Nondifferential Exposure Misclassification Research Articles

Mobile phone use and brain tumour risk – COSMOS, a prospective cohort study

BackgroundEach new generation of mobile phone technology has triggered discussions about potential carcinogenicity from exposure to radiofrequency electromagnetic fields (RF-EMF). Available evidence has been insufficient to conclude about long-term and heavy mobile phone use, limited by differential recall and selection bias, or crude exposure assessment. The Cohort Study on Mobile Phones and Health (COSMOS) was specifically designed to overcome these shortcomings. MethodsWe recruited participants in Denmark, Finland, the Netherlands, Sweden, and the UK 2007–2012. The baseline questionnaire assessed lifetime history of mobile phone use. Participants were followed through population-based cancer registers to identify glioma, meningioma, and acoustic neuroma cases during follow-up. Non-differential exposure misclassification was reduced by adjusting estimates of mobile phone call-time through regression calibration methods based on self-reported data and objective operator-recorded information at baseline. Hazard ratios (HR) and 95% confidence intervals (CI) for glioma, meningioma, and acoustic neuroma in relation to lifetime history of mobile phone use were estimated with Cox regression models with attained age as the underlying time-scale, adjusted for country, sex, educational level, and marital status. Results264,574 participants accrued 1,836,479 person-years. During a median follow-up of 7.12 years, 149 glioma, 89 meningioma, and 29 incident cases of acoustic neuroma were diagnosed. The adjusted HR per 100 regression-calibrated cumulative hours of mobile phone call-time was 1.00 (95 % CI 0.98–1.02) for glioma, 1.01 (95 % CI 0.96–1.06) for meningioma, and 1.02 (95 % CI 0.99–1.06) for acoustic neuroma. For glioma, the HR for ≥ 1908 regression-calibrated cumulative hours (90th percentile cut-point) was 1.07 (95 % CI 0.62–1.86). Over 15 years of mobile phone use was not associated with an increased tumour risk; for glioma the HR was 0.97 (95 % CI 0.62–1.52). ConclusionsOur findings suggest that the cumulative amount of mobile phone use is not associated with the risk of developing glioma, meningioma, or acoustic neuroma.

Childhood body fatness and the risk of epithelial ovarian cancer: A population-based case-control study in Montreal, Canada

ObjectiveTo assess the association between childhood body fatness and epithelial ovarian cancer (EOC), and whether this association differs by type of EOC. MethodsUsing data from a population-based case-control study (497 cases and 902 controls) in Montreal, Canada conducted 2011–2016, we examined the association between childhood body fatness and EOC, overall and separately for invasive vs. borderline EOCs. A figure rating scale was used to measure body fatness at ages 5 and 10. Multivariable logistic regression was used to estimate adjusted odds ratios (aORs) and 95% confidence intervals (95% CI). Quantitative bias analyses were conducted to assess the impact of exposure misclassification and non-participation. ResultsThe aOR (95% CI) of overall EOC for high vs. low body fatness was 1.07 (0.85–1.34) at age 5 and 1.28 (0.98–1.68) at age 10. The associations were stronger for invasive EOC, specifically the endometrioid histological type. For borderline cancers, the aORs were below the null value with wide confidence intervals. Bias analyses did not reveal a strong influence of non-participation. Non-differential exposure misclassification may have biased aORs towards the null for invasive cancers but did not appear to have an appreciable influence on the aORs for borderline cancers. ConclusionsChildhood body fatness may be a risk factor for invasive EOC in later adult life. Our study highlights the potential importance of examining early life factors for a comprehensive understanding of EOC development.

Does adjustment for non-differential misclassification of dichotomous exposure induce positive bias if there is no true association?

