-
Don't let your analysis go to seed: on the impact of random seed on machine learning-based causal inference. Epidemiology (IF 4.7) Pub Date : 2024-08-16 Lindsey M Schader, Weishan Song, Russell Kempker, David Benkeser
Machine learning techniques for causal effect estimation can enhance the reliability of epidemiologic analyses, reducing their dependence on correct model specifications. However, the stochastic nature of many machine learning algorithms implies that the results derived from such approaches may be influenced by the random seed that is set prior to model fitting. In this work, we highlight the substantial
-
Pseudo-Random Number Generator Influences on Average Treatment Effect Estimates Obtained with Machine Learning. Epidemiology (IF 4.7) Pub Date : 2024-08-16 Ashley I Naimi, Ya-Hui Yu, Lisa M Bodnar
Use of machine learning to estimate exposure effects introduces a dependence between the results of an empirical study and the value of the seed used to fix the pseudo-random number generator.
-
Evaluating Binary Outcome Classifiers Estimated from Survey Data. Epidemiology (IF 4.7) Pub Date : 2024-08-14 Adway S Wadekar, Jerome P Reiter
Surveys are commonly used to facilitate research in epidemiology, health, and the social and behavioral sciences. Often, these surveys are not simple random samples, and respondents are given weights reflecting their probability of selection into the survey. We show that using survey weights can be beneficial for evaluating the quality of predictive models when splitting data into training and test
-
The Population-level Effect of Adjuvant Therapies on Breast Cancer Recurrence: Application of the Trend-in-Trend Design. Epidemiology (IF 4.7) Pub Date : 2024-08-06 Lindsay J Collin, Lance A Waller, Deirdre P Cronin-Fenton, Thomas P Ahern, Michael Goodman, Lauren E McCullough, Anders Kjærsgaard, Kirsten M Woolpert, Rebecca A Silliman, Peer M Christiansen, Bent Ejlertsen, Henrik Toft Sørensen, Timothy L Lash
Breast cancer has an average 10-year relative survival reaching 84%. This favorable survival is due, in part, to the introduction of biomarker-guided therapies. We estimated the population-level effect of the introduction of two adjuvant therapies-tamoxifen and trastuzumab-on recurrence using the trend-in-trend pharmacoepidemiologic study design.
-
Studying Continuous, Time-varying, and/or Complex Exposures Using Longitudinal Modified Treatment Policies. Epidemiology (IF 4.7) Pub Date : 2024-08-06 Katherine L Hoffman, Diego Salazar-Barreto, Nicholas T Williams, Kara E Rudolph, Iván Díaz
This tutorial discusses a methodology for causal inference using longitudinal modified treatment policies. This method facilitates the mathematical formalization, identification, and estimation of many novel parameters and mathematically generalizes many commonly used parameters, such as the average treatment effect. Longitudinal modified treatment policies apply to a wide variety of exposures, including
-
Generalizability of heat-related health risk associations observed in a large healthcare claims database of patients with commercial health insurance. Epidemiology (IF 4.7) Pub Date : 2024-08-02 Chad W Milando, Yuantong Sun, Yasmin Romitti, Amruta Nori-Sarma, Emma L Gause, Keith R Spangler, Ian Sue Wing, Gregory A Wellenius
Extreme ambient heat is unambiguously associated with higher risk of illness and death. The Optum Labs Data Warehouse (OLDW), a database of medical claims from US-based patients with commercial or Medicare Advantage health insurance, has been used to quantify heat-related health impacts. Whether results for the insured sub-population are generalizable to the broader population has to our knowledge
-
The Causal Roadmap and Simulations to Improve the Rigor and Reproducibility of Real-data Applications. Epidemiology (IF 4.7) Pub Date : 2024-08-01 Nerissa Nance, Maya L Petersen, Mark van der Laan, Laura B Balzer
The Causal Roadmap outlines a systematic approach to asking and answering questions of cause and effect: define the quantity of interest, evaluate needed assumptions, conduct statistical estimation, and carefully interpret results. To protect research integrity, it is essential that the algorithm for statistical estimation and inference be prespecified prior to conducting any effectiveness analyses
-
Bayesian Kernel Machine Regression for Social Epidemiologic Research. Epidemiology (IF 4.7) Pub Date : 2024-08-01 Jemar R Bather, Taylor J Robinson, Melody S Goodman
Little attention has been devoted to framing multiple continuous social variables as a "mixture" for social epidemiologic analysis. We propose using the Bayesian kernel machine regression analytic framework that yields univariate, bivariate, and overall exposure mixture effects.
