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The carcinogenicity of opium consumption was recently evaluated by a Working Group convened by the International Agency for Research on Cancer (IARC). We supplement the recent IARC evaluation by conducting an extended systematic review as well as a quantitative meta-analytic assessment of the role of opium consumption and risk for selected cancers, evaluating in detail various aspects of study quality on meta-analytic findings. We searched the published literature to identify all relevant studies on opium consumption and risk of selected cancers in humans through 31 October, 2022. Meta-relative risks (mRRs) and associated 95% confidence intervals (CIs) were estimated using random-effects models for studies of cancer of the urinary bladder, larynx, lung, oesophagus, pancreas, and stomach. Heterogeneity among studies was assessed using the I2 statistic. We assessed study quality and conducted sensitivity analyses to evaluate the impact of potential reverse causation, protopathic bias, selection bias, information bias, and confounding. In total, 2 prospective cohort studies and 33 case–control studies were included. The overall pooled mRR estimated for ‘ever or regular’ versus ‘never’ use of opium ranged from 1.50 (95% CI 1.13–1.99, I2 = 0%, 6 studies) for oesophageal cancer to 7.97 (95% CI 4.79–13.3, I2 = 62%, 7 studies) for laryngeal cancer. Analyses of cumulative opium exposure suggested greater risk of cancer associated with higher opium consumption. Findings were robust in sensitivity analyses excluding studies prone to potential methodological sources of biases and confounding. Findings support an adverse association between opium consumption and cancers of the urinary bladder, larynx, lung, oesophagus, pancreas and stomach.

BackgroundOlder workers experience higher rates of fatal occupational injury than younger workers worldwide. In North Carolina, the population of older workers more than doubled between 2000 and 2017. In 2008, the Great Recession changed occupational patterns among all age groups. We examined annual rates and distribution of fatal occupational injuries experienced by older workers, comparing the pre-recession period (2000–2007) to the post-recession period (2009–2017).MethodsDetailed information on all fatal occupational injuries during the period between 1 January 2000 and 31 December 2017 were abstracted from the records of the North Carolina Office of the Chief Medical Examiner and the office of vital records. The decennial Census and American Community Survey were used to estimate the population at risk and derive annual rates of fatal occupational injury.ResultsDuring the study period, 537 occupational fatalities occurred among workers 55+ years of age. The rate of fatal occupational injury among older workers declined 2.8% per year, with a 7.7% yearly decline in the pre-recession period compared with a 1.4% increase per year in the post-recession period. Workers 65+ years of age experienced rate increases in both periods. The highest rates of unintentional fatal occupational injury (injuries that were not purposefully inflicted) were observed in forestry, fishing hunting and trapping, and wood building manufacturing. Intentional fatal occupational injury rates (homicide, suicide) were highest in transportation, gas/service stations and grocery/food stores.ConclusionsOlder workers have persistently high rates of fatal occupational injury in North Carolina before and after the Great Recession.

A covariate-adjusted estimate of an exposure-outcome association may be biased if the exposure variable suffers measurement error. We propose an approach to correct for exposure measurement error in a covariate-adjusted estimate of the association between a continuous exposure variable and outcome of interest. Our proposed approach requires data for a reference population in which the exposure was a priori set to some known level (e.g., 0, and is therefore unexposed); however, our approach does not require an exposure validation study or replicate measures of exposure, which are typically needed when addressing bias due to exposure measurement error. A key condition for this method, which we refer to as “partial population exchangeability,” requires that the association between a measured covariate and outcome in the reference population equals the association between that covariate and outcome in the target population in the absence of exposure. We illustrate the approach using simulations and an example.

Supplemental Figure 2. The association between smoking and ESR1-defined breast cancer subtypes.

Supplemental Figure 3. The association between smoking and LS-defined breast cancer subtypes.

Supplemental Figure 1. The association between smoking and ER-defined breast cancer subtypes.