This article is a response to an off-the-record discussion that I had at an international meeting of epidemiologists more than decade ago. It centered on a concern, perhaps widely spread, that adjustment for exposure misclassification can induce a false positive result. I trace the possible history of this supposition and test it in a simulated case-control study under the assumption of non-differential misclassification of binary exposure, in which a Bayesian adjustment is applied. Probabilistic bias analysis is also briefly considered. The main conclusion is that adjustment for the presumed non-differential exposure misclassification of dichotomous does not “induce” positive associations, especially if the focus of the interpretation of the result is taken away from the point estimate. The misconception about positive bias induced by adjustment for exposure misclassification, if more clearly explained during the training of epidemiologists, may promote appropriate (and wider) use of the adjustment techniques. The simple message that can be derived from this paper is: “Exposure misclassification as a tractable problem that deserves much more attention than just a typical qualitative throw-away discussion”.

Exposure to pesticides and risk of Hodgkin lymphoma in an international consortium of agricultural cohorts (AGRICOH)

PurposeSome pesticides may increase the risk of certain lymphoid malignancies, but few studies have examined Hodgkin lymphoma (HL). In this exploratory study, we examined associations between agricultural use of 22 individual active ingredients and 13 chemical groups and HL incidence.MethodsWe used data from three agricultural cohorts participating in the AGRICOH consortium: the French Agriculture and Cancer Cohort (2005–2009), Cancer in the Norwegian Agricultural Population (1993–2011), and the US Agricultural Health Study (1993–2011). Lifetime pesticide use was estimated from crop-exposure matrices or self-report. Cohort-specific covariate-adjusted overall and age-specific (< 40 or ≥ 40 years) hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox regression and combined using random effects meta-analysis.ResultsAmong 316 270 farmers (75% male) accumulating 3 574 815 person-years at risk, 91 incident cases of HL occurred. We did not observe statistically significant associations for any of the active ingredients or chemical groups studied. The highest risks of HL overall were observed for the pyrethroids deltamethrin (meta-HR = 1.86, 95% CI 0.76–4.52) and esfenvalerate (1.86, 0.78–4.43), and inverse associations of similar magnitude were observed for parathion and glyphosate. Risk of HL at ≥ 40 years of age was highest for ever-use of dicamba (2.04, 0.93–4.50) and lowest for glyphosate (0.46, 0.20–1.07).ConclusionWe report the largest prospective investigation of these associations. Nonetheless, low statistical power, a mixture of histological subtypes and a lack of information on tumour EBV status complicate the interpretability of the results. Most HL cases occurred at older ages, thus we could not explore associations with adolescent or young adult HL. Furthermore, estimates may be attenuated due to non-differential exposure misclassification. Future work should aim to extend follow-up and refine both exposure and outcome classification.

Self-reported Human Papillomavirus Vaccination and Vaccine Effectiveness Among Men Who Have Sex with Men: A Quantitative Bias Analysis.

Self-report of human papillomavirus (HPV) vaccination has ~80-90% sensitivity and ~75-85% specificity. We measured the effect of nondifferential exposure misclassification associated with self-reported vaccination on vaccine effectiveness (VE) estimates. Between 2017-2019, we recruited sexually active gay, bisexual, and other men who have sex with men aged 16-30 years in Canada. VE was derived as 1-prevalence ratio × 100% for prevalent anal HPV infection comparing vaccinated (≥1 dose) to unvaccinated men using a multivariable modified Poisson regression. We conducted a multidimensional and probabilistic quantitative bias analysis to correct VE estimates. Bias-corrected VE estimates were relatively stable across sensitivity values but differed from the uncorrected estimate at lower values of specificity. The median adjusted VE was 27% (2.5-97.5th simulation interval = -5-49%) in the uncorrected analysis, increasing to 39% (2.5-97.5th simulation interval = 2-65%) in the bias-corrected analysis. A large proportion of participants erroneously reporting HPV vaccination would be required to meaningfully change VE estimates.

Association between Outdoor Air Pollution Exposure and Handgrip Strength: Findings from the French CONSTANCES Study.

Association between Outdoor Air Pollution Exposure and Handgrip Strength: Findings from the French CONSTANCES Study.