-
Methods for extending inferences from observational studies: considering causal structures, identification assumptions, and estimators. Epidemiology (IF 4.7) Pub Date : 2024-07-31 Eleanor Hayes-Larson, Yixuan Zhou, L Paloma Rojas-Saunero, Crystal Shaw, Marissa J Seamans, M Maria Glymour, Audrey R Murchland, Daniel Westreich, Elizabeth Rose Mayeda
Most prior work in quantitative approaches to generalizability and transportability emphasizes extending causal effect estimates from randomized trials to target populations. Extending findings from observational studies is also of scientific interest, and identifiability assumptions and estimation methods differ from randomized settings when there is selection on both the exposure and exposure-outcome
-
A Counterfactual Analysis of Impact of Cesarean Birth in a First Birth on Severe Maternal Morbidity in the Subsequent Birth. Epidemiology (IF 4.7) Pub Date : 2024-07-26 Shalmali Bane, Jonathan M Snowden, Julia F Simard, Michelle Odden, Peiyi Kan, Elliott K Main, Suzan L Carmichael
It is known that cesarean birth affects maternal outcomes in subsequent pregnancies, but specific effect estimates are lacking. We sought to quantify the effect of cesarean birth reduction among nulliparous, term, singleton, vertex (NTSV) births (i.e., preventable cesarean births) on severe maternal morbidity (SMM) in the second birth.
-
EXPOSURE TO AMBIENT HEAT AND RISK OF SPONTANEOUS ABORTION: A CASE-CROSSOVER STUDY. Epidemiology (IF 4.7) Pub Date : 2024-07-26 Amelia K Wesselink, Emma L Gause, Keith D Spangler, Perry Hystad, Kipruto Kirwa, Mary D Willis, Gregory A Wellenius, Lauren A Wise
Few epidemiologic studies have examined the association of ambient heat with spontaneous abortion, a common and devastating pregnancy outcome.
-
Prenatal exposure to non-persistent chemicals and fetal-to-childhood growth trajectories. Epidemiology (IF 4.7) Pub Date : 2024-07-23 Paige A Bommarito, Sophia M Blaauwendraad, Danielle R Stevens, Michiel A van den Dries, Suzanne Spaan, Anjoeka Pronk, Henning Tiemeier, Romy Gaillard, Leonardo Trasande, Vincent V W Jaddoe, Kelly K Ferguson
Prenatal exposure to non-persistent chemicals, including organophosphate pesticides, phthalates, and bisphenols, is associated with altered fetal and childhood growth. Few studies have examined these associations using longitudinal growth trajectories or considering exposure to chemical mixtures.
-
Preventable fraction in the context of disease progression. Epidemiology (IF 4.7) Pub Date : 2024-07-23 Bronner P Gonçalves, Etsuji Suzuki
The relevance of the epidemiologic concept of preventable fraction to the study of the population-level impact of preventive exposures is unequivocal. Here, we discuss how the preventable fraction can be usefully understood for the class of outcomes that relate to disease progression (e.g., clinical severity given diagnosis), and, under the principal stratification framework, derive an expression for
-
Associations between gestational residential radon exposure and term low birthweight in Connecticut, USA. Epidemiology (IF 4.7) Pub Date : 2024-07-23 Seulkee Heo, Longxiang Li, Ji-Young Son, Petros Koutrakis, Michelle L Bell
Studies suggest biologic mechanisms for gestational exposure to radiation and impaired fetal development. We explored associations between gestational radon exposure and term low birthweight, for which evidence is limited.
-
Method for Testing Etiologic Heterogeneity Among Non-Competing Diagnoses, Applied to Impact of Perinatal Exposures on Autism and Attention Deficit Hyperactivity Disorder. Epidemiology (IF 4.7) Pub Date : 2024-07-18 Amy E Kalkbrenner, Cheng Zheng, Justin Yu, Tara E Jenson, Thomas Kuhlwein, Christine Ladd-Acosta, Jakob Grove, Diana Schendel
Testing etiologic heterogeneity - whether a disorder subtype is more or less impacted by a risk factor, is important for understanding causal pathways and optimizing statistical power. The study of mental health disorders especially benefits from strategic sub-categorization because these disorders are heterogenous and frequently co-occur. Existing methods to quantify etiologic heterogeneity are not
-
Estimating the effect of bariatric surgery on cardiovascular events using observational data? Epidemiology (IF 4.7) Pub Date : 2024-07-18 Arin L Madenci, Katherine E Kurgansky, Barbra A Dickerman, Hanna Gerlovin, Kerollos Nashat Wanis, Ann D Smith, Ludovic Trinqart, David R Gagnon, Kelly Cho, J Michael Gaziano, Juan P Casas, James M Robins, Miguel A Hernán
Observational studies have estimated strongly protective effects of bariatric surgery on cardiovascular disease, but with oversimplified definitions of the intervention, eligibility criteria, and follow-up, which deviate from those in a randomized trial. We describe studying the effect of bariatric surgery on cardiovascular disease without introducing these sources of bias, which may not be entirely
-
Understanding the intergenerational impact of migration: An adult mortality advantage for the children of forced migrants? Epidemiology (IF 4.7) Pub Date : 2024-07-10 Ben Wilson, Matthew Wallace, Jan Saarela
Children of immigrants often have excess mortality rates, in contrast to the low mortality typically exhibited by their parents' generation. However, prior research has studied children of immigrants who were selected into migration, thereby rendering it difficult to isolate the intergenerational impact of migration on adult mortality.