Background: Smoking is a possible risk factor for breast cancer and has been linked to increased risk of estrogen receptor–positive (ER+) disease in some epidemiologic studies. It is unknown whether smoking has quantitative effects on ER expression.Methods: We examined relationships between smoking and ER expression from tumors of 1,888 women diagnosed with invasive breast cancer from a population-based study in North Carolina. ER expression was characterized using binary (±) and continuous measures for ER protein, ESR1 mRNA, and a multigene luminal score (LS) that serves as a measure of estrogen signaling in breast tumors. We used logistic and linear regression models to estimate temporal and dose-dependent associations between smoking and ER measures.Results: The odds of ER+, ESR1+, and LS+ tumors among current smokers (at the time of diagnosis), those who smoked 20 or more years, and those who smoked within 5 years of diagnosis were nearly double those of nonsmokers. Quantitative levels of ESR1 were highest among current smokers compared with never smokers overall [mean (log2) = 9.2 vs. 8.7, P < 0.05] and among ER+ cases; however, we did not observe associations between smoking measures and continuous ER protein expression.Conclusions: In relationship to breast cancer diagnosis, recent smoking was associated with higher odds of the ER+, ESR1+, and LS+ subtype. Current smoking was associated with elevated ESR1 mRNA levels and an elevated LS, but not with altered ER protein.Impact: A multigene LS and single-gene ESR1 mRNA may capture tumor changes associated with smoking. Cancer Epidemiol Biomarkers Prev; 27(1); 67–74. ©2017 AACR.

Supplemental Figure Legends

Supplemental Table 1. Estimated biomarker expression values for the effect of categorical smoking measures among all cases; Supplemental Table 2. Estimated biomarker expression values for the effect of categorical smoking measures among ER+ cases.

Objectives A recent paper by Doi et al. advocated completely replacing the relative risk (RR) with the odds ratio (OR) as the effect measure in clinical trials and meta-analyses with binary outcomes. Besides some practical advantages of RR over OR, Doi et al.’s key assumption that the OR is “portable” in the meta-analysis, that is, study-specific ORs are likely not correlated with baseline risks, was not well justified. Study designs and settings We summarized Spearman's rank correlation coefficient between study-specific ORs and baseline risks in 40,243 meta-analyses from the Cochrane Database of Systematic Reviews. Results Study-specific ORs tend to be higher in studies with lower baseline risks of disease for most meta-analyses in Cochrane Database of Systematic Reviews. Using an actual meta-analysis example, we demonstrate that there is a strong negative correlation between OR (RR or RD) with the baseline risk and the conditional effects notably vary with baseline risks. Conclusions Replacing RR or RD with OR is currently unadvisable in clinical trials and meta-analyses. It is possible that no effect measure is “portable” in a meta-analysis. In addition to the overall (or marginal) effect, we suggest presenting the conditional effect based on the baseline risk using a bivariate generalized linear mixed model.

Objective To systematically review and perform a meta-analysis of radiation associated risks of cardiovascular disease in all groups exposed to radiation with individual radiation dose estimates. Design Systematic review and meta-analysis. Main outcome measures Excess relative risk per unit dose (Gy), estimated by restricted maximum likelihood methods. Data sources PubMed and Medline, Embase, Scopus, Web of Science Core collection databases. Eligibility criteria for selecting studies Databases were searched on 6 October 2022, with no limits on date of publication or language. Animal studies and studies without an abstract were excluded. Results The meta-analysis yielded 93 relevant studies. Relative risk per Gy increased for all cardiovascular disease (excess relative risk per Gy of 0.11 (95% confidence interval 0.08 to 0.14)) and for the four major subtypes of cardiovascular disease (ischaemic heart disease, other heart disease, cerebrovascular disease, all other cardiovascular disease). However, interstudy heterogeneity was noted (P Conclusions Results provide evidence supporting a causal association between radiation exposure and cardiovascular disease at high dose, and to a lesser extent at low dose, with some indications of differences in risk between acute and chronic exposures, which require further investigation. The observed heterogeneity complicates a causal interpretation of these findings, although this heterogeneity is much reduced if only higher quality studies or those at moderate doses or low dose rates are considered. Studies are needed to assess in more detail modifications of radiation effect by lifestyle and medical risk factors. Systematic review registration PROSPERO CRD42020202036

