Global Epidemiology最新文献

Environmental epidemiology has proven critical to study various associations between environmental exposures and adverse human health effects. However, there is a perception that it often does not sufficiently inform quantitative risk assessment. To help address this concern, in 2017, the Health and Environmental Sciences Institute initiated a project engaging the epidemiology, exposure science, and risk assessment communities with tripartite representation from government agencies, industry, and academia, in a dialogue on the use of environmental epidemiology for quantitative risk assessment and public health decision making. As part of this project, four meetings attended by experts in epidemiology, exposure science, toxicology, statistics, and risk assessment, as well as one additional meeting engaging funding agencies, were organized to explore incentives and barriers to realizing the full potential of epidemiological data in quantitative risk assessment. A set of questions was shared with workshop participants prior to the meetings, and two case studies were used to support the discussion.

Five key ideas emerged from these meetings as areas of desired improvement to ensure that human data can more consistently become an integral part of quantitative risk assessment: 1) reducing confirmation and publication bias, 2) increasing communication with funding agencies to raise awareness of research needs, 3) developing alternative funding channels targeted to support quantitative risk assessment, 4) making data available for reuse and analysis, and 5) developing cross-disciplinary and cross-sectoral interactions, collaborations, and training.

We explored and integrated these themes into a roadmap illustrating the need for a multi-stakeholder effort to ensure that epidemiological data can fully contribute to the quantitative evaluation of human health risks, and to build confidence in a reliable decision-making process that leverages the totality of scientific evidence.

We conducted a systematic review of epidemiology studies that evaluated the association between perchloroethylene (PCE) and non-Hodgkin's lymphoma (NHL). This included an independent detailed assessment of a few critical aspects of study quality (i.e., study design, exposure measurement, exposure levels, and potential confounding), and a consideration of other aspects of quality less formally. Of the identified 18 cohort studies of 15 unique cohorts, 17 case-control studies of 14 unique population groups, and 3 ecological studies, none was high quality for all four critical quality elements and each study also had other major methodological study limitations. Reported risk estimates were mostly null, ranged widely from below to above 1, and often had extremely wide confidence intervals (CIs), indicating unstable risk estimates. In addition, there was no consistent evidence of dose-response. Overall, given the low quality of the available epidemiology studies, the evidence does not support an association between PCE exposure and NHL.

Introduction

The US experienced a surge in use of e-cigarettes. Smoking women may consider e-cigarettes during pregnancy as an alternative to smoking. E-cigarettes typically contain nicotine, an established cause of reduction in fetal growth in animal studies.

Methods

This cohort study included 99,201 mothers who delivered live singletons in 2016–2018 from the Pregnancy Risk Assessment Monitoring System. We created exposure categories based on self-reported number of cigarettes smoked per day and vaping frequency and evaluated their associations with preterm birth and small-for-gestational-age (SGA) birth (two established cigarette smoking-related risks).

Results

Dual users in late pregnancy were a heterogeneous group: 29% lightly smoked and occasionally vaped; 19% lightly smoked and frequently vaped; 36% heavily smoked and occasionally vaped; and 15% heavily smoked and frequently vaped. While dual users who heavily smoked and occasionally vaped had the highest adjusted OR for SGA (3.4, 95% CI 2.0, 5.7), all the dual users had, on average, about twice the odds of having SGA than non-users. While the risks of preterm birth were higher among sole light smokers (adjusted OR 1.3, 95% CI 1.1, 1.5) and sole heavy smokers (adjusted OR 1.5. 95% CI 1.2, 1.8) than non-users, the adjusted odds of preterm birth for dual users were not noticeably higher than those of non-users.

Conclusion

Relative to non-users, both smoking and vaping during pregnancy appear to increase risk of SGA, but excess risk of preterm birth appears to be primarily attributable to smoking alone. Higher levels of exposure tended to confer more risk.

Misinterpretations of P-values and 95% confidence intervals are ubiquitous in medical research. Specifically, the terms significance or confidence, extensively used in medical papers, ignore biases and violations of statistical assumptions and hence should be called overconfidence terms. In this paper, we present the compatibility view of P-values and confidence intervals; the P-value is interpreted as an index of compatibility between data and the model, including the test hypothesis and background assumptions, whereas a confidence interval is interpreted as the range of parameter values that are compatible with the data under background assumptions. We also suggest the use of a surprisal measure, often referred to as the S-value, a novel metric that transforms the P-value, for gauging compatibility in terms of an intuitive experiment of coin tossing.

The initial response to the Covid-19 pandemic was characterised by swift “lockdowns,” a cluster of measures defined by a shared goal of suppressing Covid-19 and a shared character of restricting departure from the home except for specific purposes. By mid-April 2020, most countries were implementing stringent measures of this kind. This essay contends that (1) some epidemiologists played a central role in formulating and promulgating lockdown as a policy and (2) lockdowns were foreseeably harmful to the Global Poor, and foreseeably offered them little benefit, relative to less stringent measures. In view of the widespread commitment to reducing global health inequalities within the profession, this should prompt reflection within the epidemiological community and further work on pandemic response measures more appropriate for the Global Poor.

Purpose

The association between alcohol consumption and pancreatic cancer is unsettled.

Methods

Altogether 243,169 men and women 20–79 years, without cancer at baseline, were followed with respect to pancreatic cancer by linkage to the Cancer Registry of Norway and the Norwegian Cause of Death Registry. They participated in a cardiovascular survey where information on alcohol consumption, smoking habits, anthropometric measures, and some biological variables were recorded. During 20 years of follow-up, 991 incident pancreatic cancers were registered. We estimated the hazard ratios with the Cox proportional hazards model, and graphed spline curves between glass-units/d of alcohol and hazard ratio of incident pancreatic cancer.

Results

The multivariable adjusted hazard per 1 glass-unit/d was 1.08 (95% confidence interval 1.02–1.15) for men and 1.04 (0.97–1.13) for women. The association between alcohol consumption and incident pancreatic cancer was present in ex- and current smokers, but the association could be ascribed to smoking habits. The multivariable adjusted spline curves increased with increasing glass-units/d and with confidence bands not encompassing 1.0 above one glass-unit/day.

Conclusion

Our findings of an association between higher level of alcohol consumption and incident pancreatic cancer, could be attributed to confounding by smoking habits.

We simulate the impact of school reopening during the COVID-19 pandemic in three major urban centers in Brazil to identify the epidemiological indicators and the best timing for the return of in-school activities and the effect of contact tracing as a mitigation measure. Our goal is to offer guidelines for evidence-based policymaking. We implement an extended SEIR model stratified by age and considering contact networks in different settings – school, home, work, and community, in which the infection transmission rate is affected by various intervention measures. After fitting epidemiological and demographic data, we simulate scenarios with increasing school transmission due to school reopening, and also estimate the number of hospitalization and deaths averted by the implementation of contact tracing. Reopening schools results in a non-linear increase in reported COVID-19 cases and deaths, which is highly dependent on infection and disease incidence at the time of reopening. When contact tracing and quarantining are restricted to school and home settings, a large number of daily tests is required to produce significant effects in reducing the total number of hospitalizations and deaths. Policymakers should carefully consider the epidemiological context and timing regarding the implementation of school closure and return of in-person school activities. While contact tracing strategies prevent new infections within school environments, they alone are not sufficient to avoid significant impacts on community transmission.