-
Placebo Adherence as a Negative Control Exposure. Epidemiology (IF 4.7) Pub Date : 2024-07-05 Kerollos Nashat Wanis, Aaron L Sarvet
In placebo-controlled randomized clinical trials, adherence to the placebo is often supposed to have no effect on the primary outcome of interest: when unbiased methods are used, investigators expect to estimate a null effect. Estimating the 'effect' of adherence to placebo in these settings has thus been proposed and popularized as a strategy for detecting bias, for example, from unmeasured confounding
-
Overcoming data gaps in life course epidemiology by matching across cohorts. Epidemiology (IF 4.7) Pub Date : 2024-07-05 Katrina L Kezios, Scott C Zimmerman, Peter T Buto, Kara E Rudolph, Sebastian Calonico, Adina Zeki Al-Hazzouri, M Maria Glymour
Lifecourse epidemiology is hampered by the absence of large studies with exposures and outcomes measured at different life stages on the same individuals. We describe when the effect of an exposure (A) on an outcome (Y) in a target population is identifiable in a combined ("synthetic") cohort created by pooling an early-life cohort including measures of A with a late-life cohort including measures
-
Fetal Exposure to Tobacco Metabolites and Depression During Adulthood: Beyond Binary Measures. Epidemiology (IF 4.7) Pub Date : 2024-07-05 E D Shenassa, J L Gleason, K Hirabayashi
Sibling studies of maternal smoking during pregnancy and subsequent risk of depression have produced mixed results. A recent study identified not considering amount of maternal smoking and age of onset as potentially masking a true association. We examine these issues and also the relevance of maternal smoking during pregnancy as a determinant of severity of depressive symptoms.
-
A new criterion for determining a cutoff value based on the biases of incidence proportions in the presence of non-differential outcome misclassifications. Epidemiology (IF 4.7) Pub Date : 2024-07-05 Norihiro Suzuki, Masataka Taguri
When conducting database studies, researchers sometimes use an algorithm known as "case definition," "outcome definition," or "computable phenotype" to identify the outcome of interest. Generally, algorithms are created by combining multiple variables and codes, and we need to select the most appropriate one to apply to the database study. Validation studies compare algorithms with the gold standard
-
Advances in difference-in-differences methods for policy evaluation research. Epidemiology (IF 4.7) Pub Date : 2024-07-05 Guangyi Wang, Rita Hamad, Justin S White
Difference-in-differences (DiD) is a powerful, quasi-experimental research design widely used in longitudinal policy evaluations with health outcomes. However, DiD designs face several challenges to ensuring reliable causal inference, such as when policy settings are more complex. Recent economics literature has revealed that DiD estimators may exhibit bias when heterogeneous treatment effects, a common
-
Ethylene oxide hemoglobin adducts in cord blood and offspring's size at birth: The NewGeneris European Cohort Study. Epidemiology (IF 4.7) Pub Date : 2024-06-27 Barbara N Harding, Silvia Agramunt, Marie Pedersen, Lisbeth E Knudsen, Jeanette Ks Nielsen, John Wright, Marina Vafeiadi, Domenico F Merlo, Leslie Stayner, Kaitlin Kelly-Reif, Ana Espinosa, Mariona Bustamante, Kristine Bjerve Gützkow, Berit Granum, Hans von Stedingk, Per Rydberg, Jan Alexander, Margareta Törnqvist, Manolis Kogevinas
Prenatal ethylene oxide exposure may have adverse effects on fetal development. We examined the relationships between ethylene oxide hemoglobin (Hb) adduct levels and offspring's size at birth in a prospective European mother-child study.