Trace elements such as cadmium, arsenic, zinc or selenium increase or decrease risk of a wide range of human diseases. Their levels in toenails may provide a measure of mid-term intake of trace elements for studies in humans. However, in biologically and clinically aggressive diseases as pancreatic cancer, the progression of the disease could modify such concentrations and produce reverse causation bias. The aim was to analyze the influence of specific time intervals between several clinical events and the collection of toenails upon concentrations of trace elements in patients with pancreatic cancer. Subjects were 118 incident cases of pancreatic adenocarcinoma prospectively recruited in eastern Spain. Toenails were collected at cancer diagnosis, and soon thereafter interviews were conducted. Information on cancer signs and symptoms was obtained from medical records and patient interviews. Levels of 12 trace elements were determined in toenail samples by inductively coupled plasma mass spectrometry. General linear models adjusting for potential confounders were applied to analyze relations between log concentrations of trace elements and the time intervals, including the interval from first symptom of cancer to toenail collection (iST). Toenail concentrations of the 12 trace elements were weakly or not influenced by the progression of the disease or the diagnostic procedures. Concentrations of aluminum were slightly higher in subjects with a longer iST (age, sex and stage adjusted geometric means: 11.44 vs. 7.75 µg/g for iST > 120 days vs. ≤ 40 days). There was a weak inverse relation of iST with concentrations of zinc and selenium (maximum differences of about 20 and 0.08 µg/g, respectively). Conclusions: concentrations of the trace elements were weakly or not influenced by the development of the disease before toenail collection. Only concentrations of aluminum increased slightly with increasing iST, whereas levels of zinc and selenium decreased weakly. Even in an aggressive disease as pancreatic cancer, toenail concentrations of trace elements may provide a valid measure of mid-term intake of trace elements, unaffected by clinical events and disease progression. Supplementary Information The online version contains supplementary material available at 10.1007/s12403-021-00436-2.

Attention-deficit/hyperactivity-disorder (ADHD) is a leading neurodevelopmental disorder in children worldwide; however, few modifiable risk factors have been identified. Organophosphate esters (OPEs) are ubiquitous chemical compounds that are increasingly prevalent as a replacement for other regulated chemicals. Current research has linked OPEs to neurodevelopmental deficits. The purpose of this study was to assess gestational OPE exposure on clinically-assessed ADHD in children at age 3 years.In this nested case-control study within the Norwegian Mother, Father, and Child Cohort study, we evaluated the impact of OPE exposure at 17 weeks' gestation on preschool-age ADHD. Between 2007 and 2011, 260 ADHD cases were identified using the Preschool Age Psychiatric Assessment and compared to a birth-year-stratified control group of 549 children. We categorized bis(2-butoxyethyl) phosphate (BBOEP) and bis(1,3-dichloro-2-propyl) phosphate (BDCIPP) as values limit of detection (LOD) (BBOEP N = 386, BDCIPP N = 632), ≥LOD but limit of quantification (LOQ) (BBOEP N = 413; BDCIPP N = 75), or above LOQ (BBOEP N = 70; BDCIPP N = 102). Diphenyl phosphate (DPhP) and di-n-butyl phosphate (DnBP) were categorized as quartiles and also modeled with a log10 linear term. We estimated multivariable adjusted odds ratios (ORs) using logistic regression and examined modification by sex using an augmented product term approach.Mothers in the 3rd DnBP quartile had 1.71 times the odds of having a child with ADHD compared to the 1st quartile (95%CI: 1.13, 2.58); a similar trend was observed for log10 DnBP and ADHD. Mothers with BDCIPP ≥ LOD but LOQ had 1.39 times the odds of having a child with ADHD compared to those with BDCIPP LOD (95%CI: 0.83, 2.31). Girls had lower odds of ADHD with increasing BBOEP exposure (log10 OR: 0.55 (95%CI: 0.37, 0.93), however boys had a weakly increased odds (log10 OR: 1.25 (95%CI: 0.74, 2.11) p-interaction = 0.01].We found modest increased odds of preschool ADHD with higher DnBP and BDCIPP exposure.

ObjectivesRadon is carcinogenic, but more studies are needed to understand relationships with lung cancer and extrathoracic cancers at low exposures. There are few studies evaluating associations with cancer incidence or assessing the modifying effects of smoking.MethodsWe conducted a case–cohort study with 16 434 underground uranium miners in the Czech Republic with cancer incidence follow-up 1977–1996. Associations between radon exposure and lung cancer, and extrathoracic cancer, were estimated with linear excess relative rate (ERR) models. We examined potential modifying effects of smoking, time since exposure and exposure rate.ResultsUnder a simple ERR model, assuming a 5-year exposure lag, the estimated ERR of lung cancer per 100 working level months (WLM) was 0.54 (95% CI 0.33 to 0.83) and the estimated ERR of extrathoracic cancer per 100 WLM was 0.07 (95% CI −0.17 to 0.72). Most lung cancer cases were observed among smokers (82%), and the estimated ERR of lung cancer per 100 WLM was larger among smokers (ERR/100 WLM=1.35; 95% CI 0.84 to 2.15) than among never smokers (ERR/100 WLM=0.12; 95% CI −0.05 to 0.49). Among smokers, the estimated ERR of lung cancer per 100 WLM decreased with time since exposure from 3.07 (95% CI −0.04 to 10.32) in the period 5–14 years after exposure to 1.05 (95% CI 0.49 to 1.87) in the period 25+ years after exposure.ConclusionsWe observed positive associations between cumulative radon exposure and lung cancer, consistent with prior studies. We observed a positive association between cumulative radon exposure and extrathoracic cancers, although the estimates were small. There was evidence that the association between radon and lung cancer was modified by smoking in a multiplicative or super-multiplicative fashion.

