Evidence map›Paper›PMID 36311169›Full record

ArticleChild and adolescent obesity (Abingdon, England)2021

Baseline dietary patterns of children enrolled in an urban family weight management study: associations with demographic characteristics.

Parisa Assassi, Beatrice J Selwyn, David Lounsbury, Wenyaw Chan, Melissa Harrell, Judith Wylie-Rosett

Abstract read
In one paragraph

Article in Child and adolescent obesity (Abingdon, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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.

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

2 citing papers in PubMed.

  1. Review
  2. Article
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.

Parisa AssassiDepartment of Epidemiology, Human Genetics and Environmental Science, UT-Health School of Public Health, Houston, TX, US.
Beatrice J SelwynDepartment of Epidemiology, Human Genetics and Environmental Science, UT-Health School of Public Health, Houston, TX, US.
David LounsburyAlbert Einstein College of Medicine, Albert Einstein College of Medicine, Bronx, NY, US.
Wenyaw ChanDepartment of Epidemiology, Human Genetics and Environmental Science, UT-Health School of Public Health, Houston, TX, US.
Melissa HarrellDepartment of Epidemiology, Human Genetics and Environmental Science, UT-Health School of Public Health, Houston, TX, US.
Judith Wylie-RosettAlbert Einstein College of Medicine, Albert Einstein College of Medicine, Bronx, NY, US.

Funding

CTSA Administrative Supplement for Informatics Core: A novel AI/ML system to predict respiratory failure and ARDS in Covid-19 patientsUL1TR002556 · NCATS · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI KELLER, MARLA J, KIM, MIMI Y · 2018 to 2022
$26.7M
Core-010UL1TR001073 · NCATS · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI KELLER, MARLA J, SHAMOON, HARRY · 2013 to 2017
$21.3M
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
Comprehensive Approach to Family Weight ManagementR18DK075981 · NIDDK · ALBERT EINSTEIN COLLEGE OF MEDICINE · PI WYLIE-ROSETT, JUDITH · 2008 to 2012
$3.7M
Diet Quality and CVD Risk Factors in a Family Based Weight Management StudyR01HL101236 · NHLBI · TUFTS UNIVERSITY BOSTON · PI LICHTENSTEIN, ALICE H · 2010 to 2013
$1.4M
Clinical and Translational Science AwardKL2TR001071 · NCATS · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI SHAMOON, HARRY · 2013 to 2017
$968k
Clinical and Translational Science AwardTL1TR001072 · NCATS · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI SHAMOON, HARRY · 2013 to 2017
$909k
NCATS NIH HHS KL2 TR001071NCATS NIH HHS TL1 TR001072NCATS NIH HHS UL1 TR001073NCATS NIH HHS UL1 TR002556NHLBI NIH HHS R01 HL101236NIDDK NIH HHS P30 DK111022NIDDK NIH HHS R18 DK075981
6 · The paper itself

Abstract

Objective: To identify dietary patterns (DP) of children enrolled in the Family Weight Management Study (FWMS) and to examine relationship between the identified DP with demographics. Design: We performed a cross-sectional analysis of baseline data from 332 children (BMI ≥85th percentile for age and sex and 7-12 years old) who were enrolled in the FWMS. The Block Kids Food Frequency Questionnaire was used to assess dietary intake. Principal component analysis was conducted to identify DPs. Setting: Participants were recruited from Jacobi Medical Center, Bronx, NY from July 2009 - December 2011. Results: The mean age of the children was 9.3 (±1.7 SD) years; about half were female and 75% self-identified as Hispanic/Latino. The majority of parents/guardians were born outside of the mainland USA and half had less than a high school education. We identified a "pizza-pasta" DP (high loadings of pizza, pasta, red meat, chicken, fries, sweets, processed meat, and sweet breads) and a "snacks-dessert" DP (high loadings of snacks, desserts, soft drinks, and bread and refined grains) but no healthy patterns with high loadings of fruit, vegetables, nuts, and dairy products. The "pizza-pasta" pattern was associated with parents/guardian being born in the mainland USA and having a higher educational level (p < 0.05) whereas the "snack-dessert" pattern was not significantly associated with any of the demographic variables. Conclusion: Our findings suggest that poor DP is common among second-generation immigrant Hispanic/Latino children who are obese/overweight. Future research needs to address how parental education and acculturation status are related to DP to inform future directions for preventing childhood obesity.

Indexed as

childrenDietary patterneducationobese and overweightparent country of birthprincipal component analysis

Identifiers

PMID36311169
PMCPMC9608350

What OpenQuestion holds

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LicenceCC BY-NC
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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.