-
Associations of Local Cannabis Control Policies With Harmful Cannabis Exposures Reported to the California Poison Control System. Epidemiology (IF 4.7) Pub Date : 2024-06-24 Ellicott C Matthay, Leyla M Mousli, Chloe Sun, Justin Lewis, Laurie M Jacobs, Stuart Heard, Raymond Ho, Laura A Schmidt, Dorie E Apollonio
Cannabis exposures reported to the California Poison Control System increased following the initiation of recreational cannabis sales on 1 January 2018 (i.e., "commercialization"). We evaluated whether local cannabis control policies adopted by 2021 were associated with shifts in harmful cannabis exposures.
-
Scarring In Utero: An Attempt to Validate With Data Unconfounded by Migration and Medical Care. Epidemiology (IF 4.7) Pub Date : 2024-06-24 Ralph Catalano, Jason Bonham, Alison Gemmill, Tim Bruckner
"Scarring in utero" posits that populations exposed to injurious stressors yield birth cohorts that live shorter lives than expected from history. This argument implies a positive historical association between period life expectancy (i.e., average age at death in year t) and cohort life expectancy (i.e., average lifespan of persons born in year t). Tests of the argument have not produced consistent
-
Newborn Dried Blood Spot Folate in Relation to Maternal Self-reported Folic Acid Intake, Autism Spectrum Disorder, and Developmental Delay. Epidemiology (IF 4.7) Pub Date : 2024-06-24 Rebecca J Schmidt, Amanda J Goodrich, Lora Delwiche, Robin L Hansen, Claire L Simpson, Daniel Tancredi, Heather E Volk
Maternal folic acid intake has been associated with decreased risk for neurodevelopmental disorders including autism spectrum disorder (ASD). Genetic differences in folate metabolism could explain some inconsistencies. To our knowledge, newborn folate concentrations remain unexamined.
-
Effectiveness of mRNA COVID-19 Vaccines as First Booster Doses in England: An Observational Study in OpenSAFELY-TPP. Epidemiology (IF 4.7) Pub Date : 2024-06-24 Elsie M F Horne, William J Hulme, Edward P K Parker, Ruth H Keogh, Elizabeth J Williamson, Venexia M Walker, Tom M Palmer, Rachel Denholm, Rochelle Knight, Helen J Curtis, Alex J Walker, Colm D Andrews, Amir Mehrkar, Jessica Morley, Brian MacKenna, Sebastian C J Bacon, Ben Goldacre, Miguel A Hernán, Jonathan A C Sterne
The UK delivered its first "booster" COVID-19 vaccine doses in September 2021, initially to individuals at high risk of severe disease, then to all adults. The BNT162b2 Pfizer-BioNTech vaccine was used initially, then also Moderna mRNA-1273.
-
Air Pollution Exposures and Child Executive Function: A U.S. Multi-Cohort Study. Epidemiology (IF 4.7) Pub Date : 2024-06-13 Yu Ni, Alexis Sullivan, Adam A Szpiro, James Peng, Christine T Loftus, Marnie F Hazlehurst, Allison Sherris, Erin R Wallace, Laura E Murphy, Ruby H N Nguyen, Shanna H Swan, Sheela Sathyanarayana, Emily S Barrett, W Alex Mason, Nicole R Bush, Catherine J Karr, Kaja Z LeWinn
Executive function, which develops rapidly in childhood, enables problem solving, focused attention, and planning. Animal models describe executive function decrements associated with ambient air pollution exposure, but epidemiologic studies are limited.
-
Synthesizing subject-matter expertise for variable selection in causal effect estimation: A case study. Epidemiology (IF 4.7) Pub Date : 2024-06-11 Julia Debertin, Javier A Jurado Vélez, Laura Corlin, Bertha Hidalgo, Eleanor J Murray
Causal graphs are an important tool for covariate selection but there is limited applied research on how best to create them. Here, we used data from the Coronary Drug Project (CDP) trial to assess a range of approaches to directed acyclic graph (DAG) creation. We focused on the effect of adherence on mortality in the placebo arm, since the true causal effect is believed with a high degree of certainty
-
An Efficient Approach to Nowcasting the Time-varying Reproduction Number. Epidemiology (IF 4.7) Pub Date : 2024-05-24 Bryan Sumalinab, Oswaldo Gressani, Niel Hens, Christel Faes
Estimating the instantaneous reproduction number () in near real time is crucial for monitoring and responding to epidemic outbreaks on a daily basis. However, such estimates often suffer from bias due to reporting delays inherent in surveillance systems. We propose a fast and flexible Bayesian methodology to overcome this challenge by estimating while taking into account reporting delays. Furthermore
-
Outcome of pregnancy oral glucose tolerance test and preterm birth. Epidemiology (IF 4.7) Pub Date : 2024-05-21 Richard Liang, Danielle M Panelli, David K Stevenson, David H Rehkopf, Gary M Shaw, Henrik Toft Sørensen, Lars Pedersen
Gestational diabetes is associated with adverse outcomes such as preterm birth (<37 weeks). However, there is no international consensus on screening criteria or diagnostic levels for gestational diabetes, and it is unknown whether body mass index (BMI) or obesity modifies the relation between glucose level and preterm birth.