BCG vaccination at birth and COVID-19: a case-control study among U.S. military Veterans

ABSTRACT In the early stages of the COVID-19 global pandemic, caused by the SARS-CoV-2 virus, low- and middle-income countries (LMICs) appeared to be experiencing lower morbidity and mortality rates than high-income countries, particularly the United States. Various suggestions put forward to account for this included the possibility that LMICs might be experiencing off-target benefits of infant vaccination with BCG, intended primarily to protect against tuberculosis. A number of ecologic epidemiological studies that considered COVID-19 morbidity and mortality rates across countries appeared to support this suggestion. Ecologic studies, however, are primarily hypothesis-generating, given their well-known limitations in extrapolating to the individual-person level. The present study, which employed anonymized records of U.S. Military Veterans treated by the Department of Veterans Affairs was principally a case-control study of COVID-19 infections with a retrospective cohort study of mortality nested within the infections. Controls were a random sample of Veterans not recorded as having had COVID-19. There were 263,039 controls and 167,664 COVID-19 cases, of whom 5,016 died. The combination of country and year of birth was used as a surrogate for infant BCG vaccination. The study did not support the hypothesis that BCG in infancy was protective against COVID-19. The odds ratio for infection was 1.07 (95% confidence interval [CI]: 1.03, 1.11) and the risk ratio for mortality among the COVID-19 cases was 0.86 (95% CI: 0.63, 1.18). The potential for non-differential exposure misclassification was a concern, possibly biasing measures of association toward the null value.

Does administration of vaginal estrogens increase the risk of venous thromboembolism: A case-control study.

Does administration of vaginal estrogens increase the risk of venous thromboembolism: A case-control study.

P–773 Infertility treatment and the risk of small for gestational age births: a population-based study in the United States

Abstract Study question What is the association between infertility treatments and small for gestational age (SGA) births? Summary answer Women who conceived pregnancies with any infertility treatment had a decreased risk of SGA &amp;lt;10th, &amp;lt;5th and &amp;lt;3rd percentiles compared to naturally conceived pregnancies. What is known already Assisted reproductive technology (ART) and other infertility treatments have long been associated with an increased risk of SGA births, which confers a greater risk of perinatal morbidity and mortality compared to appropriate for gestational age births. Study design, size, duration This is a cross-sectional study of 16,836,228 births in the United States (US) between 2015–2019. The exposure group included women who underwent any infertility treatment, including ART and prescribed fertility enhancing medications. The comparison group included those who had naturally conceived pregnancies. The primary outcome was SGA birth, defined as sex-specific birthweight &amp;lt;10th percentile for gestational age. Secondary outcomes included SGA &amp;lt;5th and &amp;lt;3rd percentile births. Participants/materials, setting, methods Pregnant subjects (n = 16,836,228) in the US who delivered non-malformed, singleton live births between 24–44 weeks’ gestational age. We estimated risk of SGA births in relation to any infertility treatment from fitting log-linear Poisson regression models with robust variance. Risk ratios (RR) and 95% confidence intervals (CI) were estimated as the effect measure before and after adjusting for confounders. We also performed a sensitivity analysis to correct for potential non-differential exposure misclassification and unmeasured confounding biases. Main results and the role of chance During the study period, 1.4% (n = 231,177) of non-malformed singleton live births resulted from infertility treatments (0.8% ART and 0.6% fertility enhancing medications). Of these, 9.4% (n = 21,771) of pregnancies conceived with infertility treatment were complicated by SGA &amp;lt;10th percentile compared to 11.9% (n = 1,755,925) of naturally conceived pregnancies. For pregnancies conceived with infertility treatment versus naturally conceived pregnancies, the adjusted RR for SGA &amp;lt;10th percentile was 1.07 (95% CI 1.06, 1.08). However, after correction for misclassification bias and unmeasured confounding, infertility treatment was found to be protective for SGA and conferred a 27% reduced risk of SGA &amp;lt;10th percentile (bias-corrected RR 0.73, 95% CI 0.53, 0.85). These trends were similar for analyses stratified by exposure to ART and fertility enhancing medications and secondary SGA outcomes, including SGA &amp;lt;5th and &amp;lt;3rd percentile. Limitations, reasons for caution All information collected on infertility treatment relies on self-reporting by patients and recording by hospital staff at the time of delivery, which likely resulted in underreporting of infertility treatments. Additionally, we cannot determine the impact of interventions that were not recorded, such as intrauterine insemination (IUI). Wider implications of the findings: Compared to naturally conceived pregnancies, exposure to infertility treatment is associated with reduction in the risk of SGA births. These findings, which are contrary to some published reports, likely reflect changes in the modern practice of infertility care in the US, and importantly, robust analysis of the national data. Trial registration number Not applicable

