Evidence map›Paper›PMID 38828485›Full record

ArticlePediatrics2024

Screening Accuracy of BMI for Adiposity Among 8- to 19-Year-Olds.

David S Freedman, Babette S Zemel, William H Dietz, Carrie Daymont

Abstract read
In one paragraph

Article in Pediatrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

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  16. Are single-nucleotide polymorphisms previously linked to inhaled corticosteroid response associated with obese-asthma in children?Pediatric allergy and immunology : official publication of the European Society of Pediatric Allergy and Immunology · 2024
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

David S FreedmanRetired from the Centers for Disease Control and Prevention, Atlanta, Georgia.
Babette S ZemelDivision of Gastroenterology, Hepatology, and Nutrition, Children's Hospital of Philadelphia, and Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania.
William H DietzSumner M. Redstone Global Center for Prevention and Wellness, Milken Institute School of Public Health, George Washington University, Washington, District of Columbia.
Carrie DaymontDepartments of Pediatrics and Public Health Science, Penn State College of Medicine, Hershey, Pennsylvania.

Funding

CTSA INFRASTRUCTURE FOR PEDIATRIC RESEARCHUL1RR026314 · NCRR · UNIVERSITY OF CINCINNATI · PI HEUBI, JAMES E. · 2009 to 2011
$14.3M
Genomics of bone and body composition traits in childrenR01HD100406 · NICHD · CHILDREN'S HOSP OF PHILADELPHIA · PI GRANT, STRUAN F A, ZEMEL, BABETTE S · 2020 to 2024
$3.4M
NCRR NIH HHS UL1 RR026314NICHD NIH HHS R01 HD100406
6 · The paper itself

Abstract

BACKGROUND AND

objectivesAlthough the limitations of BMI have long been recognized, there are recent concerns that it is not a good screening tool for adiposity. We therefore examined the cross-sectional relation of BMI to adiposity among 6923 8- to 19-year-olds in the National Health and Nutrition Survey from 2011 through 2018.

methodsParticipants were scanned with dual-energy x-ray absorptiometry. Adiposity was expressed as fat mass index (FMI, fat mass kg ÷ m2) and percentage of body fat (%fat). Lean mass was expressed as lean mass index (LMI, lean mass ÷ m2). Regression models and 2 × 2 tables were used to assess the relation of BMI to FMI, %fat, and LMI.

resultsAge and BMI accounted (R2) for 90% to 94% of the variability of FMI and LMI in each sex. Associations with %fat were weaker (R2s ∼0.70). We also examined the screening abilities of a BMI ≥ Centers for Disease Control and Prevention 95th percentile for high levels of adiposity and LMI. Cut points were chosen so that prevalences of high values of these variables would be similar to that for high BMI. Of participants with a high BMI, 88% had a high FMI, and 76% had a high %fat. Participants with a high BMI were 29 times more likely to have a high FMI than those with lower BMIs; comparable relative risks were 12 for high %fat and 14 for high LMI.

conclusionsDespite its limitations, a high BMI is a very good screening tool for identifying children and adolescents with elevated adiposity.

Indexed as

Absorptiometry, PhotonAdiposityBody Mass IndexMass ScreeningAdolescentChildCross-Sectional StudiesFemaleHumansMaleNutrition SurveysPediatric ObesityYoung Adult

Identifiers

PMID38828485
PMCPMC11211694

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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.