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Ultra-processed foods and human health: An umbrella review and updated meta-analyses of observational evidence

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机构: [1]Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China [2]Translational Gastro-Intestinal Unit, Nuffield Department of Medicine, John Radcliffe Hospital, Oxford, UK [3]KU Leuven Department of Chronic Diseases and Metabolism, Translational Research Center for Gastrointestinal Disorders (TARGID), Leuven, Belgium [4]School of Public Health, Zhengzhou University, Zhengzhou, China [5]Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK [6]Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden [7]West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China [8]School of Public Health and Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China [9]Department of Nutrition and Food Sciences and the Center for Epidemiologic Studies, Utah State University, Logan, UT, USA [10]School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada [11]Nutrition Research Division, Health Canada, Ottawa, Ontario, Canada [12]International Prevention Research Institute, Lyon, France [13]Belgian Centre for Evidence-Based Medicine, Leuven, Belgium [14]School of Pharmacy and Life Sciences, The Robert Gordon University, Aberdeen, UK [15]Cancer Research UK Edinburgh Centre, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK [16]The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, Zhejiang, China
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关键词: Ultra-processed foods NOVA classification Heath outcomes Meta-analysis Umbrella review

摘要:
Ultra-processed food (UPF) intake has increased sharply over the last few decades and has been consistently asserted to be implicated in the development of non-communicable diseases. We aimed to evaluate and update the existing observational evidence for associations between ultra-processed food (UPF) consumption and human health.We searched Medline and Embase from inception to March 2023 to identify and update meta-analyses of observational studies examining the associations between UPF consumption, as defined by the NOVA classification, and a wide spectrum of health outcomes. For each health outcome, we estimated the summary effect size, 95% confidence interval (CI), between-study heterogeneity, evidence of small-study effects, and evidence of excess-significance bias. These metrics were used to evaluate evidence credibility of the identified associations.This umbrella review identified 39 meta-analyses on the associations between UPF consumption and health outcomes. We updated all meta-analyses by including 122 individual articles on 49 unique health outcomes. The majority of the included studies divided UPF consumption into quartiles, with the lowest quartile being the reference group. We identified 25 health outcomes associated with UPF consumption. For observational studies, 2 health outcomes, including renal function decline (OR: 1.25; 95% CI: 1.18, 1.33) and wheezing in children and adolescents (OR: 1.42; 95% CI: 1.34, 1.49), showed convincing evidence (Class I); and five outcomes were reported with highly suggestive evidence (Class II), including diabetes mellitus, overweight, obesity, depression, and common mental disorders.High UPF consumption is associated with an increased risk of a variety of chronic diseases and mental health disorders. At present, not a single study reported an association between UPF intake and a beneficial health outcome. These findings suggest that dietary patterns with low consumption of UPFs may render broad public health benefits.Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.

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大类 | 2 区 医学
小类 | 1 区 营养学
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大类 | 2 区 医学
小类 | 1 区 营养学
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Q1 NUTRITION & DIETETICS
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Q1 NUTRITION & DIETETICS

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第一作者机构: [1]Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
通讯作者:
通讯机构: [16]The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, Zhejiang, China [*1]School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
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