Predictors of postdischarge follow-up attendance among hospitalized dermatology patients: Disparities and potential interventions

Predictors of postdischarge follow-up attendance among hospitalized dermatology patients: Disparities and potential interventions

Infertility treatment and the risk of small for gestational age births: a population-based study in the United States

ObjectiveTo evaluate the association between infertility treatments and small for gestational age (SGA) births.DesignCross-sectional study.SettingUnited States, 2015–2019.Patient(s)Women (n = 16,836,228) who delivered nonmalformed, singleton live births (24–44 weeks’ gestation).Intervention(s)Any infertility treatment, including assisted reproductive technology (ART) and prescribed fertility-enhancing medications.Main Outcome Measure(s)Small for gestational age birth, defined as sex-specific birth weight <10% for gestational age. Associations between SGA and infertility treatment were derived from Poisson regression with robust variance. Risk ratios (RR) and 95% confidence intervals (CI) were derived after adjusting for confounders. In a sensitivity analysis, we corrected for nondifferential exposure misclassification and unmeasured confounding biases.Result(s)Subsequently, 1.4% (n = 231,177) of pregnancies resulted from infertility treatments (0.8% ART and 0.6% fertility-enhancing medications). Of these, SGA births occurred in 9.4% (n = 21,771) and 11.9% (n = 1,755,925) of pregnancies conceived with infertility treatment and naturally conceived pregnancies, respectively (adjusted RR, 1.07; 95% CI, 1.06, 1.08). However, after correction for misclassification bias and unmeasured confounding, infertility treatment was associated with a 27% reduced risk of SGA (bias-corrected RR, 0.73; 95% CI, 0.53, 0.85). Similar trends were seen for analyses stratified by exposure to ART and fertility-enhancing medications, as well as for SGA <5th and <3rd percentiles.Conclusion(s)Exposure to infertility treatment is associated with a reduced risk of SGA births. These findings, which are contrary to some published reports, may reflect changes in the modern practice of infertility care, maternal lifestyle, and compliance with prenatal care within the infertile population. Until these findings are corroborated, the associations must be cautiously interpreted.

Exposure misclassification bias in the estimation of vaccine effectiveness.

In epidemiology, a typical measure of interest is the risk of disease conditional upon exposure. A common source of bias in the estimation of risks and risk ratios is misclassification. Exposure misclassification affects the measurement of exposure, i.e. the variable one conditions on. This article explains how to assess biases under non-differential exposure misclassification when estimating vaccine effectiveness, i.e. the vaccine-induced relative reduction in the risk of disease. The problem can be described in terms of three binary variables: the unobserved true exposure status, the observed but potentially misclassified exposure status, and the observed true disease status. The bias due to exposure misclassification is quantified by the difference between the naïve estimand defined as one minus the risk ratio comparing individuals observed as vaccinated with individuals observed as unvaccinated, and the vaccine effectiveness defined as one minus the risk ratio comparing truly vaccinated with truly unvaccinated. The magnitude of the bias depends on five factors: the risks of disease in the truly vaccinated and the truly unvaccinated, the sensitivity and specificity of exposure measurement, and vaccination coverage. Non-differential exposure misclassification bias is always negative. In practice, if the sensitivity and specificity are known or estimable from external sources, the true risks and the vaccination coverage can be estimated from the observed data and, thus, the estimation of vaccine effectiveness based on the observed risks can be corrected for exposure misclassification. When analysing risks under misclassification, careful consideration of conditional probabilities is crucial.

