Epidemiology最新文献_第3页

Using measurement error parameters from validation data. 使用验证数据中的测量误差参数。

IF 4.4 2区医学

Epidemiology Pub Date : 2025-09-15 DOI: 10.1097/EDE.0000000000001917

Rachael K Ross, Matthew P Fox, Catherine R Lesko, Jacqueline E Rudolph, Lauren C Zalla, Jessie K Edwards

{"title":"Using measurement error parameters from validation data.","authors":"Rachael K Ross, Matthew P Fox, Catherine R Lesko, Jacqueline E Rudolph, Lauren C Zalla, Jessie K Edwards","doi":"10.1097/EDE.0000000000001917","DOIUrl":"https://doi.org/10.1097/EDE.0000000000001917","url":null,"abstract":"Measurement error is ubiquitous in the data used for epidemiologic research and can lead to meaningful information bias. Analytic approaches to address measurement error and quantitative bias analyses examining the potential impact of measurement error on study results often leverage validation data that provides information about the relationship between the true measure and the available imperfect measure, quantified by measurement error parameters such as sensitivity and specificity in the binary case. Leveraging validation data often requires transporting these measurement error parameters from the validation data to the target sample of interest (that may or may not include individuals from the validation data). In this paper we examine the independence assumptions required to transport measurement error parameters from the validation data to the target sample, highlighting how the required assumption differs depending on the form of the measurement error parameters (i.e., whether it is the true measure conditional on the imperfect measure or vice versa). We then illustrate how diagrams can clarify the conditions under which the required assumptions hold and thus what measurement error parameters can be validly transported. This work provides practical tools for epidemiologists to address measurement error using validation data in applied research.","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145063734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Use of routinely collected data to classify planned mode of delivery among pregnancies with a previous cesarean delivery: a validation study. 使用常规收集的数据对既往剖宫产妊娠的计划分娩方式进行分类：一项验证研究。

IF 4.4 2区医学

Epidemiology Pub Date : 2025-09-15 DOI: 10.1097/EDE.0000000000001915

Mary M Brown, Ya-Hui Yu, Jennifer A Hutcheon, Christy G Woolcott, Victoria M Allen, John Fahey, Irene Gagnon, Azar Mehrabadi

{"title":"Use of routinely collected data to classify planned mode of delivery among pregnancies with a previous cesarean delivery: a validation study.","authors":"Mary M Brown, Ya-Hui Yu, Jennifer A Hutcheon, Christy G Woolcott, Victoria M Allen, John Fahey, Irene Gagnon, Azar Mehrabadi","doi":"10.1097/EDE.0000000000001915","DOIUrl":"https://doi.org/10.1097/EDE.0000000000001915","url":null,"abstract":"Background: Counseling on the harms and benefits of a planned vaginal versus a planned repeat cesarean delivery often relies on observational studies using routinely collected (or administrative) data. However, the accuracy of planned (rather than actual) mode of delivery classifications in such data remains unknown. This study aimed to evaluate the validity of an administrative data-based algorithm to identify planned vaginal and planned cesarean deliveries among individuals with a previous cesarean.Methods: An algorithm based on diagnostic and procedural codes was applied to records from the Nova Scotia Atlee Perinatal Database. Included were individuals with a previous cesarean eligible for a trial of labor between 2017 and 2019. We compared the classification of planned mode of delivery using the algorithm with that determined through review of a random sample of 200 medical charts. We estimated sensitivity, specificity, and predictive values with 95% confidence intervals (CI).Results: Based on the chart review, 80 deliveries (40%) were planned vaginal deliveries. The algorithm had an estimated sensitivity of 99% (95% CI 93, 100%), specificity of 96% (95% CI 91, 99%), positive predictive value of 94% (95% CI 87, 98%), and negative predictive value of 99% (95% CI 95, 100%) for identifying planned vaginal deliveries.Conclusions: An algorithm based on routinely collected data accurately classified planned vaginal and planned cesarean deliveries among individuals with a previous cesarean. These findings suggest that studies using similar algorithms to inform counseling on planned mode of delivery in this population are minimally impacted by misclassification of this data.","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145063729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Spatial Difference-in-Differences with Bayesian Disease Mapping Models. 贝叶斯疾病制图模型的空间差中差。

