Code Review as a Simple Trick to Enhance Reproducibility, Accelerate Learning, and Improve the Quality of Your Team's Research
Am J Epidemiol. 2021 Apr 8:kwab092. doi: 10.1093/aje/kwab092. Online ahead of print.ABSTRACTProgramming for data wrangling and statistical analysis is an essential technical tool of modern Epidemiology, yet many Epidemiologists receive limited formal training in strategies to optimize the quality of our code. In complex projects, coding mistakes are easy to make, even for skilled practitioners. Such mistakes can lead to invalid research claims that reduce the credibility of the field. Code review is a straightforward technique used by the software industry to reduce the likelihood of coding bugs. The systematic implementat...
Source: Am J Epidemiol - April 9, 2021 Category: Epidemiology Authors: Anusha M Vable Scott F Diehl M Maria Glymour Source Type: research

Vable, Diehl, and Glymour respond to "Code Review: An Important Step Towards Reproducible Research"
Am J Epidemiol. 2021 Apr 8:kwab091. doi: 10.1093/aje/kwab091. Online ahead of print.NO ABSTRACTPMID:33834195 | DOI:10.1093/aje/kwab091 (Source: Am J Epidemiol)
Source: Am J Epidemiol - April 9, 2021 Category: Epidemiology Authors: Anusha M Vable Scott F Diehl M Maria Glymour Source Type: research

Code Review: An Important Step Towards Reproducible Research
Am J Epidemiol. 2021 Apr 8:kwab090. doi: 10.1093/aje/kwab090. Online ahead of print.NO ABSTRACTPMID:33834182 | DOI:10.1093/aje/kwab090 (Source: Am J Epidemiol)
Source: Am J Epidemiol - April 9, 2021 Category: Epidemiology Authors: Robert W Platt Source Type: research

Code Review as a Simple Trick to Enhance Reproducibility, Accelerate Learning, and Improve the Quality of Your Team's Research
Am J Epidemiol. 2021 Apr 8:kwab092. doi: 10.1093/aje/kwab092. Online ahead of print.ABSTRACTProgramming for data wrangling and statistical analysis is an essential technical tool of modern Epidemiology, yet many Epidemiologists receive limited formal training in strategies to optimize the quality of our code. In complex projects, coding mistakes are easy to make, even for skilled practitioners. Such mistakes can lead to invalid research claims that reduce the credibility of the field. Code review is a straightforward technique used by the software industry to reduce the likelihood of coding bugs. The systematic implementat...
Source: Am J Epidemiol - April 9, 2021 Category: Epidemiology Authors: Anusha M Vable Scott F Diehl M Maria Glymour Source Type: research

Vable, Diehl, and Glymour respond to "Code Review: An Important Step Towards Reproducible Research"
Am J Epidemiol. 2021 Apr 8:kwab091. doi: 10.1093/aje/kwab091. Online ahead of print.NO ABSTRACTPMID:33834195 | DOI:10.1093/aje/kwab091 (Source: Am J Epidemiol)
Source: Am J Epidemiol - April 9, 2021 Category: Epidemiology Authors: Anusha M Vable Scott F Diehl M Maria Glymour Source Type: research

Code Review: An Important Step Towards Reproducible Research
Am J Epidemiol. 2021 Apr 8:kwab090. doi: 10.1093/aje/kwab090. Online ahead of print.NO ABSTRACTPMID:33834182 | DOI:10.1093/aje/kwab090 (Source: Am J Epidemiol)
Source: Am J Epidemiol - April 9, 2021 Category: Epidemiology Authors: Robert W Platt Source Type: research

Code Review as a Simple Trick to Enhance Reproducibility, Accelerate Learning, and Improve the Quality of Your Team's Research
Am J Epidemiol. 2021 Apr 8:kwab092. doi: 10.1093/aje/kwab092. Online ahead of print.ABSTRACTProgramming for data wrangling and statistical analysis is an essential technical tool of modern Epidemiology, yet many Epidemiologists receive limited formal training in strategies to optimize the quality of our code. In complex projects, coding mistakes are easy to make, even for skilled practitioners. Such mistakes can lead to invalid research claims that reduce the credibility of the field. Code review is a straightforward technique used by the software industry to reduce the likelihood of coding bugs. The systematic implementat...
Source: Am J Epidemiol - April 9, 2021 Category: Epidemiology Authors: Anusha M Vable Scott F Diehl M Maria Glymour Source Type: research