-
Effects of recall and selection biases on modeling cancer risk from mobile phone use: Results from a case-control simulation study. Epidemiology (IF 4.7) Pub Date : 2024-05-20 Liacine Bouaoun, Graham Byrnes, Susanna Lagorio, Maria Feychting, Abdellah Abou-Bakre, Rémi Beranger, Joachim Schüz
The largest case-control study (Interphone Study) investigating glioma risk related to mobile phone use showed a J-shaped relationship with reduced relative risks for moderate use and a 40% increased relative risk among the 10% heaviest regular mobile phone users, using a categorical risk model based on deciles of lifetime duration of use among ever regular users.
-
Representativeness of Participants in the ACCORD Trial Compared to Middle-aged and Older Adults Living with Diabetes in the United States. Epidemiology (IF 4.7) Pub Date : 2024-05-20 Ryo Ikesu, Yingyan Wu, Scott C Zimmerman, Kosuke Inoue, Peter Buto, Melinda C Power, Catherine A Schaefer, M Maria Glymour, Elizabeth Rose Mayeda
We evaluated whether participants in the landmark Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial represent U.S. adults aged ≥40 with diabetes.
-
Assessing Direct and Spillover Effects of Intervention Packages in Network-randomized Studies. Epidemiology (IF 4.7) Pub Date : 2024-05-06 Ashley L Buchanan, Raúl Ulises Hernández-Ramírez, Judith J Lok, Sten H Vermund, Samuel R Friedman, Laura Forastiere, Donna Spiegelman
Intervention packages may result in a greater public health impact than single interventions. Understanding the separate impact of each component on the overall package effectiveness can improve intervention delivery.
-
Prediction Under Interventions: Evaluation of Counterfactual Performance Using Longitudinal Observational Data. Epidemiology (IF 4.7) Pub Date : 2024-04-18 Ruth H Keogh, Nan Van Geloven
Predictions under interventions are estimates of what a person's risk of an outcome would be if they were to follow a particular treatment strategy, given their individual characteristics. Such predictions can give important input to medical decision-making. However, evaluating the predictive performance of interventional predictions is challenging. Standard ways of evaluating predictive performance
-
A Quantitative Bias Analysis Approach to Informative Presence Bias in Electronic Health Records. Epidemiology (IF 4.7) Pub Date : 2024-04-18 Hanxi Zhang, Amy S Clark, Rebecca A Hubbard
Accurate outcome and exposure ascertainment in electronic health record (EHR) data, referred to as EHR phenotyping, relies on the completeness and accuracy of EHR data for each individual. However, some individuals, such as those with a greater comorbidity burden, visit the health care system more frequently and thus have more complete data, compared with others. Ignoring such dependence of exposure
-
Interpretations of Studies on SARS-CoV-2 Vaccination and Post-acute COVID-19 Sequelae. Epidemiology (IF 4.7) Pub Date : 2024-04-18 Bronner P Gonçalves, Piero L Olliaro, Peter Horby, Laura Merson, Benjamin J Cowling
This article discusses causal interpretations of epidemiologic studies of the effects of vaccination on sequelae after acute severe acute respiratory syndrome coronavirus 2 infection. To date, researchers have tried to answer several different research questions on this topic. While some studies assessed the impact of postinfection vaccination on the presence of or recovery from post-acute coronavirus
-
Long-term Impact of Tropical Cyclones on Disease Exacerbation Among Children with Asthma in the Eastern United States, 2000-2018. Epidemiology (IF 4.7) Pub Date : 2024-04-18 Kate R Weinberger, Nina Veeravalli, Xiao Wu, Nicholas J Nassikas, Keith R Spangler, Nina R Joyce, Gregory A Wellenius
Tropical cyclones are associated with acute increases in mortality and morbidity, but few studies have examined their longer-term health consequences. We assessed whether tropical cyclones are associated with a higher frequency of symptom exacerbation among children with asthma in the following 12 months in eastern United States counties, 2000-2018.
