Evidence map›Paper›PMID 41878060›Full record

ReviewJBMR plus2026

Rethinking race-based interpretation in pediatric densitometry: a scoping review.

Amira Ramadan, Zakora Moore, Usman A Ahmed, Nessa Tantivit, Dhriti Aiylam, Chloe Rotman, Alicia Pendleton, Carter R Petty, Mali DiMeo, Amanda Grice and 3 more

Abstract readReview
In one paragraph

Review in JBMR plus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

13 authors.

Amira RamadanDepartment of Pediatrics, Division of Endocrinology, Boston Children's Hospital and Harvard Medical School, Boston, MA 02115, United States.
Zakora MooreDepartment of Pediatrics, Division of Endocrinology, Boston Children's Hospital and Harvard Medical School, Boston, MA 02115, United States.
Usman A AhmedDepartment of Pediatrics, Division of Endocrinology, Boston Children's Hospital and Harvard Medical School, Boston, MA 02115, United States.
Nessa TantivitDepartment of Pediatrics, Division of Endocrinology, Boston Children's Hospital and Harvard Medical School, Boston, MA 02115, United States.
Dhriti AiylamDepartment of Pediatrics, Division of Endocrinology, Boston Children's Hospital and Harvard Medical School, Boston, MA 02115, United States.
Chloe RotmanMedical Library, Boston Children's Hospital, Boston, MA 02115, United States.
Alicia PendletonDepartment of Pediatrics, Division of Endocrinology, Boston Children's Hospital and Harvard Medical School, Boston, MA 02115, United States.
Carter R PettyBiostatistics and Research Design (BARD) Center, Boston Children's Hospital, Boston, MA 02115, United States.
Mali DiMeoDepartment of Pediatrics, Division of Endocrinology, Boston Children's Hospital and Harvard Medical School, Boston, MA 02115, United States.
Amanda GriceOffice of Health Equity and Inclusion, Sandra L. Fenwick Institute for Pediatric Health Equity and Inclusion, Department of Health Affairs, Boston Children's Hospital and Harvard Medical School, Boston, MA 02115, United States.
Valerie L WardOffice of Health Equity and Inclusion, Sandra L. Fenwick Institute for Pediatric Health Equity and Inclusion, Department of Health Affairs, Boston Children's Hospital and Harvard Medical School, Boston, MA 02115, United States.
Christina M JacobsenDepartment of Pediatrics, Division of Endocrinology, Boston Children's Hospital and Harvard Medical School, Boston, MA 02115, United States.
Nora E RenthalDepartment of Pediatrics, Division of Endocrinology, Boston Children's Hospital and Harvard Medical School, Boston, MA 02115, United States.ORCID https://orcid.org/0000-0002-8186-4462

Funding

TRAINING IN DIABETES AND METABOLISMT32DK007260 · NIDDK · JOSLIN DIABETES CENTER · PI LAURIE J GOODYEAR · 1986 to 2026
$13.6M
NIDDK NIH HHS T32 DK007260
6 · The paper itself

Abstract

As pediatric populations in the United States (US) become increasingly diverse, current practices for interpreting bone density using DXA in children warrant reevaluation. The International Society for Clinical Densitometry currently recommends adjusting pediatric bone density Z-scores by race, sex, and age. However, race-based adjustments risk reinforcing disparities and perpetuating systemic inequities in pediatric bone health assessment. We conducted a scoping review of studies examining racial and ethnic differences in BMD among healthy US children, identifying 3960 records across 4 databases, of which 54 met inclusion criteria. Across these studies, reporting of race and ethnicity was inconsistent: although nearly all relied on self- or parent-report, none provided explicit definitions, and only 13% confirmed concordance across grandparents. Fifty percent of studies reported statistically significant racial differences in BMD, yet most did so without comprehensive covariate adjustment. By contrast, studies that accounted for height, lean mass, and pubertal status frequently found that differences attenuated or disappeared. These findings underscore the need to critically reconsider race-based adjustments in pediatric DXA interpretation. Developing and validating race-neutral reference standards, with attention to structural determinants and biologically relevant measures, such as stature, body composition, and pubertal timing, is essential for achieving a more equitable and clinically meaningful assessment of pediatric bone health.

Indexed as

BMDDXAethnicityhealth disparitiesnormative curvespediatric bone densitypediatric reference datarace

Identifiers

PMID41878060
PMCPMC13007872

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.