Vable, Diehl, and Glymour respond to "Code Review: An Important Step Towards Reproducible Research"
Am J Epidemiol. 2021 Apr 8:kwab091. doi: 10.1093/aje/kwab091. Online ahead of print.NO ABSTRACTPMID:33834195 | DOI:10.1093/aje/kwab091 (Source: Am J Epidemiol)
Source: Am J Epidemiol - April 9, 2021 Category: Epidemiology Authors: Anusha M Vable Scott F Diehl M Maria Glymour Source Type: research

Code Review: An Important Step Towards Reproducible Research
Am J Epidemiol. 2021 Apr 8:kwab090. doi: 10.1093/aje/kwab090. Online ahead of print.NO ABSTRACTPMID:33834182 | DOI:10.1093/aje/kwab090 (Source: Am J Epidemiol)
Source: Am J Epidemiol - April 9, 2021 Category: Epidemiology Authors: Robert W Platt Source Type: research

Code Review as a Simple Trick to Enhance Reproducibility, Accelerate Learning, and Improve the Quality of Your Team's Research
Am J Epidemiol. 2021 Apr 8:kwab092. doi: 10.1093/aje/kwab092. Online ahead of print.ABSTRACTProgramming for data wrangling and statistical analysis is an essential technical tool of modern Epidemiology, yet many Epidemiologists receive limited formal training in strategies to optimize the quality of our code. In complex projects, coding mistakes are easy to make, even for skilled practitioners. Such mistakes can lead to invalid research claims that reduce the credibility of the field. Code review is a straightforward technique used by the software industry to reduce the likelihood of coding bugs. The systematic implementat...
Source: Am J Epidemiol - April 9, 2021 Category: Epidemiology Authors: Anusha M Vable Scott F Diehl M Maria Glymour Source Type: research

Vable, Diehl, and Glymour respond to "Code Review: An Important Step Towards Reproducible Research"
Am J Epidemiol. 2021 Apr 8:kwab091. doi: 10.1093/aje/kwab091. Online ahead of print.NO ABSTRACTPMID:33834195 | DOI:10.1093/aje/kwab091 (Source: Am J Epidemiol)
Source: Am J Epidemiol - April 9, 2021 Category: Epidemiology Authors: Anusha M Vable Scott F Diehl M Maria Glymour Source Type: research

RE: "A Data-Based Approach to Evaluate Representation by Gender and Affiliation in Key Presentation Formats at the SER Annual Meeting"
Am J Epidemiol. 2021 Apr 8:kwab082. doi: 10.1093/aje/kwab082. Online ahead of print.ABSTRACTThe annual meeting of the Society for Epidemiologic Research is a prominent showcase for epidemiologists to present their research and share their expertise with peers. There are multiple paths to being on a podium at the meeting, and that role has implications not only for the speaker but also for the audience. The article by Nobles et al. (Am J Epidemiol. XXXX;XXX(XX):XXXX-XXXX) represents an innovative investigation of representation of speakers at three recent SER annual meetings, with a primary focus on gender. Women were signi...
Source: Am J Epidemiol - April 8, 2021 Category: Epidemiology Authors: Diane S Lauderdale Source Type: research

Au et al. Response to Body mass index and risk of dementia- potential explanations for lifecourse differences in risk estimates and future research directions
Am J Epidemiol. 2021 Apr 8:kwab097. doi: 10.1093/aje/kwab097. Online ahead of print.NO ABSTRACTPMID:33831143 | DOI:10.1093/aje/kwab097 (Source: Am J Epidemiol)
Source: Am J Epidemiol - April 8, 2021 Category: Epidemiology Authors: Rhoda Au Jinlei Li Chunyu Liu Source Type: research

The Society for Epidemiologic Research - Striving for Equity in Our Own Backyard
Am J Epidemiol. 2021 Apr 8:kwab081. doi: 10.1093/aje/kwab081. Online ahead of print.ABSTRACTUsing a bibliometric approach, Nobles et al. (Am J Epidemiol. XXXX;XXX(XX):XXXX-XXXX) conducted a study to explore dimensions of participation at Annual Meetings of the Society for Epidemiologic Research (SER). Findings suggested differences in representation by gender and affiliation in key presentation formats, raising concerns about possible equity issues within the organization. This commentary discusses context, limitations, and strengths of the study, as well as reflections on interpretation and implications. Suggested next st...
Source: Am J Epidemiol - April 8, 2021 Category: Epidemiology Authors: Polly A Marchbanks Source Type: research

