Publication Name	World Journal of Psychiatry
Manuscript ID	39584
Country	Canada

Category	Psychiatry
Manuscript Type	Systematic Reviews
Article Title	Antidepressant foods: An evidence-based nutrient profiling system for depression
Manuscript Source	Invited Manuscript
All Author List	Laura R LaChance and Drew Ramsey
Funding Agency and Grant Number
Corresponding Author	Laura R LaChance, BSc, MD, Academic Research, Lecturer, Research Scientist, Staff Physician, Centre for Addiction and Mental Health, 250 College Street, 7th floor, Toronto M5T 1L8, ON, Canada. laura.lachance@mail.utoronto.ca
Key Words	Depressive disorder; Mental disorders; Diet; Diet therapy; Food
Core Tip	The Antidepressant Food Score was designed to identify the most nutrient-dense individual foods to prevent and promote recovery from depressive disorders and symptoms. Results can be used to inform the design of future research studies or clinical dietary recommendations. This tool is based on a systematic literature review, evidence-informed list of Antidepressant Nutrients, and nutrient density calculation. The highest scoring animal foods were bivalves such as oysters and mussels, various seafoods, and organ meats. The highest scoring plant-based foods were leafy greens, lettuces, peppers, and cruciferous vegetables. These foods can be integrated into any dietary pattern.
Citation	LaChance LR, Ramsey D. Antidepressant foods: An evidence-based nutrient profiling system for depression. World J Psychiatr 2018; 8(3): 97-104

Received	2018-04-28 00:59
Peer-Review Started	2018-04-28 14:19
To Make the First Decision	2018-06-06 08:15
Return for Revision	2018-06-08 00:44
Revised	2018-06-12 00:36
Second Decision	2018-06-28 10:14
Accepted by Journal Editor-in-Chief
Accepted by Company Editor-in-Chief	2018-06-29 01:15
Articles in Press	2018-06-29 01:15
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript	2018-09-18 07:26

ISSN	2220-3206 (online)
Open Access	This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
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