IF 4.4 2区医学

Epidemiology Pub Date : 2025-09-10 DOI: 10.1097/EDE.0000000000001912

Carl Bonander, Marta Blangiardo, Ulf Strömberg

{"title":"Spatial Difference-in-Differences with Bayesian Disease Mapping Models.","authors":"Carl Bonander, Marta Blangiardo, Ulf Strömberg","doi":"10.1097/EDE.0000000000001912","DOIUrl":"https://doi.org/10.1097/EDE.0000000000001912","url":null,"abstract":"Bayesian disease-mapping models are widely used in small-area epidemiology to account for spatial correlation and stabilize estimates through spatial smoothing. In contrast, difference-in-differences (DID) methods-commonly used to estimate treatment effects from observational panel data-typically ignore spatial dependence. This paper integrates disease mapping models into an imputation-based DID framework to address spatially structured residual variation and improve precision in small-area evaluations. The approach builds on recent advances in causal panel data methods, including two-way Mundlak estimation, to enable causal identification equivalent to fixed effects DID while incorporating spatiotemporal random effects. We implement the method using Integrated Nested Laplace Approximation, which supports flexible spatial and temporal structures and efficient Bayesian computation. Simulations show that, when the spatiotemporal structure is correctly specified, the approach improves precision and interval coverage compared to standard DID methods. We illustrate the method by evaluating local ice cleat distribution programs in Swedish municipalities.","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145029365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sensitivity of cancer registry linkage with missing or incomplete social security number and implications for cancer cohorts. 社会安全号码缺失或不完整的癌症登记联系的敏感性及其对癌症队列的影响。

IF 4.4 2区医学

Epidemiology Pub Date : 2025-09-09 DOI: 10.1097/EDE.0000000000001913

Lauren E McCullough, Anusila Deka, Christina Newton, Peter Briggs, Erin Gardner, Kevin C Ward, Lauren R Teras, Alpa V Patel

{"title":"Sensitivity of cancer registry linkage with missing or incomplete social security number and implications for cancer cohorts.","authors":"Lauren E McCullough, Anusila Deka, Christina Newton, Peter Briggs, Erin Gardner, Kevin C Ward, Lauren R Teras, Alpa V Patel","doi":"10.1097/EDE.0000000000001913","DOIUrl":"https://doi.org/10.1097/EDE.0000000000001913","url":null,"abstract":"Background: Linking cancer cohort participants to state cancer registries typically relies on personally identifiable information, including Social Security Numbers (SSN), which uniquely identify individuals. However, complete SSN collection can be limited due to privacy concerns. This study evaluates the sensitivity of cancer registry linkage using partial or missing SSN and examines differences by demographic characteristics.Methods: Using data from 284,361 participants in the Cancer Prevention Study-3 (CPS-3), we conducted probabilistic linkages with cancer registries in Georgia, Ohio, and Texas using Match*Pro software. Participants were linked using combinations of personally identifiable information: complete SSN, partial SSN (last four digits), and missing SSN. We compared the sensitivity of linkages before and after manual review and stratified by sex, age, and race-ethnicity.Results: Before manual review, sensitivity for missing and partial SSN was 92.5%. Sensitivity improved to 98.6% for missing SSN and 98.8% for partial SSN after manual review. We observed no notable heterogeneity by sex, age, or race-ethnicity, with sensitivity exceeding 87% across all subgroups. Manual review substantially reduced uncertain matches, contributing to high linkage accuracy.Discussion: This study demonstrates that high sensitivity in cancer registry linkage can be achieved without complete SSN, provided other personally identifiable information (e.g., name, date of birth, longitudinal address) is available. These findings support the feasibility of accurate cancer case identification in cohorts with limited SSN data, particularly for historically marginalized populations, and underscore the importance of designing inclusive population-based cancer studies.","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145023023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Doubly Robust Control Outcome Calibration Approach Estimation of Conditional Effects with Uncontrolled Confounding. 双鲁棒控制结果校准方法估计非控制混杂条件效应。