The Impact of Changes in Diagnostic Testing Practices on Estimates of COVID-19 Transmission in the United States
Am J Epidemiol. 2021 Apr 8:kwab089. doi: 10.1093/aje/kwab089. Online ahead of print.ABSTRACTEstimates of the reproductive number for novel pathogens such as severe acute respiratory syndrome coronavirus 2 are essential for understanding the potential trajectory of the epidemic and the level of intervention that is needed to bring the epidemic under control. However, most methods for estimating the basic reproductive number (R0) and time-varying effective reproductive number (Rt) assume that the fraction of cases detected and reported is constant through time. We explore the impact of secular changes in diagnostic testing a...
Source: Am J Epidemiol - April 8, 2021 Category: Epidemiology Authors: Virginia E Pitzer Melanie Chitwood Joshua Havumaki Nicolas A Menzies Stephanie Perniciaro Joshua L Warren Daniel M Weinberger Ted Cohen Source Type: research

The Importance of Alcohol Prevention Programs for Youth
Am J Epidemiol. 2021 Apr 8:kwab094. doi: 10.1093/aje/kwab094. Online ahead of print.NO ABSTRACTPMID:33831165 | DOI:10.1093/aje/kwab094 (Source: Am J Epidemiol)
Source: Am J Epidemiol - April 8, 2021 Category: Epidemiology Authors: Adjele Wilson Source Type: research

Commentary on: A Data-Based Approach to Evaluate Representation by Gender and Affiliation in Key Presentation Formats at the SER Annual Meeting
Am J Epidemiol. 2021 Apr 8:kwab083. doi: 10.1093/aje/kwab083. Online ahead of print.ABSTRACTIn the article by Nobles et al (Am J Epidemiol. XXXX;XXX(XX):XXXX-XXXX), characteristics of those epidemiologists selected for various chair and presentation roles at the annual meetings of the Society for Epidemiologic Research (SER) from 2015 through 2017 were examined. Characteristics were compared, including inferred gender, institutional affiliation, subject area and h-index. Important disparities were observed between session chairs, speakers and poster presenters. SER leadership considers diversity and equity a priority and i...
Source: Am J Epidemiol - April 8, 2021 Category: Epidemiology Authors: Jennifer Ahern Jay S Kaufman Martha M Werler Source Type: research

Reckoning with our biases in epidemiology
Am J Epidemiol. 2021 Apr 8:kwab085. doi: 10.1093/aje/kwab085. Online ahead of print.ABSTRACTBiases and in-group preferences limit opportunities for persons of all identities to flourish in science. Decisions made by leading professional meetings about which presentations to feature prominently, and by academic journals about which articles to publish, reinforce these biases. The paper by Nobles and colleagues (Am J Epidemiol. XXXX;XXX(XX):XXXX-XXXX)), shows that women are less likely to be selected to be symposium presenters in the field's pre-eminent scientific meeting than men. The scientific and moral arguments for prom...
Source: Am J Epidemiol - April 8, 2021 Category: Epidemiology Authors: Sandro Galea Source Type: research

A Data-Based Approach to Evaluate Representation by Gender and Affiliation in Key Presentation Formats at the SER Annual Meeting
Am J Epidemiol. 2021 Apr 8:kwab080. doi: 10.1093/aje/kwab080. Online ahead of print.ABSTRACTThe Society for Epidemiologic Research's (SER) annual meeting is a major forum for sharing new research and promoting participants' career development. As such, evaluating representation in key presentation formats is critical. For the 3,257 presentations identified at the 2015-2017 SER annual meetings, we evaluated presenter characteristics, including gender, affiliation, subject area and h-index, and representation in three highlighted presentation formats: platform talks (n=382), invited symposium talks (n=273) and serving as a C...
Source: Am J Epidemiol - April 8, 2021 Category: Epidemiology Authors: Carrie J Nobles Ya-Ling Lu Victoria C Andriessen Suzanne S Bevan Jeannie G Radoc Zeina Alkhalaf Enrique F Schisterman Source Type: research

Obtaining Prevalence Estimates of COVID-19: A Model to Inform Decision-making
We examined the situation when the true prevalence is low (0.07%-2%), medium (2%-5%) and high (6%-10%). Bayesian models informed by published validity estimates were used to account for misclassification error when estimating COVID-19 prevalence. Adjustment for misclassification error captured the true prevalence 100% of the time, irrespective of the true prevalence level. When adjustment for misclassification error was not done, the results highly varied depending on the population's underlying true prevalence and the type of diagnostic test used. Generally, the prevalence estimates without adjustment for misclassificatio...
Source: Am J Epidemiol - April 8, 2021 Category: Epidemiology Authors: Ida Sahlu Alexander B Whittaker Source Type: research