Parameters representing adjusted treatment effects may be defined marginally or conditionally on covariates. The choice between a marginal or covariate-conditional parameter should be driven by the study question. However, an unappreciated benefit of marginal estimators is a reduction in susceptibility to finite-sample bias relative to the unpenalized maximum likelihood estimator of the covariate-conditional odds ratio (OR). Using simulation, we compare the finite-sample bias of different marginal and conditional estimators of the OR. We simulated a logistic model to have 15 events per parameter and two events per parameter. We estimated the covariate-conditional OR by maximum likelihood with and without Firth’s penalization. We used three estimators of the marginal OR: g-computation, inverse probability of treatment weighting (IPTW), and augmented inverse probability of treatment weighting (AIPW). At 15 events per parameter, as expected, all estimators were effectively unbiased. At two events per parameter, the unpenalized covariate-conditional estimator was notably biased, but penalized covariate-conditional and marginal estimators exhibited minimal bias.

To evaluate trends of nonmalignant respiratory disease (NMRD) mortality among US underground uranium miners on the Colorado Plateau, and to estimate the exposure-response association between cumulative radon progeny exposure and NMRD subtype mortality.Standardized mortality ratios (SMRs) and excess relative rates per 100 working level months (excess relative rate [ERR]/100 WLM) were estimated in a cohort of 4021 male underground uranium miners who were followed from 1960 through 2016.We observed elevated SMRs for all NMRD subtypes. Silicosis had the largest SMR (n = 52, SMR = 41.4; 95% confidence interval [CI]: 30.9, 54.3), followed by other pneumoconiosis (n = 49, SMR = 39.6; 95% CI: 29.6, 52.3) and idiopathic pulmonary fibrosis (IPF) (n = 64, SMR = 4.77; 95% CI 3.67, 6.09). SMRs for silicosis increased with duration of employment; SMRs for IPF increased with duration of employment and calendar period. There was a positive association between cumulative radon exposure and silicosis with evidence of modification by smoking (ERR/100 WLMUranium mining workers had excess NMRD mortality compared with the general population; this excess persisted throughout follow-up. Exposure-response analyses indicated a positive association between radon exposure and IPF and silicosis, but these analyses have limitations due to outcome misclassification and missing information on occupational co-exposures such as silica dust.

No safe level of lead in blood has been identified. Blood lead testing is required for children on Medicaid, but it is at the discretion of providers and parents for others. Elevated blood lead levels (EBLLs) cannot be identified in children who are not tested.The aims of this research were to identify determinants of lead testing and EBLLs among North Carolina children and estimate the number of additional children with EBLLs among those not tested.We linked geocoded North Carolina birth certificates from 2011-2016 to 2010 U.S. Census data and North Carolina blood lead test results from 2011-2018. We estimated the probability of being screened for lead and created inverse probability (IP) of testing weights. We evaluated the risk of an EBLL ofMothers of the 63.5% of children (402,002 of 633,159) linked to a blood lead test result were disproportionately young, Hispanic, Black, American Indian, or on Medicaid. In full models, maternal ageOur results indicate that current North Carolina lead screening strategies fail to identify over 30% (17,543 of 57,398) of children with subclinical lead poisoning and that accounting for characteristics at birth alters the conclusions about racial disparities in children's EBLLs. https://doi.org/10.1289/EHP10335.

We sought to determine whether combined chemical, mechanical, and heat cleaning was superior to standard cleaning for the decontamination of 32 sink and shower drains harboring carbapenemase-producing organisms (CPOs). Of 16 intervention drains, 10 (63%) were decontaminated until day 7 versus 1 (5%) of 16 comparator drains (P = .002). Intensive cleaning may be useful if administered repeatedly in drain-associated CPO outbreaks.

Suppose that an investigator wants to estimate an association between a continuous exposure variable and an outcome, adjusting for a set of confounders. If the exposure variable suffers classical measurement error, in which the measured exposures are distributed with independent error around the true exposure, then an estimate of the covariate-adjusted exposure-outcome association may be biased. We propose an approach to estimate a marginal exposure-outcome association in the setting of classical exposure measurement error using a disease score–based approach to standardization to the exposed sample. First, we show that the proposed marginal estimate of the exposure-outcome association will suffer less bias due to classical measurement error than the covariate-conditional estimate of association when the covariates are predictors of exposure. Second, we show that if an exposure validation study is available with which to assess exposure measurement error, then the proposed marginal estimate of the exposure-outcome association can be corrected for measurement error more efficiently than the covariate-conditional estimate of association. We illustrate both of these points using simulations and an empirical example using data from the Orinda Longitudinal Study of Myopia (California, 1989–2001).

