Evidence map›Paper›PMID 36944386›Full record

ArticleAmerican journal of preventive medicine2023

Consumption of Ultraprocessed Foods and Body Fat Distribution Among U.S. Adults.

Junxiu Liu, Eurídice Martinez Steele, Yan Li, Stella S Yi, Carlos A Monteiro, Dariush Mozaffarian

Open access · greenAbstract read
In one paragraph

Article in American journal of preventive medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
5.5field-weighted citation impact, top 4% of its field
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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.

  1. 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

6 authors at 5 institutions in 4 countries.

Junxiu LiuDepartment of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, New York. Electronic address: junxiu.liu@mountsinai.org.
Eurídice Martinez SteeleDepartment of Nutrition, School of Public Health, University of São Paulo, São Paulo, Brazil; Center for Epidemiological Studies in Health and Nutrition, University of São Paulo, São Paulo, Brazil.
Yan LiDepartment of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, New York; School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Stella S YiDepartment of Population Health, NYU Grossman School of Medicine, New York, New York.
Carlos A MonteiroDepartment of Nutrition, School of Public Health, University of São Paulo, São Paulo, Brazil; Center for Epidemiological Studies in Health and Nutrition, University of São Paulo, São Paulo, Brazil.
Dariush MozaffarianGerald J. and Dorothy R. Friedman School of Nutrition Science and Policy, Tufts University, Boston, Massachusetts.
Universidade de São Paulo · BRIcahn School of Medicine at Mount Sinai · USNew York University · USShanghai Jiao Tong University · CNTufts University · US

Funding

Cost-Effectiveness of Health System and State-Level Strategies to Improve Diet and Reduce Cardiometabolic DiseasesR01HL115189 · NHLBI · TUFTS UNIVERSITY BOSTON · PI DARIUSH MOZAFFARIAN · 2013 to 2026
$8.2M
New York Regional Center for Diabetes Translation Research - Translational Intervention Methodology CoreP30DK111022 · NIDDK · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI JEFFREY GONZALEZ · 2016 to 2026
$7.8M
Assessment of Policies through Prediction of Long-term Effects on Cardiovascular Disease Using Simulation (APPLE CDS)R01HL141427 · NHLBI · NEW YORK ACADEMY OF MEDICINE · PI LIU, BIAN, YI, STELLA S · 2018 to 2021
$3.5M
NHLBI NIH HHS R01 HL115189NHLBI NIH HHS R01 HL141427NIDDK NIH HHS P30 DK111022
6 · The paper itself

Abstract

introductionThe association between ultraprocessed food consumption and body composition and potential variations by sociodemographic factors is unclear. This study aims to examine the cross-sectional associations of ultraprocessed food consumption with imaging markers of body fat distribution in a nationally representative sample of U.S. adults, overall and by sociodemographic strata.

methodsA total of 9,640 men and nonpregnant women aged 20-59 years were included from 4 cycles (2011-2012, 2013-2014, 2015-2016, 2017-2018) of the National Health and Nutrition Examination Survey with valid 24-hour dietary recalls and available whole-body dual-energy x-ray absorptiometry scans. Ultraprocessed foods were identified using the NOVA classification, with percentage energy from ultraprocessed food assessed in quintiles. Primary outcomes were absolute percentage fat (total, android, gynoid), and secondary ones were percentage fat (head, arm, leg, trunk), total abdominal fat (area, mass, volume), subcutaneous adipose tissue (area, mass, volume), and visceral adipose tissue (area, mass, volume). Multivariable-adjusted generalized linear regressions estimated independent relationships of ultraprocessed food intake with body composition overall and by sociodemographic subgroups. Analyses were conducted in September 2022 and January 2023.

resultsUltraprocessed food consumption accounted for more than half (55.5%) of daily energy consumption in this sample. Adults in the highest quintile (>72.1% energy) had 1.60 higher total percentage fat (95% CI=0.94, 2.26), 2.08 higher android percentage fat (95% CI=1.26, 2.89), and 1.32 higher gynoid percentage fat (95% CI=0.71, 1.93) than those in the lowest quintile of ultraprocessed food consumption (<39.4% energy) (all p-trend<0.001). Consistent findings were observed for secondary outcomes. Associations of ultraprocessed food intake with total percentage fat, android percentage fat, and gynoid percentage fat varied by age, sex, race and ethnicity, education, and income. Among those in the highest quintile of ultraprocessed food consumption compared with the lowest quintile counterpart, total percentage fat was 1.85 (95% CI=0.86, 2.84) higher for non-Hispanic White adults and 1.57 (95% CI=0.68, 2.46) higher for Hispanic adults (p-trends<0.001), whereas no difference was observed among non-Hispanic Black adults (-0.22; 95% CI= -0.93, 1.36) (p-trend=0.47) and non-Hispanic Asian adults (0.93; 95% CI= -0.57, 2.42) (p-trend=0.04) (p-interaction=0.001). Associational patterns were similar for android percentage fat and gynoid percentage fat.

conclusionsIn a national U.S. sample, higher intake of ultraprocessed food was associated with greater body fat, in particular android fat, and this relationship was most prominent in certain population subgroups. These cross-sectional findings call for prospective and interventional studies to assess the impact of ultraprocessed food on body composition in different populations.

Indexed as

Body Fat DistributionDietAdultCross-Sectional StudiesFemaleHumansMaleNutrition SurveysProspective Studies

Identifiers

PMID36944386
PMCPMC10440250
OpenAlexW4328135728

What OpenQuestion holds

Textmetadata
LicenceTDM
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Registered trials

None linked

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.