The Causal Interpretation of "Overall Vaccine Effectiveness" in Test-Negative Studies
Am J Epidemiol. 2021 Apr 8:kwab101. doi: 10.1093/aje/kwab101. Online ahead of print.ABSTRACTTest-negative studies are commonly used to estimate influenza vaccine effectiveness (VE). In a typical study, an "overall VE" estimate may be reported based on data from the entire sample. However, there may be heterogeneity in VE, particularly by age. We therefore discuss the potential for a weighted average of age-specific VE estimates to provide a more meaningful measure of overall VE. We illustrate this perspective first using simulations to evaluate how overall VE would be biased when certain age groups are over-repre...
Source: Am J Epidemiol - April 8, 2021 Category: Epidemiology Authors: Shuo Feng Sheena G Sullivan Eric J Tchetgen Tchetgen Benjamin J Cowling Source Type: research

Response to Commentaries on: A Data-Based Approach to Evaluate Representation by Gender and Affiliation in Key Presentation Formats at the SER Annual Meeting
Am J Epidemiol. 2021 Apr 8:kwab084. doi: 10.1093/aje/kwab084. Online ahead of print.NO ABSTRACTPMID:33831174 | DOI:10.1093/aje/kwab084 (Source: Am J Epidemiol)
Source: Am J Epidemiol - April 8, 2021 Category: Epidemiology Authors: Carrie J Nobles Ya-Ling Lu Victoria C Andriessen Suzanne S Bevan Jeannie G Radoc Zeina Alkhalaf Enrique F Schisterman Source Type: research

Body mass index and risk of dementia - potential explanations for lifecourse differences in risk estimates and future research directions
Am J Epidemiol. 2021 Apr 8:kwab095. doi: 10.1093/aje/kwab095. Online ahead of print.ABSTRACTThe relationship between body mass index (BMI) and health outcomes of older adults including dementia remains controversial. Many studies find inverse associations between BMI and dementia among older adults, while in other studies high BMI in mid-life is associated with increased dementia risk. In this issue, Li et al. (Am J Epidemiol. XXXX;XXX(XX):XXXX-XXXX) examine BMI from mid to late-life and risk of dementia using the extensive follow-up of the Framingham Offspring Study. They found changing trends in the association between B...
Source: Am J Epidemiol - April 8, 2021 Category: Epidemiology Authors: Willa D Brenowitz Source Type: research

Snowball Sampling Study Design for Serosurveys Early in Disease Outbreaks
Am J Epidemiol. 2021 Apr 8:kwab098. doi: 10.1093/aje/kwab098. Online ahead of print.ABSTRACTSerological surveys can provide evidence of cases that were not previously detected, depict the spectrum of disease severity, and estimate the proportion of asymptomatic infections. To capture these parameters, survey sample sizes may need to be very large, especially when the overall infection rate is still low. Therefore, we propose the use of "snowball sampling" to enrich serological surveys by testing contacts of infected individuals identified in the early stages of an outbreak. For future emerging pandemics, this obs...
Source: Am J Epidemiol - April 8, 2021 Category: Epidemiology Authors: Lee Kennedy-Shaffer Xueting Qiu William P Hanage Source Type: research

Childhood Overweight and Obesity and Pubertal Onset Among Mexican American Boys and Girls in the CHAMACOS Longitudinal Study
This study examined an understudied population and included key covariates, such as birthweight and early adverse events, which are typically omitted in studies.PMID:33831178 | DOI:10.1093/aje/kwab100 (Source: Am J Epidemiol)
Source: Am J Epidemiol - April 8, 2021 Category: Epidemiology Authors: Julianna Deardorff Jonathan W Reeves Carly Hyland Sasha Tilles Stephen Rauch Katherine Kogut Louise C Greenspan Elizabeth Shirtcliff Robert H Lustig Brenda Eskenazi Kim Harley Source Type: research

Mid- to Late- Life Body Mass Index and Dementia Risk: 38 Years of Follow-up of the Framingham Study
Am J Epidemiol. 2021 Apr 8:kwab096. doi: 10.1093/aje/kwab096. Online ahead of print.ABSTRACTGrowing evidence relates Body Mass index (BMI) to poorer health outcomes; however, results across studies associating BMI and dementia are conflicting. A total of 3632 Framingham Offspring participants aged 20 to 60 years at their second health exam (1979-1982) were included in this study with 190 cases of incident dementia identified by 2017. Cox proportional hazards regression models were performed to investigate the association of BMI at each of their 8 exams as a baseline for dementia risk, and the associations between obesity a...
Source: Am J Epidemiol - April 8, 2021 Category: Epidemiology Authors: Jinlei Li Prajakta Joshi Ting Fang Alvin Ang Chunyu Liu Sanford Auerbach Sherral Devine Rhoda Au Source Type: research

