Evidence map›Paper›PMID 38128734›Full record

ArticleThe American journal of clinical nutrition2024

Postnatal growth in small vulnerable newborns: a longitudinal study of 2 million Brazilians using routine register-based linked data.

Aline S Rocha, Rita de Cássia Ribeiro-Silva, Juliana F M Silva, Elizabete J Pinto, Natanael J Silva, Enny S Paixao, Rosemeire L Fiaccone, Gilberto Kac, Laura C Rodrigues, Craig Anderson and 1 more

Open access · hybridAbstract read
In one paragraph

Article in The American journal of clinical nutrition, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
4.1field-weighted citation impact, top 6% 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

7 citing papers in PubMed, 7 citations in OpenAlex.

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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

11 authors at 6 institutions in 3 countries.

Aline S RochaCenter of Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation, Salvador, Brazil; School of Nutrition, Federal University of Bahia (UFBA), Salvador, Brazil. Electronic address: aline.srocha@fiocuz.br.
Rita de Cássia Ribeiro-SilvaCenter of Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation, Salvador, Brazil; School of Nutrition, Federal University of Bahia (UFBA), Salvador, Brazil; Institute of Collective Health, Federal University of Bahia (ISC/UFBA), Salvador, Brazil.
Juliana F M SilvaCenter of Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation, Salvador, Brazil.
Elizabete J PintoCenter of Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation, Salvador, Brazil; Health Sciences Center, Federal University of Recôncavo da Bahia, Santo Antônio de Jesus, Brazil.
Natanael J SilvaCenter of Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation, Salvador, Brazil; ISGlobal, Hospital Clínic. Universitat de Barcelona, Barcelona, Spain.
Enny S PaixaoCenter of Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation, Salvador, Brazil; Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom. Electronic address: enny.cruz@lshtm.ac.uk.
Rosemeire L FiacconeCenter of Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation, Salvador, Brazil; Department of Statistics, Federal University of Bahia (UFBA), Salvador, Brazil.
Gilberto KacNutritional Epidemiology Observatory, Josué de Castro Nutrition Institute, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil.
Laura C RodriguesCenter of Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation, Salvador, Brazil; Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Craig AndersonSchool of Mathematics and Statistics, University of Glasgow, Scotland, United Kingdom.
Mauricio L BarretoCenter of Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation, Salvador, Brazil; Institute of Collective Health, Federal University of Bahia (ISC/UFBA), Salvador, Brazil.
Universidade Federal da Bahia · BRKnowledge Integration (United Kingdom) · GBFundação Oswaldo Cruz · BRUniversidade Federal do Recôncavo da Bahia · BRUniversidade Federal do Rio de Janeiro · BRUniversity of Glasgow · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPreterm, low-birth weight (LBW) and small-for-gestational age (SGA) newborns have a higher frequency of adverse health outcomes, including linear and ponderal growth impairment.

objectiveTo describe the growth trajectories and to estimate catch-up growth during the first 5 y of life of small newborns according to 3 vulnerability phenotypes (preterm, LBW, SGA).

methodsLongitudinal study using linked data from the 100 Million Brazilian Cohort baseline, the Brazilian National Live Birth System (SINASC), and the Food and Nutrition Surveillance System (SISVAN) from 2011 to 2017. We estimated the length/height-for-age (L/HAZ) and weight-for-age z-score (WAZ) trajectories from children of 6-59 mo using the linear mixed model for each vulnerable newborn phenotype. Growth velocity for both L/HAZ and WAZ was calculated considering the change (Δ) in the mean z-score between 2 time points. Catch-up growth was defined as a change in z-score > 0.67 at any time during follow-up.

resultsWe analyzed 2,021,998 live born children and 8,726,599 observations. The prevalence of at least one of the vulnerable phenotypes was 16.7% and 0.6% were simultaneously preterm, LBW, and SGA. For those born at term, all phenotypes had a period of growth recovery from 12 mo. For preterm infants, the onset of L/HAZ growth recovery started later at 24 mo and the growth trajectories appear to be lower than those born at term, a condition aggravated among children with the 3 phenotypes. Preterm and female infants seem to experience slower growth recovery than those born at term and males. The catch-up growth occurs at 24-59 mo for males preterm: preterm + AGA + NBW (Δ = 0.80), preterm + AGA + LBW (Δ = 0.88), and preterm + SGA + LBW (Δ = 1.08); and among females: term + SGA + NBW (Δ = 0.69), term + AGA + LBW (Δ = 0.72), term + SGA + LBW (Δ = 0.77), preterm + AGA + LBW (Δ = 0.68), and preterm + SGA + LBW (Δ = 0.83).

conclusionsChildren born preterm seem to reach L/HAZ and WAZ growth trajectories lower than those attained by children born at term, a condition aggravated among the most vulnerable.

Indexed as

Infant, PrematureInfant, Small for Gestational AgeSemantic WebSouth American PeopleBrazilChild, PreschoolFemaleHumansInfantInfant, NewbornLongitudinal StudiesMalegrowthlow–birth weight newbornpreterm birthsmall-for-gestational age

Identifiers

PMID38128734
PMCPMC10884605
OpenAlexW4389976602

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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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.