-
Improving Inverse Probability Weighting by Post-calibrating Its Propensity Scores. Epidemiology (IF 4.7) Pub Date : 2024-04-15 Rom Gutman, Ehud Karavani, Yishai Shimoni
Theoretical guarantees for causal inference using propensity scores are partially based on the scores behaving like conditional probabilities. However, scores between zero and one do not necessarily behave like probabilities, especially when output by flexible statistical estimators. We perform a simulation study to assess the error in estimating the average treatment effect before and after applying
-
Reporting and Description of Research Methodology in Studies Estimating Effects of Firearm Policies. Epidemiology (IF 4.7) Pub Date : 2024-04-09 Camerin A Rencken, Julia P Schleimer, Matthew Miller, Sonja A Swanson, Ali Rowhani-Rahbar
Evidence about which firearm policies work, to what extent, and for whom is hotly debated, perhaps partly because variation in research methodology has produced mixed and inconclusive effect estimates. We conducted a scoping review of firearm policy research in the health sciences in the United States, focusing on methodological considerations for causal inference.
-
Risk of adverse perinatal outcomes among African-born Black women in California, 2011-2020. Epidemiology (IF 4.7) Pub Date : 2024-03-29 Safyer McKenzie-Sampson, Rebecca J Baer, Brittany D Chambers Butcher, Laura L Jelliffe-Pawlowski, Deborah Karasek, Scott P Oltman, Corinne A Riddell, Elizabeth E Rogers, Jacqueline M Torres, Bridgette Blebu
African-born women have a lower risk of preterm birth and small for gestational age (SGA) birth compared to United States (US)-born Black women, however variation by country of origin is overlooked. Additionally, the extent that nativity disparities in adverse perinatal outcomes to Black women are explained by individual-level factors remains unclear.
-
Validation of ICD-10 codes for severe maternal morbidity at delivery in a public hospital. Epidemiology (IF 4.7) Pub Date : 2024-03-29 Sheree L Boulet, Kaitlyn K Stanhope, Arielle N Valdez-Sinon, Danielle Vuncannon, Jessica Preslar, Hannah Bergbower, Brendan Gray, Asmita Gathoo, Nora Hansen, Kerri Andre, Sabrine Bensouda, Braun Cally, Marissa Platner
Severe maternal morbidity is a composite measure of serious obstetric complications that is often identified in administrative data using International Classification of Diseases (ICD) diagnosis and procedure codes for a set of 21 indicators. Prior studies of screen-positive cases have demonstrated low predictive value for ICD codes relative to the medical record. To our knowledge, the validity of
-
Validation of long-term recall of pregnancy-related weight in the Life-course Experiences And Pregnancy (LEAP) study. Epidemiology (IF 4.7) Pub Date : 2024-03-29 Kriszta Farkas, Lisa M Bodnar, Rebecca L Emery Tavernier, Jessica K Friedman, Sydney T Johnson, Richard F MacLehose, Susan M Mason
Pre-pregnancy body mass index (BMI) and gestational weight gain (GWG) are determinants of maternal and child health. However, many studies of these factors rely on error-prone self-reported measures.
-
Perceptions of Racial/Ethnic Inequities in COVID-19 Healthcare and Willingness to Receive the COVID-19 Vaccine. Epidemiology (IF 4.7) Pub Date : 2024-03-28 Juliana S Sherchan, Jessica R Fernandez, Anuli Njoku, Tyson H Brown, Allana T Forde
Perceptions of the U.S. healthcare system can impact individuals' healthcare utilization, including vaccination intentions. This study examined the association between perceived racial-ethnic inequities in COVID-19 healthcare and willingness to receive the COVID-19 vaccine.
-
Defining Spatial Epidemiology: A Systematic Review and Re-Orientation. Epidemiology (IF 4.7) Pub Date : 2024-03-22 Christopher N Morrison, Christina F Mair, Lisa Bates, Dustin T Duncan, Charles C Branas, Brady R Bushover, Christina A Mehranbod, Ariana N Gobaud, Stephen Uong, Sarah Forrest, Leah Roberts, Andrew G Rundle
Spatial epidemiology has emerged as an important subfield of epidemiology over the past quarter century. We trace the origins of spatial epidemiology and note that its emergence coincided with technological developments in spatial statistics and geography. We hypothesize that spatial epidemiology makes important contributions to descriptive epidemiology and analytic risk factor studies, but is not
-
Outdoor artificial light at night and reproductive endocrine and glucose homeostasis and polycystic ovary syndrome in women of reproductive age. Epidemiology (IF 4.7) Pub Date : 2024-03-22 Lanlan Fang, Cong Ma, Guosheng Wang, Yongzhen Peng, Hui Zhao, Yuting Chen, Yubo Ma, Guoqi Cai, Yunxia Cao, Faming Pan
Artificial light at night, a well-recognized circadian clock disrupter, causes disturbances in endocrine homeostasis. However, the association of artificial light at night with polycystic ovary syndrome (PCOS) is still unknown. This study examines the effects of outdoor artificial light at night on sex hormones, glucose homeostasis markers, and PCOS prevalence in Anhui Province, China.