Diagnostic accuracy estimates for COVID-19 RT-PCR and Lateral flow immunoassay tests with Bayesian latent class models
The objective was to estimate the diagnostic accuracy of real time polymerase chain reaction (RT-PCR) and lateral flow immunoassay (LFIA) tests for COVID-19, depending on the time post symptom onset. Based on the cross-classified results of RT-PCR and LFIA, we used Bayesian latent class models (BLCMs), which do not require a gold standard for the evaluation of diagnostics. Data were extracted from studies that evaluated LFIA (IgG and/or IgM) assays using RT-PCR as the reference method. ${Se}_{RT- PCR}$ was 0.68 (95% probability intervals: 0.63; 0.73). ${Se}_{IgG/M}$ was 0.32 (0.23; 0.41) for the first week and increased st...
Source: Am J Epidemiol - April 6, 2021 Category: Epidemiology Authors: Polychronis Kostoulas Paolo Eusebi Sonja Hartnack Source Type: research

Diagnostic accuracy estimates for COVID-19 RT-PCR and Lateral flow immunoassay tests with Bayesian latent class models
The objective was to estimate the diagnostic accuracy of real time polymerase chain reaction (RT-PCR) and lateral flow immunoassay (LFIA) tests for COVID-19, depending on the time post symptom onset. Based on the cross-classified results of RT-PCR and LFIA, we used Bayesian latent class models (BLCMs), which do not require a gold standard for the evaluation of diagnostics. Data were extracted from studies that evaluated LFIA (IgG and/or IgM) assays using RT-PCR as the reference method. ${Se}_{RT- PCR}$ was 0.68 (95% probability intervals: 0.63; 0.73). ${Se}_{IgG/M}$ was 0.32 (0.23; 0.41) for the first week and increased st...
Source: Am J Epidemiol - April 6, 2021 Category: Epidemiology Authors: Polychronis Kostoulas Paolo Eusebi Sonja Hartnack Source Type: research

Data-Driven Model Building for Life Course Epidemiology
Am J Epidemiol. 2021 Mar 29:kwab087. doi: 10.1093/aje/kwab087. Online ahead of print.ABSTRACTLife course epidemiology is useful for describing and analyzing complex etiological mechanisms for disease development, but existing statistical methods are essentially confirmatory, as they rely on a priori model specification. This limits the scope of causal inquiries that can be made, since these methods are mostly suited to examine well-known hypotheses that do not question our established view of health, which may lead to confirmation bias. We propose an exploratory alternative. Instead of specifyinga life course model prior t...
Source: Am J Epidemiol - March 29, 2021 Category: Epidemiology Authors: Anne H Petersen Merete Osler Claus T Ekstr øm Source Type: research

Maternal Urinary Organophosphate Esters and Alterations in Maternal and Neonatal Thyroid Hormones
Am J Epidemiol. 2021 Mar 29:kwab086. doi: 10.1093/aje/kwab086. Online ahead of print.ABSTRACTProduction of organophosphate esters (OPEs), which represent a major flame retardant class present in consumer goods, has risen over the past two decades. Experimental studies suggest that OPEs may be associated with thyroid hormone disruption, but few human studies have examined this association. We quantified OPE metabolites in the urine of 298 pregnant women in the Health Outcomes and Measures of the Environment Study from Cincinnati, Ohio (enrolled 2003-2006) at three time points (16 and 26 weeks' gestation, delivery), and thyr...
Source: Am J Epidemiol - March 29, 2021 Category: Epidemiology Authors: Zana Percy Ann M Vuong Yingying Xu Changchun Xie Maria Ospina Antonia M Calafat Andy Hoofnagle Bruce P Lanphear Joseph M Braun Kim M Cecil Kim N Dietrich Kimberly Yolton Aimin Chen Source Type: research

Lash et al. Respond to "Dealing with the Inevitable Deficiencies of Bias Analysis-and All Analyses" and "Toward Better Bias Analysis"
Am J Epidemiol. 2021 Mar 29:kwab070. doi: 10.1093/aje/kwab070. Online ahead of print.NO ABSTRACTPMID:33778843 | DOI:10.1093/aje/kwab070 (Source: Am J Epidemiol)
Source: Am J Epidemiol - March 29, 2021 Category: Epidemiology Authors: Timothy L Lash Thomas P Ahern Lindsay J Collin Matthew P Fox Richard F MacLehose Source Type: research

Bias Analysis Gone Bad
Am J Epidemiol. 2021 Mar 29:kwab072. doi: 10.1093/aje/kwab072. Online ahead of print.ABSTRACTQuantitative Bias Analysis comprises the tools used to estimate the direction, magnitude, and uncertainty from systematic errors affecting epidemiologic research. Despite the availability of methods and tools, and guidance for good practices, few reports of epidemiologic research incorporate quantitative estimates of bias impacts. The lack of familiarity with bias analysis allows for the possibility of misuse, which is likely most often unintentional, but may occasionally include intentional efforts to mislead. We identified three ...
Source: Am J Epidemiol - March 29, 2021 Category: Epidemiology Authors: Timothy L Lash Thomas P Ahern Lindsay J Collin Matthew P Fox Richard F MacLehose Source Type: research

