Evidence map›Paper›PMID 31619225›Full record

ArticleBMC medicine2019

Customized versus population birth weight charts for identification of newborns at risk of long-term adverse cardio-metabolic and respiratory outcomes: a population-based prospective cohort study.

Jan S Erkamp, Vincent W V Jaddoe, Annemarie G M G J Mulders, Eric A P Steegers, Irwin K M Reiss, Liesbeth Duijts, Romy Gaillard

Open access · goldAbstract read
In one paragraph

Article in BMC medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
4.0field-weighted citation impact, top 7% 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

9 citing papers in PubMed, 16 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

7 authors at 1 institution in 1 country.

Jan S ErkampThe Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2040, 3000 CA, Rotterdam, The Netherlands.
Vincent W V JaddoeThe Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2040, 3000 CA, Rotterdam, The Netherlands.
Annemarie G M G J MuldersDepartment of Obstetrics & Gynaecology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Eric A P SteegersDepartment of Obstetrics & Gynaecology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Irwin K M ReissDivision of Neonatology, Department of Paediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Liesbeth DuijtsDivision of Neonatology, Department of Paediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Romy GaillardThe Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2040, 3000 CA, Rotterdam, The Netherlands. r.gaillard@erasmusmc.nl.
Erasmus MC · NL

Funding

ZonMw 543003109
6 · The paper itself

Abstract

backgroundCustomized birth weight charts take into account physiological maternal characteristics that are known to influence fetal growth to differentiate between physiological and pathological abnormal size at birth. It is unknown whether customized birth weight charts better identify newborns at risk of long-term adverse outcomes than population birth weight charts. We aimed to examine whether birth weight classification according to customized charts is superior to population charts at identification of newborns at risk of adverse cardio-metabolic and respiratory health outcomes.

methodsIn a population-based prospective cohort study among 6052 pregnant women and their children, we measured infant catch-up growth, overweight, high blood pressure, hyperlipidemia, liver steatosis, clustering of cardio-metabolic risk factors, and asthma at age 10. Small size and large size for gestational age at birth was defined as birth weight in the lowest or highest decile, respectively, of population or customized charts. Association with birth weight classification was assessed using logistic regression models.

resultsOf the total of 605 newborns classified as small size for gestational age by population charts, 150 (24.8%) were reclassified as appropriate size for gestational age by customized charts, whereas of the total of 605 newborns classified as large size for gestational age by population charts, 129 (21.3%) cases were reclassified as appropriate size for gestational age by customized charts. Compared to newborns born appropriate size for gestational age, newborns born small size for gestational age according to customized charts had increased risks of infant catch-up growth (odds ratio (OR) 5.15 (95% confidence interval (CI) 4.22 to 6.29)), high blood pressure (OR 2.05 (95% CI 1.55 to 2.72)), and clustering of cardio-metabolic risk factors at 10 years (OR 1.66 (95% CI 1.18 to 2.34)). No associations were observed for overweight, hyperlipidemia, liver steatosis, or asthma. Newborns born large-size for gestational age according to customized charts had higher risk of catch-down-growth only (OR 3.84 (95% CI 3.22 to 4.59)). The direction and strength of the observed associations were largely similar when we used classification according to population charts.

conclusionsSmall-size-for-gestational-age newborns seem to be at risk of long-term adverse cardio-metabolic health outcomes, irrespective of the use of customized or population birth weight charts.

Indexed as

Birth WeightGrowth ChartsAdultCardiovascular DiseasesChildChild, PreschoolCohort StudiesFemaleFetal DevelopmentForecastingGestational AgeHumansIndividualityInfantInfant, NewbornInfant, Small for Gestational AgeBirth weightCardiovascular healthChartsChildCustomizationOutcomesRespiratory health

Identifiers

PMID31619225
PMCPMC6796410
OpenAlexW2981268427

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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.