IF 4.4 2区医学

Epidemiology Pub Date : 2025-09-08 DOI: 10.1097/EDE.0000000000001907

Wen Wei Loh

{"title":"Doubly Robust Control Outcome Calibration Approach Estimation of Conditional Effects with Uncontrolled Confounding.","authors":"Wen Wei Loh","doi":"10.1097/EDE.0000000000001907","DOIUrl":"https://doi.org/10.1097/EDE.0000000000001907","url":null,"abstract":"Drawing causal conclusions about nonrandomized exposures rests on assuming no uncontrolled confounding, but it is rarely justifiable to rule out all putative violations of this routinely made yet empirically untestable assumption. Alternatively, this assumption can be avoided by leveraging negative control outcomes using the control outcome calibration approach (COCA). The existing COCA estimator of the average causal effect relies on correctly specifying the mean negative control outcome model, with a closed-form solution for the main exposure effect. In this article, we propose a doubly robust COCA estimator of the average causal effect that relaxes this modeling requirement and permits effect modification through covariate-exposure interaction terms. The doubly robust COCA estimator uses correctly specified exposure and focal outcome models to protect against biases from an incorrectly specified negative control outcome model. The ability to obtain unbiased point estimates and inferences is empirically evaluated using a simulation study. We demonstrate doubly robust COCA using a publicly available dataset to evaluate the effect of volunteering on mental health. This method is practical and easy to implement and permits unbiased estimation of causal effects even amid uncontrolled confounding.","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145014238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

L or M1 -Critical Challenges in Mediation Analysis. 调解分析中的L或m1关键挑战。

IF 4.4 2区医学

Epidemiology Pub Date : 2025-09-01 Epub Date: 2025-06-03 DOI: 10.1097/EDE.0000000000001888

Etsuji Suzuki

引用次数: 0

Computing True Parameter Values in Simulation Studies Using Monte Carlo Integration. 用蒙特卡罗积分计算仿真研究中的真参数值。

IF 4.4 2区医学

Epidemiology Pub Date : 2025-09-01 Epub Date: 2025-06-13 DOI: 10.1097/EDE.0000000000001873

Ashley I Naimi, David Benkeser, Jacqueline E Rudolph

{"title":"Computing True Parameter Values in Simulation Studies Using Monte Carlo Integration.","authors":"Ashley I Naimi, David Benkeser, Jacqueline E Rudolph","doi":"10.1097/EDE.0000000000001873","DOIUrl":"10.1097/EDE.0000000000001873","url":null,"abstract":"Simulation studies are used to evaluate and compare the properties of statistical methods in controlled experimental settings. In most cases, performing a simulation study requires knowledge of the true value of the parameter, or estimand, of interest. However, in many simulation designs, the true value of the estimand is difficult to compute analytically. Here, we illustrate the use of Monte Carlo integration to compute true estimand values in simple and more complex simulation designs. We provide general pseudocode that can be replicated in any software program of choice to demonstrate key principles in using Monte Carlo integration in two scenarios: a simple three-variable simulation where interest lies in the marginally adjusted odds ratio and a more complex causal mediation analysis where interest lies in the controlled direct effect in the presence of mediator-outcome confounders affected by the exposure. We discuss general strategies that can be used to minimize Monte Carlo error and to serve as checks on the simulation program to avoid coding errors. R programming code is provided illustrating the application of our pseudocode in these settings.","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"690-693"},"PeriodicalIF":4.4,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12307111/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144289331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improving the Use of Social Contact Studies in Epidemic Modeling. 改进社会接触研究在流行病建模中的应用。

IF 4.4 2区医学

Epidemiology Pub Date : 2025-09-01 Epub Date: 2025-06-13 DOI: 10.1097/EDE.0000000000001876

