based on a linear meta-regression model. Corresponding lnRRs for the individual studies ranged from 0.00061 to 0.0012. Estimated numbers of excess lung cancer deaths through 80 years of age for lifetime occupational exposures of 1, 10, and 25 μg/m3 EC were 17, 200, and 689 per 10,000, respectively. For lifetime environmental exposure to 0.8 μg/m3 EC, we estimated 21 excess lung cancer deaths per 10,000. Based on broad assumptions regarding past occupational and environmental exposures, we estimated that approximately 6% of annual lung cancer deaths may be due to DEE exposure.Conclusions: Combined data from three U.S. occupational cohort studies suggest that DEE at levels common in the workplace and in outdoor air appear to pose substantial excess lifetime risks of lung cancer, above the usually acceptable limits in the United States and Europe, which are generally set at 1/1,000 and 1/100,000 based on lifetime exposure for the occupational and general population, respectively.Citation: Vermeulen R, Silverman DT, Garshick E, Vlaanderen J, Portengen L, Steenland K. 2014. Exposure-response estimates for diesel engine exhaust and lung cancer mortality based on data from three occupational cohorts. Environ Health Perspect 122:172–177; http://dx.doi.org/10.1289/ehp.1306880

SummaryAims: This systematic review and meta-analysis evaluated the associations between shift work patterns and risks of specific types of obesity.Methods: PubMed was searched until March 2017 for observational studies that examined the relationships between shift work patterns and obesity. Odds ratio for obesity was extracted using a fixed-effects or random-effects model. Subgroup meta-analyses were carried out for study design, specific obesity types and characteristics of shift work pattern.Results: A total of 28 studies were included in this meta-analysis. The overall odds ratio of night shift work was 1.23 (95% confidence interval = 1.17-1.29) for risk of obesity/overweight. Cross-sectional studies showed a higher risk of 1.26 than those with the cohort design (risk ratio = 1.10). Shift workers had a higher frequency of developing abdominal obesity (odds ratio = 1.35) than other obesity types. Permanent night workers demonstrated a 29% higher risk than rotating shift workers (odds ratio 1.43 vs. 1.14). Conclusion:This meta-analysis confirmed the risks of night shift work for the development of overweight and obesity with a potential gradient association suggested, especially for abdominal obesity. Modification of working schedules is recommended, particularly for prolonged permanent night work. More accurate and detailed measurements on shift work patterns should be conducted in future research.

Background:The exposome constitutes a promising framework to improve understanding of the effects of environmental exposures on health by explicitly considering multiple testing and avoiding selective reporting. However, exposome studies are challenged by the simultaneous consideration of many correlated exposures.Objectives:We compared the performances of linear regression–based statistical methods in assessing exposome-health associations.Methods:In a simulation study, we generated 237 exposure covariates with a realistic correlation structure and with a health outcome linearly related to 0 to 25 of these covariates. Statistical methods were compared primarily in terms of false discovery proportion (FDP) and sensitivity.Results:On average over all simulation settings, the elastic net and sparse partial least-squares regression showed a sensitivity of 76% and an FDP of 44%; Graphical Unit Evolutionary Stochastic Search (GUESS) and the deletion/substitution/addition (DSA) algorithm revealed a sensitivity of 81% and an FDP of 34%. The environment-wide association study (EWAS) underperformed these methods in terms of FDP (average FDP, 86%) despite a higher sensitivity. Performances decreased considerably when assuming an exposome exposure matrix with high levels of correlation between covariates.Conclusions:Correlation between exposures is a challenge for exposome research, and the statistical methods investigated in this study were limited in their ability to efficiently differentiate true predictors from correlated covariates in a realistic exposome context. Although GUESS and DSA provided a marginally better balance between sensitivity and FDP, they did not outperform the other multivariate methods across all scenarios and properties examined, and computational complexity and flexibility should also be considered when choosing between these methods.Citation:Agier L, Portengen L, Chadeau-Hyam M, Basagaña X, Giorgis-Allemand L, Siroux V, Robinson O, Vlaanderen J, González JR, Nieuwenhuijsen MJ, Vineis P, Vrijheid M, Slama R, Vermeulen R. 2016. A systematic comparison of linear regression–based statistical methods to assess exposome-health associations. Environ Health Perspect 124:1848–1856; http://dx.doi.org/10.1289/EHP172

We conducted a random-effects meta-analysis of 50 publications assessing the relationship between oral/oropharyngeal cancer and chewing betel quid, with (BQ1T) or without added tobacco (BQ-T), a common practice in many parts of Asia and globally among Asian immigrants. Exposure-response, by daily amount and years of BQ chewed, was assessed using spline models. Attributable fractions (PAF%) were calculated to estimate the public health impact if BQ were no longer chewed. The meta-relative risk (mRR) for oral/oropharyngeal cancer in the Indian subcontinent was 2.56 (95%CI, 2.00-3.28; 15 studies) for BQ-T and 7.74 (95%CI, 5.38-11.13; 31 studies) for BQ1T; in Taiwan, China, the mRR for BQ-T was 10.98 (95%CI, 4.86-24.84; 13 studies). Restricting to studies that adjusted for tobacco and alcohol use had only a small effect on the risk estimates. For BQ1T in the Indian subcontinent, the mRR was much higher in women (mRR, 14.56; 95%CI,) than in men. Exposure-response analyses showed that the risk of oral/oropharyngeal cancer increased with increasing daily amount and duration (years) of chewing BQ in India and Taiwan, China. Roughly half of oral cancers in these countries could be prevented if BQ were no longer chewed (PAF% 5 53.7% for BQ-T in Taiwan, China; PAF% 5 49.5% for BQ1T in India). We demonstrate that betel quid chewing, with or without added tobacco, increases the risk of oral/oropharyngeal cancer in an exposure-dependent manner, independently of tobacco and alcohol use. Further work is needed to explain the higher risks associated with chewing BQ-T