International audience; A meta-analytic summary estimate of association often is calculated as an inverse variance weighted average of study-specific estimates of association. The variances of published estimates of association are derived from their associated confidence intervals under the assumptions typical of Wald-type statistics. However, in some research areas, epidemiological results typically are obtained by fitting linear excess relative rate models, and associated likelihood-based confidence intervals are often asymmetrical; consequently, reasonable estimates of variances associated with study-specific estimates of association may be difficult to infer from the standard approach based on the assumption of a Wald-type interval. We describe a novel method to derive estimates of variance for use in meta-analysis of published results obtained by fitting linear excess relative rate models. The approach is illustrated using a previously-published example of meta-analysis of epidemiological findings regarding circulatory disease following exposure to low-level ionizing radiation, and a new example of meta-analysis of epidemiological findings regarding leukemia following exposure to ionizing radiation from diagnostic procedures; and, the meta-analytic summary obtained using the proposed approach is compared to that obtained using the more classical approach to meta-analysis. Keywords: meta-analysis; cohort studies; excess relative risk; cancer Abbreviations: RR, relative rate; CI, confidence interval; ERR, excess relative rate; Sv, sievert.

BackgroundLow-dose, penetrating photon radiation exposure is ubiquitous, yet our understanding of cancer risk at low doses and dose rates derives mainly from high-dose studies. Although a large number of low-dose cancer studies have been recently published, concern exists about the potential for confounding to distort findings. The aim of this study was to describe and assess the likely impact of confounding and selection bias within the context of a systematic review.MethodsWe summarized confounding control methods for 26 studies published from 2006 to 2017 by exposure setting (environmental, medical, or occupational) and identified confounders of potential concern. We used information from these and related studies to assess evidence for confounding and selection bias. For factors in which direct or indirect evidence of confounding was lacking for certain studies, we used a theoretical adjustment to determine whether uncontrolled confounding was likely to have affected the results.ResultsFor medical studies of childhood cancers, confounding by indication (CBI) was the main concern. Lifestyle-related factors were of primary concern for environmental and medical studies of adult cancers and for occupational studies. For occupational studies, other workplace exposures and healthy worker survivor bias were additionally of interest. For most of these factors, however, review of the direct and indirect evidence suggested that confounding was minimal. One study showed evidence of selection bias, and three occupational studies did not adjust for lifestyle or healthy worker survivor bias correlates. Theoretical adjustment for three factors (smoking and asbestos in occupational studies and CBI in childhood cancer studies) demonstrated that these were unlikely to explain positive study findings due to the rarity of exposure (eg, CBI) or the relatively weak association with the outcome (eg, smoking or asbestos and all cancers).ConclusionConfounding and selection bias are unlikely to explain the findings from most low-dose radiation epidemiology studies.

ObjectivesTo assess lung cancer mortality across occupations and economic activities/industries in Switzerland using three statistical estimates.MethodsAll Swiss residents aged 18–65 during the 1990 or 2000 censuses were followed through 2014 to ascertain information on date and cause of death. For every occupation and economic activity/industry, causal mortality ratios (CMR) and standardised mortality ratios (SMR) were computed using national cause-specific mortality rates. We also calculated relative SMR (rSMR) and conducted analyses stratified by socioeconomic variables, job skill level and calendar periods.ResultsThe study sample comprised 5 834 618 participants (111 162 348 person-years). SMR and CMR led to similar results, while rSMR were generally higher. We found 18 occupations in men, 10 occupations in women and 3 industries in each sex with an excess of lung cancer mortality. Among men, rubber and plastic products machine operators, and workers in mining and quarrying, and construction industries were at high risk. Among women, motor vehicle drivers and workers in trade, repair of motor vehicles and of domestic articles and manufacture of goods industries showed the highest risks. In both sexes, hotel and restaurant workers presented an excess of lung cancer mortality.ConclusionMost of the activities and occupations in which we observed excess lung cancer mortality have previously been observed to involve occupational exposure to lung carcinogens. These findings suggest that the number of occupational lung cancer is likely underestimated by the official Swiss statistics. Further research should address this question and the exposure–effect relationships in the most at-risk occupational groups.