An underappreciated misclassification mechanism: implications of nondifferential dependent misclassification of covariate and exposure

Misclassification is a pervasive problem in assessing relations between exposures and outcomes. While some attention has been paid to the impact of dependence in measurement error between exposures and outcomes, there is little awareness of the potential impact of dependent error between exposures and covariates, despite the fact that this latter dependency may occur much more frequently, for example, when both are assessed by questionnaire. We explored the impact of nondifferential dependent exposure-confounder misclassification bias by simulating a dichotomous exposure (E), disease (D) and covariate (C) with varying degrees of non-differential dependent misclassification between C and E. We demonstrate that under plausible scenarios, an adjusted association can be a poorer estimate of the true association than the crude. Correlated errors in the measurement of covariate and exposure distort the covariate-exposure, covariate-outcome and exposure-outcome associations creating observed associations that can be greater than, less than, or in the opposite direction of the true associations. Under these circumstances adjusted associations may not be bounded by the crude association and true effect, as would be expected with nondifferential independent confounder misclassification. The degree and direction of distortion depends on the amount of dependent error, prevalence of covariate and exposure, and magnitude of true effect.

Occupational epidemiologist's quest to tame measurement error in exposure

I aimed to assess current practices and opportunities for addressing the problem of errors in exposure in occupational epidemiology. Occupational epidemiologists appreciate that errors in exposure are a concern, but almost none correct for these errors, although there are currently no theoretical and practical barriers for this inertia. The most serious barrier to change is a faulty belief that a well-conducted epidemiologic study suffers only non-differential exposure misclassification and that its sole impact is to attenuate risk gradients, causing a false negative. On the contrary, differential exposure misclassification is the most defensible model in occupational epidemiology, and errors in exposure increase chance of both false positive and negative results. Resistance to mathematical adjustment for errors in exposure is equivalent to denying the value of more valid exposure estimates and undermines the discipline's relevance to protection of workers by informing workplace exposure limits.

Simulation as a Tool for Teaching and Learning Epidemiologic Methods.

In aspiring to be discerning epidemiologists, we must learn to think critically about the fundamental concepts in our field and be able to understand and apply many of the novel methods being developed today. We must also find effective ways to teach both basic and advanced topics in epidemiology to graduate students, in a manner that goes beyond simple provision of knowledge. Here, we argue that simulation is one critical tool that can be used to help meet these goals, by providing examples of how simulation can be used to address 2 common misconceptions in epidemiology. First, we show how simulation can be used to explore nondifferential exposure misclassification. Second, we show how an instructor could use simulation to provide greater clarity on the correct definition of the P value. Through these 2 examples, we highlight how simulation can be used to both clearly and concretely demonstrate theoretical concepts, as well as to test and experiment with ideas, theories, and methods in a controlled environment. Simulation is therefore useful not only in the classroom but also as a skill for independent self-learning.

Post-approval Safety Surveillance Study of Golimumab in the Treatment of Rheumatic Disease Using a United States Healthcare Claims Database.

Background and ObjectiveGolimumab is a fully human anti-tumor necrosis factor monoclonal antibody approved for the treatment of rheumatoid arthritis (RA), psoriatic arthritis (PsA), and ankylosing spondylitis (AS). This study estimated rates of prespecified outcomes in patients with RA, PsA or AS initiating golimumab versus matched patients initiating non-biologic systemic (NBS) medications.MethodsPatients enrolled in a US health plan with rheumatic disease who initiated a study medication were accrued between April 2009 and November 2014. Golimumab initiators were matched by propensity score to NBS initiators in a 1:4 ratio. Outcomes were identified through September 2015. As-treated, as-matched, and nested case–control (NCC) analyses were conducted in the matched cohorts. Sensitivity analyses evaluated the impact of residual confounding and nondifferential misclassification of exposure and outcomes.ResultsRisks of outcomes were similar between golimumab and NBS initiators. In the as-treated analysis, the rate ratio (RR) for depression was elevated during current golimumab use versus golimumab non-use in the NBS cohort [RR 1.45, 95% confidence interval (CI) 1.31–1.61]. This finding was not replicated in as-matched (RR 1.08, 95% CI 0.97–1.19) or NCC (odds ratio 1.01, 95% CI 0.78–1.31) analyses, which focused on incident cases. Sensitivity analyses suggest that depression was sensitive to misclassification, and the RR changed from greater than to less than one across a plausible range of specificity.ConclusionsThis study suggests that there is no association between exposure to golimumab and an increased risk of prespecified outcomes. Increased depression risk in the as-treated analysis was not replicated in other analyses and may be associated with residual imbalance in baseline history or severity of depression.Electronic supplementary materialThe online version of this article (10.1007/s40261-020-00959-7) contains supplementary material, which is available to authorized users.