-
Comparing PCSK9 Monoclonal Antibody Treatment Strategies Following Myocardial Infarction Using Negative Control Outcomes: A Target Trial Emulation Study. Epidemiology (IF 4.7) Pub Date : 2024-03-12 Rosa Sloot, Alexander Breskin, Lisandro D Colantonio, Andrew G Allmon, Ying Yu, Swati Sakhuja, Ligong Chen, Paul Muntner, M Alan Brookhart, Nafeesa Dhalwani
Initiation of proprotein convertase subtilisin/kexin type 9 monoclonal antibody (PCSK9 mAb) for lipid-lowering following myocardial infarction (MI) is likely affected by patients' prognostic factors, potentially leading to bias when comparing real-world treatment effects.
-
Errors in the Calculation of the Population Attributable Fraction. Epidemiology (IF 4.7) Pub Date : 2024-03-12 Etsuji Suzuki, Eiji Yamamoto
One of the common errors in the calculation of the population attributable fraction (PAF) is the use of an adjusted risk ratio in the Levin formula. In this article, we discuss the errors visually using wireframes by varying the standardized mortality ratio (SMR) and associational risk ratio (aRR) when the prevalence of exposure is fixed. When SMR > 1 and SMR > aRR, the absolute bias is positive, and
-
Causal Selection of Covariates in Regression Calibration for Mismeasured Continuous Exposure. Epidemiology (IF 4.7) Pub Date : 2024-03-07 Wenze Tang, Donna Spiegelman, Xiaomei Liao, Molin Wang
Regression calibration as developed by Rosner, Spiegelman, and Willett is used to adjust the bias in effect estimates due to measurement error in continuous exposures. The method involves two models: a measurement error model relating the mismeasured exposure to the true (or gold-standard) exposure and an outcome model relating the mismeasured exposure to the outcome. However, no comprehensive guidance
-
Adjusting Incidence Estimates with Laboratory Test Performances: A Pragmatic Maximum Likelihood Estimation-Based Approach. Epidemiology (IF 4.7) Pub Date : 2024-03-07 Yingjie Weng, Lu Tian, Derek Boothroyd, Justin Lee, Kenny Zhang, Di Lu, Christina P Lindan, Jenna Bollyky, Beatrice Huang, George W Rutherford, Yvonne Maldonado, Manisha Desai
Understanding the incidence of disease is often crucial for public policy decision-making, as observed during the COVID-19 pandemic. Estimating incidence is challenging, however, when the definition of incidence relies on tests that imperfectly measure disease, as in the case when assays with variable performance are used to detect the SARS-CoV-2 virus. To our knowledge there are no pragmatic methods
-
Using negative control populations to assess unmeasured confounding and direct effects. Epidemiology (IF 4.7) Pub Date : 2024-03-07 Marco Piccininni, Mats Julius Stensrud
Sometimes treatment effects are absent in a subgroup of the population. For example, penicillin has no effect on severe symptoms in individuals infected by resistant staphylococcus aureus, and codeine has no effect on pain in individuals with certain polymorphisms in the CYP2D6 enzyme. Subgroups where a treatment is ineffective are often called negative control populations or placebo groups. They are
-
A capture-recapture-based ascertainment probability weighting method for effect estimation with under-ascertained outcomes. Epidemiology (IF 4.7) Pub Date : 2024-03-04 Carl Bonander, Anton Nilsson, Huiqi Li, Shambhavi Sharma, Chioma Nwaru, Magnus Gisslén, Magnus Lindh, Niklas Hammar, Jonas Björk, Fredrik Nyberg
Outcome under-ascertainment, characterized by the incomplete identification or reporting of cases, poses a substantial challenge in epidemiologic research. While capture-recapture methods can estimate unknown case numbers, their role in estimating exposure effects in observational studies is not well established. This paper presents an ascertainment probability weighting framework that integrates capture-recapture
-
Towards a clearer causal question underlying the association between cancer and dementia. Epidemiology (IF 4.7) Pub Date : 2024-03-04 L Paloma Rojas-Saunero, Kimberly D van der Willik, Sanne B Schagen, M Arfan Ikram, Sonja A Swanson
Several observational studies have described an inverse association between cancer diagnosis and subsequent dementia risk. Multiple biologic mechanisms and potential biases have been proposed in attempts to explain this association. One proposed explanation is the opposite expression of Pin1 in cancer and dementia, and we use this explanation and potential drug target to illustrate the required assumptions