Editorial: Robust Sensitivities
Am J Epidemiol. 2021 Mar 29:kwab071. doi: 10.1093/aje/kwab071. Online ahead of print.NO ABSTRACTPMID:33778853 | DOI:10.1093/aje/kwab071 (Source: Am J Epidemiol)
Source: Am J Epidemiol - March 29, 2021 Category: Epidemiology Authors: Catherine R Lesko Stephen R Cole Enrique F Schisterman Source Type: research

Trends in "Deaths of Despair" among Working Aged White and Black Americans, 1990-2017
Am J Epidemiol. 2021 Mar 29:kwab088. doi: 10.1093/aje/kwab088. Online ahead of print.ABSTRACTLife expectancy for U.S. white men and women declined between 2013 and 2017. Initial explanations for the decline focused on increases in "deaths of despair" (i.e., deaths from suicide, drug use, and alcohol use), which have been interpreted as a cohort-based phenomenon afflicting middle-aged white Americans. There has been less attention on black mortality trends from these same causes, and whether the trends are similar or different by cohort and period. We complement existing research and contend that recent mortality ...
Source: Am J Epidemiol - March 29, 2021 Category: Epidemiology Authors: Andrea M Tilstra Daniel H Simon Ryan K Masters Source Type: research

Invited Commentary: Toward Better Bias Analysis
Am J Epidemiol. 2021 Mar 29:kwab068. doi: 10.1093/aje/kwab068. Online ahead of print.ABSTRACTThe article by Lash et al (Am J. Epidemiol.) shows how some previously published bias analyses could have been better. Via investigation of one of their examples, we add some thoughts about routes to better bias analysis, particularly via exploration of a joint distribution of bias parameters and target parameters.PMID:33778860 | DOI:10.1093/aje/kwab068 (Source: Am J Epidemiol)
Source: Am J Epidemiol - March 29, 2021 Category: Epidemiology Authors: Paul Gustafson Source Type: research

Dealing with the Inevitable Deficiencies of Bias Analysis - and All Analyses
Am J Epidemiol. 2021 Mar 29:kwab069. doi: 10.1093/aje/kwab069. Online ahead of print.ABSTRACTLash et al. (Am. J. Epidemiol. xxx) present detailed critiques of 3 bias analyses which they identify as "suboptimal". This identification raises the question of what "optimal" means for bias analysis, because it is practically impossible to do statistically optimal analyses of typical population studies - with or without bias analysis. At best the analysis can only attempt to satisfy practice guidelines and account for available information both within and outside the study. One should not expect a full account...
Source: Am J Epidemiol - March 29, 2021 Category: Epidemiology Authors: Sander Greenland Source Type: research

Gestational Exposure to Toxicants and Autistic Behaviors using Bayesian Quantile Regression
Am J Epidemiol. 2021 Mar 29:kwab065. doi: 10.1093/aje/kwab065. Online ahead of print.ABSTRACTAutism Spectrum Disorder, which is characterized by impaired social communication and stereotypic behaviors, affects 1-2% of children. While prenatal exposure to toxicants has been associated with autistic behaviors, most studies have focused on shifts in mean behavior scores. We used Bayesian quantile regression to assess the associations between log2-transformed toxicant concentrations and autistic behaviors across the distribution of behaviors. We used data from the Maternal-Infant Research on Environmental Chemicals study, a pa...
Source: Am J Epidemiol - March 29, 2021 Category: Epidemiology Authors: Joshua D Alampi Bruce P Lanphear Joseph M Braun Aimen Chen Tim K Takaro Gina Muckle Tye E Arbuckle Lawrence C McCandless Source Type: research

Data-Driven Model Building for Life Course Epidemiology
Am J Epidemiol. 2021 Mar 29:kwab087. doi: 10.1093/aje/kwab087. Online ahead of print.ABSTRACTLife course epidemiology is useful for describing and analyzing complex etiological mechanisms for disease development, but existing statistical methods are essentially confirmatory, as they rely on a priori model specification. This limits the scope of causal inquiries that can be made, since these methods are mostly suited to examine well-known hypotheses that do not question our established view of health, which may lead to confirmation bias. We propose an exploratory alternative. Instead of specifyinga life course model prior t...
Source: Am J Epidemiol - March 29, 2021 Category: Epidemiology Authors: Anne H Petersen Merete Osler Claus T Ekstr øm Source Type: research