Pesticide residue intake from fruits and vegetables and fecundability in a North American preconception cohort study

Intake of conventionally-grown fruits and vegetables with higher levels of pesticide residue contamination has been associated with poorer semen quality and lower probability of live birth among couples undergoing fertility treatment. We examined the association between dietary intake of pesticide residues and fecundability, the per cycle probability of conception, in a preconception cohort of pregnancy planners. We enrolled women aged 21–45 years who were attempting to conceive without use of fertility treatment into Pregnancy Study Online (PRESTO) from June 2013 through September 2019. Participants completed a baseline questionnaire on demographics, lifestyle factors, and medical and reproductive histories, and bimonthly follow-up questionnaires for up to 12 months or until reported conception. Ten days after baseline, participants completed the National Cancer Institute’s Diet History Questionnaire II, a validated food frequency questionnaire. Using data from the USDA Pesticide Data Program, we classified fruits and vegetables as having high or low pesticide residues using a validated method. We examined the relation between greater intake of high- and low-pesticide residue fruits and vegetables with fecundability using proportional probabilities regression models, adjusted for potential confounders and accounting for consumption of organic produce. We restricted our analysis to 5234 women who had been attempting conception for ≤6 cycles at study entry, and further stratified by pregnancy attempt time at study entry (<3 vs. 3–6 cycles) to evaluate potential for reverse causation. Intakes of high- and low-pesticide residue fruits and vegetables were not appreciably related to fecundability in the full sample, or among women trying to conceive for <3 cycles at study entry. However, among women trying to conceive for 3–6 cycles at study entry, both high- and low-pesticide residue fruit and vegetable intakes were strongly inversely related to fecundability, indicating potential reverse causation bias. These results do not support the hypothesis that intake of pesticide residues from conventionally-grown fruits and vegetables is harmful to fertility, although non-differential exposure misclassification may have attenuated our findings.

Causal Mediation Analysis in the Presence of a Misclassified Binary Exposure

Abstract Mediation analysis is popular in examining the extent to which the effect of an exposure on an outcome is through an intermediate variable. When the exposure is subject to misclassification, the effects estimated can be severely biased. In this paper, when the mediator is binary, we first study the bias on traditional direct and indirect effect estimates in the presence of conditional non-differential misclassification of a binary exposure. We show that in the absence of interaction, the misclassification of the exposure will bias the direct effect towards the null but can bias the indirect effect in either direction. We then develop an EM algorithm approach to correcting for the misclassification, and conduct simulation studies to assess the performance of the correction approach. Finally, we apply the approach to National Center for Health Statistics birth certificate data to study the effect of smoking status on the preterm birth mediated through pre-eclampsia.

Low-to-moderate alcohol consumption and success in fertility treatment: a Danish cohort study

