Evidence map›Paper›PMID 28434273›Full record

ArticleJournal of primary care & community health2017

Development of Distinct Body Mass Index Trajectories Among Children Before Age 5 Years: A Population-Based Study.

Brian A Lynch, Lila J Finney Rutten, Jon O Ebbert, Seema Kumar, Barbara P Yawn, Debra Jacobson, Jennifer St Sauver

Abstract read
In one paragraph

Article in Journal of primary care & community health, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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.

Brian A Lynch1 Mayo Clinic, Rochester, MN, USA.
Lila J Finney Rutten1 Mayo Clinic, Rochester, MN, USA.
Jon O Ebbert1 Mayo Clinic, Rochester, MN, USA.
Seema Kumar1 Mayo Clinic, Rochester, MN, USA.
Barbara P Yawn2 Olmsted Medical Center, Rochester, MN, USA.
Debra Jacobson1 Mayo Clinic, Rochester, MN, USA.
Jennifer St Sauver1 Mayo Clinic, Rochester, MN, USA.

Funding

Rochester Epidemiology ProjectR01AG034676 · NIA · MAYO CLINIC ROCHESTER · PI ROCCA, WALTER A, ST SAUVER, JENNIFER LYNN · 2010 to 2019
$9.5M
NIA NIH HHS R01 AG034676
6 · The paper itself

Abstract

The prevalence of childhood obesity has increased over the past 3 decades. This study was designed to understand how childhood body mass index (BMI) influences later risk of obesity. We calculated BMIs for children residing in Olmsted County, Minnesota, between January 1, 2005 and December 31, 2012 using medical records data. We defined homogenous BMI trajectory clusters using a nonparametric hill-climbing algorithm. Overall, 16,538 (47%) children had >3 weight assessments at least 1 year apart and were included in the analyses. Within the 8-year follow-up period, children who were younger than 2 years and overweight had a 3- fold increase of obesity (adjusted hazard ratio [HR] = 3.24; 95% confidence interval [CI] = 2.69-3.89) and those aged 5 years and overweight had a 10-fold increased risk of obesity (adjusted HR = 9.97, 95% CI = 8.55-11.62). Three distinct BMI trajectories could be distinguished prior to 5 years of age. The risk of developing obesity in those who are overweight increased dramatically with increasing age. Interventions to prevent obesity need to occur prior to school age to prevent children from entering unhealthy BMI trajectories.

Indexed as

AlgorithmsAdolescentBody Mass IndexChildChild, PreschoolDisease ProgressionFemaleFollow-Up StudiesHumansInfantMaleMinnesotaOverweightPediatric ObesityPrevalenceProportional Hazards Modelsadolescentbody mass indexchildinfantobesityoverweightpreschooltrajectories

Identifiers

PMID28434273
PMCPMC5653452

What OpenQuestion holds

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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.