Maternal Urinary Organophosphate Esters and Alterations in Maternal and Neonatal Thyroid Hormones
Am J Epidemiol. 2021 Mar 29:kwab086. doi: 10.1093/aje/kwab086. Online ahead of print.ABSTRACTProduction of organophosphate esters (OPEs), which represent a major flame retardant class present in consumer goods, has risen over the past two decades. Experimental studies suggest that OPEs may be associated with thyroid hormone disruption, but few human studies have examined this association. We quantified OPE metabolites in the urine of 298 pregnant women in the Health Outcomes and Measures of the Environment Study from Cincinnati, Ohio (enrolled 2003-2006) at three time points (16 and 26 weeks' gestation, delivery), and thyr...
Source: Am J Epidemiol - March 29, 2021 Category: Epidemiology Authors: Zana Percy Ann M Vuong Yingying Xu Changchun Xie Maria Ospina Antonia M Calafat Andy Hoofnagle Bruce P Lanphear Joseph M Braun Kim M Cecil Kim N Dietrich Kimberly Yolton Aimin Chen Source Type: research

Lash et al. Respond to "Dealing with the Inevitable Deficiencies of Bias Analysis-and All Analyses" and "Toward Better Bias Analysis"
Am J Epidemiol. 2021 Mar 29:kwab070. doi: 10.1093/aje/kwab070. Online ahead of print.NO ABSTRACTPMID:33778843 | DOI:10.1093/aje/kwab070 (Source: Am J Epidemiol)
Source: Am J Epidemiol - March 29, 2021 Category: Epidemiology Authors: Timothy L Lash Thomas P Ahern Lindsay J Collin Matthew P Fox Richard F MacLehose Source Type: research

Bias Analysis Gone Bad
Am J Epidemiol. 2021 Mar 29:kwab072. doi: 10.1093/aje/kwab072. Online ahead of print.ABSTRACTQuantitative Bias Analysis comprises the tools used to estimate the direction, magnitude, and uncertainty from systematic errors affecting epidemiologic research. Despite the availability of methods and tools, and guidance for good practices, few reports of epidemiologic research incorporate quantitative estimates of bias impacts. The lack of familiarity with bias analysis allows for the possibility of misuse, which is likely most often unintentional, but may occasionally include intentional efforts to mislead. We identified three ...
Source: Am J Epidemiol - March 29, 2021 Category: Epidemiology Authors: Timothy L Lash Thomas P Ahern Lindsay J Collin Matthew P Fox Richard F MacLehose Source Type: research

Editorial: Robust Sensitivities
Am J Epidemiol. 2021 Mar 29:kwab071. doi: 10.1093/aje/kwab071. Online ahead of print.NO ABSTRACTPMID:33778853 | DOI:10.1093/aje/kwab071 (Source: Am J Epidemiol)
Source: Am J Epidemiol - March 29, 2021 Category: Epidemiology Authors: Catherine R Lesko Stephen R Cole Enrique F Schisterman Source Type: research

Trends in "Deaths of Despair" among Working Aged White and Black Americans, 1990-2017
Am J Epidemiol. 2021 Mar 29:kwab088. doi: 10.1093/aje/kwab088. Online ahead of print.ABSTRACTLife expectancy for U.S. white men and women declined between 2013 and 2017. Initial explanations for the decline focused on increases in "deaths of despair" (i.e., deaths from suicide, drug use, and alcohol use), which have been interpreted as a cohort-based phenomenon afflicting middle-aged white Americans. There has been less attention on black mortality trends from these same causes, and whether the trends are similar or different by cohort and period. We complement existing research and contend that recent mortality ...
Source: Am J Epidemiol - March 29, 2021 Category: Epidemiology Authors: Andrea M Tilstra Daniel H Simon Ryan K Masters Source Type: research

Invited Commentary: Toward Better Bias Analysis
Am J Epidemiol. 2021 Mar 29:kwab068. doi: 10.1093/aje/kwab068. Online ahead of print.ABSTRACTThe article by Lash et al (Am J. Epidemiol.) shows how some previously published bias analyses could have been better. Via investigation of one of their examples, we add some thoughts about routes to better bias analysis, particularly via exploration of a joint distribution of bias parameters and target parameters.PMID:33778860 | DOI:10.1093/aje/kwab068 (Source: Am J Epidemiol)
Source: Am J Epidemiol - March 29, 2021 Category: Epidemiology Authors: Paul Gustafson Source Type: research

