Evidence map›Paper›PMID 31451394›Full record

ArticleThe Lancet. Child & adolescent health2019

Predicting overweight and obesity in young adulthood from childhood body-mass index: comparison of cutoffs derived from longitudinal and cross-sectional data.

Noora Kartiosuo, Rema Ramakrishnan, Stanley Lemeshow, Markus Juonala, Trudy L Burns, Jessica G Woo, David R Jacobs, Stephen R Daniels, Alison Venn, Julia Steinberger and 9 more

Abstract readComparative StudyMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in The Lancet. Child & adolescent health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–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

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

19 authors.

Noora KartiosuoResearch Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland.
Rema RamakrishnanThe George Institute for Global Health, Nuffield Department of Women's and Reproductive Health, University of Oxford, Oxford, UK; UNSW, Sydney, NSW, Australia.
Stanley LemeshowCollege of Public Health, The Ohio State University, Columbus, OH, USA.
Markus JuonalaDepartment of Medicine, University of Turku, Turku, Finland; Division of Medicine, Turku University Hospital, Turku, Finland.
Trudy L BurnsDepartment of Epidemiology, College of Public Health, University of Iowa, Iowa City, IA, USA.
Jessica G WooDivision of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA; Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA.
David R JacobsDivision of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA.
Stephen R DanielsUniversity of Colorado School of Medicine, Aurora, CO, USA.
Alison VennMenzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia.
Julia SteinbergerDepartment of Pediatric Cardiology, University of Minnesota Masonic Children's Hospital, Minneapolis, MN, USA.
Elaine M UrbinaThe Heart Institute, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA; Department of Pediatrics, University of Cincinnati, Cincinnati, OH, USA.
Lydia BazzanoDepartment of Epidemiology, Tulane University Health Sciences Center, Tulane University, New Orleans, LA, USA.
Matthew A SabinThe Royal Children's Hospital and Murdoch Children's Research Institute, Royal Children's Hospital, Melbourne, VIC, Australia.
Tian HuDivision of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA.
Ronald J PrineasDivision of Public Health Sciences, Wake Forest University School of Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA.
Alan R SinaikoDepartment of Pediatrics, University of Minnesota Masonic Children's Hospital, Minneapolis, MN, USA.
Katja PahkalaResearch Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland; Paavo Nurmi Centre, Sports and Exercise Medicine Unit, Department of Health and Physical Activity, University of Turku, Turku, Finland; Centre for Population Health Research, Turku University Hospital, Turku, Finland.
Olli RaitakariResearch Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland; Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland; Centre for Population Health Research, Turku University Hospital, Turku, Finland.
Terence DwyerThe George Institute for Global Health, Nuffield Department of Women's and Reproductive Health, University of Oxford, Oxford, UK. Electronic address: terence.dwyer@georgeinstitute.ox.ac.uk.

Funding

Childhood CV Risk and Adult CVD Outcomes: an International Long-term Follow-upR01HL121230 · NHLBI · CINCINNATI CHILDRENS HOSP MED CTR · PI BURNS, TRUDY L, CHEN, WEI · 2015 to 2019
$13.3M
Lifespan Cardiovascular Risk Exposures and Alzheimer-related brain health: Bogalusa Heart StudyRF1AG041200 · NIA · TULANE UNIVERSITY OF LOUISIANA · PI BAZZANO, LYDIA, CARMICHAEL, OWEN T. · 2019 to 2022
$4.2M
The Role of Vascular Aging in Cognitive and Physical Function - Diversity SupplementR01AG041200 · NIA · TULANE UNIVERSITY OF LOUISIANA · PI BAZZANO, LYDIA · 2012 to 2017
$2.9M
NHLBI NIH HHS R01 HL121230NIA NIH HHS R01 AG041200NIA NIH HHS RF1 AG041200
6 · The paper itself

Abstract

backgroundHistorically, cutoff points for childhood and adolescent overweight and obesity have been based on population-specific percentiles derived from cross-sectional data. To obtain cutoff points that might better predict overweight and obesity in young adulthood, we examined the association between childhood body-mass index (BMI) and young adulthood BMI status in a longitudinal cohort.

methodsIn this study, we used data from the International Childhood Cardiovascular Cohort (i3C) Consortium (which included seven childhood cohorts from the USA, Australia, and Finland) to establish childhood overweight and obesity cutoff points that best predict BMI status at the age of 18 years. We included 3779 children who were followed up from 1970 onwards, and had at least one childhood BMI measurement between ages 6 years and 17 years and a BMI measurement specifically at age 18 years. We used logistic regression to assess the association between BMI in childhood and young adulthood obesity. We used the area under the receiver operating characteristic curve (AUROC) to assess the ability of fitted models to discriminate between different BMI status groups in young adulthood. The cutoff points were then compared with those defined by the International Obesity Task Force (IOTF), which used cross-sectional data, and tested for sensitivity and specificity in a separate, independent, longitudinal sample (from the Special Turku Coronary Risk Factor Intervention Project [STRIP] study) with BMI measurements available from both childhood and adulthood.

findingsThe cutoff points derived from the longitudinal i3C Consortium data were lower than the IOTF cutoff points. Consequently, a larger proportion of participants in the STRIP study was classified as overweight or obese when using the i3C cutoff points than when using the IOTF cutoff points. Especially for obesity, i3C cutoff points were significantly better at identifying those who would become obese later in life. In the independent sample, the AUROC values for overweight ranged from 0·75 (95% CI 0·70-0·80) to 0·88 (0·84-0·93) for the i3C cutoff points, and the corresponding values for the IOTF cutoff points ranged from 0·69 (0·62-0·75) to 0·87 (0·82-0·92). For obesity, the AUROC values ranged from 0·84 (0·75-0·93) to 0·90 (0·82-0·98) for the i3C cutoff points and 0·57 (0·49-0·66) to 0·76 (0·65-0·88) for IOTF cutoff points.

interpretationThe childhood BMI cutoff points obtained from the i3C Consortium longitudinal data can better predict risk of overweight and obesity in young adulthood than can standards that are currently used based on cross-sectional data. Such cutoff points should help to more accurately identify children at risk of adult overweight or obesity.

fundingNone.

Indexed as

Body Mass IndexAdolescentAustraliaChildChild, PreschoolCross-Sectional StudiesFinlandFollow-Up StudiesHumansIncidenceOverweightPediatric ObesityPopulation SurveillancePrognosisRisk AssessmentUnited States

Identifiers

PMID31451394
PMCPMC8717810

What Socratic holds

Textmetadata
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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.