Search Results - "International journal of epidemiology"

The SARS, MERS and novel coronavirus (COVID-19) epidemics, the newest and biggest global health threats: what lessons have we learned? by Peeri, Noah C, Shrestha, Nistha, Rahman, Md Siddikur, Zaki, Rafdzah, Tan, Zhengqi, Bibi, Saana, Baghbanzadeh, Mahdi, Aghamohammadi, Nasrin, Zhang, Wenyi, Haque, Ubydul

“…Abstract Objectives To provide an overview of the three major deadly coronaviruses and identify areas for improvement of future preparedness plans, as well as…”
Get full text

Use of directed acyclic graphs (DAGs) to identify confounders in applied health research: review and recommendations by Tennant, Peter W G, Murray, Eleanor J, Arnold, Kellyn F, Berrie, Laurie, Fox, Matthew P, Gadd, Sarah C, Harrison, Wendy J, Keeble, Claire, Ranker, Lynsie R, Textor, Johannes, Tomova, Georgia D, Gilthorpe, Mark S, Ellison, George T H

“…Directed acyclic graphs (DAGs) are an increasingly popular approach for identifying confounding variables that require conditioning when estimating causal…”
Get full text

An examination of multivariable Mendelian randomization in the single-sample and two-sample summary data settings by Sanderson, Eleanor, Davey Smith, George, Windmeijer, Frank, Bowden, Jack

“…Abstract Background Mendelian randomization (MR) is a powerful tool in epidemiology that can be used to estimate the causal effect of an exposure on an outcome…”
Get full text

Global birth prevalence of congenital heart defects 1970–2017: updated systematic review and meta-analysis of 260 studies by Liu, Yingjuan, Chen, Sen, Zühlke, Liesl, Black, Graeme C, Choy, Mun-kit, Li, Ningxiu, Keavney, Bernard D

“…Abstract Background Globally, access to healthcare and diagnostic technologies are known to substantially impact the reported birth prevalence of congenital…”
Get full text

Robust inference in summary data Mendelian randomization via the zero modal pleiotropy assumption by Hartwig, Fernando Pires, Davey Smith, George, Bowden, Jack

“…Mendelian randomization (MR) is being increasingly used to strengthen causal inference in observational studies. Availability of summary data of genetic…”
Get full text

MendelianRandomization: an R package for performing Mendelian randomization analyses using summarized data by Yavorska, Olena O, Burgess, Stephen

“…MendelianRandomization is a software package for the R open-source software environment that performs Mendelian randomization analyses using summarized data…”
Get full text

Improving the accuracy of two-sample summary-data Mendelian randomization: moving beyond the NOME assumption by Bowden, Jack, Del Greco M, Fabiola, Minelli, Cosetta, Zhao, Qingyuan, Lawlor, Debbie A, Sheehan, Nuala A, Thompson, John, Davey Smith, George

“…Abstract Background Two-sample summary-data Mendelian randomization (MR) incorporating multiple genetic variants within a meta-analysis framework is a popular…”
Get full text

Fruit and vegetable intake and the risk of cardiovascular disease, total cancer and all-cause mortality-a systematic review and dose-response meta-analysis of prospective studies by Aune, Dagfinn, Giovannucci, Edward, Boffetta, Paolo, Fadnes, Lars T, Keum, NaNa, Norat, Teresa, Greenwood, Darren C, Riboli, Elio, Vatten, Lars J, Tonstad, Serena

“…Questions remain about the strength and shape of the dose-response relationship between fruit and vegetable intake and risk of cardiovascular disease, cancer…”
Get full text

Interrupted time series regression for the evaluation of public health interventions: a tutorial by Bernal, James Lopez, Cummins, Steven, Gasparrini, Antonio

“…Interrupted time series (ITS) analysis is a valuable study design for evaluating the effectiveness of population-level health interventions that have been…”
Get full text

Accounting for missing data in statistical analyses: multiple imputation is not always the answer by Hughes, Rachael A, Heron, Jon, Sterne, Jonathan A C, Tilling, Kate