Dealing with the Inevitable Deficiencies of Bias Analysis - and All Analyses
Am J Epidemiol. 2021 Mar 29:kwab069. doi: 10.1093/aje/kwab069. Online ahead of print.ABSTRACTLash et al. (Am. J. Epidemiol. xxx) present detailed critiques of 3 bias analyses which they identify as "suboptimal". This identification raises the question of what "optimal" means for bias analysis, because it is practically impossible to do statistically optimal analyses of typical population studies - with or without bias analysis. At best the analysis can only attempt to satisfy practice guidelines and account for available information both within and outside the study. One should not expect a full account...
Source: Am J Epidemiol - March 29, 2021 Category: Epidemiology Authors: Sander Greenland Source Type: research

Gestational Exposure to Toxicants and Autistic Behaviors using Bayesian Quantile Regression
Am J Epidemiol. 2021 Mar 29:kwab065. doi: 10.1093/aje/kwab065. Online ahead of print.ABSTRACTAutism Spectrum Disorder, which is characterized by impaired social communication and stereotypic behaviors, affects 1-2% of children. While prenatal exposure to toxicants has been associated with autistic behaviors, most studies have focused on shifts in mean behavior scores. We used Bayesian quantile regression to assess the associations between log2-transformed toxicant concentrations and autistic behaviors across the distribution of behaviors. We used data from the Maternal-Infant Research on Environmental Chemicals study, a pa...
Source: Am J Epidemiol - March 29, 2021 Category: Epidemiology Authors: Joshua D Alampi Bruce P Lanphear Joseph M Braun Aimen Chen Tim K Takaro Gina Muckle Tye E Arbuckle Lawrence C McCandless Source Type: research

Data-Driven Model Building for Life Course Epidemiology
Am J Epidemiol. 2021 Mar 29:kwab087. doi: 10.1093/aje/kwab087. Online ahead of print.ABSTRACTLife course epidemiology is useful for describing and analyzing complex etiological mechanisms for disease development, but existing statistical methods are essentially confirmatory, as they rely on a priori model specification. This limits the scope of causal inquiries that can be made, since these methods are mostly suited to examine well-known hypotheses that do not question our established view of health, which may lead to confirmation bias. We propose an exploratory alternative. Instead of specifyinga life course model prior t...
Source: Am J Epidemiol - March 29, 2021 Category: Epidemiology Authors: Anne H Petersen Merete Osler Claus T Ekstr øm Source Type: research

Maternal Urinary Organophosphate Esters and Alterations in Maternal and Neonatal Thyroid Hormones
Am J Epidemiol. 2021 Mar 29:kwab086. doi: 10.1093/aje/kwab086. Online ahead of print.ABSTRACTProduction of organophosphate esters (OPEs), which represent a major flame retardant class present in consumer goods, has risen over the past two decades. Experimental studies suggest that OPEs may be associated with thyroid hormone disruption, but few human studies have examined this association. We quantified OPE metabolites in the urine of 298 pregnant women in the Health Outcomes and Measures of the Environment Study from Cincinnati, Ohio (enrolled 2003-2006) at three time points (16 and 26 weeks' gestation, delivery), and thyr...
Source: Am J Epidemiol - March 29, 2021 Category: Epidemiology Authors: Zana Percy Ann M Vuong Yingying Xu Changchun Xie Maria Ospina Antonia M Calafat Andy Hoofnagle Bruce P Lanphear Joseph M Braun Kim M Cecil Kim N Dietrich Kimberly Yolton Aimin Chen Source Type: research

Lash et al. Respond to "Dealing with the Inevitable Deficiencies of Bias Analysis-and All Analyses" and "Toward Better Bias Analysis"
Am J Epidemiol. 2021 Mar 29:kwab070. doi: 10.1093/aje/kwab070. Online ahead of print.NO ABSTRACTPMID:33778843 | DOI:10.1093/aje/kwab070 (Source: Am J Epidemiol)
Source: Am J Epidemiol - March 29, 2021 Category: Epidemiology Authors: Timothy L Lash Thomas P Ahern Lindsay J Collin Matthew P Fox Richard F MacLehose Source Type: research

Bias Analysis Gone Bad
Am J Epidemiol. 2021 Mar 29:kwab072. doi: 10.1093/aje/kwab072. Online ahead of print.ABSTRACTQuantitative Bias Analysis comprises the tools used to estimate the direction, magnitude, and uncertainty from systematic errors affecting epidemiologic research. Despite the availability of methods and tools, and guidance for good practices, few reports of epidemiologic research incorporate quantitative estimates of bias impacts. The lack of familiarity with bias analysis allows for the possibility of misuse, which is likely most often unintentional, but may occasionally include intentional efforts to mislead. We identified three ...
Source: Am J Epidemiol - March 29, 2021 Category: Epidemiology Authors: Timothy L Lash Thomas P Ahern Lindsay J Collin Matthew P Fox Richard F MacLehose Source Type: research