Evidence map›Paper›PMID 42418198›Full record

ArticleJAMA network open2026

Birth Weight Percentiles and Infant and Child Growth Dynamics.

María Alejandra Hernandez, Richard M A Parker, Tim J Cole, Izzuddin M Aris, Henrique Barros, Johan G Eriksson, Abby F Fleisch, Barbara Heude, Yung Seng Lee, Zheyuan Li and 12 more

Erratum issuedAbstract read
In one paragraph

Article in JAMA network open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Error in Figure 2 Caption.JAMA network open · 2026
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

22 authors.

María Alejandra HernandezMRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom.
Richard M A ParkerMRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom.
Tim J ColeUCL Great Ormond Street Institute of Child Health, London, United Kingdom.
Izzuddin M ArisDepartment of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts.
Henrique BarrosEPIUnit ITR, Instituto de Saúde Pública da Universidade do Porto, Universidade do Porto, Porto, Portugal.
Johan G ErikssonYong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Abby F FleischCenter for Interdisciplinary Population & Health Research, MaineHealth Institute for Research, Westbrook, Maine.
Barbara HeudeUniversité de Paris, Inserm, INRAE, Centre for Research in Epidemiology and StatisticS (CRESS), Paris, France.
Yung Seng LeeYong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Zheyuan LiSchool of Mathematics and Statistics, Henan University, Kaifeng, Henan, China.
Emily OkenDepartment of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts.
Susana SantosYong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Kok Hian TanKK Women's and Children's Hospital, Singapore, Singapore.
Chloe VainqueurUniversité de Paris, Inserm, INRAE, Centre for Research in Epidemiology and StatisticS (CRESS), Paris, France.
Tanja G M VrijkotteDepartment of Public and Occupational Health, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.
John WrightBradford Institute for Health Research, Bradford Teaching Hospitals Foundation Trust, Bradford, United Kingdom.
Tiffany C YangBradford Institute for Health Research, Bradford Teaching Hospitals Foundation Trust, Bradford, United Kingdom.
Fabian YapDepartment of Public and Occupational Health, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.
Siyu ZhouDepartment of Public and Occupational Health, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.
Kate TillingMRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom.
Deborah A LawlorMRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom.
Ahmed ElhakeemMRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Infants classified as small or large for gestational age can have different growth patterns compared with appropriate-for-gestational age counterparts. The association of birth weight percentiles beyond conventional thresholds with early-life growth remains unknown. Objective: To quantify the association of birth weight percentile range with infant and child growth. Design, Setting, and Participants: This is a prospective cohort study of singletons born between 1991 and 2011 in 7 birth cohort studies in Europe, Singapore, and the US and followed up with repeated growth measurements for 10 years. Five European cohorts were used for discovery analysis, and the Singapore and US cohorts were used for replication analyses. Exposures: Birth weight percentiles standardized for sex and gestational age using the INTERGROWTH-21st standards and classified into 10 decile groups, with the middle (fifth and sixth decile groups) as the reference group. Main Outcomes and Measures: The primary outcomes were infant height (centimeters per month) and weight (grams per month) growth velocity at 1, 6, 12, 24 months; body mass index (BMI; calculated as weight in kilograms divided by height in meters squared); age (months or years) at infant BMI peak and childhood BMI rebound; and overweight or obesity at 10 years. Associations were examined using regression models adjusted for sex and birth cohort. Results: The discovery cohort included 36 018 children (mean [SD] gestational age at birth, 39.7 [1.8] weeks; 17 238 girls [48%]). Compared with the reference group, higher decile groups had lower early infant height velocity that reversed by 24 months, higher weight velocity from 6 to 24 months, higher and earlier peak BMI, higher rebound BMI, and increased risk of overweight or obesity at age 10 years. Lower decile groups showed the opposite patterns. For example, mean differences for infant peak BMI were -0.38 (95% CI, -0.43 to -0.33) for the second decile birth weight group and 0.33 (95% CI, 0.29 to 0.38) for the ninth decile birth weight group compared with the fifth to sixth decile birth weight group. Mean differences for age at peak BMI were 0.22 months (95% CI, 0.12 to 0.33 months) for the second decile birth weight group and -0.21 months (95% CI, -0.30 to -0.11 months) for the ninth decile birth weight group compared with the fifth to sixth decile birth weight groups. Risk ratios for overweight or obesity at 10 years were 0.86 (95% CI, 0.76 to 0.97) for the second decile birth weight group and 1.25 (95% CI, 1.13 to 1.38) for the ninth decile birth weight group. Birth weight was not associated with age at rebound BMI. Replication analyses (2517 children; mean [SD] gestational age at birth, 39.2 [1.8] weeks; 1191 girls [47%]) supported these findings. Associations were typically linear and similar in boys and girls. Deciles provided only modest estimation gains over conventional categories. Conclusions and Relevance: In this cohort study of 38 535 singletons, birth weight decile was associated with early-life growth patterns. Birth weight decile group may help identify high-risk children missed by conventional thresholds, although the benefit of analysis using decile group over traditional groups remains modest.

Indexed as

Birth WeightChild DevelopmentBirth CohortBody HeightBody Mass IndexChildChild, PreschoolEuropeFemaleGestational AgeHumansInfantInfant, Large for Gestational AgeInfant, NewbornMaleProspective Studies

Identifiers

PMID42418198
PMCPMC13347239

What Socratic 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 Socratic graph.