“…Abstract Background Missing data are unavoidable in epidemiological research, potentially leading to bias and loss of precision. Multiple imputation (MI) is…”
Get full text

Quantifying impacts of the COVID-19 pandemic through life-expectancy losses: a population-level study of 29 countries by Aburto, José Manuel, Schöley, Jonas, Kashnitsky, Ilya, Zhang, Luyin, Rahal, Charles, Missov, Trifon I, Mills, Melinda C, Dowd, Jennifer B, Kashyap, Ridhi

“…Abstract Background Variations in the age patterns and magnitudes of excess deaths, as well as differences in population sizes and age structures, make…”
Get full text

Cohort Profile: The National Health Insurance Service-National Sample Cohort (NHIS-NSC), South Korea by Lee, Juneyoung, Lee, Ji Sung, Park, Sook-Hee, Shin, Soon Ae, Kim, KeeWhan

Get full text

Data resource profile: Clinical Practice Research Datalink (CPRD) Aurum by Wolf, Achim, Dedman, Daniel, Campbell, Jennifer, Booth, Helen, Lunn, Darren, Chapman, Jennifer, Myles, Puja

Get full text

Data Resource Profile: The Danish National Prescription Registry by Pottegård, Anton, Schmidt, Sigrun Alba Johannesdottir, Wallach-Kildemoes, Helle, Sørensen, Henrik Toft, Hallas, Jesper, Schmidt, Morten

Get full text

Has the prevalence of overweight, obesity and central obesity levelled off in the United States? Trends, patterns, disparities, and future projections for the obesity epidemic by Wang, Youfa, Beydoun, May A, Min, Jungwon, Xue, Hong, Kaminsky, Leonard A, Cheskin, Lawrence J

“…Abstract Background Obesity (OB) is a serious epidemic in the United States. Methods We examined OB patterns and time trends across socio-economic and…”
Get full text

Robust causal inference using directed acyclic graphs: the R package 'dagitty' by Textor, Johannes, van der Zander, Benito, Gilthorpe, Mark S, Liskiewicz, Maciej, Ellison, George Th

“…Directed acyclic graphs (DAGs), which offer systematic representations of causal relationships, have become an established framework for the analysis of causal…”
Get full text

Data Resource Profile: The National Health Information Database of the National Health Insurance Service in South Korea by Cheol Seong, Sang, Kim, Yeon-Yong, Khang, Young-Ho, Heon Park, Jong, Kang, Hee-Jin, Lee, Heeyoung, Do, Cheol-Ho, Song, Jong-Sun, Hyon Bang, Ji, Ha, Seongjun, Lee, Eun-Joo, Ae Shin, Soon

Get full text

PM2.5 air pollution and cause-specific cardiovascular disease mortality by Hayes, Richard B, Lim, Chris, Zhang, Yilong, Cromar, Kevin, Shao, Yongzhao, Reynolds, Harmony R, Silverman, Debra T, Jones, Rena R, Park, Yikyung, Jerrett, Michael, Ahn, Jiyoung, Thurston, George D

“…Abstract Background Ambient air pollution is a modifiable risk factor for cardiovascular disease, yet uncertainty remains about the size of risks at lower…”
Get full text

Improving the visualization, interpretation and analysis of two-sample summary data Mendelian randomization via the Radial plot and Radial regression by Bowden, Jack, Spiller, Wesley, Del Greco M, Fabiola, Sheehan, Nuala, Thompson, John, Minelli, Cosetta, Davey Smith, George

“…Abstract Background Summary data furnishing a two-sample Mendelian randomization (MR) study are often visualized with the aid of a scatter plot, in which…”
Get full text

Collider scope: when selection bias can substantially influence observed associations by Munafò, Marcus R, Tilling, Kate, Taylor, Amy E, Evans, David M, Davey Smith, George

“…Large-scale cross-sectional and cohort studies have transformed our understanding of the genetic and environmental determinants of health outcomes. However,…”
Get full text