Tom Britton, Frank Ball

{"title":"Improving the Use of Social Contact Studies in Epidemic Modeling.","authors":"Tom Britton, Frank Ball","doi":"10.1097/EDE.0000000000001876","DOIUrl":"10.1097/EDE.0000000000001876","url":null,"abstract":"Social contact studies are used in infectious disease epidemiology to infer a contact matrix , having the mean number of contacts between individuals of different age groups as elements. However, does not capture the (often large) variation in the number of contacts within each age group, information is also available in social contact studies. Here, we include such variation by separating each age group into two halves: the socially active (having many contacts) and the socially less active (having fewer contacts). The extended contact matrix and its associated epidemic model show that acknowledging variation in social activity within age groups has a substantial impact on the basic reproduction number, , and the final fraction getting infected if the epidemic takes off, . In fact, variation in social activity is more important for data fitting than allowing for different age groups. A difficulty with variation in social activity, however, is that social contact studies typically lack information on whether mixing with respect to social activity is assortative (when socially active mainly have contact with other socially active individuals) or not. Our analysis shows that accounting for variation in social activity improves model predictability, yielding more accurate expressions for and irrespective of whether such mixing is assortative, but different assumptions on assortativity give rather different outputs. Future social contact studies should, therefore, also try to infer the degree of assortativity (with respect to social activity) between peers and their contacts.","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"660-667"},"PeriodicalIF":4.4,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12303244/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144289332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Housing and Preterm Birth, Stillbirth and Neonatal Death in Canada: A Population-based Study Using 2006 and 2016 National Census Data. 加拿大住房与早产、死产和新生儿死亡：一项基于人口的研究，使用2006年和2016年全国人口普查数据。

IF 4.4 2区医学

Epidemiology Pub Date : 2025-09-01 Epub Date: 2025-07-29 DOI: 10.1097/EDE.0000000000001886

Azar Mehrabadi, Gabriel D Shapiro, Jay S Kaufman, Seungmi Yang

引用次数: 0

Racial and Ethnic Differences in the Relationship of SARS-CoV-2 Infection and the COVID-19 Pandemic Period With Perinatal Health in California. 加州SARS-CoV-2感染、COVID-19大流行期与围产期健康关系的种族差异

IF 4.4 2区医学

Epidemiology Pub Date : 2025-09-01 Epub Date: 2025-05-28 DOI: 10.1097/EDE.0000000000001878

Emily F Liu, Shelley Jung, Kara E Rudolph, Mahasin S Mujahid, William H Dow, Dana E Goin, Rachel Morello-Frosch, Jennifer Ahern

{"title":"Racial and Ethnic Differences in the Relationship of SARS-CoV-2 Infection and the COVID-19 Pandemic Period With Perinatal Health in California.","authors":"Emily F Liu, Shelley Jung, Kara E Rudolph, Mahasin S Mujahid, William H Dow, Dana E Goin, Rachel Morello-Frosch, Jennifer Ahern","doi":"10.1097/EDE.0000000000001878","DOIUrl":"10.1097/EDE.0000000000001878","url":null,"abstract":"Background: In this article, we test the hypothesis that SARS-CoV-2 infection and the COVID-19 pandemic period had stronger adverse implications for perinatal outcomes among marginalized racial and ethnic groups in California.Methods: We used California birth certificates and hospital data from 2019 to 2021 to estimate marginal risk differences for SARS-CoV-2 infection and the COVID-19 pandemic period in relation to perinatal outcomes for Asian, Black, Hispanic, Multiracial, and White pregnant people using targeted maximum likelihood estimation.Results: Among 849,401 deliveries, there were racial and ethnic disparities in the burden of SARS-CoV-2 infection and perinatal outcomes and in the magnitudes of risk associated with SARS-CoV-2 infection and the COVID-19 pandemic. Hispanic pregnant people had the highest incidence of SARS-CoV-2 infection. Asian and Black pregnant people had the greatest marginal risk differences for multiple outcomes, particularly outcomes already disproportionately experienced by these groups.Conclusions: Risks from SARS-CoV-2 infection and the COVID-19 pandemic period on perinatal outcomes were disproportionately experienced by marginalized racial and ethnic groups. Differential burdens of infection and larger risks experienced with pandemic exposures were associated with worse perinatal outcomes for Asian, Black, and Hispanic pregnant people in California compared with those for White pregnant people.","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"668-676"},"PeriodicalIF":4.4,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12307113/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144157429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0