-
Partial Identification of the Effects of Sustained Treatment Strategies. Epidemiology (IF 4.7) Pub Date : 2024-02-26 Elizabeth W Diemer, Joy Shi, Sonja A Swanson
Although many epidemiologic studies focus on point identification, it is also possible to partially identify causal effects under consistency and the data alone. However, the literature on the so-called "assumption-free" bounds has focused on settings with time-fixed exposures. We describe assumption-free bounds for the effects of both static and dynamic sustained interventions. To provide intuition
-
Simulating the simultaneous impact of medication for opioid use disorder and naloxone on opioid overdose death in eight New York counties. Epidemiology (IF 4.7) Pub Date : 2024-02-19 Magdalena Cerdá, Ava D Hamilton, Ayaz Hyder, Caroline Rutherford, Georgiy Bobashev, Joshua M Epstein, Erez Hatna, Noa Krawczyk, Nabila El-Bassel, Daniel J Feaster, Katherine M Keyes
The United States is in the midst of an opioid overdose epidemic; 28.3 per 100,000 people died of opioid overdose in 2020. Simulation models can help understand and address this complex, dynamic, nonlinear social phenomenon. Using the HEALing Communities Study, aimed at reducing opioid overdoses, and an agent-based model, SiCLOPS (Simulation of Community-Level Overdose Prevention Strategy), we simulated
-
Application of a web-based tool for quantitative bias analysis: the example of misclassification due to self-reported body mass index. Epidemiology (IF 4.7) Pub Date : 2024-02-01 Hailey R Banack, Samantha N Smith, Lisa M Bodnar
We describe the use of Apisensr, a web-based application that can be used to implement quantitative bias analysis for misclassification, selection bias, and unmeasured confounding. We apply Apisensr using an example of exposure misclassification bias due to use of self-reported body mass index (BMI) to define obesity status in an analysis of the relationship between obesity and diabetes.
-
Estimated excess deaths due to COVID-19 among the urban population of Mainland China, December 2022 to January 2023. Epidemiology (IF 4.7) Pub Date : 2024-01-29 Leon Raphson, Marc Lipsitch
Mainland China experienced a major surge in SARS-CoV-2 infections in December 2022-January 2023, but its impact on mortality was unclear given the under-reporting of COVID-19 deaths.
-
Association between home renovation and sleeping problems among children aged 6 to 18 years: a nationwide survey in China. Epidemiology (IF 4.7) Pub Date : 2024-01-23 Dao-Sen Wang, Hong-Zhi Zhang, Si-Han Wu, Zheng-Min Qian, Stephen Edward McMillin, Elizabeth Bingheim, Wei-Hong Tan, Wen-Zhong Huang, Pei-En Zhou, Ru-Qing Liu, Li-Wen Hu, Gong-Bo Chen, Bo-Yi Yang, Xiao-Wen Zeng, Qian-Sheng Hu, Li-Zi Lin, Guang-Hui Dong
Although indoor environment has been proposed to be associated with childhood sleep health, to our knowledge no study has investigated the association between home renovation and childhood sleep problems.
-
Distinguishing Immunologic and Behavioral Effects of Vaccination. Epidemiology (IF 4.7) Pub Date : 2024-01-03 Mats J Stensrud, Daniel Nevo, Uri Obolski
The interpretation of vaccine efficacy estimands is subtle, even in randomized trials designed to quantify the immunologic effects of vaccination. In this article, we introduce terminology to distinguish between different vaccine efficacy estimands and clarify their interpretations. This allows us to explicitly consider the immunologic and behavioral effects of vaccination, and establish that policy-relevant
-
PROVIDENT: Development and validation of a machine learning model to predict neighborhood-level overdose risk in Rhode Island. Epidemiology (IF 4.7) Pub Date : 2024-01-02 Bennett Allen, Robert C Schell, Victoria A Jent, Maxwell Krieger, Claire Pratty, Benjamin D Hallowell, William C Goedel, Melissa Bastos, Jesse L Yedinak, Yu Li, Abigail R Cartus, Brandon D L Marshall, Magdalena Cerdá, Jennifer Ahern, Daniel B Neill
Drug overdose persists as a leading cause of death in the United States, but resources to address it remain limited. As a result, health authorities must consider where to allocate scarce resources within their jurisdictions. Machine learning offers a strategy to identify areas with increased future overdose risk to proactively allocate overdose prevention resources. This modeling study is embedded