Evidence map›Paper›PMID 33385006›Full record

ArticleFrontiers in nutrition2020

Ultra-Processed Food Is Positively Associated With Depressive Symptoms Among United States Adults.

Liwen Zheng, Jing Sun, Xiaohui Yu, Dongfeng Zhang

Registry-linked trialAbstract read
In one paragraph

Article in Frontiers in nutrition, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06252701 (Assessing the Feasibility and Acceptability of the Reduction of Ultra-processed Foods From the Diets of a Subset of Patients With Depression - A Pilot Open Label Crossover Trial.), which is not on this map. Cited by 35 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 6 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT06252701 nacompletednot on this mapstarted 2024, after this paper: background citation

Assessing the Feasibility and Acceptability of the Reduction of Ultra-processed Foods From the Diets of a Subset of Patients With Depression - A Pilot Open Label Crossover Trial.

TypeinterventionalSponsorUniversity of California, San FranciscoRan2024 to 2025Enrolled20ConditionsDepression, Major Depressive Disorder, Weight Gain, ObesityArmsReduction of Ultra-processed foods
3 · Its place in the literature

Who cites it

35 citing papers in PubMed, 6 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Liwen ZhengDepartment of Epidemiology and Health Statistics, School of Public Health, Qingdao University, Qingdao, China.
Jing SunDepartment of Epidemiology and Health Statistics, School of Public Health, Qingdao University, Qingdao, China.
Xiaohui YuDepartment of Epidemiology and Health Statistics, School of Public Health, Qingdao University, Qingdao, China.
Dongfeng ZhangDepartment of Epidemiology and Health Statistics, School of Public Health, Qingdao University, Qingdao, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ultra-processed foods (UPFs) are popular in the United States. In recent years, there has been an increasing interest in the health impact of UPF. This study is conducted to assess the association between UPF consumption and depressive symptoms among United States adults. Data were collected from the National Health and Nutrition Examination Survey 2011-2016. Dietary data were obtained through 24-h dietary recall interviews. Depressive symptoms were detected by a nine-item Patient Health Questionnaire; participants with more than 10 points were diagnosed with depressive symptoms. Results of logistic regression revealed a positive association between UPF consumption and depressive symptoms. The study suggests that UPF may increase the risk of depressive symptoms, particularly in people with less exercise.

Indexed as

cross-sectional studydepressive symptomsdose-responseNHANESultra-processed food

Identifiers

PMID33385006
PMCPMC7770142

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.