Evidence map›Paper›PMID 35418073›Full record

ArticleBMC medicine2022

Predicting the earliest deviation in weight gain in the course towards manifest overweight in offspring exposed to obesity in pregnancy: a longitudinal cohort study.

Delphina Gomes, Lien Le, Sarah Perschbacher, Nikolaus A Haas, Heinrich Netz, Uwe Hasbargen, Maria Delius, Kristin Lange, Uta Nennstiel, Adelbert A Roscher and 2 more

Open access · goldAbstract read
In one paragraph

Article in BMC medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
7.6field-weighted citation impact, top 3% 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

10 citing papers in PubMed, 20 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

12 authors at 3 institutions in 2 countries.

Delphina Gomes *Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Faculty of Medicine, Ludwig-Maximilians-Universität München, Munich, Germany.
Lien Le *Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Faculty of Medicine, Ludwig-Maximilians-Universität München, Munich, Germany.
Sarah PerschbacherInstitute for Medical Information Processing, Biometry, and Epidemiology (IBE), Faculty of Medicine, Ludwig-Maximilians-Universität München, Munich, Germany.
Nikolaus A HaasDivision of Pediatric Cardiology and Intensive Care, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany.
Heinrich NetzDivision of Pediatric Cardiology and Intensive Care, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany.
Uwe HasbargenDepartment of Obstetrics and Gynecology, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany.
Maria DeliusDepartment of Obstetrics and Gynecology, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany.
Kristin LangeDepartment of General Pediatrics, Neonatology, and Pediatric Cardiology, University Children's Hospital, Faculty of Medicine, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
Uta NennstielBavarian Health and Food Safety Authority, Oberschleißheim, Germany.
Adelbert A RoscherDepartment of Pediatrics, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany.
Ulrich Mansmann *Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Faculty of Medicine, Ludwig-Maximilians-Universität München, Munich, Germany.
Regina Ensenauer *Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Faculty of Medicine, Ludwig-Maximilians-Universität München, Munich, Germany. regina.ensenauer@mri.bund.de.ORCID 0000-0002-2420-6850
Ludwig-Maximilians-Universität München · DEDüsseldorf University Hospital · DEZimmer Biomet (Netherlands) · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundObesity in pregnancy and related early-life factors place the offspring at the highest risk of being overweight. Despite convincing evidence on these associations, there is an unmet public health need to identify "high-risk" offspring by predicting very early deviations in weight gain patterns as a subclinical stage towards overweight. However, data and methods for individual risk prediction are lacking. We aimed to identify those infants exposed to obesity in pregnancy at ages 3 months, 1 year, and 2 years who likely will follow a higher-than-normal body mass index (BMI) growth trajectory towards manifest overweight by developing an early-risk quantification system.

methodsThis study uses data from the prospective mother-child cohort study Programming of Enhanced Adiposity Risk in CHildhood-Early Screening (PEACHES) comprising 1671 mothers with pre-conception obesity and without (controls) and their offspring. Exposures were pre- and postnatal risks documented in patient-held maternal and child health records. The main outcome was a "higher-than-normal BMI growth pattern" preceding overweight, defined as BMI z-score >1 SD (i.e., World Health Organization [WHO] cut-off "at risk of overweight") at least twice during consecutive offspring growth periods between age 6 months and 5 years. The independent cohort PErinatal Prevention of Obesity (PEPO) comprising 11,730 mother-child pairs recruited close to school entry (around age 6 years) was available for data validation. Cluster analysis and sequential prediction modelling were performed.

resultsData of 1557 PEACHES mother-child pairs and the validation cohort were analyzed comprising more than 50,000 offspring BMI measurements. More than 1-in-5 offspring exposed to obesity in pregnancy belonged to an upper BMI z-score cluster as a distinct pattern of BMI development (above the cut-off of 1 SD) from the first months of life onwards resulting in preschool overweight/obesity (age 5 years: odds ratio [OR] 16.13; 95% confidence interval [CI] 9.98-26.05). Contributing early-life factors including excessive weight gain (OR 2.08; 95% CI 1.25-3.45) and smoking (OR 1.94; 95% CI 1.27-2.95) in pregnancy were instrumental in predicting a "higher-than-normal BMI growth pattern" at age 3 months and re-evaluating the risk at ages 1 year and 2 years (area under the receiver operating characteristic [AUROC] 0.69-0.79, sensitivity 70.7-76.0%, specificity 64.7-78.1%). External validation of prediction models demonstrated adequate predictive performances.

conclusionsWe devised a novel sequential strategy of individual prediction and re-evaluation of a higher-than-normal weight gain in "high-risk" infants well before developing overweight to guide decision-making. The strategy holds promise to elaborate interventions in an early preventive manner for integration in systems of well-child care.

Indexed as

Pediatric ObesityPregnancy in ObesityBody Mass IndexChildChild, PreschoolCohort StudiesFemaleHumansInfantLongitudinal StudiesOverweightPregnancyProspective StudiesWeight GainBMI growthEarly preventionEarly weight gainInfancyMaternal pre-conception obesityRepeated risk assessmentSequential predictionSubclinical stage

Identifiers

PMID35418073
PMCPMC9008920
OpenAlexW4223909464

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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.