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YuHan Chiu & Target Trials

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Manage episode 294442445 series 2936838
Content provided by American Society for Nutrition. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by American Society for Nutrition or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

In this episode of AJCN In Press, AJCN’s Inaugural Dennis M. Bier Young Career Editor, Kevin C. Klatt, PhD, RD chats with YuHan Chiu, MD, PhD, a postdoctoral fellow in the Department of Epidemiology at Harvard University. Dr. Chiu is a fellow in the laboratory of Miguel Hernán, MD, DrPH, and the Kolokotrones Professor of Biostatistics and Epidemiology and focuses on applying causal inference methodologies to dietary data in epidemiological studies. In this episode, Drs. Klatt and Chiu discuss Dr. Chiu’s recent publication in AJCN estimating the effect of a theoretical randomized controlled trial, or ‘target trial’, assessing the impact of adhering to the American Heart Association 2020 Food-Based Dietary Goals. Dr. Chiu provided a really excellent history of the causal inference revolution in epidemiology, and compares and contrasts these approaches with conventional analyses in nutritional epidemiology.

In addition to the reading Dr. Chiu’s paper, be sure to check out an associated commentary on the article by AJCN’s own Academic Editor Deirdre Tobias, ScD, and Martin Lajous, MD, ScD.

Be sure to connect with us on Twitter: Dr. Klatt and AJCN. Find all of the publications from the American Society for Nutrition (@nutritionorg; @jnutritionorg) at our website.

Related articles:

Estimating the effect of nutritional interventions using observational data: the American Heart Association's 2020 Dietary Goals and mortality

What would the trial be? Emulating randomized dietary intervention trials to estimate causal effects with observational data

  continue reading

20 episodes

Artwork
iconShare
 
Manage episode 294442445 series 2936838
Content provided by American Society for Nutrition. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by American Society for Nutrition or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

In this episode of AJCN In Press, AJCN’s Inaugural Dennis M. Bier Young Career Editor, Kevin C. Klatt, PhD, RD chats with YuHan Chiu, MD, PhD, a postdoctoral fellow in the Department of Epidemiology at Harvard University. Dr. Chiu is a fellow in the laboratory of Miguel Hernán, MD, DrPH, and the Kolokotrones Professor of Biostatistics and Epidemiology and focuses on applying causal inference methodologies to dietary data in epidemiological studies. In this episode, Drs. Klatt and Chiu discuss Dr. Chiu’s recent publication in AJCN estimating the effect of a theoretical randomized controlled trial, or ‘target trial’, assessing the impact of adhering to the American Heart Association 2020 Food-Based Dietary Goals. Dr. Chiu provided a really excellent history of the causal inference revolution in epidemiology, and compares and contrasts these approaches with conventional analyses in nutritional epidemiology.

In addition to the reading Dr. Chiu’s paper, be sure to check out an associated commentary on the article by AJCN’s own Academic Editor Deirdre Tobias, ScD, and Martin Lajous, MD, ScD.

Be sure to connect with us on Twitter: Dr. Klatt and AJCN. Find all of the publications from the American Society for Nutrition (@nutritionorg; @jnutritionorg) at our website.

Related articles:

Estimating the effect of nutritional interventions using observational data: the American Heart Association's 2020 Dietary Goals and mortality

What would the trial be? Emulating randomized dietary intervention trials to estimate causal effects with observational data

  continue reading

20 episodes

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