Does female weekly alcohol intake and binge drinking impact the chance of a successful fertility treatment? Low-to-moderate weekly alcohol drinking and binge drinking were not associated with the chance of achieving a clinical pregnancy or a live birth among women and couples undergoing medically assisted reproduction (MAR) treatments. Alcohol consumption is common among women of reproductive age, even though health authorities advise women trying to conceive to abstain from drinking. A growing number of couples struggle with infertility, but it is unknown whether low-to-moderate levels of alcohol consumption and alcohol binge drinking impair success in fertility treatment. Cohort study with prospectively collected exposure information including 1708 women and potential partners undergoing fertility treatment at the public fertility clinic, Aarhus University Hospital, 1 January 2010 to 31 August 2015. In total, data on 1511 intrauterine insemination (IUI) cycles, 2870 in vitro fertilization (IVF)/intracytoplasmic sperm injection (ICSI) cycles and 1355 frozen embryo transfer cycles. Exposure to weekly average alcohol intake was assessed from questionnaires completed by participants before the start of treatment. Outcome measures are the achievement of a clinical pregnancy and live birth in consecutive treatment cycles in the Danish national health registries, enabling complete follow-up. A modified Poisson regression with robust standard errors was used to evaluate associations between a weekly average alcohol intake and MAR outcomes, adjusting for female age, body mass index, cigarette smoking, coffee consumption, chronic diseases, level of education, and cycle number. When evaluating the association between binge drinking in the month prior to baseline and MAR outcomes the analyses were further adjusted for average weekly alcohol consumption. Low-to-moderate average weekly alcohol intake was not statistically significantly associated with the chance of achieving a clinical pregnancy or a live birth following IUI or IVF/ICSI treatment cycles. Compared to women abstaining from alcohol, the adjusted relative risks for achieving a live birth among those reporting 1-2, 3-7, and >7 drinks per week were 1.00 (95% CI 0.66; 1.53), 1.20 (0.76; 1.91), and 1.48 (0.56; 3.93), respectively, among women initiating IUI treatments. Among those initiating IVF/ICSI treatments, the chance for achieving a live birth among those reporting 1-2, 3-7, and >7 drinks per week were 1.00 (0.83; 1.21), 0.95 (0.75; 1.20), and 0.89 (0.53; 1.51), respectively. The chance of achieving a live birth in the first IUI or IVF/ICSI treatment cycle was unrelated to the number of binge drinking episodes in the month preceding baseline. The risk of non-differential exposure misclassification, confounding, or chance cannot be ruled out. In addition, due to the low number of women reporting an intake of >7 drinks/week, the potential effect of high alcohol consumption should be interpreted with caution. Although it remains unsettled if and how alcohol affects female reproduction, our results indicate that is not necessary to abstain from alcohol when striving for a successful outcome following fertility treatment. J.L. is supported by a fully financed Ph.D. scholarship from Aarhus University and has received funds from the A.P. Møller foundation. The funding sources had no involvement in the conduct of the article. Dr Kesmodel reports personal fees from MSD and Ferring Pharmaceuticals outside the submitted work. All other authors have no conflicts of interest to declare and all have completed the ICMJE disclosure form. Not relevant.

Pesticide use and risk of non-Hodgkin lymphoid malignancies in agricultural cohorts from France, Norway and the USA: a pooled analysis from the AGRICOH consortium.

BackgroundPesticides are commonly used in agriculture, and previous studies endorsed the need to further investigate the possible association between their use and risk of lymphoid malignancies in agricultural workers.MethodsWe investigated the relationship of ever use of 14 selected pesticide chemical groups and 33 individual active chemical ingredients with non-Hodgkin lymphoid malignancies (NHL) overall or major subtypes, in a pooled analysis of three large agricultural worker cohorts. Pesticide use was derived from self-reported history of crops cultivated combined with crop-exposure matrices (France and Norway) or self-reported lifetime use of active ingredients (USA). Cox regression models were used to estimate cohort-specific hazard ratios (HRs) and 95% confidence intervals (CIs), which were combined using random effects meta-analysis to calculate meta-HRs.ResultsDuring follow-up, 2430 NHL cases were diagnosed in 316 270 farmers accruing 3 574 815 person-years under risk. Most meta-HRs suggested no association. Moderately elevated meta-HRs were seen for: NHL and ever use of terbufos (meta-HR = 1.18, 95% CI: 1.00–1.39); chronic lymphocytic leukaemia/small lymphocytic lymphoma and deltamethrin (1.48, 1.06–2.07); and diffuse large B-cell lymphoma and glyphosate (1.36, 1.00–1.85); as well as inverse associations of NHL with the broader groups of organochlorine insecticides (0.86, 0.74–0.99) and phenoxy herbicides (0.81, 0.67–0.98), but not with active ingredients within these groups, after adjusting for exposure to other pesticides.ConclusionsAssociations of pesticides with NHL appear to be subtype- and chemical-specific. Non-differential exposure misclassification was an important limitation, showing the need for refinement of exposure estimates and exposure–response analyses.